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Energy Penalties Enhance Flexible Receptor Docking in a Model Cavity
Open accessPreprint — published as 10.1073/pnas.2106195118 · Paper page
Abstract
Protein flexibility remains a major challenge in library docking due to difficulties in sampling conformational ensembles with accurate probabilities. Here we use the model cavity site of T4 Lysozyme L99A to test flexible receptor docking with energy penalties from molecular dynamics (MD) simulations. Crystallography with larger and smaller ligands indicates that this cavity can adopt three major conformations, open, intermediate, and closed. Since smaller ligands typically bind better to the cavity site, we anticipate an energy penalty for cavity opening. To estimate its magnitude, we calculate conformational preferences from MD simulations. We find that including a penalty term is essential for retrospective ligand enrichment, otherwise high-energy states dominate the docking. We then prospectively docked a library of over 900,000 compounds for new molecules binding to each conformational state. Absent a penalty term, the open conformation dominated the docking results; inclusion of this term led to a balanced sampling of ligands against each state. High ranked molecules were experimentally tested by T m -upshift and X-ray crystallography. From 33 selected molecules, we identified 18 new ligands and determined 13 crystal structures. Most interesting were those bound to the open cavity, where the buried site opens to bulk solvent. Here, highly unusual ligands for this cavity had been predicted, including large ligands with polar tails; these were confirmed both by binding and by crystallography. In docking, incorporating protein flexibility with thermodynamic weightings may thus access new ligand chemotypes. The MD approach to accessing and, crucially, weighting such alternative states may find general applicability. Significance Statement: The dynamic nature of biomolecules is typically neglected in docking screens for ligand discovery. 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 MD 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 novel ligands with T m -upshift and X-ray crystallography.
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Identification of slow molecular order parameters for Markov model construction
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BackgroundMarkov state models of biomolecular conformational dynamics
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“Encouraging studies on how MD simulation can be leveraged to explore the flexibility of ligand binding sites include work from the Bowman group, in which exhaustive MD simulations aided the discovery of allosteric binders (6, 10).”
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Metadata
- 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
- openRxiv
- Published
- 2021-04-20
- Volume
- 118
- Issue
- 36
- ISSN
- 0027-8424 (ISSN-L)
- PMC
- PMC8433570
- OpenAlex
- W3196694646
- Cited by
- 32
- References
- 4
- Citations by year
- 2026: 3 · 2025: 10 · 2024: 8 · 2023: 3 · 2022: 7 · 2021: 1
- FWCI
- 2.50
- 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
- Austrian Science Fund (P3037, P30737)
- National Institute of General Medical Sciences (GM122481, R35GM122481)
- Topics
- Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Drug Discovery › 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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