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Autodock Vina 1.2.0: New Docking Methods, Expanded Force Field, And

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Autodock Vina 1.2.0: New Docking Methods, Expanded Force Field, And AutoDock Vina 1.2.0: new docking methods, expanded force field, and Python bindings Jerome Eberhardt1,a, , Diogo Santos-Martins1,a, Andreas F. Tillacka, and Stefano Forlia, 1These authors contributed equally to this work. a Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, California, USA AutoDock Vina is arguably one of the fastest and most widely plement additional functionality without significant changes used open-source docking engines. However, compared to other in the source code. docking engines in the AutoDock Suite, it lacks features that The usefulness of such specialized methods is hindered by support modeling of specific systems such as macrocycles or the poor search efficiency of AD4. In fact, AD4 can be up modeling water explicitly. Here, we describe the implemen- to 100x slower than Vina 1, depending on the search com- tation of these functionality in AutoDock Vina 1.2.0. Addi- plexity. The large performance difference is due to the bet- tionally, AutoDock Vina 1.2.0 supports the AutoDock4.2 scor- ter search algorithm used in Vina, a Monte-Carlo (MC) iter- ing function, simultaneous docking of multiple ligands, and a 17 batch mode for docking a large number of ligands. Further- ated search combined with the BFGS gradient-based op- more, we implemented Python bindings to facilitate scripting timizer. In comparison with the Lamarckian Genetic Algo- 3 and the development of docking workflows. This work is an ef- rithm (LGA) and Solis-Wets local search of AD4 , the search fort toward the unification of the features of the AutoDock4 and efficiency of Vina leads to better docking results with fewer AutoDock Vina docking engines. The source code is available at scoring function evaluations. https://github.com/ccsb-scripps/AutoDock-Vina We implemented some of the specialized AD4 features in docking | autodock | vina | drug discovery | virtual screening the Vina source code, enabling their use of the powerful Correspondence: [email protected] MC/BFGS search algorithm. Then, we further extended the Vina engine enabling simultaneous docking of multiple lig- ands, and adding Python bindings to facilitate programmatic Introduction access to the docking engine functionalities. AutoDock Vina (Vina) 1 is one of the docking en- 2 gines in the AutoDock Suite , together with AutoDock4 Scoring function extensions and improve- 3 4 5 (AD4) , AutoDockGPU , AutoDockFR , and AutoDock- ments CrankPep 6. Vina is arguably among the most widely used docking engines, probably because of its ease of use and AutoDock4.2 scoring function. One major improvement speed, when compared to the other docking engines in the is the availability of the AD4 scoring function in Vina. This suite and elsewhere, as well as being open source. allows users to access it using the Vina MC-based search al- Research groups around the world have modified and built gorithm and explore with equal efficiency its energy land- upon the Vina source code, improving the search algorithm scape. This will likely facilitate large-scale consensus dock- (QuickVina2 7), made the interface more user friendly and al- ing virtual screening campaigns 18,19. low modification of scoring terms through the user interface The AD4 and Vina scoring functions are quite different. (Smina 8), and improved the scoring function for carbohy- AD4 uses a physics-based 3 model with van der Waals, elec- drate docking (Vina-Carb 9), halogen bonds (VinaXB 10), as trostatic, directional hydrogen-bond potentials derived from well as ranking and scoring (Vinardo 11). an early version of the AMBER force field 3,20, a pairwise- Beside these valuable developments, there are still several additive desolvation term based on partial charges, and a methods within the AutoDock Suite that are not available in simple conformational entropy penalty. On the other hand, Vina because they have been implemented specifically for ei- Vina lacks electrostatics and solvation 1, and consists of a van ther the scoring function or the docking engine in AD4. Ex- der Waals-like potential (defined by a combination of a re- amples of such methods include docking with macrocyclic pulsion term and two attractive gaussians), a non-directional flexibility 12, specialized metal coordination models 13, mod- hydrogen-bond term, a hydrophobic term, and a conforma- eling of explicit waters 14, coarse-grained ligand models 15, tional entropy penalty. and ligand irreversible binding 16. Despite being a less effi- Performance-wise, the average time required to perform en- cient docking engine, AD4 allows the user to modify a large ergy evaluations with the AD4 scoring function is nearly 3x number of docking parameters, providing direct access to larger than with the Vina scoring function. This is due to the some of the engine internals, making