Discovery of wild-type and Y181C mutant non-nucleoside HIV-1 reverse transcriptase inhibitors using virtual screening with multiple protein structures

Contemporary Medicinal Chemistry Strategies for the Discovery and Development of Novel HIV-1 Non-nucleoside Reverse Transcriptase Inhibitors

Currently, HIV-1 non-nucleoside reverse transcriptase inhibitors (NNRTIs) are a major component of the highly active anti-retroviral therapy (HAART) regimen. However, the occurrence of drug-resistant strains and adverse reactions after long-term usage have inevitably compromised the clinical application of NNRTIs. Therefore, the development of novel inhibitors with distinct anti-resistance profiles and better pharmacological properties is still an enormous challenge. Herein, we summarize state-of-the-art medicinal chemistry strategies for the discovery of potent NNRTIs, such as structure-based design strategies, contemporary computer-aided drug design, covalent-binding strategies, and the application of multi-target-directed ligands. The strategies described here will facilitate the identification of promising HIV-1 NNRTIs.

Medicinal chemistry strategies for discovering antivirals effective against drug-resistant viruses

During the last forty years we have witnessed impressive advances in the field of antiviral drug discovery culminating with the introduction of therapies able to stop human immunodeficiency virus (HIV) replication, or cure hepatitis C virus infections in people suffering from liver disease. However, there are important viral diseases without effective treatments, and the emergence of drug resistance threatens the efficacy of successful therapies used today. In this review, we discuss strategies to discover antiviral compounds specifically designed to combat drug resistance. Currently, efforts in this field are focused on targeted proteins (e.g. multi-target drug design strategies), but also on drug conformation (either improving drug positioning in the binding pocket or introducing conformational constraints), in the introduction or exploitation of new binding sites, or in strengthening interaction forces through the introduction of multiple hydrogen bonds, covalent binding, halogen bonds, additional van der Waals forces or multivalent binding. Among the new developments, proteolysis targeting chimeras (PROTACs) have emerged as a valid approach taking advantage of intracellular mechanisms involving protein degradation by the ubiquitin-proteasome system. Finally, several molecules targeting host factors (e.g. human dihydroorotate dehydrogenase and DEAD-box polypeptide 3) have been identified as broad-spectrum antiviral compounds. Implementation of herein described medicinal chemistry strategies are expected to contribute to the discovery of new drugs effective against current and future threats due to emerging and re-emerging viral pandemics.

Computational drug design strategies applied to the modelling of human immunodeficiency virus-1 reverse transcriptase inhibitors

Reverse transcriptase (RT) is a multifunctional enzyme in the human immunodeficiency virus (HIV)-1 life cycle and represents a primary target for drug discovery efforts against HIV-1 infection. Two classes of RT inhibitors, the nucleoside RT inhibitors (NRTIs) and the nonnucleoside transcriptase inhibitors are prominently used in the highly active antiretroviral therapy in combination with other anti-HIV drugs. However, the rapid emergence of drug-resistant viral strains has limited the successful rate of the anti-HIV agents. Computational methods are a significant part of the drug design process and indispensable to study drug resistance. In this review, recent advances in computer-aided drug design for the rational design of new compounds against HIV-1 RT using methods such as molecular docking, molecular dynamics, free energy calculations, quantitative structure-activity relationships, pharmacophore modelling and absorption, distribution, metabolism, excretion and toxicity prediction are discussed. Successful applications of these methodologies are also highlighted.

Computer-aided discovery of anti-HIV agents

A review is provided on efforts in our laboratory over the last decade to discover anti-HIV agents. The work has focused on computer-aided design and synthesis of non-nucleoside inhibitors of HIV-1 reverse transcriptase (NNRTIs) with collaborative efforts on biological assaying and protein crystallography. Numerous design issues were successfully addressed including the need for potency against a wide range of viral variants, good aqueous solubility, and avoidance of electrophilic substructures. Computational methods including docking, de novo design, and free-energy perturbation (FEP) calculations made essential contributions. The result is novel NNRTIs with picomolar and low-nanomolar activities against wild-type HIV-1 and key variants that also show much improved solubility and lower cytotoxicity than recently approved drugs in the class.

