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

Covalent and noncovalent strategies for targeting Lys102 in HIV-1 reverse transcriptase

Reverse transcriptase (RT) is one of three key proteins responsible for the replication cycle of HIV-1 in the host. Several classes of inhibitors have been developed to target the enzyme, with non-nucleoside reverse transcriptase inhibitors forming first-line treatment. Previously, covalent RT inhibitors have been identified and found to bind irreversibly to commonly mutated residues such as Y181C. In this work we aim to circumvent the issue of NNRTI resistance through targeting K102, which has not yet been identified to confer drug resistance. As reported here, 34 compounds were synthesized and characterized biochemically and structurally with wild-type (WT) HIV-1 RT. Two of these inhibitors demonstrate covalent inhibition as evidenced by protein crystallography, enzyme kinetics, mass spectrometry, and antiviral potency in HIV-1 infected human T-cell assays.

Exploring novel HIV-1 reverse transcriptase inhibitors with drug-resistant mutants: A double mutant surprise

HIV-1 reverse transcriptase (RT) remains a key target for HIV drug development. As successful management of the disease requires lifelong treatment, the emergence of resistance mutations is inevitable, making development of new RT inhibitors, which remain effective against resistant variants crucial. To this end, previous computationally guided drug design efforts have resulted in catechol diether compounds, which inhibit wildtype RT with picomolar affinities and appear to be promising preclinical candidates. To confirm that these compounds remain potent against Y181C, a widespread mutation conferring resistance to first generation inhibitors, they were screened against the HIV-1 N119 clinical isolate, reported as a Y181C single mutant. In comparison to a molecular clone with the same mutation, N119 appears less susceptible to inhibition by our preclinical candidate compounds. A more detailed sequencing effort determined that N119 was misidentified and carries V106A in combination with Y181C. While both indolizine and naphthalene substituted catechol diethers are potent against the classical Y181C single mutant, the addition of V106A confers more resistance against the indolizine derivatives than the naphthalene derivatives. Crystal structures presented in this study highlight key features of the naphthyl group, which allow these compounds to remain potent in the double mutant, including stronger interactions with F227 and less reliance on V106 for stabilization of the ethoxy-uracil ring, which makes critical hydrogen bonds with other residues in the binding pocket.

The maximal and current accuracy of rigorous protein-ligand binding free energy calculations

Computational techniques can speed up the identification of hits and accelerate the development of candidate molecules for drug discovery. Among techniques for predicting relative binding affinities, the most consistently accurate is free energy perturbation (FEP), a class of rigorous physics-based methods. However, uncertainty remains about how accurate FEP is and can ever be. Here, we present what we believe to be the largest publicly available dataset of proteins and congeneric series of small molecules, and assess the accuracy of the leading FEP workflow. To ascertain the limit of achievable accuracy, we also survey the reproducibility of experimental relative affinity measurements. We find a wide variability in experimental accuracy and a correspondence between binding and functional assays. When careful preparation of protein and ligand structures is undertaken, FEP can achieve accuracy comparable to experimental reproducibility. Throughout, we highlight reliable protocols that can help maximize the accuracy of FEP in prospective studies.

In Vitro and In Silico Antiviral Activity of Di-Halogenated Compounds Derived from L-Tyrosine against Human Immunodeficiency Virus 1 (HIV-1)

HIV-1 infection is considered one of the major public health problems worldwide. Due to the limited access to antiretroviral therapy, the associated side effects, and the resistance that the virus can generate, it has become necessary to continue the development of new antiviral agents. The study aimed to identify potential antiviral agents for HIV-1 by evaluating the in vitro and in silico activity of 16 synthetic di-halogenated compounds derived from L-Tyrosine. The compounds were tested for cytotoxicity, which was determined using MTT, and a combined antiviral screening strategy (pre- and post-infection treatment) was performed against R5 and X4 strains of HIV-1. The most promising compounds were evaluated against a pseudotyped virus (HIV-GFP-VSV-G), and the effectiveness of these compounds was measured through GFP flow cytometry. Also, the antiviral effect of these compounds was evaluated in PBMCs using flow cytometry and ELISA for p24. The TODB-2M, TODC-2M, TODC-3M, and YDC-3M compounds showed low toxicity and significant inhibitory activity against HIV-1. In silico docking and molecular dynamics assays suggest that the compounds' antiviral activity may be due to interaction with reverse transcriptase, viral protease, or envelope gp120.

Strategies in the Design and Development of Non-Nucleoside Reverse Transcriptase Inhibitors (NNRTIs)

AIDS (acquired immunodeficiency syndrome) is a potentially life-threatening infectious disease caused by human immunodeficiency virus (HIV). To date, thousands of people have lost their lives annually due to HIV infection, and it continues to be a big public health issue globally. Since the discovery of the first drug, Zidovudine (AZT), a nucleoside reverse transcriptase inhibitor (NRTI), to date, 30 drugs have been approved by the FDA, primarily targeting reverse transcriptase, integrase, and/or protease enzymes. The majority of these drugs target the catalytic and allosteric sites of the HIV enzyme reverse transcriptase. Compared to the NRTI family of drugs, the diverse chemical class of non-nucleoside reverse transcriptase inhibitors (NNRTIs) has special anti-HIV activity with high specificity and low toxicity. However, current clinical usage of NRTI and NNRTI drugs has limited therapeutic value due to their adverse drug reactions and the emergence of multidrug-resistant (MDR) strains. To overcome drug resistance and efficacy issues, combination therapy is widely prescribed for HIV patients. Combination antiretroviral therapy (cART) includes more than one antiretroviral agent targeting two or more enzymes in the life cycle of the virus. Medicinal chemistry researchers apply different optimization strategies including structure- and fragment-based drug design, prodrug approach, scaffold hopping, molecular/fragment hybridization, bioisosterism, high-throughput screening, covalent-binding, targeting highly hydrophobic channel, targeting dual site, and multi-target-directed ligand to identify and develop novel NNRTIs with high antiviral activity against wild-type (WT) and mutant strains. The formulation experts design various delivery systems with single or combination therapies and long-acting regimens of NNRTIs to improve pharmacokinetic profiles and provide sustained therapeutic effects.

Advanced virtual screening enables the discovery of a host-targeting and broad-spectrum antiviral agent

We employed an advanced virtual screening (AVS) approach to identify potential inhibitors of human dihydroorotate dehydrogenase (DHODH), a validated target for development of broad-spectrum antivirals. We screened a library of 495118 compounds and identified 495 compounds that exhibited better binding scores than the reference ligands involved in the screening. From the top 100 compounds, we selected 28 based on their consensus docking scores and structural novelty. Then, we conducted in vitro experiments to investigate the antiviral activity of selected compounds on HSV-1 infection, which is susceptible to DHODH inhibitors. Among the tested compounds, seven displayed statistically significant antiviral effects, with Comp 19 being the most potent inhibitor. We found that Comp 19 exerted its antiviral effect in a dose-dependent manner (IC50 = 1.1 μM) and exhibited the most significant antiviral effect when added before viral infection. In the biochemical assay, Comp 19 inhibited human DHODH in a dose-dependent manner with the IC50 value of 7.3 μM. Long-timescale molecular dynamics simulations (1000 ns) revealed that Comp 19 formed a very stable complex with human DHODH. Comp 19 also displayed broad-spectrum antiviral activity and suppressed cytokine production in THP-1 cells. Overall, our study provides evidence that AVS could be successfully implemented to discover novel DHODH inhibitors with broad-spectrum antiviral activity.

Recent Advances in the Synthesis and Applications of m-Aryloxy Phenols

Since phenol derivatives have high potential as building blocks for the synthesis of bioactive natural products and conducting polymers, many synthesis methods have been invented. In recent years, innovative synthetic methods have been developed for the preparation of m-aryloxy phenols, which has allowed for the preparation of complex m-aryloxy phenols with functional groups, such as esters, nitriles, and halogens, that impart specific properties of these compounds. This review provides an overview of recent advances in synthetic strategies for m-aryloxy phenols and their potential biological activities. This paper highlights the importance of m-aryloxy phenols in various industries, including plastics, adhesives, and coatings, and it discusses their applications as antioxidants, ultraviolet absorbers, and flame retardants.

Design, synthesis, and biological testing of biphenylmethyloxazole inhibitors targeting HIV-1 reverse transcriptase

We report non-nucleoside inhibitors of HIV-1 reverse transcriptase (NNRTIs) using a biphenylmethyloxazole pharmacophore. A crystal structure of benzyloxazole 1 was obtained and suggested the potential viability of biphenyl analogues. In particular, 6a, 6b, and 7 turned out to be potent NNRTIs with low-nanomolar activity in enzyme inhibition and infected T-cell assays, and with low cytotoxicity. Though modeling further suggested that analogues with fluorosulfate and epoxide warheads might provide covalent modification of Tyr188, synthesis and testing did not find evidence for this outcome.

The slow but steady rise of binding free energy calculations in drug discovery

Binding free energy calculations are increasingly used in drug discovery research to predict protein-ligand binding affinities and to prioritize candidate drug molecules accordingly. It has taken decades of collective effort to transform this academic concept into a technology adopted by the pharmaceutical and biotech industry. Having personally witnessed and taken part in this transformation, here I recount the (incomplete) list of problems that had to be solved to make this computational tool practical and suggest areas of future development.

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.

Structural Studies and Structure Activity Relationships for Novel Computationally Designed Non-nucleoside Inhibitors and Their Interactions With HIV-1 Reverse Transcriptase

Reverse transcriptase (RT) from the human immunodeficiency virus continues to be an attractive drug target for antiretroviral therapy. June 2022 will commemorate the 30th anniversary of the first Human Immunodeficiency Virus (HIV) RT crystal structure complex that was solved with non-nucleoside reverse transcriptase inhibitor nevirapine. The release of this structure opened opportunities for designing many families of non-nucleoside reverse transcriptase inhibitors (NNRTIs). In paying tribute to the first RT-nevirapine structure, we have developed several compound classes targeting the non-nucleoside inhibitor binding pocket of HIV RT. Extensive analysis of crystal structures of RT in complex with the compounds informed iterations of structure-based drug design. Structures of seven additional complexes were determined and analyzed to summarize key interactions with residues in the non-nucleoside inhibitor binding pocket (NNIBP) of RT. Additional insights comparing structures with antiviral data and results from molecular dynamics simulations elucidate key interactions and dynamics between the nucleotide and non-nucleoside binding sites.

The Fellowship of Privileged Scaffolds-One Structure to Inhibit Them All

Over the past few years, the application of privileged structure has emerged as a powerful approach to the discovery of new biologically active molecules. Privileged structures are molecular scaffolds with binding properties to the range of different biological targets. Moreover, privileged structures typically exhibit good drug-like properties, thus assuring more drug-like properties of modified compound. Our main objective is to discuss the privileged structures used for the development of antiviral agents.

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.

Covalent Inhibition of Wild-Type HIV-1 Reverse Transcriptase Using a Fluorosulfate Warhead

Covalent inhibitors of wild-type HIV-1 reverse transcriptase (CRTIs) are reported. Three compounds derived from catechol diether non-nucleoside inhibitors (NNRTIs) with addition of a fluorosulfate warhead are demonstrated to covalently modify Tyr181 of HIV-RT. X-ray crystal structures for complexes of the CRTIs with the enzyme are provided, which fully demonstrate the covalent attachment, and confirmation is provided by appropriate mass shifts in ESI-TOF mass spectra. The three CRTIs and six noncovalent analogues are found to be potent inhibitors with both IC₅₀ values for in vitro inhibition of WT RT and EC₅₀ values for cytopathic protection of HIV-1-infected human T-cells in the 5-320 nM range.

Thermodynamics and Kinetics of Drug-Target Binding by Molecular Simulation

Computational studies play an increasingly important role in chemistry and biophysics, mainly thanks to improvements in hardware and algorithms. In drug discovery and development, computational studies can reduce the costs and risks of bringing a new medicine to market. Computational simulations are mainly used to optimize promising new compounds by estimating their binding affinity to proteins. This is challenging due to the complexity of the simulated system. To assess the present and future value of simulation for drug discovery, we review key applications of advanced methods for sampling complex free-energy landscapes at near nonergodicity conditions and for estimating the rate coefficients of very slow processes of pharmacological interest. We outline the statistical mechanics and computational background behind this research, including methods such as steered molecular dynamics and metadynamics. We review recent applications to pharmacology and drug discovery and discuss possible guidelines for the practitioner. Recent trends in machine learning are also briefly discussed. Thanks to the rapid development of methods for characterizing and quantifying rare events, simulation's role in drug discovery is likely to expand, making it a valuable complement to experimental and clinical approaches.

A machine learning based intramolecular potential for a flexible organic molecule

Here, we employ the kernel regression machine learning technique to construct an analytical potential that reproduces the quantum mechanical potential energy surface of a small, flexible, drug-like molecule, 3-(benzyloxy)pyridin-2-amine.

Structure activity relationship towards design of cryptosporidium specific thymidylate synthase inhibitors

Cryptosporidiosis is a human gastrointestinal disease caused by protozoans of the genus Cryptosporidium, which can be fatal in immunocompromised individuals. The essential enzyme, thymidylate synthase (TS), is responsible for de novo synthesis of deoxythymidine monophosphate. The TS active site is relatively conserved between Cryptosporidium and human enzymes. In previous work, we identified compound 1, (2-amino-4-oxo-4,7-dihydro-pyrrolo[2,3-d]pyrimidin-methyl-phenyl-l-glutamic acid), as a promising selective Cryptosporidium hominis TS (ChTS) inhibitor. In the present study, we explore the structure-activity relationship around 1 glutamate moiety by synthesizing and biochemically evaluating the inhibitory activity of analogues against ChTS and human TS (hTS). X-Ray crystal structures were obtained for compounds bound to both ChTS and hTS. We establish the importance of the 2-phenylacetic acid moiety methylene linker in optimally positioning compounds 23, 24, and 25 within the active site. Moreover, through the comparison of structural data for 5, 14, 15, and 23 bound in both ChTS and hTS identified that active site rigidity is a driving force in determining inhibitor selectivity.

Molecular and cellular studies evaluating a potent 2-cyanoindolizine catechol diether NNRTI targeting wildtype and Y181C mutant HIV-1 reverse transcriptase

The development of efficacious NNRTIs for HIV/AIDS therapy is commonly met with the emergence of drug resistant strains, including the Y181C variant. Using a computationally-guided approach, we synthesized the catechol diether series of NNRTIs, which display sub-nanomolar potency in cellular assays. Among the most potent were a series of 2-cyanoindolizine substituted catechol diethers, including Compound 1. We present here a thorough evaluation of this compound, including biochemical, cellular, and structural studies. The compound demonstrates low nanomolar potency against both WT and Y181C HIV-1 RT in in vitro and cellular assays. Our crystal structures of both the wildtype and mutant forms of RT in complex with Compound 1 allow the interrogation of this compound's features that allow it to maintain strong efficacy against the drug resistant mutant. Among these are compensatory shifts in the NNRTI binding pocket, persistence of multiple hydrogen bonds, and van der Waals contacts throughout the binding site. Further, the fluorine at the C6 position of the indolizine moiety makes multiple favorable interactions with both RT forms. The present study highlights the indolizine-substituted catechol diether class of NNRTIs as promising therapeutic candidates possessing optimal pharmacological properties and significant potency against multiple RT variants.

Current structure-based methods for designing non-nucleoside reverse transcriptase inhibitors

In 2019, structure-based methods continue to guide the design of novel antiretroviral therapies targeting HIV reverse transcriptase. This Review summarizes key findings from reverse transcriptase–non-nucleoside reverse transcriptase inhibitor analog crystal structure complexes reported from 2015 to 2019. Results from the literature and structure analysis have informed new ideas for structure-guided non-nucleoside reverse transcriptase inhibitor drug design.

An Overview of Molecular Modeling for Drug Discovery with Specific Illustrative Examples of Applications

In this paper we review the current status of high-performance computing applications in the general area of drug discovery. We provide an introduction to the methodologies applied at atomic and molecular scales, followed by three specific examples of implementation of these tools. The first example describes in silico modeling of the adsorption of small molecules to organic and inorganic surfaces, which may be applied to drug delivery issues. The second example involves DNA translocation through nanopores with major significance to DNA sequencing efforts. The final example offers an overview of computer-aided drug design, with some illustrative examples of its usefulness.

Aryl Substituted Benzimidazolones as Potent HIV-1 Non-Nucleoside Reverse Transcriptase Inhibitors

Since the discovery of HIV as the etiological agent of AIDS, the virus has infected millions of people each year. Fortunately, with the use of HAART, viremia can be suppressed to below detectable levels in the infected individuals, which significantly improves their quality of life and prevents the onset of AIDS. However, HAART is not curative and issues relating to adherence and drug resistance may lead to the re-emergence of viremia, the development of AIDS, and ultimately death. To address a pressing need for the development of new and efficacious antiretroviral agents with activity against viruses bearing prevalent resistant mutations, we have designed two generations of benzimidazolone derivatives as HIV non-nucleoside reverse transcriptase inhibitors. The first generation benzimidazolone inhibitors were found to be potent inhibitors of wild-type HIV reverse transcriptase but were ineffective in the presence of common resistance mutations such as K103N and Y181C. A second generation benzimidazolone inhibitor (compound 42) not only showed inhibitory activity against wild-type HIV but also remained active against HIV containing the K103N, Y181C, and K103N/Y181C drug resistance mutations.

Torsional flexibility of undecorated catechol diether compound as potent NNRTI targeting HIV-1 reverse transcriptase

Conformational adaptation of non-nucleoside reverse transcriptase inhibitor (NNRTI) via torsional flexibility is found to be very significant for targeting human immunodeficiency virus type 1 reverse transcriptase (HIV-1 RT) mutants. Catechol diether derivative including flexible torsions is new potent NNRTI with picomolar activity. Moreover, this derivative also reveals the good solubility, low toxicity and potent inhibition for HIV-1 mutants. In this study, torsional flexibility of an undecorated catechol diether compound in the binding pocket of wild type and mutants (Y181C and K103N/Y181C) HIV-1 RT is investigated by using QM/MM calculations. From the results, the uracil ring is found to exhibit more flexibility in the NNIBP. On the contrary, potential energy surfaces show that high energy is encountered by changing of the corresponding torsion of the cyanovinyl aryl ring indicating the limitation for torsional flexibility. For pointing out the key interaction for the binding, the residual interaction energies are performed by means of QM calculations. Important attractive interactions through hydrogen bonds between the inhibitor and K102, K/N103, V106, and Y188 are observed. The catechol ring is proposed to be modified in order to strengthen interactions with surrounding amino acids. The results may help for the designing of new potent NNRTIs.

Predicting Binding Free Energies in a Large Combinatorial Chemical Space Using Multisite λ Dynamics

In this study, we demonstrate the extensive scalability of the biasing potential replica exchange multisite λ dynamics (BP-REX MSλD) free energy method by calculating binding affinities for 512 inhibitors to HIV Reverse Transcriptase (HIV-RT). This is the largest exploration of chemical space using free energy methods known to date, requires only a few simulations, and identifies 55 new inhibitor designs against HIV-RT predicted to be at least as potent as a tight binding reference compound (i.e., as potent as 56 nM). We highlight that BP-REX MSλD requires an order of magnitude less computational resources than conventional free energy methods while maintaining a similar level of precision, overcomes the inherent poor scalability of conventional free energy methods, and enables the exploration of combinatorially large chemical spaces in the context of in silico drug discovery.

The BioFragment Database (BFDb): An open-data platform for computational chemistry analysis of noncovalent interactions

Accurate potential energy models are necessary for reliable atomistic simulations of chemical phenomena. In the realm of biomolecular modeling, large systems like proteins comprise very many noncovalent interactions (NCIs) that can contribute to the protein's stability and structure. This work presents two high-quality chemical databases of common fragment interactions in biomolecular systems as extracted from high-resolution Protein DataBank crystal structures: 3380 sidechain-sidechain interactions and 100 backbone-backbone interactions that inaugurate the BioFragment Database (BFDb). Absolute interaction energies are generated with a computationally tractable explicitly correlated coupled cluster with perturbative triples [CCSD(T)-F12] "silver standard" (0.05 kcal/mol average error) for NCI that demands only a fraction of the cost of the conventional "gold standard," CCSD(T) at the complete basis set limit. By sampling extensively from biological environments, BFDb spans the natural diversity of protein NCI motifs and orientations. In addition to supplying a thorough assessment for lower scaling force-field (2), semi-empirical (3), density functional (244), and wavefunction (45) methods (comprising >1M interaction energies), BFDb provides interactive tools for running and manipulating the resulting large datasets and offers a valuable resource for potential energy model development and validation.

Phenotype-Based High-Content Screening Using Fluorescent Chemical Bioprobes: Lipid Droplets and Glucose Uptake Quantification in Live Cells

Phenotypic screening in live cells has emerged as a promising strategy for drug discovery in pharmaceutical communities. For relevant phenotype-based screening setups, it is critical to develop adequate reporters in order to selectively visualize subcellular compartments or phenotypic changes that represent disease-related characteristics during compound screening. In this chapter, we introduce two phenotype-based high-content/high-throughput assays using fluorescent bioprobes that have been designed and refined to selectively stain cellular lipid droplets (LDs) and to show cellular glucose uptake. In conjunction with target identification process for the hit compounds from phenotypic screening, these fluorescent chemical probe-based screening techniques are expected to drive a great advancement for the discovery of novel first-in-class therapeutics.

Predicting Binding Free Energies of PDE2 Inhibitors. The Difficulties of Protein Conformation

A congeneric series of 21 phosphodiesterase 2 (PDE2) inhibitors are reported. Crystal structures show how the molecules can occupy a 'top-pocket' of the active site. Molecules with small substituents do not enter the pocket, a critical leucine (Leu770) is closed and water molecules are present. Large substituents enter the pocket, opening the Leu770 conformation and displacing the waters. We also report an X-ray structure revealing a new conformation of the PDE2 active site domain. The relative binding affinities of these compounds were studied with free energy perturbation (FEP) methods and it represents an attractive real-world test case. In general, the calculations could predict the energy of small-to-small, or large-to-large molecule perturbations. However, accurately capturing the transition from small-to-large proved challenging. Only when using alternative protein conformations did results improve. The new X-ray structure, along with a modelled dimer, conferred stability to the catalytic domain during the FEP molecular dynamics (MD) simulations, increasing the convergence and thereby improving the prediction of ΔΔG of binding for some small-to-large transitions. In summary, we found the most significant improvement in results when using different protein structures, and this data set is useful for future free energy validation studies.

