Potent antiviral HIV-1 protease inhibitor GRL-02031 adapts to the structures of drug resistant mutants with its P1'-pyrrolidinone ring

Emerging Promise of Computational Techniques in Anti-Cancer Research: At a Glance

Research on the immune system and cancer has led to the development of new medicines that enable the former to attack cancer cells. Drugs that specifically target and destroy cancer cells are on the horizon; there are also drugs that use specific signals to stop cancer cells multiplying. Machine learning algorithms can significantly support and increase the rate of research on complicated diseases to help find new remedies. One area of medical study that could greatly benefit from machine learning algorithms is the exploration of cancer genomes and the discovery of the best treatment protocols for different subtypes of the disease. However, developing a new drug is time-consuming, complicated, dangerous, and costly. Traditional drug production can take up to 15 years, costing over USD 1 billion. Therefore, computer-aided drug design (CADD) has emerged as a powerful and promising technology to develop quicker, cheaper, and more efficient designs. Many new technologies and methods have been introduced to enhance drug development productivity and analytical methodologies, and they have become a crucial part of many drug discovery programs; many scanning programs, for example, use ligand screening and structural virtual screening techniques from hit detection to optimization. In this review, we examined various types of computational methods focusing on anticancer drugs. Machine-based learning in basic and translational cancer research that could reach new levels of personalized medicine marked by speedy and advanced data analysis is still beyond reach. Ending cancer as we know it means ensuring that every patient has access to safe and effective therapies. Recent developments in computational drug discovery technologies have had a large and remarkable impact on the design of anticancer drugs and have also yielded useful insights into the field of cancer therapy. With an emphasis on anticancer medications, we covered the various components of computer-aided drug development in this paper. Transcriptomics, toxicogenomics, functional genomics, and biological networks are only a few examples of the bioinformatics techniques used to forecast anticancer medications and treatment combinations based on multi-omics data. We believe that a general review of the databases that are now available and the computational techniques used today will be beneficial for the creation of new cancer treatment approaches.

Management of Antiretroviral Therapy with Boosted Protease Inhibitors-Darunavir/Ritonavir or Darunavir/Cobicistat

A major challenge in the management of antiretroviral therapy (ART) is to improve the patient's adherence, reducing the burden caused by the high number of drugs that compose the treatment regimens for human immunodeficiency virus positive (HIV+) patients. Selection of the most appropriate treatment regimen is responsible for therapeutic success and aims to reduce viremia, increase the immune system response capacity, and reduce the incidence rate and intensity of adverse reactions. In general, protease inhibitor (PI) is one of the pillars of regimens, and darunavir (DRV), in particular, is frequently recommended, along with low doses of enzyme inhibitors as cobicistat (COBI) or ritonavir (RTV), by the international guidelines. The potential of clinically significant drug interactions in patients taking COBI or RTV is high due to the potent inhibitory effect on cytochrome CYP 450, which attracts significant changes in the pharmacokinetics of PIs. Regardless of the patient or type of virus, the combined regimens of DRV/COBI or DRV/RTV are available to clinicians, proving their effectiveness, with a major impact on HIV mortality/morbidity. This study presents current information on the pharmacokinetics, pharmacology, drug interactions, and adverse reactions of DRV; it not only compares the bioavailability, pharmacokinetic parameters, immunological and virological responses, but also the efficacy, advantages, and therapeutic disadvantages of DRV/COBI or DRV/RTV combinations.

Multiple Molecular Dynamics Simulations of the Inhibitor GRL-02031 Complex with Wild Type and Mutant HIV-1 Protease Reveal the Binding and Drug-Resistance Mechanism

Human immunodeficiency virus type 1 (HIV-1) protease is regarded as a fascinating target for drug development against HIV infection. However, mutations causing drug resistance severely limit the efficiency of the recently marketed drugs in the treatment of HIV replication. To elucidate the binding mechanism of HIV-1 protease with promising inhibitor GRL-02031 and further to probe the resistance mechanism associated with mutations (I47V, L76V, V82A, and N88D) to the inhibitor, we applied multiple molecular dynamics (MMD) simulations along with energy analysis by the molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) and solvated interaction energy (SIE) methodology on specific HIV-1 protease with GRL-0231 complexes. On the basis of detail analysis of the simulations, we revealed key characteristics that constitute the drug resistance of four mutation HIV-1 proteases toward GRL-02031: substitution of the side chain in these four mutation residues leads to a change in the distances between the flaps and catalytic sites, thereby reducing the affinity for GRL-02031 with these four mutation proteases, even though the L76V and N88D residues cannot directly contact GRL-02031. The results of energy analysis according to the MM-PBSA and SIE methods further indicated that hydrophobic interaction was considered to be the prime driving force for inhibitor GRL-02031 binding to protease and the decrease in van der Waals interactions between inhibitor GRL-02031 and mutant proteases as the primary cause of the drug resistance. Analyses of the hydrogen bonds and atomic interactions further provided detailed explanations for the resistance of these four mutation proteases toward inhibitor GRL-02031. The present study provides potential guidance on the structure-based inhibitors' design targeting HIV-1 protease.

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.

