Antiviral drug design: computational analyses of the effects of the L100I mutation for HIV-RT on the binding of NNRTIs

Non-active site mutants of HIV-1 protease influence resistance and sensitisation towards protease inhibitors

Background

HIV-1 can develop resistance to antiretroviral drugs, mainly through mutations within the target regions of the drugs. In HIV-1 protease, a majority of resistance-associated mutations that develop in response to therapy with protease inhibitors are found in the protease’s active site that serves also as a binding pocket for the protease inhibitors, thus directly impacting the protease-inhibitor interactions. Some resistance-associated mutations, however, are found in more distant regions, and the exact mechanisms how these mutations affect protease-inhibitor interactions are unclear. Furthermore, some of these mutations, e.g. N88S and L76V, do not only induce resistance to the currently administered drugs, but contrarily induce sensitivity towards other drugs. In this study, mutations N88S and L76V, along with three other resistance-associated mutations, M46I, I50L, and I84V, are analysed by means of molecular dynamics simulations to investigate their role in complexes of the protease with different inhibitors and in different background sequence contexts.

Results

Using these simulations for alchemical calculations to estimate the effects of mutations M46I, I50L, I84V, N88S, and L76V on binding free energies shows they are in general in line with the mutations’ effect on \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$IC_{50}$$\end{document}IC50 values. For the primary mutation L76V, however, the presence of a background mutation M46I in our analysis influences whether the unfavourable effect of L76V on inhibitor binding is sufficient to outweigh the accompanying reduction in catalytic activity of the protease. Finally, we show that L76V and N88S changes the hydrogen bond stability of these residues with residues D30/K45 and D30/T31/T74, respectively.

Conclusions

We demonstrate that estimating the effect of both binding pocket and distant mutations on inhibitor binding free energy using alchemical calculations can reproduce their effect on the experimentally measured \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$IC_{50}$$\end{document}IC50 values. We show that distant site mutations L76V and N88S affect the hydrogen bond network in the protease’s active site, which offers an explanation for the indirect effect of these mutations on inhibitor binding. This work thus provides valuable insights on interplay between primary and background mutations and mechanisms how they affect inhibitor binding.

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.

Adaptive Landscape Flattening Accelerates Sampling of Alchemical Space in Multisite λ Dynamics

Multisite λ dynamics (MSλD) is a powerful emerging method in free energy calculation that allows prediction of relative free energies for a large set of compounds from very few simulations. Calculating free energy differences between substituents that constitute large volume or flexibility jumps in chemical space is difficult for free energy methods in general, and for MSλD in particular, due to large free energy barriers in alchemical space. This study demonstrates that a simple biasing potential can flatten these barriers and introduces an algorithm that determines system specific biasing potential coefficients. Two sources of error, deep traps at the end points and solvent disruption by hard-core potentials, are identified. Both scale with the size of the perturbed substituent and are removed by sharp biasing potentials and a new soft-core implementation, respectively. MSλD with landscape flattening is demonstrated on two sets of molecules: derivatives of the heat shock protein 90 inhibitor geldanamycin and derivatives of benzoquinone. In the benzoquinone system, landscape flattening leads to 2 orders of magnitude improvement in transition rates between substituents and robust solvation free energies. Landscape flattening opens up new applications for MSλD by enabling larger chemical perturbations to be sampled with improved precision and accuracy.

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.

Novel theoretically designed HIV-1 non-nucleoside reverse transcriptase inhibitors derived from nevirapine

A common problem with non-nucleoside reverse transcriptase inhibitors (NNRTIs) of HIV-1 is the emergence of mutations in the HIV-1 RT, in particular Lys103 → Asn (K103N) and Tyr181 → Cys (Y181C), which lead to resistance to this entire class of inhibitors. In this study, we theoretically designed two new non-nucleoside HIV-1 RT inhibitors, Mnev-1 and Mnev-2, derived from nevirapine, in order to reduce the resistance caused by those HIV-1 RT mutations. The binding modes of Mnev-1 and Mnev-2 with the wild-type HIV-1 RT and its mutants (K103N and Y181C) were suggested by molecular docking followed by 20-ns molecular dynamics (MD) simulations in explicit water of those binding complexes (HIV-1 RTs with the new inhibitors). A molecular mechanics/generalized Born surface area (MM/GBSA) calculation was carried out for multiple snapshots extracted from the MD trajectory to estimate the binding free energy. The results of the calculations show that each of the new inhibitors forms a stable hydrogen bond with His235 during the MD simulations, leading to tighter binding of the new inhibitors with their targets. In addition, the repulsive interaction with Cys181 in the Y181C-nevirapine complex is not present in the novel inhibitors. The binding affinities predicted using the MM/GBSA calculations indicate that the new inhibitors could be effective at bypassing the drug resistance of these HIV-1 RT mutants.

