Structure-based design, synthesis, and structure-activity relationship studies of HIV-1 protease inhibitors incorporating phenyloxazolidinones

In silico Antivirus Repurposing and its Modification to Organoselenium Compounds as SARS-CoV-2 Spike Inhibitors

<b>Background and Objective:</b> The COVID-19, which has been circulating since late 2019, is caused by SARS-CoV-2. Because of its high infectivity, this virus has spread widely throughout the world. Spike glycoprotein is one of the proteins found in SARS-CoV-2. Spike glycoproteins directly affect infection by forming ACE-2 receptors on host cells. Inhibiting glycoprotein spikes could be one method of treating COVID-19. In this study, the antivirus marketed as a database will be repurposed into an antiviral SARS-CoV-2 and the selected compounds will be modified to become organoselenium compounds. <b>Materials and Methods:</b> The research was carried out using <i>in silico</i> methods, such as rigid docking and flexible docking. To obtain information about the interaction between spike glycoprotein and ligands, MOE 2014.09 was used to perform the molecular docking simulation. <b>Results:</b> The analysis of binding energy values was used to select the ten best ligands from the first stage of the molecular docking simulation, which was then modified according to the previous QSAR study to produce 96 new molecules. The second stage of molecular docking simulation was performed with modified molecules. The best-modified ligand was chosen by analyzing the ADME-Tox property, RMSD value and binding energy value. <b>Conclusion:</b> The best three unmodified ligands, Ombitasvir, Elbasvir and Ledipasvir, have a binding energy value of -15.8065, -15.3842 and -15.1255 kcal mol<sup>1</sup>, respectively and the best three modified ligands ModL1, ModL2 and ModL3 has a binding value of -15.6716, -13.9489 and -13.2951 kcal mol<sup>1</sup>, respectively with an RMSD value of 1.7109 Å, 2.3179 Å and 1.7836 Å.

MDO: A Computational Protocol for Prediction of Flexible Enzyme-Ligand Binding Mode

AIM

Developing a method for use in computer aided drug design Background: Predicting the structure of enzyme-ligand binding mode is essential for understanding the properties, functions, and mechanisms of the bio-complex, but is rather difficult due to the enormous sampling space involved.

OBJECTIVE

Accurate prediction of enzyme-ligand binding mode conformation.

METHOD

A new computational protocol, MDO, is proposed for finding the structure of ligand binding pose. MDO consists of sampling enzyme sidechain conformations via molecular dynamics simulation of enzyme-ligand system and clustering of the enzyme configurations, sampling ligand binding poses via molecular docking and clustering of the ligand conformations, and the optimal ligand binding pose prediction via geometry optimization and ranking by the ONIOM method. MDO is tested on 15 enzyme-ligand complexes with known accurate structures.

RESULTS

The success rate of MDO predictions, with RMSD < 2 Å, is 67%, substantially higher than the 40% success rate of conventional methods. The MDO success rate can be increased to 83% if the ONIOM calculations are applied only for the starting poses with ligands inside the binding cavities.

CONCLUSION

The MDO protocol provides high quality enzyme-ligand binding mode prediction with reasonable computational cost. The MDO protocol is recommended for use in the structure-based drug design.

Improving Drug Sensitivity of HIV-1 Protease Inhibitors by Restriction of Cellular Efflux System in a Fission Yeast Model

Fission yeast can be used as a cell-based system for high-throughput drug screening. However, higher drug concentrations are often needed to achieve the same effect as in mammalian cells. Our goal here was to improve drug sensitivity so reduced drugs could be used. Three different methods affecting drug uptakes were tested using an FDA-approved HIV-1 protease inhibitor (PI) drug Darunavir (DRV). First, we tested whether spheroplasts without cell walls increase the drug sensitivity. Second, we examined whether electroporation could be used. Although small improvements were observed, neither of these two methods showed significant increase in the EC₅₀ values of DRV compared with the traditional method. In contrast, when DRV was tested in a mutant strain PR836 that lacks key proteins regulating cellular efflux, a significant increase in the EC₅₀ was observed. A comparison of nine FDA-approved HIV-1 PI drugs between the wild-type RE294 strain and the mutant PR836 strain showed marked enhancement of the drug sensitivities ranging from an increase of 0.56 log to 2.48 logs. Therefore, restricting cellular efflux through the adaption of the described fission yeast mutant strain enhances the drug sensitivity, reduces the amount of drug used, and increases the chance of success in future drug discovery.