Exploration of the effects of sequence variations between HIV-1 and HIV-2 proteases on their three-dimensional structures

HIV protease inhibitors (PIs) approved by the FDA (US Food and Drug Administration) are a major class of antiretroviral. HIV-2 protease (PR2) is naturally resistant to most of them as PIs were designed for HIV-1 protease (PR1). In this study, we explored the impact of amino-acid substitutions between PR1 and PR2 on the structure of protease (PR) by comparing the structural variability of 13 regions using 24 PR1 and PR2 structures complexed with diverse ligands. Our analyses confirmed structural rigidity of the catalytic region and highlighted the important role of three regions in the conservation of the catalytic region conformation. Surprisingly, we showed that the flap region, corresponding to a flexible region, exhibits similar conformations in PR1 and PR2. Furthermore, we identified regions exhibiting different conformations in PR1 and PR2, which could be explained by the intrinsic flexibility of these regions, by crystal packing, or by PR1 and PR2 substitutions. Some substitutions induce structural changes in the R2 and R4 regions that could have an impact on the properties of PI-binding site and could thus modify PI binding mode. Substitutions involved in structural changes in the elbow region could alter the flexibility of the PR2 flap regions relative to PR1, and thus play a role in the transition from the semi-open form to the closed form, and have an impact on ligand binding. These results improve the understanding of the impact of sequence variations between PR1 and PR2 on the natural resistance of HIV-2 to commercially available PIs.Communicated by Ramaswamy H. Sarma.

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.

Developing HIV-1 Protease Inhibitors through Stereospecific Reactions in Protein Crystals

Protease inhibitors are key components in the chemotherapy of HIV infection. However, the appearance of viral mutants routinely compromises their clinical efficacy, creating a constant need for new and more potent inhibitors. Recently, a new class of epoxide-based inhibitors of HIV-1 protease was investigated and the configuration of the epoxide carbons was demonstrated to play a crucial role in determining the binding affinity. Here we report the comparison between three crystal structures at near-atomic resolution of HIV-1 protease in complex with the epoxide-based inhibitor, revealing an in-situ epoxide ring opening triggered by a pH change in the mother solution of the crystal. Increased pH in the crystal allows a stereospecific nucleophile attack of an ammonia molecule onto an epoxide carbon, with formation of a new inhibitor containing amino-alcohol functions. The described experiments open a pathway for the development of new stereospecific protease inhibitors from a reactive lead compound.

Recent Progress in the Development of HIV-1 Protease Inhibitors for the Treatment of HIV/AIDS

HIV-1 protease inhibitors continue to play an important role in the treatment of HIV/AIDS, transforming this deadly ailment into a more manageable chronic infection. Over the years, intensive research has led to a variety of approved protease inhibitors for the treatment of HIV/AIDS. In this review, we outline current drug design and medicinal chemistry efforts toward the development of next-generation protease inhibitors beyond the currently approved drugs.

Highly resistant HIV-1 proteases and strategies for their inhibition

The virally encoded protease is an important drug target for AIDS therapy. Despite the potency of the current drugs, infections with resistant viral strains limit the long-term effectiveness of therapy. Highly resistant variants of HIV protease from clinical isolates have different combinations of about 20 mutations and several orders of magnitude worse binding affinity for clinical inhibitors. Strategies are being explored to inhibit these highly resistant mutants. The existing inhibitors can be modified by introducing groups with the potential to form new interactions with conserved protease residues, and the flexible flaps. Alternative strategies are discussed, including designing inhibitors to bind to the open conformation of the protease dimer, and inhibition of the protease-catalyzed processing of the Gag-Pol precursor.

Extreme multidrug resistant HIV-1 protease with 20 mutations is resistant to novel protease inhibitors with P1'-pyrrolidinone or P2-tris-tetrahydrofuran

Extreme drug resistant mutant of HIV-1 protease (PR) bearing 20 mutations (PR20) has been studied with the clinical inhibitor amprenavir (1) and two potent antiviral investigational inhibitors GRL-02031 (2) and GRL-0519 (3). Clinical inhibitors are >1000-fold less active on PR20 than on wild-type enzyme, which is consistent with dissociation constants (KL) from isothermal titration calorimetry of 40 nM for 3, 178 nM for amprenavir, and 960 nM for 2. High resolution crystal structures of PR20-inhibitor complexes revealed altered interactions compared with the corresponding wild-type PR complexes in agreement with relative inhibition. Amprenavir lacks interactions due to PR20 mutations in the S2/S2' subsites relative to PR. Inhibitors 2 and 3 lose interactions with Arg8' in PR20 relative to the wild-type enzyme because Arg8' shifts to interact with mutated L10F side chain. Overall, inhibitor 3 compares favorably with darunavir in affinity for PR20 and shows promise for further development.

Novel P2 tris-tetrahydrofuran group in antiviral compound 1 (GRL-0519) fills the S2 binding pocket of selected mutants of HIV-1 protease

GRL-0519 (1) is a potent antiviral inhibitor of HIV-1 protease (PR) possessing tris-tetrahydrofuran (tris-THF) at P2. The high resolution X-ray crystal structures of inhibitor 1 in complexes with single substitution mutants PR(R8Q), PR(D30N), PR(I50V), PR(I54M), and PR(V82A) were analyzed in relation to kinetic data. The smaller valine side chain in PR(I50V) eliminated hydrophobic interactions with inhibitor and the other subunit consistent with 60-fold worse inhibition. Asn30 in PR(D30N) showed altered interactions with neighboring residues and 18-fold worse inhibition. Mutations V82A and I54M showed compensating structural changes consistent with 6-7-fold lower inhibition. Gln8 in PR(R8Q) replaced the ionic interactions of wild type Arg8 with hydrogen bond interactions without changing the inhibition significantly. The carbonyl oxygen of Gly48 showed two alternative conformations in all structures likely due to the snug fit of the large tris-THF group in the S2 subsite in agreement with high antiviral efficacy of 1 on resistant virus.