ArticleJournal of chemical information and modeling2025
Development of Receptor Desolvation Scoring and Covalent Sampling in DOCK 6: Methods Evaluated on a RAS Test Set.
Article in Journal of chemical information and modeling, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Discovery of Covalent Ligands with AlphaFold3.Journal of the American Chemical Society · 2026Article
- Deep GIST: Deep Learning Models for Predicting the Distribution of Hydration Thermodynamics around Proteins.Journal of chemical information and modeling · 2026Article
- The covalent docking software landscape: features and applications in drug design.Briefings in bioinformatics · 2025Review
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Authors and funding
8 authors.
Funding
Abstract
Molecular docking methods are widely used in drug discovery efforts. RAS proteins are important cancer drug targets, and are useful systems for evaluating docking methods, including accounting for solvation effects and covalent small molecule binding. Water often plays a key role in small molecule binding to RAS proteins, and many inhibitors─including FDA-approved drugs─covalently bind to oncogenic RAS proteins. We assembled a RAS test set, consisting of 138 RAS protein structures and 2 structures of KRAS DNA in complex with ligands. In DOCK 6, we have implemented a receptor desolvation scoring function and a covalent docking algorithm. These new features were evaluated using the test set, with pose reproduction, cross-docking, and enrichment calculations. We tested two solvation methods for generating receptor desolvation scoring grids: GIST and 3D-RISM. Using grids from GIST or 3D-RISM, water displacements are precomputed with Gaussian-weighting, and trilinear interpolation is used to speed up this scoring calculation. To test receptor desolvation scoring, we prepared GIST and 3D-RISM grids for all KRAS systems in the test set, and we compare enrichment performance with and without receptor desolvation. Accounting for receptor desolvation using GIST improves enrichment for 51% of systems and worsens enrichment for 35% of systems, while using 3D-RISM improves enrichment for 44% of systems and worsens enrichment for 30% of systems. To more rigorously test accounting for receptor desolvation using 3D-RISM, we compare pose reproduction with and without 3D-RISM receptor desolvation. Pose reproduction docking with 3D-RISM yields a 1.8 ± 2.41% increase in success rate compared to docking without 3D-RISM. Accounting for receptor desolvation provides a small, but significant, improvement in both enrichment and pose reproduction for this set. We tested the covalent attach-and-grow algorithm on 70 KRAS systems containing covalent ligands, obtaining similar pose reproduction success rates between covalent and noncovalent docking. Comparing covalent docking to noncovalent docking, there is a 2.4 ± 3.29% increase and a 1.27 ± 3.33% decline in the success rate when docking with experimental and SMILES-generated ligand conformations, respectively. As a proof-of-concept, we performed covalent virtual screens with and without receptor desolvation scoring, targeting the switch II pocket of KRAS, using 3.4 million make-on-demand acrylamide compounds from the Enamine REAL database. On average, the attach-and-grow algorithm spends approximately 17.61 s per molecule across the screen. The test set is available at https://github.com/tbalius/teb_docking_test_sets.
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Registered trials
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