Combining classical molecular docking with self-consistent charge density-functional tight-binding computations for the efficient and quality prediction of ligand binding structure

To improve the successful prediction rate of the existing molecular docking methods, a new docking approach is proposed that consists of three steps: generating an ensemble of docked poses with a conventional docking method, performing clustering analysis of the ensemble to select the representative poses, and optimizing the representative structures with a low-cost quantum mechanics method. Three quantum mechanics methods, self-consistent charge density-functional tight-binding, ONIOM(DFT:PM6), and ONIOM(SCC-DFTB:PM6), are tested on 18 ligand-receptor bio-complexes. The rate of successful binding pose predictions by the proposed self-consistent charge density-functional tight-binding docking method is the highest, at 67%. The self-consistent charge density-functional tight-binding docking method should be useful for the structure-based drug design.

Drug discovery in the era of cryo-electron microscopy

Structure-based drug discovery (SBDD) is an indispensable approach for the design and optimization of new therapeutic agents. Here, we highlight the rapid progress that has turned cryo-electron microscopy (cryoEM) into an exceptional SBDD tool, and the wealth of new structural information it is providing for high-value pharmacological targets. We review key advantages of a technique that directly images vitrified biomolecules without the need for crystallization; both in terms of a broader array of systems that can be studied and the different forms of information it can provide, including heterogeneity and dynamics. We discuss near- and far-future developments, working in concert towards achieving the resolution and throughput necessary for cryoEM to make a widespread impact on the SBDD pipeline.

Single-Agent and Fixed-Dose Combination HIV-1 Protease Inhibitor Drugs in Fission Yeast (Schizosaccharomyces pombe)

Successful combination antiretroviral therapies (cART) eliminate active replicating HIV-1, slow down disease progression, and prolong lives. However, cART effectiveness could be compromised by the emergence of viral multidrug resistance, suggesting the need for new drug discoveries. The objective of this study was to further demonstrate the utility of the fission yeast cell-based systems that we developed previously for the discovery and testing of HIV protease (PR) inhibitors (PIs) against wild-type or multi-PI drug resistant _M11PR that we isolated from an infected individual. All thirteen FDA-approved single-agent and fixed-dose combination HIV PI drugs were tested. The effect of these drugs on HIV PR activities was tested in pure compounds or formulation drugs. All FDA-approved PI drugs, except for a prodrug FPV, were able to suppress the wild-type PR-induced cellular and enzymatic activities. Relative drug potencies measured by EC₅₀ in fission yeast were discussed in comparison with those measured in human cells. In contrast, none of the FDA-approved drugs suppressed the multi-PI drug resistant _M11PR activities. Results of this study show that fission yeast is a reliable cell-based system for the discovery and testing of HIV PIs and further demonstrate the need for new PI drugs against viral multi-PI resistance.

Benzothiazoles as potential antiviral agents

OBJECTIVES

The recent viral pandemic poses a unique challenge for healthcare providers. Despite the remarkable progress, the number of novel antiviral agents in the pipeline is woefully inadequate against the evolving virulence and drug resistance of current viruses. This highlights the urgent need for new and improved vaccines, diagnostics and therapeutic agents to obviate the viral pandemic.

