Science method

Molecular Modeling - Science method

Molecular Modeling are molecular modelling encompasses all theoretical methods and computational techniques used to model or mimic the behaviour of molecules.
Questions related to Molecular Modeling
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what is benifit of doing molecular simualiton in reduce units especially if have moleuclar like dna or potein where are so many different atoms??
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Using reduced units in molecular dynamics (MD) simulations simplifies calculations by making properties dimensionless, allowing for easier comparison across systems. It is particularly useful for studying fundamental physical behaviors without being tied to specific units. However, for complex biomolecules like DNA or proteins, reduced units may oversimplify interactions, making them less practical for detailed biological simulations.
All of which can be easily done at mdsim360.com, a new platform that lets you run MD simulations entirely online without local installation.
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Hi, folks!
I am studying the hyperpolarizability of a crystal using DFT calculations. I learned that Gaussian code is able to do that with POLAR keyword in the input file. As Gaussian is not professional at dealing with periodic structures, I abandoned the crystal box and took out the coordinates of its unit cell as well as 1*1*2,1*2*1, 2*1*1, 1*1*3 supercells for input structures of Gaussian. The calculations are performed at CAM-B3LYP/6-311++g(d,p) level. Below are some results of total beta in the unit of 10^-30 esu.
1*1*1: 33
1*1*2: 97
1*2*1: 78
2*1*1: 53
1*1*3: 199
As can been see, these values diff largely and do show any convergence. What is the correct way to simulate the crystal? How large size of crystal structure should be used?
Thank you very much in advance!
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Dear Yin Li,
The functional choices depends of your system. If you are working with a complex system, hybrid functional will have expensive computational cost. But, if is possible to work with it, you can use.
You can perform a geometry optimization using pure (GGA or LDA) functionals or hybrid (HSE06/PBE0) and calculate NLO properties. CASTEP have a specific keyword for this. You can you on the fly pseudopotentials, because it is more precise than conventional pseudopotentials.
You can contact me trhough my email bruno.poti@ifce.edu.br and we can discuss in more detailed way
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Hello,
I have been performing differential expression gene analysis on various microarray and RNA-seq samples from NCBI GEO and TCGA databases.From there we either get a specific gene as up or downregulated. For an upregulated gene, we can inhibit it through various computer-aided drug discovery and molecular modelling approaches, but what about a downregulated gene? What further computational analysis could be performed before moving forward to wet-lab experiments?
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You may use either MITHRIL
or PHENSIM
You will get a predfiction of all perturbed genes and pathways and use those drugs whose simulation with PHENSIM is anticorrelated with the given phenotype at the pathway level you would like tro restore
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Virtual reality for molecular modelling
If someone share related best citated articles to me.
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Dear Alisha Aziz one the most mistake is to dictate model nature to follow. How could nature follow our modeling?
We must observe nature not model it .
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I want to simulate polymer in water for that I have confusion in reduce units according my understanding of reduce units if we perform simulation in reduce units means we are make a generalize model because we set sigma , Ellison, mass and other bonding parameters equal to one means we are simulating not real model.
It's like we are doing simulation of ball and spring model.
My confusion is regarding parameter that is equal to one or not for all atoms?
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Your understanding of reduced units in molecular dynamics simulations is on the right track. Reduced units are a way to scale the physical properties of a system so that certain parameters are set to unity, which can simplify calculations and make the simulation more general. Here’s a clearer explanation of reduced units and how they apply to your polymer in water simulation:
Reduced Units:
In reduced units, the following parameters are often set to 1:
  • Length (σ): The length unit is typically set to the size of a particle, which could be the van der Waals radius or another relevant length scale.
  • Energy (ε): The energy unit is often set to the strength of the pairwise Lennard-Jones interaction between particles.
  • Mass (m): The mass unit is set to the mass of a particle in the system.
These units are defined relative to the system you are studying. For example, in a Lennard-Jones fluid, σ might be the distance at which the interparticle potential is zero, and ε might be the depth of the potential well.
Are All Parameters Equal to One?
No, not all parameters are equal to one. Only the base units (length, energy, and mass) are set to one. Other parameters, such as bond lengths, angles, charges, and force constants, are scaled relative to these base units. Here’s how it works for your polymer in water system:
  • Bond lengths and angles: These are scaled relative to the length unit (σ). For example, if a bond length in your polymer is 0.2 nm, and σ is defined as 0.1 nm, then the bond length in reduced units would be 2σ.
  • Charges: These are scaled relative to the square root of the energy unit (ε) divided by the length unit (σ). This ensures that the electrostatic interaction energy has the correct dimensions.
  • Force constants: For bonded interactions like harmonic bonds and angles, the force constants are scaled relative to the energy unit (ε) and the length or angle unit.
Simulating a Real Model:
When you perform a simulation in reduced units, you are still simulating a real model. The advantage is that the simulation becomes more general and can be applied to a wide range of systems with similar interactions. The parameters you use (like σ, ε, and m) are chosen to reflect the physical properties of the actual system you are studying.
Polymer in Water:
For a polymer in water, you would typically define your reduced units based on the properties of the solvent (water) and the polymer. For example:
  • Length (σ): Could be set to the oxygen-oxygen van der Waals distance in water.
  • Energy (ε): Could be set to the strength of the Lennard-Jones interaction between water molecules.
  • Mass (m): Could be set to the mass of a water molecule.
Then, the polymer’s properties would be scaled accordingly. This does not mean you are simulating a ball and spring model; rather, it’s a way to abstract the physical properties to a set of units that makes the simulation more manageable and computationally efficient.
In summary, using reduced units does not mean you are simulating a non-real model. It is a way to standardize the system so that the simulation can be applied broadly while still reflecting the physical properties of the real system. The choice of what parameters to set to one and how to scale the others depends on the specifics of the system you are simulating.
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Hello everybody !
I am working on a medium size organic molecule (around 40 atoms) and I try to check the presence of a conical intersection between S1 and S0. I used DFT and TD-DFT to compute the PES of S0 and S1 in my molecule along different modes and motions but for now no conical intersection was identified.
Do you think it would be a possible and interesting approach to use TD-DFT/MD simulation to start from the S1 optimized geometry and apply temperature to check the evolution of the geometry in the S1 state of the molecule in time ? Will it go back to the S0 optimized geometry in the case of an easy accessible conical intersection ?
Thank you for any help you may provide and for your interesting comments about it.
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Yes, using Time-Dependent Density Functional Theory (TD-DFT) combined with Molecular Dynamics (MD) simulations can be a viable approach to find conical intersections.
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Hi there,
I understand one can use the mouse to click the control panel to show disulphide bonds on the protein, but just out of curiosity, is there any command line that is able to do the same, which is to show the disulphide bonds on a certain object?
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select SSbond, CYS/SG and bound_to CYS/SG
show sticks, SSbond
You can further refine the selection by specifying the object, chain, range of residues etc.
example:
#load antibody
fetch 1igt
color slate, chain B+D
color pink, chain A+C
color white, hetatm
#show hinge disulphides
select hingeSS, (/1igt/B/B/CYS/SG and bound_to /1igt/D/D/CYS/SG) or (/1igt/D/D/CYS/SG and bound_to /1igt/B/B/CYS/SG)
show sticks, hingeSS
color yellow, hingeSS
#since this shows only the bond between the sulfur atoms, you may want to expand the selection to the entire cystein residue
show sticks, br. hingeSS
color yellow, br. hingeSS
Similarely, you can selectively display the disulfide bonds between light and heavy chain and the various intradomain disulfide bonds
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How can I download DESMOND for molecular dynamics analysis from the website: https://www.deshawresearch.com/downloads/download_desmond.cgi/ ?
