Structural Studies of a Rationally Selected Multi-Drug Resistant HIV-1 Protease Reveal Synergistic Effect of Distal Mutations on Flap Dynamics

Design, Synthesis, and Biological Evaluation of Darunavir Analogs as HIV-1 Protease Inhibitors

Darunavir, a frontline treatment for HIV infection, faces limitations due to emerging multidrug resistant (MDR) HIV strains, necessitating the development of analogs with improved activity. In this study, a combinatorial in silico approach was used to initially design a series of HIV-1 PI analogs with modifications at key sites, P1' and P2', to enhance interactions with HIV-1 PR. Fifteen analogs with promising binding scores were selected for synthesis and evaluated for the HIV-1 PR inhibition activity. The variation of P2' substitution was found to be effective, as seen in 5aa (1.54 nM), 5ad (0.71 nM), 5ac (0.31 nM), 5ae (0.28 nM), and 5af (1.12 nM), featuring halogen, aliphatic, and alkoxy functionalities on the phenyl sulfoxide motif exhibited superior inhibition against HIV-1 PR compared to DRV, with minimal cytotoxicity observed in Vero and 293T cell lines. Moreover, computational studies demonstrated the potential of selected analogs to inhibit various HIV-1 PR mutations, including I54M and I84V. Further structural dynamics and energetic analyses confirmed the stability and binding affinity of promising analogs, particularly 5ae, which showed strong interactions with key residues in HIV-1 PR. Overall, this study underscores the importance of flexible moieties and interaction enhancement at the S2' subsite of HIV-1 PR in developing effective DRV analogs to combat HIV and other global health issues.

Premature Activation of the HIV-1 Protease Is Influenced by Polymorphisms in the Hinge Region

HIV-1 protease inhibitors are an essential component of antiretroviral therapy. However, drug resistance is a pervasive issue motivating a persistent search for novel therapies. Recent reports found that when protease activates within the host cell's cytosol, it facilitates the pyroptotic killing of infected cells. This has led to speculation that promoting protease activation, rather than inhibiting it, could help to eradicate infected cells and potentially cure HIV-1 infection. Here, we used a nanoscale flow cytometry-based assay to characterize protease resistance mutations and polymorphisms. We quantified protease activity, viral concentration, and premature protease activation and confirmed previous findings that major resistance mutations generally destabilize the protease structure. Intriguingly, we found evidence that common polymorphisms in the hinge domain of protease can influence its susceptibility to premature activation. This suggests that viral heterogeneity could pose a considerable challenge for therapeutic strategies aimed at inducing premature protease activation in the future.

Natural Polymorphisms D60E and I62V Stabilize a Closed Conformation in HIV-1 Protease in the Absence of an Inhibitor or Substrate

HIV infection remains a global health issue plagued by drug resistance and virological failure. Natural polymorphisms (NPs) contained within several African and Brazilian protease (PR) variants have been shown to induce a conformational landscape of more closed conformations compared to the sequence of subtype B prevalent in North America and Western Europe. Here we demonstrate through experimental pulsed EPR distance measurements and molecular dynamic (MD) simulations that the two common NPs D60E and I62V found within subtypes F and H can induce a closed conformation when introduced into HIV-1PR subtype B. Specifically, D60E alters the conformation in subtype B through the formation of a salt bridge with residue K43 contained within the nexus between the flap and hinge region of the HIV-1 PR fold. On the other hand, I62V modulates the packing of the hydrophobic cluster of the cantilever and fulcrum, also resulting in a more closed conformation.

HIV-1 protease with 10 lopinavir and darunavir resistance mutations exhibits altered inhibition, structural rearrangements and extreme dynamics

Antiretroviral drug resistance is a therapeutic obstacle for people with HIV. HIV protease inhibitors darunavir and lopinavir are recommended for resistant infections. We characterized a protease mutant (PR10x) derived from a highly resistant clinical isolate including 10 mutations associated with resistance to lopinavir and darunavir. Compared to the wild-type protease, PR10x exhibits ∼3-fold decrease in catalytic efficiency and Ki values of 2-3 orders of magnitude worse for darunavir, lopinavir, and potent investigational inhibitor GRL-519. Crystal structures of the mutant were solved in a ligand-free form and in complex with GRL-519. The structures show altered interactions in the active site, flap-core interface, hydrophobic core, hinge region, and 80s loop compared to the corresponding wild-type protease structures. The ligand-free crystal structure exhibits a highly curled flap conformation which may amplify drug resistance. Molecular dynamics simulations performed for 1 μs on ligand-free dimers showed extremely large fluctuations in the flaps for PR10x compared to equivalent simulations on PR with a single L76V mutation or wild-type protease. This analysis offers insight about the synergistic effects of mutations in highly resistant variants.

