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Cited by 345Click Chemistry and ApplicationsComputational Drug Discovery MethodsEnzyme function and inhibition

Covalent inhibitors design and discovery.

De Cesco, Stephane, Kurian, Jerry, Dufresne, Caroline, Mittermaier, Anthony K., Moitessier, Nicolas·2017·European Journal of Medicinal Chemistry
DOI 10.1016/j.ejmech.2017.06.019
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Abstract

In the history of therapeutics, covalent drugs occupy a very distinct category. While representing a significant fraction of the drugs on the market, very few have been deliberately designed to interact covalently with their biological target. In this review, the prevalence of covalent drugs will first be briefly covered, followed by an introduction to their mechanisms of action and more detailed discussions of their discovery and the development of safe and efficient covalent enzyme inhibitors. All stages of a drug discovery program will be covered, from target considerations to lead optimization, strategies to tune reactivity and computational methods. The goal of this article is to provide an overview of the field and to outline good practices that are needed for the proper assessment and development of covalent inhibitors as well as a good understanding of the potential and limitations of current computational methods for the design of covalent drugs.

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Crossref · 10.1016/j.ejmech.2017.06.019

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126 of 126 references verified0 citation errors · 0 not checkable

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  • There is a whole class of inhibitors that form a covalent bond with their enzyme/receptor target.

    “However, there is a whole class of inhibitors that form a covalent bond with their enzyme/receptor target (De Cesco et al., 2017).”

    From Empirical scoring functions for structure-based virtual screening: applications, critical aspects, and challenges (2018) · cites this paper as De Cesco et al., 2017

  • Two critical aspects in the future development of covalent scoring functions are the capacity to predict the kinetics of ligand binding and the intrinsic reactivity of electrophilic and nucleophilic pairs of atoms.

    “Two critical aspects in the future development of covalent scoring functions are the capacity to predict the kinetics of ligand binding (e.g., residence times) and the intrinsic reactivity of electrophilic and nucleophilic pairs of atoms (De Cesco et al., 2017).”

    From Empirical scoring functions for structure-based virtual screening: applications, critical aspects, and challenges (2018) · cites this paper as De Cesco et al., 2017

  • Development of covalent-docking methodologies is very important due to potential advantages of covalent inhibitors, including sustained duration of action, increased ligand efficiency, ability to inhibit shallow binding sites previously categorized as undruggable, and increased ability to overcome resistant mutations.

    “The development of covalent-docking methodologies capable of dealing with such type of inhibition is very important due to the potential advantages associated with covalent inhibitors (De Cesco et al., 2017), including (i) sustained duration of action leading to less frequent dosing, (ii) increased ligand efficiency, (iii) ability to inhibit targets with shallow binding sites previously”

    From Empirical scoring functions for structure-based virtual screening: applications, critical aspects, and challenges (2018) · cites this paper as De Cesco et al., 2017

  • Due to increasing interest in covalent drugs, many non-covalent docking programs have developed covalent versions and some new docking programs focused on covalent ligands have been developed.

    “Due to the increasing interest in covalent drugs, many non-covalent docking programs have developed covalent versions and some new docking programs focused on covalent ligands have been developed (Kumalo et al., 2015; Awoonor-Williams et al., 2017; De Cesco et al., 2017).”

    From Empirical scoring functions for structure-based virtual screening: applications, critical aspects, and challenges (2018) · cites this paper as De Cesco et al., 2017

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Authors
De Cesco, S., Kurian, J., Dufresne, C., Mittermaier, A. K., & Moitessier, N.
Affiliations
McGill University (CA)
Corresponding author
Moitessier, Nicolas
ORCID
Venue
European Journal of Medicinal Chemistry
Publisher
Elsevier BV
Published
2017-09
Volume
138
Pages
96-114
ISSN
0223-5234 (ISSN-L)
DOI
10.1016/j.ejmech.2017.06.019
OpenAlex
W2622009965
Cited by
315
References
127
Citations by year
2026: 20 · 2025: 41 · 2024: 30 · 2023: 39 · 2022: 30 · 2021: 46 · 2020: 45 · 2019: 30 · 2018: 28 · 2017: 5
FWCI
1.76
Type
journal article
Language
en
Open access
closed
Licence
www.elsevier.com/tdm/userlicense/1.0/ (tdm)
Locations
  • European Journal of Medicinal Chemistry (publishedVersion)
  • PubMed (publishedVersion)
Funders
CIHR (MOP-136943)
Topics
  • Physical Sciences › Chemistry › Organic Chemistry › Click Chemistry and Applications
  • Physical Sciences › Computer Science › Computational Theory and Mathematics › Computational Drug Discovery Methods
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Enzyme function and inhibition
Keywords
covalent inhibitors, covalent enzyme inhibitors, drug discovery, lead optimization, reactivity tuning, computer-aided drug design, mechanism of action, target selection, drug safety
MeSH terms
Biological Products, Humans, Kinetics, Quantum Theory, Drug Discovery

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