Design, discovery, modelling, synthesis, and biological evaluation of novel and small, low toxicity s-triazine derivatives as HIV-1 non-nucleoside reverse transcriptase inhibitors

A set of top-ranked compounds from a multi-objective in silico screen was experimentally tested for toxicity and the ability to inhibit the activity of HIV-1 reverse transcriptase (RT) in cell-free assay and in cell-based assay using HIV-1 based virus-like particles. Detailed analysis of a commercial sample that indicated specific inhibition of HIV-1 reverse transcription revealed that a minor component that was structurally similar to that of the main compound was responsible for the strongest inhibition. As a result, novel s-triazine derivatives were proposed, modelled, discovered, and synthesised, and their antiviral activity and cellular toxicity were tested. Compounds 18a and 18b were found to be efficient HIV-1 RT inhibitors, with an IC50 of 5.6±1.1μM and 0.16±0.05μM in a cell-based assay using infectious HIV-1, respectively. Compound 18b also had no detectable toxicity for different human cell lines. Their binding mode and interactions with the RT suggest that there was strong and adaptable binding in a tight (NNRTI) hydrophobic pocket. In summary, this iterative study produced structural clues and led to a group of non-toxic, novel compounds to inhibit HIV-RT with up to nanomolar potency.

Advances in the development of pyridinone derivatives as non-nucleoside reverse transcriptase inhibitors

Medicinal chemistry, computational design and biological screening have advanced pyridin-2(1H)-one derivatives as a promising class of non-nucleoside reverse transcriptase inhibitors for the treatment of HIV/AIDS.

Ligand similarity guided receptor selection enhances docking accuracy and recall for non-nucleoside HIV reverse transcriptase inhibitors

Non-nucleoside reverse transcriptase inhibitors (NNRTI) are allosteric inhibitors of human immunodeficiency virus type 1 (HIV-1) reverse transcriptase (RT), a viral polymerase essential to infection. Despite the availability of >150 NNRTI-bound RT crystal structures, rational design of new NNRTI remains challenging because of the variability of their induced fit, hydrophobic binding patterns. Docking NNRTI yields inconsistent results that vary markedly depending on the receptor structure used, as only 27% of the >20k cross-docking calculations we performed using known NNRTI were accurate. In order to determine if a hospitable receptor for docking could be selected a priori, we evaluated more than 40 chemical descriptors for their ability to pre-select a best receptor for NNRTI cross-docking. The receptor selection was based on similarity scores between the bound- and target-ligands generated by each descriptor. The top descriptors were able to double the probability of cross-docking accuracy over random receptor selection. Additionally, recall of known NNRTI from a large library of similar decoys was increased using the same approach. The results demonstrate the utility of pre-selecting receptors when docking into difficult targets. Graphical Abstract Cross-docking accuracy increases when using chemical descriptors to determine the NNRTI with maximum similarity to the new compound and then docking into its respective receptor.

Improving the use of ranking in virtual screening against HIV-1 integrase with triangular numbers and including ligand profiling with antitargets

