Computational multi-target approach to target essential enzymes of Leishmania donovani using comparative molecular dynamic simulations and MMPBSA analysis

Uncovering PPAR-γ agonists: An integrated computational approach driven by machine learning

Peroxisome proliferator-activated receptor gamma (PPAR-γ) serves as a nuclear receptor with a pivotal function in governing diverse facets of metabolic processes. In diabetes, the prime physiological role of PPAR-γ is to enhance insulin sensitivity and regulate glucose metabolism. Although PPAR-γ agonists such as Thiazolidinediones are effective in addressing diabetes complications, it is vital to be mindful that they are associated with substantial side effects that could potentially give rise to health challenges. The recent surge in the discovery of selective modulators of PPAR-γ inspired us to formulate an integrated computational strategy by leveraging the promising capabilities of both machine learning and in silico drug design approaches. In pursuit of our objectives, the initial stage of our work involved constructing an advanced machine learning classification model, which was trained utilizing chemical information and physicochemical descriptors obtained from known PPAR-γ modulators. The subsequent application of machine learning-based virtual screening, using a library of 31,750 compounds, allowed us to identify 68 compounds having suitable characteristics for further investigation. A total of four compounds were identified and the most favorable configurations were complemented with docking scores ranging from -8.0 to -9.1 kcal/mol. Additionally, the compounds engaged in hydrogen bond interactions with essential conserved residues including His323, Leu330, Phe363, His449 and Tyr473 that describe the ligand binding site. The stability indices investigated herein for instance root-mean-square fluctuations in the backbone atoms indicated higher mobility in the region of orthosteric site in the presence of agonist with the deviation peaks in the range of 0.07-0.69 nm, signifying moderate conformational changes. The deviations at global level revealed that the average values lie in the range of 0.25-0.32 nm. In conclusion, our identified hits particularly, CHEMBL-3185642 and CHEMBL-3554847 presented outstanding results and highlighted the stable conformation within the orthosteric site of PPAR-γ to positively modulate the activity.

A combination of virtual screening, molecular dynamics simulation, MM/PBSA, ADMET, and DFT calculations to identify a potential DPP4 inhibitor

DPP4 inhibitors can control glucose homeostasis by increasing the level of GLP-1 incretins hormone due to dipeptidase mimicking. Despite the potent effects of DPP4 inhibitors, these compounds cause unwanted toxicity attributable to their effect on other enzymes. As a result, it seems essential to find novel and DPP4 selective compounds. In this study, we introduce a potent and selective DPP4 inhibitor via structure-based virtual screening, molecular docking, molecular dynamics simulation, MM/PBSA calculations, DFT analysis, and ADMET profile. The screened compounds based on similarity with FDA-approved DPP4 inhibitors were docked towards the DPP4 enzyme. The compound with the highest docking score, ZINC000003015356, was selected. For further considerations, molecular docking studies were performed on selected ligands and FDA-approved drugs for DPP8 and DPP9 enzymes. Molecular dynamics simulation was run during 200 ns and the analysis of RMSD, RMSF, Rg, PCA, and hydrogen bonding were performed. The MD outputs showed stability of the ligand-protein complex compared to available drugs in the market. The total free binding energy obtained for the proposed DPP4 inhibitor was more negative than its co-crystal ligand (N7F). ZINC000003015356 confirmed the role of the five Lipinski rule and also, have low toxicity parameter according to properties. Finally, DFT calculations indicated that this compound is sufficiently soft.

Evaluation of Adenanthera pavonina-derived compounds against diabetes mellitus: insight into the phytochemical analysis and in silico assays

Adenanthera pavonina is a medicinal plant with numerous potential secondary metabolites showing a significant level of antidiabetic activity. The objective of the current study was to identify potential phytochemicals from the methanolic leaf extract of Adenanthera pavonina as therapeutic agents against diabetes mellitus using GC-MS and in silico methods. The GC-MS analysis of the leaf extract revealed a total of 17 phytochemicals. Molecular docking was performed using these phytochemicals, targeting the mutated insulin receptor tyrosine kinase (5hhw), which inhibits glucose uptake by cells. Diazoprogesterone (-9.2 kcal/mol), 2,4,4,7a-Tetramethyl-1-(3-oxobutyl)octahydro-1H-indene-2-carboxylic acid (-6.9 kcal/mol), and 2-Naphthalenemethanol, decahydro-.alpha.,.alpha.,4a-trimethyl-8-methylene-, [2R-(2.alpha.,4a.alpha.,8a.beta.)] (-6.6 kcal/mol) exhibited better binding with the target protein. The ADMET analysis was performed for the top three compounds with the best docking scores, which showed positive results with no observed toxicity in the AMES test. Furthermore, the molecular dynamics study confirmed the favorable binding of Diazoprogesterone, 2,4,4,7a-Tetramethyl-1-(3-oxobutyl)octahydro-1H-indene-2-carboxylic acid and 2-Naphthalenemethanol, decahydro-.alpha.,.alpha.,4a-trimethyl-8-methylene-, [2R-(2.alpha.,4a.alpha.,8a.beta.)] with the receptor throughout the 100 ns simulation period.

