Search

Darunavir (DRV) is exceptional among potent HIV-1 protease inhibitors (PIs) in high drug concentrations that are achieved in vivo. Little is known about the de novo resistance pathway for DRV. We selected for resistance to high drug concentrations against 10 PIs and their structural precursor DRV. Mutations accumulated through two pathways (anchored by protease mutations I50V or I84V). Small changes in the inhibitor P1'-equivalent position led to preferential use of one pathway over the other. Changes in the inhibitor P2'-equivalent position determined differences in potency that were retained in the resistant viruses and that impacted the selected mutations. Viral variants from the two pathways showed differential selection of compensatory mutations in Gag cleavage sites. These results reveal the high level of selective pressure that is attainable with fifth-generation PIs and how features of the inhibitor affect both the resistance pathway and the residual potency in the face of resistance.

Drugs that target the main protease (Mpro) of SARS-CoV-2 are effective therapeutics that have entered clinical use. Wide-scale use of these drugs will apply selection pressure for the evolution of resistance mutations. To understand resistance potential in Mpro, we performed comprehensive surveys of amino acid changes that can cause resistance in a yeast screen to nirmatrelvir (contained in the drug Paxlovid), and ensitrelvir (Xocova) that is currently in phase III trials. The most impactful resistance mutation (E166V) recently reported in multiple viral passaging studies with nirmatrelvir showed the strongest drug resistance score for nirmatrelvir, while P168R had the strongest resistance score for ensitrelvir. Using a systematic approach to assess potential drug resistance, we identified 142 resistance mutations for nirmatrelvir and 177 for ensitrelvir. Among these mutations, 99 caused apparent resistance to both inhibitors, suggesting a strong likelihood for the evolution of cross-resistance. Many mutations that exhibited inhibitor-specific resistance were consistent with distinct ways that each inhibitor protrudes beyond the substrate envelope. In addition, mutations with strong drug resistance scores tended to have reduced function. Our results indicate that strong pressure from nirmatrelvir or ensitrelvir will select for multiple distinct resistant lineages that will include both primary resistance mutations that weaken interactions with drug while decreasing enzyme function and secondary mutations that increase enzyme activity. The comprehensive identification of resistance mutations enables the design of inhibitors with reduced potential of developing resistance and aids in the surveillance of drug resistance in circulating viral populations.

The three pan-genotypic HCV NS3/4A protease inhibitors (PIs) currently in clinical use-grazoprevir, glecaprevir, and voxilaprevir-are quinoxaline-based P2-P4 macrocycles and thus exhibit similar resistance profiles. Using our quinoxaline-based P1-P3 macrocyclic lead compounds as an alternative chemical scaffold, we explored structure-activity relationships (SARs) at the P2 and P4 positions to develop pan-genotypic PIs that avoid drug resistance. A structure-guided strategy was used to design and synthesize two series of compounds with different P2 quinoxalines in combination with diverse P4 groups of varying sizes and shapes, with and without fluorine substitutions. Our SAR data and cocrystal structures revealed the interplay between the P2 and P4 groups, which influenced inhibitor binding and the overall resistance profile. Optimizing inhibitor interactions in the S4 pocket led to PIs with excellent antiviral activity against clinically relevant PI-resistant HCV variants and genotype 3, providing potential pan-genotypic inhibitors with improved resistance profiles.

Viruses from the Flavivirus genus infect millions of people worldwide and cause severe diseases, including recent epidemics of dengue virus (DENV), and Zika virus (ZIKV). There is currently no antiviral treatment against flavivirus infections, despite considerable efforts to develop inhibitors against essential viral enzymes including NS2B/NS3 protease. Targeting the flavivirus NS2B/NS3 protease proved to be challenging because of the conformational dynamics, topology, and electrostatic properties of the active site. Here, we report the identification of quinoxaline-based allosteric inhibitors by fragment-based drug discovery approach as a promising new drug-like scaffold to target the NS2B/NS3 protease. Enzymatic assays and mutational analysis of the allosteric site in ZIKV NS2B/NS3 protease support noncompetitive inhibition mechanism as well as engineered DENV protease construct indicating the compounds likely compete with the NS2B cofactor for binding to the protease domain. Furthermore, antiviral activity confirmed the therapeutic potential of this new inhibitor scaffold.

