In Silico Pharmacology

Dihydropyrimidine derivatives possess many biological activities due to presence of pyrimidine ring structure in various nucleic acids, vitamins, coenzymes, uric acid and their derivatives. They have possessed broad spectrum actions like antibacterial, antifungal, antiviral, anticancer and antihypertensive etc. Before synthesis of compounds, it is good to predict biological activity using in silico methods. Here, we have selected some of N (3a–f) and O (4a–f) mannich bases of dihydro pyrimidine derivatives emphasized on histone deacetylase 4 (HDAC-4) inhibitions activity. We have used the different software tools like Lipinski’s rule of five; pass online; osiris property explorer and docking studies to predict anti cancer activity. All the selected compounds exhibited potential drug like molecule with anti cancer activity. Among all compound the substitution with methoxy group (3c) exhibited more drugs like property and substation with hydrogens (4a) showed high anti neoplastic activity; whereas substitution with dichloro groups (4e) showed more drug docking scores. These were compared with standard drugs tamoxifen and 5-flourouracil. The approach of predicting anticancer activity using in silico method may be more useful to select and synthesis novel compounds in research as well as in industry.

The neurotransmitter acetylcholine (ACh) plays a ubiquitous role in cognitive functions including learning and memory with widespread innervation in the cortex, subcortical structures, and the cerebellum. Cholinergic receptors, transporters, or enzymes associated with many neurodegenerative diseases, including Alzheimer’s disease (AD) and Parkinson’s disease (PD), are potential imaging targets. In the present study, we have developed 2D-quantitative structure–activity relationship (2D-QSAR) models for 19 positron emission tomography (PET) imaging agents targeted against presynaptic vesicular acetylcholine transporter (VAChT). VAChT assists in the transport of ACh into the presynaptic storage vesicles, and it becomes one of the main targets for the diagnosis of various neurodegenerative diseases. In our work, we aimed to understand the important structural features of the PET imaging agents required for their binding with VAChT. This was done by feature selection using a Genetic Algorithm followed by the Best Subset Selection method and developing a Partial Least Squares- based 2D-QSAR model using the best feature combination. The developed QSAR model showed significant statistical performance and reliability. Using the features selected in the 2D-QSAR analysis, we have also performed similarity-based chemical read-across predictions and obtained encouraging external validation statistics. Further, we have also performed molecular docking analysis to understand the molecular interactions occurring between the PET imaging agents and the VAChT receptor. The molecular docking results were correlated with the QSAR features for a better understanding of the molecular interactions. This research serves to fulfill the experimental data gap, highlighting the applicability of computational methods in the PET imaging agents’ binding affinity prediction.

During metastasis, cancer cells transcend from primary site to normal cells area upon attaining epithelial to mesenchymal transition (EMT) causing malignant cancer disease. Increased expression of TGF-β and its receptor ALK5 is an important hallmark of malignant cancer. In the present study, efficacy of curcumin and its analogues as inhibitors of ALK5 (TGFβR-I) receptor was evaluated using in silico approaches. A total of 142 curcumin analogues and curcumin were retrieved from peer reviewed literature and constructed a combinatorial library. Further their drug-likeness was assessed using Molinspiration, cheminformatics and preADMET online servers. The interaction of 142 curcumin analogues and curcumin with ALK5 receptor was studied using Autodock Vina. This study revealed six curcumin analogues as promising ALK5 inhibitors with significant binding energy and H-bonding interaction.

Oral cancer (OC) which is the most predominant malignant epithelial neoplasm in the oral cavity, is the 8th commonest type of cancer globally. Natural products are excellent sources of functionally active compounds and essential nutrients that play an important role in cancer therapeutics. Using the structure-based virtual screening, drug-likeness, toxicity, and molecular dynamics simulation, the current study focused on the evaluation of anticancer activity of bioactive compounds from Curcumis maderaspatanus. AURKA, CDK1, and VEGFR-2 proteins which play a crucial role in the development and progression of oral cancer was selected as targets and 216 phytochemicals along with a known reference inhibitor were docked against these target proteins. Based on the docking score, it was found that phytochemicals namely 3-Benzoyl-2,4(1H,3H)-Pyrimidinedione (− 8.0 kcal/mol), 1-Cyclohexylethanol, trifluoroacetate (− 6.3 kcal/mol), and Alpha-Curcumene (− 8.9 kcal/mol) interacts with AURKA, CDK1, and VEGFR-2 with highest binding affinity. The molecular dynamics simulation demonstrated that the best docked complexes exhibited excellent structural stability in terms of RMSD, RSMF, SASA and Rg for a period of 100 ns. Altogether, our computational analysis reveals that the bioactives from C. maderaspatanus could emerge as efficacious drug candidates in oral cancer therapy.

