Molecular Docking Software and Tools

Molecular docking is the mutual identification process between two or more molecules through geometric matching and energy matching.

The binding posture and affinity between ligand and receptor are very important information in computer-aided drug design. In the initial stages of drug discovery projects, this information is often obtained through the use of molecular docking methods. Currently, computer-aided drug design (CADD) is commonly used to predict top lead potential compounds. This method is widely used because it helps to significantly reduce the cost and time of developing drugs. Molecular docking software plays a crucial role in drug discovery by simulating the interactions between protein targets and potential drug molecules. Structure-based docking screening of large compound libraries has become a common method for early drug and probe discovery. As computer efficiency has increased and compound libraries have grown, the ability to sift through hundreds of millions or even billions of compounds have become feasible for medium-sized computer clusters.

These tools enable researchers to predict the binding affinity and orientation of ligands, helping to identify promising drug candidates. There is a lot of free molecular docking software available, which allows researchers to perform docking simulations of protein-ligand complexes, providing valuable insights into molecular interactions.

Popular Molecular Docking Software Download

Free molecular docking software download

There is a wide range of molecular docking software that has been reported or not reported in the literature, many of which were originally developed in laboratories and distributed for free. When the software is perfect and has few defects, it may be purchased by a specialized commercial software company and become a module in a large package.

Most life science processes involve the identification of two molecules at the atomic scale. Predicting such interactions at the molecular level through so-called docking software is a daunting task. Docking programs have a wide range of applications, from protein engineering to drug design. We have compiled the free high throughput virtual screening molecular docking software available to users and attached the corresponding website.

• Autodock: Autodock is an open-source molecular simulation software developed and maintained by the Olson Laboratory at the Scripps Research Institute for the docking of biological macromolecules with small molecular ligands.
  Web: https://Autodock.scripps.edu/
• Autodock Vina: Vina is also a molecular docking software developed by MGL Laboratories. Compared to Autodock 4.0, Autodock Vina has a higher average accuracy for combined model predictions.
  Web: https://vina.scripps.edu/
• DOCK: A set of software for simulating molecular docking.
  Web: https://dock.compbio.ucsf.edu/
• UCSF Chimera: UCSF Chimera is an interactive visualization software for the analysis of three-dimensional structures of proteins.
  Web: https://www.cgl.ucsf.edu/chimera/
• rDock: rDock is a fast and versatile open-source docking program that can be used to dock small molecules with proteins and nucleic acids.
  Web: http://rdock.sourceforge.net/
• LeDock: Small molecules can be flexibly attached to proteins quickly and accurately.
  Web: https://www.lephar.com/software

Commercial software docking downloads

This paid molecular docking software have powerful capabilities in the field of drug discovery and molecular simulation, each with its own characteristics, and choosing the right tool often depends on the specific research needs. For example, Glide and MOE are suitable for precise docking analysis and multifunctional integration.

• Schrödinger's Glide: Glide is Schrodinger's high-precision molecular docking software that provides efficient virtual screening and precise molecular docking results. It supports both rigid and flexible docking and can handle various types of docking such as protein-ligand, protein-protein, DNA-ligand, etc.
  Web: https://www.schrodinger.com/platform/products/glide/
• MOE: MOE is an integrated molecular simulation software that provides functions such as molecular docking, molecular dynamics, quantitative structure-activity relationship (QSAR), drug design, and more. MOE's docking module is highly flexible and supports the docking of proteins, DNA, RNA and small molecules.
  Web: https://www.chemcomp.com/en/Products.htm

Best Molecular Docking Software for Drug Discovery

Performance Evaluation of Docking Software

Molecular docking is a popular technique in the field of drug design, which can be used to predict both binding patterns and binding affinity. In the last 20 years, there have been a lot of molecular docking software such as Autodock, Autodock Vina, LeDock, rDock, UCSF DOCK, LigandFit, GLIDE, GOLD, MOE Dock, Surflex-Dock and so on, they have both commercial and academic software.

The sampling algorithm and scoring function are the core parts of docking software. The former is responsible for posing the compound in the protein pocket, and the sampling algorithm determines the sampling power of the docking software. The latter is responsible for scoring each pose, which determines the scoring power of the docking software. Because the sampling algorithms and scoring functions of different docking software are different, their performance is also very different, so it is very important to evaluate and compare the performance of these software. The results of performance evaluation can reveal the advantages and disadvantages of each software, and thus help users choose software reasonably.

Overall, if the optimized conformation of the ligand is used as an input to the molecular docking, the highest-scoring postures have a success rate of about 40 to 60 percent, and the best postures have a success rate of about 60 to 80 percent. Based on the results of the highest-scoring postures, the performance of the academic program follows the following order: LeDock (57.4%) > rDock (50.3%) ≈ Autodock Vina (49.0%) > Autodock (PSO) (47.3%) > UCSF DOCK (44.0%) > Autodock (LGA) (37.4%), the order of business procedures is as follows: GOLD (59.8%) > Glide (XP) (57.8%) > Glide (SP) (53.8%) > Surflex-Dock (53.2%) > LigandFit (46.1%) > MOE Dock (45.6%).

Table 1 The features of the evaluated docking programs (Wang Z et al.,2016)

Autodock4 vs Autodock Vina

Autodock4 and Autodock Vina stand out as popular open-source software tools widely utilized for this purpose, each garnering over 6,000 citations in the past decade. Comparing the efficacy of these molecular docking software applications across a diverse spectrum of protein-ligand complexes holds substantial significance.

