Deciphering the Inhibition Mechanism of under Trial Hsp90 Inhibitors and Their Analogues: A Comparative Molecular Dynamics Simulation

Characterization of Plant-Derived Natural Inhibitors of Dipeptidyl Peptidase-4 as Potential Antidiabetic Agents: A Computational Study

Diabetes, characterized by elevated blood sugar levels, poses significant health and economic risks, correlating with complications like cardiovascular disease, kidney failure, and blindness. Dipeptidyl peptidase-4 (DPP-4), also referred to as T-cell activation antigen CD26 (EC 3.4.14.5.), plays a crucial role in glucose metabolism and immune function. Inhibiting DPP-4 was anticipated as a potential new therapy for diabetes. Therefore, identification of plant-based natural inhibitors of DPP-4 would help in eradicating diabetes worldwide. Here, for the identification of the potential natural inhibitors of DPP-4, we developed a phytochemicals library consisting of over 6000 phytochemicals detected in 81 medicinal plants that exhibited anti-diabetic potency. The library has been docked against the target proteins, where isorhamnetin, Benzyl 5-Amino-5-deoxy-2,3-O-isopropyl-alpha-D-mannofuranoside (DTXSID90724586), and 5-Oxo-7-[4-(trifluoromethyl) phenyl]-4H,6H,7H-[1,2]thiazolo[4,5-b]pyridine 3-carboxylic acid (CHEMBL3446108) showed binding affinities of -8.5, -8.3, and -8.3 kcal/mol, respectively. These compounds exhibiting strong interactions with DPP-4 active sites (Glu205, Glu206, Tyr547, Trp629, Ser630, Tyr662, His740) were identified. ADME/T and bioactivity predictions affirmed their pharmacological safety. Density functional theory calculations assessed stability and reactivity, while molecular dynamics simulations demonstrated persistent stability. Analyzing parameters like RMSD, RG, RMSF, SASA, H-bonds, MM-PBSA, and FEL confirmed stable protein-ligand compound formation. Principal component analysis provided structural variation insights. Our findings suggest that those compounds might be possible candidates for developing novel inhibitors targeting DPP-4 for treating diabetes.

Identification of inhibitors for Agr quorum sensing system of Staphylococcus aureus by machine learning, pharmacophore modeling, and molecular dynamics approaches

CONTEXT

Staphylococcus aureus is a highly pathogenic organism that is the most common cause of postoperative complications as well as severe infections like bacteremia and infective endocarditis. By mediating the formation of biofilms and the expression of virulent genes, the quorum sensing (QS) mechanism is a major contributor to the development of these diseases. By hindering its QS network, an innovative approach to avoiding this bacterial infection is taken. Targeting the AgrA of the Agr system serves as beneficial in holding the top position in the QS system cascade.

METHODS

Using known AgrA inhibitors, the machine learning algorithms (artificial neural network, naïve Bayes, random forest, and support vector machine) and pharmacophore model were developed. The potential lead compounds were screened against the Zinc and COCONUT databases using the best pharmacophore hypothesis. The hits were then subjected second screening process using the best machine learning model. The predicted active compounds were then reranked based on the docking score. The stability of AgrA-lead compounds was studied using molecular dynamics approaches, and an ADME profile was also carried out. Five lead compounds, namely, CNP02386963,4,5-trihydroxy-2-[({7,13,14-trihydroxy-3,10-dioxo-2,9-dioxatetracyclo[6.6.2.04,16.011,15]hexadeca-1(14),4,6,8(16),11(15),12-hexaen-6-yl}oxy)methyl]benzoic acid, CNP0129274 4-(dimethylamino)-1,5,6,10,12,12a-hexahydroxy-6-methyl-3,11-dioxo-3,4,4a,5,5a,6,11,12a-octahydrotetracene-2-carboxamide, CNP0242717 3-Hydroxyasebotin, CNP0361624 3,4,5-trihydroxy-6-[(2,4,5,6,7-pentahydroxy-1-oxooctan-3-yl)oxy]oxane-2-carboxylic acid, and CNP0285058 2-{[4,5-dihydroxy-6-(hydroxymethyl)-3-[(3,4,5-trihydroxy-6-methyloxan-2-yl)oxy]oxan-2-yl]oxy}-2-(4-hydroxyphenyl)acetonitrile were obtained using the two-step virtual screening process. The molecular dynamics study revealed that the CNP0238696 was found to be stable in the binding pocket of AgrA. ADME profiles show that this compound has two Lipinski violations and low bioavailability. Further studies should be performed to assess the anti-biofilm activity of the lead compound in vitro.