With the continual evolution of new strains of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) that are more virulent, transmissible, and able to evade current vaccines, there is an urgent need for effective anti-viral drugs. The SARS-CoV-2 main protease (Mpro) is a leading target for drug design due to its conserved and indispensable role in the viral life cycle. Drugs targeting Mpro appear promising but will elicit selection pressure for resistance. To understand resistance potential in Mpro, we performed a comprehensive mutational scan of the protease that analyzed the function of all possible single amino acid changes. We developed three separate high throughput assays of Mpro function in yeast, based on either the ability of Mpro variants to cleave at a defined cut-site or on the toxicity of their expression to yeast. We used deep sequencing to quantify the functional effects of each variant in each screen. The protein fitness landscapes from all three screens were strongly correlated, indicating that they captured the biophysical properties critical to Mpro function. The fitness landscapes revealed a non-active site location on the surface that is extremely sensitive to mutation, making it a favorable location to target with inhibitors. In addition, we found a network of critical amino acids that physically bridge the two active sites of the Mpro dimer. The clinical variants of Mpro were predominantly functional in our screens, indicating that Mpro is under strong selection pressure in the human population. Our results provide predictions of mutations that will be readily accessible to Mpro evolution and that are likely to contribute to drug resistance. This complete mutational guide of Mpro can be used in the design of inhibitors with reduced potential of evolving viral resistance.

APOBEC3 enzymes are key enzymes in our innate immune system regulating antiviral response in HIV and unfortunately adding diversity in cancer as they deaminate cytosine. Seven unique single and double domain APOBEC3s provide them with unique activity and specificity profiles for this deamination. Recent crystal and NMR structures of APOBEC3 complexes are unraveling the variety of epitopes involved in binding nucleic acids, including at the catalytic site, elsewhere on the catalytic domain and in the inactive N-terminal domain. The interplay between these diverse interactions is critical to uncovering the mechanisms by which APOBEC3s recognize and process their substrates.

Drug resistance is prevalent across many diseases, rendering therapies ineffective with severe financial and health consequences. Rather than accepting resistance after the fact, proactive strategies need to be incorporated into the drug design and development process to minimize the impact of drug resistance. These strategies can be derived from our experience with viral disease targets where multiple generations of drugs had to be developed to combat resistance and avoid antiviral failure. Significant efforts including experimental and computational structural biology, medicinal chemistry, and machine learning have focused on understanding the mechanisms and structural basis of resistance against direct-acting antiviral (DAA) drugs. Integrated methods show promise for being predictive of resistance and potency. In this review, we give an overview of this research for human immunodeficiency virus type 1, hepatitis C virus, and influenza virus and the lessons learned from resistance mechanisms of DAAs. These lessons translate into rational strategies to avoid resistance in drug design, which can be generalized and applied beyond viral targets. While resistance may not be completely avoidable, rational drug design can and should incorporate strategies at the outset of drug development to decrease the prevalence of drug resistance.

Broadly neutralizing antibodies (bnAbs) targeting conserved influenza A virus (IAV) hemagglutinin (HA) epitopes can provide valuable information for accelerating universal vaccine designs. Here, we report structural details for heterosubtypic recognition of HA from circulating and emerging IAVs by the human antibody 3I14. Somatic hypermutations play a critical role in shaping the HCDR3, which alone and uniquely among VH3-30 derived antibodies, forms contacts with five sub-pockets within the HA-stem hydrophobic groove. 3I14 light-chain interactions are also key for binding HA and contribute a large buried surface area spanning two HA protomers. Comparison of 3I14 to bnAbs from several defined classes provide insights to the bias selection of VH3-30 antibodies and reveals that 3I14 represents a novel structural solution within the VH3-30 repertoire. The structures reported here improve our understanding of cross-group heterosubtypic binding activity, providing the basis for advancing immunogen designs aimed at eliciting a broadly protective response to IAV.

Third generation Hepatitis C virus (HCV) NS3/4A protease inhibitors (PIs), glecaprevir and voxilaprevir, are highly effective across genotypes and against many resistant variants. Unlike earlier PIs, these compounds have fluorine substitutions on the P2-P4 macrocycle and P1 moieties. Fluorination has long been used in medicinal chemistry as a strategy to improve physicochemical properties and potency. However, the molecular basis by which fluorination improves potency and resistance profile of HCV NS3/4A PIs is not well understood. To systematically analyze the contribution of fluorine substitutions to inhibitor potency and resistance profile, we used a multi-disciplinary approach involving inhibitor design and synthesis, enzyme inhibition assays, co-crystallography, and structural analysis. A panel of inhibitors in matched pairs were designed with and without P4 cap fluorination, tested against WT protease and the D168A resistant variant, and a total of 22 high-resolution co-crystal structures were determined. While fluorination did not significantly improve potency against the WT protease, PIs with fluorinated P4 caps retained much better potency against the D168A protease variant. Detailed analysis of the co-crystal structures revealed that PIs with fluorinated P4 caps can sample alternate binding conformations that enable adapting to structural changes induced by the D168A substitution. Our results elucidate molecular mechanisms of fluorine-specific inhibitor interactions that can be leveraged in avoiding drug resistance.

