Threat of respiratory syncytial virus infection knocking the door: a proposed potential drug candidate through molecular dynamics simulations, a future alternative

Bioactive compounds from Morchella esculenta as potential inhibitors of RNA-binding protein La in ovarian cancer: a molecular modeling and quantum mechanics approach

La protein is significantly expressed in various malignant tumors, including ovarian cancer (OC), which is related to the poor response to platinum-based chemotherapy. Thus, inhibiting La protein could control the expression of the potential downstream genes involved in promoting proliferation and chemotherapy resistance to OC, which could serve as a therapeutic intervention. Through a molecular docking approach, 12 compounds from Morchella esculenta were screened against the crystal structure of La protein and four hit compounds were identified, including beta-carotene, p-hydroxybenzoic acid, gamma-tocopherol, and alpha-tocopherol, with a binding affinity of - 10.7, - 8.1, - 7.9, and - 7.6 kcal/mol, respectively, higher than pyridine-2-carboxylate (control), with a binding affinity of - 5.2 kcal/mol. To explore the interaction of the hit compounds with the target receptor, they were selected for a molecular dynamic simulation and post-simulation analysis for 100 ns. The result showed promising reliability of the ligands due to a stable interaction with the La protein crystal structure. Furthermore, the drug-likeness and physicochemical chemical properties of the compounds were investigated using ADMET study and density functional theory analysis, respectively, and the result shows that the hit compounds could serve as a promising starting for the development of novel LA protein inhibitors for OC therapeutics. Finally, this study compared HOMO and LUMO values from global hybrids with long-range corrected DFAs, and the result from the two followed the same qualitative pattern while calculating HOMO values; however, MO62X/cc-pVTZ could better predict LUMO values when considering a global hybrid.

Inhibition of respiratory syncytial virus by Daclatasvir and its derivatives: synthesis of computational derivatives as a new drug development

The most common cause of respiratory tract illness in newborns and young children is the respiratory syncytial virus (RSV). There is no approved vaccination or specific antiviral medication for RSV infections. Here, an attempt has been made to explore the potential of currently marketed drugs as well as their probable derivatives to improve the possibility of developing stronger medications against RSV. From the 100 synthetic drug compounds library, the best drug molecule was identified through drug-likeness properties, toxicity, molecular docking and molecular dynamics simulations. Molecular Mechanics Generalized Born Surface Area (MM-GBSA) was also a method that was applied in this study. Daclatasvir showed the highest binding energy and appeared as the best drug to inhibit matrix protein and a fusion protein of RSV. Based on Daclatasvir, 40 computational derivatives were made. D28, D34 and D40 showed far better results than the actual drug. Changes in lipophilicity character increase the binding energy of derivatives. Molecular dynamic simulations showed their non-deviated, non-fluctuated and stable complex formation with target proteins. The high number of amino acid contacts throughout the trajectory increases the stability and effectiveness of derivatives. The key to producing a novel medicine to eradicate RSV is provided by derivatives. Daclatasvir will be employed as a potential RSV inhibitor up until that point.Communicated by Ramaswamy H. Sarma.

Potentiality of bioactive compounds as inhibitor of M protein and F protein function of human respiratory syncytial virus

The human respiratory syncytial virus (RSV) creates a pandemic every year in several countries in the world. Lack of target therapeutics and absence of vaccines have prompted scientists to create novel vaccines or small chemical treatments against RSV's numerous targets. The matrix (M) protein and fusion (F) glycoprotein of RSV are well characterized and attractive drug targets. Five bioactive compounds from Alnus japonica (Thunb.) Steud. were taken into consideration as lead compounds. Drug-likeness characters of them showed the drugs are non-toxic and non-mutagenic and mostly lipophobic. Molecular docking reveals that all bioactive compounds have better binding and better inhibitory effect than ribavirin which is currently used against RSV. Praecoxin A appeared as the best lead compound between them. It creates 7 different types of bonds with amino acids of M protein and 5 different types of bonds with amino acids of F protein. Van der Waals interactions highly influenced the binding energies. Molecular dynamic simulations represent the non-deviated and less fluctuating nature of praecoxin A. Principal Component Analysis showed praecoxin A complex with RSV matrix protein is more stable than ribavirin complex. This study will help to develop a new drug to inhibit RSV. All ligands were minimized through semi-empirical PM3 process with MOPAC. Toxicity was tested by ProTox-II server. Molecular docking studies were carried out using AutoDock 4.2. Molecular dynamics simulations for 100 ns were carried out through GROMACS 5.12 MD and GROMOS96 43a1 force field. The graphs were produced by GROMACS's XMGrace program.