I have already tried filling out the form and so far I can't access the download link or receive any link by email. Has anyone had the same problem?
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I tried filling the form thrice. Still couldn't get the download link. Also can you give more details on which upper part because the option for "already filled the form can't be seen".
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[INFO ] Running calculations on normal system...
[INFO ] Beginning GB calculations with /home/bio/anaconda3/envs/gmxMMPBSA/bin/sander
[INFO ] calculating complex contribution...
100%|##########| 101/101 [elapsed: 08:08 remaining: 00:00]
[INFO ] calculating receptor contribution...
100%|##########| 101/101 [elapsed: 08:16 remaining: 00:00]
[INFO ] calculating ligand contribution...
100%|##########| 101/101 [elapsed: 00:02 remaining: 00:00]
[INFO ] Beginning PB calculations with /home/bio/anaconda3/envs/gmxMMPBSA/bin/sander
[INFO ] calculating complex contribution...
0%| | 0/101 [elapsed: 00:00 remaining: ?][ERROR ] CalcError
/home/bio/anaconda3/envs/gmxMMPBSA/bin/sander failed with prmtop COM.prmtop!
If you are using sander and PB calculation, check the *.mdout files to get the sander error
Check the gmx_MMPBSA.log file to report the problem.
File "/home/bio/anaconda3/envs/gmxMMPBSA/bin/gmx_MMPBSA", line 8, in <module>
sys.exit(gmxmmpbsa())
File "/home/bio/anaconda3/envs/gmxMMPBSA/lib/python3.9/site-packages/GMXMMPBSA/app.py", line 101, in gmxmmpbsa
app.run_mmpbsa()
File "/home/bio/anaconda3/envs/gmxMMPBSA/lib/python3.9/site-packages/GMXMMPBSA/main.py", line 205, in run_mmpbsa
self.calc_list.run(rank, self.stdout)
File "/home/bio/anaconda3/envs/gmxMMPBSA/lib/python3.9/site-packages/GMXMMPBSA/calculation.py", line 142, in run
calc.run(rank, stdout=stdout, stderr=stderr)
File "/home/bio/anaconda3/envs/gmxMMPBSA/lib/python3.9/site-packages/GMXMMPBSA/calculation.py", line 625, in run
GMXMMPBSA_ERROR('%s failed with prmtop %s!\n\t' % (self.program, self.prmtop) +
File "/home/bio/anaconda3/envs/gmxMMPBSA/lib/python3.9/site-packages/GMXMMPBSA/exceptions.py", line 171, in __init__
raise exc('\n\n' + msg + '\n\nCheck the gmx_MMPBSA.log file to report the problem.')
CalcError:
/home/bio/anaconda3/envs/gmxMMPBSA/bin/sander failed with prmtop COM.prmtop!
If you are using sander and PB calculation, check the *.mdout files to get the sander error
Check the gmx_MMPBSA.log file to report the problem.
Error occurred on rank 6.
Exiting. All files have been retained.
Abort(1) on node 6 (rank 6 in comm 0): application called MPI_Abort(MPI_COMM_WORLD, 1) - process 6
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Okay! I'll do this.
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Now, I am intrested in the molecular modelling of proteins and one of the most important protein-ligand docking software is Autodock vina so I want to know how can I get free download for windows 10 ? thanks anyway.
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Dr. Noor, please find detailed instructions attached to the email, providing a step-by-step guide for downloading and running the software.
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Hello everyone,
I docked the inhibitor to the metalloenzyme and the next step was the minimization of the complex. Unfortunately, during the minimization protocol, I got the error as below:
>Solvent file: XXX\bin\Windows-x64\..\..\data\water.slv
>Block specifies desired NFIELD -- accepting block
>RDSOLV: missing params for atom number 36261 (type n2) in .slv file, solvation model 3
>MINI: Error generating interactions
>Problem in minimization of distinct structures.
>Skipping input structure due to forcefield interaction errors.
>BatchMin: normal termination
The atom number 36261 is the Nickel 2+ ion. I've tried to change for the one without charge, but still the OPLSe do not operate with it.
My question is about: how to add the nickel ions to the FF with proper parameters.
Thank you!
Michal
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Try with Schrodinger Q/A
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Molecular dynamics simulation , bioinformatics , molecular docking
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In my opinion, for simulation analysis, you should use a different working setup instead of using a laptop. However, for docking analysis, any laptop can be used.
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Are you familiar with Research4Life? It's a program that provides free or low-cost access to scientific research in low-income countries. Research4Life has two eligibility lists: Group A and Group B. Group A includes countries with the lowest gross domestic product, lowest human development index, and other factors that indicate lower-income countries. As an immunoinformatics, Bioinformatics and Molecular Modelling researcher, I'm calling on researchers from Research4Life's Group A countries to join me in collaborative research efforts. By working together and utilizing the program's valuable resources, we can advance our research and make a difference in the world. Best of all, with this collaboration, it will be completely free. #Research4Life #immunoinformatics #bioinformatics #molecularmodelling #collaboration
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I’m interested
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I want to perform a MD simulation in LAMMPS for a water droplet impacting a rough Copper surface at an assigned velocity and then nucleate this droplet into ice.
I have made the droplet structure and the substrate surface individually using ATOMSK. I'm able to equilibrate the structures in LAMMPS individually as well - both at 250K which is the target temperature. However, the output from the two equilibration (droplet and copper substrate) yields two data files using the "write_data" command that need to be combined in order to obtain the final system.
My query is on what will be the best technique to merge these data files for a final equilibrated structure that can be used in LAMMPS. Any help or insight is appreciated.
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Hello,
The following article might help you.
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Hi there,
I would like to understand numerical hessian calculation in molecular modelling better.
If I estimate the (semi)numerical hessian, so either using the gradient or only the energies for the displaced molecule, I get the hessian matrix. After mass weighting, diagonalisation, taking the root and some unit conversion, I end up with frequencies. In case of imaginary ones, I have a not fully optimsed structure or transition state.
After implementing all this in own code, I ended up with sometimes having imaginary frequencies for structure being in a geometrical equilibrium.
--
Eigen::SelfAdjointEigenSolver<Geometry> diag;
diag.compute(hessian);
vector = diag.eigenvalues().cwiseSqrt();
--
For smaller molecules, the results fit to the results obtained with another program (some differences due to numerical noise). For larger molecules, there are imaginary frequencies I don't understand.
I found an illustrating whitepaper at
. Why would the force constants be different if the molecule is centered and reorientated, if at all. Is there something else I have overlooked?
The WIP code is located at:
Thanks and best regards,
Conrad
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Understanding the differences in frequencies obtained from a numerical hessian calculation when the Eckart equation is not included is an important aspect of molecular modeling. The Eckart equation is commonly used to transform the mass-weighted Hessian matrix into normal modes by accounting for the rotation and translation motions of the molecule. Not including the Eckart equation can lead to several differences in the frequencies:
1. Translation and Rotation: The Eckart equation accounts for the translation and rotation of the molecule as a whole. Neglecting these terms can cause the frequencies to include contributions from these global motions, resulting in spurious low-frequency modes that do not represent molecular vibrations.
2. Zero Modes: Zero modes correspond to the translation and rotation of the molecule, and they should have a frequency of zero. When the Eckart equation is not included, these modes may have non-zero frequencies, leading to erroneous results.
3. Inaccurate Frequency Scaling: The Eckart equation is also used to scale the frequencies obtained from the Hessian matrix to match experimental values. Neglecting this scaling can result in frequency values that are not in good agreement with experimental data.
4. Numerical Noise: Numerical noise can also contribute to differences in frequencies, particularly for larger molecules. Small errors in the calculation of the Hessian matrix and subsequent diagonalization can accumulate and lead to deviations in the frequencies.
In your case, the presence of imaginary frequencies for structures in geometrical equilibrium could indicate issues with the optimization procedure or potential instabilities in the geometry. It's important to ensure that the optimization is performed correctly, considering convergence criteria and appropriate settings for the optimization algorithm.
I would recommend reviewing the implementation of your code, ensuring that the Hessian calculation, mass weighting, diagonalization, and unit conversions are correctly implemented. Additionally, consider checking the accuracy of the employed optimization algorithm and potential issues specific to larger molecules.
For further insights, I suggest consulting literature on numerical hessian calculations, vibrational analysis, and molecular modeling methodologies. Comparing your implementation with established methods and validating it with benchmark systems can also help in identifying and resolving any discrepancies.
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Dear All,
Here is a simple and effective way to use ChatGPT with PyMOL (a molecular visualization software based on Python).
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Dear respected researchers
We have worked on a paper on that particular issue (ChatGPT and Academic research)
Title: "ChatGPT and Academic Research: A Review and Recommendations Based on Practical Examples"
The article's link:
I hope you will enjoy the article and it will be helpful for academic people.
Regards.
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We can estimate the pore diameter for a high-resolution TEM image visually and easily. At the same time the DFT calculations are based on molecular modelling and takes into account direct interaction of adsorbate with the adsorbent surface. If both methods gave different results, which would be taken into consideration?
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Agree @Jurgen, thanks
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How to find pkb value of nicotine using Gaussian 16 software ?
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Dear Anandhu Gopan,
The easiest way to compute a pKa value in Gaussian is to use the isodesmic method. This allows you to avoid any complex thermodynamic cycles. In this method you use a reference with known pKa (e.g. formic acid) to compute the pKa of interest. Please be also aware that the implicit solvation models implemented in Gaussian are far from perfect. Fortunately it fails in a predictable manner so you can scale the obtained raw pKa value in order to obtain a reasonable guess. Using this method you can get pKa values with an accuracy of roughly 1 pKa unit with minor computational costs.
A detailed description of the method, its accuracy and suitable scaling relations can be found here:
Best wishes
Michael
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Hello everyone,
I'm trying to model the silica-water interface using classical molecular dynamics. Hope to use LAMMPS for the simulations and CHARMM potential to model the atomic interactions. I wonder how to generate the initial atomic structure of the system. The "nanomaterial modeler" module in CHARMM-GUI comes in handy creating the atomic structure. But I do not have complete control over my structure if I use it. I need to attach the hydroxyl groups to the dangling silicon atoms in the interface as well. Therefore, it feels a bit complicated when defining the bonds and angles in the system using Matlab or python. As I'm using CHARMM potential, the relevant potential parameters need to be specified as well in the atomic data file. Any advice would be highly appreciated.
This is the system I could generate from CHARMM-GUI,
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To generate an initial atomic structure of a silica-water system, there are several approaches that can be used. One popular approach is to use a software package like Materials Studio or Avogadro, which has built-in tools for generating molecular structures. Here are the steps you can follow:
  1. Create a crystalline silica structure: You can generate the α-cristobalite structure using a software package like Materials Studio. Alternatively, you can find the atomic coordinates of the α-cristobalite structure from a database such as the Crystallography Open Database (COD) and import them into your simulation package.
  2. Add water molecules: Once you have your silica structure, you can add water molecules to the system. You can do this by placing water molecules in the voids of the silica structure or by equilibrating the system with water molecules using an NPT simulation.
  3. Define bonds and angles: To define the bonds and angles in the system, you can use a software package like CHARMM or LAMMPS. These packages have built-in tools for defining bonds and angles in a system.
  4. Assign parameters: Once you have defined the bonds and angles in the system, you need to assign parameters to the various atomic interactions in the system. For example, you need to assign force field parameters for the silica-water interactions.
  5. Equilibrate the system: Once you have created the initial atomic structure and assigned parameters, you need to equilibrate the system using an NPT simulation to ensure that the system is at the correct temperature and pressure.
Note that the process of generating an atomic structure can be time-consuming and require some trial and error. However, by following the steps outlined above and with some experimentation, you should be able to create a reliable structure for your silica-water system.
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I want parameterise the ZN metal, which is coordinated with CCCH (three CYS and one HIS residues) residues. I just followed MCPB tutorial. While side chain modelling i got errors and unable to fix the problem. Here, i have attached my pdb file , sidechain.bcl file and sidechain.bcl log files.
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Dear all,
I made a semiempirical orbital calculation (using MOPAC) of a fairly large complex of a ligand and a protein binding site. Now I am trying to find the highest occupied orbital with a large (the largest) contribution of the catalytic residue (oxygen of a serine in this case) as well as the lowest unoccupied orbital with a large contribution of the reactive atom (carbonyl carbon) within the ligand.
The output contains a total of roughly 2000 molecular orbitals. Does anyone have suggestions of a piece of software that could help me here?
Thanks in advance
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It is worth mentioning that what you are looking for is not a unique solution to the problem. Although in your case what I am about to speak is somewhat unfeasible, it is absolutely possible from a theoretical point of view: imagine you have all the basis sets coming from a complete set centered on a single atom; the energy and electron density of the entire system will be exactly the same, but your question whether which atom will have the greater contribution to a given orbital will be meaningless since there is only one atom with orbitals.
I am not sure if I have explained in a satisfactory manner, but the section "covalent bonds to point charges" on the paper below, from Thimothy Clark, explains it very nicely:
Tim Clark cites the paper from Stone and Misquitta as the source of this idea:
Therefore, caution is advised when looking for "the atom with the greater contribution to a given orbital", because the answer might be tied to the particular choice of basis sets made prior to the actual calculation. In a semiempirical calculation, this seems even more dangerous because of the drastic simplifications made through the calculation.
Cheers,
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I am trying to do simple modelling similar to the basic tutorial given on the modeller's website following error occurs while I compile in the same directory.
FATAL ERROR: Cannot open file build_profile.py: No such file or directory.
Please help me to figure out this.
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hi, are you in the same folder where this file (build_profile.py) is? It seems you are terminal is in another folder and the modeler can not access this file.
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I have performed ligand docking analysis and found that some of my results have a mixture of positive and negative Rerank Score. Although all of them have highly negative MolDock score which was suppose to represent best binding affinity, I was wondering if having a positive Rerank score will cause effects to this prediction.
