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Biophysics - Science topic

biophysics, protein folding and stability, spectroscopy, bioinformatics, molecular dynamics. . . .
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Press release, 22 October 2024
Understanding the physics of cancer, preventing metastases: Leopoldina honours the physician Bahriye Aktas and the biophysicists Jochen Guck and Josef Käs with the Greve Prize
Dealing with metastases is one of the major challenges of cancer therapy. More than 90 percent of deaths caused by cancer are linked to metastases. Understanding the conditions that cause cancer metastases and how these move through the body is key to developing new approaches to cancer treatment. Biophysics can provide valuable insights, as cancer is also subject to the laws of physics. In honour of their groundbreaking insights into the movement of tumour cells, the physician Professor Dr Bahriye Aktas, and the biophysicists Professor Dr Jochen Guck, and Professor Dr Josef Käs are receiving the 2024 Greve Prize from the German National Academy of Sciences Leopoldina. The award, endowed with 250,000 euros, is donated by the Helmut and Hannelore Greve Foundation for Science, Development and Culture.
The biophysicist Professor Dr Josef Käs from the University of Leipzig/Germany and Professor Dr Jochen Guck from the Max Planck Institute for the Physics of Light in Erlangen/Germany are leading global scientists in the physics of cancer. Their research, some of which they have conducted jointly, investigates the physical properties of cells when they interact with surrounding tissue. They have managed to demonstrate how tumour cells actively change from solid and stiff to a fluid and soft condition in order to move between the dense tissue of the human body and form metastases. This discovery has led to a paradigmatic shift in how cancer cells are viewed and motivated collaboration with the physician Professor Dr Bahriye Aktas from the University of Leipzig Medical Center. Aktas has made it possible to study human tumour samples directly after operating and thus also live-cell microscopy of the active deformation of cancer cells. Building on the work of their predecessor Professor Dr Michael Höckel, this raises the question of what limits cancer cells in the body experience. “Bahriye Aktas, Jochen Guck, and Josef Käs provide an impressive example of how interdisciplinary basic research can significantly deepen the understanding of cancerous diseases,” says Leopoldina President Professor (ETHZ) Dr Gerald Haug. “Studying the behaviour of tumour cells from the perspective of physics and linking it to direct insights gained from medical institutions has the potential to develop completely new means of treating cancer.”
The potential for cancer treatment is already apparent with respect to breast cancer. Whether the cancer has metastasised or not is key in determining the success of therapies. To date, however, it has not been possible to accurately predict when a tumour forms metastases. Käs and Aktas, working together with Professor Dr Axel Niendorf (Hamburg/Germany), managed to identify markers that, in combination with existing criteria, are significantly better at indicating a tumour’s potential to metastasise. They have done so using biophysical concepts, the central idea of which – that metastasising cancer cells must be softer – Jochen Guck played an important role in developing. Cancer cells in primary tumours are, at the local level, very solid and densely packed. In order to release themselves from the original tumour and move through the human body, cancer cells must soften, allowing the cancer cell aggregate to become fluid. In the study carried out by Käs and Aktas together with Axel Niendorf, the scientists identified the histological characteristics of the cancer cells that become fluid: they were longer and had deformed cell nuclei, allowing them to “squeeze” through neighbouring tissue. Their study of more than 1,000 breast cancer patients offers a strong indication that these deformed cell and nuclei forms can be used as a reliable marker for a cancer’s aggressiveness, and to predict a tumour’s potential to metastasise. This could permit breast cancer treatments to be more individually tailored to patients. In Erlangen, parallel to the activities in Leipzig, Guck developed a high-throughput method to measure the deformability of cells (real-time deformability cytometry, RT-DC). This method is particularly suited to finding substances that can change cancer cell mechanics to prevent metastases.
Bahriye Aktas (born in 1975) is Professor of Gynaecology at the University of Leipzig and Director of the Department of Gynaecology at the Leipzig Medical Center. Aktas studied medicine at the Justus Liebig University Gießen/Germany. She completed her medical training as a gynaecologist and obstetrician at the University Hospital Essen/Germany, obtained her habilitation there in 2013, and was appointed Associate Professor in 2017. That year she switched to the University of Leipzig. As a gynaecologist, her focus is on minimally invasive and robot-assisted surgery, which is used for gentler and precise operations with improved chances of healing, and she also has a particular interest in surgery for cancer treatment. She and her predecessor have helped to globally establish new operation methods that take into account how a tumour spreads.
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Recent advances in the physics of cancer have led to significant progress in understanding and treating metastases, particularly through emerging radiotherapy techniques, let me talk about this. One notable development is stereotactic body radiation therapy (SBRT), which delivers highly focused, high-dose radiation to small tumors with extreme precision. As we know, this modality has shown promising results in treating oligometastatic disease, where cancer has spread to a limited number of sites.Another emerging approach is proton beam therapy, which uses charged particles to deliver radiation more precisely to tumors while sparing surrounding healthy tissue. This is particularly beneficial for treating metastases in sensitive areas like the brain or spine.Adaptive radiotherapy is gaining action, especilly for oART, using real-time imaging to adjust treatment plans based on changes in tumor size and position during the course of therapy. This allows for more accurate targeting of metastatic lesions.MRI-guided radiotherapy is another innovative technique, combining high-quality soft-tissue imaging with radiation delivery. This enables better visualization and targeting of metastases, especially in areas with complex anatomy.Lastly, researchers are exploring the combination of radiotherapy with immuno, leveraging radiation's ability to enhance the immune response against cancer cells. This approach, known as radioimmunotherapy, shows promise in treating widespread metastatic disease by potentially creating a systemic anti-tumor effect.These advancements in radiotherapy techniques offer new hope for patients with metastatic cancer, potentially improving outcomes and quality of life. In a nutsell, we have to be optimisitc about physics applied to cancer especially due to radiotherapy.
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I ran a 100ns molecular dynamics simulation of a protein-membrane system where the protein is 10 angstroms away from the membrane. After concatenating the trajectory files and performing post-processing (centering the protein-membrane complex), I noticed that the protein sometimes appears to go below the membrane for some frames in the visualization (Figure 2_462thframe) from the normal orientation (figure1_461thframe).
I'm unsure if this is an issue with the simulation itself or if I'm handling the periodic boundary conditions (PBC) incorrectly during post-processing. I've tried various gmx trjconv -pbc options, including -ur rect and -ur compact, but the problem persists.
Could someone please provide guidance on how to resolve this issue in GROMACS?
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Hello Smit Patel,
I apologize for the late response.
What force field are you using? That can also affect the behavior of the lipids.
Anyways, I believe there is no issue with your system. I would recommend building a membrane control using the same conditions and lipid types, and performing APL, thickness, and density analyses for comparison.
Additionally, the way you visualize your system can change by using either "Perspective" or "Orthographic" visualization modes. Check the attached images for the differences.
Best regards.
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Dear colleagues,
I defended my Ph.D. thesis in October 2016 and now I am looking for a postdoctoral position in microscopy (AFM, TEM, SEM) and biophysics of microorganisms (especially, viruses, I like them :)).
My CV is attached. If there is an open position in your lab, please, write me.
Best regards,
Denis  
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That sounds like an exciting field! Here are some steps you can take to find a postdoctoral position in microscopy and physics of microorganisms:
  1. Identify Research Groups: Look for research groups or labs that specialize in microscopy and physics of microorganisms. Search university websites, scientific journals, and research databases for relevant publications and projects.
  2. Networking: Attend scientific conferences, workshops, and seminars related to microscopy, microbiology, and physics. Network with researchers in the field and express your interest in potential postdoctoral opportunities. You can also reach out to professors or researchers whose work you admire to inquire about available positions.
  3. Online Resources: Explore online platforms and job boards dedicated to academic and research positions. Websites like Nature Careers, Science Careers, and ResearchGate often list postdoctoral positions in various scientific disciplines.
  4. Collaborations: Consider collaborating with researchers who are conducting interdisciplinary work at the intersection of microscopy and microbiology. Collaborative projects can provide valuable insights and connections within the scientific community.
