Coevolutionary Analysis Identifies Protein-Protein Interaction Sites between HIV-1 Reverse Transcriptase and...

The replication of human immunodeficiency virus-1 (HIV-1) requires reverse transcription of the viral RNA genome and integration of newly synthesized pro-viral DNA into the host genome. This is mediated by the viral proteins reverse transcriptase (RT) and integrase (IN). The formation and stabilization of the pre-integration complex (PIC), which is an essential step for reverse transcription, nuclear import, chromatin targeting, and subsequent integration, involves direct and indirect modes of interaction between RT and IN proteins. While epitope-based treatments targeting IN-viral DNA and IN-RT complexes appear to be a promising combination for an anti-HIV treatment, the mechanisms of IN-RT interactions within the PIC are not well understood due to the transient nature of the protein complex and the intrinsic flexibility of its components. Here, we identify potentially interacting regions between the IN and RT proteins within the PIC through the coevolutionary analysis of amino acid sequences of the two proteins. Our results show that specific regions in the two proteins have strong coevolutionary signatures, suggesting that these regions either experience direct and prolonged interactions between them that require high affinity and/or specificity or that the regions are involved in interactions mediated by dynamic conformational changes and, hence, may involve both direct and indirect interactions. Other regions were found to exhibit weak, but positive correlations, implying interactions that are likely transient and/or have low affinity. We identified a series of specific regions of potential interactions between the IN and RT proteins (e.g., specific peptide regions within the C-terminal domain of IN were identified as potentially interacting with the Connection domain of RT). Coevolutionary analysis can serve as an important step in predicting potential interactions, thus informing experimental studies. These studies can be integrated with structural data to gain a better understanding of the mechanisms of HIV protein interactions.