Exact reaction coordinates for flap opening in HIV-1 protease

The primary goal of protein science is to understand how proteins function, which requires understanding the functional dynamics responsible for transitions between different functional structures of a protein. A central concept is the exact reaction coordinates that can determine the value of committor for any protein configuration, which provide the optimal description of functional dynamics. Despite intensive efforts, identifying the exact reaction coordinates (RCs) in complex molecules remains a formidable challenge. Using the recently developed generalized work functional, we report the discovery of the exact RCs for an important functional process-the flap opening of HIV-1 protease. Our results show that this process has six RCs, each one is a linear combination of ~240 backbone dihedrals, providing the precise definition of collectivity and cooperativity in the functional dynamics of a protein. Applying bias potentials along each RC can accelerate flap opening by [Formula: see text] to [Formula: see text] folds. The success in identifying the RCs of a protein with 198 residues represents a significant progress beyond that of the alanine dipeptide, currently the only other complex molecule for which the exact RCs for its conformational changes are known. Our results suggest that the generalized work functional (GWF) might be the fundamental operator of mechanics that controls protein dynamics.

Discovery of Novel HIV Protease Inhibitors Using Modern Computational Techniques

The human immunodeficiency virus type 1 (HIV-1) has continued to be a global concern. With the new HIV incidence, the emergence of multi-drug resistance and the untoward side effects of currently used anti-HIV drugs, there is an urgent need to discover more efficient anti-HIV drugs. Modern computational tools have played vital roles in facilitating the drug discovery process. This research focuses on a pharmacophore-based similarity search to screen 111,566,735 unique compounds in the PubChem database to discover novel HIV-1 protease inhibitors (PIs). We used an in silico approach involving a 3D-similarity search, physicochemical and ADMET evaluations, HIV protease-inhibitor prediction (IC50/percent inhibition), rigid receptor-molecular docking studies, binding free energy calculations and molecular dynamics (MD) simulations. The 10 FDA-approved HIV PIs (saquinavir, lopinavir, ritonavir, amprenavir, fosamprenavir, atazanavir, nelfinavir, darunavir, tipranavir and indinavir) were used as reference. The in silico analysis revealed that fourteen out of the twenty-eight selected optimized hit molecules were within the acceptable range of all the parameters investigated. The hit molecules demonstrated significant binding affinity to the HIV protease (PR) when compared to the reference drugs. The important amino acid residues involved in hydrogen bonding and п-п stacked interactions include ASP25, GLY27, ASP29, ASP30 and ILE50. These interactions help to stabilize the optimized hit molecules in the active binding site of the HIV-1 PR (PDB ID: 2Q5K). HPS/002 and HPS/004 have been found to be most promising in terms of IC50/percent inhibition (90.15%) of HIV-1 PR, in addition to their drug metabolism and safety profile. These hit candidates should be investigated further as possible HIV-1 PIs with improved efficacy and low toxicity through in vitro experiments and clinical trial investigations.

Sequence dependencies and biophysical features both govern cleavage of diverse cut-sites by HIV protease

The infectivity of HIV-1 requires its protease (PR) cleave multiple cut-sites with low sequence similarity. The diversity of cleavage sites has made it challenging to investigate the underlying sequence properties that determine binding and turnover of substrates by PR. We engineered a mutational scanning approach utilizing yeast display, flow cytometry, and deep sequencing to systematically measure the impacts of all individual amino acid changes at 12 positions in three different cut-sites (MA/CA, NC/p1, and p1/p6). The resulting fitness landscapes revealed common physical features that underlie cutting of all three cut-sites at the amino acid positions closest to the scissile bond. In contrast, positions more than two amino acids away from the scissile bond exhibited a strong dependence on the sequence background of the rest of the cut-site. We observed multiple amino acid changes in cut-sites that led to faster cleavage rates, including a preference for negative charge five and six amino acids away from the scissile bond at locations where the surface of protease is positively charged. Analysis of individual cut sites using full-length matrix-capsid proteins indicate that long-distance sequence context can contribute to cutting efficiency such that analyses of peptides or shorter engineered constructs including those in this work should be considered carefully. This work provides a framework for understanding how diverse substrates interact with HIV-1 PR and can be extended to investigate other viral PRs with similar properties.

A novel chimeric antigen receptor (CAR) system using an exogenous protease, in which activation of T cells is controlled by expression patterns of cell‑surface proteins on target cells

Anti-CD19 chimeric antigen receptor (CAR)-T cell therapy against refractory B-cell malignancies shows excellent therapeutic effects. However, there are some obstacles to be overcome in this treatment. Since current CAR-T cells target a single cell-surface protein on tumor cells, the CAR-T cells also attack normal cells expressing the protein. This is one of the major adverse effects of this therapy. To improve target-cell-specificity of this therapy, we established a novel CAR system, in which T-cell activation was controlled by expression patterns of proteins on target cells. Our novel CAR-T cells had two distinct CARs consisting of a 'Signal-CAR', recognizing a protein on tumor cells, and a 'Scissors-CAR', recognizing another protein on normal cells. The signal-CAR had a peptide sequence which was cleaved by the Scissors-CAR, and functional domains for cellular activation. The Scissors-CAR had a protease domain that cleaved its recognition peptide sequence in the Signal-CAR. When tumor cells expressed only the protein recognized by the Signal-CAR, the tumor cells were attacked. By contrast, normal cells expressing both the proteins induced inactivation of the Signal-CAR through cleavage of the recognition site when getting in contact with the CAR-T cells. To establish this system, we invented a Scissors-CAR that was dominantly localized on cell membranes and was activated only when the CAR-T cells were in contact with the normal cells. Using a T-cell line, Jurkat, and two proteins, CD19 and HER2, as target proteins, we showed that the anti-CD19-Signal-CAR was cleaved by the anti-HER2-Scissors-CAR when the CAR-T cells were co-cultivated with cells expressing both the proteins, CD19 and HER2. Furthermore, we demonstrated that primary CAR-T cells expressing both the CARs showed attenuated cytotoxicity againsT cells with both the target proteins. Our novel system would improve safety of the CAR-T cell therapy, leading to expansion of treatable diseases by this immunotherapy.