KEY FINDINGS

Benzothiazole plays a pivotal role in the design and development of antiviral drugs. This is evident from the fact that it comprises many clinically useful agents. The current review is aimed to provide an insight into the recent development of benzothiazole-based antiviral agents, with a special focus on their structure-activity relationships and lead optimisation. One hundred and five articles were initially identified, and from these studies, 64 potential novel lead molecules and main findings were highlighted in this review.

SUMMARY

We hope this review will provide a logical perspective on the importance of improving the future designs of novel broad-spectrum benzothiazole-based antiviral agents to be used against emerging viral diseases.

The recent application of 3D-QSAR and docking studies to novel HIV-protease inhibitor drug discovery

INTRODUCTION

Despite the availability of FDA approved inhibitors of HIV protease, numerous efforts are still ongoing to achieve 'near-perfect' drugs devoid of characteristic adverse side effects, toxicities, and mutational resistance. While experimental methods have been plagued with huge consumption of time and resources, there has been an incessant shift towards the use of computational simulations in HIV protease inhibitor drug discovery.

AREAS COVERED

Herein, the authors review the numerous applications of 3D-QSAR modeling methods over recent years relative to the design of new HIV protease inhibitors from a series of experimentally derived compounds. Also, the augmentative contributions of molecular docking are discussed.

EXPERT OPINION

Efforts to optimize 3D QSAR and molecular docking for HIV-1 drug discovery are ongoing, which could further incorporate inhibitor motions at the active site using molecular dynamics parameters. Also, highly predictive machine learning algorithms such as random forest, K-means, decision trees, linear regression, hierarchical clustering, and Bayesian classifiers could be employed.

Performance of radial distribution function-based descriptors in the chemoinformatic studies of HIV-1 protease

Aim: This letter investigates the role of radial distribution function-based descriptors for in silico design of new drugs. Methodology: The multiple linear regression models for HIV-1 protease and its complexes with a series of inhibitors were constructed. A detailed analysis of major atomic contributions to the radial distribution function descriptor weighted by the number of valence shell electrons identified residues Arg8, Asp29 and residues of the catalytic triad as crucial for the correlation with the inhibition constant, together with residues Asp30 and Ile50, whose mutations are known to cause an emergence of drug resistant variants. Conclusion: This study demonstrates an easy and fast assessment of the activity of potential drugs and the derivation of structural information of their complexes with the receptor or enzyme.

Novel tertiary sulfonamide derivatives containing benzimidazole moiety as potent anti-gastric cancer agents: Design, synthesis and SAR studies

With the expectation to find out new anti-gastric cancer agents with high efficacy and selectivity, a series of novel tertiary sulfonamide derivatives were synthesized and the anti-cancer activity was studied in three selected cancer cell lines (MGC-803, PC-3, MCF-7) in vitro. Some of the synthesized compounds could significantly inhibit the proliferation of these tested cancer cells and were more potent than the positive control (5-Fu). The structure-activity relationship of tertiary sulfonamide derivatives was explored in this report. Among the tested compounds, compound 13g containing benzimidazole moiety showed the best anti-proliferation activities against MGC-803 cells (IC₅₀ = 1.02 μM), HGC-27 cells (IC₅₀ = 1.61 μM), SGC-7901 (IC₅₀ = 2.30 μM) cells as well as the good selectivity between the cancer and normal cells. Cellular mechanism studies elucidated compound 13g inhibited the colony formation of gastric cancer cell lines. Meanwhile, compound 13g arrested cell cycle at G2/M phase and induced cell apoptosis. Mechanistically, compound 13g markedly decreased p-Akt and p-c-Raf expression, which revealed that compound 13g targeted gastric cancer cell lines via interfering with AKT/mTOR and RAS/Raf/MEK/ERK pathways. All the findings suggest that compound 13g might be a valuable lead compound for the anti-gastric cancer agents.