it well-suited for the presence of additional electrostatic and desolvation maps that development of new docking methods. Conversely, the Vina need to be interpolated for each movable atom. interface is highly specialized and optimized, and one of its hallmarks is the very limited amount of user input necessary Grid map files support. Both AD4 and Vina calculate in- to perform a docking. In turn, this makes it impossible to im- termolecular interactions by performing trilinear interpola- June 10, 2021 tions of grid maps pre-calculated on the target structure. Vina considering the first two sets of poses (top 2). also uses the target structure to perform a post-processing minimization of the docked poses. In AD4, maps are pre- Hydrated docking. The hydrated docking protocol 14 has calculated using a separate program (AutoGrid 2) prior to been developed to model waters directly involved in the docking and loaded at runtime, while Vina calculates them ligand-receptor interaction. The method is based on dock- on-the-fly prior to running the MC search. The availability ing ligands explicitly hydrated with spherical waters, and can to accessible grid map files generated by AutoGrid provided be used to predict the position and the role (i.e., bridging or the foundations for a number of specialized methods, such displaced) of individual water molecules and generally im- as the zinc-coordination potentials in the AutoDock4Zn force prove ligand pose predictions. Waters are represented by a field 13, biasing docking using information from molecular single atom of type W, and are added to the ligand molecule dynamics simulations in AutoDock-Bias 21, and the integra- at the end of each hydrogen bond vector. During docking, tion of Grid Inhomogenous Solvation Theory (GIST) 22–24 in W atoms move along with the ligand, do not contribute to AutoDock-GIST 25. intramolecular interactions, and are allowed to overlap with In AutoDock Vina 1.2.0 we added the support to optionally the protein. In fact, when that happens, a water is consid- load external grid map files, enabling all these methods in ered displaced (i.e., removed from the system), and an en- both the AD4 and Vina scoring functions. These methods ergy reward is added to the ligand score to reflect the en- can be applied by following the existing protocols to prepare tropy gain resulting from releasing the water to bulk solvent. target structures and the corresponding grid maps, then re- Following the standard hydrated docking protocol 14, the W place the AutoDock4 binary with the new version of Vina. map, which represents water-receptor interactions is obtained The availability of reading and writing maps facilitates the by combining the oxygen-acceptor (OA) and hydrogen donor development of similar methods for the Vina scoring func- (HD) maps of the AD force field. tion. Pose rank New atom types. We extended both the Vina and AD4 PDB ID 1 2 3 4 5 scoring functions to support new atom types for atoms and 4ykq 0.45 0.43 2.37 6.16 4.01 pseudo-atoms as required by the hydrated docking method 4ykt 9.23 8.24 8.50 3.40 2.86 and the macrocycle sampling methods. These atom types are 4yku 6.02 1.14 0.67 6.04 5.89 implemented in the source code. Additionally, we also added 4ykx 0.98 0.95 6.24 1.79 1.75 parameters for silicon to address user requests for better sup- 4ykw 6.27 0.64 6.50 1.32 1.34 port to the chemical space covered in public repositories such 4ykz 5.30 1.68 0.77 5.30 6.00 as the ZINC database 26. Table 1. RMSD of 6 ligands redocked against HSP90 using the hydrated docking protocol. Values under 2 Å in bold. New docking methods To validate the implementation of this docking protocol in We increased the number of the docking methods available in Vina v.1.2.0, we used six HSP90 protein-ligand complexes Vina leveraging the availability of new atom types, the possi- from the D3R Grand Challenge 2015 28. This is an interest- bility of specifying grid map files to be used during docking, ing system for the hydrated docking because different ligands and by extending the existing code. bind with a different number of waters bridging hydrogen bonds with the protein. The RMSD of the redocked ligands Simultaneous multiple ligand docking. Vina is now able in reported in Table1, and a hand-picked system (PDB 4ykq) to dock simultaneously multiple ligands. This functionality is depicted in Figure1B. When looking at the best pose, only may find application in fragment based drug design, where two ligands could be redocked with an RMSD below 2 Å but small molecules that bind the same target can be grown or this number increases to 5 if the top 2 poses are considered. combined into larger compounds with potentially better affin- ity. AutoDock4Zn. One of the most used methods developed for The protein PDEδ in complex with two inhibitors (PDB AD4 is the AutoDock4Zn, a specialized force field to model 5x72) 27 was used as a proof of concept to test the ability of zinc-coordinating ligands 13.
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