COVID-19 caused by SARS-CoV-2 has become a global pandemic requiring the development of interventions for the prevention or treatment to curtail mortality and morbidity. No vaccine to boost mucosal immunity, or as a therapeutic, has yet been developed to SARS-CoV-2. In this study, we discover and characterize a cross-reactive human IgA monoclonal antibody, MAb362. MAb362 binds to both SARS-CoV and SARS-CoV-2 spike proteins and competitively blocks ACE2 receptor binding, by overlapping the ACE2 structural binding epitope. Furthermore, MAb362 IgA neutralizes both pseudotyped SARS-CoV and SARS-CoV-2 in 293 cells expressing ACE2. When converted to secretory IgA, MAb326 also neutralizes authentic SARS-CoV-2 virus while the IgG isotype shows no neutralization. Our results suggest that SARS-CoV-2 specific IgA antibodies, such as MAb362, may provide effective immunity against SARS-CoV-2 by inducing mucosal immunity within the respiratory system, a potentially critical feature of an effective vaccine.

Type 1 diabetes (T1D) is caused by the autoimmune destruction of pancreatic beta cells. Pluripotent stem cells can now be differentiated into beta cells, thus raising the prospect of a cell replacement therapy for T1D. However, autoimmunity would rapidly destroy newly transplanted beta cells. Using a genome-scale CRISPR screen in a mouse model for T1D, we show that deleting RNLS, a genome-wide association study candidate gene for T1D, made beta cells resistant to autoimmune killing. Structure-based modelling identified the U.S. Food and Drug Administration-approved drug pargyline as a potential RNLS inhibitor. Oral pargyline treatment protected transplanted beta cells in diabetic mice, thus leading to disease reversal. Furthermore, pargyline prevented or delayed diabetes onset in several mouse models for T1D. Our results identify RNLS as a modifier of beta cell vulnerability and as a potential therapeutic target to avert beta cell loss in T1D.

Twinning is a crystal-growth anomaly in which protein monomers exist in different orientations but are related in a specific way, causing diffraction reflections to overlap. Twinning imposes additional symmetry on the data, often leading to the assignment of a higher symmetry space group. Specifically, in merohedral twinning, reflections from each monomer overlap and require a twin law to model unique structural data from overlapping reflections. Neglecting twinning in the crystallographic analysis of quasi-rotationally symmetric homo-oligomeric protein structures can mask the degree of structural non-identity between monomers. In particular, any deviations from perfect symmetry will be lost if higher than appropriate symmetry is applied during crystallographic analysis. Such cases warrant choosing between the highest symmetry space group possible or determining whether the monomers have distinguishable structural asymmetries and thus require a lower symmetry space group and a twin law. Using hexagonal cocrystals of HIV-1 protease, a C 2-symmetric homodimer whose symmetry is broken by bound ligand, it is shown that both assigning a lower symmetry space group and applying a twin law during refinement are critical to achieving a structural model that more accurately fits the electron density. By re-analyzing three recently published HIV-1 protease structures, improvements in nearly every crystallographic metric are demonstrated. Most importantly, a procedure is demonstrated where the inhibitor can be reliably modeled in a single orientation. This protocol may be applicable to many other homo-oligomers in the PDB.