Pharmaceutical and medicinal significance of sulfur (SVI)-Containing motifs for drug discovery: A critical review

Sulfur (S^VI) based moieties, especially, the sulfonyl or sulfonamide based analogues have showed a variety of pharmacological properties, and its derivatives propose a high degree of structural diversity that has established useful for the finding of new therapeutic agents. The developments of new less toxic, low cost and highly active sulfonamides containing analogues are hot research topics in medicinal chemistry. Currently, more than 150 FDA approved Sulfur (S^VI)-based drugs are available in the market, and they are widely used to treat various types of diseases with therapeutic power. This comprehensive review highlights the recent developments of sulfonyl or sulfonamides based compounds in huge range of therapeutic applications such as antimicrobial, anti-inflammatory, antiviral, anticonvulsant, antitubercular, antidiabetic, antileishmanial, carbonic anhydrase, antimalarial, anticancer and other medicinal agents. We believe that, this review article is useful to inspire new ideas for structural design and developments of less toxic and powerful Sulfur (S^VI) based drugs against the numerous death-causing diseases.

Classification of HIV-1 Protease Inhibitors by Machine Learning Methods

HIV-1 protease plays an important role in the processing of virus infection. Protease is an effective therapeutic target for the treatment of HIV-1. Our data set is based on a selection of 4855 HIV-1 protease inhibitors (PIs) from ChEMBL. A series of 15 classification models for predicting the active inhibitors were built by machine learning methods, including k-nearest neighors (K-NN), decision tree (DT), random forest (RF), support vector machine (SVM), and deep neural network (DNN). The molecular structures were characterized by (1) fingerprint descriptors including MACCS fingerprints and PubChem fingerprints and (2) physicochemical descriptors calculated by CORINA Symphony. The prediction accuracies of all of the models are more than 70% on the test set; the best accuracy of 83.07% was obtained by model 4A, which was built by the SVM method based on MACCS fingerprint descriptors. Nine consensus models were built with three kinds of different descriptors, which combined all of the machine learning methods using the "consensus prediction". Model C3_a developed with MACCS fingerprint descriptors showed the highest accuracy on both training set (91.96%) and test set (83.15%). An external validation set including 35 989 compounds from DUD database and 239 active inhibitors from the recent literature was used to verify the performance of our model. The best prediction accuracy of 98.37% was obtained by model 3C, which was built by RF based on CORINA Symphony descriptors. In addition, from the analysis of molecular descriptors, it shows that the aromatic system and atoms related to hydrogen bonding provide important contributions to the bioactivity of PIs.

Structural exploration of hydroxyethylamines as HIV-1 protease inhibitors: new features identified

The current study deals with chemometric modelling strategies (Naïve Bayes classification, hologram-based quantitative structure-activity relationship (HQSAR), comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA)) to explore the important features of hydroxylamine derivatives for exerting potent human immunodeficiency virus-1 (HIV-1) protease inhibition. Depending on the statistically validated reliable and robust quantitative structure-activity relationship (QSAR) models, important and crucial structural features have been identified that may be responsible for enhancing the activity profile of these hydroxylamine compounds. Arylsulfonamide function along with methoxy or fluoro substitution is important for enhancing activity. Bulky steric substitution at the sulfonamide nitrogen disfavours activity whereas smaller hydrophobic substitution at the same position is found to be favourable. Apart from the crucial oxazolidinone moiety, pyrrolidine, cyclic urea and methyl ester functions are also responsible for increasing the HIV-1 protease inhibitory profile. Observations derived from these modelling studies may be utilized further in designing promising HIV-1 protease inhibitors of this class.

Synthesis of N-(Hetero)aryl Carbamates via CuI/MNAO Catalyzed Cross-Coupling of (Hetero)aryl Halides with Potassium Cyanate in Alcohols

An efficient route to N-(hetero)aryl carbamates was developed through CuI/MNAO [2-((2-methylnaphthalen-1-yl)amino)-2-oxoacetic acid] catalyzed cross-coupling of (hetero)aryl chlorides with potassium cyanate in alcohols at 120-130 °C. This method utilizes broadly available substrates to afford various N-(hetero)aryl carbamates in good to excellent yields. Moreover, (hetero)aryl bromides and (hetero)aryl iodides were also reacted at low catalyst loadings and relatively low temperatures to provide N-(hetero)aryl carbamates.