  5. Tailored Applications: Customize your application materials, including your CV, cover letter, and research statement, to highlight your expertise in microscopy and physics of microorganisms. Emphasize relevant skills, research experience, and achievements that align with the requirements of the position.
  6. Funding Opportunities: Look for postdoctoral fellowship programs or research grants that support projects in your area of interest. Many funding agencies offer fellowships specifically for early-career researchers pursuing research in microscopy, microbiology, or physics.
  7. Stay Informed: Stay updated on the latest developments and advancements in microscopy techniques, microbiology, and physics research. Familiarize yourself with emerging trends and technologies that could enhance your research interests and expertise.
  8. Persistence and Patience: Finding the right postdoctoral position can take time and persistence. Be proactive in your search, maintain a positive attitude, and keep refining your skills and qualifications to increase your competitiveness as a candidate.
By following these steps and leveraging your expertise in microscopy and physics, you can increase your chances of securing a rewarding postdoctoral position in this exciting field of research.
l Perhaps this protocol list can give us more information to help solve the problem.
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I am trying to make a simplified model of the movement of meiofaunal animals in marine sediments.
Depending on their mode of movement, meiofauna can be classified as either "interstitial" (i.e. they move through sediment particles) or "burrowing" (i.e. they displace particles to move).
The organisms I am interested in, the kinorhynchs, move by anchoring an eversible introvert armoured with hook-like structures (scalids) in the sediment and actively pulling on them. That means that the locomotion of these animals mainly relies on the resistance offered by the sediment matrix in response to the force exerted by the scalids. Thus, it should be possible to make a study of momentum or quantity of movement with the weight of these organisms and the weight of the sediment through which they move. This could help us better understand how these animals move and how they are distributed according to the granulometry of the sediment.
However, this "model" becomes more complicated in fine sediments. It is relatively acceptable to assume that the resistance offered by coarse sediments, such as sand or gravel, is primarily due to the weight of the particles, and other minor forces exerting extra resistance can be neglected (for the purposes of this model). However, in fine sediments the resistance to displacement is (possibly) not exerted only by the weight of the particles, but is much greater than the sum of the weights of the grains due to other elements such as electrostatic forces between particles (and possibly others).
My questions are:
1. Are these assumptions correct?
2. Is there any way to calculate the resistance of fine sediments to the movement of these animals comparable to the resistance exerted by sandy sediments due to the weight of their particles?
Comments, suggestions or related literature are welcome.
Thank you very much,
Alberto.
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The resistance to movement of fine sediments, such as silt or clay, can be calculated using empirical formulas like the Shields equation, which considers factors such as sediment size, density, and critical shear stress. Laboratory tests, such as direct shear tests, can provide more precise measurements under controlled conditions, enhancing the accuracy of calculations.
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Respectfully, which esoteric beliefs are the least plausibly true ? Why?
1)Scientific materialism because the fundamental choice to reason, DESPITE UNCERTAINTY, requires more than material. Source:
2)Reincarnation because if every entity is unique, or might as well be due to UNCERTAINTY, then sharing spirits is less likely. Source:
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Oh. Then you must mean epistemologically sound?
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This question refers to biophysics.
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Here's attached, a small amount of information for the discussion, attached as PDF. Thanks for your time. Hope this helps
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I am searching for a dataset in ASD that contains EEG+ECG signals and biophysical data of the participants. The biophysical data can be in the form of either blood data (neutrophils, T-cells, lymphocytes, etc) or questionnaire (sleep problems, gut problems, allergy, autoimmunity etc). Any input is greatly appreciated.
Thanks.
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This question refers to biophysics.
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Reynold's number is between 0 to 2000, then the flow of liquid is streamlined or laminar. If Reynold's number is between 2000 to 3000, the flow of liquid becomes unstable and changing from streamline to turbulent flow. If Reynold's number is above 3000, the flow of liquid is turbulent. In turbulant flow so much particles are deposited and accumulatet in the tube mainly blood vessels where by time can bb completely occluded so ischemia starts in the related tissues...
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Does anyone know an institute/research facility in Europe running research in the field of cancer therapy and willing to accept a student of Micro- and Nanotechnoligies in Biophysics for Erasmus+ holiday traineeship?
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ips institute upm university Malaysia
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A NEW METHOD FOR ELECTROCHEMICAL ETCHING: I. Results with dc Voltage.
L. Tommasino, G. Zapparoli, F. Caiazzo
Thanks in advance.
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Thank you for your answer, but unfortunatly it's not the whole article (it's only the first page of it)
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I am reaching out to #researchers in the field of #Biochemistry, #Biophysics and #Bioinformatics, for collaborative partnership in scientific research. The researcher should be academic staff at the tertiary institutions in following listed countries:
#Afghanistan
#Angola
#Bangladesh
#Belarus
#Belize
#Benin
#Bhutan
#Burkina Faso
#Burma
#Burundi
#CaboVerde
#Cambodia
#Cameroon
#CentralAfricanRepublic
#Chad
#Comoros
#Congo
#CookIslands
#Cuba
#Democratic People's Republic of Korea
#Democratic Republic of the Congo
#Djibouti
#Dominica
#EquatorialGuinea
#Eritrea
#Eswatini
#Ethiopia
#Gambia
#Ghana
#Grenada
#Guinea
#Guinea-Bissau
#Guyana
#Haiti
#Iran
#IvoryCoast
#Kenya
#Kiribati
#Kyrgyzstan
#Lao People's Democratic Republic
#Lebanon
#Lesotho
#Liberia
#Madagascar
#Malawi
#Maldives
#Mali
#Marshall Islands
#Mauritania
#Micronesia (Federated States of)
#Mozambique
#Myanmar
#Nauru
#Nepal
#Nicaragua
#Niger
#Niue
#Palau
#PapuaNewGuinea
#Moldova (Republic of)
#Rwanda
#SaintHelena
#SaintLucia
#SaintVincent and the #Grenadines
#Samoa
#SaoTome and #Principe
#Senegal
#Sierra Leone
#SolomonIslands
#Somalia
#SouthSudan
#Sudan
#Suriname
#Syrian Arab Republic
#Tajikistan
#Timor-Leste
#Togo
#Tokelau
#Tonga
#Tuvalu
#Uganda
#Ukraine
#Tanzania (United Republic of)
#Vanuatu
#Yemen
#Zambia
#Zimbabwe
Interested researcher should kindly email to hezesapience@gmail.com with the subject: Research Collaboration from "your country".
Thanks.
Toluwase H. Fatoki
Visionary @ Heze-Sapience International, Nigeria.
Lecturer @ Department of Biochemistry, Federal University Oye-Ekiti, Nigeria.
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And why don’t you want any collaboration from Nigeria?
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Is there any system with small molecule binders and a short protein tag that is higher affinity than 6xHIS-NTA?
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V5 and Flag tag are the only ones I've seen other than His.
Einhauer A, Jungbauer A. The FLAG peptide, a versatile fusion tag for the purification of recombinant proteins. J Biochem Biophys Methods. 2001 Oct 30;49(1-3):455-65. doi: 10.1016/s0165-022x(01)00213-5. PMID: 11694294.
Also consider the MBP that is engineered with a linker with a protease cut site. MBP sticks to the affinity column, and you use the protease to elute your protein of interest. Then of course the protease has to be purified out, so it should have an affinity tag or biotin.
Wikipedia has a long list.