Mechanistic QSAR modeling derived virtual screening, drug repurposing, ADMET and in-vitro evaluation to identify anticancer lead as lysine-specific demethylase 5a inhibitor

A lysine-specific demethylase is an enzyme that selectively eliminates methyl groups from lysine residues. KDM5A, also known as JARID1A or RBP2, belongs to the KDM5 Jumonji histone demethylase subfamily. To identify novel molecules that interact with the LSD5A receptor, we created a quantitative structure-activity relationship (QSAR) model. A group of 435 compounds was used in a study of the quantitative relationship between structure and activity to guess the IC50 values for blocking LASD5A. We used a genetic algorithm-multilinear regression-based quantitative structure-activity connection model to forecast the bioactivity (PIC50) of 1615 food and drug administration pharmaceuticals from the zinc database with the goal of repurposing clinically used medications. We used molecular docking, molecular dynamic simulation modelling, and molecular mechanics generalised surface area analysis to investigate the molecule's binding mechanism. A genetic algorithm and multi-linear regression method were used to make six variable-based quantitative structure-activity relationship models that worked well (R2 = 0.8521, Q2LOO = 0.8438, and Q2LMO = 0.8414). ZINC000000538621 was found to be a new hit against LSD5A after a quantitative structure-activity relationship-based virtual screening of 1615 zinc food and drug administration compounds. The docking analysis revealed that the hit molecule 11 in the KDM5A binding pocket adopted a conformation similar to the pdb-6bh1 ligand (docking score: -8.61 kcal/mol). The results from molecular docking and the quantitative structure-activity relationship were complementary and consistent. The most active lead molecule 11, which has shown encouraging results, has good absorption, distribution, metabolism, and excretion (ADME) properties, and its toxicity has been shown to be minimal. In addition, the MTT assay of ZINC000000538621 with MCF-7 cell lines backs up the in silico studies. We used molecular mechanics generalise borne surface area analysis and a 200-ns molecular dynamics simulation to find structural motifs for KDM5A enzyme interactions. Thus, our strategy will likely expand food and drug administration molecule repurposing research to find better anticancer drugs and therapies.Communicated by Ramaswamy H. Sarma.

Targeting with Structural Analogs of Natural Products the Purine Salvage Pathway in Leishmania (Leishmania) infantum by Computer-Aided Drug-Design Approaches

Visceral Leishmaniasis (VL) has a high death rate, with 500,000 new cases and 50,000 deaths occurring annually. Despite the development of novel strategies and technologies, there is no adequate treatment for the disease. Therefore, the purpose of this study is to find structural analogs of natural products as potential novel drugs to treat VL. We selected structural analogs from natural products that have shown antileishmanial activities, and that may impede the purine salvage pathway using computer-aided drug-design (CADD) approaches. For these, we started with the vastly studied target in the pathway, the adenine phosphoribosyl transferase (APRT) protein, which alone is non-essential for the survival of the parasite. Keeping this in mind, we search for a substance that can bind to multiple targets throughout the pathway. Computational techniques were used to study the purine salvage pathway from Leishmania infantum, and molecular dynamic simulations were used to gather information on the interactions between ligands and proteins. Because of its low homology to human proteins and its essential role in the purine salvage pathway proteins network interaction, the findings further highlight the significance of adenylosuccinate lyase protein (ADL) as a therapeutic target. An analog of the alkaloid Skimmianine, N,N-diethyl-4-methoxy-1-benzofuran-6-carboxamide, demonstrated a good binding affinity to APRT and ADL targets, no expected toxicity, and potential for oral route administration. This study indicates that the compound may have antileishmanial activity, which was granted in vitro and in vivo experiments to settle this finding in the future.