A delicate balance exists between a drug molecule's toxicity and its activity. Indeed, efficacy, toxicity, and side effect problems are a common cause for the termination of drug candidate compounds and development projects. To address this, an antitarget interaction profile is built and combined with virtual screening and cross docking for new inhibitors of HIV-1 integrase, in order to consider possible off-target interactions as early as possible in a drug or hit discovery program. New ranking techniques using triangular numbers improve ranking information on the compounds and recovery of known inhibitors into the top compounds using different docking programs. This improved ranking arises from using consensus of ranks between docking programs and ligand efficiencies to derive a new rank, instead of using absolute score values, or average of ranks. The triangular number rerank also allowed the objective combination of results from several protein targets or screen conditions and several programs. Triangular number reranking conserves more information than other reranking methods such as average of scores or averages of ranks. In addition, the use of triangular numbers for reranking makes possible the use of thresholds with a justified leeway based on the number of available known inhibitors, so that the majority of the compounds above the threshold in ranks compare to the compounds that have known experimentally determined biological activity. The battery of anti- or off-targets can be tailored to specific molecular or drug design challenges. In silico filters can thus be deployed in successive stages, for prefiltering, activity profiling, and for further analysis and triaging of libraries of compounds.

Discovery of novel inhibitors of HIV-1 reverse transcriptase through virtual screening of experimental and theoretical ensembles

Non-nucleoside reverse transcriptase inhibitors (NNRTIs) are potent anti-HIV chemotherapeutics. Although there are FDA-approved NNRTIs, challenges such as the development of resistance have limited their utility. Here, we describe the identification of novel NNRTIs through a combination of computational and experimental approaches. Based on the known plasticity of the NNRTI binding pocket (NNIBP), we adopted an ensemble-based virtual screening strategy: coupling receptor conformations from 10 X-ray crystal structures with 120 snapshots from a total of 480 ns of molecular dynamics (MD) trajectories. A screening library of 2864 National Cancer Institute (NCI) compounds was built and docked against the ensembles in a hierarchical fashion. Sixteen diverse compounds were tested for their ability to block HIV infection in human tissue cultures using a luciferase-based reporter assay. Three promising compounds were further characterized, using a HIV-1 RT-based polymerase assay, to determine the specific mechanism of inhibition. We found that 2 of the three compounds inhibited the polymerase activity of RT (with potency similar to the positive control, the FDA-approved drug nevirapine). Through a computational approach, we were able to discover two compounds which inhibit HIV replication and block the activity of RT, thus offering the potential for optimization into mature inhibitors.

Identification of HIV inhibitors guided by free energy perturbation calculations

Free energy perturbation (FEP) theory coupled to molecular dynamics (MD) or Monte Carlo (MC) statistical mechanics offers a theoretically precise method for determining the free energy differences of related biological inhibitors. Traditionally requiring extensive computational resources and expertise, it is only recently that its impact is being felt in drug discovery. A review of computer-aided anti-HIV efforts employing FEP calculations is provided here that describes early and recent successes in the design of human immunodeficiency virus type 1 (HIV-1) protease and non-nucleoside reverse transcriptase inhibitors. In addition, our ongoing work developing and optimizing leads for small molecule inhibitors of cyclophilin A (CypA) is highlighted as an update on the current capabilities of the field. CypA has been shown to aid HIV-1 replication by catalyzing the cis/trans isomerization of a conserved Gly-Pro motif in the Nterminal domain of HIV-1 capsid (CA) protein. In the absence of a functional CypA, e.g., by the addition of an inhibitor such as cyclosporine A (CsA), HIV-1 has reduced infectivity. Our simulations of acylurea-based and 1-indanylketone-based CypA inhibitors have determined that their nanomolar and micromolar binding affinities, respectively, are tied to their ability to stabilize Arg55 and Asn102. A structurally novel 1-(2,6-dichlorobenzamido) indole core was proposed to maximize these interactions. FEP-guided optimization, experimental synthesis, and biological testing of lead compounds for toxicity and inhibition of wild-type HIV-1 and CA mutants have demonstrated a dose-dependent inhibition of HIV-1 infection in two cell lines. While the inhibition is modest compared to CsA, the results are encouraging.

On the use of molecular dynamics receptor conformations for virtual screening

Receptors are inherently dynamic and this flexibility is important to consider when constructing a model of molecular association. Conformations from molecular dynamics simulations, a well-established method for examining protein dynamics, can be used in virtual screening to account for flexibility in structure-based drug discovery. Different receptor configurations influence docking results. Molecular dynamics simulations can provide snapshots that improve virtual screening predictive power over known crystal structures, most likely as a result of sampling more relevant receptor conformations. Here we highlight some details and nuances of using such snapshots and evaluating them for predictive performance.