Peptide tags
  • ALFA-tag, a de novo designed helical peptide tag (SRLEEELRRRLTE) for biochemical and microscopy applications. The tag is recognized by a repertoire of single-domain antibodies [5]
  • AviTag, a peptide allowing biotinylation by the enzyme BirA and so the protein can be isolated by streptavidin (GLNDIFEAQKIEWHE)
  • C-tag, a peptide that binds to a single-domain camelid antibody developed through phage display (EPEA)[6][7]
  • Calmodulin-tag, a peptide bound by the protein calmodulin (KRRWKKNFIAVSAANRFKKISSSGAL)
  • iCapTag™ (intein Capture Tag), peptide-based a self-removing tag controlled by pH change (MIKIATRKYLGKQNVYGIGVERDHNFALKNGFIAHN). Its patented component derived from Nostoc punctiforme (Npu) intein. This tag is used for protein purification of recombinant proteins and its fragments. It can be used in research labs and it is intended for large-scale purification during downstream manufacturing process as well. The iCapTag™-target protein complex can be expressed in a wide range of expression hosts (e.g. CHO and E.coli cells). It is not intended for fully expressed mAbs or membrane proteins[8][9][10]
  • polyglutamate tag, a peptide binding efficiently to anion-exchange resin such as Mono-Q (EEEEEE) [11]
  • polyarginine tag, a peptide binding efficiently to cation-exchange resin (from 5 to 9 consecutive R)
  • E-tag, a peptide recognized by an antibody (GAPVPYPDPLEPR)
  • FLAG-tag, a peptide recognized by an antibody (DYKDDDDK)[12]
  • HA-tag, a peptide from hemagglutinin recognized by an antibody (YPYDVPDYA)[13]
  • His-tag, 5-10 histidines bound by a nickel or cobalt chelate (HHHHHH)Gly-His-tags are N-terminal His-Tag variants (e.g. GHHHH, or GHHHHHH, or GSSHHHHHH) that still bind to immobilised metal cations but can also be activated via azidogluconoylation to enable click-chemistry applications[14]
  • Myc-tag, a peptide derived from c-myc recognized by an antibody (EQKLISEEDL)
  • NE-tag, an 18-amino-acid synthetic peptide (TKENPRSNQEESYDDNES) recognized by a monoclonal IgG1 antibody, which is useful in a wide spectrum of applications including Western blotting, ELISA, flow cytometry, immunocytochemistry, immunoprecipitation, and affinity purification of recombinant proteins [15]
  • Rho1D4-tag, refers to the last 9 amino acids of the intracellular C-terminus of bovine rhodopsin (TETSQVAPA). It is a very specific tag that can be used for purification of membrane proteins.
  • S-tag, a peptide derived from Ribonuclease A (KETAAAKFERQHMDS)
  • SBP-tag, a peptide which binds to streptavidin (MDEKTTGWRGGHVVEGLAGELEQLRARLEHHPQGQREP)[16][17][self-published source?]
  • Softag 1, for mammalian expression (SLAELLNAGLGGS)
  • Softag 3, for prokaryotic expression (TQDPSRVG)
  • Spot-tag, a peptide recognized by a nanobody (PDRVRAVSHWSS) for immunoprecipitation, affinity purification, immunofluorescence and super resolution microscopy
  • Strep-tag, a peptide which binds to streptavidin or the modified streptavidin called streptactin (Strep-tag II: WSHPQFEK)[2]
  • T7-tag, an epitope tag derived from the T7 major capsid protein of the T7 gene (MASMTGGQQMG). Used in different immunoassays as well as affinity purification Mainly used [18]
  • TC tag, a tetracysteine tag that is recognized by FlAsH and ReAsH biarsenical compounds (CCPGCC)
  • Ty tag (EVHTNQDPLD)
  • V5 tag, a peptide recognized by an antibody (GKPIPNPLLGLDST)[19]
  • VSV-tag, a peptide recognized by an antibody (YTDIEMNRLGK)
  • Xpress tag (DLYDDDDK), a peptide recognized by an antibody
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Have you noticed, formation and dissociation of triplex DNA is not fully reversible upon pH titration? After several cycles it becomes almost irreversible, i.e. fold in triplex conformation. Any thoughts?
On Wednesday, September 27th, we will have journal club (seminar) about dynamics and biophysics of non-canonical DNA. Please join for free :)
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The reversible formation and dissociation of triplex DNA can be influenced by various factors, including pH changes. Triplex DNA typically involves the formation of a third DNA strand (the triplex-forming oligonucleotide or TFO) binding to the major groove of a double-stranded DNA (dsDNA) molecule through Hoogsteen base pairing. The stability of this triplex structure can be affected by several factors:
1. **pH:** The pH of the solution can have a significant impact on the stability of triplex DNA. At different pH levels, the protonation states of the DNA bases can change, which, in turn, can affect the binding and stability of the triplex structure.
2. **Ionic Strength:** The concentration of ions in the solution, particularly divalent cations like Mg²⁺, can influence the stability of triplex DNA. These ions can help stabilize the triplex structure through electrostatic interactions.
3. **Temperature:** Triplex formation is temperature-dependent. Lower temperatures generally favor triplex formation, while higher temperatures can promote dissociation.
4. **Sequence Specificity:** The sequence of the TFO and the target dsDNA plays a crucial role in triplex stability. Specific sequences may form more stable triplex structures than others.
5. **Structural Features:** The presence of mismatches, bulges, or other structural irregularities in the TFO or the target dsDNA can affect the stability of the triplex.
6. **Base Modifications:** Chemical modifications to the DNA bases, such as methylation or incorporation of analogs, can alter the stability of the triplex.
It's not uncommon for DNA structures to exhibit hysteresis in their stability during pH titration or other environmental changes. This hysteresis can be due to several reasons:
1. **Kinetic Trapping:** Sometimes, the transition between different DNA conformations (like triplex to duplex) may involve kinetic barriers. Even if the conditions are reversed, the system might not readily return to its initial state due to these barriers.
2. **Structural Changes:** pH changes can induce structural changes in the DNA or alter the protonation states of specific bases. These changes may not fully revert when the pH is reversed.
3. **Aggregation:** DNA molecules can aggregate or interact with other molecules or surfaces under certain conditions, making it difficult for them to return to their original state.
4. **Chemical Modifications:** pH changes can lead to chemical modifications of DNA bases, which can be irreversible.
To address the issue of irreversibility in triplex formation and dissociation, you might consider careful optimization of experimental conditions, such as pH, temperature, and ion concentrations. Additionally, studying the kinetics of triplex formation and dissociation can provide insights into the underlying processes and help identify ways to mitigate irreversibility. It's important as well to be aware that the specific DNA sequences and environmental conditions can greatly influence the behavior of triplex DNA.
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Hello everyone! We have organized a special topic "Emerging Tools, Concepts, and Applications in Multi-Scale Mechanobiology" on the journal Frontiers in Bioengineering and Biotechnology (IF=5.7, JCR 1), which is currently accepting submissions, and the deadline for submission of articles is 2024 January 23.
The topic covers but is not limited to:
• Cell/nuclear mechanobiology, Tissue biomechanics • Engineered biomaterials / Matrix biology • Bioinformatics-based approaches in mechanobiology • Tumor microenvironment • Cardiovascular physiology and pathology • Stem cells and regenerative medicine • Mechanobiology-based therapies • Multi-scale modeling.
Contributions are welcome! It is also possible to send me the abstract at my email: zengxi@link.cuhk.edu.hk
For more information, please visit the dedicated website. Thanks for the support! Here is the website for the special topic: https://www.frontiersin.org/research-topics/58995/emerging-tools-concepts-and-applications-in-multi-scale-mechanobiology
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I apologize and excuse the owner of the post. I would like to invite you to read my ebook and discover why microorganisms are so fantastic. https://www.amazon.com.br/dp/B0CF1VKKK8
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I'm asking for experts who's interested in neuroscience, philosophy of mind, philosophy of religion, biophysics or artificial intelligence systems and computation or related fields. Thank you!
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Hi,
While AI can mimic aspects of understanding and feeling through algorithms, it lacks true human-like consciousness. Its abilities are rooted in programming and data, not genuine self-awareness. The prospect of AI gaining advanced traits like 'theory of mind' remains a subject of ongoing debate and research.
Just shared my thoughts.
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Looking for a sequence or vector map of pEC86, a plasmid which expresses E. coli cytochrome maturation (ccm) genes.
Here is a reference for the plasmid:
Arslan, Engin, et al. "Overproduction of theBradyrhizobium japonicum c-Type Cytochrome Subunits of thecbb3Oxidase inEscherichia coli." Biochemical and biophysical research communications 251.3 (1998): 744-747.