Assessment of a Computational Approach to Predict Drug Resistance Mutations for HIV, HBV and SARS-CoV-2

Viral resistance is a worldwide problem mitigating the effectiveness of antiviral drugs. Mutations in the drug-targeting proteins are the primary mechanism for the emergence of drug resistance. It is essential to identify the drug resistance mutations to elucidate the mechanism of resistance and to suggest promising treatment strategies to counter the drug resistance. However, experimental identification of drug resistance mutations is challenging, laborious and time-consuming. Hence, effective and time-saving computational structure-based approaches for predicting drug resistance mutations are essential and are of high interest in drug discovery research. However, these approaches are dependent on accurate estimation of binding free energies which indirectly correlate to the computational cost. Towards this goal, we developed a computational workflow to predict drug resistance mutations for any viral proteins where the structure is known. This approach can qualitatively predict the change in binding free energies due to mutations through residue scanning and Prime MM-GBSA calculations. To test the approach, we predicted resistance mutations in HIV-RT selected by (-)-FTC and demonstrated accurate identification of the clinical mutations. Furthermore, we predicted resistance mutations in HBV core protein for GLP-26 and in SARS-CoV-2 3CLpro for nirmatrelvir. Mutagenesis experiments were performed on two predicted resistance and three predicted sensitivity mutations in HBV core protein for GLP-26, corroborating the accuracy of the predictions.

The structural, dynamic, and thermodynamic basis of darunavir resistance of a heavily mutated HIV-1 protease using molecular dynamics simulation

The human immunodeficiency virus type 1 protease (HIV-1 PR) is an important enzyme in the life cycle of the HIV virus. It cleaves inactive pre-proteins of the virus and changes them into active proteins. Darunavir (DRV) suppresses the wild-type HIV-1 PR (WT-Pr) activity but cannot inhibit some mutant resistant forms (MUT-Pr). Increasing knowledge about the resistance mechanism can be helpful for designing more effective inhibitors. In this study, the mechanism of resistance of a highly MUT-Pr strain against DRV was investigated. For this purpose, complexes of DRV with WT-Pr (WT-Pr-D) and MUT-Pr (MUT-Pr-D) were studied by all-atom molecular dynamics simulation in order to extract the dynamic and energetic properties. Our data revealed that mutations increased the flap-tip flexibility due to the reduction of the flap-flap hydrophobic interactions. So, the protease’s conformation changed from a closed state to a semi-open state that can facilitate the disjunction of DRV from the active site. On the other hand, energy analysis limited to the final basins of the energy landscape indicated that the entropy of binding of DRV to MUT-Pr was more favorable than that of WT-Pr. However, the enthalpy penalty overcomes it and makes binding more unfavorable relative to the WT-Pr. The unfavorable interaction of DRV with R8, I50, I84, D25′, and A28′ residues in MUT-Pr-D relative to WT-Pr-D is the reason for this enthalpy penalty. Thus, mutations drive resistance to DRV. The hydrogen bond analysis showed that compared with WT-Pr, the hydrogen bonds between DRV and the active-site residues of MUT-Pr were disrupted.

Prune homolog 2 with BCH domain (PRUNE2) gene expression is associated with feed efficiency-related traits in Nelore steers

Animal feeding is a critical factor in increasing producer profitability. Improving feed efficiency can help reduce feeding costs and reduce the environmental impact of beef production. Candidate genes previously identified for this trait in differential gene expression studies (e.g., case-control studies) have not examined continuous gene-phenotype variation, which is a limitation. The aim of this study was to investigate the association between the expression of five candidate genes in the liver, measured by quantitative real-time PCR and feed-related traits. We adopted a linear mixed model to associate liver gene expression from 52 Nelore steers with the following production traits: average daily gain (ADG), body weight (BW), dry matter intake (DMI), feed conversion ratio (FCR), feed efficiency (FE), Kleiber index (KI), metabolic body weight (MBW), residual feed intake (RFI), and relative growth ratio (RGR). The total expression of the prune homolog 2 (PRUNE2) gene was significantly associated with DMI, FCR, FE, and RFI (P < 0.05). Furthermore, we have identified a new transcript of PRUNE2 (TCONS_00027692, GenBank MZ041267) that was inversely correlated with FCR and FE (P < 0.05), in contrast to the originally identified PRUNE2 transcript. The cytochrome P450 subfamily 2B (CYP2B6), early growth response protein 1 (EGR1), collagen type I alpha 1 chain (COL1A1), and connective tissue growth factor (CTGF) genes were not associated with any feed efficiency-related traits (P > 0.05). The findings reported herein suggest that PRUNE2 expression levels affects feed efficiency-related traits variation in Nelore steers.

Age-associated changes in gene expression in the anterior pituitary glands of female Japanese black cattle

Proper functioning of the anterior pituitary (AP) gland is imperative, however, is suppressed by aging via unclear mechanisms. Therefore, we identified differentially expressed genes (DEGs) in the AP glands of Japanese Black young heifers (approximately 22 months old) compared to old cows (approximately 120 months old) via deep sequencing of the transcriptome (RNA-seq) to characterize potentially important pathways. The young and old AP glands expressed 20,171 annotated genes. Of the total transcripts per million, approximately 41.6% and 35.5% were the sum of seven AP hormone genes in young and old AP glands, respectively, with difference observed in the sum between the young and old AP glands (P < 0.05). Moreover, we identified 48 downregulated genes and 218 upregulated genes in old compared to young AP glands (P < 0.01, fold change > 120%). The DEGs included 1 cytokine (AIMP1), 3 growth factors (NRG2, PTN, and TGFB1), 1 receptor-associated protein gene (AGTRAP), and 10 receptor genes, including PRLHR and two orphan G-protein-coupled receptors (GPR156 and GPR176). Metascape analysis of the DEGs revealed "Peptide metabolic process," "Regulation of hormone levels," and "Peptide hormone processing" as enriched pathways. Furthermore, Ingenuity Pathway analysis of the DEGs revealed (1) a network of 24 genes (including GPR156 and PRLHR) named "Neurological disease, organismal injury and abnormalities, and psychological disorders", and (2) two canonical pathways (P < 0.01), namely "Huntington's disease signaling", and "AMPK signaling". Thus, the findings of the current study revealed relevant DEGs, while identifying important pathways that occur during aging in AP glands of female cattle.

