Modeling covalent-modifier drugs

Department of Chemistry, Memorial University of Newfoundland, St. John's, Newfoundland and Labrador, Canada
DOI
10.7287/peerj.preprints.2857v2
Subject Areas
Biochemistry, Bioinformatics, Biophysics, Pharmacology, Computational Science
Keywords
irreversible inhibition, pKa, docking, cysteine, kinase, bioinformatics, QM/MM, computer modeling, Michael addition, covalent modifiers
Copyright
© 2017 Awoonor-Williams et al.
Licence
This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Preprints) and either DOI or URL of the article must be cited.
Cite this article
Awoonor-Williams E, Walsh AG, Rowley CN. 2017. Modeling covalent-modifier drugs. PeerJ Preprints 5:e2857v2

Abstract

In this review, we present a summary of how computer modeling has been used in the development of covalent modifier drugs. Covalent modifier drugs bind by forming a chemical bond with their target. This covalent binding can improve the selectivity of the drug for a target with complementary reactivity and result in increased binding affinities due to the strength of the covalent bond formed. In some cases, this results in irreversible inhibition of the target, but some targeted covalent inhibitor (TCI) drugs bind covalently but reversibly. Computer modeling is widely used in drug discovery, but different computational methods must be used to model covalent modifiers because of the chemical bonds formed. Structural and bioinformatic analysis has identified sites of modification that could yield selectivity for a chosen target. Docking methods, which are used to rank binding poses of large sets of inhibitors, have been augmented to support the formation of protein--ligand bonds and are now capable of predicting the binding pose of covalent modifiers accurately. The pKa's of amino acids can be calculated in order to assess their reactivity towards electrophiles. QM/MM methods have been used to model the reaction mechanisms of covalent modification. The continued development of these tools will allow computation to aid in the development of new covalent modifier drugs.

Author Comment

The manuscript was revised to correct typographical errors, references, and to clarify aspects of the text.