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GenBank: OM367995.1
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I searched yesterday and could not find any references, apart from hypercubes etc, to mathematical modeling using 4 dimensions other than my articles on arXiv and RG. That may explain why the role of 4/3 scaling has been unnoticed by physics.
I think a fourth dimension does play a role in modeling:
3/4 metabolic scaling.
Peto’s paradox
Brain weight scaling
4/3 fractal envelope of Brownian motion.
Clausius 1860 article on gas molecular mean path lengths.
Waterston on the energy to maintain a levitating elastic plane in a gravitational field (Roy Soc 1892 publication of 1845 submission).
Dark energy.
Are there any others?
Several articles on RG discuss 4/3 scaling, which involves the 4th dimension, including:
and several other RG articles back to .
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There's nothing special about four components. It's not the number of components that's relevant, it's the symmetries. From the symmetries it's then possible to deduce what are the particular properties of four-component objects.
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By genetically modifying we can alter some properties of plants. But can we modify the biophysical, optical or thermal properties of leaves?
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The optical properties of a leaf are determined by its biochemical and biophysical characteristics, including its 3-D cellular organization. The absorption and scattering properties of leaves together create the shape of their reflectance spectra.
Genetic engineering is a technique that allows scientists to introduce new traits or modify existing ones in plants by altering their DNA. Genetic engineering can be used to improve various aspects of plant performance, such as yield, quality, resistance, or adaptation.
Therefore, it is possible that genetic engineering could modify the biophysical, optical or thermal properties of leaves by altering their biochemical and biophysical characteristics. For example, genetic engineering could change the concentration or composition of pigments, such as chlorophyll, carotenoids, or anthocyanins, that affect the absorption and reflection of light by leaves. Genetic engineering could also change the structure or arrangement of cells, tissues, or organelles, such as stomata, mesophyll, or chloroplasts, that affect the scattering and transmission of light by leaves. Genetic engineering could also change the water content or thermal conductivity of leaves that affect their temperature and heat exchange with the environment.
However, modifying the biophysical, optical or thermal properties of leaves by genetic engineering may also have some trade-offs or consequences for other aspects of plant function or ecology. For example, changing the pigment concentration or composition may affect the photosynthetic efficiency or stress tolerance of leaves. Changing the cellular structure or arrangement may affect the gas exchange or transpiration of leaves. Changing the water content or thermal conductivity may affect the water balance or frost resistance of leaves. Therefore, genetic engineering of leaf properties may require careful consideration of the benefits and costs for plant performance and adaptation.
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Yes, there are many examples in physics where one can switch from a scaling to a dimensional conceptual reference frame for solving a problem. In fact, such a switch can often simplify the problem and make it easier to solve.
A common example is the study of fluid dynamics. In many fluid dynamics problems, it is useful to work with dimensionless quantities, such as the Reynolds number, which describes the ratio of inertial forces to viscous forces in a fluid flow. By using dimensionless quantities, one can simplify the governing equations and make them more amenable to analysis.
However, there are situations where working with dimensional quantities may be more appropriate. For example, in problems involving the motion of objects in a gravitational field, it is often necessary to work with dimensional quantities such as mass, length, and time. Similarly, in problems involving electromagnetic fields, it may be necessary to work with dimensional quantities such as charge and electric potential.
The choice of whether to work with scaling or dimensional quantities depends on the specific problem at hand and the physical phenomena involved. In general, it is important to choose the appropriate reference frame that best captures the relevant physics and simplifies the problem.
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The phrase in the Title line imitates Karl Popper’s All Life is Problem Solving.
Since thermodynamics plays a role in life processes, it was surprising that searching “All life is thermodynamics” on Google on August 16, 2022 gave no results.
Don’t organisms seek to optimize and preserve the entropy of their internal energy distribution? And to optimize their use of energy and outcomes based on energy inputs? Aren’t survival and procreation ways of preserving previous products of energy use?
Is there justification for the statement, All life is thermodynamics? Or is the statement too simple to convey any insight?
Schrodinger in What is Life referred to thermodynamics, statistical mechanics; chapter 6 is Order, Disorder and Entropy. And more recently there is: J. Chem. Phys. 139, 121923 (2013); doi: 10.1063/1.4818538 Statistical physics of self-replication by Jeremy England.
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Just one random emerent simulation that shows emerence of the second level emergence---emerents are brathing emerents---using modified 'Game of Life' cellular automaton, it was simulated by the open-source Python software GoL-N24.
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Hey everyone..
Would like to get your views on certain questions relating to Blood Pressure & cardiovascular physiology...
How is vascular pressure generated in the body? Is it because of the heart or the vessels?
What happens to pulse pressure when central artery stiffness rises?
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Blood pressure is the force that blood exerts on the walls of the blood vessels as it flows through them. It is generated by the heart pumping blood into the blood vessels and the resistance of the blood vessels to this flow.
When the heart beats, it generates a pressure wave that travels through the arteries, causing them to expand and contract. This wave of pressure is known as a pulse. The pressure generated by the heart during each beat is known as systolic pressure, while the pressure in the arteries when the heart is at rest between beats is known as diastolic pressure. The difference between these two pressures is called pulse pressure.
The vessels also play a role in generating blood pressure. The resistance of the blood vessels to the flow of blood creates a pressure gradient that helps to maintain blood flow and generate blood pressure. The diameter of the blood vessels, the thickness of their walls, and the viscosity of the blood all contribute to this resistance.
When the central artery stiffness rises, the pulse pressure increases. This is because the artery walls become less elastic and more rigid, which reduces their ability to expand and contract in response to the pressure wave generated by the heart. As a result, the pressure wave is reflected back to the heart more quickly, causing an increase in systolic pressure and a decrease in diastolic pressure, leading to an increase in pulse pressure. This increase in pulse pressure can put additional strain on the heart and increase the risk of cardiovascular disease.
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Hello
I need it urgently
Can you give me articles in the field of aflatoxin that are both biophysical and bioinformatics?(for example biosensor)
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"Development of a biosensor for the detection of aflatoxin M1 in milk using surface plasmon resonance" by Xu et al. (2020) - This article describes the development of a biosensor based on surface plasmon resonance for the detection of aflatoxin M1 in milk samples. The biosensor was developed using a combination of biophysical techniques such as surface plasmon resonance and bioinformatics techniques for the optimization of sensor design.
"Development of a portable aflatoxin detection system based on fluorescence polarization" by Wang et al. (2019) - This article presents a biosensor for the detection of aflatoxin based on fluorescence polarization. The biosensor was developed using a combination of biophysical techniques such as fluorescence polarization and bioinformatics techniques for the design and optimization of the detection system.
"A review of biosensors for the detection of aflatoxins" by Liao et al. (2018) - This review article summarizes the latest developments in biosensors for the detection of aflatoxins, with a focus on the combination of biophysical and bioinformatics techniques in the design and optimization of biosensors.
"DNA-based biosensors for the detection of aflatoxins: a review" by Kaushik et al. (2017) - This review article discusses the development of DNA-based biosensors for the detection of aflatoxins, highlighting the use of biophysical techniques such as electrochemical and optical methods, and the role of bioinformatics in the optimization of biosensor design.
"A label-free biosensor for aflatoxin B1 detection based on a graphene oxide-enhanced surface plasmon resonance technique" by Yang et al. (2015) - This article presents a label-free biosensor for the detection of aflatoxin B1 based on a combination of biophysical techniques such as surface plasmon resonance and the use of bioinformatics for the optimization of biosensor design.
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Which textbook do you recommend for an introductory biophysics course (aimed at 2nd year students from different disciplines: https://apps.ualberta.ca/catalogue/archive/course/bioph/201/1810)?
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2nd Edition
Quantitative Understanding of Biosystems An Introduction to Biophysics, Second Edition
ByThomas M. Nordlund, Peter M. Hoffmann Copyright Year 2019
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Is it possible to suggest a title (Biophysics of food) that includes all three NMR SAXS DSC devices?
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In my suggestion the title may be " Characterization of Food materials for their quality"
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Biophysical assay involves cleaving a quenched fluoregenic substrate that results in increased fluorescence. Difference between racemic mixture and pure components came to be ten times different in terms of IC50!