With the continual evolution of new strains of SARS-CoV-2 that are more virulent, transmissible, and able to evade current vaccines, there is an urgent need for effective anti-viral drugs. SARS-CoV-2 main protease (Mpro) is a leading target for drug design due to its conserved and indispensable role in the viral life cycle. Drugs targeting Mpro appear promising but will elicit selection pressure for resistance. To understand resistance potential in Mpro, we performed a comprehensive mutational scan of the protease that analyzed the function of all possible single amino acid changes. We developed three separate high-throughput assays of Mpro function in yeast, based on either the ability of Mpro variants to cleave at a defined cut-site or on the toxicity of their expression to yeast. We used deep sequencing to quantify the functional effects of each variant in each screen. The protein fitness landscapes from all three screens were strongly correlated, indicating that they captured the biophysical properties critical to Mpro function. The fitness landscapes revealed a non-active site location on the surface that is extremely sensitive to mutation making it a favorable location to target with inhibitors. In addition, we found a network of critical amino acids that physically bridge the two active sites of the Mpro dimer. The clinical variants of Mpro were predominantly functional in our screens, indicating that Mpro is under strong selection pressure in the human population. Our results provide predictions of mutations that will be readily accessible to Mpro evolution and that are likely to contribute to drug resistance. This complete mutational guide of Mpro can be used in the design of inhibitors with reduced potential of evolving viral resistance.

Over the last few decades, protein NMR isotope labeling methods using E. coli based expression have revolutionized the information accessible from biomolecular NMR experiments. Selective labeling of a protein of interest in a multi-protein complex can significantly reduce the number of cross-peaks and allow for study of large protein complexes. However, limitations still remain since some proteins are not stable independently and cannot be separately labeled in either NMR active isotope enriched or unenriched media and reconstituted into a multimeric complex. To overcome this limitation, the LEGO-NMR method was previously developed using protein expression plasmids containing T7 or araBAD promoters to separately express proteins in the same E. coli after changing between labeled and unlabeled media. Building on this, we developed a method to label the Human Immunodeficiency Virus type 1 viral infectivity factor (HIV-1 Vif), a monomerically unstable protein, in complex with CBFβ, it’s host binding partner. We designed a dual promoter plasmid containing both T7 and araBAD promoters to independently control the expression of HIV-1 Vif in NMR active isotope enriched media and CBFβ in unenriched media. Using this method, we assigned the backbone resonance and directly observed the binding of HIV-1 Vif with APOBEC3G, a host restriction factor to HIV-1.

SummaryInfluenza viruses pose severe public health threats; they cause millions of infections and tens of thousands of deaths annually in the US. Influenza viruses are extensively pleomorphic, in both shape and size as well as organization of viral structural proteins. Analysis of influenza morphology and ultrastructure can help elucidate viral structure-function relationships as well as aid in therapeutics and vaccine development. While cryo-electron tomography (cryoET) can depict the 3D organization of pleomorphic influenza, the low signal-to-noise ratio inherent to cryoET and extensive viral heterogeneity have precluded detailed characterization of influenza viruses. In this report, we developed a cryoET processing pipeline leveraging convolutional neural networks (CNNs) to characterize the morphological architecture of the A/Puerto Rico/8/34 (H1N1) influenza strain. Our pipeline improved the throughput of cryoET analysis and accurately identified viral components within tomograms. Using this approach, we successfully characterized influenza viral morphology, glycoprotein density, and conduct subtomogram averaging of HA glycoproteins. Application of this processing pipeline can aid in the structural characterization of not only influenza viruses, but other pleomorphic viruses and infected cells.Graphical abstract

Viral proteases are diverse in structure, oligomeric state, catalytic mechanism, and substrate specificity. This chapter focuses on proteases from viruses that are relevant to human health: human immunodeficiency virus subtype 1 (HIV-1), hepatitis C (HCV), human T-cell leukemia virus type 1 (HTLV-1), flaviviruses, enteroviruses, and coronaviruses. The proteases of HIV-1 and HCV have been successfully targeted for therapeutics, with picomolar FDA-approved drugs currently used in the clinic. The proteases of HTLV-1 and the other virus families remain emerging therapeutic targets at different stages of the drug development process. This chapter provides an overview of the current knowledge on viral protease structure, mechanism, substrate recognition, and inhibition. Particular focus is placed on recent advances in understanding the molecular basis of diverse substrate recognition and resistance, which is essential toward designing novel protease inhibitors as antivirals.

Rupintrivir targets the 3C cysteine proteases of the picornaviridae family, which includes rhinoviruses and enteroviruses that cause a range of human diseases. Despite being a pan-3C protease inhibitor, rupintrivir activity is extremely weak against the homologous 3C-like protease of SARS-CoV-2. In this study, the crystal structures of rupintrivir were determined bound to enterovirus 68 (EV68) 3C protease and the 3C-like main protease (Mpro) from SARS-CoV-2. While the EV68 3C protease-rupintrivir structure was similar to previously determined complexes with other picornavirus 3C proteases, rupintrivir bound in a unique conformation to the active site of SARS-CoV-2 Mpro splitting the catalytic cysteine and histidine residues. This bifurcation of the catalytic dyad may provide a novel approach for inhibiting cysteine proteases.

