In-silico modelling studies of 5-benzyl-4-thiazolinone derivatives as influenza neuraminidase inhibitors via 2D-QSAR, 3D-QSAR, molecular docking, and ADMET predictions

2,4,6-Trimethoxy chalcone derivatives: an integrated study for redesigning novel chemical entities as anticancer agents through QSAR, molecular docking, ADMET prediction, and computational simulation

QSAR, an efficient and successful approach for optimizing lead compounds in drug design, was employed to study a reported series of compounds derived from 2,4,6-trimethoxy chalcone derivatives. The ability of these compounds to inhibit CDK1 was examined, with the help of QSARINS software for model development. The generated QSAR model revealed three significant descriptors, exhibiting strong correlations with impressive statistical values: cross-validation leave-one-out correlation coefficient (Q2LOO) = 0.6663, coefficient of determination (R2) = 0.7863, external validation coefficient (R2ext) = 0.7854, cross-validation leave-many-out correlation coefficient (Q2LMO) = 0.6256, Concordance Correlation Coefficient for cross-validation (CCCcv) = 0.8150, CCCtr = 0.8804, and CCCext = 0.8750. From the key structural findings and the insights gained from the descriptors, ETA_dPsi_A, WTPT-5, and GATS7s, new lead molecules were designed. The designed molecules were then evaluated for their CDK1 inhibitory activity using the three-descriptor model developed in this study. To evaluate their drug likeliness, in-silico ADMET predictions were made using Schrodinger's Software. Molecular docking was carried out to determine the interactions of designed compounds with the target protein. The designed compounds having excellent binding pocket molecular stability and anticancer effectiveness was substantiated by the findings of the molecular dynamics simulation. The results of this work point out important properties and crucial interactions necessary for efficient protein inhibition, suggesting lead candidates for further development as novel anticancer agents.

Modeling the Blood-Brain Barrier Permeability of Potential Heterocyclic Drugs via Biomimetic IAM Chromatography Technique Combined with QSAR Methodology

Penetration through the blood-brain barrier (BBB) is desirable in the case of potential pharmaceuticals acting on the central nervous system (CNS), but is undesirable in the case of drug candidates acting on the peripheral nervous system because it may cause CNS side effects. Therefore, modeling of the permeability across the blood-brain barrier (i.e., the logarithm of the brain to blood concentration ratio, log BB) of potential pharmaceuticals should be performed as early as possible in the preclinical phase of drug development. Biomimetic chromatography with immobilized artificial membrane (IAM) and the quantitative structure-activity relationship (QSAR) methodology were successful in modeling the blood-brain barrier permeability of 126 drug candidates, whose experimentally-derived lipophilicity indices and computationally-derived molecular descriptors (such as molecular weight (MW), number of rotatable bonds (NRB), number of hydrogen bond donors (HBD), number of hydrogen bond acceptors (HBA), topological polar surface area (TPSA), and polarizability (α)) varied by class. The QSARs model established by multiple linear regression showed a positive effect of the lipophilicity (log kw, IAM) and molecular weight of the compound, and a negative effect of the number of hydrogen bond donors and acceptors, on the log BB values. The model has been cross-validated, and all statistics indicate that it is very good and has high predictive ability. The simplicity of the developed model, and its usefulness in screening studies of novel drug candidates that are able to cross the BBB by passive diffusion, are emphasized.

Structure-based drug design, molecular dynamics simulation, ADMET, and quantum chemical studies of some thiazolinones targeting influenza neuraminidase

The genetic mutability of the influenza virus leads to the existence of drug-resistant strains which is dangerous, particularly with the lingering coronavirus disease (COVID-19). This necessitated the need for the search and discovery of more potential anti-influenza agents to avert future outbreaks. In furtherance of our previous in-silico studies on 5-benzyl-4-thiazolinones as anti-influenza neuraminidase (NA) inhibitors, molecule 11 was selected as the template scaffold for the structure-based drug design due to its good binding, pharmacokinetic profiling, and better NA inhibitory activity. As such, eighteen (18) new molecules (11a-r) were designed with better MolDock scores as compared with the template scaffold and the zanamivir reference drug. However, the dynamic stability of molecule 11a in the binding cavity of the NA target (3TI5) showed water-mediated hydrogen and hydrophobic bondings with the active residues such as Arg118, Ile149, Arg152, Ile222, Trp403, and Ile427 after the MD simulation for 100 ns. The drug-likeness and ADMET assessment of all designed molecules predicted non-violation of the stipulated thresholds of Lipinski's rule and good pharmacokinetic properties respectively. In addition, the quantum chemical calculations also suggested the significant chemical reactivity of molecules with their smaller band energy gap, high electrophilicity, high softness, and low hardness. The results obtained in this study proposed a reliable in-silico viewpoint for anti-influenza drug discovery and development.Communicated by Ramaswamy H. Sarma.

Lipophilicity and ADMET Analysis of Quinoline-1,4-quinone Hybrids

Lipophilicity is one of the basic properties of a potential drug determining its solubility in non-polar solvents and, consequently, its ability to passively penetrate the cell membrane, as well as the occurrence of various pharmacokinetic processes, including adsorption, distribution, metabolism, excretion, and toxicity (ADMET). Heterocyclic compounds containing a nitrogen atom play a significant role in the search for new drugs. In this study, lipophilicity as well as other physicochemical, pharmacokinetic and toxicity properties affecting the bioavailability of the quinolone-1,4-quinone hybrids are presented. Lipophilicity was determined experimentally as well as theoretically using various computer programs. The tested compounds showed low values of experimental lipophilicity and its relationship with the type of 1,4-quinone moiety. Introduction of the nitrogen atom reduced the lipophilicity depending on the position at the 5,8-quinolinedione moiety. The bioavailability of the tested compounds was determined in silico using the ADMET parameters. The obtained parameters showed that most of the hybrids can be used orally and do not exhibit neurotoxic effects. Similarity analysis was used to examine the relationship between the ADMET parameters and experimental lipophilicity. The ability of hybrids to interact with biological targets was characterized by global reactivity descriptors. The molecular docking study showed that the hybrids can inhibit the BCL-2 protein.