Arylsulfone-based HIV-1 non-nucleoside reverse transcriptase inhibitors

HIV-1 non-nucleoside reverse transcriptase inhibitors (NNRTIs) represent one of the most significant classes of drugs for the treatment of AIDS/HIV infection. Over the past two decades several potent arylsulfone-based HIV-1 NNRTIs and related analogs have been developed. This review provides an essential overview of the structure–activity relationships of the arylsulfone-based HIV-1 NNRTIs. Furthermore, structural information useful for the design and development of new sulfur containing NNRTIs with enhanced antiretroviral activity against HIV-1 wild type and clinically relevant drug resistant HIV-1 mutant strains will be discussed.

Molecular docking studies of marine diterpenes as inhibitors of wild-type and mutants HIV-1 reverse transcriptase

AIDS is a pandemic responsible for more than 35 million deaths. The emergence of resistant mutations due to drug use is the biggest cause of treatment failure. Marine organisms are sources of different molecules, some of which offer promising HIV-1 reverse transcriptase (RT) inhibitory activity, such as the diterpenes dolabelladienotriol (THD, IC₅₀ = 16.5 µM), (6R)-6-hydroxydichotoma-3,14-diene-1,17-dial (HDD, IC₅₀ = 10 µM) and (6R)-6-acetoxydichotoma-3,14-diene-1,17-dial (ADD, IC₅₀ = 35 µM), isolated from a brown algae of the genus Dictyota, showing low toxicity. In this work, we evaluated the structure-activity relationship (SAR) of THD, HDD and ADD as anti HIV-1 RT, using a molecular modeling approach. The analyses of stereoelectronic parameters revealed a direct relationship between activity and HOMO (Highest Occupied Molecular Orbital)-LUMO (Lowest Unoccupied Molecular Orbital) gap (E_LUMO–E_HOMO), where antiviral profile increases with larger HOMO-LUMO gap values. We also performed molecular docking studies of THD into HIV-1 RT wild-type and 12 different mutants, which showed a seahorse conformation, hydrophobic interactions and hydrogen bonds with important residues of the binding pocket. Based on in vitro experiments and docking studies, we demonstrated that mutations have little influence in positioning and interactions of THD. Following a rational drug design, we suggest a modification of THD to improve its biological activity.

Accurate calculation of mutational effects on the thermodynamics of inhibitor binding to p38α MAP kinase: a combined computational and experimental study

A major current challenge for drug design efforts focused on protein kinases is the development of drug resistance caused by spontaneous mutations in the kinase catalytic domain. The ubiquity of this problem means that it would be advantageous to develop fast, effective computational methods that could be used to determine the effects of potential resistance-causing mutations before they arise in a clinical setting. With this long-term goal in mind, we have conducted a combined experimental and computational study of the thermodynamic effects of active-site mutations on a well-characterized and high-affinity interaction between a protein kinase and a small-molecule inhibitor. Specifically, we developed a fluorescence-based assay to measure the binding free energy of the small-molecule inhibitor, SB203580, to the p38α MAP kinase and used it measure the inhibitor's affinity for five different kinase mutants involving two residues (Val38 and Ala51) that contact the inhibitor in the crystal structure of the inhibitor-kinase complex. We then conducted long, explicit-solvent thermodynamic integration (TI) simulations in an attempt to reproduce the experimental relative binding affinities of the inhibitor for the five mutants; in total, a combined simulation time of 18.5 μs was obtained. Two widely used force fields - OPLS-AA/L and Amber ff99SB-ILDN - were tested in the TI simulations. Both force fields produced excellent agreement with experiment for three of the five mutants; simulations performed with the OPLS-AA/L force field, however, produced qualitatively incorrect results for the constructs that contained an A51V mutation. Interestingly, the discrepancies with the OPLS-AA/L force field could be rectified by the imposition of position restraints on the atoms of the protein backbone and the inhibitor without destroying the agreement for other mutations; the ability to reproduce experiment depended, however, upon the strength of the restraints' force constant. Imposition of position restraints in corresponding simulations that used the Amber ff99SB-ILDN force field had little effect on their ability to match experiment. Overall, the study shows that both force fields can work well for predicting the effects of active-site mutations on small molecule binding affinities and demonstrates how a direct combination of experiment and computation can be a powerful strategy for developing an understanding of protein-inhibitor interactions.