Non-covalent binding interaction of bioactive coumarin esculetin with calf thymus DNA and yeast transfer RNA: A detailed investigation to decipher the binding affinities, binding location, interacting forces and structural alterations at a molecular level

Esculetin is a well-known coumarin derivative found abundantly in nature possessing an extensive array of pharmacological and therapeutic properties. Consequently, to comprehend its molecular recognition mechanism, our objective is to conduct a complete investigation of its interactions with the nucleic acid, specifically ct-DNA, and t-RNA, using spectroscopic and computational techniques. The intrinsic fluorescence of esculetin is quenched when it interacts with ct-DNA and t-RNA, and this occurs through a static quenching mechanism. The thermodynamic parameters demonstrated that the interaction is influenced by hydrogen bonding and weak van der Waals forces. CD and FT-IR results revealed no conformational changes in ct-DNA and t-RNA structure on binding with esculetin. Furthermore, competitive displacement assay with ethidium bromide, melting temperature, viscosity measurement, and potassium iodide quenching experiments, reflected that esculetin probably binds to the minor groove of ct-DNA. The molecular docking results provided further confirmation for the spectroscopic findings, including the binding location of esculetin and binding energies of esculetin complexes with ct-DNA and t-RNA. Molecular dynamics simulation studies demonstrated the conformational stability and flexibility of nucleic acids.

Interactions of Turmeric- and Curcumin-Functionalized Gold Nanoparticles with Human Serum Albumin: Exploration of Protein Corona Formation, Binding, Thermodynamics, and Antifibrillation Studies

In order to better understand the bioavailability and biocompatibility of polyphenol-assisted surface-modified bioengineered nanoparticles in nanomedicine applications, here, we address a series of photophysical experiments to quantify the binding affinity of serum albumin toward polyphenol-capped gold nanoparticles. For this, two different gold nanoparticles (AuNPs) were synthesized via the green synthesis approach, where curcumin and turmeric extract act as reducing as well as capping agents. The size, surface charge, and surface plasmon bands of the AuNPs were highly affected by the adsorption of human serum albumin (HSA) during protein corona formation, which was investigated using dynamic light scattering (DLS), ξ-potential, ultraviolet-visible (UV-vis) spectroscopy, and transmission electron microscopy (TEM) measurements. Fluorescence-based methods, absorbance, and SERS experiments were carried out to evaluate the binding aspects of AuNPs with HSA. We found that the AuNPs show moderate binding affinity toward HSA (Kb ∼ 104 M-1), irrespective of the capping agents on the surface. Hydrophobic association, along with some contribution of electrostatic interaction, played a key role in the binding process. The binding interaction was more toward the subdomain IIA region of HSA, as indicated by the competitive displacement studies using site-specific binders (warfarin and flufenamic acid). Because of the large surface curvature of small-sized AuNPs, the secondary structural conformations of HSA were slightly altered, as revealed by circular dichroism (CD), Fourier transform infrared (FT-IR) spectroscopy, and surface-enhanced Raman scattering (SERS) measurements. Additionally, the findings of the binding interactions were re-evaluated using molecular dynamics (MD) simulation studies by determining the root-mean-square deviation (RMSD), root-mean-square fluctuation (RMSF), radius of gyration (Rg), and changes in the binding energy of HSA upon complexation with AuNPs. To determine the tentative evidence for pharmacokinetic administration, these biocompatible AuNPs were applied to inhibit the amyloid fibril formation of HSA and monitored by using the thioflavin T (ThT) assay, ANS fluorescence assay, fluorescence microscopic imaging, and FESEM. AuNPs were found to show better resistance toward fibrillation of the adsorbed protein.

Review on the Drug Intolerance and Vaccine Development for the Leishmaniasis

Leishmaniasis is one of the Neglected Tropical Diseases (NTDs), a zoonotic disease of vector-borne nature that is caused by a protozoan parasite Leishmania. This parasite is transmitted by the vector sandfly into the human via a bite. Visceral leishmaniasis (VL), also called kala-azar, is the most fatal among the types of leishmaniasis, with high mortality mostly spread in the East Africa and South Asia regions. WHO report stated that approximately 3.3 million disabilities occur every year due to the disease along with approximately 50,000 annual deaths. The real matter of concern is that there is no particular effective medicine/vaccine available against leishmaniasis to date except a few approved drugs and chemotherapy for the infected patient. The current selection of small compounds was constrained, and their growing drug resistance had been a major worry. Additionally, the serious side effects on humans of the available therapy or drugs have made it essential to discover efficient and low-cost methods to speed up the development of new drugs against leishmaniasis. Ideally, the vaccine could be a low risk and effective alternative for both CL and VL and elicit long-lasting immunity against the disease. There are a number of vaccine candidates at various stages of clinical development and preclinical stage. However, none has successfully passed all clinical trials. But, the successful development and approval of commercially available vaccines for dogs against canine leishmaniasis (CanL) provides evidence that it can be possible for humans in distant future. In the present article, the approaches used for the development of vaccines for leishmaniasis are discussed and the progress being made is briefly reviewed.