AutoDock Vina Multiple Ligand Docking (Simultaneous Multiple Ligand Docking)

1. Introduction to multi-ligand molecular docking

Simultaneous Multiple Ligand Docking (SMLD) or Multiple Ligand Simultaneous Docking (MLSD) is a molecular docking technology used to dock multiple ligands (small molecule drug candidates) to a protein molecule simultaneously. binding site. Unlike traditional molecular docking techniques, traditional methods usually only consider the interaction between one ligand and one protein. The goal of SMLD is to more efficiently study how multiple ligands interact with the same protein to find potential drug candidates.

Here are some of the key features and benefits of SMLD:

  1. Diversity Studies: SMLD enables researchers to study multiple ligands with different structures to determine how they interact with the same protein. This allows for a better understanding of ligand diversity and binding modes.

  2. Drug combination research: SMLD can be used to study how multiple ligands interact with proteins at the same time, which is very important for studying multi-drug combination therapy or multi-ligand combination therapy.

  3. Computational Challenges: Despite its attractiveness, SMLD also faces computational challenges due to the need to consider different conformations and interactions of multiple ligands simultaneously. Therefore, high-performance computing resources and advanced algorithms are required to effectively perform SMLD.

Currently, the open source tool that can realize multi-ligand molecular docking is AutoDock Vina. For the official English tutorial on AutoDock Vina’s multi-ligand docking, please refer to Multiple ligands docking. Taking the complex of PDE and two inhibitors (pdb id: 5×72) as an example, AutoDock Vina’s ability to successfully dock multiple ligands is demonstrated.

The following content will take PRMT5 as an example to perform multi-ligand molecular docking using AutoDock Vina. For the introduction and docking calculation of AutoDock Vina 1.2.0, please refer to the previous blog AutoDock Vina 1.2.0 docking calculation (large batch).

Software used:

  • AutoDock Vina 1.2.0 (the latest version AutoDock Vina 1.2.5)
  • ADFR (prepare_receptor/prepare_ligand/reduce/babel)
  • PYMOLl
  • PyMOL plugin GetBox

2. Introduction to PRMT5

The PRMT5·MTA complex has recently emerged as a novel synthetic lethal drug target for the treatment of MTAP-deficient cancers. MRTX1719 is a potent and selective inhibitor of the PRMT5?MTA complex, selectively inhibiting PRMT5 activity in MTAP-deficient cells compared to MTAP wild-type cells. Therefore, taking the structure of this complex (PDB: 7S1S) as an example, the two small molecules 85k and MTA in the figure below are double ligands and perform multi-ligand calculations with the PRMT5 binding site.

3. Preprocessing before docking

3.1 Receptor pretreatment

  1. Download the PDB file of the PRMT5·MTA complex structure from the RCSB PDB database: 7S1S.pdb
    Or open PyMol and enter fetch 7S1S in the command line to directly download and import PyMol.
  2. Remove water molecules in PyMol remove resn HOH
  3. In PyMol, since the B chain is not the protein we are concerned about, we delete the B chain remove chain B
  4. Check in PyMol that the binding sites of small molecule 85k and MTA are free of amino acid mutations and loop deletions.
  5. Use the plug-in GetBox in PyMol to obtain the pocket parameters of vina, as shown in the figure below?
  6. Get pocket parameters in PyMol: –center_x -31.9 –center_y -43.7 –center_z -7.1 –size_x 25.8 –size_y 29.8 –size_z 20.6
  7. Remove all small molecule ligands in PyMol and save the receptor structure
 remove resn MTA + 85k
 save 7S1S_pro.pdb
  1. The reduce program hydrogenates the acceptor structure (7S1S_pro.pdb). reduce is included in the ADFR package.
reduce 7S1S_pro.pdb >7S1S_H.pdb
  1. prepare_receptor Converts the PDB format of the receptor structure to PDBQT format. prepare_receptor is also included in the ADFR package
prepare_receptor -r 7S1S_H.pdb -o 7S1S_H.pdbqt

Finally, the 7S1S_H.pdbqt file was obtained as the receptor for Vina docking calculations.

3.2 Small molecule ligand pretreatment

  1. Download PDB from RCSB PDB database: 7S1S mol2 format files of small molecules: 7s1s_C_MTA.mol2, 7s1s_D_85K.mol2
  2. Convert the mol2 format of small molecule ligands to PDBQT format, prepare_ligand is also included in the ADFR package
prepare_ligand -l 7s1s_C_MTA.mol2
prepare_ligand -l 7s1s_D_85K.mol2

You will get the files 7s1s_C_MTA.pdbqt and 7s1s_D_85K.pdbqt.

3.3 Preparation of docking pocket parameter file

Obtain the pocket parameter information from the above 3.1.6: center_x, center_y, center_z and size_x, size_y , size_z, write it into the file 7s1s_vina.txt. The content of the file is as follows?:

center_x = -31.9
center_y = -43.7
center_z = -7.1
size_x = 25.8
size_y = 29.8
size_z = 20.6

4. Vina docking

So far, we have prepared all the files required before Vina docking:

  • Receptor file (–receptor): 7S1S_H.pdbqt
  • Small molecule ligand files (–ligand): 7s1s_C_MTA.pdbqt and 7s1s_D_85K.pdbqt
  • Docking pocket parameter file (–config): 7s1s_vina.txt

Then you can start the docking calculation directly. This script assumes that vina is already in the PATH environment variable. Otherwise, please modify accordingly.

$ vina --receptor 7S1S_H.pdbqt --ligand 7s1s_C_MTA.pdbqt 7s1s_D_85K.pdbqt --config 7s1s_vina.txt --exhaustiveness 32 --out 7s1s_vina_out.pdbqt

The running process is as follows?:

As can be seen from the figure above, 9 conformations were finally generated. The predicted affinity of the conformation with the lowest score, that is, the first-ranked conformation, is -16.37 kcal/mol. All conformations are saved in the 7s1s_vina_out.pdbqt file.

5. Result analysis

Convert the 7s1s_vina_out.pdbqt file to SDF format to facilitate visual analysis of conformations in PyMol. This script assumes that ADFR is already in the PATH environment variable. Otherwise, please modify accordingly.

babel -ipdbqt 7s1s_vina_out.pdbqt -osdf 7s1s_vina_out.sdf

Load the result file 7s1s_vina_out.sdf after docking and the original experimental structure 7S1S.pdb file before docking into the PyMOL program. By visually comparing the conformation after vina docking (blue) and the small molecule conformation (purple) in the original experimental structure in PyMOL, the top-ranked conformation is compared with it as shown in the figure below?:

Among them, the purple part is the original experimental conformation, and the blue part is the small molecule conformation after vina docking. It can be seen from the above figure thatvina’s conformational prediction of 85k is very accurate, while the conformation prediction of MTA molecule is slightly different, but the spatial position arrangement of the two molecules is calculated. Cloth (←MTA, 85k→) is consistent with the experimental results.