Novel pyridinium-type fullerene derivatives as multitargeting inhibitors of HIV-1 reverse transcriptase, HIV-1 protease, and HCV NS5B polymerase

In the present study, we newly synthesized four types of novel fullerene derivatives: pyridinium/ethyl ester-type derivatives 3b-3l, pyridinium/carboxylic acid-type derivatives 4a, 4e, 4f, pyridinium/amide-type derivative 5a, and pyridinium/2-morpholinone-type derivative 6a. Among the assessed compounds, cis-3c, cis-3d, trans-3e, trans-3h, cis-3l, cis-4e, cis-4f, trans-4f, and cis-5a were found to inhibit HIV-1 reverse transcriptase (HIV-RT), HIV-1 protease (HIV-PR), and HCV NS5B polymerase (HCV NS5B), with IC₅₀ values observed in the micromolar range. Cellular uptake of pyridinium/ethyl ester-type derivatives was higher than that of corresponding pyridinium/carboxylic acid-type derivatives and pyridinium/amide-type derivatives. This result might indicate that pyridinium/ethyl ester-type derivatives are expected to be lead compounds for multitargeting drugs to treat HIV/HCV coinfection.

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.

Elasticity-Associated Functionality and Inhibition of the HIV Protease

HIV protease plays a critical role in the life cycle of the virus through the generation of mature and infectious virions. Detailed knowledge of the structure of the enzyme and its substrate has led to the development of protease inhibitors. However, the development of resistance to all currently available protease inhibitors has contributed greatly to the decreased success of antiretroviral therapy. When therapy failure occurs, multiple mutations are found within the protease sequence starting with primary mutations, which directly impact inhibitor binding, which can also negatively impact viral fitness and replicative capacity by decreasing the binding affinity of the natural substrates to the protease. As such, secondary mutations which are located outside of the active site region accumulate to compensate for the recurrently deleterious effects of primary mutations. However, the resistance mechanism of these secondary mutations is not well understood, but what is known is that these secondary mutations contribute to resistance in one of two ways, either through increasing the energetic penalty associated with bringing the protease into the closed conformation, or, through decreasing the stability of the protein/drug complex in a manner that increases the dissociation rate of the drug, leading to diminished inhibition. As a result, the elasticity of the enzyme-substrate complex has been implicated in the successful recognition and catalysis of the substrates which may be inferred to suggest that the elasticity of the enzyme/drug complex plays a role in resistance. A realistic representation of the dynamic nature of the protease may provide a more powerful tool in structure-based drug design algorithms.

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.

Evaluation of binding of potential ADMET/tox screened saquinavir analogues for inhibition of HIV-protease via molecular dynamics and binding free energy calculations

Developing novel drug molecules against HIV is a scientific quest necessitated by development of drug resistance against used drugs. We report comparative results of molecular dynamics simulation studies on 11 structural analogues of Saquinavir (SQV) - against HIV-protease that were earlier examined for pharmacodynamic and pharmacokinetic properties. We reported analogues S1, S5 and S8 to qualify the ADMET criterion and may be considered as potential lead molecules. In this study the designed molecules were successively docked with native HIV-protease at AutoDock. Docking scores established relative goodness of the 11 analogues against the benchmark for Saquinavir. The docked complexes were subjected to molecular dynamics simulation studies using GROMACS 4.6.2. Four parameters viz. H-bonding, RMSD, Binding energy and Protein-Ligand Distance were used for comparative analyses of the analogues relative to Saquinavir. The comparison and analysis of the results are indicative that analogues S8, S9 and S1 are promising candidates among all the analogues studied. From our earlier work and present study it is evident that among the three S8 and S1 qualify the ADMET criterion and between S1 and S8, the analogue S8 shows more target efficacy and specificity over S1 and have better molecular dynamics simulation results. Thus, of the 11 de novo Saquinavir analogues, the S8 appears to be the most promising candidate as lead molecule for HIV-protease inhibitor and is best suited for testing under biological system. Further validation of the proposed lead molecules through wet lab studies involving antiviral assays however is required.Communicated by Ramaswamy H. Sarma.

Improved 3D-QSAR Prediction by Multiple Conformational Alignments and Molecular Docking Studies to Design and Discover HIV-I Protease Inhibitors

BACKGROUND

Inhibition of HIV-I protease enzyme is a strategic step for providing better treatment in retrovirus infections, which avoids resistance and possesses less toxicity.

OBJECTIVES

In the course of our research to discover new and potent protease inhibitors, 3D-QSAR (CoMFA and CoMSIA) models were generated using 3 different alignment techniques, including multifit alignment, docking based and Distill based alignment for 63 compounds. Novel molecules were designed from the output of this study.

METHODS

A total of 3 alignment methods were used to generate CoMFA and CoMSIA models. A Distill based alignment method was considered a better method according to different validation parameters. A 3D-QSAR model was generated and contour maps were discussed. The biological activity of designed molecules was predicted using the generated QSAR model to validate QSAR. The newly designed molecules were docked to predict binding affinity.

RESULTS

In CoMFA, leave one out cross-validated coefficient (q²), conventional coefficient (r²) and predicted correlation coefficient (r²_Predicted) values were found to be 0.721, 0.991 and 0.780, respectively. The best obtained CoMSIA model also showed significant cross-validated coefficient (q²), conventional coefficient (r²) and predicted correlation coefficient (r²_Predicted) values of 0.714, 0.987 and 0.721, respectively. Steric and electrostatic contour maps generated from CoMFA and hydrophobic and hydrogen bond donor and hydrogen bond acceptor contour maps from CoMSIA models were used to design new and bioactive protease inhibitors by incorporating bioisosterism and knowledge-based structure-activity relationship.

CONCLUSION

The results from both these approaches, ligand-based drug design and structure-based drug design, are adequate and promising to discover protease inhibitors.

Fullerene derivatives as dual inhibitors of HIV-1 reverse transcriptase and protease

In the present study, we newly synthesized three types of novel fullerene derivatives: pyridinium-type derivatives trans-3a and 4a-5b, piperidinium-type derivative 9, and proline-type derivatives 10a-12. Among the assessed compounds, 5a, 10e, 10f, 10i, 11a-d, and 12 were found to inhibit both HIV reverse transcriptase and HIV protease (HIV-PR), with IC₅₀ values in the low micromolar range being observed. Regarding HIV-PR inhibition activity, proline-type derivatives 11a-11d and 12, bearing an alkyl chain between the hydroxylmethylcarbonyl (HMC) moiety and pyrrolidine ring, were more potent than other derivatives. This result might indicate that connecting HMC moieties with proline-type fullerene derivatives through properly sized alkyl chain leads to improved HIV-PR inhibitory activity.

Evolution of drug resistance in HIV protease

BACKGROUND

Drug resistance is a critical problem limiting effective antiviral therapy for HIV/AIDS. Computational techniques for predicting drug resistance profiles from genomic data can accelerate the appropriate choice of therapy. These techniques can also be used to identify protease mutants for experimental studies of resistance and thereby assist in the development of next-generation therapies. Few studies, however, have assessed the evolution of resistance from genotype-phenotype data.