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how to analyze results Molegro Virtual Docker
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I want to visualise secondary structures of multiple proteins aligned (something similar to this figure). Any recommendations?
Thanks in advance
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try this one:
all the best
fred
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I have performed MD simulation of 100ns on Desmond and now I want to calculate solvent accessible surface (SASA) area over the trajectory. Can Anyone please guide how to do it? Thanking you all in Anticipation.
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Waseem Ahmad Ansari Thank you for your answer. The automatic calculations do include SASA but this is for ligand, I wanted to know the calculation for SASA of protein. However, I have sorted it out now. Thanks once again.
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Hi All,
I am currently trying to make a solvent box with dichloromethane, which can then be used to solvate a solute I am working with.
For that, I embedded 1050 dichloromethane (DCM) molecules into a 5x5x5 nm box. The force field I am using is OPLS-AA. Energy minimization and NVT equilibration results look good. However, when I conduct the NPT equilibriation step, I run into the problem that the density of my dichloromethane box is given as 1.53 g/cm^3, which is quite far off the literature value of 1.33. I used the npt.mdp file from the well-known lysozyme tutorial (http://www.mdtutorials.com/gmx/), and ran it for a bit longer (1 ns), while changing the isothermal compressibility from 4.5e-5 (water) to 1.02e-4 bar^-1 (dichloromethane). I’ve attached the .mdp file.
Interestingly, when I look another DCM box (OPLS-UA forcefield) that has been made available through user contributions on the gromacs homepage (https://www.gromacs.org/user_contributions.html#:~:text=20%20May%202003-,ch2cl2_box.tgz,-The%20package%20contains), they used the isothermal compressibility value for water (!) and arrive at a dichloromethane density close to literature value. I did the same for my dichloromethane box and also arrive at a density of 1.34 g/cm^3, which is very close to literature. But surely there must be something wrong, with this, as I assume I can’t just swap compressibility values between compounds.
Is the higher density obtained with the dichloromethane compressibility much of an issue for further simulations? If so, what could be the problem with using the correct compressibility that causes the density to increase so much and is there a way to fix it?
I've attached the .mdp and files of my NVT equilibrated box.
Thank you all in advance! I appreciate any help with this issue, as I am fairly new in the field!
Kind Regards,
Nick
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Isothermal compressibility defined in gromacs is not the fluid property, its an indirect way of putting the fictitious mass for the P-R barostat. While its recommended to use the compre value close to the compre of the fluid, its not a necessary requirement. If you are obtaining the right density and other thermodynamics correctly with the default (say water compressibility), its okay to go with it further. All you need is to make sure that the given parameters describe the physics and thermodynamics of the fluid correctly.
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Hi everybody
I am seeking for a molecular modelling package with graphical interface for drawing molecules in Ubuntu. Previously, I have worked with HyperChem and Gaussian in windows. Is there a software similar to HyperChem?
Thank you
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Thanks for your responces
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In order to represent our observations or sight of a physical process and to further investigate it by conducting experiments or Numerically models? What are basics one need to focus ? Technically, how one should think? First, thing is understanding, you should be there! If we are modeling a flow we have to be the flow, if representing a let's say a ball, you have to be the ball! To better understand it! What are others?
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Aditya Kumar Mishra replication is tough though i do agree with the expert comments above that physical replication like visualization is a must one of the important criteria I feel is to To assess applicability one must always specify the requirements along with exact what attribute of a previous results of interest.
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Most pharmacy students rated the use of complex molecular modelling or computational tools as useful for improving engagement and learning outcomes. Further, it significantly improves students' understanding of pharmacological concepts necessary for competency in medication management, based on significant improvements in post-test scores. 
My concern is that if all the above mentioned/stated positive outcomes generated through the use of these pedagogical tools in some ways or other help to reduce the cognitive load or not? Do we have reasons to believe this? I am trying to establish the link between how 2D or 3D visualisation technologies and their relation to cognitive load management.
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Thanks, Mohammed Yaseen Alzahawi , I am of the same opinion, however, I am more interested in the underlying rationale.
Dear
Wajd Alkhawaldeh
, thanks for your elaboration on the query. With my limited understanding and what the literature outlined, it depends on the VSA (Visual-spatial abilities) capability of the individuals. Individuals with high VSA are able to process spatially complex procedures while still retaining sufficient cognitive resources to benefit from using 3D visualisation while learning. With low VSA, individuals utilise more cognitive resources when performing a spatially complex task. This results in an increase in cognitive load as they learn. Therefore, in individuals with low VSA, it may be possible to compensate for the higher cognitive demands by improving instructional methods.
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Cannot find any complete set of parameters for Na-Al-Si-O (or sodium aluminosilicates) for ReaxFF. Any help will be very much appreciated. 
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How does one go about parameterizing the forcefields? I do not seem to be able to find any code used for training/reparameterizing ReaxFF work.
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I trying to install vina using pip and get this error(see file). I think the problem is that boost is not added to path. I have tried various tips posted on stackoverflow threads, read the boost docs for working with python and even watched the videos about how to install boost, but have not been able to solve this problem.
Apart from using pip I tried to install via conda following this manual:
Error not fixed. How i can add boost to path? After installing boost via bootstrap.bat and then .\b2 i get 2 links, but if i add it to PATH variable it doesn't solve this problem. I want to try use Vina scripts in python file
Has anyone been able to install Autodock Vina via pip or conda?
Brief output:
...
ValueError: Boost library location was not found!
Directories searched: conda env, /usr/local/include and /usr/include.
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I have described how to solve this problem on stackoverflow if anyone gets this error.
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I have performed a simulation via Desmond, now i want to perform MMPBSA. I dont think Desmond has any functionality of calculating MM/PBSA. I wonder how to move forward? Youre guidance will be highly appreciated.
Thanks
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Hi, I think you should look into this thread for details:
From "Bowen Tang"
Of course you can do this.
thermal_mmgbsa.py is in $SCHRODINGER/mmshare-vxxxxx/python/common
run it as below:
$SCHRODINGER/run thermal_mmgbsa.py <your_trajectory.cms>
Good luck.
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Actually I am printing unwrapped coordinates of atom but in that output file lot of extra things are written so how I can avoid these things. Is there any inbuilt lammps command. Please help me to overcome this problem #lammps
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Like Rahul Sahu mentioned above you can use the command in your input file (.in)
dump 1 all custom 100 file.xyz id xu yu zu
dump_modify 1 sort id
where file.xyz is the name of the output file
The second dump modify sort command makes sure atoms are written in same order for every frame. This is useful for easy post processing and data analysis.
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I'm trying to build outer membrane of e. coli with small peptides above it, with CHARMM-gui. Peptides should be positioned above the membrane, but charmm-gui creates space for them between LPS (lipopolisacharides) pushing LPS-s to the edges of simulation box.
If I use only one peptide, it is not problem, empty spaces is not big, and charmm-gui sucessfully finishes job. But when using more peptides, empty space created underneath them is large, so LPS-s are pushed to the edges, tightly packed, which obaviously causes problem for charmm-gui and gives error:
"Charmm terminates abnormally. Please check the output or report this failure to the CHARMM-GUI developers. The bilayer generation is stopped to prevent an infinite loop. Please refresh the browser to restart the bilayer generation with different random seed."
