Resilience to resistance of HIV-1 protease inhibitors: profile of darunavir

The current effectiveness of HAART in the management of HIV infection is compromised by the emergence of extensively cross-resistant strains of HIV-1, requiring a significant need for new therapeutic agents. Due to its crucial role in viral maturation and therefore HIV-1 replication and infectivity, the HIV-1 protease continues to be a major development target for antiretroviral therapy. However, new protease inhibitors must have higher thresholds to the development of resistance and cross-resistance. Research has demonstrated that the binding characteristics between a protease inhibitor and the active site of the HIV-1 protease are key factors in the development of resistance. More specifically, the way in which a protease inhibitor fits within the substrate consensus volume, or substrate envelope , appears to be critical. The currently available inhibitors are not only smaller than the native substrates, but also have a different shape. This difference in shape underlies observed patterns of resistance because primary drug-resistant mutations often arise at positions in the protease where the inhibitors protrude beyond the substrate envelope but are still in contact with the enzyme. Since all currently available protease inhibitors occupy a similar space (in spite of their structural differences) in the active site of the enzyme, the specific positions where the inhibitors protrude and contact the enzyme correspond to the locations where most mutations occur that give rise to multidrug-resistant HIV-1 strains. Detailed investigation of the structure, thermodynamics, and dynamics of the active site of the protease enzyme is enabling the identification of new protease inhibitors that more closely fit within the substrate envelope and therefore decrease the risk of drug resistance developing. The features of darunavir, the latest FDA-approved protease inhibitor, include its high binding affinity (Kd = 4.5 x 10-12 M) for the protease active site, the presence of hydrogen bonds with the backbone, and its ability to fit closely within the substrate envelope (or consensus volume). Darunavir is potent against both wild-type and protease inhibitor-resistant viruses in vitro, including a broad range of over 4,000 clinical isolates. Additionally, in vitro selection studies with wild-type HIV-1 strains have shown that resistance to darunavir develops much more slowly and is more difficult to generate than for existing protease inhibitors. Clinical studies have shown that darunavir administered with low-dose ritonavir (darunavir/ritonavir) provides highly potent viral suppression (including significant decreases in HIV viral load in patients with documented protease inhibitor resistance) together with favorable tolerability. In conclusion, as a result of its high binding affinity for and overall fit within the active site of HIV-1 protease, darunavir has a higher genetic barrier to the development of resistance and better clinical efficacy against multidrug-resistant HIV relative to current protease inhibitors. The observed efficacy, safety and tolerability of darunavir in highly treatment-experienced patients makes darunavir an important new therapeutic option for HIV-infected patients

REdiii: a pipeline for automated structure solution

High-throughput crystallographic approaches require integrated software solutions to minimize the need for manual effort. REdiii is a system that allows fully automated crystallographic structure solution by integrating existing crystallographic software into an adaptive and partly autonomous workflow engine. The program can be initiated after collecting the first frame of diffraction data and is able to perform processing, molecular-replacement phasing, chain tracing, ligand fitting and refinement without further user intervention. Preset values for each software component allow efficient progress with high-quality data and known parameters. The adaptive workflow engine can determine whether some parameters require modifications and choose alternative software strategies in case the preconfigured solution is inadequate. This integrated pipeline is targeted at providing a comprehensive and efficient approach to screening for ligand-bound co-crystal structures while minimizing repetitiveness and allowing a high-throughput scientific discovery process

Deciphering complex mechanisms of resistance and loss of potency through coupled molecular dynamics and machine learning [preprint]

Drug resistance threatens many critical therapeutics through mutations in the drug target. The molecular mechanisms by which combinations of mutations, especially involving those distal from the active site, alter drug binding to confer resistance are poorly understood and thus difficult to counteract. A strategy coupling parallel molecular dynamics simulations and machine learning to identify conserved mechanisms underlying resistance was developed. A series of 28 HIV-1 protease variants with up to 24 varied substitutions were used as a rigorous model of this strategy. Many of the mutations were distal from the active site and the potency to darunavir varied from low pM to near μM. With features extracted from molecular dynamics simulations, elastic network machine learning was applied to correlate physical interactions at the molecular level with potency loss. This fit to within 1 kcal/mol of experimental potency for both the training and test sets, outperforming MM/GBSA calculations. Feature reduction resulted in a model with 4 specific features that correspond to interactions critical for potency regardless of enzyme variant. These predictive features throughout the enzyme would not have been identified without dynamics and machine learning and specifically varied with potency. This approach enables capturing the conserved dynamic molecular mechanisms by which complex combinations of mutations confer resistance and identifying critical interactions which serve as bellwethers over a wide range of inhibitor potency. Machine learning models leveraging molecular dynamics can thus elucidate mechanisms that confer loss of affinity due to variations distal from the active site, such as in drug resistance

NAD(H) phosphates mediate tetramer assembly of human C-terminal binding protein (CtBP)