In silico virtual screening approaches for anti-viral drug discovery

Despite the considerable advances in medical and pharmaceutical research during the past years, diseases caused by viruses have remained a major burden to public health. Virtual in silico screening has repeatedly proven to be useful to meet the special challenges of antiviral drug discovery. Large virtual compound libraries are filtered by different computational screening methods such as docking, ligand-based similarity searches or pharmacophore-based screening, reducing the number of candidate molecules to a smaller set of promising candidates that are then tested biologically. This rational approach makes the drug discovery process more goal-oriented and saves resources in terms of time and money. In this review we discuss how different virtual screening techniques can be applied to antiviral drug discovery, present recent success stories in this field and finally address the main differences between the methods.:

Rational prediction with molecular dynamics for hit identification

Although the motions of proteins are fundamental for their function, for pragmatic reasons, the consideration of protein elasticity has traditionally been neglected in drug discovery and design. This review details protein motion, its relevance to biomolecular interactions and how it can be sampled using molecular dynamics simulations. Within this context, two major areas of research in structure-based prediction that can benefit from considering protein flexibility, binding site detection and molecular docking, are discussed. Basic classification metrics and statistical analysis techniques, which can facilitate performance analysis, are also reviewed. With hardware and software advances, molecular dynamics in combination with traditional structure-based prediction methods can potentially reduce the time and costs involved in the hit identification pipeline.

Computationally-guided optimization of a docking hit to yield catechol diethers as potent anti-HIV agents

A 5-μM docking hit has been optimized to an extraordinarily potent (55 pM) non-nucleoside inhibitor of HIV reverse transcriptase. Use of free energy perturbation (FEP) calculations to predict relative free energies of binding aided the optimizations by identifying optimal substitution patterns for phenyl rings and a linker. The most potent resultant catechol diethers feature terminal uracil and cyanovinylphenyl groups. A halogen bond with Pro95 likely contributes to the extreme potency of compound 42. In addition, several examples are provided illustrating failures of attempted grafting of a substructure from a very active compound onto a seemingly related scaffold to improve its activity.

Predictive power of molecular dynamics receptor structures in virtual screening

Molecular dynamics (MD) simulation is a well-established method for understanding protein dynamics. Conformations from unrestrained MD simulations have yet to be assessed for blind virtual screening (VS) by docking. This study presents a critical analysis of the predictive power of MD snapshots to this regard, evaluating two well-characterized systems of varying flexibility in ligand-bound and unbound configurations. Results from such VS predictions are discussed with respect to experimentally determined structures. In all cases, MD simulations provide snapshots that improve VS predictive power over known crystal structures, possibly due to sampling more relevant receptor conformations. Additionally, MD can move conformations previously not amenable to docking into the predictive range.

HIV-1 NNRTIs: structural diversity, pharmacophore similarity, and implications for drug design

Nonnucleoside reverse transcriptase inhibitors (NNRTIs) nowadays represent very potent and most promising anti-AIDS agents that specifically target the HIV-1 reverse transcriptase (RT). However, the effectiveness of NNRTI drugs can be hampered by rapid emergence of drug-resistant viruses and severe side effects upon long-term use. Therefore, there is an urgent need to develop novel, highly potent NNRTIs with broad spectrum antiviral activity and improved pharmacokinetic properties, and more efficient strategies that facilitate and shorten the drug discovery process would be extremely beneficial. Fortunately, the structural diversity of NNRTIs provided a wide space for novel lead discovery, and the pharmacophore similarity of NNRTIs gave valuable hints for lead discovery and optimization. More importantly, with the continued efforts in the development of computational tools and increased crystallographic information on RT/NNRTI complexes, structure-based approaches using a combination of traditional medicinal chemistry, structural biology, and computational chemistry are being used increasingly in the design of NNRTIs. First, this review covers two decades of research and development for various NNRTI families based on their chemical scaffolds, and then describes the structural similarity of NNRTIs. We have attempted to assemble a comprehensive overview of the general approaches in NNRTI lead discovery and optimization reported in the literature during the last decade. The successful applications of medicinal chemistry strategies, crystallography, and computational tools for designing novel NNRTIs are highlighted. Future directions for research are also outlined.

Mining protein dynamics from sets of crystal structures using "consensus structures"

In this work, we describe two novel approaches to utilize the dynamic structure information implicitly contained in large crystal structure data sets. The first approach visualizes both consistent as well as variable ligand-induced changes in ligand-bound compared with apo protein crystal structures. For this purpose, information was mined from B-factors and ligand-induced residue displacements in multiple crystal structures, minimizing experimental error and noise. With this approach, the mechanism of action of non-nucleoside reverse transcriptase inhibitors (NNRTIs) as an inseparable combination of distortion of protein dynamics and conformational changes of HIV-1 reverse transcriptase was corroborated (a combination of the previously proposed "molecular arthritis" and "distorted site" mechanisms). The second approach presented here uses "consensus structures" to map common binding features that are present in a set of structures of NNRTI-bound HIV-1 reverse transcriptase. Consensus structures are based on different levels of structural overlap of multiple crystal structures and are used to analyze protein-ligand interactions. The structures are shown to yield information about conserved hydrogen bonding interactions as well as binding-pocket flexibility, shape, and volume. From the consensus structures, a common wild type NNRTI binding pocket emerges. Furthermore, we were able to identify a conserved backbone hydrogen bond acceptor at P236 and a novel hydrophobic subpocket, which are not yet utilized by current drugs. Our methods introduced here reinterpret the atom information and make use of the data variability by using multiple structures, complementing classical 3D structural information of single structures.

E/Z Energetics for Molecular Modeling and Design

Thermochemical data have been obtained from G3B3 quantum mechanical calculations for 18 prototypical organic molecules, which exhibit E/Z conformational equilibria. The results are fundamentally important for molecular design including evaluation of structures from protein-ligand docking. For the 18 E/Z pairs, relative energies, enthalpies, free energies, and dipole moments are reported; the E - Z free-energy differences at 298 K range from +8.2 kcal/mol for 1,3-dimethyl carbamate to -6.4 kcal/mol for acetone oxime. A combination of steric and electronic effects can rationalize the variations. Free energies of hydration were also estimated using the GB/SA continuum solvent model. These results indicate that differential hydration is unlikely to qualitatively change the preferred direction of the E/Z equilibria, though further study with free-energy methods using explicit solvent is desirable.

Discovery of novel fibroblast growth factor receptor 1 kinase inhibitors by structure-based virtual screening

Fibroblast growth factors (FGFs) play important roles in embryonic development, angiogenesis, wound healing, and cell proliferation and differentiation. In search of inhibitors of FGFR1 kinase, 2.2 million compounds were docked into the ATP binding site of the protein. A co-crystal structure, which shows two alternative conformations for the nucleotide binding loop, is reported. Docking was performed on both conformations and, ultimately, 23 diverse compounds were purchased and assayed. Following hit validation, two compounds 10 and 16, a benzylidene derivative of pseudothiohydantoin and a thienopyrimidinone derivative, respectively, were discovered that inhibit FGFR1 kinase with IC(50) values of 23 and 50 microM. Initial optimization of 16 led to the more unsaturated 40, which has significantly enhanced potency, 1.9 microM. The core structures represent new structural motifs for FGFR1 kinase inhibitors. The study also illustrates complexities associated with the choice of protein structures for docking, possible use of multiple kinase structures to seek selectivity, and hit identification.