Binding Mechanism of Inhibitors to Heat Shock Protein 90 Investigated by Multiple Independent Molecular Dynamics Simulations and Prediction of Binding Free Energy

The heat shock protein (HSP90) has been an import target of drug design in the treatment of human disease. An exploration of the conformational changes in HSP90 can provide useful information for the development of efficient inhibitors targeting HSP90. In this work, multiple independent all-atom molecular dynamics (AAMD) simulations followed by calculations of the molecular mechanics generalized Born surface area (MM-GBSA) were performed to explore the binding mechanism of three inhibitors (W8Y, W8V, and W8S) to HSP90. The dynamics analyses verified that the presence of inhibitors impacts the structural flexibility, correlated movements, and dynamics behavior of HSP90. The results of the MM-GBSA calculations suggest that the selection of GB models and empirical parameters has important influences on the predicted results and verify that van der Waals interactions are the main forces that determine inhibitor-HSP90 binding. The contributions of separate residues to the inhibitor-HSP90 binding process indicate that hydrogen-bonding interactions (HBIs) and hydrophobic interactions play important roles in HSP90-inhibitor identifications. Moreover, residues L34, N37, D40, A41, D79, I82, G83, M84, F124, and T171 are recognized as hot spots of inhibitor-HSP90 binding and provide significant target sites of for the design of drugs related to HSP90. This study aims to contribute to the development of efficient inhibitors that target HSP90 by providing an energy-based and theoretical foundation.

Inhibition of albendazole and 2-(2-aminophenyl)-1H-benzimidazole against tyrosinase: mechanism, structure-activity relationship, and anti-browning effect

BACKGROUND

Tyrosinase is the key enzyme involved in enzymatic browning of plant-derived foods. Inhibition of tyrosinase activity contributes to the control of food browning. Due to safety regulations or other issues, most identified tyrosinase inhibitors are not suitable for practical use. Therefore, it is necessary to search for novel tyrosinase inhibitors. In this study, the anti-tyrosinase activity and mechanism of albendazole and 2-(2-aminophenyl)-1H-benzimidazole (2-2-A-1HB) were investigated through ultraviolet-visible absorption spectroscopy, fluorescence spectra, molecular docking, and molecular dynamic (MD) simulation. The anti-browning effect of albendazole on fresh-cut apples was then elucidated.

RESULTS

Albendazole and 2-2-A-1HB were both efficient tyrosinase inhibitors with IC₅₀ of 51 ± 1.5 and 128 ± 1.3 μmol L^-1 , respectively. Albendazole suppressed tyrosinase non-competitively and formed tyrosinase-albendazole complex statically. Hydrogen bond and hydrophobic interaction were major driving forces in stabilizing the tyrosinase-albendazole complex. While 2-2-A-1HB inhibited the enzyme competitively and quenched its intrinsic fluorescence through a static mechanism, it generated strong binding affinity with tyrosinase through hydrophobic interaction. MD simulations further validated that albendazole/2-2-A-1HB could form stable complexes with tyrosinase and loosened its basic framework structure, leading to a change in secondary structure and conformation. In addition, albendazole could delay the browning of fresh-cut apples by inhibiting the activity of polyphenol oxidase, peroxidase and phenylalanine ammonia-lyase, and reducing the oxidation of phenolic compounds.

CONCLUSION

This research might provide a deep view of tyrosinase inhibition by benzimidazole derivatives and a theoretical basis for developing albendazole as a potential fresh-keeping agent. © 2023 Society of Chemical Industry.