Hydroxyethylamine derivatives as HIV-1 protease inhibitors: a predictive QSAR modelling study based on Monte Carlo optimization

Application of HIV-1 protease inhibitors (as an anti-HIV regimen) may serve as an attractive strategy for anti-HIV drug development. Several investigations suggest that there is a crucial need to develop a novel protease inhibitor with higher potency and reduced toxicity. Monte Carlo optimized QSAR study was performed on 200 hydroxyethylamine derivatives with antiprotease activity. Twenty-one QSAR models with good statistical qualities were developed from three different splits with various combinations of SMILES and GRAPH based descriptors. The best models from different splits were selected on the basis of statistically validated characteristics of the test set and have the following statistical parameters: r² = 0.806, Q² = 0.788 (split 1); r² = 0.842, Q² = 0.826 (split 2); r² = 0.774, Q² = 0.755 (split 3). The structural attributes obtained from the best models were analysed to understand the structural requirements of the selected series for HIV-1 protease inhibitory activity. On the basis of obtained structural attributes, 11 new compounds were designed, out of which five compounds were found to have better activity than the best active compound in the series.

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′ and S2′ 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′ subsite highly influences other subsites: the extension of the hydrophobic P1′ moiety results in 1) reduced van der Waals contacts in the P2′ 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.

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.

Recent patents and emerging therapeutics for HIV infections: a focus on protease inhibitors

The inclusion of protease inhibitors (PIs) in highly active antiretroviral therapy has significantly improved clinical outcomes in HIV-1-infected patients. To date, PIs are considered to be the most important therapeutic agents for the treatment of HIV infections. Despite high anti-HIV-1 potency, poor oral bioavailability of PIs has been a major concern. For achieving therapeutic concentrations, large doses of PIs are administered, which results in unacceptable systemic toxicities. Such severe and long-term toxicities necessitate the development of safer and potentially promising PIs. Recently, considerable attention has been paid to the development of newer compounds capable of inhibiting wild-type and resistant HIV-1 protease. Some of these PIs have displayed potent HIV-1 protease inhibitory activity. In this review, we have made an attempt to provide an overview on clinically approved and newly developing PIs, and related recent patents in the development of novel PIs.

Measuring the shapes of macromolecules - and why it matters

The molecular basis of life rests on the activity of biological macromolecules, mostly nucleic acids and proteins. A perhaps surprising finding that crystallized over the last handful of decades is that geometric reasoning plays a major role in our attempt to understand these activities. In this paper, we address this connection between geometry and biology, focusing on methods for measuring and characterizing the shapes of macromolecules. We briefly review existing numerical and analytical approaches that solve these problems. We cover in more details our own work in this field, focusing on the alpha shape theory as it provides a unifying mathematical framework that enable the analytical calculations of the surface area and volume of a macromolecule represented as a union of balls, the detection of pockets and cavities in the molecule, and the quantification of contacts between the atomic balls. We have shown that each of these quantities can be related to physical properties of the molecule under study and ultimately provides insight on its activity. We conclude with a brief description of new challenges for the alpha shape theory in modern structural biology.

Testing the substrate-envelope hypothesis with designed pairs of compounds

Acquired resistance to therapeutic agents is a significant barrier to the development of clinically effective treatments for diseases in which evolution occurs on clinical time scales, frequently arising from target mutations. We previously reported a general strategy to design effective inhibitors for rapidly mutating enzyme targets, which we demonstrated for HIV-1 protease inhibition [Altman et al. J. Am. Chem. Soc. 2008, 130, 6099–6113]. Specifically, we developed a computational inverse design procedure with the added constraint that designed inhibitors bind entirely inside the substrate envelope, a consensus volume occupied by natural substrates. The rationale for the substrate-envelope constraint is that it prevents designed inhibitors from making interactions beyond those required by substrates and thus limits the availability of mutations tolerated by substrates but not by designed inhibitors. The strategy resulted in subnanomolar inhibitors that bind robustly across a clinically derived panel of drug-resistant variants. To further test the substrate-envelope hypothesis, here we have designed, synthesized, and assayed derivatives of our original compounds that are larger and extend outside the substrate envelope. Our designs resulted in pairs of compounds that are very similar to one another, but one respects and one violates the substrate envelope. The envelope-respecting inhibitor demonstrates robust binding across a panel of drug-resistant protease variants, whereas the envelope-violating one binds tightly to wild type but loses affinity to at least one variant. This study provides strong support for the substrate-envelope hypothesis as a design strategy for inhibitors that reduce susceptibility to resistance mutations.

Substrate envelope-designed potent HIV-1 protease inhibitors to avoid drug resistance

The rapid evolution of HIV under selective drug pressure has led to multidrug resistant (MDR) strains that evade standard therapies. We designed highly potent HIV-1 protease inhibitors (PIs) using the substrate envelope model, which confines inhibitors within the consensus volume of natural substrates, providing inhibitors less susceptible to resistance because a mutation affecting such inhibitors will simultaneously affect viral substrate processing. The designed PIs share a common chemical scaffold but utilize various moieties that optimally fill the substrate envelope, as confirmed by crystal structures. The designed PIs retain robust binding to MDR protease variants and display exceptional antiviral potencies against different clades of HIV as well as a panel of 12 drug-resistant viral strains. The substrate envelope model proves to be a powerful strategy to develop potent and robust inhibitors that avoid drug resistance.

HIV-1 assembly, budding, and maturation

A defining property of retroviruses is their ability to assemble into particles that can leave producer cells and spread infection to susceptible cells and hosts. Virion morphogenesis can be divided into three stages: assembly, wherein the virion is created and essential components are packaged; budding, wherein the virion crosses the plasma membrane and obtains its lipid envelope; and maturation, wherein the virion changes structure and becomes infectious. All of these stages are coordinated by the Gag polyprotein and its proteolytic maturation products, which function as the major structural proteins of the virus. Here, we review our current understanding of the mechanisms of HIV-1 assembly, budding, and maturation, starting with a general overview and then providing detailed descriptions of each of the different stages of virion morphogenesis.

A combined 3D-QSAR and docking studies for the In-silico prediction of HIV-protease inhibitors

BACKGROUND

Tremendous research from last twenty years has been pursued to cure human life against HIV virus. A large number of HIV protease inhibitors are in clinical trials but still it is an interesting target for researchers due to the viral ability to get mutated. Mutated viral strains led the drug ineffective but still used to increase the life span of HIV patients.

RESULTS

In the present work, 3D-QSAR and docking studies were performed on a series of Danuravir derivatives, the most potent HIV- protease inhibitor known so far. Combined study of 3D-QSAR was applied for Danuravir derivatives using ligand-based and receptor-based protocols and generated models were compared. The results were in good agreement with the experimental results. Additionally, docking analysis of most active 32 and least active 46 compounds into wild type and mutated protein structures further verified our results. The 3D-QSAR and docking results revealed that compound 32 bind efficiently to the wild and mutated protein whereas, sufficient interactions were lost in compound 46.

CONCLUSION

The combination of two computational techniques would helped to make a clear decision that compound 32 with well inhibitory activity bind more efficiently within the binding pocket even in case of mutant virus whereas compound 46 lost its interactions on mutation and marked as least active compound of the series. This is all due to the presence or absence of substituents on core structure, evaluated by 3D-QSAR studies. This set of information could be used to design highly potent drug candidates for both wild and mutated form of viruses.

