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Incorporation of protein flexibility and conformational energy penalties in docking screens to improve ligand discovery.
Open accessAbstract
Proteins fluctuate between alternative conformations, which presents a challenge for ligand discovery because such flexibility is difficult to treat computationally owing to problems with conformational sampling and energy weighting. Here we describe a flexible docking method that samples and weights protein conformations using experimentally derived conformations as a guide. The crystallographically refined occupancies of these conformations, which are observable in an apo receptor structure, define energy penalties for docking. In a large prospective library screen, we identified new ligands that target specific receptor conformations of a cavity in cytochrome c peroxidase, and we confirm both ligand pose and associated receptor conformation predictions by crystallography. The inclusion of receptor flexibility led to ligands with new chemotypes and physical properties. By exploiting experimental measures of loop and side-chain flexibility, this method can be extended to the discovery of new ligands for hundreds of targets in the Protein Data Bank for which similar experimental information is available.
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“Recently, Fischer et al. (2014) successfully identified new ligands targeting specific receptor conformations of cytochrome c peroxidase using a flexible docking method that samples and weights protein conformations guided by experimentally derived conformations, integrating the Boltzmann-weighted energy penalties related with the protein flexibility to the DOCK3.7 scoring function.”
From Empirical scoring functions for structure-based virtual screening: applications, critical aspects, and challenges (2018) · cites this paper as Fischer et al. (2014)
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“In this context, the development of scoring functions adapted for flexible receptor docking is crucial to achieve real improvements in pose and affinity prediction (Totrov and Abagyan, 1997; Wei et al., 2002; Fischer et al., 2014; Ravindranath et al., 2015; Lam et al., 2017; Kong et al., 2018).”
From Empirical scoring functions for structure-based virtual screening: applications, critical aspects, and challenges (2018) · cites this paper as Fischer et al., 2014
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Metadata
- Authors
- Fischer, M., Coleman, R. G., Fraser, J. S., & Shoichet, B. K.
- Affiliations
- University of California, San Francisco (US)
- Corresponding author
- Fraser, James S.
- Shoichet, Brian K.
- Venue
- Nature Chemistry
- Published
- 2014-05-25
- Volume
- 6
- Issue
- 7
- Pages
- 575-583
- ISSN
- 1755-4330 (ISSN-L)
- 1755-4349
- PMC
- PMC4144196
- OpenAlex
- W2089879448
- Cited by
- 149
- References
- 51
- Citations by year
- 2026: 7 · 2025: 14 · 2024: 11 · 2023: 14 · 2022: 11 · 2021: 9 · 2020: 8 · 2019: 8 · 2018: 15 · 2017: 14 · 2016: 16 · 2015: 16 · 2014: 6
- FWCI
- 18.63
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Nature Chemistry (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Funders
- National Institutes of Health (DP5OD009180)
- National Institute of General Medical Sciences (F32GM096544, GM59957, R01GM059957)
- 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 › Structural Biology › Enzyme Structure and Function
- Keywords
- protein flexibility, flexible docking, conformational sampling, ligand discovery, cytochrome c peroxidase, ligand pose prediction, loop flexibility, side-chain flexibility
- MeSH terms
- Ligands, Models, Molecular, Protein Binding, Protein Conformation, Proteins
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