I tried several times, with the same outcome. It looks like membrane builder thinks that peptides are "inserted" in LPS, so it leaves empty space for them in between LPS-s.
I report error to charmm-gui developers, and got short answer: "View “step3_packing.pdb”. "
I looked, and see nothing strange, nothing to lead me to solve the problem.
Any idea where to look, or how to solve problem?
Third picture is outer membrane without peptides
Thanks
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What about adding your peptides on the other side of the bilayer?
If you are using pbc they should still be able to move over and interact with the LPS. Just be sure to put a good bit of space between them and the inner leaflet.
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Hello.
I am trying to use gromacs to start an MD simulation of a protein-ligand complex.
I was following the recommended tutorial http://www.mdtutorials.com/gmx/complex/index.html
- I did the system preparation, minimization and heating.
- I am trying to start an equilibrium as a continuation from the heating, getting two errors: FATAL ERROR or INCONSISTENCY INPUT.
_____________________________________________________________________________
---> options in my step07_npt.mdp file:
[...]
continuation = yes ; continuing from NVT
[...]
gen_vel = no ; velocity generation off after NVT
_____________________________________________________________________________
running previous grompp to generate tpr.
_____________________________________________________________________________
$ gmx_mpi grompp -f par/mdp/step07a_npt.mdp
-c str/complex/step06d_nvt_ann_LONG.gro
-r str/complex/step06d_nvt_ann_LONG.gro
-p top/top/test.top
-t bin/cpt/step06d_nvt_ann_LONG.cpt
-n str/idx/step06c_complex.ndx
-o bin/tpr/step07a_npt.tpr
-pp top/top/step07a_npt_POSRE.top
-po run/log/mdout/step07a_npt_mdout.mdp
I tried different options:
[ step06_nvt is previous heating step - step07_npt is equilibrium step]
1. try running continuation from heating using heating output files:
_____________________________________________________________________________
$ gmx_mpi mdrun -v -s bin/tpr/step07a_npt.tpr
-cpi bin/cpt/step06d_nvt_ann_LONG.cpt
-o bin/trj/step06d_nvt_ann_LONG.trr
-x bin/trj/step06d_nvt_ann_LONG.xtc
-cpo bin/cpt/step07a_npt.cpt -cpt 60
-c str/complex/step07a_npt.gro
-e bin/edr/step06d_nvt_ann_LONG.edr
-g run/log/mdlog/step06_nvt_ann_LONG.log
ERROR:
>
Inconsistency in user input:
Some output files listed in the checkpoint file
bin/cpt/step06d_nvt_ann_LONG.cpt are not present or not named as the output
files by the current program:)
Expected output files that are present:
Expected output files that are not present or named differently:
run/log/mdlog/step06_nvt_ann_LONG.log
bin/trj/step06d_nvt_ann_LONG.xtc
bin/edr/step06d_nvt_ann_LONG.edr
To keep your simulation files safe, this simulation will not restart. Either
name your output files exactly the same as the previous simulation part (e.g.
with -deffnm or explicit naming), or make sure all the output files are
present (e.g. run from the same directory as the previous simulation part), or
instruct mdrun to write new output files with mdrun -noappend. In the last
case, you will not be able to use appending in future for this simulation.
_____________________________________________________________________________
2. running with noappend option and using new file names.
_____________________________________________________________________________
$ gmx_mpi mdrun -v -s bin/tpr/step07a_npt.tpr
-cpi bin/cpt/step06d_nvt_ann_LONG.cpt
-o bin/trj/step07a_npt.trr
-x bin/trj/step07a_npt.xtc
-cpo bin/cpt/step07a_npt.cpt -cpt 60
-c str/complex/step07a_npt.gro
-e bin/edr/step07a_npt.edr
-g run/log/mdlog/step07a_npt.log
-noappend
ERROR:
>
Fatal error:
Cannot change a simulation algorithm during a checkpoint restart. Perhaps you
should make a new .tpr with grompp -f new.mdp -t
bin/cpt/step06d_nvt_ann_LONG.cpt
_____________________________________________________________________________
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My understanding is that you produced a new binary (step07a_npt.tpr) from a new .mdp file (step07a_npt.mdp), and now you are trying to continue the previous nvt run (step06d_nvt.*0, right?
In that case this is wrong
$ gmx_mpi mdrun -v -s bin/tpr/step07a_npt.tpr
-cpi bin/cpt/step06d_nvt_ann_LONG.cpt
-o bin/trj/step06d_nvt_ann_LONG.trr
-x bin/trj/step06d_nvt_ann_LONG.xtc
-cpo bin/cpt/step07a_npt.cpt -cpt 60
-c str/complex/step07a_npt.gro
-e bin/edr/step06d_nvt_ann_LONG.edr
-g run/log/mdlog/step06_nvt_ann_LONG.log
You are using a NEW mdp file, and generated a NEW binary. The info from the previous state should be already inside the new binary, that's why in the preprocessor phase you wrote the flags -c, -r, and -t. Therefore this
$ gmx_mpi mdrun -v -s bin/tpr/step07a_npt.tpr
should do the work. Consider that -o, -x etc specify the OUTPUT options, not the input, therefore when you write
-x bin/trj/step06d_nvt_ann_LONG.xtc
you are telling mdrun to write your trajectory to that file, not to take from that file and continue it. The error you get in the first case is related to the fact that the -cpi option is a continuation from a checkpoint, which is going to search for some files to continue a given run. This is useful when a simulation crashes or when you want to make a simulation longer. For example, you run 100ns of something and would like to go to 150ns. Then you run gmx conver-tpr, you extend the tpr file time and continue from there (using -cpi flag, read https://manual.gromacs.org/documentation/current/user-guide/managing-simulations.html)
Here you got a new tpr, so you don't have to specify the -cpi flag.
Second error is similar. You are going from NVT to NpT, therefore you are now coupling the pressure. What mdrun is telling you is that it is not able to go on with the NVT phase because the tpr you are using (the step07) has something different from the state you are trying to continue (step06), most likely the barostat but something else as well for sure.
If you want to make the NVT longer you can go
gmx convert-tpr -s npt.tpr -extend TIME_YOU_WANT_TO_EXTEND_IN_PS
and then go
gmx mdrun -v -s npt.tpr -cpi npt.cpt
In this case you want a NpT, so a change in the binary, therefore you (rightly) compiled a new tpr (specifying the input status with -c/-r/-t flags) and can now just run the
gmx mdrun -v -s npt.tpr
Hope this is clear! :)
Nicola
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Hi,
I am a new user of ORCA. My initial calculations were successful but at this moment I am facing a problem to run a new calculation on my laptop. However, I can run calculation with the same input file on my older laptop.
Here is an example of my input file for the calculation on nitric oxide:
!RKS BP86 RI SV(P) SV/J TightSCF Opt
*xyz 0 2
N 0 0 0
O 0 0 1.2
*
Here is the error message mentioned at the bottom of the .out file:
ERROR : GSTEP Program returns an error
cannot continue with the optimization
COMMAND : orca_gstep NO.ginp.tmp
RETURN CODE : -1
I would appreciate your help.
Best regards,
Subrata
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This is due to the difference between the number of cores in the input and sbatch files.
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Molecular modeling softwares
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Biovia Discovary studio for QSAR and AutoDock Vina for molecular docking
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I am trying to create a similar diagram to this one attached below for my ligand. I ran a 100ns for the complex of ligand and protein. i am willing to consider interaction fractions of hydrophobic and h-bonds interactions only since my ligand is not charged, thus electrostatics are zeros.
now i was told i can calculate the nonbonding energy and vdw energy using the NAMDenergy plugin in vmd. so my files were in gromacs format. therefore, I converted them to dcd and psf by saving my trajectory in dcd format and using these two commands in vmd console to get the psf file
set all [atomselect top all]
$all writepsf XXXX.psf
unfortunately, i got this error from NAMDenergy plugin:
FATAL ERROR: Structure (psf) file is either in CHARMM format (with numbers for atoms types, the X-PLOR format using names is required) or the segment name field is empty.
when i checked the psf file it was already in xplor format and the segment name filed is there as well. so i don't know why it is giving me this error. here is a part of my psf file
PSF
1 !NTITLE
REMARKS VMD-generated NAMD/X-Plor PSF structure file
68834 !NATOM
1 1 GLU N N 0 14.007 0
2 1 GLU H1 H1 0 1.008 0
3 1 GLU H2 H2 0 1.008 0
4 1 GLU H3 H3 0 1.008 0
5 1 GLU CA CA 0 12.011 0
6 1 GLU HA HA 0 1.008 0
7 1 GLU CB CB 0 12.011 0
8 1 GLU HB1 HB1 0 1.008 0
9 1 GLU HB2 HB2 0 1.008 0
so the questions are:
1- how to solve this error so i can calculate the nonbonding and vdw energies
2- how to calculate the energy for hbonds so i can fractionate it as well
3- is there alternative way to calculate these energies or to create such graph?
thanks in advance
loay
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It should be possible to define groups of atoms (such as ligand, individual amino acid residues), store sums of all electrostatic and van der Waals interactions between groups of interest, and, after the simulation is finished, to calculate ensemble average. I would also plot the histograms to confirm that the distributions are normal.
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I want to model my system of fiber and matrix for my molecular dynamics simulation. What are the various Software available for modelling system?
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Hi,
there is large palete of MD software packages that can be used for your system. It depends if you want free software or you can buy one. Also depends if you want only the MD solver or also visualization capabilities.
Im familiar with following software packages:
GROMACS
- free
- widely used
BIOVIA Materials Studio
- not free
- user friendly
- with nice GUI
LAMMPS
- free
- widely used on clusters
Best regards,
Milan
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Hi,
In the previous questions I have successfully performed and analyzed the MD from two small molecules with Desmond/Maestro. However, I found that MD with Desmond cannot simulate the bond forming and breaking which is a crucial part in the design of our drug delivery system. MD can only gave me the simulation of weak forces.
To the best of limited my knowledge, I found two ways. 1. Reaxff reactive force field. 2. Quantum mechanics simulation (QM/MM).
I tried the Qsite (a tool of QM/MM in the maestro), but it did not gave out a trajectory file that can be visualized and analyze with MDanalysis. So, I turned to Reaxff. Now, I am trying to use Amber/Reaxff package to do the simulation. Right now, I faced some installation errors in Amber. I have sent the problem to the Amber mail list.
My main goal is to simulate the reaction between two molecules (the binding of the drug delivery agent and the target ligand) Both of them are small organic molecules.
My questions are:
1. How can I analyze and visualize the results (trajectory) from QM/MM?
2. After the simulation from the Amber/Reaxff, how can I analyze and visualize the results (trajectory)? I found some information stating that traditional MD viewer and analyzing tools cannot do the job. Can you suggest some software that I can dive into?
3. How to get the parameterization of the small organic molecules?
Is my approaches correct? Please, I really need your advices.
Thank you very much for your help!
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Shang-Wei Li : Your general approach of introducing QM into the simulations is correct. As you have noted, classical MD is not equipped to model the breaking and making of chemical bonds. You might also take a look at another approach that is described in the following reference:
Journal of Chemical Education • Vol. 83 No. 1 January 2006
They make use of a free program, "Molecular Workbench":
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Where the dim.exxxxx presented this as it content:
"cp: cannot stat 'DIMCAR' : No such file or directory - VASP"
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Thank you, Hadi Jabbar Alagealy I have already read through that resource but did not present a clear answer as to why the error message that I shared
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Hello.
which one have more hydrogenic bond,alpha helix or beta sheet?
iappreciate your comments.
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Here is the video on the topic that explains hydrogen bounding in Alpha helix https://youtu.be/wM06U0IAv5c
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I would like to study the apo form (lipid-free) of a protein that only has been crystallized with lipids. I want to explore if it is possible to generate with a molecular dynamic a reasonable structure, making subtraction of lipids in several steps until obtaining the apo form. Likewise, I don't know if, during the molecular dynamic trajectory, it is possible to disappear lipids. I am thinking of using programs like GROMACS, AMBER, etc.
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You need to remove lipid before MD simulation. You can not delete or add any atom/residue/molecule during and after MD simulation, as it will destroy your trajectory data.
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I want to start some chemical reaction calculations, but I need some basic reference to get started. Thank you in advance. Sincerely.
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When dealing with QM calculations on chemical reactions, one basic problem is thermochemistry. The evaluation of thermodynamic parameters allows a theoretical determination of enthalpy, free energy, and entropy variations associated with the reaction and hence reaction constant. If this is your goal, I suggest strongly this paper, available for Gaussian but whose concept can be easily generalised:
I hope this may be a good starting point (as it was for me!).
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My ligand has a quaternized pyridine ring in it's structure, but after editing, when I export it from AutoDock Tools as a .pdbqt file and open it in Discovery Studio Visualizer, the structure of my ligand changes and nitrogen appears to no longer be quaternized (a C=N double bond is lost, the +1 charge on the nitrogen is lost, there are now only 2 double bonds in the ring). The rest of the ligand stays as is, the problem appears to be happening only to the quaternized nitrogen. Is there a way to fix this from happening?
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Yes. The programs/subroutines that do the calculations do this based on the properties of the individual atoms, independent of the bond model. There is no localised +1 charge on the nitrogen, which you would have in the protonated nitrogen, but the lone electron pair of the nitrogen is part of the aromatic pi electron system.
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We know that the brain sends and directs meaningful messages to control the patient's cells.
as we know, The brain is affected by factors such as diseases And we know that the brain also controls other organs of the body.nevertheless,Damage to the CELLS is visible on eeg?
Is Cancer Effective In EEG?
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Stomach cancer is cancer that may affect any part of the stomach and extend to the esophagus or small intestine, and it causes the death of nearly one million people annually. It is more prevalent in Korea, Japan, England and South America. It is more prevalent among men than women. It is associated with eating too much salt, smoking, and also low intake of fruits and vegetables. Therefore, it is believed that its spread in countries such as Korea and Japan is due to the consumption of salted fish mainly by Koreans and Japanese, as well as the use of canned food and food preservatives. Mucosal colonization of H. pylori is believed to be the main risk factor in about 80% of stomach cancers
Stomach cancer is diagnosed through an endoscopic examination that allows a biopsy to be extracted from the affected tissue, and then analyzed to confirm the presence of a tumor. Dr. Riccardo Rosati, a specialist in gastroenterology at San Raffaele Hospital in Milan, says, "Before undergoing treatment, the patient needs to do a series of other ultrasound and other examinations to check the areas, glands and organs covered by the disease, in order to determine the degree of its progression.
