Ligand - Science topic

Hello, in my experience, you must first obtain a 3D structure either de novo or by sequence construction of your peptide. I´ve tried using PepFOLD3 for structural prediction. Afterwards, you must decide which docking software you want to use, I´m familiar with Autodock and Autodock Vina, being both capable to dock small peptides, take in count that in this case, the definition of the charges in the ligands is relevant for the docking calculation. Other than that, preparation is pretty much straight forward and similar to that of the classic small ligands for docking.

Hope it helps

Some factors to consider when comparing results from different methods:

1. Methodological differences: Docking and free energy calculations using ONIOM are based on different underlying principles and assumptions. Docking typically predicts the binding pose and affinity of a ligand to a receptor based on scoring functions and geometric complementarity. ONIOM calculations, on the other hand, use a combination of quantum mechanical (QM) and molecular mechanics (MM) methods to describe the electronic structure and energetics of a system. These differences in approach can lead to variations in the absolute values obtained.

2. Relative comparisons: As you correctly mentioned, the primary utility of comparing results from different methods lies in their relative comparisons. The goal is to assess the relative binding affinities or trends between different ligands or receptor-ligand complexes within the same method. For example, if docking experiments consistently rank a set of ligands in a certain order of affinity, and the ONIOM calculations show a similar trend, it provides confidence in the relative comparison between ligands using both methods.

3. Calibration and validation: To establish a meaningful correlation between different methods, it is often necessary to calibrate and validate the results against experimental data or reference datasets. This can involve benchmarking a set of compounds with known binding affinities and comparing the relative rankings obtained from different methods. Calibration can help adjust the scaling factors or parameters to improve the agreement between methods and experimental results.

4. Limitations and assumptions: It's important to consider the limitations and assumptions of each method. Docking, for instance, may not fully capture the precise energetics of the binding process, while ONIOM calculations may have limitations in terms of the chosen level of theory, basis set, or representation of the system. Understanding these limitations can guide the interpretation and comparison of results.

Hope it helps:credit AI

Here are a few popular docking tools that allow for multiple-ligand docking:

When this type of error occurs to me, I prepare the ligand file again using the openbabel software, without making any modifications... just rewriting it.

example:

obabel -ipdbqt lig.pdbqt -opdbqt -Olig.pdbqt

Typically, such a solution works.

Citra Hasanah Please, send us a message here (https://groups.google.com/g/gmx_mmpbsa) with the error information and we'll help you through the installation process

To analyze and validate docking procedure for a protein with no co-crystallized ligand, you need to find the key residue in the active site or binding site of the protein. After choosing the best pose based on docking score and interactions with key residue, you can perform molecular dynamics to validate the docking procedure.

There can be 2-3 reasons for this. The main reason might be the gridbox not matching with the configuration file.

1. The parameters(center_x, center_y, center_z) in the config file not matching the coordinates set in the grid box - For this you can open the grid.txt file you had prepared and copy the last lines as dimensions for x, y and z in the config file . This will ensure that both the coordinates are matching.

2. Size of parameters in the config file might be incorrect from what is specified by you in the grid - We can set it correctly by opening the grid file and then setting the size in the config file.

Let me know if that works !

Pls don't hesitate to ping me if the problem persists :)

I am also having same issues as you. Trying several concentrations of both protein-protein and protein-ligand but cannot get that full saturation.

What is the ideal concentration that may give this saturation?

Thank you Waseem Ahmad Ansari and Soykan Agar for your answers. But I could not solve the problem. Can you kindly suggest how to choose the ligand as a static molecule?

"skipped empty mol2 file" typically indicates that the program encountered an issue with the input files during the generation of the PDB file in CHARMM-GUI Solution Builder. Reasons and troubleshooting steps to try:

1. Check the input files: Ensure that the input files (.mol2 files) are not empty and contain valid molecular structure information. You can open the .mol2 files with a text editor to verify their contents.

2. Verify the file formats: Confirm that the .mol2 files are in the correct format and adhere to the specifications required by CHARMM-GUI Solution Builder. The files should include the necessary sections such as "@<TRIPOS>MOLECULE" and "@<TRIPOS>ATOM" with appropriate molecular and atom information.

3. Validate the input files: If you suspect any issues with the .mol2 files, you can try validating them using external tools or online validators. There are various online resources available that can check the integrity and correctness of the .mol2 file format.