Multiple Molecular Dynamics Simulations and Energy Analysis Unravel the Dynamic Properties and Binding Mechanism of Mutants HIV-1 Protease with DRV and CA-p2

PRS17, a variant of human immunodeficiency virus type I protease (HIV-1 PR), has 17 mutated residues showing high levels of multidrug resistance. To describe the effects of these mutated residues on the dynamic properties and the binding mechanism of PR with substrate and inhibitor, focused on six systems (two complexes of WT PR and PRS17 with inhibitor Darunavir (DRV), two complexes of WT PR and PRS17 with substrate analogue CA-p2, two unligand WT PR and PRS17), we performed multiple molecular dynamics (MD) simulations combined with MM-PBSA and solvated interaction energy (SIE) methods. For both the unligand PRs and ligand-PR complexes, the results from simulations revealed 17 mutated residues alter the flap-flap distance, the distance from flap regions to catalytic sites, and the curling degree of the flap tips. These mutated residues changed the flexibility of the flap region in PR, and thus affected its binding energy with DRV and CA-p2, resulting in differences in sensitivity. Hydrophobic cavity makes an important contribution to the binding of PR and ligands. And most noticeable of all, the binding of the guanidine group in CA-p2 and Arg8' of PRS17 is useful for increasing their binding ability. These results have important guidance for the further design of drugs against multidrug resistant PR. IMPORTANCE Developing effective anti-HIV inhibitors is the current requirement to cope with the emergence of the resistance of mutants. Compared with the experiments, MD simulations along with energy calculations help reduce the time and cost of designing new inhibitors. Based on our simulation results, we propose two factors that may help design effective inhibitors against HIV-1 PR: (i) importance of hydrophobic cavity, and (ii) introduction of polar groups similar to the guanidine group.

Hybrid QM/MM Free-Energy Evaluation of Drug-Resistant Mutational Effect on the Binding of an Inhibitor Indinavir to HIV-1 Protease

A human immunodeficiency virus-1 (HIV-1) protease is a homodimeric aspartic protease essential for the replication of HIV. The HIV-1 protease is a target protein in drug discovery for antiretroviral therapy, and various inhibitor molecules of transition state analogues have been developed. However, serious drug-resistant mutants have emerged. For understanding the molecular mechanism of the drug resistance, an accurate examination of the impacts of the mutations on ligand binding and enzymatic activity is necessary. Here, we present a molecular simulation study on the ligand binding of indinavir, a potent transition state analogue inhibitor, to the wild-type protein and a V82T/I84V drug-resistant mutant of the HIV-1 protease. We employed a hybrid ab initio quantum mechanical/molecular mechanical (QM/MM) free-energy optimization technique which combines a highly accurate QM description of the ligand molecule and its interaction with statistically ample conformational sampling of the MM protein environment by long-time molecular dynamics simulations. Through the free-energy calculations of protonation states of catalytic groups at the binding pocket and of the ligand-binding affinity changes upon the mutations, we successfully reproduced the experimentally observed significant reduction of the binding affinity upon the drug-resistant mutations and elucidated the underlying molecular mechanism. The present study opens the way for understanding the molecular mechanism of drug resistance through the direct quantitative comparison of ligand binding and enzymatic reaction with the same accuracy.

Prediction and molecular field view of drug resistance in HIV-1 protease mutants

Conquering the mutational drug resistance is a great challenge in anti-HIV drug development and therapy. Quantitatively predicting the mutational drug resistance in molecular level and elucidating the three dimensional structure-resistance relationships for anti-HIV drug targets will help to improve the understanding of the drug resistance mechanism and aid the design of resistance evading inhibitors. Here the MB-QSAR (Mutation-dependent Biomacromolecular Quantitative Structure Activity Relationship) method was employed to predict the molecular drug resistance of HIV-1 protease mutants towards six drugs, and to depict the structure resistance relationships in HIV-1 protease mutants. MB-QSAR models were constructed based on a published data set of K_i values for HIV-1 protease mutants against drugs. Reliable MB-QSAR models were achieved and these models display both well internal and external prediction abilities. Interpreting the MB-QSAR models supplied structural information related to the drug resistance as well as the guidance for the design of resistance evading drugs. This work showed that MB-QSAR method can be employed to predict the resistance of HIV-1 protease caused by polymorphic mutations, which offer a fast and accurate method for the prediction of other drug target within the context of 3D structures.

