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12

You can analyze your docking results in two ways. First way is looking for the score function your program uses. For some score functions, lower value indicates better interactions and for others, higher values indicate better interactions. Also,, look for the decomposition of the score. Normally, the score is composed by different type of interaction/...


11

The main requirement is to have structures files with good resolution. According to RSCB PDB documentation: Resolution is a measure of the quality of the data that has been collected on the crystal containing the protein or nucleic acid. The figure bellow is an example of how the resolution indicates the quality of the structure (linked from original ...


10

CDOCKER CDOCKER is docking program developed by the Brooks Lab and it works with CHARMM. CHARMM does have a free version named charmm. The difference is no DOMDEC or GPU high performance modules. Pros: Rigid and flexible receptors, highly customizable Cons: Need to get free charmm, creating scripts can sometimes be laborious, no high performance GPU modules ...


8

H++ H++ is a web service that permits to protonate your macromolecules using using different pH conditions. From its site: H++ is an automated system that computes pK values of ionizable groups in macromolecules and adds missing hydrogen atoms according to the specified pH of the environment. Given a (PDB) structure file on input, H++ outputs the completed ...


8

HADDOCK HADDOCK is both a web service and a standalone code. From the web server: HADDOCK (High Ambiguity Driven protein-protein DOCKing) is an information-driven flexible docking approach for the modeling of biomolecular complexes. HADDOCK distinguishes itself from ab-initio docking methods in the fact that it encodes information from identified or ...


8

Changing the force field parameters is not a good/recommended approach. This is due to the high number of parameters you have to know. Many of them, you cannot obtain from experimental data. Instead, you will need high precision methods like Density Functional Theory, Hartree-Fock, pos Hartree-Fock or semi-empirical methods to calculate them for two, three ...


7

AUTODOCK VINA Autodock Vina (associated paper) is quite old and hasn't been updated since 2011 but is still commonly used. Autodock Vina has flexible ligands by default, although selected (or all) dihedrals (a.k.a. torsions) can be made rigid by the user. The receptor is rigid by default, but flexible regions can be selected by the user. Vina is the program ...


7

Docking results can be analyzed in a number of ways by looking at various geometric parameters, such as a distances, angles and dihedrals. These are then typically compared against "ideal" values, such as a those at the transition state. Graphs typically contain a parameter on each axis with the results and ideal points plotted. Interactions can mean various ...


6

One way these calculations are performed is using MD and implicit solvent calculations. The general procedure for these simulations are: Perform simulations and get frames Perform implicit solvent calculations on the complex, receptor, and ligand Calculate docking energy from the three individual components Generally there is not an additional ...


6

The Prime MM-GBSA panel is bellow. As you can see, the first section is about choosing the structures to calculate the MM-GBSA energy. The marked option works only for pose viewer files. IFD don't create this kind of file. If you want to use it, you need to work with some scripts/export in order to convert a mae (or maegz) file into a .pv.mae (or .pv....


6

MEGADOCK Megadock (associated paper) is a free GPU-enabled docking program for rigid protein–protein docking. Pros: Very fast. Can screen thousands of structures in a few hours. Cons: Both ligand and receptor are rigid. For proteins only.


5

PLANTS PLANTS uses a class of stochastic optimization algorithms called ant colony optimization (ACO). Feature list: ACO-based search engine two scoring functions (PLANTS_CHEMPLP and PLANTS_PLP) flexible protein side-chains rigid-body docking of multiconformer libraries into rigid and flexible receptors constraint system docking with selected explicit, ...


5

FLEXPEPDOCK FlexPepDock (associated paper) is part of the Rosetta toolkit and useful for peptide–protein docking. Pros: Peptide is fully flexible. Makes use of Rosetta's excellent protein modeling facilities. Cons: Requires a Rosetta installation (free). Doesn't yet support disulfide bridges or cyclization.


5

1. Ab-initio protein--protein docking: GRAMM (=Global Range Molecular Modeling) Performs rigid-body docking based on the shape complementarity and Miyazawa-Jernigan contact potentials; Exhaustively samples the search space (i.e., identifies the Global Energy Minimum solution, in the given formulation); Very fast (employs Fast Fourier Transform) and is ...


