Machine learning-guided design of potent darunavir analogs targeting HIV-1 proteases: A computational approach for antiretroviral drug discovery

In the pursuit of novel antiretroviral therapies for human immunodeficiency virus type-1 (HIV-1) proteases (PRs), recent improvements in drug discovery have embraced machine learning (ML) techniques to guide the design process. This study employs ensemble learning models to identify crucial substructures as significant features for drug development. Using molecular docking techniques, a collection of 160 darunavir (DRV) analogs was designed based on these key substructures and subsequently screened using molecular docking techniques. Chemical structures with high fitness scores were selected, combined, and one-dimensional (1D) screening based on beyond Lipinski's rule of five (bRo5) and ADME (absorption, distribution, metabolism, and excretion) prediction implemented in the Combined Analog generator Tool (CAT) program. A total of 473 screened analogs were subjected to docking analysis through convolutional neural networks scoring function against both the wild-type (WT) and 12 major mutated PRs. DRV analogs with negative changes in binding free energy (ΔΔ G bind ) compared to DRV could be categorized into four attractive groups based on their interactions with the majority of vital PRs. The analysis of interaction profiles revealed that potent designed analogs, targeting both WT and mutant PRs, exhibited interactions with common key amino acid residues. This observation further confirms that the ML model-guided approach effectively identified the substructures that play a crucial role in potent analogs. It is expected to function as a powerful computational tool, offering valuable guidance in the identification of chemical substructures for synthesis and subsequent experimental testing.

FMO-guided design of darunavir analogs as HIV-1 protease inhibitors

The prevalence of HIV-1 infection continues to pose a significant global public health issue, highlighting the need for antiretroviral drugs that target viral proteins to reduce viral replication. One such target is HIV-1 protease (PR), responsible for cleaving viral polyproteins, leading to the maturation of viral proteins. While darunavir (DRV) is a potent HIV-1 PR inhibitor, drug resistance can arise due to mutations in HIV-1 PR. To address this issue, we developed a novel approach using the fragment molecular orbital (FMO) method and structure-based drug design to create DRV analogs. Using combinatorial programming, we generated novel analogs freely accessible via an on-the-cloud mode implemented in Google Colab, Combined Analog generator Tool (CAT). The designed analogs underwent cascade screening through molecular docking with HIV-1 PR wild-type and major mutations at the active site. Molecular dynamics (MD) simulations confirmed the assess ligand binding and susceptibility of screened designed analogs. Our findings indicate that the three designed analogs guided by FMO, 19-0-14-3, 19-8-10-0, and 19-8-14-3, are superior to DRV and have the potential to serve as efficient PR inhibitors. These findings demonstrate the effectiveness of our approach and its potential to be used in further studies for developing new antiretroviral drugs.

Advanced molecular mechanisms of modified DRV compounds in targeting HIV-1 protease mutations and interrupting monomer dimerization

HIV-1 protease (PR) plays a crucial role in the treatment of HIV as a key target. The global issue of emerging drug resistance is escalating, and PR mutations pose a substantial challenge to the effectiveness of inhibitors. HIV-1 PR is an ideal model for studying drug resistance to inhibitors. The inhibitor, darunavir (DRV), exhibits a high genetic barrier to viral resistance, but with mutations of residues in the PR, there is also some resistance to DRV. Inhibitors can impede PR in two ways: one involves binding to the active site of the dimerization protease, and the other involves binding to the PR monomer, thereby preventing dimerization. In this study, we aimed to investigate the inhibitory effect of DRV with a modified inhibitor on PR, comparing the differences between wild-type and mutated PR, using molecular dynamics simulations. The inhibitory effect of the inhibitors on PR monomers was subsequently investigated. And molecular mechanics Poisson-Boltzmann surface area evaluated the binding free energy. The energy contribution of individual residues in the complex was accurately calculated by the alanine scanning binding interaction entropy method. The results showed that these inhibitors had strong inhibitory effects against PR mutations, with GRL-142 exhibiting potent inhibition of both the PR monomer and dimer. Improved inhibitors could strengthen hydrogen bonds and interactions with PR, thereby boosting inhibition efficacy. The binding of the inhibitor and mutation of the PR affected the distance between D25 and I50, preventing their dimerization and the development of drug resistance. This study could accelerate research targeting HIV-1 PR inhibitors and help to further facilitate drug design targeting both mechanisms.

Exploration of imatinib and nilotinib-derived templates as the P2-Ligand for HIV-1 protease inhibitors: Design, synthesis, protein X-ray structural studies, and biological evaluation

Structure-based design, synthesis, X-ray structural studies, and biological evaluation of a new series of potent HIV-1 protease inhibitors are described. These inhibitors contain various pyridyl-pyrimidine, aryl thiazole or alkylthiazole derivatives as the P2 ligands in combination with darunavir-like hydroxyethylamine sulfonamide isosteres. These heterocyclic ligands are inherent to kinase inhibitor drugs, such as nilotinib and imatinib. These ligands are designed to make hydrogen bonding interactions with the backbone atoms in the S2 subsite of HIV-1 protease. Various benzoic acid derivatives have been synthesized and incorporation of these ligands provided potent inhibitors that exhibited subnanomolar level protease inhibitory activity and low nanomolar level antiviral activity. Two high resolution X-ray structures of inhibitor-bound HIV-1 protease were determined. These structures provided important ligand-binding site interactions for further optimization of this class of protease inhibitors.

Understanding Drug Resistance of Wild-Type and L38HL Insertion Mutant of HIV-1 C Protease to Saquinavir

Acquired immunodeficiency syndrome (AIDS) is one of the most challenging infectious diseases to treat on a global scale. Understanding the mechanisms underlying the development of drug resistance is necessary for novel therapeutics. HIV subtype C is known to harbor mutations at critical positions of HIV aspartic protease compared to HIV subtype B, which affects the binding affinity. Recently, a novel double-insertion mutation at codon 38 (L38HL) was characterized in HIV subtype C protease, whose effects on the interaction with protease inhibitors are hitherto unknown. In this study, the potential of L38HL double-insertion in HIV subtype C protease to induce a drug resistance phenotype towards the protease inhibitor, Saquinavir (SQV), was probed using various computational techniques, such as molecular dynamics simulations, binding free energy calculations, local conformational changes and principal component analysis. The results indicate that the L38HL mutation exhibits an increase in flexibility at the hinge and flap regions with a decrease in the binding affinity of SQV in comparison with wild-type HIV protease C. Further, we observed a wide opening at the binding site in the L38HL variant due to an alteration in flap dynamics, leading to a decrease in interactions with the binding site of the mutant protease. It is supported by an altered direction of motion of flap residues in the L38HL variant compared with the wild-type. These results provide deep insights into understanding the potential drug resistance phenotype in infected individuals.