4. Regenerate the .mol2 files: If the input .mol2 files are generated using external tools like OpenBabel or sort_mol2_bonds.pl, try regenerating them using different settings or approaches. It's possible that the previous generation process introduced some errors or inconsistencies in the files.

5. Check for any special characters or file encoding issues: Ensure that there are no special characters or unexpected file encoding issues present in the .mol2 files. Special characters or incompatible encodings can cause parsing errors during the PDB generation process.

6. Contact CHARMM-GUI support: If the issue persists despite trying the above steps, it may be helpful to reach out to the support team of CHARMM-GUI. They can provide specific guidance or troubleshoot any potential bugs or technical issues related to the Solution Builder module.

Hope it helps

Dear Nathan Soper

What if your protein has two binding sites (non-identical)? If so, you do not see the full saturation yet. That would explain the result. Then, you should continue the titration to the higher ratio values.

Regards

The numbers for the concentrations in your text do not agree with those observed in the figure.

Since the ligand is a dimer, would the dimer bind one single molecule of the other protein, or two?

When dealing with dimeric proteins, I always recommend, if possible, to perform the assay with the dimeric protein in the cell, to avoid additional problems.

If you have information about that interaction in a certain experimental scheme, I would recommend following the same experimental scheme. After you reproduce the known behavior, then you can explore other possibilities.

Regarding the c-value: c-value is not a goal in itself. Forget about pursuing a high enough c-value guaranteeing a sigmoidal isotherm. Very often it is not achievable (low affinity), and very often it is not necessary for an experiment to be considered good (there are many other features people pay little attention that are even more important than the c-value).

This error typically occurs when the atom names provided in the pdb file that you are using to generate the topology do not match the (unique) atom names contained in the off file. As a consequence, tleap is not able to assign to the atoms in the pdb the correct atom type, connectivity, and partial charges. To solve the problem, just rename the pdb atoms according to the naming that appears in the "unit.atoms table" section of the off file. The same error may arise also if there is a mismatch between the three-letter residue name between pdb and off file. The solution in that case is to change the pdb residue name to the one that appears in the "index array str" section of the off file.

Hi Kwasi Kantanka Safo ,

This question has been answered before. You can check https://www.researchgate.net/post/How-can-I-parametrize-an-atom-for-Autodock-Tools

Yes, it is possible to present docking results without additional support from the results of molecular dynamics (MD) simulations. However, increasingly, reviewers of manuscripts under consideration for publication in journals are requesting MD simulations to help bolster conclusions derived from docking results. It is, of course, also helpful (and often necessary) to have experimental results pertaining to the binding of ligands to macromolecular targets and to use docking and/or MD simulations to provide explanations for the observed experimental results.

Dear Vinh,

some more information:

1. The colour of Cu(II) complexes in solution is ranging from green to blue. Cu(I) complexes are usually colourless (simple to see).

2. The Cu(II) +e- = Cu(I) redox potential is sensitive on the ligands that coordinate to Cu(II) or Cu(I).

3. OH- is a ligand in aqueous solution! OH- is probably not a strong ligand, but it can change the charge of the dissolved Cu(II) complex-species from [Cu(H2O)6]2+ in acidic to neutral to [Cu(OH)(H2O)5]+ in slightly basic and to [Cu(OH)3(H2O)6]- in strongly basic solution (see also next point). This change of charge WILL change the redox potential.

4. When adding OH- to a Cu(II) solution, you should observe the precipitation of Cu(OH)2 (lightblue). This means that the complex [Cu(OH)2(H2O)4] is poorly (or not) soluble. On excess OH- the solid Cu(OH)2 re-dissolves forming the soluble complex [Cu(OH)3(H2O)3]- (as Kyle pointed out).

Unfortunately, you did not tell us about the other ligands. So, my answer is very general. Next, please provide all necessary information.

Best,

AXEL

Arkajyoti Banerjee

My version of YASARA (YASARA-Structure) requires a paid license. However, the price is very reasonable compared to other comparable software such as Schrodinger or CCG MOE. In addition, the licensing policies are extremely liberal. For example, I can run as many simultaneous instances as I wish, on the same computer and/or on multiple computers with the same or different operating systems (it runs on Linux, Mac, Windows, and Android).

There is also a free "viewer" version of YASARA. I have not tried the free version, and I do not know its capabiliites, but I suspect that it would not include docking.