Co-evolution of drug resistance and broadened substrate recognition in HIV protease variants isolated from an Escherichia coli genetic selection system

A genetic selection system for activity of HIV protease is described that is based on a synthetic substrate constructed as a modified AraC regulatory protein that when cleaved stimulate L-arabinose metabolism in an Escherichia coli araC strain. Growth stimulation on selective plates was shown to depend on active HIV protease and the scissile bond in the substrate. In addition, the growth of cells correlated well with the established cleavage efficiency of the sites in the viral polyprotein, Gag, when these sites were individually introduced into the synthetic substate of the selection system. Plasmids encoding protease variants selected based on stimulation of cell growth in the presence of saquinavir or cleavage of a site not cleaved by wild-type protease, were indistinguishable with respect to both phenotypes. Also, both groups of selected plasmids encoded side chain substitutions known from clinical isolates or displayed different side chain substitutions but at identical positions. One highly frequent side chain substitution, E34V, not regarded as a major drug resistance substitution was found in variants obtained under both selective conditions and is suggested to improve protease processing of the synthetic substrate. This substitution is away from the substrate-binding cavity and together with other substitutions in the selected reading frames supports the previous suggestion of a substrate-binding site extended from the active site binding pocket itself.

Revertant mutation V48G alters conformational dynamics of highly drug resistant HIV protease PRS17

Drug resistance is a serious problem for controlling the HIV/AIDS pandemic. Current antiviral drugs show several orders of magnitude worse inhibition of highly resistant clinical variant PRS17 of HIV-1 protease compared with wild-type protease. We have analyzed the effects of a common resistance mutation G48V in the flexible flaps of the protease by assessing the revertant PRS17_V48G for changes in enzyme kinetics, inhibition, structure, and dynamics. Both PRS17 and the revertant showed about 10-fold poorer catalytic efficiency than wild-type enzyme (0.55 and 0.39 μM^-1min^-1 compared to 6.3 μM^-1min^-1). Clinical inhibitors, amprenavir and darunavir, showed 2-fold and 8-fold better inhibition, respectively, of the revertant than of PRS17, although the inhibition constants for PRS17_V48G were still 25 to 1,200-fold worse than for wild-type protease. Crystal structures of inhibitor-free revertant and amprenavir complexes with revertant and PRS17 were solved at 1.3-1.5 Å resolution. The amprenavir complexes of PRS17_V48G and PRS17 showed no significant differences in the interactions with inhibitor, although changes were observed in the conformation of Phe53 and the interactions of the flaps. The inhibitor-free structure of the revertant showed flaps in an open conformation, however, the flap tips do not have the unusual curled conformation seen in inhibitor-free PRS17. Molecular dynamics simulations were run for 1 μs on the two inhibitor-free mutants and wild-type protease. PRS17 exhibited higher conformational fluctuations than the revertant, while the wild-type protease adopted the closed conformation and showed the least variation. The second half of the simulations captured the transition of the flaps of PRS17 from a closed to a semi-open state, whereas the flaps of PRS17_V48G tucked into the active site and the wild-type protease retained the closed conformation. These results suggest that mutation G48V contributes to drug resistance by altering the conformational dynamics of the flaps.

Novel HIV PR inhibitors with C4-substituted bis-THF and bis-fluoro-benzyl target the two active site mutations of highly drug resistant mutant PRS17

The emergence of multidrug resistant (MDR) HIV strains severely reduces the effectiveness of antiretroviral therapy. Clinical inhibitor darunavir (1) has picomolar binding affinity for HIV-1 protease (PR), however, drug resistant variants like PR^S17 show poor inhibition by 1, despite the presence of only two mutated residues in the inhibitor-binding site. Antiviral inhibitors that target MDR proteases like PR^S17 would be valuable as therapeutic agents. Inhibitors 2 and 3 derived from 1 through substitutions at P1, P2 and P2' positions exhibit 3.4- to 500-fold better inhibition than clinical inhibitors for PR^S17 with the exception of amprenavir. Crystal structures of PR^S17/2 and PR^S17/3 reveal how these inhibitors target the two active site mutations of PR^S17. The substituted methoxy P2 group of 2 forms new interactions with G48V mutation, while the modified bis-fluoro-benzyl P1 group of 3 forms a halogen interaction with V82S mutation, contributing to improved inhibition of PR^S17.

HIV Protease: Historical Perspective and Current Research

The retroviral protease of human immunodeficiency virus (HIV) is an excellent target for antiviral inhibitors for treating HIV/AIDS. Despite the efficacy of therapy, current efforts to control the disease are undermined by the growing threat posed by drug resistance. This review covers the historical background of studies on the structure and function of HIV protease, the subsequent development of antiviral inhibitors, and recent studies on drug-resistant protease variants. We highlight the important contributions of Dr. Stephen Oroszlan to fundamental knowledge about the function of the HIV protease and other retroviral proteases. These studies, along with those of his colleagues, laid the foundations for the design of clinical inhibitors of HIV protease. The drug-resistant protease variants also provide an excellent model for investigating the molecular mechanisms and evolution of resistance.

Structural Impacts of Drug-Resistance Mutations Appearing in HIV-2 Protease

The use of antiretroviral drugs is accompanied by the emergence of HIV-2 resistances. Thus, it is important to elucidate the mechanisms of resistance to antiretroviral drugs. Here, we propose a structural analysis of 31 drug-resistant mutants of HIV-2 protease (PR2) that is an important target against HIV-2 infection. First, we modeled the structures of each mutant. We then located structural shifts putatively induced by mutations. Finally, we compared wild-type and mutant inhibitor-binding pockets and interfaces to explore the impacts of these induced structural deformations on these two regions. Our results showed that one mutation could induce large structural rearrangements in side-chain and backbone atoms of mutated residue, in its vicinity or further. Structural deformations observed in side-chain atoms are frequent and of greater magnitude, that confirms that to fight drug resistance, interactions with backbone atoms should be favored. We showed that these observed structural deformations modify the conformation, volume, and hydrophobicity of the binding pocket and the composition and size of the PR2 interface. These results suggest that resistance mutations could alter ligand binding by modifying pocket properties and PR2 stability by impacting its interface. Our results reinforce the understanding of the effects of mutations that occurred in PR2 and the different mechanisms of PR2 resistance.