RESULTS

The machine learning produced highly accurate and robust classification of resistance to HIV protease inhibitors. Genotype data were mapped to the enzyme structure and encoded using Delaunay triangulation. Estimates of evolutionary relationships, based on this encoding, and using Minimum Spanning Trees, showed clusters of mutations that closely resemble the wild type. These clusters appear to evolve uniquely to more resistant phenotypes.

CONCLUSIONS

Using the triangulation metric and spanning trees results in paths that are consistent with evolutionary theory. The majority of the paths show bifurcation, namely they switch once from non-resistant to resistant or from resistant to non-resistant. Paths that lose resistance almost uniformly have far lower levels of resistance than those which either gain resistance or are stable. This strongly suggests that selection for stability in the face of a rapid rate of mutation is as important as selection for resistance in retroviral systems.

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.

Sensing HIV Protease and Its Inhibitor Using "Helical Epitope"-Imprinted Polymers

A helical epitope-peptide (lle⁸⁵-Gly⁹⁴) was selected from the α-helix structure of the HIV protease (PR) as the template, which represents an intricate interplay between structure conformation and dimerization. The peptide template was mixed with water, trifluoroethanol (TFE), and acetonitrile (ACN) at a certain ratio to enlarge the helical conformation in the solution for the fabrication of helical epitope-mediated molecularly imprinted polymers (HEMIPs) on a quartz crystal microbalance (QCM) chip. The template molecules were then removed under equilibrium batch rebinding conditions involving 5% acetic acid/water. The resulting HEMIPs chip exhibited a high affinity toward template peptide HIV PR_85-94, His-tagged HIV PR, and HIV PR, with dissociation constants (K_d) as 160, 43.3, and 78.5 pM, respectively. The detection limit of the developed HIV PR_85-94 QCM sensor is 0.1 ng/mL. The HEMIPs chip exhibited a high affinity and selectivity to bind HIV PR and subsequently to an inhibitor of HIV PR (nelfinavir). The HIV PR binding site was properly oriented on the HEMIPs-chip to develop a HIV PR/HEMIPs chip, which can effectively bind nelfinavir to establish a sandwich assay. The nelfinavir then attached to the HIV PR/HEMIPs chip, which can be easily removed involving 0.8% acetic acid/water. Therefore, HIV PR/HEMIPs chip can be useful to screen for other HIV PR inhibitors. This technique may improve drug targeting for HIV therapy and also strengthen investigations into other virus assays.

Investigation of novel indole-based HIV-1 protease inhibitors using virtual screening and text mining

Human immunodeficiency virus type 1 protease (HIV-1 PR) inhibitors have been used as possible therapeutic agents for HIV-1 infection in clinical study. Most of the HIV therapy-related problems usually stem from long-term opioid usage. The rapid development of drug-resistant variants limits the long-term effectiveness of current inhibitors as therapeutic agents. In addition, different side effects were reported. Further drug development is required to design new compounds which have similar efficacy as the drugs currently used in HIV infection but without having undesirable side effects. Indole derivatives were considered as one of the effective HIV inhibitors. Indole is an important fragment used in many FDAapproved medicines and used in various diseases. For this purpose, in this study the molecules containing" indole" keywords in their fragments are taken from the Specs-SC database which includes 212520 small molecules. 5194 molecules that include indole keywords are selected. These selected molecules are then screened against HIV-1 PR target protein using molecular docking simulations. Then the molecules are ranked according to the their docking scores. Top docking poses of ten ligands and FDA approved drug Amprenavir are subjected to 100 ns Molecular Dynamics (MD) simulations. Thus, by using combination of text mining and integrated molecular modeling approaches, we identified novel indole-based hits against HIV-1 PR.Communicated by Ramaswamy H. Sarma.

Two-Step Preparation of Highly Pure, Soluble HIV Protease from Inclusion Bodies Recombinantly Expressed in Escherichia coli

Heterologous expression of exogenous proteases in Escherichia coli often results in the formation of insoluble inclusion bodies. When sequestered into inclusion bodies, the functionality of the proteases is minimized. To be characterized structurally and functionally, however, proteases must be obtained in their native conformation. HIV protease is readily expressed as inclusion bodies, but must be recovered from the inclusion bodies. This protocol describes an efficient method for recovering HIV protease from inclusion bodies, as well as refolding and purifying the protein. HIV protease-containing inclusion bodies are treated with 8 M urea and purified via cation-exchange chromatography. Subsequent refolding by buffer exchange via dialysis and further purification by anion-exchange chromatography produces highly pure HIV protease that is functionally active. © 2020 by John Wiley & Sons, Inc. Basic Protocol: Recovery, refolding, and purification of HIV protease from inclusion bodies Support Protocol 1: Expression and extraction of inclusion bodies containing HIV protease expressed in Escherichia coli Support Protocol 2: Determination of the active site concentration of HIV protease via isothermal titration calorimetry.

The Influence of Hydrogen Atoms on the Performance of Radial Distribution Function-Based Descriptors in the Chemoinformatic Studies of HIV-1 Protease Complexes with Inhibitors

AIMS

The aim of this letter is to explore the influence of adding hydrogen atoms to the crystallographic structures of HIV-1 protease complexes with a series of inhibitors on the performance of radial distribution function based descriptors recently introduced in chemoinformatic studies.

BACKGROUND

Quite recently the successful application of molecular descriptors based on a radial distribution function to correlate it with biologically interesting properties of a ligand - enzyme complex was demonstrated. Except its predictive power, the analysis of atoms with dominant contributions to the RDFs can be used to identify relevant atoms and interactions. Since original paper was published on dataset consisting of the X-ray structures of complexes without hydrogen atoms, we wonder weather addition of light atoms can provide us new piece of information.

OBJECTIVE

The primarily objective is to create the model correlating the RDF based descriptors and physicochemical properties of the HIV-1 protease complexes with inhibitors with hydrogen atoms. Then, we will compare the performance of new model with previous one, where the hydrogen atoms were discarded. Information about interactions between the enzyme and the inhibitors will be extracted from the analysis of the RDF.

METHODS

The radial distribution function descriptor weighted by the number of valence shell electrons has proven to be sensitive to the changes in the structure of the enzyme and enzyme-ligand complexes. For each structure in our data set, RDF will be calculated and using multiple linear regression method the mathematical model will be designed correlating RDF based descriptors and the physicochemical properties. Statistical analysis of the atom's contribution to the total RDF will reveal relevant interactions.