HIV-1 protease with 10 lopinavir and darunavir resistance mutations exhibits altered inhibition, structural rearrangements and extreme dynamics

Antiretroviral drug resistance is a therapeutic obstacle for people with HIV. HIV protease inhibitors darunavir and lopinavir are recommended for resistant infections. We characterized a protease mutant (PR10x) derived from a highly resistant clinical isolate including 10 mutations associated with resistance to lopinavir and darunavir. Compared to the wild-type protease, PR10x exhibits ∼3-fold decrease in catalytic efficiency and Ki values of 2-3 orders of magnitude worse for darunavir, lopinavir, and potent investigational inhibitor GRL-519. Crystal structures of the mutant were solved in a ligand-free form and in complex with GRL-519. The structures show altered interactions in the active site, flap-core interface, hydrophobic core, hinge region, and 80s loop compared to the corresponding wild-type protease structures. The ligand-free crystal structure exhibits a highly curled flap conformation which may amplify drug resistance. Molecular dynamics simulations performed for 1 μs on ligand-free dimers showed extremely large fluctuations in the flaps for PR10x compared to equivalent simulations on PR with a single L76V mutation or wild-type protease. This analysis offers insight about the synergistic effects of mutations in highly resistant variants.

Discovery of Novel HIV Protease Inhibitors Using Modern Computational Techniques

The human immunodeficiency virus type 1 (HIV-1) has continued to be a global concern. With the new HIV incidence, the emergence of multi-drug resistance and the untoward side effects of currently used anti-HIV drugs, there is an urgent need to discover more efficient anti-HIV drugs. Modern computational tools have played vital roles in facilitating the drug discovery process. This research focuses on a pharmacophore-based similarity search to screen 111,566,735 unique compounds in the PubChem database to discover novel HIV-1 protease inhibitors (PIs). We used an in silico approach involving a 3D-similarity search, physicochemical and ADMET evaluations, HIV protease-inhibitor prediction (IC50/percent inhibition), rigid receptor-molecular docking studies, binding free energy calculations and molecular dynamics (MD) simulations. The 10 FDA-approved HIV PIs (saquinavir, lopinavir, ritonavir, amprenavir, fosamprenavir, atazanavir, nelfinavir, darunavir, tipranavir and indinavir) were used as reference. The in silico analysis revealed that fourteen out of the twenty-eight selected optimized hit molecules were within the acceptable range of all the parameters investigated. The hit molecules demonstrated significant binding affinity to the HIV protease (PR) when compared to the reference drugs. The important amino acid residues involved in hydrogen bonding and п-п stacked interactions include ASP25, GLY27, ASP29, ASP30 and ILE50. These interactions help to stabilize the optimized hit molecules in the active binding site of the HIV-1 PR (PDB ID: 2Q5K). HPS/002 and HPS/004 have been found to be most promising in terms of IC50/percent inhibition (90.15%) of HIV-1 PR, in addition to their drug metabolism and safety profile. These hit candidates should be investigated further as possible HIV-1 PIs with improved efficacy and low toxicity through in vitro experiments and clinical trial investigations.

Decoding drug resistant mechanism of V32I, I50V and I84V mutations of HIV-1 protease on amprenavir binding by using molecular dynamics simulations and MM-GBSA calculations

Mutations V32I, I50V and I84V in the HIV-1 protease (PR) induce drug resistance towards drug amprenavir (APV). Multiple short molecular dynamics (MSMD) simulations and molecular mechanics generalized Born surface area (MM-GBSA) method were utilized to investigate drug-resistant mechanism of V32I, I50V and I84V towards APV. Dynamic information arising from MSMD simulations suggest that V32I, I50V and I84V highly affect structural flexibility, motion modes and conformational behaviours of two flaps in the PR. Binding free energies calculated by MM-GBSA method suggest that the decrease in binding enthalpy and the increase in binding entropy induced by mutations V32I, I50V and I84V are responsible for drug resistance of the mutated PRs on APV. The energetic contributions of separate residues on binding of APV to the PR show that V32I, I50V and I84V highly disturb the interactions of two flaps with APV and mostly drive the decrease in binding ability of APV to the PR. Thus, the conformational changes of two flaps in the PR caused by V32I, I50V and I84V play key roles in drug resistance of three mutated PR towards APV. This study can provide useful dynamics information for the design of potent inhibitors relieving drug resistance.

Multiple Molecular Dynamics Simulations and Energy Analysis Unravel the Dynamic Properties and Binding Mechanism of Mutants HIV-1 Protease with DRV and CA-p2

PRS17, a variant of human immunodeficiency virus type I protease (HIV-1 PR), has 17 mutated residues showing high levels of multidrug resistance. To describe the effects of these mutated residues on the dynamic properties and the binding mechanism of PR with substrate and inhibitor, focused on six systems (two complexes of WT PR and PRS17 with inhibitor Darunavir (DRV), two complexes of WT PR and PRS17 with substrate analogue CA-p2, two unligand WT PR and PRS17), we performed multiple molecular dynamics (MD) simulations combined with MM-PBSA and solvated interaction energy (SIE) methods. For both the unligand PRs and ligand-PR complexes, the results from simulations revealed 17 mutated residues alter the flap-flap distance, the distance from flap regions to catalytic sites, and the curling degree of the flap tips. These mutated residues changed the flexibility of the flap region in PR, and thus affected its binding energy with DRV and CA-p2, resulting in differences in sensitivity. Hydrophobic cavity makes an important contribution to the binding of PR and ligands. And most noticeable of all, the binding of the guanidine group in CA-p2 and Arg8' of PRS17 is useful for increasing their binding ability. These results have important guidance for the further design of drugs against multidrug resistant PR. IMPORTANCE Developing effective anti-HIV inhibitors is the current requirement to cope with the emergence of the resistance of mutants. Compared with the experiments, MD simulations along with energy calculations help reduce the time and cost of designing new inhibitors. Based on our simulation results, we propose two factors that may help design effective inhibitors against HIV-1 PR: (i) importance of hydrophobic cavity, and (ii) introduction of polar groups similar to the guanidine group.

Drug Resistance Mechanism of M46I-Mutation-Induced Saquinavir Resistance in HIV-1 Protease Using Molecular Dynamics Simulation and Binding Energy Calculation

Drug-resistance-associated mutation in essential proteins of the viral life cycle is a major concern in anti-retroviral therapy. M46I, a non-active site mutation in HIV-1 protease has been clinically associated with saquinavir resistance in HIV patients. A 100 ns molecular dynamics (MD) simulation and MM-PBSA calculations were performed to study the molecular mechanism of M46I-mutation-based saquinavir resistance. In order to acquire deeper insight into the drug-resistance mechanism, the flap curling, closed/semi-open/open conformations, and active site compactness were studied. The M46I mutation significantly affects the energetics and conformational stability of HIV-1 protease in terms of RMSD, RMSF, Rg, SASA, and hydrogen formation potential. This mutation significantly decreased van der Waals interaction and binding free energy (∆G) in the M46I–saquinavir complex and induced inward flap curling and a wider opening of the flaps for most of the MD simulation period. The predominant open conformation was reduced, but inward flap curling/active site compactness was increased in the presence of saquinavir in M46I HIV-1 protease. In conclusion, the M46I mutation induced structural dynamics changes that weaken the protease grip on saquinavir without distorting the active site of the protein. The produced information may be utilized for the discovery of inhibitor(s) against drug-resistant HIV-1 protease.

Role of Surfactants on Release Performance of Amorphous Solid Dispersions of Ritonavir and Copovidone

PURPOSE

To understand the role of different surfactants, incorporated into amorphous solid dispersions (ASDs) of ritonavir and copovidone, in terms of their impact on release, phase behavior and stabilization of amorphous precipitates formed following drug release.