C-terminal binding proteins (CtBPs) are co-transcriptional factors that play key roles in cell fate. We have previously shown that NAD(H) promotes the assembly of similar tetramers from either human CtBP1 and CtBP2 and that CtBP2 tetramer destabilizing mutants are defective for oncogenic activity. To assist structure-based design efforts for compounds that disrupt CtBP tetramerization, it is essential to understand how NAD(H) triggers tetramer assembly. Here, we investigate the moieties within NAD(H) that are responsible for triggering tetramer formation. Using multi-angle light scattering (MALS) we show that ADP is able to promote tetramer formation of both CtBP1 and CtBP2, whereas AMP promotes tetramer assembly of CtBP1, but not CtBP2. Other NAD(H) moieties that lack the adenosine phosphate, including adenosine and those incorporating nicotinamide, all fail to promote tetramer assembly. Our crystal structures of CtBP1 with AMP reveal participation of the adenosine phosphate in the tetrameric interface, pinpointing its central role in NAD(H) linked assembly. CtBP1 and CtBP2 have overlapping but unique roles, suggesting that a detailed understanding of their unique structural properties might have utility in the design of paralog specific inhibitors. We investigated the different responses to AMP through a series of site-directed mutants at 13 positions. These mutations reveal a central role for a hinge segment, which we term the 120s hinge, that connects the substrate with coenzyme binding domains and influences nucleotide binding and tetramer assembly. Our results provide insight into suitable pockets to explore in structure-based drug design to interfere with co-transcriptional activity of CtBP in cancer

Drug-resistant HIV-1 protease regains functional dynamics through cleavage site coevolution

Drug resistance is caused by mutations that change the balance of recognition favoring substrate cleavage over inhibitor binding. Here, a structural dynamics perspective of the regained wild-type functioning in mutant HIV-1 proteases with coevolution of the natural substrates is provided. The collective dynamics of mutant structures of the protease bound to p1-p6 and NC-p1 substrates are assessed using the Anisotropic Network Model (ANM). The drug-induced protease mutations perturb the mechanistically crucial hinge axes that involve key sites for substrate binding and dimerization and mainly coordinate the intrinsic dynamics. Yet with substrate coevolution, while the wild-type dynamic behavior is restored in both p1-p6 ((LP) (1\u27F)p1-p6D30N/N88D) and NC-p1 ((AP) (2) (V)NC-p1V82A) bound proteases, the dynamic behavior of the NC-p1 bound protease variants (NC-p1V82A and (AP) (2) (V)NC-p1V82A) rather resemble those of the proteases bound to the other substrates, which is consistent with experimental studies. The orientational variations of residue fluctuations along the hinge axes in mutant structures justify the existence of coevolution in p1-p6 and NC-p1 substrates, that is, the dynamic behavior of hinge residues should contribute to the interdependent nature of substrate recognition. Overall, this study aids in the understanding of the structural dynamics basis of drug resistance and evolutionary optimization in the HIV-1 protease system

Time-averaging crystallographic refinement: possibilities and limitations using alpha-cyclodextrin as a test system

The method of time-averaging crystallographic refinement is assessed using a small molecule, alpha-cyclodextrin, as a test system. A total of 16 refinements are performed on simulated data. Three resolution ranges of the data are used, the memory relaxation time of the averaging is varied, and several overall temperature factors are used. The most critical factor in the reliable application of time-averaging is the resolution of the data. The ratio of data to molecular degrees of freedom should be large enough to avoid overfitting of the data by the time-averaging procedure. The use of a free R-factor can aid in determining whether time-averaging can be reliably applied. Good ensembles of structures are obtained using data up to 1.0 or 2.0 A resolution. Comparison of electron-density maps from time-averaging refinement and anisotropic temperature-factor refinement indicates that the former technique yields a better representation of the exact data than the latter

HIV-1 protease-substrate coevolution in nelfinavir resistance

Resistance to various human immunodeficiency virus type 1 (HIV-1) protease inhibitors (PIs) challenges the effectiveness of therapies in treating HIV-1-infected individuals and AIDS patients. The virus accumulates mutations within the protease (PR) that render the PIs less potent. Occasionally, Gag sequences also coevolve with mutations at PR cleavage sites contributing to drug resistance. In this study, we investigated the structural basis of coevolution of the p1-p6 cleavage site with the nelfinavir (NFV) resistance D30N/N88D protease mutations by determining crystal structures of wild-type and NFV-resistant HIV-1 protease in complex with p1-p6 substrate peptide variants with L449F and/or S451N. Alterations of residue 30\u27s interaction with the substrate are compensated by the coevolving L449F and S451N cleavage site mutations. This interdependency in the PR-p1-p6 interactions enhances intermolecular contacts and reinforces the overall fit of the substrate within the substrate envelope, likely enabling coevolution to sustain substrate recognition and cleavage in the presence of PR resistance mutations. IMPORTANCE: Resistance to human immunodeficiency virus type 1 (HIV-1) protease inhibitors challenges the effectiveness of therapies in treating HIV-1-infected individuals and AIDS patients. Mutations in HIV-1 protease selected under the pressure of protease inhibitors render the inhibitors less potent. Occasionally, Gag sequences also mutate and coevolve with protease, contributing to maintenance of viral fitness and to drug resistance. In this study, we investigated the structural basis of coevolution at the Gag p1-p6 cleavage site with the nelfinavir (NFV) resistance D30N/N88D protease mutations. Our structural analysis reveals the interdependency of protease-substrate interactions and how coevolution may restore substrate recognition and cleavage in the presence of protease drug resistance mutations