5

Another factor to consider might be blind docking or targeted. In this latter, only a region indicated on protein is targeted. In blind docking, the ligand will bind wherever suited on the protein while in targeted only the region indicated will be accessible to the ligand. Blind docking is closer to the real biological setting but computationally expensive. ...


5

You cannot "fix" it. As a RMSD value is considered good below $2 \overset{\circ}{\mathrm{A}}$, you can try one of this two methods to obtain better RMSD: Repeat the docking calculation several times. In general, docking software start the search from a generated conformer population. If you run it several times, this initial population will be ...


5

Here's what I did. Assuming that you have a part of the protein crystal structure. In my case, I have an incomplete structure of the protein. Lets say if I have an amino acid (AA) sequence of 520 (full length), I have the pdb for certain domains which are functionally important. So, I went for homology modelling. I used two predictors Robetta and tr-Rosetta. ...


5

In the past I had the same question and after a long search I found that every two year there is a worldwide competition to assess the quality of 3D structure prediction of proteins. In the past the winner was an online services called I-tasser that you can find here. I tested it also in the past year with the covid spike protein and after the publication of ...


4

I'm adding another answer because I recently find these news. The machine learning-based methods alphafold and rosettafold were recently released on github. Someone has just implemented it in Google colab as Jupiter notebook that you can simply reuse with your colab account. The only thing that you need to do is change the AA sequence. It seems that in the ...


4

Your protocol is right and rigorous in the sense as if you don't have the crystal structure of your protein and want to do some predictions, them the only way is using homology modeling. I am not a big fan of homology modeling, so I always recommend to avoid it as possible. My addition will be that, instead using only one resource to model the 3D structure, ...


4

In a molecular docking, the affinity between a protein and a ligand is determined using what is called score functions. Each docking software has its own score function. These score functions are created/modified by the software developers and, in principle, they are not interchangeable: you can not compare two docking studies made with different docking ...


4

Using different score functions One way to validate the docking results is scoring your poses using a different score function. You will need to use one of this two methods: Use another docking software: in this case you have to do a score-in-place procedure, i.e. not re-docking your ligands, just score the poses. For example, if you work with GLIDE (that ...


4

Here are the steps to validate your docking protocol (not your docking results): (Note: this is one way to do the validation, not the only one) Download a crystal structure of a complex (ligand/substrate + protein) from Protein Data Bank server. Note: It is recommended to use the same protein (not necessarily the same structure) you used in your docking. Do ...


4

In my opinion, there are no new drug molecules totally designed by computer. These designed drug molecules with CADD must be tested with many experiments. Here is a review paper about the current and future of CADD: https://www.sciencedirect.com/science/article/pii/B978012816125800002X And take a look at Wikipedia: https://en.wikipedia.org/wiki/Drug_design. ...


4

Packmol is used to pack molecules into a given box at random positions and with random rotations. If you want the spike glycoprotein to be attached to the membrane, you should probably prepare a new structure containing the two molecules as a single unit which Packmol won't break. Now you have achieved your goal. Next, you can use packmol for what it's ...


4

The main issue here is not about the type of ligands (glycans) even when it is known that there are force fields that are specific for each type of system. The main issue is about how flexible and big is the ligand you are using to dock. The GLIDE software, for example, has been increasing the number of atoms and rotatable bonds it is able to handle. Since ...


3

PATCHDOCK Patchdock is a Molecular Docking Algorithm Based on Shape Complementarity Principles. Pros: Web Based Over 100 possible docked structures with the first one being the best structure. Free Cons Takes over 2.5 to 3 hours for the results to be sent to you via mail


3

The software GLIDE is not used for RMSD calculation. GLIDE is dedicated to do small ligand/protein docking (rigid/rigid and flexible/rigid). You can calculate the RMSD by hand, using MAESTRO, CHIMERA and VMD interfaces (all free for academics) among many other software (also free).


2

You need to use the advanced option --score_only which means: score only - search space can be omitted To get info about advanced options you run vina --help_advanced that will return: Input: --receptor arg rigid part of the receptor (PDBQT) --flex arg flexible side chains, if any (PDBQT) --ligand arg ...


2

Open Drug Discovery Toolkit Open Drug Discovery Toolkit provides nice features of rescoring with different scoring function your docked poses. This is important due to the limitations of scoring functions.


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