Background: Non-nucleoside reverse transcriptase inhibitors (NNRTIs) are used in
combination with antiretroviral therapy to suppress viral loads in HIV patients. The chemical design
of NNRTIs has changed in recent years in response to resistance-associated mutations (RAMs) and
resistance. NNRTIs are chemically diverse compounds that bind an allosteric site of HIV RT. Resistance-
associated mutations (RAMs) identified in HIV patients are associated with NNRTI resistance.
RAMs confer amino acid changes that alter both structural and physiochemical properties
of the allosteric site. Ultimately, these changes reduce NNRTI affinity. Previously, we used a combination
of computational and experimental methods to analyze and validate RAMs for 3 diarylpyrimidine
Objective: The objective of this study is to apply these methods to other chemically diverse, non-
Materials and Methods: We selected MIV-150 (experimental microbicide) and doravirine for this
study. A computational and molecular modeling strategy was used to evaluate the effects of RAMs.
Calculated changes in drug affinity and stability (ΔS + ΔA) were used to determine overall resistance
levels: susceptible, low, intermediate, and high. The ΔS + ΔA values for K101P suggest
that this mutation confers intermediate/high-level resistance to MIV-150, but remains susceptible to
doravirine. Based on the determined resistance levels, we analyzed the models and used Molecular
Dynamics (MD) to compare the interactions of MIV-150/doravirine with RT wild-type (WT) and
RT (K101P). From MD, we found that key interactions were lost with RT (K101P), but were retained
with doravirine. To experimentally validate our findings, we conducted a fluorescence-based
reverse transcription assay for MIV-150 with RT (WT) and RT (K101P). IC50 values determined in
assays showed a 101-fold change in potency for MIV-150, but essentially no change for doravirine.
Results: Our computational and experimental results are also consistent with antiviral data reported
in the literature.
Conclusion: We believe that this approach is effective for analyzing mutations to determine resistance
profiles for chemically diverse NNRTIs in development.