Investigating the relationships between protein function and fitness provides keys for understanding biochemical mechanisms that underly evolution. Mutations with partial fitness defects can delineate the threshold of biochemical function required for viability. We utilized a previous deep mutational scan of HIV-1 protease (PR) to identify variants with 15–45 per cent defects in replication and analysed the biochemical function of eight variants (L10M, L10S, V32C, V32I, A71V, A71S, Q92I, Q92N). We purified each variant and assessed the efficiency of peptide cleavage for three cut sites (MA-CA, TF-PR, and PR-RT) as well as gel-based analyses of processing of purified Gag. The cutting activity of at least one site was perturbed relative to WT protease for all variants, consistent with cutting activity being a primary determinant of fitness effects. We examined the correlation of fitness defects with cutting activity of different sites. MA-CA showed the weakest correlation (R2 = 0.02) with fitness, suggesting relatively weak coupling with viral replication. In contrast, cutting of the TF-PR site showed the strongest correlation with fitness (R2 = 0.53). Cutting at the TF-PR site creates a new PR protein with a free N-terminus that is critical for activity. Our findings indicate that increasing the pool of active PR is rate limiting for viral replication, making this an ideal step to target with inhibitors.

Antibodies elicited by infection accumulate somatic mutations in germinal centers that can increase affinity for cognate antigens. We analyzed 6 independent groups of clonally related severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) Spike receptor-binding domain (RBD)-specific antibodies from 5 individuals shortly after infection and later in convalescence to determine the impact of maturation over months. In addition to increased affinity and neutralization potency, antibody evolution changed the mutational pathways for the acquisition of viral resistance and restricted neutralization escape options. For some antibodies, maturation imposed a requirement for multiple substitutions to enable escape. For certain antibodies, affinity maturation enabled the neutralization of circulating SARS-CoV-2 variants of concern and heterologous sarbecoviruses. Antibody-antigen structures revealed that these properties resulted from substitutions that allowed additional variability at the interface with the RBD. These findings suggest that increasing antibody diversity through prolonged or repeated antigen exposure may improve protection against diversifying SARS-CoV-2 populations, and perhaps against other pandemic threat coronaviruses.

Drug resistance impacts the effectiveness of many new therapeutics. Mutations in the therapeutic target confer resistance, however deciphering which mutations, often remote from the enzyme active site, drive resistance is challenging. In a series of Pneumocystis Jirovecii dihydrofolate reductase variants we elucidate which interactions are key bellwethers to confer resistance to trimethoprim using homology modeling, molecular dynamics and machine learning. Six molecular features involving mainly residues that did not vary, were the best indicators of resistance.

A structure-guided design strategy was used to improve the resistance profile of HIV-1 protease inhibitors by optimizing hydrogen bonding and van der Waals interactions with the protease while staying within the substrate envelope. Stereoisomers of 4-(1-hydroxyethyl)benzene and 4-(1,2-dihydroxyethyl)benzene moieties were explored as P2' ligands providing pairs of diastereoisomers epimeric at P2', which exhibited distinct potency profiles depending on the configuration of the hydroxyl group and size of the P1' group. While compounds with the 4-(1-hydroxyethyl)benzene P2' moiety maintained excellent antiviral potency against a panel of multidrug-resistant HIV-1 strains, analogues with the polar 4-(1,2-dihydroxyethyl)benzene moiety were less potent, and only the (R)-epimer incorporating a larger 2-ethylbutyl P1' group showed improved potency. Crystal structures of protease-inhibitor complexes revealed strong hydrogen bonding interactions of both (R)- and (S)-stereoisomers of the hydroxyethyl group with Asp30'. Notably, the (R)-dihydroxyethyl group was involved in a unique pattern of direct hydrogen bonding interactions with the backbone amides of Asp29' and Asp30'. The SAR data and analysis of crystal structures provide insights for optimizing these promising HIV-1 protease inhibitors.