Relative Binding Free Energy Calculations in Drug Discovery: Recent Advances and Practical Considerations

Accurate in silico prediction of protein-ligand binding affinities has been a primary objective of structure-based drug design for decades due to the putative value it would bring to the drug discovery process. However, computational methods have historically failed to deliver value in real-world drug discovery applications due to a variety of scientific, technical, and practical challenges. Recently, a family of approaches commonly referred to as relative binding free energy (RBFE) calculations, which rely on physics-based molecular simulations and statistical mechanics, have shown promise in reliably generating accurate predictions in the context of drug discovery projects. This advance arises from accumulating developments in the underlying scientific methods (decades of research on force fields and sampling algorithms) coupled with vast increases in computational resources (graphics processing units and cloud infrastructures). Mounting evidence from retrospective validation studies, blind challenge predictions, and prospective applications suggests that RBFE simulations can now predict the affinity differences for congeneric ligands with sufficient accuracy and throughput to deliver considerable value in hit-to-lead and lead optimization efforts. Here, we present an overview of current RBFE implementations, highlighting recent advances and remaining challenges, along with examples that emphasize practical considerations for obtaining reliable RBFE results. We focus specifically on relative binding free energies because the calculations are less computationally intensive than absolute binding free energy (ABFE) calculations and map directly onto the hit-to-lead and lead optimization processes, where the prediction of relative binding energies between a reference molecule and new ideas (virtual molecules) can be used to prioritize molecules for synthesis. We describe the critical aspects of running RBFE calculations, from both theoretical and applied perspectives, using a combination of retrospective literature examples and prospective studies from drug discovery projects. This work is intended to provide a contemporary overview of the scientific, technical, and practical issues associated with running relative binding free energy simulations, with a focus on real-world drug discovery applications. We offer guidelines for improving the accuracy of RBFE simulations, especially for challenging cases, and emphasize unresolved issues that could be improved by further research in the field.

Enzymatic Synthesis of a Novel Neuroprotective Hydroxytyrosyl Glycoside

The eco-friendly synthesis of non-natural glycosides from different phenolic antioxidants was carried out using a fungal β-xylosidase to evaluate changes in their bioactivities. Xylosides from hydroquinone and catechol were successfully formed, although the best results were obtained for hydroxytyrosol, the main antioxidant from olive oil. The formation of the new products was followed by thin-layer chromatography, liquid chromatography, and mass spectrometry. The hydroxytyrosyl xyloside was analyzed in more detail, to maximize its production and evaluate the effect of glycosylation on some hydroxytyrosol properties. The synthesis was optimized up to the highest production reported for a hydroxytyrosyl glycoside. The structure of this compound was solved by two-dimensional nuclear magnetic resonance and identified as 3,4-dihydroxyphenyl-ethyl-O-β-d-xylopyranoside. Evaluation of its biological effect showed an enhancement of both its neuroprotective capacity and its ability to ameliorate intracellular levels of reactive oxygen species.

Diaryl ethers with carboxymethoxyphenacyl motif as potent HIV-1 reverse transcriptase inhibitors with improved solubility

In search of new non-nucleoside reverse transcriptase inhibitors (NNRTIs) with improved solubility, two series of novel diaryl ethers with phenacyl moiety were designed and evaluated for their HIV-1 reverse transcriptase inhibition potentials. All compounds exhibited good to excellent results with IC₅₀ at low micromolar to submicromolar concentrations. Two most active compounds (7e and 7 g) exhibit inhibitory potency comparable or even better than that of nevirapine and rilpivirine. Furthermore, SupT1 and CD4⁺ cell infectivity assays for the most promising (7e) have confirmed its strong antiviral potential while docking studies indicate a novel binding interactions responsible for high activity.

A systematic analysis of atomic protein-ligand interactions in the PDB

As the protein databank (PDB) recently passed the cap of 123 456 structures, it stands more than ever as an important resource not only to analyze structural features of specific biological systems, but also to study the prevalence of structural patterns observed in a large body of unrelated structures, that may reflect rules governing protein folding or molecular recognition. Here, we compiled a list of 11 016 unique structures of small-molecule ligands bound to proteins - 6444 of which have experimental binding affinity - representing 750 873 protein-ligand atomic interactions, and analyzed the frequency, geometry and impact of each interaction type. We find that hydrophobic interactions are generally enriched in high-efficiency ligands, but polar interactions are over-represented in fragment inhibitors. While most observations extracted from the PDB will be familiar to seasoned medicinal chemists, less expected findings, such as the high number of C-H···O hydrogen bonds or the relatively frequent amide-π stacking between the backbone amide of proteins and aromatic rings of ligands, uncover underused ligand design strategies.