As a researcher, I believe that stomach cancer cells do not send messages to the brain due to the lack of associated neurons
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Hello to All,
When converting a pdb. file (generated by Materials Studio) of polymer model(PE,PLA) into lammps data file by VMD topo tools, there's too many atom types in the output file(lammps data file). What could I do to reduce the atom types in lammps data file?
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You can also use the OpenBabel free software..It is easy to use. choose lmpdat for the output format.
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In Becke's B3LYP hybrid functional, Fock exchange is being mixed with Slater LSDA exchange (and then plus gradient correction), plus correlation expressions. But what LSDA exchange parametrization is used?
  • It appears to me that Becke in his DFT Thermochemistry I paper (J. Chem. Phys. 96, 2155 (1992)) uses the VWN parametrization, being the then modern alternative to the older Perdew-Zunger version.
  • Then in his Half-and-Half paper (J. Chem. Phys. 98, 1372 (1993)), he apparently switches to the then recent Perdew-Wang 1992 parametrization.
  • In his 3-parameter hybrid (DFT Thermochem III) paper (J. Chem. Phys. 98, 5648 (1993)) he seems to only comment on correlation being taken from the PW 1992 parametrization and not mention which LSDA version he uses for the exchange part, presumabely still the standard Slater exchange (E_X ~ int n_(alpha)^(4/3) + n_(beta)^(4/3) dr.
So which LSDA parametrization is used nowadays in B3LYP? Did people stick to the VWN version from Becke's initial paper or did they switch to the more modern PW version as Becke probably did? Or do different implementations in program packages use different versions?
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There are some references that might prove helpful:
Sholl. D.S. and Steckel, J.A., Density Functional Theory: A Practical Introduction, Wiley, 2009. Page 218.
Here some parameterizations are specifically mentioned.
(3) The Bretonnet article is attached.
I hope you may find something of these to be of use.
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How is the value for the spring constant (force/time units) and velocity (distance/time units) determined for any Steered Molecular Dynamics simulation? Is there an exact science behind it or is it more about referring previous published literature and using the values from there?
I am pretty new to both MD Simulations and SMD, so any insight is appreciated.
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I would say that it largely depends on what you want to do. For example, do you want to perturb the system or to drive a near-equilibrium transformation?
This being said, looking for previous works done in the same field is quite mandatory to see what has been done, what constants have been used and so on. If you want to unfold a protein, you will need to use force constants large enough to actually unfold it, and not play a tug-of-war with the intra-protein forces of the system. On the other hand, if you want to drag a solute/permeant through a membrane/a protein channel/a nanotube/etc. you may want to not perturb/disrupt the bilayer, or you may want to sample the interaction along the protein channel therefore you need slow velocities to let the permeant interact with its surroundings.
Overall, apart from the limits intrinsic to the software you are using and to the artifact you can introduce, it greatly depends on the theory you are applying. Does it depend on the velocity/k constants? Are you sampling states which need equilibrium conditions, and therefore must perturb the system the least possible? Or does it depend on fast dragging with ensembles of out-of-equilibium trajectories? Does it depend on any approximation, like stiff-spring which maybe would work better with constraints rather than restraints? Or maybe are you trying to reproduce a pulling AFM experiment, and therefore can get some insights from the experimental work?
In a way, it is always a matter of trial and error and checking was has already been done.
Hope this helps,
Nicola
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Hi,
I'm working on one of the ORC protein that is usually found in a complex for the most part of the cell cycle: from G1 to the end of S faze. But it is present in the nucleus as a single molecule in G2. It structure is available in the PBD repository but only in the complex. Is there any approach you can take to model a protein like that out of the context of the complex it usually resides in?
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Thank you both for your answers. I hope in time I will have an opportunity to help you in the future as much as you have helped me.
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I am working on a ligand that is co-crystalized to parotein, but the ligand is missing some residues that makes it appear as if it was separated into two ligands!
what I need is to connect them into one to run molecular dynamics simulation, what is the best tool to do so, also what are the steps to make sure that it will be mostly accurate?
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Try Ligandscout or Maestro, Schrodinger.
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I want to parameterize a few molecules. I need of course torsional, dihedral angles, charges , etc.
What is the most popular program for that right now? I know that gaussian is quite popular, but it is not for free. I want to parametrize lipids: mgdg and dgdg in OPLS-AA force field and some other molecules in charmm force field. I need also something which has quite good tutorials because I want to learn that things.
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You can also use GAMESS
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I am currently performing coarse-grained MD simulations in LAMMPS using mW potential for water. I initialize the water model at 273K, equilibrate for 50ns followed by a quenching process from 273K to 200K at a rate of 0.5K/ns for a total of 146ns. At the end I observe what looks like a nucleated structure. But how can I be certain that homogeneous nucleation has indeed taken place?
Can a specific property be extracted from LAMMPS or any visualization technique be used to confirm that the structure has indeed nucleated?
Any insight is appreciated.
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Write a script to calculate the radial distribution function of your system along a predefined reaction coordinate between the interface and the buried atoms. Check the coordination number and the behavior of the RDF to get insights about nucleation.
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I would like to perform a computational study of how solvatochromism is affected by viscosity of the medium.
I usually use Gaussian as software for molecular modelling, and my question is whether is it possible to include the viscosity in a Gaussian calculation for a UV-Vis spectrum or if there is a software that could do this.
Does anyone know of a software or approach that could help me with this study???
Thanks in advance
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This Question which interested me a lot, thank you very much
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If I have to draw a FCC 111 surface, am assuming the miller indices are: [1,0,0], [0,1,0] and [0,0,1]
How can miller indices be determined for orientations like FCC 211 or FCC 110 etc.?
I am trying to build atomic models through ASE Python, so any help in that regard will be greatly appreciated.
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I am trying to calculate the RMSF plots for some trajectories that have periodic boundary conditions. Unfortunately, I am unable to do this in GROMACS due to installation issues, so I have to use the Python-based MDanalysis instead. During my trajectories, the proteins do end up partially crossing the boundaries. Is there a way to calculate RMSF under these constraints? How might I do this?
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Dear colleagues, I have some experience with MD for studies of drug-target interactions, mainly NAMD and Amber. For quite some time, I wanted to try studying the binding/unbinding process of the drug to/from its target. I was thinking of using Steered MD, is it a good approach? I have seen some tutorials for SMD to “unbind” the ligand but none such tutorial to “bind” a potential ligand to its target. Is it even doable this way? Have you come across some tutorials for this?
What should I consider for such simulations, e.g. should the protein be restrained to limit its movement and inherently the SMD vector? should I use temp/pressure control?
Thank you for your responses.
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Starting with a ligand bound complex and probing the unbinding path should require no restrain, but if you start with a dissociated state, restrain is necessary. Otherwise, the ligand would possibly never find its binding site.