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I'm assuming that you are asking about inhibitors of an enzyme. If the mixture of enantiomers is truly racemic (50:50), then the maximal differential potency between the racemic mixture and the more active of the purified enantiomers is 2-fold, since the racemic mixture is 50% active enantiomer. The differential between the more active and less active enantiomer can be much larger, since one enantiomer can, in principle, be completely inactive.
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I have to create .cgc file for vitamin E in VMD. Kindly help me to create it. I need literature for it. Thanks in advance
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Did you get some help regarding your query? I also need to create CG file for RNA.
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Hello,
For intramolecular FRET, I've always had one position labeled with the donor and another position with the acceptor, in a controlled way (e.g. one at a lysine and one at a cysteine). But I need to figure out if I can do FRET if the two positions are the same reactive group (in this case, both positions are cysteines).
The proposition is that the purified protein's 2 positions be labeled with donor and acceptor randomly, so that the two positions can be donor-acceptor, donorx2, acceptorx2, donor-unlabeled, acceptor-unlabeled, and unlabeledx2 in a mixture.
I am worried that the background from the improperly labeled proteins in the mixture will obscure the signal from the properly labeled protein to such an extent that the FRET has too small a dynamic range.
Is it better to have even donor:acceptor ratio or should one or the other be in excess? Should the labeling be saturated or substoichiometric? Not sure what will work best.
Has anyone tried something like this? Did it work? What helped?
Thanks!
~Beverley
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Also, I think single molecule FRET might work for this instead of a bulk experiment. It could allow one to pick out the DA and AD labeled proteins.
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Hello. I am working on a kinase that binds to ATP. I cocrystallized the protein with the ATP analog AMP and solved the structure. However, while performing ITC, I am not getting a complete saturation. The attached image is for a reaction wherein a 1:10 ratio of protein and the ligand (AMP) was used. Later I also increased and decreased the ligand ratios, but there was no binding. I have also tried using different protein concentrations and repeated the experiment multiple times, but the results remain the same.
Also, the N value for one site binding is 0.01.
So, what could be the most probable reason for such a result?
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Could you share with us concentrations and volumes you used in this titration? And how does it look like the control dilution experiment? It could be easier to answer your question then.
Regards
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I was saddened to receive a message today that Dr Jean Garnier, a dear friend, mentor, and scientific colleague, has passed way. He held the Order of Honors in Agronomy (Mérite Agricole), Officer, Order of Honors in Education (Palmes Académiques), Knight. He has also held a laureate position at the Ministry of Agriculture, USA, and the position of Research Director at the French National Institute for Agricultural Research. He was until quite recently the Editor in Chief of Biophysical Reviews, a journal sponsored by the International Union of Pure and Applied Biophysics of which he has been President. He was a widely respected expert in protein science and a founder of bioinformatics. He wrote many scientific papers, and he was a huge influence on my work and the work of many others. We coauthored a textbook on proteins and protein engineering that was widely used in universities. Under his guidance, our research and early papers together, particularly on the prediction of protein secondary structure and protein modeling, achieved many thousands of citations. The GOR method is still widely used today, and I saw that it played a significant role in the published research of many protein scientists responding to the rise of COVID-19. We kept in touch, and he will be very much missed.
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First of all, my sincere condolences, it is always sad to lose someone dear to you. It sounds like a good initiative to search for a way to honor someone’s scientific work/life. There are I believe, some good examples of ways to honor a great scientist/human being:
-Write a in memoriam like the one for Gerhard Woeginger: in memoriam Gerhard Woeginger
And/or dedicate a special issue on the work/field of the late scientist like:
Kind regards.
PS. I am/was familiar with the GOR method for predicting protein secondary structures from amino acid sequences but never realised that GOR was the abbreviation of Garnier–Osguthorpe–Robson
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I have noticed while reading different publications that some have used collagen to coat slide/chamber surface in fluid-flow cell experiments, while others used fibronectin. Does coating rely on the type of cells that I am going to use? Example: collagen coating for bone cells, fibronectin coating for endothelial cells?
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This is going to be cell type dependent mostly, but one consideration is that a fibronectin, being extremely sticky, will attach to collagen type I (i.e. 10% serum fibronectin is about 30 ug/ml). So unless you are blocking the surface with heat-denatured 1% BSA it likely will still be a fibronectin coating. Usually 1-10 ug/ml fibronectin is ample, but 100 ug/ml of collagen type I is needed. Also collagen solutions are pH sensitive and will self polymerize. If using a collagen coating add cold (4C) PBS and coat for 4 hours at 4C to stop the polymerization from occurring. Fibronectin is best coated at 37C for 1 hour diluted in PBS (it can precipitate at 4C).
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It requires about 5.3 kcal/mol (or 8 kBT) of energy to break one phoshodiester bond of DNA. How do these enzymes cut the DNA only by using thermal energy and not ATP? I am only considering the ATP-independent restriction enzymes (Type II). How do these enzymes manage to generate the necessary energy? I couldn't find the exact mechanism with energetics of restriction enzymes cleaving DNA. Please provide me any relevant references.
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No, the standard free energy of hydrolysis of the phosphodiester bond in DNA is -5.3 kcal/mol. It requires energy to forge a phosphodiester bond, while to break one requires only enough energy to overcome the activation energy barrier, which is lowered by enzymatic- , acid- or base catalysis. Under physiological conditions, hydrolysis is further facilitated by the high water concentration.
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During AFM imaging, the tip does the raster scanning in xy-axes and deflects in z-axis due to the topographical changes on the surface being imaged. The height adjustments made by the piezo at every point on the surface during the scanning is recorded to reconstruct a 3D topographical image. How does the laser beam remain on the tip while the tip moves all over the surface? Isn't the optics static inside the scanner that is responsible for directing the laser beam onto the cantilever or does it move in sync with the tip? How is it that only the z-signal is affected due to the topography but the xy-signal of the QPD not affected by the movement of the tip?
or in other words, why is the QPD signal affected only due to the bending and twisting of the cantilever and not due to its translation?
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Indeed, in the case of a tip-scanning AFM the incident laser beam should follow the tip scanning motion, to record throughout the deflection signal for the same spot on the cantilever backside. This can be achieved by integrating the laser diode with a kind of tube (with its long axis parallel to the z-axis) that carries the cantilever holder at its lower end and is kind of hinged at its upper end. The scan piezos would act on the entire tube, incl the laser diode, in a plane between the tube's upper and lower ends. Whether or not your AFM system works exactly the same way I cannot tell for sure though.
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It need metal ion as cofactor. How does the charge balance affect docking result?
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What are the Biophysical and Biochemical techniques that used in Recombinat DNA technology??
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Biochemical methods are based on specific reagents and chemical transformations, using e.g. enzymes, antibodies, ligands etc
Biophysical methods are based on equipment and spectral properties: absorbance and fluorescence spectroscopy, light, x-ray and neutron scattering, nuclear magnetic resonance, Forster resonance energy transfer
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One might argue: Animals increase their survivability by increasing the degrees of freedom available to them in interacting with their environment and other members of their species.
Right, wrong, or in between? Your views?
Are there articles discussing this?
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Also check please the following useful RG link:
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I am computing Van der Waal interactions in python for a peptide of size 10 residues for various conformations. The total conformations (or the number of PDB files is 300,000). Is it possible to compute only the 1-4 atom distances to compute Van der Waals interactions as the bonded and 1-3 atom distances are irrelevant when it comes to Van der Waal interactions using some python module?
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Does the DNA remain stable or degrade at this temperature? Would there be any difference in thermal stability between supercoiled and linear forms of say, 3 kb plasmid.