METHODS

Ternary ASDs with ritonavir, copovidone and surfactants (30:70:5 w/w/w) were prepared by rotary evaporation. ASD release performance was tested using Wood's intrinsic dissolution rate apparatus and compared to the binary drug-polymer ASD with 30% drug loading. Size measurement of amorphous droplets was performed using dynamic light scattering. Solid state characterization was performed using attenuated total reflectance-infrared spectroscopy, differential scanning calorimetry and scanning electron microscopy.

RESULTS

All surfactant-containing ASDs showed improvement over the binary ASD. Span 85 and D-α-tocopheryl polyethylene glycol succinate (TPGS) showed complete release with no evidence of AAPS or crystallization whereas Span 20 and Tween 80 showed < 50% release with amorphous amorphous phase separation (AAPS). Span 20 also induced solution crystallization. Sodium dodecyl sulfate (SDS) showed very rapid, albeit incomplete (~ 80%) release. AAPS was not observed with SDS. However, crystallization on the dissolving solid surface was noted. Span 20 and TPGS formed the smallest and most size-stable droplets with ~ 1 µm size whereas coalescence was noted with other surfactants.

CONCLUSIONS

Surfactants improved the release performance relative to the binary ASD. Different surfactant types impacted overall performance to varying extents and affected different attributes. Overall, Span 85 showed best performance (complete release, no crystallization/AAPS and small droplet size). Correlation between physicochemical properties and surfactant performance was not observed.

Computational Simulation of HIV Protease Inhibitors to the Main Protease (Mpro) of SARS-CoV-2: Implications for COVID-19 Drugs Design

SARS-CoV-2 is highly homologous to SARS-CoV. To date, the main protease (Mpro) of SARS-CoV-2 is regarded as an important drug target for the treatment of Coronavirus Disease 2019 (COVID-19). Some experiments confirmed that several HIV protease inhibitors present the inhibitory effects on the replication of SARS-CoV-2 by inhibiting Mpro. However, the mechanism of action has still not been studied very clearly. In this work, the interaction mechanism of four HIV protease inhibitors Darunavir (DRV), Lopinavir (LPV), Nelfinavir (NFV), and Ritonavire (RTV) targeting SARS-CoV-2 Mpro was explored by applying docking, molecular dynamics (MD) simulations, and MM-GBSA methods using the broad-spectrum antiviral drug Ribavirin (RBV) as the negative and nonspecific control. Our results revealed that LPV, RTV, and NFV have higher binding affinities with Mpro, and they all interact with catalytic residues His41 and the other two key amino acids Met49 and Met165. Pharmacophore model analysis further revealed that the aromatic ring, hydrogen bond donor, and hydrophobic group are the essential infrastructure of Mpro inhibitors. Overall, this study applied computational simulation methods to study the interaction mechanism of HIV-1 protease inhibitors with SARS-CoV-2 Mpro, and the findings provide useful insights for the development of novel anti-SARS-CoV-2 agents for the treatment of COVID-19.

Cellulose derivatives as effective recrystallization inhibitor for ternary ritonavir solid dispersions: In vitro-in vivo evaluation

Amorphous solid dispersions (ASDs) are regarded as one of the most promising techniques for poorly-soluble active pharmaceutical ingredients (API). However, the thermodynamic instability of ASDs at supersaturated state makes them easy to recrystallize in aqueous media. In this study, ritonavir (RTV) was selected as a model drug for evaluating the solubility enhancement and recrystallization inhibition effect of various cellulose derivatives and the combinations of them with typical surfactants. Combination of HPMCAS-HF/SLS was filtrated for preparing ternary RTV solid dispersions (RTV SD) via solvent evaporation method. RTV SD exhibited enhanced dissolution manner, while the oral bioavailability of RTV SD was equivalent with the Reference Standard Norvir® but increased significantly compared to the ternary physical mixture. Thus, the ternary SD system might be promisingly employed as efficient drug delivery system for RTV, while the HPMCAS-HF/SLS combination could be recommended as effective excipient for fabricating steady solid dispersions loading poorly soluble API.

Towards the De Novo Design of HIV-1 Protease Inhibitors Based on Natural Products

Acquired immunodeficiency syndrome (AIDS) caused by the human immunodeficiency virus (HIV) continues to be a public health problem. In 2020, 680,000 people died from HIV-related causes, and 1.5 million people were infected. Antiretrovirals are a way to control HIV infection but not to cure AIDS. As such, effective treatment must be developed to control AIDS. Developing a drug is not an easy task, and there is an enormous amount of work and economic resources invested. For this reason, it is highly convenient to employ computer-aided drug design methods, which can help generate and identify novel molecules. Using the de novo design, novel molecules can be developed using fragments as building blocks. In this work, we develop a virtual focused compound library of HIV-1 viral protease inhibitors from natural product fragments. Natural products are characterized by a large diversity of functional groups, many sp³ atoms, and chiral centers. Pseudo-natural products are a combination of natural products fragments that keep the desired structural characteristics from different natural products. An interactive version of chemical space visualization of virtual compounds focused on HIV-1 viral protease inhibitors from natural product fragments is freely available in the supplementary material.

Prediction of HIV drug resistance based on the 3D protein structure: Proposal of molecular field mapping

A method for predicting HIV drug resistance by using genotypes would greatly assist in selecting appropriate combinations of antiviral drugs. Models reported previously have had two major problems: lack of information on the 3D protein structure and processing of incomplete sequencing data in the modeling procedure. We propose obtaining the 3D structural information of viral proteins by using homology modeling and molecular field mapping, instead of just their primary amino acid sequences. The molecular field potential parameters reflect the physicochemical characteristics associated with the 3D structure of the proteins. We also introduce the Bayesian conditional mutual information theory to estimate the probabilities of occurrence of all possible protein candidates from an incomplete sequencing sample. This approach allows for the effective use of uncertain information for the modeling process. We applied these data analysis techniques to the HIV-1 protease inhibitor dataset and developed drug resistance prediction models with reasonable performance.

Insights into effect of the Asp25/Asp25' protonation states on binding of inhibitors Amprenavir and MKP97 to HIV-1 protease using molecular dynamics simulations and MM-GBSA calculations

The protonation states of two aspartic acids in the catalytic strands of HIV-1 protease (PR) remarkably affect bindings of inhibitors to PR. It is requisite for the design of potent inhibitors towards PR to investigate the influences of Asp25/Asp25' protonated states on dynamics behaviour of PR and binding mechanism of inhibitors to PR. In this work, molecular dynamics (MD) simulations, MM-GBSA method and principal component (PC) analysis were coupled to explore the effect of Asp25/Asp25' protonation states on conformational changes of PR and bindings of Amprenavir and MKP97 to PR. The results show that the Asp25/Asp25' protonation states exert different impacts on structural fluctuations, flexibility and motion modes of PR. Dynamics analysis verifies that Asp25/Asp25' protonated states highly affect conformational dynamics of two flaps in PR. The binding free energy calculations results suggest that the Asp25/Asp25' protonated states obviously strengthen bindings of inhibitors to PR compared to the non-protonation state. Calculations of residue-based free energy decomposition indicate that the Asp25/Asp25' protonation not only disturbs the interaction network of inhibitors with PR but also stabilizes bindings of inhibitors to PR by cancelling the electrostatic repulsive interaction. Therefore, special attentions should be paid to the Asp25/Asp25' protonation in the design of potent inhibitors towards PR.

Deciphering Complex Mechanisms of Resistance and Loss of Potency through Coupled Molecular Dynamics and Machine Learning

Drug resistance threatens many critical therapeutics through mutations in the drug target. The molecular mechanisms by which combinations of mutations, especially those remote from the active site, alter drug binding to confer resistance are poorly understood and thus difficult to counteract. A machine learning strategy was developed that coupled parallel molecular dynamics simulations with experimental potency to identify specific conserved mechanisms underlying resistance. Physical features were extracted from the simulations, analyzed, and integrated into one consistent and interpretable elastic network model. To rigorously test this strategy, HIV-1 protease variants with diverse mutations were used, with potencies ranging from picomolar to micromolar to the drug darunavir. Feature reduction resulted in a model with four specific features that predicts for both the training and test sets inhibitor binding free energy within 1 kcal/mol of the experimental value over this entire range of potency. These predictive features are physically interpretable, as they vary specifically with affinity and diagonally transverse across the protease homodimer. This physics-based strategy of parallel molecular dynamics and machine learning captures mechanisms by which complex combinations of mutations confer resistance and identify critical features that serve as bellwethers of affinity, which will be critical in future drug design.

Computational Determination of Potential Inhibitors of SARS-CoV-2 Main Protease

The novel coronavirus (SARS-CoV-2) has infected several million people and caused thousands of deaths worldwide since December 2019. As the disease is spreading rapidly all over the world, it is urgent to find effective drugs to treat the virus. The main protease (Mpro) of SARS-CoV-2 is one of the potential drug targets. Therefore, in this context, we used rigorous computational methods, including molecular docking, fast pulling of ligand (FPL), and free energy perturbation (FEP), to investigate potential inhibitors of SARS-CoV-2 Mpro. We first tested our approach with three reported inhibitors of SARS-CoV-2 Mpro, and our computational results are in good agreement with the respective experimental data. Subsequently, we applied our approach on a database of ∼4600 natural compounds, as well as 8 available HIV-1 protease (PR) inhibitors and an aza-peptide epoxide. Molecular docking resulted in a short list of 35 natural compounds, which was subsequently refined using the FPL scheme. FPL simulations resulted in five potential inhibitors, including three natural compounds and two available HIV-1 PR inhibitors. Finally, FEP, the most accurate and precise method, was used to determine the absolute binding free energy of these five compounds. FEP results indicate that two natural compounds, cannabisin A and isoacteoside, and an HIV-1 PR inhibitor, darunavir, exhibit a large binding free energy to SARS-CoV-2 Mpro, which is larger than that of 13b, the most reliable SARS-CoV-2 Mpro inhibitor recently reported. The binding free energy largely arises from van der Waals interaction. We also found that Glu166 forms H-bonds to all of the inhibitors. Replacing Glu166 by an alanine residue leads to ∼2.0 kcal/mol decreases in the affinity of darunavir to SARS-CoV-2 Mpro. Our results could contribute to the development of potential drugs inhibiting SARS-CoV-2.

Aspartic peptidase of Phialophora verrucosa as target of HIV peptidase inhibitors: blockage of its enzymatic activity and interference with fungal growth and macrophage interaction

Phialophora verrucosa causes several fungal human diseases, mainly chromoblastomycosis, which is extremely difficult to treat. Several studies have shown that human immunodeficiency virus peptidase inhibitors (HIV-PIs) are attractive candidates for antifungal therapies. This work focused on studying the action of HIV-PIs on peptidase activity secreted by P. verrucosa and their effects on fungal proliferation and macrophage interaction. We detected a peptidase activity from P. verrucosa able to cleave albumin, sensitive to pepstatin A and HIV-PIs, especially lopinavir, ritonavir and amprenavir, showing for the first time that this fungus secretes aspartic-type peptidase. Furthermore, lopinavir, ritonavir and nelfinavir reduced the fungal growth, causing remarkable ultrastructural alterations. Lopinavir and ritonavir also affected the conidia-macrophage adhesion and macrophage killing. Interestingly, P. verrucosa had its growth inhibited by ritonavir combined with either itraconazole or ketoconazole. Collectively, our results support the antifungal action of HIV-PIs and their relevance as a possible alternative therapy for fungal infections.

In Silico Insights into the SARS CoV-2 Main Protease Suggest NADH Endogenous Defences in the Control of the Pandemic Coronavirus Infection

COVID-19 is a pandemic health emergency faced by the entire world. The clinical treatment of the severe acute respiratory syndrome (SARS) CoV-2 is currently based on the experimental administration of HIV antiviral drugs, such as lopinavir, ritonavir, and remdesivir (a nucleotide analogue used for Ebola infection). This work proposes a repurposing process using a database containing approximately 8000 known drugs in synergy structure- and ligand-based studies by means of the molecular docking and descriptor-based protocol. The proposed in silico findings identified new potential SARS CoV-2 main protease (M^PRO) inhibitors that fit in the catalytic binding site of SARS CoV-2 M^PRO. Several selected structures are NAD-like derivatives, suggesting a relevant role of these molecules in the modulation of SARS CoV-2 infection in conditions of cell chronic oxidative stress. Increased catabolism of NAD(H) during protein ribosylation in the DNA damage repair process may explain the greater susceptibility of the elderly population to the acute respiratory symptoms of COVID-19. The molecular modelling studies proposed herein agree with this hypothesis.

Piperidine scaffold as the novel P2-ligands in cyclopropyl-containing HIV-1 protease inhibitors: Structure-based design, synthesis, biological evaluation and docking study

A series of potent HIV-1 protease inhibitors, containing diverse piperidine analogues as the P2-ligands, 4-substituted phenylsulfonamides as the P2'-ligands and a hydrophobic cyclopropyl group as the P1'-ligand, were designed, synthesized and evaluated in this work. Among these twenty-four target compounds, many of them exhibited excellent activity against HIV-1 protease with half maximal inhibitory concentration (IC50) values below 20 nM. Particularly, compound 22a containing a (R)-piperidine-3-carboxamide as the P2-ligand and a 4-methoxylphenylsulfonamide as the P2'-ligand exhibited the most effective inhibitory activity with an IC50 value of 3.61 nM. More importantly, 22a exhibited activity with inhibition of 42% and 26% against wild-type and Darunavir (DRV)-resistant HIV-1 variants, respectively. Additionally, the molecular docking of 22a with HIV-1 protease provided insight into the ligand-binding properties, which was of great value for further study.

Pesticides, cosmetics, drugs: identical and opposite influences of various molecular features as measures of endpoints similarity and dissimilarity

The similarity is an important category in natural sciences. A measure of similarity for a group of various biochemical endpoints is suggested. The list of examined endpoints contains (1) toxicity of pesticides towards rainbow trout; (2) human skin sensitization; (3) mutagenicity; (4) toxicity of psychotropic drugs; and (5) anti HIV activity. Further applying and evolution of the suggested approach is discussed. In particular, the conception of the similarity (dissimilarity) of endpoints can play the role of a "useful bridge" between quantitative structure property/activity relationships (QSPRs/QSARs) and read-across technique.

Pyromellitic dianhydride crosslinked soluble cyclodextrin polymers: Synthesis, lopinavir release from sub-micron sized particles and anti-HIV-1 activity

We report the synthesis of water soluble cyclodextrin (CD) polymers prepared by crosslinking pyromellitic dianhydride (PMDA) with two CD derivatives (methyl-β-CD - MβCD and (2-hydroxy)propyl-β-CD - HPβCD) and their evaluation as functional sub-micron sized carriers in the development of antiretroviral drug delivery systems. Using the protease inhibitor lopinavir (LPV) as model drug, LPV loaded CD polymers (pHPβCD and pMβCD) were prepared and fully characterized. The physicochemical characterization and in vitro drug release confirmed the successful synthesis of pHPβCD and pMβCD, the formation of sub-micron sized particles and a 12-14 fold increase in LPV solubility. Cytotoxicity assays indicated that both pHPβCD and pMβCD were able to improve the safety profile of LPV while the viral infectivity assay revealed a concentration independent anti-HIV-1 effect for both pHPβCD and pMβCD with a maximum percentage inhibition (MPI) of 79 and 91% respectively. After LPV loading, the antiviral profile of pHPβCD was reversed to the sigmoidal dose-response profile of LPV, while pMβCD maintained its dose-independent profile followed by a LPV mediated increase in viral inhibition. Overall, both pHPβCD and pMβCD demonstrated anti-HIV-1 activity, while drug loaded pMβCD indicated its potential as functional sub-micron sized drug delivery polymers for achieving synergistic anti-HIV activity.

Optimizing the refinement of merohedrally twinned P61 HIV-1 protease-inhibitor cocrystal structures

Twinning is a crystal-growth anomaly in which protein monomers exist in different orientations but are related in a specific way, causing diffraction reflections to overlap. Twinning imposes additional symmetry on the data, often leading to the assignment of a higher symmetry space group. Specifically, in merohedral twinning, reflections from each monomer overlap and require a twin law to model unique structural data from overlapping reflections. Neglecting twinning in the crystallographic analysis of quasi-rotationally symmetric homo-oligomeric protein structures can mask the degree of structural non-identity between monomers. In particular, any deviations from perfect symmetry will be lost if higher than appropriate symmetry is applied during crystallographic analysis. Such cases warrant choosing between the highest symmetry space group possible or determining whether the monomers have distinguishable structural asymmetries and thus require a lower symmetry space group and a twin law. Using hexagonal cocrystals of HIV-1 protease, a C2-symmetric homodimer whose symmetry is broken by bound ligand, it is shown that both assigning a lower symmetry space group and applying a twin law during refinement are critical to achieving a structural model that more accurately fits the electron density. By re-analyzing three recently published HIV-1 protease structures, improvements in nearly every crystallographic metric are demonstrated. Most importantly, a procedure is demonstrated where the inhibitor can be reliably modeled in a single orientation. This protocol may be applicable to many other homo-oligomers in the PDB.

Characterization of Nine Compounds Isolated from the Acid Hydrolysate of Lonicera fulvotomentosa Hsu et S. C. Cheng and Evaluation of Their In Vitro Activity towards HIV Protease

In this study, we isolated nine compounds from the acid hydrolysate of the flower buds of Lonicera fulvotomentosa Hsu et S. C. Cheng and characterized their chemical structures using ¹H-NMR, ¹³C-NMR, and electron ionization mass spectroscopy (EI-MS). These compounds were identified as β-sitosterol (1), 5,5′-dibutoxy-2,2′-bifuran (2), nonacosane-10-ol (3), ethyl (3β)-3,23-dihydroxyolean-12-en-28-oate (4), oleanolic acid (5), ethyl caffeate (6), caffeic acid (7), isovanillin (8), and hederagenin (9), with 4 as a new triterpene compound. Inhibitory activity against human immunodeficiency virus (HIV) protease was also evaluated for the compounds, and only ethyl caffeate, caffeic acid, and isovanillin (6, 7, and 8) exhibited inhibitory effects, with IC₅₀ values of 1.0 μM, 1.5 μM, and 3.5 μM, respectively. Molecular docking with energy minimization and subsequent molecular dynamic (MD) simulation showed that ethyl caffeate and caffeic acid bound to the active site of HIV protease, while isovanillin drifted out from the active site and dissociated into bulk water during MD simulations, and most of the binding residues of HIV protease have been previously identified for HIV protease inhibitors. These results suggest that caffeic acid derivatives may possess inhibitory activities towards HIV protease other than previously reported inhibitory activities against HIV integrase, and thus ethyl caffeate and caffeic acid could be used as lead compounds in developing potential HIV protease inhibitors, and possibly even dual-function inhibitors against HIV.

Anti-HIV-1 protease activity of the crude extracts and isolated compounds from Auricularia polytricha

BACKGROUND

Acquired immunodeficiency syndrome (AIDS) is caused by the Human immunodeficiency virus type-1 (HIV-1). HIV-1 protease (HIV-1 PR) is an essential enzyme for the HIV replication, and therefore, it is an important target for antiretroviral drugs development, particularly from natural products. Auricularia polytricha (AP) is an edible mushroom with several important therapeutic properties. These properties will be investigated as HIV-1 PR inhibitors.

METHODS

The sequential hexane (APH), ethanol (APE) and water (APW) extracts from AP were screened for inhibitory activity against HIV-1 PR. The extract that consistently showed the strong HIV-1 PR inhibition was further investigated for its phytochemical constituents. The compounds were purified by column chromatography. The isolated compounds were structurally elucidated using 1D and 2D NMR, HRMS, FTIR, and GC/MS techniques. Each compound was screened against HIV-1 PR to determine its inhibitory activity and to provide an explanation for the activity found in the extract.

RESULTS

Hexane crude extract of AP (APH) exhibited significant inhibition on HIV-1 PR activity. Four major compounds isolated from APH fraction were identified to be two triacylglycerols, linoleic acid and ergosterol. Moreover, all four compounds showed significant inhibition of HIV-1 PR activity.

CONCLUSION

The findings from this study suggest that AP is a good source of fatty esters, fatty acids and ergosterol. These natural products exhibit anti-HIV-1 properties by blocking HIV-1 PR. These important biological results warrant further development of AP as an alternative antiretroviral drug.

Target-Specific Prediction of Ligand Affinity with Structure-Based Interaction Fingerprints

Discovery and optimization of small molecule inhibitors as therapeutic drugs have immensely benefited from rational structure-based drug design. With recent advances in high-resolution structure determination, computational power, and machine learning methodology, it is becoming more tractable to elucidate the structural basis of drug potency. However, the applicability of machine learning models to drug design is limited by the interpretability of the resulting models in terms of feature importance. Here, we take advantage of the large number of available inhibitor-bound HIV-1 protease structures and associated potencies to evaluate inhibitor diversity and machine learning models to predict ligand affinity. First, using a hierarchical clustering approach, we grouped HIV-1 protease inhibitors and identified distinct core structures. Explicit features including protein-ligand interactions were extracted from high-resolution cocrystal structures as 3D-based fingerprints. We found that a gradient boosting machine learning model with this explicit feature attribution can predict binding affinity with high accuracy. Finally, Shapley values were derived to explain local feature importance. We found specific van der Waals (vdW) interactions of key protein residues are pivotal for the predicted potency. Protein-specific and interpretable prediction models can guide the optimization of many small molecule drugs for improved potency.

Potent HIV-1 protease inhibitors incorporating squaramide-derived P2 ligands: Design, synthesis, and biological evaluation

We describe the design, synthesis, and biological evaluation of novel HIV-1 protease inhibitors containing a squaramide-derived scaffold as the P2 ligand in combination with a (R)-hydroxyethylamine sulfonamide isostere. Inhibitor 3h with an N-methyl-3-(R)-aminotetrahydrofuranyl squaramide P2-ligand displayed an HIV-1 protease inhibitory Ki value of 0.51 nM. An energy minimized model of 3h revealed the major molecular interactions between HIV-1 protease active site and the tetrahydrofuranyl squaramide scaffold that may be responsible for its potent activity.

NMR and MD studies combined to elucidate inhibitor and water interactions of HIV-1 protease and their modulations with resistance mutations

Over the last two decades, both the sensitivity of NMR and the time scale of molecular dynamics (MD) simulation have increased tremendously and have advanced the field of protein dynamics. HIV-1 protease has been extensively studied using these two methods, and has presented a framework for cross-evaluation of structural ensembles and internal dynamics by integrating the two methods. Here, we review studies from our laboratories over the last several years, to understand the mechanistic basis of protease drug-resistance mutations and inhibitor responses, using NMR and crystal structure-based parallel MD simulations. Our studies demonstrate that NMR relaxation experiments, together with crystal structures and MD simulations, significantly contributed to the current understanding of structural/dynamic changes due to HIV-1 protease drug resistance mutations.

Active learning strategies with COMBINE analysis: new tricks for an old dog

The COMBINE method was designed to study congeneric series of compounds including structural information of ligand-protein complexes. Although very successful, the method has not received the same level of attention than other alternatives to study Quantitative Structure Active Relationships (QSAR) mainly because lack of ways to measure the uncertainty of the predictions and the need for large datasets. Active learning, a semi-supervised learning approach that makes use of uncertainty to enhance models' performance while reducing the size of the training sets, has been used in this work to address both problems. We propose two estimators of uncertainty: the pool of regressors and the distance to the training set. The performance of the methods has been evaluated by testing the resulting active learning workflows in 3 diverse datasets: HIV-1 protease inhibitors, Taxol-derivatives and BRD4 inhibitors. The proposed strategies were successful in 80% of the cases for the taxol-derivatives and BRD4 inhibitors, while outperformed random selection in the case of the HIV-1 protease inhibitors time-split. Our results suggest that AL-COMBINE might be an effective way of producing consistently superior QSAR models with a limited number of samples.

Finding the structural requirements of diverse HIV-1 protease inhibitors using multiple QSAR modelling for lead identification

Multiple Quantitative Structure-Activity Relationship (QSAR) analysis is widely used in drug discovery for lead identification. Human Immunodeficiency Virus (HIV) protease is one of the key targets for the treatment of Acquired Immunodeficiency Syndrome (AIDS). One of the major challenges for the design of HIV-1 protease inhibitors (HIV PRIs) is to increase the inhibitory activities against the enzyme to a level where the problem associated to drug resistance may be considerably delayed. Herein, chemometric analyses were performed with 346 structurally diverse HIV PRIs with experimental bioactivities against a sub-type B mutant to develop highly predictable QSAR models and also to identify the effective structural determinants for higher affinity against HIV PR. The QSAR models were developed using OCHEM-based machine learning tools (ASNN, FSMLR, KNN, RF, MANN and XGBoost), with descriptors calculated by eight different software packages. Simultaneously, a Monte Carlo optimization-based QSAR modelling was performed using SMILES and graph-based descriptors to understand fragment and topochemical contributions. To validate the actual predictability of all these models, an additional set of 104 compounds (also with known experimental activities) with slightly different chemical space were employed. This ligand-based study serves as a crucial benchmark for further development of the HIV protease inhibitors with improved activities.

Sub-picomolar Inhibition of HIV-1 Protease with a Boronic Acid

Boronic acids have been typecast as moieties for covalent complexation and are employed only rarely as agents for non-covalent recognition. By exploiting the profuse ability of a boronic acid group to form hydrogen bonds, we have developed an inhibitor of HIV-1 protease with extraordinary affinity. Specifically, we find that replacing an aniline moiety in darunavir with a phenylboronic acid leads to 20-fold greater affinity for the protease. X-ray crystallography demonstrates that the boronic acid group participates in three hydrogen bonds, more than the amino group of darunavir or any other analog. Importantly, the boronic acid maintains its hydrogen bonds and its affinity for the drug-resistant D30N variant of HIV-1 protease. The BOH···OC hydrogen bonds between the boronic acid hydroxy group and Asp30 (or Asn30) of the protease are short ( rO···O = 2.2 Å), and density functional theory analysis reveals a high degree of covalency. These data highlight the utility of boronic acids as versatile functional groups in the design of small-molecule ligands.

Analysis of drug resistance in HIV protease

BACKGROUND

Drug resistance in HIV is the major problem limiting effective antiviral therapy. Computational techniques for predicting drug resistance profiles from genomic data can accelerate the appropriate choice of therapy. These techniques can also be used to select protease mutants for experimental studies of resistance and thereby assist in the development of next-generation therapies.

RESULTS

The machine learning produced highly accurate and robust classification of HIV protease resistance. Genotype data were mapped to the enzyme structure and encoded using Delaunay triangulation. Generative machine learning models trained on one inhibitor could classify resistance from other inhibitors with varying levels of accuracy. Generally, the accuracy was best when the inhibitors were chemically similar.

CONCLUSIONS

Restricted Boltzmann Machines are an effective machine learning tool for classification of genomic and structural data. They can also be used to compare resistance profiles of different protease inhibitors.

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

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

Multi-spectroscopic and molecular docking studies on the interaction of darunavir, a HIV protease inhibitor with calf thymus DNA

Molecular interaction of darunavir (DRV), a HIV protease inhibitor with calf thymus deoxyribonucleic acid (ct-DNA) was studied in physiological buffer (pH7.4) by multi-spectroscopic approaches hand in hand with viscosity measurements and molecular docking technique. The UV absorption and fluorescence results together revealed the formation of a DRV-ct-DNA complex having binding affinities of the order of 10³M^-1, which was more in keeping with the groove binding. The results that DRV bound to ct-DNA via groove binding mode was further evidenced by KI quenching studies, viscosity measurements, competitive binding investigations with EB and Rhodamine B and CD spectral analysis. The effect of ionic strength indicated the negligible involvement of electrostatic interaction between DRV and ct-DNA. The thermodynamic parameters regarding the binding interaction of DRV with ct-DNA in terms of enthalpy change (ΔH⁰) and entropy change (ΔS⁰) were -63.19kJ mol^-1 and -141.92J mol^-1K^-1, indicating that hydrogen bonds and van der Waals forces played a predominant role in the binding process. Furthermore, molecular simulation studies suggested that DRV molecule was prone to bind in the A-T rich region of the minor groove of DNA.

Probing Structural Changes among Analogous Inhibitor-Bound Forms of HIV-1 Protease and a Drug-Resistant Mutant in Solution by Nuclear Magnetic Resonance

In the era of state-of-the-art inhibitor design and high-resolution structural studies, detection of significant but small protein structural differences in the inhibitor-bound forms is critical to further developing the inhibitor. Here, we probed differences in HIV-1 protease (PR) conformation among darunavir and four analogous inhibitor-bound forms and compared them with a drug-resistant mutant using nuclear magnetic resonance chemical shifts. Changes in amide chemical shifts of wild-type (WT) PR among these inhibitor-bound forms, ΔCSP, were subtle but detectable and extended >10 Å from the inhibitor-binding site, asymmetrically between the two subunits of PR. Molecular dynamics simulations revealed differential local hydrogen bonding as the molecular basis of this remote asymmetric change. Inhibitor-bound forms of the drug-resistant mutant also showed a similar long-range ΔCSP pattern. Differences in ΔCSP values of the WT and the mutant (ΔΔCSPs) were observed at the inhibitor-binding site and in the surrounding region. Comparing chemical shift changes among highly analogous inhibitors and ΔΔCSPs effectively eliminated local environmental effects stemming from different chemical groups and enabled exploitation of these sensitive parameters to detect subtle protein conformational changes and to elucidate asymmetric and remote conformational effects upon inhibitor interaction.

Multi-spectroscopic and molecular modeling approaches to elucidate the binding interaction between bovine serum albumin and darunavir, a HIV protease inhibitor

Darunavir (DRV), a second-generation HIV protease inhibitor, is widely used across the world as an important component of HIV therapy. The interaction of DRV with bovine serum albumin (BSA), a major carrier protein, has been studied under simulated physiological conditions (pH7.4) by multi-spectroscopic techniques in combination with molecular modeling. Fluorescence data revealed that the intrinsic fluorescence of BSA was quenched by DRV in terms of a static quenching procedure due to the formation of the DRV-BSA complex. The results indicated the presence of single weak affinity binding site (~10³M^-1, 310K) on protein. The thermodynamic parameters, namely enthalpy change (ΔH⁰), entropy change (ΔS⁰) and Gibbs free energy change (ΔG⁰) were calculated, which signified that the binding reaction was spontaneous, the main binding forces were hydrogen bonding and van der Waals forces. Importantly, competitive binding experiments with three site probes, phenylbutazone (in sub-domain IIA, site I), ibuprofen (in sub-domain IIIA, site II) and artemether (in the interface between sub-domain IIA and IIB, site II'), suggested that DRV was preferentially bound to the hydrophobic cavity in site II' of BSA, and this finding was validated by the docking results. Additionally, synchronous fluorescence, three-dimensional fluorescence and Resonance Rayleigh Scattering (RRS) spectroscopy gave qualitative information on the conformational changes of BSA upon adding DRV, while quantitative data were obtained with Fourier transform infrared spectroscopy (FT-IR).

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

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

I36T↑T mutation in South African subtype C (C-SA) HIV-1 protease significantly alters protease-drug interactions

The efficacy of HIV-1 protease (PR) inhibition therapies is often compromised by the emergence of mutations in the PR molecule that reduces the binding affinity of inhibitors while maintaining viable catalytic activity and affinity for natural substrates. In the present study, we used a recombinant HIV-1 C-SA PR and a recently reported variant for inhibition (Ki, IC50) and thermodynamic studies against nine clinically used inhibitors. This is the first time that binding free energies for C-SA PR and the mutant are reported. This variant PR harbours a mutation and insertion (I36T↑T) at position 36 of the C-SA HIV-1 PR, and did not show a significant difference in the catalytic effect of the HIV-1 PR. However, the nine clinically approved HIV PR drugs used in this study demonstrated weaker inhibition and lower binding affinities toward the variant when compared to the wild type HIV-1 PR. All the protease inhibitors (PIs), except Amprenavir and Ritonavir exhibited a significant decrease in binding affinity (p<0.0001). Darunavir and Nelfinavir exhibited the weakest binding affinity, 155- and 95-fold decreases respectively, toward the variant. Vitality values for the variant PR, against the seven selected PIs, confirm the impact of the mutation and insertion on the South African HIV-1 subtype C PR. This information has important clinical implications for thousands of patients in Sub-Saharan Africa.

Medicinal attributes of 1,2,3-triazoles: Current developments

1,2,3-Triazoles are important five-membered heterocyclic scaffold due to their extensive biological activities. This framework can be readily obtained in good to excellent yields on the multigram scale through click chemistry via reaction of aryl/alkyl halides, alkynes and NaN₃ under ambient conditions. It has been an emerging area of interest for many researchers throughout the globe owing to its immense pharmacological scope. The present work aims to summarize the current approaches adopted for the synthesis of the 1,2,3-triazole and medicinal significance of these architectures as a lead structure for the discovery of drug molecules such as COX-1/COX-2 inhibitors (celecoxib, pyrazofurin), HIV protease inhibitors, CB1 cannabinoid receptor antagonist and much more which are in the pipeline of clinical trials. The emphasis has been given on the major advancements in the medicinal prospectus of this pharmacophore for the period during 2008-2016.

Elucidating the druggable interface of protein-protein interactions using fragment docking and coevolutionary analysis

Protein-protein interactions play a central role in cellular function. Improving the understanding of complex formation has many practical applications, including the rational design of new therapeutic agents and the mechanisms governing signal transduction networks. The generally large, flat, and relatively featureless binding sites of protein complexes pose many challenges for drug design. Fragment docking and direct coupling analysis are used in an integrated computational method to estimate druggable protein-protein interfaces. (i) This method explores the binding of fragment-sized molecular probes on the protein surface using a molecular docking-based screen. (ii) The energetically favorable binding sites of the probes, called hot spots, are spatially clustered to map out candidate binding sites on the protein surface. (iii) A coevolution-based interface interaction score is used to discriminate between different candidate binding sites, yielding potential interfacial targets for therapeutic drug design. This approach is validated for important, well-studied disease-related proteins with known pharmaceutical targets, and also identifies targets that have yet to be studied. Moreover, therapeutic agents are proposed by chemically connecting the fragments that are strongly bound to the hot spots.

Mass spectrometry captures off-target drug binding and provides mechanistic insights into the human metalloprotease ZMPSTE24

Off-target binding of hydrophobic drugs can lead to unwanted side effects, either through specific or non-specific binding to unintended membrane protein targets. However, distinguishing the binding of drugs to membrane proteins from that of detergents, lipids and cofactors is challenging. Here, we use high-resolution mass spectrometry to study the effects of HIV protease inhibitors on the human zinc metalloprotease ZMPSTE24. This intramembrane protease plays a major role in converting prelamin A to mature lamin A. We monitored the proteolysis of farnesylated prelamin A peptide by ZMPSTE24 and unexpectedly found retention of the C-terminal peptide product with the enzyme. We also resolved binding of zinc, lipids and HIV protease inhibitors and showed that drug binding blocked prelamin A peptide cleavage and conferred stability to ZMPSTE24. Our results not only have relevance for the progeria-like side effects of certain HIV protease inhibitor drugs, but also highlight new approaches for documenting off-target drug binding.

Effect of allosteric molecules on structure and drug affinity of HIV-1 protease by molecular dynamics simulations

Recent experiments show that small molecules can bind onto the allosteric sites of HIV-1 protease (PR), which provides a starting point for developing allosteric inhibitors. However, the knowledge of the effect of such binding on the structural dynamics and binding free energy of the active site inhibitor and PR is still lacking. Here, we report 200ns long molecular dynamics simulation results to gain insight into the influences of two allosteric molecules (1H-indole-6-carboxylic acid, 1F1 and 2-methylcyclohexano, 4D9). The simulations demonstrate that both allosteric molecules change the PR conformation and stabilize the structures of PR and the inhibitor; the residues of the flaps are sensitive to the allosteric molecules and the flexibility of the residues is pronouncedly suppressed; the additions of the small molecules to the allosteric sites strengthen the binding affinities of 3TL-PR by about 12-15kal/mol in the binding free energy, which mainly arises from electrostatic term. Interestingly, it is found that the action mechanisms of 1F1 and 4D9 are different, the former behaviors like a doorman that keeps the inhibitor from escape and makes the flaps (door) partially open; the latter is like a wedge that expands the allosteric space and meanwhile closes the flaps. Our data provide a theoretical support for designing the allosteric inhibitor.

