Rational Approaches to Improving Selectivity in Drug Design
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Tidor_Rational approaches.pdf
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Author(s)
Huggins, David J.
Sherman, Woody
Tidor, Bruce
Date Issued
January 2012
Journal
Journal of Medicinal Chemistry
Publisher
American Chemical Society (ACS)
Citation
Huggins, David J., Woody Sherman, and Bruce Tidor. “Rational Approaches to Improving Selectivity in Drug Design.” Journal of Medicinal Chemistry 55.4 (2012): 1424–1444. Copyright © 2012 American Chemical Society
Version
Final published version
Abstract
Appropriate tuning of binding selectivity is a primary objective
in the discovery and optimization of a compound on the path
toward developing a drug. The environment in which drugs act
is complex, with many potential interaction partners. Proteins,
DNA, RNA, lipids, sugars, metabolites, and other small molecules
all have the potential to interact with a drug, and in many
cases these unexpected interactions lead to undesired and often
severe side effects. Conversely, the ability to interact with
multiple targets or drug resistance mutants can be advantageous
in certain contexts. Designing a drug with the appropriate
balance of avoidance of undesirable targets (narrow selectivity)
and coverage of one or more targets of interest (broad selectivity,
also referred to as promiscuity) is a continual drug development
challenge. In many cases this objective is attained through trial
and error, but there are rational approaches that can guide the
tuning of selectivity, and examples have been published that
illustrate a number of generalizable strategies. In this review, we
discuss fundamental principles that account for selectivity and
highlight examples where selectivity has been attained through
rational design. An understanding of the general principles that
drive selectivity should allow for more efficient design of
compounds with desirable selectivity profiles.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Whitehead Institute for Biomedical Research
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DOI of Published Version
https://doi.org/10.1021/jm2010332
