Energy penalties enhance flexible receptor docking in a model cavity
Open accessPublished version of a preprint
Abstract
Significance: The dynamic nature of biomolecules is typically neglected in docking screens for ligand discovery. The key to benefitting from various receptor conformations is not only structural but also thermodynamic information. Here, we test a general approach that uses conformational preferences from enhanced and conventional molecular dynamics simulations to account for the cost of transitions to high-energy states. Including this information as a conformational penalty term in a docking, scoring function, we perform retrospective and prospective screens and experimentally confirm predicted ligands with T m upshift and X-ray crystallography. This not only allows us to test the predicted ligands for binding, it also tests whether they bind to the conformation of the binding site for which they were predicted.
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Cites
Directory of useful decoys, enhanced (DUD-E): better ligands and decoys for better benchmarking.
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Markov state models of biomolecular conformational dynamics
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A model binding site for testing scoring functions in molecular docking.
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Self-citationFischer, M., Coleman, R. G., Fraser, J. S., & Shoichet, B. K. (2014) · Nature Chemistry · doi:10.1038/nchem.1954 · Cited by 149 · see citing works
Self-citationSARS-CoV-2 Nsp16 activation mechanism and a cryptic pocket with pan-coronavirus antiviral potential
Vithani, N., Ward, M. D., Zimmerman, M. I., Novak, B., Borowsky, J. H., Singh, S., & Bowman, G. R. (2021) · Biophysical Journal · doi:10.1016/j.bpj.2021.03.024 · Cited by 84 · see citing works
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- Authors
- Kamenik, A. S., Singh, I., Lak, P., Balius, T. E., Liedl, K. R., & Shoichet, B. K.
- Affiliations
- University of California, San Francisco (US)
- Universität Innsbruck (AT)
- Corresponding author
- Kamenik, Anna S.
- Singh, Isha
- Balius, Trent E.
- Liedl, Klaus R.
- Shoichet, Brian K.
- Venue
- Proceedings of the National Academy of Sciences
- Publisher
- National Academy of Sciences
- Published
- 2021-09-02
- Volume
- 118
- Issue
- 36
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- PMC
- PMC8433570
- OpenAlex
- W3196694646
- Cited by
- 32
- References
- 6
- Citations by year
- 2026: 3 · 2025: 10 · 2024: 8 · 2023: 3 · 2022: 7 · 2021: 1
- FWCI
- 2.49
- Type
- journal article
- Language
- en
- Open access
- green
- doi.org
- Licence
- Locations
- Proceedings of the National Academy of Sciences (publishedVersion)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Funders
- HHS | NIH | National Institute of General Medical Sciences (GM122481)
- Austrian Science Fund (P3037)
- Topics
- Physical Sciences › Computer Science › Computational Theory and Mathematics › Computational Drug Discovery Methods
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Receptor Mechanisms and Signaling
- Keywords
- ligand binding prediction, binding site conformation, ligand discovery, enhanced sampling molecular dynamics, docking scoring functions
- MeSH terms
- Binding Sites, Kinetics, Ligands, Protein Binding, Protein Conformation, Proteins, Retrospective Studies, Thermodynamics, Crystallography, X-Ray, Molecular Dynamics Simulation, Molecular Docking Simulation
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