Water, water, everywhere… It’s time to stop and think.
Abstract
Despite the numerous methods available for predicting the location and affinity of water molecules, there is still a degree of scepticism and reluctance towards using such information within a drug discovery program. Here, I review some of the most common and popular methods to assess whether these apparent concerns are justified. I suggest that the field is approaching maturity and that some methods are capable of giving quantitative predictions, which are confirmed experimentally. This suggests that water-placement methods should be used more widely to help direct chemistry efforts, although more successful examples are required to help validate the techniques.
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Bodnarchuk published an extensive review of water-placement methods helpful for locating conserved water molecules within the protein binding site to be considered explicitly during docking simulation.
“Recently, Bodnarchuk (2016) published an extensive review of water-placement methods helpful for locating conserved water molecules within the protein binding site to be considered explicitly during the docking simulation.”
From Empirical scoring functions for structure-based virtual screening: applications, critical aspects, and challenges (2018) · cites this paper as Bodnarchuk (2016)
The correct prediction of the free energy of binding associated with the ligand displacement of water molecules is a key challenge for currently available docking scoring functions.
“The correct prediction of the free energy of binding associated to the ligand displacement of water molecules is a key challenge for the currently available docking scoring functions (Riniker et al., 2012; Spyrakis and Cavasotto, 2015; Bodnarchuk, 2016).”
From Empirical scoring functions for structure-based virtual screening: applications, critical aspects, and challenges (2018) · cites this paper as Bodnarchuk, 2016
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BindingDB Entry 50007681: Achieving
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BindingDB Entry 50013003: Drugging the undruggable: a computational chemist's view of KRAS
BindingDB (2022) · UC San Diego · doi:10.7270/q2db85kh
BindingDB (2023) · UC San Diego · doi:10.7270/q2w09b1p
- Authors
- Bodnarchuk, M. S.
- Corresponding author
- Bodnarchuk, Michael S.
- Venue
- Drug Discovery Today
- Publisher
- Elsevier BV
- Published
- 2016-07
- Volume
- 21
- Issue
- 7
- Pages
- 1139-1146
- ISSN
- 1359-6446 (ISSN-L)
- OpenAlex
- W2407851381
- Cited by
- 81
- References
- 72
- Citations by year
- 2026: 3 · 2025: 3 · 2024: 4 · 2023: 5 · 2022: 11 · 2021: 10 · 2020: 10 · 2019: 6 · 2018: 17 · 2017: 10 · 2016: 2
- FWCI
- 0.90
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Drug Discovery Today (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computational Theory and Mathematics › Computational Drug Discovery Methods
- Physical Sciences › Physics and Astronomy › Atomic and Molecular Physics, and Optics › Advanced Chemical Physics Studies
- Physical Sciences › Chemistry › Physical and Theoretical Chemistry › Crystallography and molecular interactions
- Keywords
- water affinity, drug discovery, quantitative prediction, experimental validation
- MeSH terms
- Monte Carlo Method, Water, Drug Discovery
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