Darunavir-Resistant HIV-1 Protease Constructs Uphold a Conformational Selection Hypothesis for Drug Resistance

Multidrug resistance continues to be a barrier to the effectiveness of highly active antiretroviral therapy in the treatment of human immunodeficiency virus 1 (HIV-1) infection. Darunavir (DRV) is a highly potent protease inhibitor (PI) that is oftentimes effective when drug resistance has emerged against first-generation inhibitors. Resistance to darunavir does evolve and requires 10–20 amino acid substitutions. The conformational landscapes of six highly characterized HIV-1 protease (PR) constructs that harbor up to 19 DRV-associated mutations were characterized by distance measurements with pulsed electron double resonance (PELDOR) paramagnetic resonance spectroscopy, namely double electron–electron resonance (DEER). The results show that the accumulated substitutions alter the conformational landscape compared to PI-naïve protease where the semi-open conformation is destabilized as the dominant population with open-like states becoming prevalent in many cases. A linear correlation is found between values of the DRV inhibition parameter K_i and the open-like to closed-state population ratio determined from DEER. The nearly 50% decrease in occupancy of the semi-open conformation is associated with reduced enzymatic activity, characterized previously in the literature.

Highly drug-resistant HIV-1 protease reveals decreased intra-subunit interactions due to clusters of mutations

Drug-resistance is a serious problem for treatment of the HIV/AIDS pandemic. Potent clinical inhibitors of HIV-1 protease show several orders of magnitude worse inhibition of highly drug-resistant variants. Hence, the structure and enzyme activities were analyzed for HIV protease mutant HIV-1 protease (EC 3.4.23.16) (PR) with 22 mutations (PRS5B) from a clinical isolate that was selected by machine learning to represent high-level drug-resistance. PRS5B has 22 mutations including only one (I84V) in the inhibitor binding site; however, clinical inhibitors had poor inhibition of PRS5B activity with kinetic inhibition value (K_i ) values of 4-1000 nm or 18- to 8000-fold worse than for wild-type PR. High-resolution crystal structures of PRS5B complexes with the best inhibitors, amprenavir (APV) and darunavir (DRV) (K_i ~ 4 nm), revealed only minor changes in protease-inhibitor interactions. Instead, two distinct clusters of mutations in distal regions induce coordinated conformational changes that decrease favorable internal interactions across the entire protein subunit. The largest structural rearrangements are described and compared to other characterized resistant mutants. In the protease hinge region, the N83D mutation eliminates a hydrogen bond connecting the hinge and core of the protease and increases disorder compared to highly resistant mutants PR with 17 mutations and PR with 20 mutations with similar hinge mutations. In a distal β-sheet, mutations G73T and A71V coordinate with accessory mutations to bring about shifts that propagate throughout the subunit. Molecular dynamics simulations of ligand-free dimers show differences consistent with loss of interactions in mutant compared to wild-type PR. Clusters of mutations exhibit both coordinated and antagonistic effects, suggesting PRS5B may represent an intermediate stage in the evolution of more highly resistant variants. DATABASES: Structural data are available in Protein Data Bank under the accession codes 6P9A and 6P9B for PRS5B/DRV and PRS5B/APV, respectively.

An Innovative Sequence-to-Structure-Based Approach to Drug Resistance Interpretation and Prediction: The Use of Molecular Interaction Fields to Detect HIV-1 Protease Binding-Site Dissimilarities

In silico methodologies have opened new avenues of research to understanding and predicting drug resistance, a pressing health issue that keeps rising at alarming pace. Sequence-based interpretation systems are routinely applied in clinical context in an attempt to predict mutation-based drug resistance and thus aid the choice of the most adequate antibiotic and antiviral therapy. An important limitation of approaches based on genotypic data exclusively is that mutations are not considered in the context of the three-dimensional (3D) structure of the target. Structure-based in silico methodologies are inherently more suitable to interpreting and predicting the impact of mutations on target-drug interactions, at the cost of higher computational and time demands when compared with sequence-based approaches. Herein, we present a fast, computationally inexpensive, sequence-to-structure-based approach to drug resistance prediction, which makes use of 3D protein structures encoded by input target sequences to draw binding-site comparisons with susceptible templates. Rather than performing atom-by-atom comparisons between input target and template structures, our workflow generates and compares Molecular Interaction Fields (MIFs) that map the areas of energetically favorable interactions between several chemical probe types and the target binding site. Quantitative, pairwise dissimilarity measurements between the target and the template binding sites are thus produced. The method is particularly suited to understanding changes to the 3D structure and the physicochemical environment introduced by mutations into the target binding site. Furthermore, the workflow relies exclusively on freeware, making it accessible to anyone. Using four datasets of known HIV-1 protease sequences as a case-study, we show that our approach is capable of correctly classifying resistant and susceptible sequences given as input. Guided by ROC curve analyses, we fined-tuned a dissimilarity threshold of classification that results in remarkable discriminatory performance (accuracy ≈ ROC AUC ≈ 0.99), illustrating the high potential of sequence-to-structure-, MIF-based approaches in the context of drug resistance prediction. We discuss the complementarity of the proposed methodology to existing prediction algorithms based on genotypic data. The present work represents a new step toward a more comprehensive and structurally-informed interpretation of the impact of genetic variability on the response to HIV-1 therapies.