Integrated computational approach towards identification of HSPG and ACE2 mimicking moieties for SARS-CoV-2 inhibition

A key step to inhibit severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is to prevent the entry of the virus into the host cells. The receptor-binding domains (RBDs) of spike proteins of SARS-CoV and other human coronaviruses utilize heparan sulfate proteoglycans (HSPGs) as the primary receptors for their accumulation on the cell surface and then scan for binding to the main entry receptor angiotensin-converting enzyme 2 (ACE2). SARS-CoV and SARS-CoV-2 share structurally similar RBDs and therefore, it is possible that SARS-COV-2 primarily binds to HSPGs followed by binding to the ACE2 receptors. A promising strategy to inhibit virus infection is to circulate exogenous bioactive moieties structurally mimicking cellular HSPG and ACE2 which act as decoy receptors binding to SARS-CoV-2 and competitively inhibit virus entry to the host cells mediated by cellular-bound HSPG and ACE2. Using a molecular docking tool, we identified carboxymethyl benzyl amide sulfonate (CMBS) and polyanetholesulfonic acid (PAS) as the suitable HSPG mimicking ligands, and Paenibacillus sp. B38-derived carboxypeptidase (B38-CAP) and Bacillus subtilis-derived carboxypeptidase (BS-CAP) as the potential ACE2-like enzymes having a strong binding affinity to the spike proteins as that of cellular HSPG and ACE2. Further, the binding stability and compactness of these moieties with SARS-CoV-2 were analyzed through molecular dynamics (MD) simulations, and the results indicated that these moieties form well-stable complexes with the RBD of spike proteins. The identified moieties could be conjugated to the surfaces of non-toxic nanoparticles to provide multiple interactions to efficiently shield SARS-CoV-2, and inhibit viral entry to the host cells.

Mebendazole's Conformational Space and Its Predicted Binding to Human Heat-Shock Protein 90

Recent experimental evidence suggests that mebendazole, a popular antiparasitic drug, binds to heat shock protein 90 (Hsp90) and inhibits acute myeloid leukemia cell growth. In this study we use quantum mechanics (QM), molecular similarity, and molecular dynamics (MD) calculations to predict possible binding poses of mebendazole to the adenosine triphosphate (ATP) binding site of Hsp90. Extensive conformational searches and minimization of the five mebendazole tautomers using the MP2/aug-cc-pVTZ theory level resulted in 152 minima. Mebendazole-Hsp90 complex models were subsequently created using the QM optimized conformations and protein coordinates obtained from experimental crystal structures that were chosen through similarity calculations. Nine different poses were identified from a total of 600 ns of explicit solvent, all-atom MD simulations using two different force fields. All simulations support the hypothesis that mebendazole is able to bind to the ATP binding site of Hsp90.

Heat Shock Protein 90 (HSP90) Inhibitors as Anticancer Medicines: A Review on the Computer-Aided Drug Discovery Approaches over the Past Five Years

Cancer is a disease caused by the uncontrolled, abnormal growth of cells in different anatomic sites. In 2018, it was predicted that the worldwide cancer burden would rise to 18.1 million new cases and 9.6 million deaths. Anticancer compounds, often known as chemotherapeutic medicines, have gained much interest in recent cancer research. These medicines work through various biological processes in targeting cells at various stages of the cell's life cycle. One of the most significant roadblocks to developing anticancer drugs is that traditional chemotherapy affects normal cells and cancer cells, resulting in substantial side effects. Recently, advancements in new drug development methodologies and the prediction of the targeted interatomic and intermolecular ligand interaction sites have been beneficial. This has prompted further research into developing and discovering novel chemical species as preferred therapeutic compounds against specific cancer types. Identifying new drug molecules with high selectivity and specificity for cancer is a prerequisite in the treatment and management of the disease. The overexpression of HSP90 occurs in patients with cancer, and the HSP90 triggers unstable harmful kinase functions, which enhance carcinogenesis. Therefore, the development of potent HSP90 inhibitors with high selectivity and specificity becomes very imperative. The activities of HSP90 as chaperones and cochaperones are complex due to the conformational dynamism, and this could be one of the reasons why no HSP90 drugs have made it beyond the clinical trials. Nevertheless, HSP90 modulations appear to be preferred due to the competitive inhibition of the targeted N-terminal adenosine triphosphate pocket. This study, therefore, presents an overview of the various computational models implored in the development of HSP90 inhibitors as anticancer medicines. We hereby suggest an extensive investigation of advanced computational modelling of the three different domains of HSP90 for potent, effective inhibitor design with minimal off-target effects.