I am glad to know that you got good results with classical AutoDock 4. Sometimes, it works out that AutoDock 4 gives better results than Vina. It depends in part on the particular receptor-ligand system. Standard AutoDock 4 is slower than Vina, although now there is an accelerated version, AutoDock-GPU, than runs on OpenCL or CUDA to achieve very fast speeds.

Here are some considerations:

Docking Software: Different molecular docking software packages handle hydrogen atoms differently. Some software, like AutoDock, do not require users to add hydrogen atoms to the ligand, as they can predict hydrogen positions during the docking process. Others, like AutoDock Vina, rely on hydrogen atoms being present in the ligand.

Ligand Preparation: If your ligand structure lacks hydrogen atoms, some docking programs may not be able to accurately predict interactions involving hydrogen bonds. In such cases, you may need to add hydrogen atoms to the ligand using molecular editing software.

Research Goals: The decision to add hydrogen atoms to the ligand may also depend on your research goals. If you want to study hydrogen bonding interactions between the ligand and the receptor, it's essential to have accurate hydrogen positions.

Ligand Flexibility: If your ligand is flexible and can form hydrogen bonds with the receptor, accurate hydrogen positions become more critical. In rigid ligand docking, where ligands are considered to be unchanging, this may be less of a concern.

Hydrogen Bonding: Hydrogen bonds play a crucial role in molecular recognition. Accurate modeling of hydrogen bonds can significantly impact the quality of your docking results.

Here are some factors that can contribute to differences in docking results:

Software and Versions: Different docking software packages may use distinct algorithms and scoring functions. Even updates to the same software can lead to differences in results.

Scoring Functions: The scoring functions used to evaluate the binding affinity of ligands to the protein can vary between software and versions. Different scoring functions may prioritize different types of interactions (e.g., hydrogen bonds, hydrophobic interactions) or use different energy terms.

Ligand and Protein Preparation: The way ligands and proteins are prepared for docking, including the addition of hydrogen atoms, assignment of charges, and optimization of structures, can affect the results.

Grid Settings: The definition of the docking grid or search space can have an impact. Slight variations in grid dimensions and placement can yield different results.

Conformational Flexibility: The treatment of ligand and protein flexibility can also influence results. Some docking programs allow flexible ligands or proteins, while others keep them rigid.

Optimization: As you mentioned, optimization of ligands can significantly affect results. Different optimization methods and parameters can lead to variations.

Parameter Settings: Docking programs have numerous parameters and settings that can be adjusted. Small changes in these parameters can lead to differences in results.

Initial Position: The initial position of the ligand within the binding site can also influence the outcome. Docking software often performs multiple runs with different initial positions.

Hi, did you remove the PBC and align the structure to that of reference? What group did you select while creating RMSD? ca, backbone etc.

If in VMD, you structure seems intact, right? then there might be significant difference between your simulation and reference structure.

You can create RMSD between first structure in trajectory with the rest of the frames in simulation to see what is going on in your simulation.

Dear Edward Francisco Méndez Otálvaro , thanks a lot for your kind response. I think it does make sense in that way,

Best wishes

Marlet

Hello Smruti,

I had the same problem and I solved it by updating the "Configuration" TAB

After I did that, it seems all the plugins need it for each docking method uploaded into "DockingPie".

Please try that

Please can you talk us through one of the sensorgrams (e.g. Cy 25). What were the injected solutions from left to right.

Hi Mohd Sufiyan Ansari ,

I noticed that you named your folder "Project Docking" which contained a space between the word.

Therefore, rom your screenshot, it stated that it can't find or open Grid Parameter File "C:/Project" means it reads your folder as Project instead of Project Docking.

My suggestion is to remove the space in your folder name (ProjectDocking). restart ADT, and make sure to set your folder as the startup directory (this is essential whenever using AutoDock or AutoDockTool in Windows).

Hope this help. All the best.

Thank u. I will try doing this

Please start a new topic and do not ask a new question in an existing topic.

Amanpreet Kaur Thank you for your information. Could you provide a reference for free-binding protein (-8 kcal/mol), please? I will drive into it.

All the best,

Ramkumar Katturajan Hicham Mechqoq sir will you please tell me how to do merging of files

With individual dock parameter files of the inhibitor molecules, substrate’s dpf was merged into one single file to run MLSD simulation??

Please go through this for some help.

Sethupathi Raj S Did you get any procedures?

