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Predicting Resistance To Investigational Microbicide MIV‐150 Using Structure‐based methods and Fluorescence Enzyme Inhibition
Author(s) -
Muwonge Alecia Nicole,
Azeem Syeda Maryam,
Frey Kathleen M.
Publication year - 2018
Publication title -
the faseb journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.709
H-Index - 277
eISSN - 1530-6860
pISSN - 0892-6638
DOI - 10.1096/fasebj.2018.32.1_supplement.830.1
Subject(s) - microbicide , reverse transcriptase , microbicides for sexually transmitted diseases , nucleoside reverse transcriptase inhibitor , drug resistance , human immunodeficiency virus (hiv) , resistance mutation , virology , mutation , potency , pharmacology , biology , computational biology , medicine , in vitro , population , genetics , rna , gene , health services , environmental health
Microbicides may be an alternative option in HIV prevention for women affected in sub‐Saharan Africa. Many microbicides are non‐nucleoside reverse transcriptase inhibitors (NNRTIs) that target HIV reverse transcriptase (RT). Resistance mutations result in NNRTI treatment failure. These mutations may also affect the efficacy of chemically similar NNRTIs used as microbicides. The objective of this study was to predict mutations in RT that may cause resistance to investigational microbicide NNRTI MIV‐150. A computational, structure‐based approach was used to predict resistance mutations for MIV‐150. This method calculates changes in affinity (ΔA) and stability (ΔS) imparted by the mutation. The ΔA + ΔS values for K101P predict that this mutation confers high‐level resistance to MIV‐150. Based on this prediction, we analyzed the models and used Molecular Dynamics (MD) to compare the interactions of MIV‐150 with RT wild type (WT) and with RT (K101P). From MD, we found key interactions were lost with K101P. To experimentally validate our findings, we conducted a fluorescence‐based reverse transcription assay for MIV‐150 with RT (WT) and RT (K101P). Our IC 50 values showed a 170‐fold change in potency. The assays results validate that the K101P mutation confers resistance to MIV‐150. Our results are consistent with antiviral data reported in the literature. From these results, we believe that this approach is effective for predicting resistance to microbicide NNRTIs. Support or Funding Information Research is supported by Dr. Kathleen Frey at Long Island University, Brooklyn. This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .