3D-QSAR and molecular docking analysis of (4-piperidinyl)-piperazines as acetyl-CoA carboxylases inhibitors

Identification of the structural features of quinazoline derivatives as EGFR inhibitors using 3D-QSAR modeling, molecular docking, molecular dynamics simulations and free energy calculations

Epidermal growth factor receptor (EGFR) is a promising target for the treatment of different types of malignant tumors. Therefore, a combined molecular modeling study was performed on a series of quinazoline derivatives as EGFR inhibitors. The optimum ligand-based CoMFA and CoMSIA models showed reliable and satisfactory predictability (with R²_cv=0.681, R²_ncv=0.844, R²_pred=0.8702 and R²_cv=0.643, R²_ncv=0.874, R²_pred=0.6423). The derived contour maps provide structural features to improve inhibitory activity. Furthermore, the contour maps, molecular docking, and molecular dynamics (MD) simulations have good consistency, illustrating that the derived models are reliable. In addition, MD simulations and binding free energy calculations were also carried out to understand the conformational fluctuations at the binding pocket of the receptor. The results indicate that hydrogen bond, hydrophobic and electrostatic interactions play significant roles on activity and selectivity. Furthermore, amino acids Val31, Lys50, Thr95, Leu149 and Asp160 are considered as essential residues to participate in the ligand-receptor interactions. Overall, this work would offer reliable theoretical basis for future structural modification, design and synthesis of novel EGFR inhibitors with good potency.Communicated by Ramaswamy H. Sarma.

Comparison of various methods for validity evaluation of QSAR models

BACKGROUND

Quantitative structure-activity relationship (QSAR) modeling is one of the most important computational tools employed in drug discovery and development. The external validation of QSAR models is the main point to check the reliability of developed models for the prediction activity of not yet synthesized compounds. It was performed by different criteria in the literature.

METHODS

In this study, 44 reported QSAR models for biologically active compounds reported in scientific papers were collected. Various statistical parameters of external validation of a QSAR model were calculated, and the results were discussed.

RESULTS

The findings revealed that employing the coefficient of determination (r²) alone could not indicate the validity of a QSAR model. The established criteria for external validation have some advantages and disadvantages which should be considered in QSAR studies.

CONCLUSION

This study showed that these methods alone are not only enough to indicate the validity/invalidity of a QSAR model.

In silico exploration of hydroxylated polychlorinated biphenyls as estrogen receptor β ligands by 3D-QSAR, molecular docking and molecular dynamics simulations

Hydroxylated polychlorinated biphenyls (HO-PCBs), as the major metabolites of PCBs, have been reported to act as estrogen receptor β (ERβ) agonists. However, the chemical-biological interactions governing their activities toward ERβ have not been elucidated. Therefore, three dimensional quantitative structure-activity relationship (3D-QSAR), molecular docking and molecular dynamics (MD) simulations, to the best of our knowledge, for the first time were performed to explore the correlation between the structures and activities. The best 3D-QSAR model presented higher predictive ability (R²_cv=0.543, R²_pred=0.5793/R²_cv=0.543, R²_pred=0.6795) based on comparative molecular field analysis (CoMFA) and comparative similarity indices analysis (CoMSIA), respectively. At the same time, the derived contour maps indicated the important structural features required for improving the activity. Furthermore, molecular docking studies and MD simulations predicted the binding mode and the interactions between the ligand and the receptor. All the results would lead to a better understanding of the specific mechanism of HO-PCBs on estrogen receptor β (ERβ).Communicated by Ramaswamy H. Sarma.