Computationally-guided optimization of small-molecule inhibitors of the Aurora A kinase-TPX2 protein-protein interaction

Free energy perturbation theory, in combination with enhanced sampling of protein-ligand binding modes, is evaluated in the context of fragment-based drug design, and used to design two new small-molecule inhibitors of the Aurora A kinase-TPX2 protein-protein interaction.

Novel fused pyrimidine and isoquinoline derivatives as potent HIV-1 NNRTIs: a patent evaluation of WO2016105532A1, WO2016105534A1 and WO2016105564A1

INTRODUCTION

In the three patent applications, the impact of changing the pyrimidine core of the rilpivirine (RPV) to a variety of alternative fused cores was explored, culminating in the identification of a series of conformationally restricted compounds with comparable potencies against WT and mutant HIV-1 strains with those of efavirenz (EFV) and RPV, and higher security in the Human Ether-a-go-go-Related Gene (hERG) assay. Areas covered: The present review provides a fused pyrimidine and isoquinoline derivatives as potent HIV-1 NNRTIs, and highlights the conformational restriction strategies in the development of NNRTIs. Expert opinion: The molecular docking analysis of the newly synthesized compounds maintain the classical horseshoe conformation and shares similar binding mode with RPV. The conformational restriction strategies have greatly accelerated the optimization of the DAPY NNRTIs and contribute to finding new chemical entities (NCEs) with favorable druggability.

Metal Ion Modeling Using Classical Mechanics

Metal ions play significant roles in numerous fields including chemistry, geochemistry, biochemistry, and materials science. With computational tools increasingly becoming important in chemical research, methods have emerged to effectively face the challenge of modeling metal ions in the gas, aqueous, and solid phases. Herein, we review both quantum and classical modeling strategies for metal ion-containing systems that have been developed over the past few decades. This Review focuses on classical metal ion modeling based on unpolarized models (including the nonbonded, bonded, cationic dummy atom, and combined models), polarizable models (e.g., the fluctuating charge, Drude oscillator, and the induced dipole models), the angular overlap model, and valence bond-based models. Quantum mechanical studies of metal ion-containing systems at the semiempirical, ab initio, and density functional levels of theory are reviewed as well with a particular focus on how these methods inform classical modeling efforts. Finally, conclusions and future prospects and directions are offered that will further enhance the classical modeling of metal ion-containing systems.

Structural and Preclinical Studies of Computationally Designed Non-Nucleoside Reverse Transcriptase Inhibitors for Treating HIV infection

The clinical benefits of HIV-1 non-nucleoside reverse transcriptase (RT) inhibitors (NNRTIs) are hindered by their unsatisfactory pharmacokinetic (PK) properties along with the rapid development of drug-resistant variants. However, the clinical efficacy of these inhibitors can be improved by developing compounds with enhanced pharmacological profiles and heightened antiviral activity. We used computational and structure-guided design to develop two next-generation NNRTI drug candidates, compounds I and II, which are members of a class of catechol diethers. We evaluated the preclinical potential of these compounds in BALB/c mice because of their high solubility (510 µg/ml for compound I and 82.9 µg/ml for compound II), low cytotoxicity, and enhanced antiviral activity against wild-type (WT) HIV-1 RT and resistant variants. Additionally, crystal structures of compounds I and II with WT RT suggested an optimal binding to the NNRTI binding pocket favoring the high anti-viral potency. A single intraperitoneal dose of compounds I and II exhibited a prolonged serum residence time of 48 hours and concentration maximum (C_max) of 4000- to 15,000-fold higher than their therapeutic/effective concentrations. These C_max values were 4- to 15-fold lower than their cytotoxic concentrations observed in MT-2 cells. Compound II showed an enhanced area under the curve (0-last) and decreased plasma clearance over compound I and efavirenz, the standard of care NNRTI. Hence, the overall (PK) profile of compound II was excellent compared with that of compound I and efavirenz. Furthermore, both compounds were very well tolerated in BALB/c mice without any detectable acute toxicity. Taken together, these data suggest that compounds I and II possess improved anti-HIV-1 potency, remarkable in vivo safety, and prolonged in vivo circulation time, suggesting strong potential for further development as new NNRTIs for the potential treatment of HIV infection.