Thank Ayaz Anwar & Pawan Kumar for your inputs

Ayesha Fatima, Can you share the structure files so that I can try them on my end?

You can use this split_SDF.py python package to spilt your SDF files into smaller chunks

MOE is also a very reliable software for protein-ligand docking, I've used it several times and I use Schrodinger too. So u can use it if you need an alternative to Schrodinger

there was probably an error in defining the protein and ligand molecules. You can try to check the structure manually on Notepad for errors

You're welcome Citra Hasanah. You should be careful when choosing a docking solution pose, and try to stay away from poses that exhibit clashes. Nevertheless, depending on the case you might be force to choose a pose that has clashes.

The answer to the second question is exactly what you assumed. As the ligand's atoms are having clashes with the protein's atoms, the ligand undergoes orientation changes to try to reach one that is favorable (i.e., does not have clashes and establishes favorable interactions with the protein). Moreover, this would result in a ligand RMSd graph with high values. Concerning the backbone RMSd, this means that the clashes probably do not involve backbone atoms. Thus, the protein's backbone is stable (i.e., does not deviate significantly from the starting structure).

I agree with Hüseyin Besir that ELISA is not an appropriate method for measuring the Kd (equilibrium dissociation constant) of an interaction because it is not an equilibrium method. That is because of the washing steps required to remove unbound components.

The thermogram shows a huge heat effect, very likely stemming from DMSO dilution. It is not enough performing the control experiment and then subtracting it. You will be subtracting large quantities and the residual amounts may be meaningless.

Imagine you have a scale which is not well adjusted having two unbalanced arms and, to get it even, you have to put a 1 kg weight in one side. Now, you want to detect a 1 g weight placed on any arm. Will you be able to detect that small weight?

I recommend you to follow the suggestions provided by Verna Frasca

Your box size was insufficient. Increase the size of your box.

Asma Iqbal nicely copied from chatgpt. being a researcher please provide authenticated answers don't just copy-paste and spread misinformation.

Hi,

the best way is to do it already in the database. Create a database with all you ligands and then Compute -> Molecule -> Wash. Here you define protonation states and all the rest.

Dear Dr Gautum

"MD" typically refers to "Molecular Dynamics," a computational simulation method used to study the behavior of atoms and molecules over time. The amount of time required for a molecular dynamics simulation is highly dependent on several factors, including the complexity of the system being studied, the desired level of accuracy, the computational resources available, and the specific simulation parameters being used.

The time step used in a molecular dynamics simulation is usually in the range of femtoseconds (10^-15 seconds) to picoseconds (10^-12 seconds). This time step determines how often the simulation calculates the forces and updates the positions and velocities of the atoms in the system. The total simulation time is then a product of the number of time steps and the time step size.

For example, if you are simulating a system for 1 nanosecond (10^-9 seconds) with a time step of 1 femtosecond, you would need 1,000,000 time steps to cover that time span.

Keep in mind that the length of a simulation doesn't directly correlate with the accuracy of the results. Longer simulations can provide more statistically significant data, but the choice of simulation parameters and the quality of the force field used (if applicable) are also crucial factors in determining the reliability of the results.

Additionally, the computational resources available play a significant role in how quickly a simulation can be performed. More powerful hardware can complete simulations faster. Some simulations might take hours, while others could take days, weeks, or even longer.

In summary, there is no fixed answer to how many nanoseconds are required for a molecular dynamics simulation, as it depends on various factors. Scientists and researchers often perform preliminary tests to determine an appropriate simulation length based on their specific research goals and available resources.

Hello Piyush. I am not able to completely understand your problem. Did you download a protein with an ion "nd" that you want to re-dock with using pyrx? Or did you separately downloaded the ion file and want to perform docking with the unbound protein?

Chandni Pathak

Save your docking complex as a PDB file. Open the file in a text editor (not a word processor) such as gedit for linux or Notepad++ for Windows. Scroll down near the end of the file to the "HETATM" section and look at the atom names for the atoms in the ligand. Do the same with the PDB file of the X-ray structure of the complex. The names of the corresponding atoms in the ligand in the docking complex and the ligand in the X-ray structure need to be the same for doing an RMSD calculation. To help with recognizing the atoms in the ligand, you could open the docking ligand and the X-ray ligand in a molecular viewer. You can manually edit the ligand atoms in one of your PDB files using a text editor so that the corresponding ligand atoms have the same atom names. Then save the file as a PDB file. If all goes well, you can then align the two PDB structures in a molecular viewer and carry out the RMSD calculation. I hope this helps. Good luck!