RESULTS

The applicability of RDF based descriptor for the correlation with pKi and EC50 values is demonstrated, while simple models containing only two or three parameters are able to explain 78 and 86 % of the variance, respectively. The models with explicitly included hydrogens are of comparable quality with the previous models without hydrogens. The analysis of the atom's dominant contributions highlighted the importance of the hydroxyl groups of the inhibitor near the Asp25 and Asp25' residues when it is bounded to the protease.

CONCLUSION

Models based on the RDF weighted by the number of valence shell electrons for correlating small number of molecular descriptors and physicocehmical properties for structures with and without hydrogens are of comparable quality and both can be used for identification of relevant functional groups and interactions. Other: Our approach can be integrated to the next generation virtual screening methods, because is fast, reliable with high predictability potential.

Cheng and Evaluation of Their In Vitro Activity towards HIV Protease

In this study, we isolated nine compounds from the acid hydrolysate of the flower buds of Lonicera fulvotomentosa Hsu et S. C. Cheng and characterized their chemical structures using ¹H-NMR, ¹³C-NMR, and electron ionization mass spectroscopy (EI-MS). These compounds were identified as β-sitosterol (1), 5,5′-dibutoxy-2,2′-bifuran (2), nonacosane-10-ol (3), ethyl (3β)-3,23-dihydroxyolean-12-en-28-oate (4), oleanolic acid (5), ethyl caffeate (6), caffeic acid (7), isovanillin (8), and hederagenin (9), with 4 as a new triterpene compound. Inhibitory activity against human immunodeficiency virus (HIV) protease was also evaluated for the compounds, and only ethyl caffeate, caffeic acid, and isovanillin (6, 7, and 8) exhibited inhibitory effects, with IC₅₀ values of 1.0 μM, 1.5 μM, and 3.5 μM, respectively. Molecular docking with energy minimization and subsequent molecular dynamic (MD) simulation showed that ethyl caffeate and caffeic acid bound to the active site of HIV protease, while isovanillin drifted out from the active site and dissociated into bulk water during MD simulations, and most of the binding residues of HIV protease have been previously identified for HIV protease inhibitors. These results suggest that caffeic acid derivatives may possess inhibitory activities towards HIV protease other than previously reported inhibitory activities against HIV integrase, and thus ethyl caffeate and caffeic acid could be used as lead compounds in developing potential HIV protease inhibitors, and possibly even dual-function inhibitors against HIV.

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.

The pharmacokinetic properties of HIV-1 protease inhibitors: A computational perspective on herbal phytochemicals

Acquired Immune Deficiency Syndrome is the most severe phase of Human Immunodeficiency Virus (HIV) infection. Recent studies have seen an effort to isolate phytochemicals from plants to repress HIV, but less studies have focused on the effects of these phytochemicals on the activities of enzymes/transporters involved in the metabolism of these drugs, which is one of the aims of this study and, to examine the antiviral activity of these compounds against HIV-1 protease enzyme using computational tools. Centre of Awareness-Food Supplement (COA®-FS) herbal medicine, has been said to have potential anti-HIV features. SWISSTARGETPREDICTION and SWISSADME servers were used for determination of the enzymes/transporters involved in the metabolism of these protease inhibitor drugs, (PIs) (Atazanavir, Lopinavir, Darunavir, Saquinavir) and the effects of the selected phytochemicals on the enzymes/transporters involved in the metabolism of these PIs. Using Computational tools, potential structural inhibitory activities of these phytochemicals were explored. Two sub-families of Cytochrome P450 enzymes (CYP3A4 and CYP2C19) and Permeability glycoprotein (P-gp) were predicted to be involved in metabolism of the PIs. Six phytochemicals (Geranin, Apigenin, Fisetin, Luteolin, Phthalic acid and Gallic acid) were predicted to be inhibitors of CYP3A4 and, may slowdown elimination of PIs thereby maintain optimal PIs concentrations. Free binding energy analysis for antiviral activities identified four phytochemicals with favourable binding landscapes with HIV-1 protease enzyme. Epigallocatechin gallate and Kaempferol-7-glucoside exhibited pronounced structural evidence as potential HIV-1 protease enzyme inhibitors. This study acts as a steppingstone toward the use of natural products against diseases that are plagued with adverse drug-interactions.

Double trouble? Gag in conjunction with double insert in HIV protease contributes to reduced DRV susceptibility

HIV protease is essential for processing the Gag polyprotein to produce infectious virions and is a major target in antiretroviral therapy. We have identified an unusual HIV-1 subtype C variant that contains insertions of leucine and asparagine (L38↑N↑L) in the hinge region of protease at position 38. This was isolated from a protease inhibitor naïve infant. Isothermal titration calorimetry showed that 10% less of L38↑N↑L protease was in the active conformation as compared with a reference strain. L38↑N↑L protease displayed a ±50% reduction in K _M and k _cat The catalytic efficiency (k _cat/K _M) of L38↑N↑L protease was not significantly different from that of wild type although there was a 42% reduction in specific activity for the variant. An in vitro phenotypic assay showed the L38↑N↑L protease to be susceptible to lopinavir (LPV), atazanavir (ATV) and darunavir in the context of an unrelated Gag. However, in the presence of the related Gag, L38↑N↑L showed reduced susceptibility to darunavir while remaining susceptible to LPV and ATV. Furthermore, a reduction in viral replication capacity (RC) was observed in combination with the related Gag. The reduced susceptibility to darunavir and decrease in RC may be due to PTAPP duplication in the related Gag. The present study shows the importance of considering the Gag region when looking at drug susceptibility of HIV-1 protease variants.

Gaussian accelerated molecular dynamics for elucidation of drug pathways

INTRODUCTION

Understanding pathways and mechanisms of drug binding to receptors is important for rational drug design. Remarkable advances in supercomputing and methodological developments have opened a new era for application of computer simulations in predicting drug-receptor interactions at an atomistic level. Gaussian accelerated molecular dynamics (GaMD) is a computational enhanced sampling technique that works by adding a harmonic boost potential to reduce energy barriers. GaMD enables free energy calculations without the requirement of predefined collective variables. GaMD has proven useful in biomolecular simulations, in particular, the prediction of drug-receptor interactions. Areas covered: Herein, the authors review recent GaMD simulation studies that elucidated pathways of drug binding to proteins including the G-protein-coupled receptors and HIV protease. Expert opinion: GaMD is advantageous for enhanced simulations of, amongst many biological processes, drug binding to target receptors. Compared with conventional molecular dynamics, GaMD speeds up biomolecular simulations by orders of magnitude. GaMD enables routine drug binding simulations using personal computers with GPUs or common computing clusters. GaMD and, more broadly, enhanced sampling simulations are expected to dramatically increase our capabilities to determine the mechanisms of drug binding to a wide range of receptors in the near future. This will greatly facilitate computer-aided drug design.