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Cheminformatics-based discovery of new organoselenium compounds with potential for the treatment of cutaneous and visceral leishmaniasis

Leishmaniasis affects more than 12 million humans globally and a further 1 billion people are at risk in leishmaniasis endemic areas. The lack of a vaccine for leishmaniasis coupled with the limitations of existing anti-leishmanial therapies prompted this study. Cheminformatic techniques are widely used in screening large libraries of compounds, studying protein-ligand interactions, analysing pharmacokinetic properties, and designing new drug molecules with great speed, accuracy, and precision. This study was undertaken to evaluate the anti-leishmanial potential of some organoselenium compounds by quantitative structure-activity relationship (QSAR) modeling, molecular docking, pharmacokinetic analysis, and molecular dynamic (MD) simulation. The built QSAR model was validated (R2train = 0.8646, R2test = 0.8864, Q2 = 0.5773) and the predicted inhibitory activity (pIC50) values of the newly designed compounds were higher than that of the template (Compound 6). The new analogues (6a, 6b, and 6c) showed good binding interactions with the target protein (Pyridoxal kinase, PdxK) while also presenting excellent drug-likeness and pharmacokinetic profiles. The results of density functional theory, MD simulation, and molecular mechanics generalized Born surface area (MM/GBSA) analyses suggest the favourability and stability of protein-ligand interactions of the new analogues with PdxK, comparing favourably well with the reference drug (Pentamidine). Conclusively, the newly designed compounds could be synthesized and tested experimentally as potential anti-leishmanial drug molecules.Communicated by Ramaswamy H. Sarma.

In-silico screening of Acacia pennata and Bridelia retusa reveals pinocembrin-7-O-β-D-glucopyranoside as a promising β-lactamase inhibitor to combat antibiotic resistance

The β-lactamase of Pseudomonas aeruginosa is known to degrade β-lactam antibiotics such as penicillins, cephalosporins, monobactams, and carbapenems. With the discovery of an extended-spectrum β-lactamase in a clinical isolate of P. aeruginosa, the bacterium has become multi-drug resistant. In this study, we aim to identify new β-lactamase inhibitors by virtually screening a total of 43 phytocompounds from two Indian medicinal plants. In the molecular docking studies, pinocembrin-7-O-β-D-glucopyranoside (P7G) (-9.6 kcal/mol) from Acacia pennata and ellagic acid (EA) (-9.2 kcal/mol) from Bridelia retusa had lower binding energy than moxalactam (-8.4 kcal/mol). P7G and EA formed 5 (Ser62, Asn125, Asn163, Thr209, and Ser230) and 4 (Lys65, Ser123, Asn125, and Glu159) conventional hydrogens bonds with the active site residues. 100 ns MD simulations revealed that moxalactam and P7G (but not EA) were able to form a stable complex. The binding free energy calculations further revealed that P7G (-59.6526 kcal/mol) formed the most stable complex with β-lactamase when compared to moxalactam (-46.5669 kcal/mol) and EA (-28.4505 kcal/mol). The HOMO-LUMO and other DFT parameters support the stability and chemical reactivity of P7G at the active site of β-lactamase. P7G passed all the toxicity tests and bioavailability tests indicating that it possesses drug-likeness. Among the studied compounds, we identified P7G of A. pennata as the most promising phytocompound to combat antibiotic resistance by potentially inhibiting the β-lactamase of P. aeruginosa.Communicated by Ramaswamy H. Sarma.