Significant reduction in errors associated with nonbonded contacts in protein crystal structures: automated all-atom refinement with PrimeX

All-atom models are essential for many applications in molecular modeling and computational chemistry. Nonbonded atomic contacts much closer than the sum of the van der Waals radii of the two atoms (clashes) are commonly observed in such models derived from protein crystal structures. A set of 94 recently deposited protein structures in the resolution range 1.5-2.8 Å were analyzed for clashes by the addition of all H atoms to the models followed by optimization and energy minimization of the positions of just these H atoms. The results were compared with the same set of structures after automated all-atom refinement with PrimeX and with nonbonded contacts in protein crystal structures at a resolution equal to or better than 0.9 Å. The additional PrimeX refinement produced structures with reasonable summary geometric statistics and similar R(free) values to the original structures. The frequency of clashes at less than 0.8 times the sum of van der Waals radii was reduced over fourfold compared with that found in the original structures, to a level approaching that found in the ultrahigh-resolution structures. Moreover, severe clashes at less than or equal to 0.7 times the sum of atomic radii were reduced 15-fold. All-atom refinement with PrimeX produced improved crystal structure models with respect to nonbonded contacts and yielded changes in structural details that dramatically impacted on the interpretation of some protein-ligand interactions.

Design, synthesis, and biological and structural evaluations of novel HIV-1 protease inhibitors to combat drug resistance

A series of new HIV-1 protease inhibitors (PIs) were designed using a general strategy that combines computational structure-based design with substrate-envelope constraints. The PIs incorporate various alcohol-derived P2 carbamates with acyclic and cyclic heteroatomic functionalities into the (R)-hydroxyethylamine isostere. Most of the new PIs show potent binding affinities against wild-type HIV-1 protease and three multidrug resistant (MDR) variants. In particular, inhibitors containing the 2,2-dichloroacetamide, pyrrolidinone, imidazolidinone, and oxazolidinone moieties at P2 are the most potent with K(i) values in the picomolar range. Several new PIs exhibit nanomolar antiviral potencies against patient-derived wild-type viruses from HIV-1 clades A, B, and C and two MDR variants. Crystal structure analyses of four potent inhibitors revealed that carbonyl groups of the new P2 moieties promote extensive hydrogen bond interactions with the invariant Asp29 residue of the protease. These structure-activity relationship findings can be utilized to design new PIs with enhanced enzyme inhibitory and antiviral potencies.

SAR and Lead Optimization of an HIV-1 Vif-APOBEC3G Axis Inhibitor

We describe structure-activity relationship and optimization studies of RN-18, an HIV-1 Vif-APOBEC3G axis inhibitor. Targeted modifications of RN-18 ring-C, ring-B, ring-A, bridge A-B, and bridge B-C were performed to identify the crucial structural features, which generated new inhibitors with similar (4g and 4i) and improved (5, 8b, and 11) activities. Two potent water-soluble RN-18 analogues, 17 and 19, are also disclosed, and we describe the results of pharmacological studies with compound 19. The findings described here will be useful in the development of more potent Vif inhibitors and in the design of probes to identify the target protein of RN-18 and its analogues.

Tetrahydrofuran, tetrahydropyran, triazoles and related heterocyclic derivatives as HIV protease inhibitors

HIV/AIDS remains a formidable disease with millions of individuals inflicted worldwide. Although treatment regimens have improved considerably, drug resistance brought on by viral mutation continues to erode their effectiveness. Intense research efforts are currently underway in search of new and improved therapies. This review is concerned with the design of novel HIV-1 protease inhibitors that incorporate heterocyclic scaffolds and which have been reported within the recent literature (2005-2010). Various examples in this review showcase the essential role heterocycles play as scaffolds and bioisosteres in HIV-1 protease inhibitor drug development. This review will hopefully stimulate the widespread application of these heterocycles in the design of other therapeutic agents.