The present research aims to explore the intricate link between SARS-CoV infection and susceptibility to Alzheimer’s disease, focusing on the role of APOE4, a genetic factor associated with both conditions. Our research aims to uncover shared molecular pathways, considering APOE4’s impact on lipid metabolism, immune responses, and neuroinflammation relevant to COVID-19 and AD. The Chyawanprash phytocompounds were subjected to in-silico ADMET profiling and Zeatin a neuroprotective cytokinin emerged as a promising regulator of the ACE2-SPIKE complex as it exhibits favourable pharmacological attributes, presenting as a non-substrate for Permeability glycoprotein, low Protein Binding Percentage, and distinctive toxicity endpoints. Therapeutic candidate. Zeatin’s robust binding disrupts the intricate APOE4-ACE2-SPIKE interplay (AAS), offering a potential therapeutic avenue that is further corroborated by Molecular dynamic simulation as the system remained stable without any major fluctuation throughout the 100ns simulation. The AAS binding free energy, determined as -124.849 +/- 15.513 KJ/mol using MMPBSA assay, reveals significant contributions to complex stability from amino acids including, GLN41: 1.211 kcal/mol, GLU340: 1.188 kcal/mol, ALA344: 1.198 kcal/mol, while ARG38: 2.011 kcal/mol establishes pivotal strong bonds integral to the interaction between AAS and Zeatin. Rigorous cytotoxicity assessments reveal Zeatin’s safety profile, highlighting its inhibitory effect on LN18 cell viability that sharply decreases to 32.47% at 200 µg/ml, underscoring its modulatory impact on cellular metabolism. These findings enhance our understanding of the convergent mechanisms linking SARS-CoV and AD, providing valuable insights for potential therapeutic interventions. Further research is warranted to elucidate the specific pathways and molecular mechanisms through which zeatin exerts its protective effects.

A2B receptor agonists are studied as possible therapeutic tools for a variety of pathological conditions. Unfortunately, medicinal chemistry efforts have led to the development of a limited number of potent agonists of this receptor, in most cases with a low or no selectivity versus the other adenosine receptor subtypes. Among the developed molecules, two structural families of compounds have been identified based on nucleoside and non-nucleoside (pyridine) scaffolds. The aim of this work is to analyse the binding mode of these molecules at 3D models of the human A2B receptor to identify possible common interaction features and the key receptor residues involved in ligand interaction. The A2B receptor models are built by using two recently published crystal structures of the human A2A receptor in complex with two different agonists. The developed models are used as targets for molecular docking studies of nucleoside and non-nucleoside agonists. The generated docking conformations are subjected to energy minimization and rescoring by using three different scoring functions. Further analysis of top-score conformations are performed with a tool evaluating the interaction energy between the ligand and the binding site residues. Results suggest a set of common interaction points between the two structural families of agonists and the receptor binding site, as evidenced by the superimposition of docking conformations and by analysis of interaction energy with the receptor residues. The obtained results show that there is a conserved pattern of interaction between the A2B receptor and its agonists. These information and can provide useful data to support the design and the development of A2B receptor agonists belonging to nucleoside or non-nucleoside structural families.

G Protein-Coupled Receptors (GPCRs) are a large family of therapeutically important proteins and as diverse X-ray structures become available it is increasingly possible to leverage structural information for rational drug design. We present herein approaches that use explicit water networks combined with energetic surveys of the binding site (GRID), providing an enhanced druggability and ligand design approach, with structural understanding of ligand binding, including a ‘magic’ methyl and binding site mutations, and a fast new approach to generate and score waters. The GRID program was used to identify lipophilic and hydrogen bonding hotspots. Explicit full water networks were generated and scored for (pseudo)apo structures and ligand-protein complexes using a new approach, WaterFLAP (Molecular Discovery), together with WaterMap (Schrödinger) for (pseudo)apo structures. A scoring function (MetaScore) was developed using a fast computational protocol based on several short adiabatic biased MD simulations followed by multiple short well-tempered metadynamics runs. Analysis of diverse ligands binding to the adenosine A2A receptor together with new structures for the δ/κ/μ opioid and CCR5 receptors confirmed the key role of lipophilic hotspots in driving ligand binding and thus design; the displacement of ‘unhappy’ waters generally found in these regions provides a key binding energy component. Complete explicit water networks could be robustly generated for protein-ligand complexes using a WaterFLAP based approach. They provide a structural understanding of structure-activity relationships such as a ‘magic methyl’ effect and with the metadynamics approach a useful estimation of the binding energy changes resulting from active site mutations. The promise of full structure-based drug design (SBDD) for GPCRs is now possible using a combination of advanced experimental and computational data. The conformational thermostabilisation of StaR® proteins provide the ability to easily generate biophysical screening data (binding including fragments, kinetics) and to get crystal structures with both potent and weak ligands. Explicit water networks for apo and ligand-complex structures are a critical ‘third dimension’ for SBDD and are key for understanding ligand binding energies and kinetics. GRID lipophilic hotspots are found to be key drivers for binding. In this context ‘high end’ GPCR ligand design is now enabled.

Tropical theileriosis is a protozoan infection caused by Theileria annulata, which significantly affects cattle worldwide. This study was aimed to analyze the TaSPAG1 protein and design a novel multi-epitope vaccine candidate. Online tools were employed for the prediction of Physico-chemical properties, antigenicity, allergenicity, solubility, transmembrane domains and signal peptide, posttranslational modification (PTM) sites, secondary and tertiary structures as well as intrinsically disordered regions, followed by identification and screening of potential linear and conformational B-cell epitopes and those peptides having affinity to bind bovine major histocompatibility complex class I (MHC-I) molecules. Next, a multi-epitope vaccine construct was designed and analyzed. This 907-residue protein was hydrophilic (GRAVY: -0.399) and acidic (pI: 5.04) in nature, with high thermotolerance (aliphatic: 71.27). Also, 5 linear and 12 conformational B-cell epitopes along with 8 CTL epitopes were predicted for TaSPAG1. The 355-residue vaccine candidate had a MW of about 35 kDa and it was antigenic, non-allergenic, soluble and stable, which was successfully interacted with cattle MHC-I molecule and finally cloned into the pET28a(+) vector. Further wet studies are required to assess the vaccine efficacy in cattle.