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If we heat up a tube of DNA dissolved in water, the energy of the heat can pull the two strands of DNA apart (there's a critical temperature called the Tm at which this happens). This process is called 'denaturation'; when we've 'denatured' the DNA, we have heated it to separate the strands. The two strands still have the same nucleotide sequences, however, so they are still complementry. If we cool the tube again, then in the course of the normal, random molecular motion they'll eventually bump into each other ... and stick tightly, reforming double-stranded DNA. This process is called 'annealing' or 'hybridization', and it is very specific; only complementary strands will come together if it is done right. This process is used in many crime labs to identify specific strands of DNA in a mixture. Now, when we've denatured the two strands, there's something else we can do - replicate the DNA. The key here is that any single-stranded piece of DNA can only hybridize with another if their sequences are complementary. If we have just one strand, we can actually buildanother strand to match it. Here's how it's done, either in a test tube or in a live cell: The DNA strands are separated (for example, by heating them in a test tube). For each strand, we provide a primer, which is a short piece of DNA that sticks to one end of the strand. An enzyme is added. This is a specific type of protein called a "DNA polymerase" that can "read" the bases on one strand and can attach the complementary base to the growing strand. The polymerase "walks" down the template strand and creates its exact complement as it goes. The same thing happens to the other original strand. When we started, we had one double-stranded piece of DNA. After polymerase is done, we've got twoidentical pieces - exact copies of each other.
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Hello,
I intend to perform thermal unfolding of my proteins by CD, to determine their melting temperatures.
I initially scanned the proteins over a wavelength range of 250 -190 nm at 25 °C (in 20 mM Phosphate bufffer pH 7.4) to determine their structural content. The results confirm that the proteins are made up of alpha-helices (which is what i expected), with two negative bands at ~208 nm and ~221 nm, and one positive band at ~ 192 nm . See attached image!
Next, I will like to thermally unfold the proteins at a specific wavelength. Given the results attached, could anyone please suggest what wavelength would be idle to monitor the thermal denaturation of the proteins and why?
Best
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The earlier mentioned 222 nm find its origin in the following source: The ellipticity at 222 nm has been used as a rough measure for the relative helicity, for which q222=36 300 deg.cm2/dmol was taken as 100% a-helix (Hodges et al., 1988).
Hodges, R. S., Semchuk, P. D., Taneja, A. K., Kay, C. M., Parker, J. M., & Mant, C. T. (1988). Protein design using model synthetic peptides. Peptide Research, 1(1), 19-30.
You can find the paper here:
and in Figure (they actually used 220 nm) examples of thermal melting profiles).
Best regards.
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Compiled allometric data might help to detect scaling patterns.
Or similarities in the scaling relationships might suggest connections otherwise too subtle to find.
Does such a list exist?
Does such a list exist for biological phenomena?
If such lists do not exist should they?
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No such compilation that I know of (only some reviews, for the scaling of a specific trait in a specific group). So regarding your last question "should it exist", I think creating such a list would be an admirable but difficult task - depends on what you're thinking of exactly as "all known instances". Using all the raw data available would basically be a "database of everything", virtually impossible. It would still take a ton of work to even make a list of every allometric equation ever explicitly stated for every trait in every organism, and you'd also need to be able to update it, and to subset it by trait, taxa (down to intraspecific resolution, don't forget), external factors such as region/temperature/season/age/sex, etc.
(btw if somebody does go and make such a database it should definitely be named ALLometric right?)
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I want to know if the number of fringes and their shape is an important factor for the accuracy of phase definition?
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Hello,
Our old but not to old DynaPro Plate reader I does not work anymore and Wyatt does not want to investigate the problem as the instrument is 10 years old. We have the money to pay them but they really do not want to loose time on it...
We would like to know if some of you know DLS instruments that are compatible with the measurement of several conditions (at least 30 conditions) in parallel. Of course the goal is to find a company that is able to do a maintenance.
Best,
Sébastien
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Protein aggregation over a range of temperatures (protein denaturation) is a common application for the plate reader. The wells can take tiny amounts of fluid. Have you spoken to Malvern SA?
Bâtiment Le Phénix 1, 24 Rue Émile Baudot, Palaiseau, 91120 France
Tel: Sales: + 33 1 69 35 18 08
Tel: Support: + 33 1 6935 1806
Fax: + 33 1 6019 1326
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If I use AVI, BSI, SI and TI as biophysical factor.
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Please see attached file
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Hi I have attached the link to article and the table from the article with this question, I wanted to know how the value of 0.7 s-1 is calculated from the slope and intercept values using the bell evans equation. The values of slope is 85.3 and intercept is -351.
Thank you in advance
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0.048/4.1*exp(-((-351*0.048)/4.1))
kBT = 4.1 pN*nm
It is clearly written in equation 5 of that paper.
However, I would advise using better models for such data analyses: https://iopscience.iop.org/article/10.1088/1742-5468/ab6a05/meta
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I have a set of Ramachandran angles. I wish to make Ramachandran plot out of it with standard allowed region contours in the background in Python. I couldn't do that in python. If not in python, Is there in anyother software where I can do this?
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Is anyone aware of a scientific answer, specifically what type of biochemical or biophysical triggers can trigger activation?
Thanks.
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endogenous retrovirus comprises up to 5–8% of the human genome, it is vertically inherited.
The majority of ERVs that occur in vertebrate genomes are ancient, inactivated by mutation, and have reached genetic fixation in their host species. For these reasons, they are extremely unlikely to have negative effects on their hosts except under unusual circumstances such as (people with schizophrenia), therefore we can suggest that some Neurological disorders lead to activation ERV
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Biophysical remote sensing pertains to the detection and analysis of the biological and/or physical characteristics of a landscape, particularly its vegetation and soil.
In carrying out a research in biophysical remote sensing and it's application to climate and land change science what methods or approaches can be used?
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The easiest way to analyze the biological properties of the landscape is to use spectral data in GIS programs like QGIS, ENVI, and ArcGis. Also you can search pre-prepared data at https://earthengine.google.com/
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This question leads me to ask another one.
Why do the osmoles of urea when they pass into the cell exert an osmotic effect and draw water into the cell, while when they were outside they had no effect?
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Urea freely crosses the cell membrane, therefore independent of the osmolarity of the solution, it cannot build up a gradient of osmotic pressure across the cell membrane - The extracellular urea concentration will quickly equilibrate and build up a similar intracellular concentration.
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Hi! I am quite curious about mitochondrial mechanobiology. How does mechanotransduction (both cell-matrix and cell-cell) affect mitochondial behaviour (mitophagy, mitochondriokinesis & ?) What is the signalling pathway behind (both transcriptomic/proteomic and metabonomic)? How are mitochondrial behaviours and signalling in wound-healing process? Are there some most nonnegligible/core article in this topic?
Thank you!
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Very interesting topic that motivates the search
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Hi,
I and working on a project for extraterrestrial life, and i need few work on the titled topic. If is there any data, recommend it or please discuss the evaluation mechanism.
Thank you,
Muhammad Furqan Ali
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You can search for the following articles: National Environmental and Natural Resources Information System Environment and Temperature Report, light, atmosphere, wind
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Hi everyone
Could you share your research and/ or other researches related to the application of magnetic fields in biophysics and Medical physics?
Thanks
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Also, one can mention this although rather exotic technique https://en.wikipedia.org/wiki/Magnetoencephalography
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I need a way to rotate my entire system (DNA and solvent) such that the axis of the DNA lies along the x-axis, but I want the periodic boundaries to be preserved. I added pictures of my system before and after rotation.
How can I edit things in such a way that the entire system is rotated, but molecules stay within the box? (basically the water molecules that were rotated down and went outside the box should reappear up inside the box)
Thank you in advance!
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PBCs are always respected from a simulation perspective as far as you have turned on them in the .mdp file.
If you want a rotated system for the purpose of having nice images, then play around with gmx editconf -rotate/center/translate and when you have the orientation you want clean up the PBC representation by shifting everything inside the box with gmx trjconv -pbc mol or similar. Adding the flag -center and selecting the DNA could also be helpful in this case.
Hope this helps
Nicola
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Dear Sirs,
I did not find this material on the internet. There are only mechanical models of some aspects of self-replication. Full mechanical model is absent. Of course it is enourmous problem if one precisely build it. But maybe there are simple and simultaneously more complete mechanical models? I prefer purely mechanical self-replicating machine but self-replicating robots are also good.