Acylguanidine Beta Secretase 1 Inhibitors: A Combined Experimental and Free Energy Perturbation Study

A series of acylguanidine beta secretase 1 (BACE1) inhibitors with modified scaffold and P3 pocket substituent was synthesized and studied with free energy perturbation (FEP) calculations. The resulting molecules showed potencies in enzymatic BACE1 inhibition assays up to 1 nM. The correlation between the predicted activity from the FEP calculations and the experimental activity was good for the P3 pocket substituents. The average mean unsigned error (MUE) between prediction and experiment was 0.68 ± 0.17 kcal/mol for the default 5 ns lambda window simulation time improving to 0.35 ± 0.13 kcal/mol for 40 ns. FEP calculations for the P2' pocket substituents on the same acylguanidine scaffold also showed good agreement with experiment and the results remained stable with repeated simulations and increased simulation time. It proved more difficult to use FEP calculations to study the scaffold modification from increasing 5 to 6 and 7 membered-rings. Although prediction and experiment were in agreement for short 2 ns simulations, as the simulation time increased the results diverged. This was improved by the use of a newly developed "Core Hopping FEP+" approach, which also showed improved stability in repeat calculations. The origins of these differences along with the value of repeat and longer simulation times are discussed. This work provides a further example of the use of FEP as a computational tool for molecular design.

Design, Conformation, and Crystallography of 2-Naphthyl Phenyl Ethers as Potent Anti-HIV Agents

Catechol diethers that incorporate a 7-cyano-2-naphthyl substituent are reported as non-nucleoside inhibitors of HIV-1 reverse transcriptase (NNRTIs). Many of the compounds have 1-10 nM potencies toward wild-type HIV-1. An interesting conformational effect allows two unique conformers for the naphthyl group in complexes with HIV-RT. X-ray crystal structures for 4a and 4f illustrate the alternatives.

Structural biology in antiviral drug discovery

Structural biology has emerged during the last thirty years as a powerful tool for rational drug discovery. Crystal structures of biological targets alone and in complex with ligands and inhibitors provide essential insights into the mechanisms of actions of enzymes, their conformational changes upon ligand binding, the architectures and interactions of binding pockets. Structure-based methods such as crystallographic fragment screening represent nowadays invaluable instruments for the identification of new biologically active compounds. In this context, three-dimensional protein structures have played essential roles for the understanding of the activity and for the design of novel antiviral agents against several different viruses. In this review, the evolution in the resolution of viral structures is analysed, along with the role of crystal structures in the discovery and optimisation of new antivirals.

Predicting Binding Affinities for GPCR Ligands Using Free-Energy Perturbation

The rapid growth of structural information for G-protein-coupled receptors (GPCRs) has led to a greater understanding of their structure, function, selectivity, and ligand binding. Although novel ligands have been identified using methods such as virtual screening, computationally driven lead optimization has been possible only in isolated cases because of challenges associated with predicting binding free energies for related compounds. Here, we provide a systematic characterization of the performance of free-energy perturbation (FEP) calculations to predict relative binding free energies of congeneric ligands binding to GPCR targets using a consistent protocol and no adjustable parameters. Using the FEP+ package, first we validated the protocol, which includes a full lipid bilayer and explicit solvent, by predicting the binding affinity for a total of 45 different ligands across four different GPCRs (adenosine A_2AAR, β₁ adrenergic, CXCR4 chemokine, and δ opioid receptors). Comparison with experimental binding affinity measurements revealed a highly predictive ranking correlation (average spearman ρ = 0.55) and low root-mean-square error (0.80 kcal/mol). Next, we applied FEP+ in a prospective project, where we predicted the affinity of novel, potent adenosine A_2A receptor (A_2AR) antagonists. Four novel compounds were synthesized and tested in a radioligand displacement assay, yielding affinity values in the nanomolar range. The affinity of two out of the four novel ligands (plus three previously reported compounds) was correctly predicted (within 1 kcal/mol), including one compound with approximately a tenfold increase in affinity compared to the starting compound. Detailed analyses of the simulations underlying the predictions provided insights into the structural basis for the two cases where the affinity was overpredicted. Taken together, these results establish a protocol for systematically applying FEP+ to GPCRs and provide guidelines for identifying potent molecules in drug discovery lead optimization projects.

Application of Free Energy Perturbation for the Design of BACE1 Inhibitors

Novel spiroaminodihydropyrroles probing for optimized interactions at the P3 pocket of β-secretase 1 (BACE1) were designed with the use of free energy perturbation (FEP) calculations. The resulting molecules showed pIC50 potencies in enzymatic BACE1 inhibition assays ranging from approximately 5 to 7. Good correlation was observed between the predicted activity from the FEP calculations and experimental activity. Simulations run with a default 5 ns approach delivered a mean unsigned error (MUE) between prediction and experiment of 0.58 and 0.91 kcal/mol for retrospective and prospective applications, respectively. With longer simulations of 10 and 20 ns, the MUE was in both cases 0.57 kcal/mol for the retrospective application, and 0.69 and 0.59 kcal/mol for the prospective application. Other considerations that impact the quality of the calculations are discussed. This work provides an example of the value of FEP as a computational tool for drug discovery.