Proton transfer and drug binding details revealed in neutron diffraction studies of wild-type and drug resistant HIV-1 protease

HIV-1 protease is an essential therapeutic target for the design and development of antiviral inhibitors to treat AIDS. We used room temperature neutron crystallography to accurately determine hydrogen atom positions in several protease complexes with clinical drugs, amprenavir and darunavir. Hydrogen bonding interactions were carefully mapped to provide an unprecedented picture of drug binding to the protease target. We demonstrate that hydrogen atom positions within the enzyme catalytic site can be altered by introducing drug resistant mutations and by protonating surface residues that trigger proton transfer reactions between the catalytic Asp residues and the hydroxyl group of darunavir. When protein perdeuteration is not feasible, we validate the use of initial H/D exchange with unfolded protein and partial deuteration in pure D2O with hydrogenous glycerol to maximize deuterium incorporation into the protein, with no detrimental effects on the growth of quality crystals suitable for neutron diffraction experiments.

The Impact of HIV-1 Drug Escape on the Global Treatment Landscape

The rising prevalence of HIV drug resistance (HIVDR) could threaten gains made in combating the HIV epidemic and compromise the 90-90-90 target proposed by United Nations Programme on HIV/AIDS (UNAIDS) to have achieved virological suppression in 90% of all persons receiving antiretroviral therapy (ART) by the year 2020. HIVDR has implications for the persistence of HIV, the selection of current and future ART drug regimens, and strategies of vaccine and cure development. Focusing on drug classes that are in clinical use, this Review critically summarizes what is known about the mechanisms the virus utilizes to escape drug control. Armed with this knowledge, strategies to limit the expansion of HIVDR are proposed.

Evolutionary coupling saturation mutagenesis: Coevolution-guided identification of distant sites influencing Bacillus naganoensis pullulanase activity

Pullulanases are well-known debranching enzymes hydrolyzing α-1,6-glycosidic linkages. To date, engineering of pullulanase is mainly focused on catalytic pocket or domain tailoring based on structure/sequence information. Saturation mutagenesis-involved directed evolution is, however, limited by the low number of mutational sites compatible with combinatorial libraries of feasible size. Using Bacillus naganoensis pullulanase as a target protein, here we introduce the 'evolutionary coupling saturation mutagenesis' (ECSM) approach: residue pair covariances are calculated to identify residues for saturation mutagenesis, focusing directed evolution on residue pairs playing important roles in natural evolution. Evolutionary coupling (EC) analysis identified seven residue pairs as evolutionary mutational hotspots. Subsequent saturation mutagenesis yielded variants with enhanced catalytic activity. The functional pairs apparently represent distant sites affecting enzyme activity.

Potent antiviral HIV-1 protease inhibitor combats highly drug resistant mutant PR20

Drug-resistance threatens effective treatment of HIV/AIDS. Clinical inhibitors, including darunavir (1), are ineffective for highly resistant protease mutant PR20, however, antiviral compound 2 derived from 1 with fused tricyclic group at P2, extended amino-benzothiazole P2' ligand and two fluorine atoms on P1 shows 16-fold better inhibition of PR20 enzyme activity. Crystal structures of PR20 and wild-type PR complexes reveal how the extra groups of 2 counteract the expanded ligand-binding pocket, dynamic flaps, and faster dimer dissociation of PR20.

Molecular Determinants of Epistasis in HIV-1 Protease: Elucidating the Interdependence of L89V and L90M Mutations in Resistance

Protease inhibitors have the highest potency among antiviral therapies against HIV-1 infections, yet the virus can evolve resistance. Darunavir (DRV), currently the most potent Food and Drug Administration-approved protease inhibitor, retains potency against single-site mutations. However, complex combinations of mutations can confer resistance to DRV. While the interdependence between mutations within HIV-1 protease is key for inhibitor potency, the molecular mechanisms that underlie this control remain largely unknown. In this study, we investigated the interdependence between the L89V and L90M mutations and their effects on DRV binding. These two mutations have been reported to be positively correlated with one another in HIV-1 patient-derived protease isolates, with the presence of one mutation making the probability of the occurrence of the second mutation more likely. The focus of our investigation is a patient-derived isolate, with 24 mutations that we call "KY"; this variant includes the L89V and L90M mutations. Three additional KY variants with back-mutations, KY(V89L), KY(M90L), and the KY(V89L/M90L) double mutation, were used to experimentally assess the individual and combined effects of these mutations on DRV inhibition and substrate processing. The enzymatic assays revealed that the KY(V89L) variant, with methionine at residue 90, is highly resistant, but its catalytic function is compromised. When a leucine to valine mutation at residue 89 is present simultaneously with the L90M mutation, a rescue of catalytic efficiency is observed. Molecular dynamics simulations of these DRV-bound protease variants reveal how the L90M mutation induces structural changes throughout the enzyme that undermine the binding interactions.