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.

Exploring the Reasons for Decrease in Binding Affinity of HIV-2 Against HIV-1 Protease Complex Using Interaction Entropy Under Polarized Force Field

In this study, the differences of binding patterns between two type HIV (HIV-1 and HIV-2) protease and two inhibitors (darunavir and amprenavir) are analyzed and compared using the newly developed interaction entropy (IE) method for the entropy change calculation combined with the polarized force field. The functional role of protonation states in the two HIV-2 complexes is investigated and our study finds that the protonated OD1 atom of Asp25' in B chain is the optimal choice. Those calculated binding free energies obtained from the polarized force field combined with IE method are significantly consistent with the experimental observed. The bridging water W301 is favorable to the binding of HIV-1 complexes; however, it is unfavorable to the HIV-2 complexes in current study. The volume of pocket, B-factor of Cα atoms and the distance of flap tip in HIV-2 complexes are smaller than that of HIV-1 consistently. These changes may cause localized rearrangement of residues lining their surface and finally result in the different binding mode for the two types HIV. Predicated hot-spot residues (Ala28/Ala28', Ile50/Ile50', and Ile84/Ile84') are nearly same in the four systems. However, the contribution to the free energy of Asp30 residue is more favorable in HIV-1 system than in HIV-2 system. Current study, to some extent, reveals the origin for the decrease in binding affinity of inhibitors against HIV-2 compared with HIV-1 and will provides theoretical guidance for future design of potent dual inhibitors targeting two type HIV protease.

Design, synthesis, X-ray studies, and biological evaluation of novel macrocyclic HIV-1 protease inhibitors involving the P1'-P2' ligands

Design, synthesis, and evaluation of a new class of HIV-1 protease inhibitors containing diverse flexible macrocyclic P1'-P2' tethers are reported. Inhibitor 5a with a pyrrolidinone-derived macrocycle exhibited favorable enzyme inhibitory and antiviral activity (K_i=13.2nM, IC₅₀=22nM). Further incorporation of heteroatoms in the macrocyclic skeleton provided macrocyclic inhibitors 5m and 5o. These compounds showed excellent HIV-1 protease inhibitory (K_i=62pM and 14pM, respectively) and antiviral activity (IC₅₀=5.3nM and 2.0nM, respectively). Inhibitor 5o also remained highly potent against a DRV-resistant HIV-1 variant.

Improving fold resistance prediction of HIV-1 against protease and reverse transcriptase inhibitors using artificial neural networks

Background

Drug resistance in HIV treatment is still a worldwide problem. Predicting resistance to antiretrovirals (ARVs) before starting any treatment is important. Prediction accuracy is essential, as low-accuracy predictions increase the risk of prescribing sub-optimal drug regimens leading to patients developing resistance sooner. Artificial Neural Networks (ANNs) are a powerful tool that would be able to assist in drug resistance prediction. In this study, we constrained the dataset to subtype B, sacrificing generalizability for a higher predictive performance, and demonstrated that the predictive quality of the ANN regression models have definite improvement for most ARVs.

Results

Trained regression ANNs were optimized for eight protease inhibitors, six nucleoside reverse transcriptase (RT) inhibitors and four non-nucleoside RT inhibitors by experimenting combinations of rare variant filtering (none versus 1 residue occurrence) and ANN topologies (1–3 hidden layers with 2, 4, 6, 8 and 10 nodes per layer). Single hidden layers (5–20 nodes) were used for training where overfitting was detected. 5-fold cross-validation produced mean R² values over 0.95 and standard deviations lower than 0.04 for all but two antiretrovirals.

Conclusions

Overall, higher accuracies and lower variances (compared to results published in 2016) were obtained by experimenting with various preprocessing methods, while focusing on the most prevalent subtype in the raw dataset (subtype B).We thus highlight the need to develop and make available subtype-specific datasets for developing higher accuracy in drug-resistance prediction methods.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-017-1782-x) contains supplementary material, which is available to authorized users.

The HIV-1 late domain-2 S40A polymorphism in antiretroviral (or ART)-exposed individuals influences protease inhibitor susceptibility

Background

The p6 region of the HIV-1 structural precursor polyprotein, Gag, contains two motifs, P₇TAP₁₁ and L₃₅YPLXSL₄₁, designated as late (L) domain-1 and -2, respectively. These motifs bind the ESCRT-I factor Tsg101 and the ESCRT adaptor Alix, respectively, and are critical for efficient budding of virus particles from the plasma membrane. L domain-2 is thought to be functionally redundant to PTAP. To identify possible other functions of L domain-2, we examined this motif in dominant viruses that emerged in a group of 14 women who had detectable levels of HIV-1 in both plasma and genital tract despite a history of current or previous antiretroviral therapy.

Results

Remarkably, variants possessing mutations or rare polymorphisms in the highly conserved L domain-2 were identified in seven of these women. A mutation in a conserved residue (S40A) that does not reduce Gag interaction with Alix and therefore did not reduce budding efficiency was further investigated. This mutation causes a simultaneous change in the Pol reading frame but exhibits little deficiency in Gag processing and virion maturation. Whether introduced into the HIV-1 NL4-3 strain genome or a model protease (PR) precursor, S40A reduced production of mature PR. This same mutation also led to high level detection of two extended forms of PR that were fairly stable compared to the WT in the presence of IDV at various concentrations; one of the extended forms was effective in trans processing even at micromolar IDV.

Conclusions

Our results indicate that L domain-2, considered redundant in vitro, can undergo mutations in vivo that significantly alter PR function. These may contribute fitness benefits in both the absence and presence of PR inhibitor.

Electronic supplementary material

The online version of this article (doi:10.1186/s12977-016-0298-1) contains supplementary material, which is available to authorized users.

