Novel HIV-1 Integrase Inhibitor Development by Virtual Screening Based on QSAR Models.

Abstract:

:HIV-1 integrase (IN) plays an important role in the life cycle of HIV and is responsible for integration of the virus into the human genome. We present computational approaches used to design novel HIV-1 IN inhibitors. We created an IN inhibitor database by collecting experimental data from the literature. We developed quantitative structure-activity relationship (QSAR) models of HIV-1 IN strand transfer (ST) inhibitors using this database. The prediction accuracy of these models was estimated by external 5-fold cross-validation as well as with an additional validation set of 308 structurally distinct compounds from the publicly accessible BindingDB database. The validated models were used to screen a small combinatorial library of potential synthetic candidates to identify hits, with a subsequent docking approach applied to further filter out compounds to arrive at a small set of potential HIV-1 IN inhibitors. As result, 236 compounds with good druglikeness properties and with correct docking poses were identified as potential candidates for synthesis. One of the six compounds finally chosen for synthesis was experimentally confirmed to inhibit the ST reaction with an IC50(ST) of 37 µM. The IN inhibitor database is available for download from http://cactus.nci.nih.gov/download/iidb/.

journal_name

Curr Top Med Chem

authors

Guasch L,Zakharov AV,Tarasova OA,Poroikov VV,Liao C,Nicklaus MC

doi

10.2174/1568026615666150813150433

subject

Has Abstract

pub_date

2016-01-01 00:00:00

pages

441-8

issue

4

eissn

1568-0266

issn

1873-4294

pii

CTMC-EPUB-69524

journal_volume

16

pub_type

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