Discovery and optimization of small molecule inhibitors as therapeutic drugs have immensely benefited from rational structure-based drug design. With recent advances in high-resolution structure determination, computational power, and machine learning methodology, it is becoming more tractable to elucidate the structural basis of drug potency. However, the applicability of machine learning models to drug design is limited by the interpretability of the resulting models in terms of feature importance. Here, we take advantage of the large number of available inhibitor-bound HIV-1 protease structures and associated potencies to evaluate inhibitor diversity and machine learning models to predict ligand affinity. First, using a hierarchical clustering approach, we grouped HIV-1 protease inhibitors and identified distinct core structures. Explicit features including protein-ligand interactions were extracted from high-resolution cocrystal structures as 3D-based fingerprints. We found that a gradient boosting machine learning model with this explicit feature attribution can predict binding affinity with high accuracy. Finally, Shapley values were derived to explain local feature importance. We found specific van der Waals (vdW) interactions of key protein residues are pivotal for the predicted potency. Protein-specific and interpretable prediction models can guide the optimization of many small molecule drugs for improved potency.

The potent antiretroviral protein APOBEC3G (A3G) specifically targets and deaminates deoxycytidine nucleotides, generating deoxyuridine, in single stranded DNA (ssDNA) intermediates produced during HIV replication. A non-catalytic domain in A3G binds strongly to RNA, an interaction crucial for recruitment of A3G to the virion; yet, A3G displays no deamination activity for cytidines in viral RNA. Here, we report NMR and molecular dynamics (MD) simulation analysis for interactions between A3Gctd and multiple substrate or non-substrate DNA and RNA, in combination with deamination assays. NMR ssDNA-binding experiments revealed that the interaction with residues in helix1 and loop1 (T201-L220) distinguishes the binding mode of substrate ssDNA from non-substrate. Using 2′-deoxy-2′-fluorine substituted cytidines, we show that a 2′-endo sugar conformation of the target deoxycytidine is favored for substrate binding and deamination. Trajectories of the MD simulation indicate that a ribose 2′-hydroxyl group destabilizes the π-π stacking of the target cytosine and H257, resulting in dislocation of the target cytosine base from the catalytic position. Interestingly, APOBEC3A, which can deaminate ribocytidines, retains the ribocytidine in the catalytic position throughout the MD simulation. Our results indicate that A3Gctd catalytic selectivity against RNA is dictated by both the sugar conformation and 2′-hydroxyl group.

Direct acting antivirals have dramatically increased the efficacy and tolerability of hepatitis C treatment, but drug resistance has emerged with some of these inhibitors, including non-structural protein 3/4A protease inhibitors (PIs). Although many co-crystal structures of PIs with the NS3/4A protease have been reported, a systematic review of these crystal structures in the context of the rapidly emerging drug resistance especially for early PIs has not been performed. To provide a framework for designing better inhibitors with higher barriers to resistance, we performed a quantitative structural analysis using co-crystal structures and models of HCV NS3/4A protease in complex with natural substrates and inhibitors. By comparing substrate structural motifs and active site interactions with inhibitor recognition, we observed that the selection of drug resistance mutations correlates with how inhibitors deviate from viral substrates in molecular recognition. Based on this observation, we conclude that guiding the design process with native substrate recognition features is likely to lead to more robust small molecule inhibitors with decreased susceptibility to resistance.

Retroviral proteases (PR) have a unique specificity that allows cleavage of sites with or without a P1’ proline. A P1’ proline is required at the MA/CA cleavage site due to its role in a post-cleavage conformational change in the capsid protein. However, the HIV-1 PR prefers to have large hydrophobic amino acids flanking the scissile bond, suggesting PR recognizes two different classes of substrate sequences. We analyzed the cleavage rate of over 150 iterations of six different HIV-1 cleavage sites to explore rate determinants of cleavage. We found that cleavage rates are strongly influenced by the two amino acids flanking the amino acids at the scissile bond (P2-P1/P1’-P2’), with two complementary sets of rules. When P1’ is proline, the P2 side chain interacts with a polar region in the S2 subsite of the PR, while the P2’ amino acid interacts with a hydrophobic region of the S2’ subsite. When P1’ is not proline, the orientations of the P2 and P2’ side chains with respect to the scissile bond are reversed; P2 residues interact with a hydrophobic face of the S2 subsite while the P2’ amino acid usually engages hydrophilic amino acids in the S2’ subsite. These results reveal that the HIV-1 PR has evolved bi-functional S2 and S2’ subsites to accommodate the steric effects imposed by a P1’ proline on the orientation of P2 and P2’ substrate side chains. These results also suggest a new strategy for inhibitor design to engage the multiple specificities in these subsites.