Evolution under Drug Pressure Remodels the Folding Free-Energy Landscape of Mature HIV-1 Protease

Using high-pressure NMR spectroscopy and differential scanning calorimetry, we investigate the folding landscape of the mature HIV-1 protease homodimer. The cooperativity of unfolding was measured in the absence or presence of a symmetric active site inhibitor for the optimized wild type protease (PR), its inactive variant PRD25N, and an extremely multidrug-resistant mutant, PR20. The individual fit of the pressure denaturation profiles gives rise to first order, ∆GNMR, and second order, ∆VNMR (the derivative of ∆GNMR with pressure); apparent thermodynamic parameters for each amide proton considered. Heterogeneity in the apparent ∆VNMR values reflects departure from an ideal cooperative unfolding transition. The narrow to broad distribution of ∆VNMR spanning the extremes from inhibitor-free PR20D25N to PR-DMP323 complex, and distinctively for PRD25N-DMP323 complex, indicated large variations in folding cooperativity. Consistent with this data, the shape of thermal unfolding transitions varies from asymmetric for PR to nearly symmetric for PR20, as dimer-inhibitor ternary complexes. Lack of structural cooperativity was observed between regions located close to the active site, including the hinge and tip of the glycine-rich flaps, and the rest of the protein. These results strongly suggest that inhibitor binding drastically decreases the cooperativity of unfolding by trapping the closed flap conformation in a deep energy minimum. To evade this conformational trap, PR20 evolves exhibiting a smoother folding landscape with nearly an ideal two-state (cooperative) unfolding transition. This study highlights the malleability of retroviral protease folding pathways by illustrating how the selection of mutations under drug pressure remodels the free-energy landscape as a primary mechanism.

Unraveling HIV protease flaps dynamics by Constant pH Molecular Dynamics simulations

The active site of HIV protease (HIV-PR) is covered by two flaps. These flaps are known to be essential for the catalytic activity of the HIV-PR, but their exact conformations at the different stages of the enzymatic pathway remain subject to debate. Understanding the correct functional dynamics of the flaps might aid the development of new HIV-PR inhibitors. It is known that, the HIV-PR catalytic efficiency is pH-dependent, likely due to the influence of processes such as charge transfer and protonation/deprotonation of ionizable residues. Several Molecular Dynamics (MD) simulations have reported information about the HIV-PR flaps. However, in MD simulations the protonation of a residue is fixed and thus it is not possible to study the correlation between conformation and protonation state. To address this shortcoming, this work attempts to capture, through Constant pH Molecular Dynamics (CpHMD), the conformations of the apo, substrate-bound and inhibitor-bound HIV-PR, which differ drastically in their flap arrangements. The results show that the HIV-PR flaps conformations are defined by the protonation of the catalytic residues Asp25/Asp25' and that these residues are sensitive to pH changes. This study suggests that the catalytic aspartates can modulate the opening of the active site and substrate binding.

Design of new potent HTLV-1 protease inhibitors: in silico study

HTLV-1 and HIV-1 are two major causes for severe T-cell leukemia disease and acquired immune deficiency syndrome (AIDS). HTLV-1 protease, a member of aspartic acid protease family, plays important roles in maturation during virus replication cycle. The impairment of these proteases results in uninfectious HTLV-1virions.Similar to HIV-1protease deliberate mutations that confer drug resistance on HTLV-1 are frequently seen in this protease. Therefore, inhibition of HTLV-1 protease activity is expected to disrupt HTLV-1's ability to replicate and infect additional cells. In this study, we initially designed fifteen inhibitory compounds based on the conformations of a class of HIV-1 aspartyl protease inhibitors, sulfonamid-peptoid. Five compounds were chosen based on the goodness of their Drug-Likeness scoreusing "Lipinsk's rule of five". Here, using protein-ligand docking approach we compared the inhibitory constants of these compounds to those available in literatures and observed significantly higher inhibition for two compounds, SP-4 and SP-5. Our data suggest that the addition of two cyclic hydrocarbons to both ends of sulfonamide peptoids leads to the formation of new hydrophobic interactions due to the semi-circular form of these compounds, connecting the first chain of protease to the two ends of tested ligands via Hydrophobic interactions. We conclude that hydrophobic force plays an important role in suppressing protease activity especially for HTLV-1 protease, which in turn prevents the virus maturity. Therefore, designing and development of new ligands based on aromatic hydrocarbons in both ends of inhibitors is very promising for efficient treatment.

Structure-guided, target-based drug discovery - exploiting genome information from HIV to mycobacterial infections

The use of protein crystallography in structure-guided drug discovery allows identification of potential inhibitor-binding sites and optimisation of interactions of hits and lead compounds with a target protein. An early example of this approach was the use of the structure of HIV protease in designing AIDS antivirals. More recently, use of structure-guided design with fragment-based drug discovery, which reduces the size of screening libraries by decreasing complexity, has improved ligand efficiency in drug design. Here, we discuss the use of structure-guided target identification and lead optimisation using fragment-based approaches in the development of new antimicrobials for mycobacterial infections.

Direct Analysis of Gene Synthesis Reactions Using Solid-State Nanopores

Synthetic nucleic acids offer rich potential to understand and engineer new cellular functions, yet an unresolved limitation in their production and usage is deleterious products, which restrict design complexity and add cost. Herein, we employ a solid-state nanopore to differentiate molecules of a gene synthesis reaction into categories of correct and incorrect assemblies. This new method offers a solution that provides information on gene synthesis reactions in near-real time with higher complexity and lower costs. This advance can permit insights into gene synthesis reactions such as kinetics monitoring, real-time tuning, and optimization of factors that drive reaction-to-reaction variations as well as open venues between nanopore-sensing, synthetic biology, and DNA nanotechnology.

Virtual Screening for HIV Protease Inhibitors Using a Novel Database Filtering Procedure

A virtual screening to find novel inhibitors for HIV protease was performed on the ZINC database.1 A critical part in virtual screening and associated techniques is preliminary database filtering and size reduction and for that purpose a novel feature matrix matching procedure was used. The reduction of ∼14 million available ligands to a subset of 14299 ligands was achieved with a structure based approach where the analysis of the 3D structure of the active site of the protease produced a graph with hydrogen bond donor, hydrogen bond acceptor and hydrophobic subsites represented as graph nodes. A similar treatment was also applied to the compound database content and the comparison of binding site and ligand graphs was used to preselect potentially active ligands. The resulting set was further subjected to docking. The algorithm used was able to find several novel as well as previously known and experimentally tested ligands, demonstrating the validity of the approach.