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.

Efficient discovery of potent anti-HIV agents targeting the Tyr181Cys variant of HIV reverse transcriptase

Non-nucleoside reverse transcriptase inhibitors (NNRTIs) that interfere with the replication of human immunodeficiency virus (HIV) are being pursued with guidance from molecular modeling including free-energy perturbation (FEP) calculations for protein-inhibitor binding affinities. The previously reported pyrimidinylphenylamine 1 and its chloro analogue 2 are potent anti-HIV agents; they inhibit replication of wild-type HIV-1 in infected human T-cells with EC(50) values of 2 and 10 nM, respectively. However, they show no activity against viral strains containing the Tyr181Cys (Y181C) mutation in HIV-RT. Modeling indicates that the problem is likely associated with extensive interaction between the dimethylallyloxy substituent and Tyr181. As an alternative, a phenoxy group is computed to be oriented in a manner diminishing the contact with Tyr181. However, this replacement leads to a roughly 1000-fold loss of activity for 3 (2.5 μM). The present report details the efficient, computationally driven evolution of 3 to novel NNRTIs with sub-10 nM potency toward both wild-type HIV-1 and Y181C-containing variants. The critical contributors were FEP substituent scans for the phenoxy and pyrimidine rings and recognition of potential benefits of addition of a cyanovinyl group to the phenoxy ring.

Multi-Site λ-dynamics for simulated Structure-Activity Relationship studies

Multi-Site λ-dynamics (MSλD) is a new free energy simulation method that is based on λ-dynamics. It has been developed to enable multiple substituents at multiple sites on a common ligand core to be modeled simultaneously and their free energies assessed. The efficacy of MSλD for estimating relative hydration free energies and relative binding affinties is demonstrated using three test systems. Model compounds representing multiple identical benzene, dihydroxybenzene and dimethoxybenzene molecules show total combined MSλD trajectory lengths of ~1.5 ns are sufficient to reliably achieve relative hydration free energy estimates within 0.2 kcal/mol and are less sensitive to the number of trajectories that are used to generate these estimates for hybrid ligands that contain up to ten substituents modeled at a single site or five substituents modeled at each of two sites. Relative hydration free energies among six benzene derivatives calculated from MSλD simulations are in very good agreement with those from alchemical free energy simulations (with average unsigned differences of 0.23 kcal/mol and R(2)=0.991) and experiment (with average unsigned errors of 1.8 kcal/mol and R(2)=0.959). Estimates of the relative binding affinities among 14 inhibitors of HIV-1 reverse transcriptase obtained from MSλD simulations are in reasonable agreement with those from traditional free energy simulations and experiment (average unsigned errors of 0.9 kcal/mol and R(2)=0.402). For the same level of accuracy and precision MSλD simulations are achieved ~20-50 times faster than traditional free energy simulations and thus with reliable force field parameters can be used effectively to screen tens to hundreds of compounds in structure-based drug design applications.

A combined sequence-structure approach for predicting resistance to the non-nucleoside HIV-1 reverse transcriptase inhibitor Nevirapine

The development of drug resistance to antiretroviral medications used to treat infection with HIV-1 is a major concern. Given the cost and time constraints associated with phenotypic resistance testing, computational approaches leading to accurate predictive models of resistance based on a patient's mutational patterns in the target protein would provide a welcome alternative. A combined sequence-structure computational mutagenesis procedure is used to generate attribute vectors for each of 222 mutational patterns of HIV-1 reverse transcriptase that were isolated and sequenced from patients. Phenotypic fold-levels of resistance to the non-nucleoside inhibitor Nevirapine are known for over 25% of these mutants, whose values are used to assign each assayed mutant to a drug susceptibility class, either sensitive or resistant. Support vector machine and random forest supervised learning algorithms applied to this subset respectively classify mutants based on drug susceptibility with 85% and 92% cross-validation accuracy. The trained models are used to predict susceptibility to Nevirapine for all remaining mutant isolates, and predictions are in agreement for 90% of the test cases.

Modeling Protein-Ligand Binding by Mining Minima

We present the first application of the mining minima algorithm to protein-small molecule binding. This end-point approach use an empirical force field and implicit solvent models, treats the protein binding-site as fully flexible and estimates free energies as sums over local energy wells. The calculations are found to yield encouraging agreement with experiment for three sets of HIV-1protease inhibitors and a set of phosphodiesterase 10a inhibitors. The contributions of various aspects of the model to its accuracy are examined, and the Poisson-Boltzmann correction is found to be the most critical. Interestingly, the computed changes in configurational entropy upon binding fall roughly along the same entropy-energy correlation previously observed for smaller host-guest systems. Strengths and weaknesses of the method are discussed, as are the prospects for enhancing accuracy and speed.

Efavirenz binding to HIV-1 reverse transcriptase monomers and dimers

Efavirenz (EFV) is a nonnucleoside reverse transcriptase inhibitor (NNRTI) of HIV-1 reverse transcriptase (RT) used for the treatment of AIDS. RT is a heterodimer composed of p66 and p51 subunits; p51 is produced from p66 by C-terminal truncation by HIV protease. The monomers can form p66/p66 and p51/p51 homodimers as well as the p66/p51 heterodimer. Dimerization and efavirenz binding are coupled processes. In the crystal structure of the p66/p51-EFV complex, the drug is bound to the p66 subunit. The binding of efavirenz to wild-type and dimerization-defective RT proteins was studied by equilibrium dialysis, tryptophan fluorescence, and native gel electrophoresis. A 1:1 binding stoichiometry was determined for both monomers and homodimers. Equilibrium dissociation constants are approximately 2.5 microM for both p66- and p51-EFV complexes, 250 nM for the p66/p66-EFV complex, and 7 nM for the p51/p51-EFV complex. An equilibrium dissociation constant of 92 nM for the p66/p51-EFV complex was calculated from the thermodynamic linkage between dimerization and inhibitor binding. Binding and unbinding kinetics monitored by fluorescence were slow. Progress curve analyses revealed a one-step, direct binding mechanism with association rate constants k(1) of approximately 13.5 M(-1) s(-1) for monomers and heterodimer and dissociation rate constants k(-1) of approximately 9 x 10(-5) s(-1) for monomers. A conformational selection mechanism is proposed to account for the slow association rate. These results show that efavirenz is a slow, tight-binding inhibitor capable of binding all forms of RT and suggest that the NNRTI binding site in monomers and dimers is similar.

Efficient drug lead discovery and optimization

During the 1980s, advances in the abilities to perform computer simulations of chemical and biomolecular systems and to calculate free energy changes led to the expectation that such methodology would soon show great utility for guiding molecular design. Important potential applications included design of selective receptors, catalysts, and regulators of biological function including enzyme inhibitors. This time also saw the rise of high-throughput screening and combinatorial chemistry along with complementary computational methods for de novo design and virtual screening including docking. These technologies appeared poised to deliver diverse lead compounds for any biological target. As with many technological advances, realization of the expectations required significant additional effort and time. However, as summarized here, striking success has now been achieved for computer-aided drug lead generation and optimization. De novo design using both molecular growing and docking are illustrated for lead generation, and lead optimization features free energy perturbation calculations in conjunction with Monte Carlo statistical mechanics simulations for protein-inhibitor complexes in aqueous solution. The specific applications are to the discovery of non-nucleoside inhibitors of HIV reverse transcriptase (HIV-RT) and inhibitors of the binding of the proinflammatory cytokine MIF to its receptor CD74. A standard protocol is presented that includes scans for possible additions of small substituents to a molecular core, interchange of heterocycles, and focused optimization of substituents at one site. Initial leads with activities at low-micromolar concentrations have been advanced rapidly to low-nanomolar inhibitors.