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

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

Design, synthesis, biological evaluation and X-ray structural studies of HIV-1 protease inhibitors containing substituted fused-tetrahydropyranyl tetrahydrofuran as P2-ligands

Design, synthesis, biological and X-ray crystallographic studies of a series of potent HIV-1 protease inhibitors are described. Various polar functionalities have been incorporated on the tetrahydropyranyl-tetrahydrofuran-derived P2 ligand to interact with the backbone atoms in the S2-subsite. The majority of the inhibitors showed very potent enzyme inhibitory and antiviral activity. Two high-resolution X-ray structures of 30b- and 30j-bound HIV-1 protease provide insight into ligand-binding site interactions. In particular, the polar functionalities on the P2-ligand appear to form unique hydrogen bonds with Gly48 amide NH and amide carbonyl groups in the flap region.

HIV-1 Protease Dimerization Dynamics Reveals a Transient Druggable Binding Pocket at the Interface

The binding mechanism of HIV-1 protease monomers leading to the catalytically competent dimeric enzyme has been investigated by means of state-of-the-art atomistic simulations. The emerging picture allows a deeper understanding of experimental observations and reveals that water molecules trapped at the interface have an important role in slowing down the kinetics of the association process. Unexpectedly, a cryptic binding pocket is identified at the interface of the complex, corresponding to a partially bound dimer that lacks enzymatic function. The pocket has a transient nature with a lifetime longer than 1 μs, and it displays very favorable druggability features. Docking as well as MM-GBSA free-energy calculations further support the possibility to target the new binding site by means of inhibitors able to prevent the complete dimerization by capturing the inactive conformation. This discovery could open the way to the rational design of a new class of anti-HIV drugs.

A simple and efficient dispersion correction to the Hartree-Fock theory (2): Incorporation of a geometrical correction for the basis set superposition error

One of the most challenging problems in computer-aided drug discovery is the accurate prediction of the binding energy between a ligand and a protein. For accurate estimation of net binding energy ΔEbind in the framework of the Hartree-Fock (HF) theory, it is necessary to estimate two additional energy terms; the dispersion interaction energy (Edisp) and the basis set superposition error (BSSE). We previously reported a simple and efficient dispersion correction, Edisp, to the Hartree-Fock theory (HF-Dtq). In the present study, an approximation procedure for estimating BSSE proposed by Kruse and Grimme, a geometrical counterpoise correction (gCP), was incorporated into HF-Dtq (HF-Dtq-gCP). The relative weights of the Edisp (Dtq) and BSSE (gCP) terms were determined to reproduce ΔEbind calculated with CCSD(T)/CBS or /aug-cc-pVTZ (HF-Dtq-gCP (scaled)). The performance of HF-Dtq-gCP (scaled) was compared with that of B3LYP-D3(BJ)-bCP (dispersion corrected B3LYP with the Boys and Bernadi counterpoise correction (bCP)), by taking ΔEbind (CCSD(T)-bCP) of small non-covalent complexes as 'a golden standard'. As a critical test, HF-Dtq-gCP (scaled)/6-31G(d) and B3LYP-D3(BJ)-bCP/6-31G(d) were applied to the complex model for HIV-1 protease and its potent inhibitor, KNI-10033. The present results demonstrate that HF-Dtq-gCP (scaled) is a useful and powerful remedy for accurately and promptly predicting ΔEbind between a ligand and a protein, albeit it is a simple correction procedure.

Molecular mechanisms and design principles for promiscuous inhibitors to avoid drug resistance: lessons learned from HIV-1 protease inhibition

Molecular recognition is central to biology and ranges from highly selective to broadly promiscuous. The ability to modulate specificity at will is particularly important for drug development, and discovery of mechanisms contributing to binding specificity is crucial for our basic understanding of biology and for applications in health care. In this study, we used computational molecular design to create a large dataset of diverse small molecules with a range of binding specificities. We then performed structural, energetic, and statistical analysis on the dataset to study molecular mechanisms of achieving specificity goals. The work was done in the context of HIV‐1 protease inhibition and the molecular designs targeted a panel of wild‐type and drug‐resistant mutant HIV‐1 protease structures. The analysis focused on mechanisms for promiscuous binding to bind robustly even to resistance mutants. Broadly binding inhibitors tended to be smaller in size, more flexible in chemical structure, and more hydrophobic in nature compared to highly selective ones. Furthermore, structural and energetic analyses illustrated mechanisms by which flexible inhibitors achieved binding; we found ligand conformational adaptation near mutation sites and structural plasticity in targets through torsional flips of asymmetric functional groups to form alternative, compensatory packing interactions or hydrogen bonds. As no inhibitor bound to all variants, we designed small cocktails of inhibitors to do so and discovered that they often jointly covered the target set through mechanistic complementarity. Furthermore, using structural plasticity observed in experiments, and potentially in simulations, is suggested to be a viable means of designing adaptive inhibitors that are promiscuous binders. Proteins 2015; 83:351–372. © 2014 Wiley Periodicals, Inc.

Solving molecular docking problems with multi-objective metaheuristics

Molecular docking is a hard optimization problem that has been tackled in the past with metaheuristics, demonstrating new and challenging results when looking for one objective: the minimum binding energy. However, only a few papers can be found in the literature that deal with this problem by means of a multi-objective approach, and no experimental comparisons have been made in order to clarify which of them has the best overall performance. In this paper, we use and compare, for the first time, a set of representative multi-objective optimization algorithms applied to solve complex molecular docking problems. The approach followed is focused on optimizing the intermolecular and intramolecular energies as two main objectives to minimize. Specifically, these algorithms are: two variants of the non-dominated sorting genetic algorithm II (NSGA-II), speed modulation multi-objective particle swarm optimization (SMPSO), third evolution step of generalized differential evolution (GDE3), multi-objective evolutionary algorithm based on decomposition (MOEA/D) and S-metric evolutionary multi-objective optimization (SMS-EMOA). We assess the performance of the algorithms by applying quality indicators intended to measure convergence and the diversity of the generated Pareto front approximations. We carry out a comparison with another reference mono-objective algorithm in the problem domain (Lamarckian genetic algorithm (LGA) provided by the AutoDock tool). Furthermore, the ligand binding site and molecular interactions of computed solutions are analyzed, showing promising results for the multi-objective approaches. In addition, a case study of application for aeroplysinin-1 is performed, showing the effectiveness of our multi-objective approach in drug discovery.

Organic carbamates in drug design and medicinal chemistry

The carbamate group is a key structural motif in many approved drugs and prodrugs. There is an increasing use of carbamates in medicinal chemistry and many derivatives are specifically designed to make drug-target interactions through their carbamate moiety. In this Perspective, we present properties and stabilities of carbamates, reagents and chemical methodologies for the synthesis of carbamates, and recent applications of carbamates in drug design and medicinal chemistry.