Multi-drug resistance profile of PR20 HIV-1 protease is attributed to distorted conformational and drug binding landscape: molecular dynamics insights

The PR20 HIV-1 protease, a variant with 20 mutations, exhibits high levels of multi-drug resistance; however, to date, there has been no report detailing the impact of these 20 mutations on the conformational and drug binding landscape at a molecular level. In this report, we demonstrate the first account of a comprehensive study designed to elaborate on the impact of these mutations on the dynamic features as well as drug binding and resistance profile, using extensive molecular dynamics analyses. Comparative MD simulations for the wild-type and PR20 HIV proteases, starting from bound and unbound conformations in each case, were performed. Results showed that the apo conformation of the PR20 variant of the HIV protease displayed a tendency to remain in the open conformation for a longer period of time when compared to the wild type. This led to a phenomena in which the inhibitor seated at the active site of PR20 tends to diffuse away from the binding site leading to a significant change in inhibitor-protein association. Calculating the per-residue fluctuation (RMSF) and radius of gyration, further validated these findings. MM/GBSA showed that the occurrence of 20 mutations led to a drop in the calculated binding free energies (ΔGbind) by ~25.17 kcal/mol and ~5 kcal/mol for p2-NC, a natural peptide substrate, and darunavir, respectively, when compared to wild type. Furthermore, the residue interaction network showed a diminished inter-residue hydrogen bond network and changes in inter-residue connections as a result of these mutations. The increased conformational flexibility in PR20 as a result of loss of intra- and inter-molecular hydrogen bond interactions and other prominent binding forces led to a loss of protease grip on ligand. It is interesting to note that the difference in conformational flexibility between PR20 and WT conformations was much higher in the case of substrate-bound conformation as compared to DRV. Thus, developing analogues of DRV by retaining its key pharmacophore features will be the way forward in the search for novel protease inhibitors against multi-drug resistant strains.

FDT 2.0: Improving scalability of the fuzzy decision tree induction tool - integrating database storage

Effective machine-learning handles large datasets efficiently. One key feature of handling large data is the use of databases such as MySQL. The freeware fuzzy decision tree induction tool, FDT, is a scalable supervised-classification software tool implementing fuzzy decision trees. It is based on an optimized fuzzy ID3 (FID3) algorithm. FDT 2.0 improves upon FDT 1.0 by bridging the gap between data science and data engineering: it combines a robust decisioning tool with data retention for future decisions, so that the tool does not need to be recalibrated from scratch every time a new decision is required. In this paper we briefly review the analytical capabilities of the freeware FDT tool and its major features and functionalities; examples of large biological datasets from HIV, microRNAs and sRNAs are included. This work shows how to integrate fuzzy decision algorithms with modern database technology. In addition, we show that integrating the fuzzy decision tree induction tool with database storage allows for optimal user satisfaction in today's Data Analytics world.

Conformation of inhibitor-free HIV-1 protease derived from NMR spectroscopy in a weakly oriented solution

Flexibility of the glycine-rich flaps is known to be essential for catalytic activity of the HIV-1 protease, but their exact conformations at the different stages of the enzymatic pathway remain subject to much debate. Although hundreds of crystal structures of protease-inhibitor complexes have been solved, only about a dozen inhibitor-free protease structures have been reported. These latter structures reveal a large diversity of flap conformations, ranging from closed to semi-open to wide open. To evaluate the average structure in solution, we measured residual dipolar couplings (RDCs) and compared these to values calculated for crystal structures representative of the closed, semi-open, and wide-open states. The RDC data clearly indicate that the inhibitor-free protease, on average, adopts a closed conformation in solution that is very similar to the inhibitor-bound state. By contrast, a highly drug-resistant protease mutant, PR20, adopts the wide-open flap conformation.

Impact of Stereochemistry on Ligand Binding: X-ray Crystallographic Analysis of an Epoxide-Based HIV Protease Inhibitor

A new pseudopeptide epoxide inhibitor, designed for irreversible binding to HIV protease (HIV-PR), has been synthesized and characterized in solution and in the solid state. However, the crystal structure of the complex obtained by inhibitor-enzyme cocrystallization revealed that a minor isomer, with inverted configuration of the epoxide carbons, has been selected by HIV-PR during crystallization. The structural characterization of the well-ordered pseudopeptide, inserted in the catalytic channel with its epoxide group intact, provides deeper insights into inhibitor binding and HIV-PR stereoselectivity, which aids development of future epoxide-based HIV inhibitors.

Teaching foundational topics and scientific skills in biochemistry within the conceptual framework of HIV protease

HIV protease has served as a model protein for understanding protein structure, enzyme kinetics, structure-based drug design, and protein evolution. Inhibitors of HIV protease are also an essential part of effective HIV/AIDS treatment and have provided great societal benefits. The broad applications for HIV protease and its inhibitors make it a perfect framework for integrating foundational topics in biochemistry around a big picture scientific and societal issue. Herein, I describe a series of classroom exercises that integrate foundational topics in biochemistry around the structure, biology, and therapeutic inhibition of HIV protease. These exercises center on foundational topics in biochemistry including thermodynamics, acid/base properties, protein structure, ligand binding, and enzymatic catalysis. The exercises also incorporate regular student practice of scientific skills including analysis of primary literature, evaluation of scientific data, and presentation of technical scientific arguments. Through the exercises, students also gain experience accessing computational biochemical resources such as the protein data bank, Proteopedia, and protein visualization software. As these HIV centered exercises cover foundational topics common to all first semester biochemistry courses, these exercises should appeal to a broad audience of undergraduate students and should be readily integrated into a variety of teaching styles and classroom sizes.

Evaluation of novel Saquinavir analogs for resistance mutation compatibility and potential as an HIV-Protease inhibitor drug

A fundamental issue related to therapy of HIV-1 infection is the emergence of viral mutations which severely limits the long term efficiency of the HIV-protease (HIV-PR) inhibitors. Development of new drugs is therefore continuously needed. Chemoinformatics enables to design and discover novel molecules analogous to established drugs using computational tools and databases. Saquinavir, an anti-HIV Protease drug is administered for HIV therapy. In this work chemoinformatics tools were used to design structural analogs of Saquinavir as ligand and molecular dockings at AutoDock were performed to identify potential HIV-PR inhibitors. The analogs S1 and S2 when docked with HIV-PR had binding energies of -4.08 and -3.07 kcal/mol respectively which were similar to that for Saquinavir. The molecular docking studies revealed that the changes at N2 of Saquinavir to obtain newly designed analogs S1 (having N2 benzoyl group at N1) and S2 (having 3-oxo-3phenyl propanyl group at N2) were able to dock with HIV-PR with similar affinity as that of Saquinavir. Docking studies and computationally derived pharmacodynamic and pharmacokinetic properties׳ comparisons at ACD/I-lab establish that analog S2 has more potential to evade the problem of drug resistance mutation against HIV-1 PR subtype-A. S2 can be further developed and tested clinically as a real alternative drug for HIV-1 PR across the clades in future.