Optimization of azoles as anti-human immunodeficiency virus agents guided by free-energy calculations

Efficient optimization of an inactive 2-anilinyl-5-benzyloxadiazole core has been guided by free energy perturbation (FEP) calculations to provide potent non-nucleoside inhibitors of human immunodeficiency virus (HIV) reverse transcriptase (NNRTIs). An FEP "chlorine scan" was performed to identify the most promising sites for substitution of aryl hydrogens. This yielded NNRTIs 8 and 10 with activities (EC50) of 820 and 310 nM for protection of human T-cells from infection by wild-type HIV-1. FEP calculations for additional substituent modifications and change of the core heterocycle readily led to oxazoles 28 and 29, which were confirmed as highly potent anti-HIV agents with activities in the 10-20 nM range. The designed compounds were also monitored for possession of desirable pharmacological properties by use of additional computational tools. Overall, the trends predicted by the FEP calculations were well borne out by the assay results. FEP-guided lead optimization is confirmed as a valuable tool for molecular design including drug discovery; chlorine scans are particularly attractive since they are both straightforward to perform and highly informative.

Energetic effects for observed and unobserved HIV-1 reverse transcriptase mutations of residues L100, V106, and Y181 in the presence of nevirapine and efavirenz

The effect of mutations on amino acid residues L100, V106, and Y181 for unbound HIV-1 reverse transcriptase (RT) and RT bound to nevirapine and efavirenz was investigated using Monte Carlo/free energy perturbation calculations. Using both native and bound crystal structures of RT, mutation of the amino acid residues to both those observed and unobserved in patients was carried out. The results of the calculations revealed that the variant that survives in patients dosed with either nevirapine or efavirenz had a more positive Delta Delta G value than other variants that were not observed in patients. These data suggest that the mutation observed in patients is the most effective (the one that binds the drug most weakly) of all possible codon change mutations.

Reverse transcription of the HIV-1 pandemic

The HIV/AIDS pandemic has existed for >25 years. Extensive work globally has provided avenues to combat viral infection, but the disease continues to rage on in the human population and infected approximately 4 million people in 2006 alone. In this review, we provide a brief history of HIV/AIDS, followed by analysis of one therapeutic target of HIV-1: its reverse transcriptase (RT). We discuss the biochemical characterization of RT in order to place emphasis on possible avenues of inhibition, which now includes both nucleoside and non-nucleoside modalities. Therapies against RT remain a cornerstone of anti-HIV treatment, but the virus eventually resists inhibition through the selection of drug-resistant RT mutations. Current inhibitors and associated resistance are discussed, with the hopes that new therapeutics can be developed against RT.

Arylthiopyrrole (AThP) Derivatives as Non-Nucleoside HIV-1 Reverse Transcriptase Inhibitors: Synthesis, Structure–Activity Relationships, and Docking Studies (Part 2)

Arylthio isopropyl pyridinylmethylpyrrolemethanols (AThPs) have been recently reported as a new class of human immunodeficiency virus type 1 (HIV-1) reverse transcriptase (RT) inhibitors acting at the non-nucleoside binding site (NNBS) of this enzyme. Docking experiments of the potent inhibitors 4k (IC(50) = 0.24 microM, SI = 167) and 5e (IC(50) = 0.11 microM, SI > 1667) of wild-type RT prompted the synthesis and biological evaluation of novel AThP derivatives featuring a number of polar groups in position 3 of the pyrrole ring and larger and more hydrophobic alicyclic substituents in place of the isopropyl group at position 4. Among the compounds synthesized and tested in cell-based assays against HIV-1 infected cells, 19b was the most active, with EC(50) = 0.007 microM, CC(50) = 114.5 microm, and SI = 16357. This compound and its precursor 18b retained interesting activities against clinically relevant drug-resistant RT forms carrying K103N, Y181I, and L100I mutations. Docking calculations of 10, 14, 18b, and 19b were also performed to investigate their binding mode into the RT NNBS and to rationalize both structure-activity relationship and resistance data.

Computational Study of the Interaction between TIBO Inhibitors and Y181 (C181), K101, and Y188 Amino Acids

The non-nucleoside inhibitors of HIV-1 reverse transcriptase (NNRTIs) are an important class of drugs employed in anti-HIV chemotherapy. TIBO compounds, which belong to the NNRTIs class, are potent inhibitors of the HIV-1 reverse transcriptase enzyme (HIV-1 RT). However, mutations in the amino acids present in the active site of these inhibitors limit their clinical use. In this work, the intermolecular interactions taking place between compounds of the TIBO family and Y181 (C181), K101, and Y188 amino acids are investigated. For this purpose the coordinates of three RT crystalline structures complexed with TIBO were taken from PDB database, and were analyzed by means of the B3LYP/6-31+G(d,p) model. The natural bond orbital (NBO) and atoms in molecules (AIM) methods indicate that not only does the Y181C mutation lead to loss of favorable interactions between the TIBO side chains and tyrosine, but it also affects the interaction between the inhibitor and K101 and Y188. Results also revealed that the interaction between TIBO and K101 is stabilized by N-H...O and N-H...S hydrogen bonds. This is the first time that the presence of the latter hydrogen bond (N-H...S) is reported to play an important role in the stabilization of the interaction between TIBO and K101. In addition the NBO and natural population analyses (NPA) indicate that the 8 Cl-TIBO inhibitor presents a more effective interaction with the Y181, K101, and Y188 than that of 9 Cl-TIBO.