Characterizing protein-ligand binding using atomistic simulation and machine learning: Application to drug resistance in HIV-1 protease

Over the past several decades, atomistic simulations of biomolecules, whether carried out using molecular dynamics or Monte Carlo techniques, have provided detailed insights into their function. Comparing the results of such simulations for a few closely related systems has guided our understanding of the mechanisms by which changes like ligand binding or mutation can alter function. The general problem of detecting and interpreting such mechanisms from simulations of many related systems, however, remains a challenge. This problem is addressed here by applying supervised and unsupervised machine learning techniques to a variety of thermodynamic observables extracted from molecular dynamics simulations of different systems. As an important test case, these methods are applied to understanding the evasion by HIV-1 protease of darunavir, a potent inhibitor to which resistance can develop via the simultaneous mutation of multiple amino acids. Complex mutational patterns have been observed among resistant strains, presenting a challenge to developing a mechanistic picture of resistance in the protease. In order to dissect these patterns and gain mechanistic insight on the role of specific mutations, molecular dynamics simulations were carried out on a collection of HIV-1 protease variants, chosen to include highly resistant strains and susceptible controls, in complex with darunavir. Using a machine learning approach that takes advantage of the hierarchical nature in the relationships among sequence, structure and function, an integrative analysis of these trajectories reveals key details of the resistance mechanism, including changes in protein structure, hydrogen bonding and protein-ligand contacts

Interdependence of Inhibitor Recognition in HIV-1 Protease

Molecular recognition is a highly interdependent process. Subsite couplings within the active site of proteases are most often revealed through conditional amino acid preferences in substrate recognition. However, the potential effect of these couplings on inhibition and thus inhibitor design is largely unexplored. The present study examines the interdependency of subsites in HIV-1 protease using a focused library of protease inhibitors, to aid in future inhibitor design. Previously a series of darunavir (DRV) analogs was designed to systematically probe the S1\u27 and S2\u27 subsites. Co-crystal structures of these analogs with HIV-1 protease provide the ideal opportunity to probe subsite interdependency. All-atom molecular dynamics simulations starting from these structures were performed and systematically analyzed in terms of atomic fluctuations, intermolecular interactions, and water structure. These analyses reveal that the S1\u27 subsite highly influences other subsites: the extension of the hydrophobic P1\u27 moiety results in 1) reduced van der Waals contacts in the P2\u27 subsite, 2) more variability in the hydrogen bond frequencies with catalytic residues and the flap water, and 3) changes in the occupancy of conserved water sites both proximal and distal to the active site. In addition, one of the monomers in this homodimeric enzyme has atomic fluctuations more highly correlated with DRV than the other monomer. These relationships intricately link the HIV-1 protease subsites and are critical to understanding molecular recognition and inhibitor binding. More broadly, the interdependency of subsite recognition within an active site requires consideration in the selection of chemical moieties in drug design; this strategy is in contrast to what is traditionally done with independent optimization of chemical moieties of an inhibitor

Assembly of human C-terminal binding protein (CtBP) into tetramers

C-terminal binding protein 1 (CtBP1) and CtBP2 are transcriptional coregulators that repress numerous cellular processes, such as apoptosis, by binding transcription factors and recruiting chromatin-remodeling enzymes to gene promoters. The NAD(H)-linked oligomerization of human CtBP is coupled to its co-transcriptional activity, which is implicated in cancer progression. However, the biologically relevant level of CtBP assembly has not been firmly established; nor has the stereochemical arrangement of the subunits above that of a dimer. Here, multi-angle light scattering (MALS) data established the NAD(+)- and NADH-dependent assembly of CtBP1 and CtBP2 into tetramers. An examination of subunit interactions within CtBP1 and CtBP2 crystal lattices revealed that both share a very similar tetrameric arrangement resulting from assembly of two dimeric pairs, with specific interactions probably being sensitive to NAD(H) binding. Creating a series of mutants of both CtBP1 and CtBP2, we tested the hypothesis that the crystallographically observed interdimer pairing stabilizes the solution tetramer. MALS data confirmed that these mutants disrupt both CtBP1 and CtBP2 tetramers, with the dimer generally remaining intact, providing the first stereochemical models for tetrameric assemblies of CtBP1 and CtBP2. The crystal structure of a subtle destabilizing mutant suggested that small structural perturbations of the hinge region linking the substrate- and NAD-binding domains are sufficient to weaken the CtBP1 tetramer. These results strongly suggest that the tetramer is important in CtBP function, and the series of CtBP mutants reported here can be used to investigate the physiological role of the tetramer