Quantitative assessment of in vivo HIV protease activity using genetically engineered QD-based FRET probes

HIV protease plays a central role in its life cycle leading to release of functional viral particles. It has been successfully used as a therapeutic target to block HIV infection. Several protease inhibitors (PIs) are currently being employed as a part of anti-HIV therapy. However, the constant genetic drift in the virus leads to accumulation of mutations in both cleavage site and the protease, resulting in resistance and failure of therapy. We reported the use of a quantum dot (QD)-based protein probe for the in vivo monitoring of HIV-1 protease activity based on fluorescence resonance energy transfer. In the current study, we demonstrate the utility of this approach by quantifying the in vivo cleavage rates of three known protease and cleavage site mutations in the presence or absence of different PIs. The changes in IC50 values for the different PIs were similar to that observed in patients, validating our assay as a rapid platform for PI screening.

Sparse Representation for Prediction of HIV-1 Protease Drug Resistance

HIV rapidly evolves drug resistance in response to antiviral drugs used in AIDS therapy. Estimating the specific resistance of a given strain of HIV to individual drugs from sequence data has important benefits for both the therapy of individual patients and the development of novel drugs. We have developed an accurate classification method based on the sparse representation theory, and demonstrate that this method is highly effective with HIV-1 protease. The protease structure is represented using our newly proposed encoding method based on Delaunay triangulation, and combined with the mutated amino acid sequences of known drug-resistant strains to train a machine-learning algorithm both for classification and regression of drug-resistant mutations. An overall cross-validated classification accuracy of 97% is obtained when trained on a publically available data base of approximately 1.5×10⁴ known sequences (Stanford HIV database http://hivdb.stanford.edu/cgi-bin/GenoPhenoDS.cgi). Resistance to four FDA approved drugs is computed and comparisons with other algorithms demonstrate that our method shows significant improvements in classification accuracy.

Development of a Novel Screening Strategy Designed to Discover a New Class of HIV Drugs

Current antiretroviral treatments target multiple pathways important for human immunodeficiency virus (HIV) multiplication, including viral entry, synthesis and integration of the DNA provirus, and the processing of viral polyprotein precursors. However, HIV is becoming increasingly resistant to these "combination therapies." Recent findings show that inhibition of HIV Gag protein cleavage into its two structural proteins, matrix (MA) and capsid (CA), has a devastating effect on viral production, revealing a potential new target class for HIV treatment. Unlike the widely used HIV protease inhibitors, this new class of inhibitor would target the substrate, not the protease enzyme itself. This approach offers a distinct advantage in that inhibitors of MA/CA would only need to affect a subset of the Gag molecules to disable viral replication. To discover MA/CA-specific inhibitors, we constructed a modified MA/CA fusion peptide (MA/CAΔ) that contains the HIV protease (PR) cleavage site as well as a tetracysteine motif for fluorescent labeling. The HIV PR cleavage of MA/CAΔ can then be monitored via fluorescence polarization (FP). We have adapted this FP assay for high-throughput screening and validated it according to industry standards using a 384-well plate format. We have currently tested 24,000 compounds in this assay and here detail the screening methodology and the results of this screening campaign.

Crystallographic fragment-based drug discovery: use of a brominated fragment library targeting HIV protease

A library of 68 brominated fragments was screened against a new crystal form of inhibited HIV-1 protease in order to probe surface sites in soaking experiments. Often, fragments are weak binders with partial occupancy, resulting in weak, difficult-to-fit electron density. The use of a brominated fragment library addresses this challenge, as bromine can be located unequivocally via anomalous scattering. Data collection was carried out in an automated fashion using AutoDrug at SSRL. Novel hits were identified in the known surface sites: 3-bromo-2,6-dimethoxybenzoic acid (Br6) in the flap site and 1-bromo-2-naphthoic acid (Br27) in the exosite, expanding the chemistry of known fragments for development of higher affinity potential allosteric inhibitors. At the same time, mapping the binding sites of a number of weaker binding Br-fragments provides further insight into the nature of these surface pockets.

Mining the protein data bank to differentiate error from structural variation in clustered static structures: an examination of HIV protease

The Protein Data Bank (PDB) contains over 71,000 structures. Extensively studied proteins have hundreds of submissions available, including mutations, different complexes, and space groups, allowing for application of data-mining algorithms to analyze an array of static structures and gain insight about a protein’s structural variation and possibly its dynamics. This investigation is a case study of HIV protease (PR) using in-house algorithms for data mining and structure superposition through generalized formulæ that account for multiple conformations and fractional occupancies. Temperature factors (B-factors) are compared with spatial displacement from the mean structure over the entire study set and separately over bound and ligand-free structures, to assess the significance of structural deviation in a statistical context. Space group differences are also examined.

Disubstituted Bis-THF Moieties as New P2 Ligands in Nonpeptidal HIV-1 Protease Inhibitors

A series of darunavir analogues featuring a substituted bis-THF ring as P2 ligand have been synthesized and evaluated. High affinity protease inhibitors (PIs) with an interesting activity on wild-type HIV and a panel of multi-PI resistant HIV-1 mutants containing clinically observed, primary mutations were identified using a cell-based assay. A number of PIs have been synthesized that show equivalent and greater activity for HIV-1 mutant strains as compared to wild-type HIV-1. The activity on the purified enzyme was confirmed for a selection of analogues.

Comparative studies on retroviral proteases: substrate specificity

Exogenous retroviruses are subclassified into seven genera and include viruses that cause diseases in humans. The viral Gag and Gag-Pro-Pol polyproteins are processed by the retroviral protease in the last stage of replication and inhibitors of the HIV-1 protease are widely used in AIDS therapy. Resistant mutations occur in response to the drug therapy introducing residues that are frequently found in the equivalent position of other retroviral proteases. Therefore, besides helping to understand the general and specific features of these enzymes, comparative studies of retroviral proteases may help to understand the mutational capacity of the HIV-1 protease.

Current and Novel Inhibitors of HIV Protease

The design, development and clinical success of HIV protease inhibitors represent one of the most remarkable achievements of molecular medicine. This review describes all nine currently available FDA-approved protease inhibitors, discusses their pharmacokinetic properties, off-target activities, side-effects, and resistance profiles. The compounds in the various stages of clinical development are also introduced, as well as alternative approaches, aiming at other functional domains of HIV PR. The potential of these novel compounds to open new way to the rational drug design of human viruses is critically assessed.