Molecular modeling of organic and biomolecular systems using BOSS and MCPRO

An overview is provided of the capabilities for the current versions of the BOSS and MCPRO programs for molecular modeling of organic and biomolecular systems. Recent applications are noted, particularly for QM/MM studies of organic and enzymatic reactions and for protein-ligand binding.

Computer-aided design of non-nucleoside inhibitors of HIV-1 reverse transcriptase

Design principles are delineated for non-nucleoside inhibitors for HIV-1 reverse transcriptase (NNRTIs). Simultaneous optimization of binding affinity for wild-type RT, tolerance for viral mutations, and physical properties is pursued. Automated lead generation with the growing program BOMB, Monte Carlo simulations with free-energy perturbation theory for lead optimization, and property analysis with QikProp are featured. An initial 30 microM lead has been optimized rapidly to the 10 nM level.

Binding energy analysis for wild-type and Y181C mutant HIV-1 RT/8-Cl TIBO complex structures: Quantum chemical calculations based on the ONIOM method

Two-layered and three-layered ONIOM calculations were performed to compare the binding energies of 8-Cl TIBO inhibitor when bound into the human immunodeficiency virus reverse transcriptase binding pocket and a Y181C variant. Both consisted of 20 residues within a radius of 15 A. A combination of different methods [MP2/6-31G(d), B3LYP/6-31G(d,p), and PM3] were performed to take advantage of ONIOM's layering strategy analysis. The obtained results clearly indicate that the Y181C mutation reduces the binding affinity and stability of the inhibitor by approximately 8-9 kcal/mol as obtained from different combined MO:MO methods. Analyses regarding the energetic components of the interaction and deformation energies for 8-Cl TIBO inhibitor upon binding were also examined extensively. Additional calculations involving the interaction energies between 8-Cl TIBO with individual residues surrounding the binding pocket were performed at MP2/6-31G(d,p) and B3LYP/6-31G(d,p) levels of theory to gain more insight into the energetic differences of wild-type and Y181C mutant type at the atomistic level.

Effects of drug resistance mutations L100I and V106A on the binding of pyrrolobenzoxazepinone nonnucleoside inhibitors to the human immunodeficiency virus type 1 reverse transcriptase catalytic complex

We have previously described a novel class of nonnucleoside reverse transcriptase (RT) inhibitors, the pyrrolobenzoxazepinone (PBO) and the pyridopyrrolooxazepinone (PPO) derivatives, which were effective inhibitors of human immunodeficiency virus type 1 (HIV-1) RT, either wild type or carrying known drug resistance mutations (G. Campiani et al., J. Med. Chem. 42:4462-4470, 1999). The lead compound of the PPO class, (R)-(-)-PPO464, was shown to selectively target the ternary complex formed by the viral RT with its substrates nucleic acid and nucleotide (G. Maga et al., J. Biol. Chem. 276:44653-44662, 2001). In order to better understand the structural basis for this selectivity, we exploited some PBO analogs characterized by various substituents at C-3 and by different inhibition potencies and drug resistance profiles, and we studied their interaction with HIV-1 RT wild type or carrying the drug resistance mutations L100I and V106A. Our kinetic and thermodynamic analyses showed that the formation of the complex between the enzyme and the nucleotide increased the inhibition potency of the compound PBO354 and shifted the free energy (energy of activation, DeltaG(#)) for inhibitor binding toward more negative values. The V106A mutation conferred resistance to PBO 354 by increasing its dissociation rate from the enzyme, whereas the L100I mutation mainly decreased the association rate. This latter mutation also caused a severe reduction in the catalytic efficiency of the RT. These results provide a correlation between the efficiency of nucleotide utilization by RT and its resistance to PBO inhibition.