Dynamics of Preferential Substrate Recognition in HIV-1 Protease: Redefining the Substrate Envelope

Human immunodeficiency virus type 1 (HIV-1) protease (PR) permits viral maturation by processing the gag and gag-pro-pol polyproteins. HIV-1 PR inhibitors (PIs) are used in combination antiviral therapy but the emergence of drug resistance has limited their efficacy. The rapid evolution of HIV-1 necessitates consideration of drug resistance in novel drug design. Drug-resistant HIV-1 PR variants no longer inhibited efficiently, continue to hydrolyze the natural viral substrates. Though highly diverse in sequence, the HIV-1 PR substrates bind in a conserved three-dimensional shape we termed the substrate envelope. Earlier, we showed that resistance mutations arise where PIs protrude beyond the substrate envelope, because these regions are crucial for drug binding but not for substrate recognition. We extend this model by considering the role of protein dynamics in the interaction of HIV-1 PR with its substrates. We simulated the molecular dynamics of seven PR-substrate complexes to estimate the conformational flexibility of the bound substrates. Interdependence of substrate–protease interactions might compensate for variations in cleavage-site sequences and explain how a diverse set of sequences are recognized as substrates by the same enzyme. This diversity might be essential for regulating sequential processing of substrates. We define a dynamic substrate envelope as a more accurate representation of PR–substrate interactions. This dynamic substrate envelope, described by a probability distribution function, is a powerful tool for drug design efforts targeting ensembles of resistant HIV-1 PR variants with the aim of developing drugs that are less susceptible to resistance.

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► Incorporation of protein dynamics into the substrate envelope better defines substrate specificity for HIV-1 protease.
► The dynamic substrate envelope, a probability distribution of substrate volume, can be incorporated easily into computer-aided, structure-based drug design algorithms as an added constraint.
► The balance between shape commonality and sequence diversity of the substrates is maintained by interdependence within the substrate sequences.