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Upon equilibrating an Ice Ih structure at 250K and using write_data command for obtaining the end structure post-equilibration, I found that it does not contain the required bond information that was present in the initial geometry file.
Also, if the previous bond info from the initial geometry file is copied over to this new post-equilibrated data file, the bonds look incorrect on visualization and LAMMPS gives an error stating "Inconsistent image flags" and "bond/angle/dihedral extent > half of periodic box length"
Does anyone know how to write or extract the bond info post-equilibration successfully in LAMMPS? Attached are the initial (1hx20.lmp) and equilibrated (data.equibicev2) files pertaining to the problem.
Any insight is appreciated.
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The LAMMPS trajectory does not contain the bond topology information. The psf file should be made on your initial configuration. If you are not using create and delete bond then pre and post equlibrated structure will sure find the correct topology from the psf file.
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Hi, I've been an experimentalist throughout my career and I want to add to my knowledge and expertise in Materials Science by delving into computation, modeling and simulation. However, I'm very confused about where to begin as it appears that field of modeling and simulation is quite vast and expansive. If I had to choose a starting material type, I'd say composites and modeling of failure modes of composites. Can anyone guide me on where to begin? I'm a complete novice when it comes to anything computational. Where do I begin, if I'm starting from scratch.
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These concerns MD simulations using Gromacs. Suggestions involving Amber/LAMMPS/etc., aren't going to be of any help.
I'm looking for strategies that might save me on lines of code.
As I am sure you are aware there are several strategies for relaxing a protein in a bilayer. For example, a population approach is placing position restraints on the backbone which are decreased between simulations whilst preserving velocities. Finally, all position restraints are removed and the simulation is left to run unrestrained. This is useful for a sequential simulation->simulation->....->simulation, where the velocities are preserved.
My concern is when I want to run e.g., 4 identical simulations, each with different starting velocities. That way I can cover more phase space and I can calculate a metric of uncertainty when I'm measuring a property. This is very easy to do by hand. Each of the four production runs will use preserved velocities for a separate set of equilibration runs i.e.,
Sim1: eq_run -> eq_run -> eq_run -> production_run
Sim2: eq_run -> eq_run -> eq_run -> production_run
Sim3: eq_run -> eq_run -> eq_run -> production_run
Sim4: eq_run -> eq_run -> eq_run -> production_run
But this becomes very difficult when I have e.g., 100 models to build and run. That's 4*100 + 4*100 + 4*100 + 4*100 simulations with all corresponding files. Ultimately, I am looking for a strategy where I can introduce a bias or short external influence so that each model shares the same equilibration runs before spawning 4 unique production runs but without destroying the velocities preserved from the equilibration simulations i.e.,
Sim1,2,3,4: eq_run -> eq_run -> eq_run -> production_run1/2/3/4
I have a feeling, something like replica-exchange might work? Introducing 4 different temperature that gradually relaxes back to what they should be over a very short period of time just so that the preserved velocities diverge.
Thoughts are most welcome.
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The strategy you're trying to find is self contradicting. You try to "cover more phase space" by introducing some kind of perturbation from the same point in phase space (end of equ runs). But if you try to preserve the exact state at end of equ runs, it's limiting your exploration of the phase space.
If the only reason of asking this kind of strategy is file management, I'd suggest you to use scripts to do that. Trying to explore more phase space by starting from the same state point doesn't make sense, considering after the "perturbation", you still have to wait for your system to reach equilibrium again. It's equivalent to starting from, say different initial velocities.
Having said that, simulated annealing seems a good candidate of the "perturbation". Just raise/lower the temperature to some random temperature. Again, you have to wait the system to reach equilibrium after restoring your target temperature.
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Hi to all, I'have to perform a docking in haddock. i have determined the most susceptible residues upon ligand binding by chemical shift perturbation. now i need to determine which among the are active resiues, and i need to calculate which of them have a >=50% solvent accessibility.
I know that NACCESS is a very reliable program to do that, but i have to send a mail (a normal mail) to get the code for decrypt the rar file.
Is there anyone that could give me that code? or is there any software as reliable as NACCESS capable of perform that calculations?
Thank u
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You can use this very user friendly web server for ASA calculation http://cib.cf.ocha.ac.jp/bitool/ASA/
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Applications in Drug Design and Molecular Modeling
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RDKit is a popular Open-Source Cheminformatics Software.
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It is well known that for a closed shell (all electrons are paired up) molecule, the HOMO-LUMO gap is related to its stability. However, I often see that the same argument is used for open-shell systems (Unrestricted calculation). In such a case, the authors consider energies of both alpha and beta spin orbitals, and the orbital with the highest energy is considered as SOMO. Similarly, the LUMO is decided among both alpha and beta, and the respective gap is considered as the SOMO-LUMO gap. Next, the authors discuss the stability of the system based on that value.
However, to the best of my understanding, for an unrestricted calculation, three SOMO-LUMO gaps can be calculated (1) Gap between alpha spin HOMO and alpha spin LUMO (2) Gap between beta spin HOMO and beta spin LUMO, and (3). The method I mentioned above (considering both alpha and beta).
So, my questions are the following,
a) Is it technically correct to relate stability with the SOMO-LUMO gap calculated by method 3 for an open-shell system? Is it even possible to draw such a relation? How correct are such value and such correlation? If yes, then is there any reason why we are ignoring the other two gaps?
b) Are the gaps obtained by an unrestricted calculation have any practical significance at all (As argued here: https://joaquinbarroso.com/2018/09/27/the-homo-lumo-gap-in-open-shell-calculations-meaningful-or-meaningless/)
Any insightful response will be welcome. Thank you in advance.
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The precise role of UV exposure time in controlling the orbital transition energies, optical and electrical parameters of thermally vacuum evaporated Se 50 Te 50 thin film
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I am not sure whether crystalexplorer is corrupted or not? I have tried to open .cif file downloaded the Crystallography Open Database, but still can't open it ? I hereby attach this file and please do check it. if it works well, please advise how I can perform hirshfeld surface analysis?
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Probably the latest version does not match with the hardware of your system.
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I have a pre-equilibrated Ice 1h structure at 250K. I also have an Aluminium substrate which is 10 Angstroms below it within a simulation box. With the potential defined for structures (TIP4P for Ice, EAM for Al, LJ for cross-interactions), how can I bring both structures together to form an adhesive bond at the interface?
In terms of LAMMPS commands, how can this be achieved? Any insight is appreciated.
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Abhay Vincent in your model the LJ cross-interactions are the only ones between ice and Al, and the adhesion will be a consequence of them. Those are nonbonded pair interactions, so you don't need to create anything in terms of topology.
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Is it possible to transfer heat from one group to another using simulated aneeling technique in the Gromacs software? I would like to transfer heat from a gold nanoparticle (group 1 from 310 to 350 K) into a dppc bilayer (group 2) that is at 310 K. How can I do it using a NPT ensemble in a molecular dynamics?
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Maybe you have to apply a linear or non-linear temperature increments and decrements for each group. AMBER package can do it, but you can make a script for gromacs, perhaps it is already implemented in last version of gromacs, I dont know. Also, you can try with three groups: nanoparticle (group-1), polymers in the first and/or second shells (group-2) and remained polymers (group-3). Thus, you will only modify the temprature in group1 and group2.
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