Vina is employed not only to assess the binding affinity of small molecules to biomolecular targets such as peptides, proteins, and genes but also to stand out for its robust computational capabilities in predicting the binding poses of large substrates with protein targets. Docking simulations were conducted using both Autodock4 and Autodock Vina, employing various docking configurations that impact computational resource utilization and accuracy. Our computational findings align closely with previous research, highlighting Vina's significantly faster convergence compared to Autodock4. Interestingly, Autodock4 demonstrates superior performance across 21 specific targets, whereas Vina's protocol proves more effective than Autodock4 for 10 other targets.

Fig 1. Comprehensive comparison of AD4 and Vina (Nguyen NT et al.,2020)

AutoDock was chosen over AutoDock Vina because of the need for control accuracy, more complex docking tasks, and the need to adapt to specific workflows. While AutoDock Vina is popular due to its speed and simplicity, AutoDock is still a better choice for certain application scenarios.

How to Perform Molecular Docking in Drug Discovery

Drug discovery is a complex and interdisciplinary process that covers multiple stages from target identification to clinical trials. Identify the target through genomics, proteomics, and literature studies, and confirm the biological role of the target through experimental methods such as gene knockout, RNA interference (RNAi), or CRISPR. Once the target is reconfirmed and validated, an active initial "hit compound" can be found by screening a large chemical library. In the later stage, animal clinical trials such as structural optimization and toxicity testing of the targeted compounds are required to finally confirm the candidate drug. One of the most critical is to find active initial "hit compounds" by screening large-scale chemical libraries. At present, the most common method is to predict the compounds that may be combined with the target in the compound library by computational method, that is, "virtual screening".

Common ideas for using interworking software

There is many software for virtual screening, and the process is relatively similar, which requires the user to prepare proteins and ligand molecules that can be identified by the software. On the basis of determining the docking pocket, the algorithm in the software is used to screen out the most important compounds.

Different software modules have different names and default parameters, but in general, we need to carry out four parts of operations: protein processing, ligand processing, regulation box and docking.

As one of the most commonly used and popular docking software in the field of molecular docking, AutoDock is not only because it can be downloaded for free and used freely, but more importantly, AutoDock adopts advanced docking algorithms, including Monte Carlo simulation, genetic algorithm, and local optimization. These algorithms can find the optimal binding mode between protein and ligand in a short time, and the results are more accurate. At the same time, as a popular open-source project, AutoDock has a huge user base and developer support, and there are a large number of tutorials, forums, and questions on the Internet to facilitate users to solve problems, so the following is a brief summary of the simple use of Autodock.

How to perform molecular docking using Autodock

Starting docking analysis via Autodock's interface requires only three steps: The user must define the protein structure, one or more putative ligands, and docking parameters. For the docking of the protein-molecule complex using Autodock, in addition to downloading Autodock, downloading Pymol, mgltools, and other software may be more helpful for the analysis and understanding of results.

Download

You can download it from the website https://Autodock.scripps.edu/. Note that the folder cannot contain Chinese names.

Prepare the 3D structure file

• Protein: The target protein structure can be determined by specifying its identifier from a protein database or by uploading a structure file. For the three-dimensional structure of protein that has been reported in the literature, it can be obtained directly from PDB. If multiple PDB records are available for the same target, those with high resolution and ligands similar to the record to be docked should be considered first. When there are multiple chains in the PDB file, the user can specify the identifier of the chain that will perform the docking. If the structure file is generated by a nuclear magnetic response experiment, it must be edited first to preserve only one structure model.
  Enter the software and process the protein into information that the software can recognize. The protein is dehydrated. The downloaded protein PDB structure contains only one carbon chain backbone, so it needs to be filled with hydrogen atoms.
• Molecule: Use PubChem to search for the required small molecules and download them using the structure of the corresponding results. You can also use software to map small molecule structures. Import a small molecule file. Detect and set the torsion of small molecules. According to the need to choose, generally choose the maximum distortion number. Once set, save the small molecule as a. pdbqt file.

Select grid box

When default parameters are used, the entire target protein structure is considered during docking. However, if the target protein is particularly large and/or if the putative binding pocket is known, the docking can be restricted to a rectangular region of space for local docking measurements. Select the target protein region, and the region surrounded by the tricolor cube is the protein region that needs to be docked. Cover the target area by adjusting the size of xyz, the overall multiple (red box below), and the xyz center.

Run AutoGrid4. Save the box file.

Run program

Select processed protein and small molecule files, select docking algorithms, and generally choose Genetic Algorithms. After the setting is complete, output the. dpf file. Note that Lamarckian GA is selected here to generate the output file.

Reliable Molecular Docking Service

The ability to predict binding affinity and orientation using various docking software tools significantly reduces the time and cost associated with experimental screening. However, the success of docking research depends on the selection of the right software and the expertise to use the software effectively. For researchers and pharmaceutical companies looking to leverage molecular docking for drug development projects, professional docking services can provide valuable support. These services provide advanced simulation, custom algorithm selection, and outcome analysis to help optimize the drug discovery process and improve the likelihood of identifying successful drug candidates. By collaborating with Creative Proteomics, organizations can maximize the efficiency and accuracy of research, ensuring faster progress in developing new treatment options.