Combined machine learning and pharmacophore based virtual screening approaches to screen for antibiofilm inhibitors targeting LasR of Pseudomonas aeruginosa

Pseudomonas aeruginosa, a virulent pathogen affects patients with cystic fibrosis and nosocomial infections. Quorum sensing (QS) mechanism plays a crucial role in causing these ailments by mediating biofilm formation and expressing virulent genes. A novel approach to circumvent this bacterial infection is by hindering its QS network. Targeting LasR of las system serves beneficial as it holds the top position in QS system cascade. Here, we have integrated machine learning, pharmacophore based virtual screening, molecular docking and simulation studies to look for new leads as inhibitors for LasR. Support vector machine (SVM) learning algorithm was used to generate QSAR models from 66 antagonist dataset. The top three models resulted in correlation coefficient (R²) values of 0.67, 0.86, and 0.91, respectively. The correlation coefficient (R²_test) values on external test set were found to be 0.62, 0.57, and 0.55, respectively. A four-point pharmacophore model was developed. The pharmacophore hypothesis AAAD_1 was used to screen for potential leads against MolPort database in ZincPharmer. The leads which showed predicted pIC50 value of >8.00 by SVM models were subjected to docking analysis that reranked the compounds based on docking scores. Four top leads namely ZINC3851967 N-[3,5-bis(trifluoromethyl)phenyl]-5-tert-butyl-6-chloropyrazine-2-carboxamide, ZINC4024175 4-Amino-1-[(2R,3S,4S,5S)-3,4-dihydroxy-5-(hydroxymethyl)oxolan-2-yl]-2-oxopyrimidine-5-carbonitrile, ZINC2125703 N-[(5-Methoxy-4,7-dimethyl-2-oxo-2H-chromen-3-yl)acetyl]-beta-alanine, and ZINC3851966 N-[3,5-Bis(trifluoromethyl)phenyl]5-tert-butylpyrazine-2-carboxamide were selected. These compounds were checked for its stability by performing a molecular dynamics simulation for a period of 100 ns. The ADME properties of the leads were also determined. Hence, the compounds identified in this study can be used as possible leads for developing a novel inhibitor for LasR.Communicated by Ramaswamy H. Sarma.

Epitope-Based Potential Vaccine Candidate for Humoral and Cell-Mediated Immunity to Combat Severe Acute Respiratory Syndrome Coronavirus 2 Pandemic

The emergence of severe acute respiratory syndrome from novel Coronavirus (SARS-CoV-2) has put an immense pressure worldwide where vaccination is believed to be an efficient way for developing hard immunity. Herein, we employ immunoinformatic tools to identify B-cell, T-cell epitopes associated with the spike protein of SARS-CoV-2, which is important for genome release. The results showed that the highly immunogenic epitopes located at the stalk part are mostly conserved compared to the receptor binding domain (RDB). Further, two vaccine candidates were computationally modeled from the linear B-cell, T-cell epitopes. Molecular docking reveals the crucial interactions of the vaccines with immune-receptors, and their stability is assessed by MD simulation studies. The chimeric vaccines showed remarkable binding affinity toward the immune cell receptors computed by the MM/PBSA method. van der Waals and electrostatic interactions are found to be the dominant factors for the stability of the complexes. The molecular-level interaction obtained from this study may provide deeper insight into the process of vaccine development against the pandemic of COVID-19.