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The first mechanistic model of self-replication was given by John von Neumann by his self-replicating cellular automaton. He was followed by others: Langdon, Reggia, ...
It would be interesting to study this research stream as it provides great insights into creation of mechanistic description of certain properties of living structures.
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How can/should we distinguish between a Biochemical and a Chemical Reaction.
As per one explanation:-
Chemical reactions are discrete reactions with catalyst involved in the process where as in biochemical reactions there are a series of reactions involved with the product of one acting as the substrate for another and this complex process of interchanges taking place with the involvement of enzymes.
For a more specific example if we are conducting photosynthesis in vitro then it will be considered as a biochemical reaction rather than a chemical reaction.
But the dilemma stems from the fact that, even chemical reactions go through complex series of steps, like any organic synthesis reaction. In this case also there is the involvement of catalysts like enzymes. Thus, can we consider it as a biochemical reaction! But mostly we only attribute it to be a chemical reaction which is indeed the case.
So, what is the proper difference or point of distinction between a biochemical and a chemical reaction. How can we exactly relate that one reaction is a biochemical and the other is chemical!
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Dear @Mrutyunjaya Panda All biochemical reactions are chemical reactions. I agree with Dr @Frank T. Edelmann in that in principle, there is no major difference. The same reaction can occur 'in vivo' and 'ex vivo'. You can also access a similar discussion at the following link:
Best wishes, AKC
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I need brief information about the field of the researchers who work with bioimaging techniques in their researches. In Finland, there is the public concept that they think a researcher with biomolecular and biochemical background must stay in his/her old methods of researches which is work in the lab and pipetting, etc. I am so much interested to know is it true about all scientific groups that you cant get a chance of trying new techniques and also learning which suppose to be the main purpose of science and its progress or as I understood it is just an excuse? Science cant grows with a limit or making exclusiveness.
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Breakthroughs and discoveries in science usually occur when scientists do something different or notice something odd. This happens far more frequently on the boundaries between disciplines than in the core of the discipline. For example, sequencing DNA used to be a very slow, painstaking process. Then the instrument makers got involved in the biochemistry processes and things got much quicker, paving the way to more discoveries. The fun science is usually the science which combines multiple fields, so learn and do what you enjoy. You will be far more successful than if you artificially limit yourself. But beware of overcommitting, as well. Have a goal and do what it takes to get there, but avoid distractions as much as possible. Finally, be aware that what you study in college does not necessarily define your career. I am a physicist by training, but worked for 15 years as a professional computer programmer. I have had no formal computer programming instruction, but learned it all by doing. Just keep learning and doing what you love, and you will never run out of things to do. Good luck!
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For the simulation purpose, I need force-field for Mn3O4. I searched and tried a lot but almost unable to get appropriate force-field parameters for it. Can anyone help me by suggesting or availing it ?
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You can try with Swissparam to generate required force-fields parameters.
Please follow the link:
Upload your structure in .mol2 format. You can use Avogadro or Jmol to prepare the structure in .mol2 format. Once prepared, run the .mol2 structure and wait for few minutes to get output file from Swiss param based software and then do the required changes for the force-field parameters.
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What impacts do these drivers have on socioeconomic and biophysical activities in the country
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In a small search, the climate of South Africa is cataloged with mild and rainy winters, and hot and sunny summers, however the atmospheric effects will sometimes show a significant deterioration.
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Dear all,
Besides biophysical or Biochemical approach, is there any other way of studying protein-protein interaction. I am planning to work on viral protein interaction with host proteins. The conventional method to study is yeast hybrid tool. However, I would like to explore other approach. Please suggest the way other that yeast as it takes huge amount of time and mutations issues are always a concern in yeast that results into some unexpected unexplained results. looking forward to hear from you.
Thank you in advance
Prem
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Thank you very much for sharing the posts
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What are the differences between Medical and Biophysics?
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1. biophysics is the study of biological processes and materials through the theories and tools of physics; the application of physical methods to analyze biologic problems and processes.
2. The study of physical processes (for example, electricity, luminescence) occurring in organisms.
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I'm taking some measurements using Raman spectroscopy of healthy pig eye samples using a new excitation wavelength and my supervisor said to choose a sample size to allow for spec/sens of 85%. These measurements will be identical just on different, healthy eye tissue to simply show that I obtain similar things each time. Is there a way to estimate/calculate what my sample size should be for this or do I need previous data, numerical limits etc? Any help would be great, thanks!
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Based on the results that we have presented, a sample of minimum 300 subjects is often sufficiently large to evaluate both sensitivity and specificity of most screening or diagnostic tests
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I have had unheard of success with protein crystallography lately from a super successful protein expression and purification batch.
I have attained a lately reproducible vast amount of crystals of no average size. Is there a way to tell based on appearance which of these crystals should diffract the best?
All these crystals grow from a clear droplet in 12 hours.
What's the most important parameter?
* transparency?
* size?
* how intensely it reflects light? birefringence?
* geometry?
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Hi there, Unfortunately there is absolutely no link between the size and appearance of a crystal and its ability to diffract. Gorgeous crystals may diffract very badly and little dirty bits may result in structure at 0.8A resolution (The opposite may also apply!).
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It is well known that heating can denature proteins. However, what does happen to proteins in the case of short and ultrashort (microsecond or nanosecond scale) heating to extreme temperatures (100-1000 degrees of Celsius) ? Such heating occurs for example when applying ultra/short laser pulses or pulsed intense electric fields.
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At these short times proteins can withstand much higher temperatures. For example, gelatin gel (5-10 %w/v) remains solid when heated to 500-700 degrees C by IR radiation of microsecond duration. Instead, explosive evaporation of water will occur with mechanical damage to the tissue, possibly breakdown plasma cascades. The paper below LITERALLY has it all. Also you may read about Arrhenius integral which is a measure of thermal damage to macromolecules.
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Solving the protein structure prediction problem by AlphaFold2(AF2) from sequence seems at its core a game-changing breakthrough. Major areas of biology and biophysics will thrive and others may become diminished or even obsolete.
Will AF2 hurt or benefit experimental methods for determination of protein structure? Structures of large macromolecular machines should be enabled by having accurate computational structures for subunits and components. X-ray structure value may become more specialized. One thing that seems likely is that the already great value of sequence data (which is doubling every 8 months) is likely to become far greater by being more directly connected to spatial information. At its core solving the protein folding problem will enhance sequence impact and thereby increase the overall the pace of biology and biophysical advances by improving the ability of structural biology to better harness the flood of sequence data. How much will medical areas such as cancer biology and cancer drug discovery benefit? How about research areas such as protein design? What areas are likely to be most powerfully advanced and which most negatively impacted? What do you think?
How should senior and early stage researchers position themselves to ride the wave of growing positive impacts and reduce research wipeouts when this new mega-wave adds constructively or destructively with current research waves of systems biology and single molecule and single cell advances? What should we change in training for graduate students and fellows to insure they are correctly positioned for science with reliable protein structure prediction?
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John,
You have asked an interesting question. For a senior member of structural biology community it shows the yearning for practical solutions as well as naivety of the real difficulties in even defining the problem. The protein folding problem is an ill-defined and most likely unsolvable problem in its classic sense of axiomatic reductionist sciences. If the old Anfinsen view was true about the minimum of global free energy there never would be life on Earth or anywhere else. The new paradigm that I partially formulated is that every protein (as a matter of fact every macromolecule of life) has its own specific recipe how to combine the structural with dynamical features to accomplish the desired function (PNAS 106(2009)10505). It means that there is a unique proportion of conditionally stable structure to conditionally unstable elements to perform given function. This ill defined condition is not solvable by classic axioms but it just might be partially solvable by fuzzy methods such as AI. Why AI is so good? Because the protein folding problem is a practical not a theoretical problem. Depending on conditions and their possible changes the protein suppose to perform a certain function. This is what physics call "self organized criticality". This is far from equivalency of having a certain structure nor a possible unique binding site nor anything that remotely can be called a solution. AI just simply captures better the set of heuristic rules than other methods particularly dynamical coupling with solvent. There are millions of examples to support this view. If anybody wants to engage I will be happy to, but not now. There is no place here to mention even a single one.