-- RJR

Ajit Kumar Singh I am using CHARMM27 forcefield.

Zahra Rajabi

Assalam o alikum wa rahmatullahi wa barkatuhu

In Gaussian, the energy minimization in the mechanics method by applying UFF, Dreiding, and Amber force field. If you want to minimize the structure so you have to go through Biovia Discovery studio and apply CHarmm force field easily.

You would be right, the cyclodextrin is not meant to be a typical receptor but I was wondering if the autodock software by any chance could read it as such. The beta cyclodextrin is used to encapsulate other hydrophobic substances like drugs with such properties. That’s why I was asking this question. If I find anything I’ll let you know too. Thank you for your response either way I appreciate it.

Hello Matthew,

Thank you very much for your reply. I thought about the potential change in pI, especially because when I tried to purify them in the first place I thought they were not binding the resin of the Ion exchange column.

I am running the PrDOS now... Thanks for the idea. The M346 is buried in the protein so the mutations can lead indeed to a change in the pattern of intramolecular interactions. However, valine and threonine are very different amino acids. I find strange that regardless the mutation, they both cause the same effect. So I was thinking that the lack of methionine -and the intramolecular interaction of methionine with the surrounding residues - might be the cause. What do you think?

Cheers!

To identify major and minor groove binding in the case of molecular docking of A-DNA with a ligand/complex, you can analyze the groove binding using PyMOL or Discovery Studio 2021 Client software. Here's a general approach you can follow:

Using PyMOL:

Using Discovery Studio 2021 Client software:

Remember, the specific steps and features available may vary slightly depending on the version and capabilities of the software you are using.

You can use PLIP (https://plip-tool.biotec.tu-dresden.de/plip-web/plip/index) to get details regarding non-bonded interactions between two macro molecules. Alternatively you can use the native software tools to find out about such interactions.

Frederic Vellieux , after defining the receptor and ligand molecule in the analysis and clicking on ligand interactions, you can see the option in middle bottom the program which will open a dialog box upwards (screenshot attached) then you can click on "non-bond" to get the table for the information about the interactions (screenshot # 2). Hope this helps.

the ligand bind but not inside the grid box. I think I find out why it happened.

If you just want to group the files into a single .pdbqt just

cat *.pdbqt > group.pdbqt

Alireza Mohebbi Thank you for the idea, it helps. I've changed the chain ID using Pymol before docking process.

As you can see in the supplementary material of the paper you cited, the method has been implemented in AMBER 20.

Thank you sir

it is very easy to make this. Please read my articles. You can find all of them from my RG profile.

I have python 3.5.2, networkx 2.3 and numpy-1.25.0 all installed, the error persists, now i get the message

File "cgenff_charmm2gmx_py3_nx2.py", line 53, in <module>

import numpy as np

ImportError: No module named 'numpy'

Check the file .../charmm36.ff/ions.rtp to find out the exact residue name of copper ion.

Hello

I guess he wants the MM-GBSA analysis. You can use the gmx_MMPBSA for the same.

Regards

Naphtol green b is the sodium salt of naohtol green y. The coordination is supposed to be performed by th N in the NO substituent and the deprotonated phenol function. Charge is zero, multiplicity depends on whether Fe(iii) is high-spin or low-spin so either 2 or 6

Hello Rubem, thank you for answering my question. However i tried the method that you pointed out and failed to make work, error message "NameError: name 'rms_cur' is not defined" pops out. I apologise for the inconvinience but can you help me with help me further?

By "linker" I assume you mean "ligand"?

Assuming that's what you meant, I did separate the two files but encountered errors when I tried to generate the topology of the ligand because of incorrect bond order.

That is precisely why I posed my question here. If someone can tell me how I can correct the bond orders post-docking, I will then be able to generate the necessary topologies and continue with the molecular dynamics simulations following the standard protocols.

The relationship between ligand size and binding affinity in silico docking can be complex and depends on several factors. In general, larger ligands are more likely to interact favorably with the binding site due to the greater contact area and flexibility. However, the size of the binder can also lead to steric challenges and difficulty in fitting. Binding affinity depends not only on size, but also on the chemical composition and properties of the ligand. Each system must be analyzed individually, considering other factors, such as physical-chemical properties and characteristics of the binding site.