Open AccessRapid Optimization of the Metabolic Stability of a Human Immunodeficiency Virus Type-1 Capsid Inhibitor Using a Multistep Computational Workflow
Author(s) -
Megan E. Meuser,
Poli Adi Narayana Reddy,
Alexej Dick,
Jean Marc Maurancy,
Joseph M. Salvino,
Chantal Simon
Publication year - 2021
Publication title -
journal of medicinal chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.01
H-Index - 261
eISSN - 1520-4804
pISSN - 0022-2623
DOI - 10.1021/acs.jmedchem.0c01810
Subject(s) - workflow , capsid , chemistry , human immunodeficiency virus (hiv) , metabolic stability , stability (learning theory) , computational biology , combinatorial chemistry , biochemistry , computer science , virology , in vitro , biology , machine learning , database , gene
Poor metabolic stability of the human immunodeficiency virus type-1 (HIV-1) capsid (CA) inhibitor PF-74 is a major concern in its development toward clinical use. To improve on the metabolic stability, we employed a novel multistep computationally driven workflow, which facilitated the rapid design of improved PF-74 analogs in an efficient manner. Using this workflow, we designed three compounds that interact specifically with the CA interprotomer pocket, inhibit HIV-1 infection, and demonstrate enantiomeric preference. Moreover, using this workflow, we were able to increase the metabolic stability 204-fold in comparison to PF-74 in only three analog steps. These results demonstrate our ability to rapidly design CA compounds using a novel computational workflow that has improved metabolic stability over the parental compound. This workflow can be further applied to the redesign of PF-74 and other promising inhibitors with a stability shortfall.