Evidence map›Paper›PMID 39757424›Full record

ArticleJournal of chemical information and modeling2025

Development of Receptor Desolvation Scoring and Covalent Sampling in DOCK 6: Methods Evaluated on a RAS Test Set.

Y Stanley Tan, Mayukh Chakrabarti, Reed M Stein, Lauren E Prentis, Robert C Rizzo, Tom Kurtzman, Marcus Fischer, Trent E Balius

Abstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Discovery of Covalent Ligands with AlphaFold3.Journal of the American Chemical Society · 2026
    Article
  2. Article
  3. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Y Stanley TanNCI RAS Initiative, Cancer Research Technology Program, Frederick National Laboratory for Cancer Research, Leidos Biomedical Research, Inc., P.O. Box B, Frederick 21702, Maryland, United States.
Mayukh ChakrabartiNCI RAS Initiative, Cancer Research Technology Program, Frederick National Laboratory for Cancer Research, Leidos Biomedical Research, Inc., P.O. Box B, Frederick 21702, Maryland, United States.ORCID 0000-0003-2653-9728
Reed M SteinDepartment of Pharmaceutical Chemistry, University of California─San Francisco, San Francisco 94158, California, United States.
Lauren E PrentisDepartment of Biochemistry and Structural Biology, Stony Brook University, Stony Brook 11794, New York, United States.
Robert C RizzoInstitute of Chemical Biology and Drug Discovery, Stony Brook University, Stony Brook11794, New York, United States.ORCID 0000-0003-0525-6147
Tom KurtzmanPhD Programs in Chemistry, Biochemistry, and Biology, The Graduate Center of the City University of New York, New York 10016, New York, United States.ORCID 0000-0003-0900-772X
Marcus FischerDepartment of Chemical Biology and Therapeutics, St. Jude Children's Research Hospital, Memphis38105, Tennessee, United States.ORCID 0000-0002-7179-2581
Trent E BaliusNCI RAS Initiative, Cancer Research Technology Program, Frederick National Laboratory for Cancer Research, Leidos Biomedical Research, Inc., P.O. Box B, Frederick 21702, Maryland, United States.ORCID 0000-0002-6811-4667

Funding

WORK ORDER 126643 B539 EXPAND IC SUITE75N91019D00024 · NIAID · LEIDOS BIOMEDICAL RESEARCH, INC. · 2019 to 2025
$3932.6M
Development, Validation, and Application of Structure-based Tools for Computational Molecular DesignR35GM126906 · NIGMS · STATE UNIVERSITY NEW YORK STONY BROOK · PI ROBERT C. RIZZO · 2018 to 2026
$3.2M
Exploiting Water Network Perturbations in Protein Binding SitesR35GM142772 · NIGMS · ST. JUDE CHILDREN'S RESEARCH HOSPITAL · PI FISCHER, MARCUS · 2021 to 2025
$2.2M
Solvation directed drug design: from molecular physics to lead optimizationR35GM144089 · NIGMS · HERBERT H. LEHMAN COLLEGE · PI Thomas Philip Kurtzman · 2022 to 2026
$1.9M
NCI NIH HHS 75N91019D00024NIGMS NIH HHS R35 GM126906NIGMS NIH HHS R35 GM142772NIGMS NIH HHS R35 GM144089
6 · The paper itself

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.

Indexed as

Molecular Docking SimulationProto-Oncogene Proteins p21(ras)ras ProteinsAlgorithmsHumansLigandsKRAS protein, humanLigandsProto-Oncogene Proteins p21(ras)ras Proteins

Identifiers

PMID39757424
PMCPMC11776051

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.