So the only hope is that we found an effective heuristic tool that gives us better approximation to reality. To be properly tested the method needs to be exposed to finding bordering cases when it breaks down. What conditions produce divergencies. What percentages of certain structures are folded and are not. For instance only around 30% of genomes of higher eukaryotes are properly folded. Around 30% is conditionally folded (on the target, in the particular compartment) since the misfolding diseases. And finally around 30% is almost never folded with residual presence of folding nuclei that precipitate the function. So all these classes of proteins must be tested against this new AI approach to see when the rules break down and how to enhance them.
Therefore, it is not a breakthrough that John is so excited about. But it is definitely progress. But, I would not see anytime in the future, abolishing or significant diminished importance of any particular field of science, in exactly the same way as radio did not get extinct by TV.
Bog
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AF2 may most strongly impact experimental determination of protein structure by multiple methods with possible benefits and negative impacts over time.
Some areas may need to quickly pivot or become obsolescent, whereas other may thrive.
Structures of large macromolecular machines should be enabled by having accurate computational structures for subunits and components.
The already great value of sequence data (which is doubling every 8 months) is likely to become far greater by being more directly connected to spatial information.
Overall the pace of biology and biophysical advances can be expected in increase by the ability to better harness the flood of sequence data.
What do you think?
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X-ray people might be impacted more than NMR and cryo-EM people by AF2. It may replace all biophysical techniques for structural determination someday, IMHO, they advertise much better than academic groups for the things they've achieved and still a long way to go (like when Rosetta first introduced). Not to mention the missing pieces like non-natural amino acids, binding partners, dynamics, different circumstances in the cell, more or less scientists would like to validate the prediction experimentally. However, it is hard to argue with its valuable inputs and insights before wet bench works that cost a lot.
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Hey scientists,
I am intending to observe the extension of a short 10-mer primer on a 16-mer template. I just use a certain DNA polymerase to extend the primer on a templating strand with a matching or mismatching deoxynucleotide triphosphate (dNTP) and the necessary cofactor magnesium.
I was thinking that depending upon the polymerization efficiency, I might have products that are size "n", "n + 1", "n + 2", "n + 3", " n + 4", "n + 5", "n + 6" in size where size "n" is the size of dsDNA duplex without addition of dNTPs, or in other words no extension.
I was envisioning I just combine in a test tube the enzyme with the template:primer construct + the dNTPs of interest + MgCl2 and let the reaction happen for 30 minutes. Then I would denature my protein with heating the test tube to 50°C. (My polymerase isn't one of those thermal stable polymerases), and slow cool the test tube to room temperature.
I could run the products on an ethidium bromide stained gel with a control being a lane with just the template:primer construct with no extension, and then lanes with attempted extension of the dsDNA construct. If at least one base is added I want there to be a notable shift.
What resolution gel could achieve that?
4% Agarose or 16% polyacrylamide or something?
It would be cool, but it's not a big deal for me to distinguish exactly how many bases were extended from "n". So long as I can see an extension from "n" and I would be satisfied.
Thanks!
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I would use 20% denaturing PAGE on a long gel ( 40cm old fashioned sequencing gel rig) if possible and silver stain for visualisation. If you have access to a dna sequencer then you could put a long (20-30 base) 5' tail on your oligo to increase its size and dye label the oligo. Then if you run the extension products in the linear acrylamide capillaries it will give you single base discrimination. Size standards are a problem with short sequences which is why I suggest a tailed oligo to bring the product size into the range of the size standards
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There is a growing interest in developing means of early detection of crop nutrient deficiencies. It has held that by the time a deficiency shows up in a soil sample, the crop is already under stress. Does crop sap analysis help to resolve this information gap? If so, how can we expand the use of this from high margin specialty crops to commodity crops?
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Leaf and petiole analysis is an established tool. Protocol for perennial crops have been standardized for nutrient analysis.
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So I am trying to crystallize a Protein:DNA complex with DNA at at least 5 times excess at basic pH with a certain poleythene glycol molecular weight (PEG) and a mixture of soluble salts at low concentration less than 110 mM. I was getting a microcrystalline shower at a certain concentration of the components but lots of amorphous brown precipitate.
So I tried glycerol concentrations logically from 0 to 5%. I blocked the microcrystalline shower at glycerol concentrations greater than 1%. I kept increasing the concentration of glycerol regardless and at glycerol concentrations higher than 5% (v/v) and all other components in the system no brown amorphous precipitate appears; total protein is soluble. At glycerol concentrations greater than or equal to 15% (v/v) all other components in the system, the brown amorphous precipitate comes back. When glycerol is @ 13% (v/v) I got some small crystals not a showers worth. But nucleation seemed to fall asleep and that was it.
Then I lowered the concentration of one of the salts potassium citrate monohydrate to 100 mM and I get a reproducible white haze or white sheen appear over the droplet from the edge. The haze now seems to appear at any concentration of PEG much less than or equal to the concentration of PEG that I would expect to give me crystals. I also think the haze is growing.
I have seen this haze before when I crystallized the free protein under totally different conditions with different components in the system and acidic pH. This white haze would move from the edge of the droplet towards the center and then medium sized to large crystals would appear out of the haze in less than 30 minutes. Those crystals diffracted and a protein structure was solved. Of course under these conditions, crystals haven't grown out of the haze yet. Crystallizing the more conformationally inflexible tight binding DNA complex is more difficult than it logically should be.
Is there a term for this white haze or any information I can read about it?
What does it suggest to you?
Thanks!
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To me, this looks like amorphous precipitate of your protein and maybe a sort of "crust" or skin of mother liquor that covers the droplet during vapour diffusion. I'm not sure what you are looking for, but this specific condition does not contain any crystals, and the precipitate does not really look pre-cristalline.
How did you come up with this condition? Have you tried using commercial screens to determine a suitable crystallisation condition before optimising this specific buffer combination? You usually don't optimise until you actually have a hit condition.
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What happens when we culture cancer epithelial cells in TCPS?. Is the cell present as epithelial or differentiate into mesenchymal cells?.
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Aug 2, 2016 - Three-dimensional (3-D) cultures of cancer cells can potentially bridge the gap ... alternative to 2-D cell culture [3] as they can reproduce many aspects of the tumor ... to cells grown on 2-D tissue culture polystyrene plates (TCPS). ... If you allow us to do so, we also inform our social media, advertising and ...
by SP Lamichhane - ‎2016 - ‎Cited by 32 - ‎Related articles
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Hello fellow scientists,
I have some additional questions about the dissociation constant for a protein binding ligand.
My main questions is if the protein concentration is much greater than the KD and the ligand concentration is still in excess of the K_D how much protein is bound?
For a Protein binding a ligand, we have the relationship:
P + L ⇌ PL . This has forward and reverse rates of binding, and ...
KD = {[P] * [L]} / [PL],
The fraction of protein bound (FPL) will be:
FPL = [PL] / ([P] + [PL]) = {[L] / ([L] + KD)}
If the ligand concentration is some multiple integer n of the KD we get this cool relationship:
[L] = n * KD ; n = 1, 2, 3, ... etc.
FPL= (n * KD) / (n*KD + KD)
= n / (n + 1)
What they teach you in school is that if the ligand concentration is at the KD, n = 1 then half the protein is bound: 1 / (1 + 1) = 1 / 2. This relationship also tells you that if [L] = 9 * KD then 90% of the protein is bound.
One can plot this relationship as I have.
So I have some questions assuming a reasonable good ligand interaction with KD = 10 µM,
(A) If [L] = 9 * KD, and fixed protein concentration = KD = 10 µM, how much protein is bound?
I think that 90% of the protein is bound.
B) Say you are a structural biologist and you need more ligand and protein than the KD at 10 µM,
If [L] = 500 µM (that is 50KD) and initial protein concentration is 100 µM (that is 10KD), then how much protein is bound?
Given the relationship I derived, {50 / (50 + 1)} = 98% of the protein should be bound.
But the protein concentration is beyond the KD so can that even be correct?