Structural and binding insights into HIV-1 protease and P2-ligand interactions through molecular dynamics simulations, binding free energy and principal component analysis

HIV-1 protease (HIV-1-pr) plays an important role in viral replication and maturation, making it one of the most attractive targets for anti-retroviral therapy. To design new effective inhibitors able to combat drug resistance in mutant HIV-1-pr variants, it is essential to gain further understanding about the mechanisms by which the recently proposed inhibitors deactivate the mutant HIV-1-pr variants. In the present work, we explored the interactions between two P2-ligands (DRV, and one new derivative, 4UY) with wild type (WT) and two multiple mutant HIV-1-pr variants (p20 and p51) with all atom molecular dynamics (MD) simulations, binding free energy calculations, and principal component analysis (PCA). The trajectories of MD simulations show that both 4UY and DRV primarily bind with the active sites, flap and 80s loop regions of HIV-1-pr variants through either hydrogen bonds or hydrophobic interactions. More hydrogen bonds and hydrophobic interactions were located for 4UY/HIV-1-pr complexes than for DRV/HIV-1-pr counterparts. More importantly, 4UY was found to have an extra hydrogen bond with the backbone of Gly48' in the flap region of the HIV-1-prs. The flap tip-tip distance (I50-I50') and flap tip-active site distance (I50-D25 and I50'-D25') indicate that the flaps turn more closed in 4UY bound HIV-1-prs than DRV bound ones, and the former also have more compact hydrophobic cavities than the latter. Further, the vector projections from PCA indicate that 4UY/DRV inhibitor binding projects the closing of flap in HIV-1-pr variants. In line with the above trajectory analysis, the thermodynamics calculation with MM-PBSA method suggests much stronger binding affinity for 4UY/HIV-1-pr than DRV/HIV-1-pr by 4.3-6.4 kcal/mol. Although p20 and p51 also induce weaker binding due to multiple mutants for 4UY inhibitor by 1.9-1.8 kcal/mol, their bindings to the new P2 ligand (4UY) are indeed significantly enhanced as compared to DRV. The thermodynamic components responsible for the binding differences and the contribution from key residues to the binding were also discussed in detail.

Highly Drug-Resistant HIV-1 Protease Mutant PRS17 Shows Enhanced Binding to Substrate Analogues

We report the structural analysis of highly drug-resistant human immunodeficiency virus protease (PR) variant PR^S17, rationally selected by machine learning, in complex with substrate analogues. Crystal structures were solved of inhibitor-free inactive PR^S17-D25N, wild-type PR/CA-p2 complex, and PR^S17 in complex with substrate analogues, CA-p2 and p2-NC. Peptide analogues p2-NC and CA-p2 exhibit inhibition constants of 514 and 22 nM, respectively, for PR^S17 or approximately 3-fold better than for PR. CA-p2 is a better inhibitor of PR^S17 than are clinical inhibitors (K _i = 50-8390 nM) except for amprenavir (K _i = 11 nM). G48V resistance mutation induces curled flap tips in PR^S17-D25N structure. The inner P2-P2' residues of substrate analogues in PR^S17 complexes maintain similar conformations to those of wild-type complex, while significant conformational changes are observed in the peripheral residues P3, P4' of CA-p2 and P3, P4, and P3' of p2-NC. The loss of β-branched side chain by V82S mutation initiates a shift in 80's loop and reshapes the S3/S3' subsite, which enhances substrate binding with new hydrogen bonds and van der Waals interactions that are absent in the wild-type structures. The steric hindrance caused by G48V mutation in the flap of PR^S17 contributes to altered binding interactions of P3 Arg, P4' norleucine of CA-p2, and P4 and P3' of p2-NC with the addition of new hydrogen bonds and van der Waals contacts. The enhanced interaction of PR^S17 with substrate analogues agrees with their relative inhibition, suggesting that this mutant improves substrate binding while decreasing affinity for clinical inhibitors.

Protein engineering: the potential of remote mutations

Engineered proteins, especially enzymes, are now commonly used in many industries owing to their catalytic power, specific binding of ligands, and properties as materials and food additives. As the number of potential uses for engineered proteins has increased, the interest in engineering or designing proteins to have greater stability, activity and specificity has increased in turn. With any rational engineering or design pursuit, the success of these endeavours relies on our fundamental understanding of the systems themselves; in the case of proteins, their structure-dynamics-function relationships. Proteins are most commonly rationally engineered by targeting the residues that we understand to be functionally important, such as enzyme active sites or ligand-binding sites. This means that the majority of the protein, i.e. regions remote from the active- or ligand-binding site, is often ignored. However, there is a growing body of literature that reports on, and rationalises, the successful engineering of proteins at remote sites. This minireview will discuss the current state of the art in protein engineering, with a particular focus on engineering regions that are remote from active- or ligand-binding sites. As the use of protein technologies expands, exploiting the potential improvements made possible through modifying remote regions will become vital if we are to realise the full potential of protein engineering and design.

Structural Adaptation of Darunavir Analogues against Primary Mutations in HIV-1 Protease

HIV-1 protease is one of the prime targets of agents used in antiretroviral therapy against HIV. However, under selective pressure of protease inhibitors, primary mutations at the active site weaken inhibitor binding to confer resistance. Darunavir (DRV) is the most potent HIV-1 protease inhibitor in clinic; resistance is limited, as DRV fits well within the substrate envelope. Nevertheless, resistance is observed due to hydrophobic changes at residues including I50, V82, and I84 that line the S1/S1' pocket within the active site. Through enzyme inhibition assays and a series of 12 crystal structures, we interrogated susceptibility of DRV and two potent analogues to primary S1' mutations. The analogues had modifications at the hydrophobic P1' moiety compared to DRV to better occupy the unexploited space in the S1' pocket where the primary mutations were located. Considerable losses of potency were observed against protease variants with I84V and I50V mutations for all three inhibitors. The crystal structures revealed an unexpected conformational change in the flap region of I50V protease bound to the analogue with the largest P1' moiety, indicating interdependency between the S1' subsite and the flap region. Collective analysis of protease-inhibitor interactions in the crystal structures using principle component analysis was able to distinguish inhibitor identity and relative potency solely based on van der Waals contacts. Our results reveal the complexity of the interplay between inhibitor P1' moiety and S1' mutations and validate principle component analyses as a useful tool for distinguishing resistance and inhibitor potency.

Analysis of drug resistance in HIV protease

BACKGROUND

Drug resistance in HIV is the major problem limiting effective antiviral therapy. Computational techniques for predicting drug resistance profiles from genomic data can accelerate the appropriate choice of therapy. These techniques can also be used to select protease mutants for experimental studies of resistance and thereby assist in the development of next-generation therapies.

RESULTS

The machine learning produced highly accurate and robust classification of HIV protease resistance. Genotype data were mapped to the enzyme structure and encoded using Delaunay triangulation. Generative machine learning models trained on one inhibitor could classify resistance from other inhibitors with varying levels of accuracy. Generally, the accuracy was best when the inhibitors were chemically similar.

CONCLUSIONS

Restricted Boltzmann Machines are an effective machine learning tool for classification of genomic and structural data. They can also be used to compare resistance profiles of different protease inhibitors.

Drug Resistance Mutation L76V Alters Nonpolar Interactions at the Flap-Core Interface of HIV-1 Protease

Four HIV-1 protease (PR) inhibitors, clinical inhibitors lopinavir and tipranavir, and two investigational compounds 4 and 5, were studied for their effect on the structure and activity of PR with drug-resistant mutation L76V (PR_L76V). Compound 5 exhibited the best K _i value of 1.9 nM for PR_L76V, whereas the other three inhibitors had K _i values of 4.5-7.6 nM, 2-3 orders of magnitude worse than for wild-type enzymes. Crystal structures showed only minor differences in interactions of inhibitors with PR_L76V compared to wild-type complexes. The shorter side chain of Val76 in the mutant lost hydrophobic interactions with Lys45 and Ile47 in the flap, and with Asp30 and Thr74 in the protein core, consistent with decreased stability. Inhibitors forming additional polar interactions with the flaps or dimer interface of PR_L76V were unable to compensate for the decrease in internal hydrophobic contacts. These structures provide insights for inhibitor design.

Exploring the flap dynamics of the South African HIV subtype C protease in presence of FDA-approved inhibitors: MD study

HIV-1 protease (HIV PR) is considered as one of the most attractive targets for the treatment of HIV and the impact of flap dynamics of HIV PR on the binding affinities of protease inhibitors (PIs) is a crucial ongoing research field. Recently, our research group evaluated the binding affinities of different FDA approved PIs against the South African HIV-1 subtype C (C-SA) protease (PR). The CSA-HIV PR displayed weaker binding affinity for most of the clinical PIs compared to HIV-1 B subtype for West and Central Europe, the Americas. In the current work, the flap dynamics of four different systems of HIV-1 C-SA PR complexed to FDA approved second generation PIs and its impact on binding was explored over the molecular dynamic trajectories. It was observed that the interactions of the selected drugs with the binding site residues of the protease may not be the major contributor for affinity towards PIs. Various post-MD analyses were performed, also entropic contributions, solvation free energies and hydrophobic core formation interactions were studied to assess how the flap dynamics of C-SA PR which is affected by such factors. From these contributions, large van der Waals interactions and low solvation free energies were found to be major factors for the higher activity of ATV against C-SA HIV PR. Furthermore, a comparatively stable hydrophobic core may be responsible for higher stability of the PR flaps of the ATV complex. The outcome of this study provides significant guidance to how the flap dynamics of C-SA PR is affected by various factors as a result of the binding affinity of various protease inhibitors. It will also assist with the design of potent inhibitors against C-SA HIV PR that apart from binding in the active site of PR can interacts with the flaps to prevent opening of the flaps resulting in inactivation of the protease.

Decoding HIV resistance: from genotype to therapy

Genetic variation in HIV poses a major challenge for prevention and treatment of the AIDS pandemic. Resistance occurs by mutations in the target proteins that lower affinity for the drug or alter the protein dynamics, thereby enabling viral replication in the presence of the drug. Due to the prevalence of drug-resistant strains, monitoring the genotype of the infecting virus is recommended. Computational approaches for predicting resistance from genotype data and guiding therapy are discussed. Many prediction methods rely on rules derived from known resistance-associated mutations, however, statistical or machine learning can improve the classification accuracy and assess unknown mutations. Adding classifiers such as information on the atomic structure of the protein can further enhance the predictions.