Investigating the binding mechanism of piperidinyl ureas inhibitors based on the UBC12-DCN1 interaction by 3D-QSAR, molecular docking and molecular dynamics simulations

Neddylation regulates a variety of biological processes by modulating Cullin-RING E3 ubiquitin ligases (CRLs) which is considered to be an important target for human diseases. The activation of CRLs required Cullins Neddylation, which regulated by the interaction of UBC12-DCN1 complex. Here, to investigate the structure-activity relationship and binding mechanism of 41 piperidinyl ureas inhibitors based on the UBC12-DCN1 protein-protein interaction, we carried out molecular modeling studies using three-dimensional quantitative structure-activity relationship (3D-QSAR), molecular docking and molecular dynamics (MD) simulations.Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were used to generate 3D-QSAR models. The results show that the best CoMFA model has q²=0.736, r²_ncv=0.978, r²_pred=0.78 (CoMFA), and the best CoMSIA model has q²=0.761, r²_ncv=0.987, r²_pred=0.86. The electrostatic, hydrophobic and H-bond donor fields play important roles in the models. Molecular docking studies predict the binding mode and the interactions between the ligand and the receptor protein. Molecular dynamics simulations results reveal that the complex of the ligand and the receptor protein are stable at 300 K. The results of MM-GBSA indicated the residues of Ile1083, Ile1086, Ala1098, Val1102, Ile1105, Gln1114, Phe1164 and Leu1184 might be the key residues during the process of inhibitors bound to DCN1. This study could provide an important theoretical basis for further developing novel inhibitors design based on UBC12-DCN1 protein-protein interaction. All the results can provide us more useful information for our further drug design. Communicated by Ramaswamy H. Sarma.

Investigations of retinoic acid receptor-related orphan receptor-gamma t (RORγt) agonists: a combination of 3D-QSAR, molecular docking and molecular dynamics

Retinoic acid receptor-related orphan receptor-gamma t (RORγt) is an attractive target for Th17-driven autoimmune diseases. In the present work, a series of RORγt agonists were investigated by a molecular modeling study combining three-dimensional quantitative structure activity relationship (3D-QSAR), molecular docking, molecular dynamics (MD) simulations and binding free energies to get insight into the molecular features that would promote binding activity. The optimum comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) models for 3D-QSAR studies possess satisfactory predictive ability, with R²_cv=0.615, R²_pred=0.8702 for CoMFA, and R²_cv=0.670, R²_pred=0.7683 for CoMSIA model, respectively. In addition, molecular docking studies, molecular dynamics simulations and binding free energies were used to find the actual conformations of compounds in the active site of RORγt, and key residues GLN-286, LEU-287, HIS-323 and ARG-367 for higher binding activity were pointed out. The predicted models will help us to understand the structural requirements of RORγt agonists for the designing of better active compounds. Communicated by Ramaswamy H. Sarma.

Physicochemical and Pharmacokinetic Analysis of Anacardic Acid Derivatives

Anacardic acid (AA) and its derivatives are well-known for their therapeutic applications ranging from antitumor, antibacterial, antioxidant, anticancer, and so forth. However, their poor pharmacokinetic and safety properties create significant hurdles in the formulation of the final drug molecule. As a part of our endeavor to enhance the potential and exploration of the anticancer activities, a detailed study on the properties of selected AA derivatives was performed in this work. A comprehensive analysis of the drug-like properties of 100 naturally occurring AA derivatives was performed, and the results were compared with certain marketed anticancer drugs. The work focused on the understanding of the interplay among eight physicochemical properties. The relationships between the physicochemical properties, absorption, distribution, metabolism, and excretion attributes, and the in silico toxicity profile for the set of AA derivatives were established. The ligand efficacy of the finally scrutinized 17 AA derivatives on the basis of pharmacokinetic properties and toxicity parameters was further subjected to dock against the potential anticancer target cyclin-dependent kinase 2 (PDB ID: 1W98). In the docked complex, the ligand molecules (AA derivatives) selectively bind with the target residues, and a high binding affinity of the ligand molecules was ensured by the full fitness score using the SwissDock Web server. The BOILED-Egg model shows that out of 17 scrutinized molecules, 3 molecules exhibit gastrointestinal absorption capability and 14 molecules exhibit permeability through the blood-brain barrier penetration. The analysis can also provide some useful insights to chemists to modify the existing natural scaffolds in designing new anacardic anticancer drugs. The increased probability of success may lead to the identification of drug-like candidates with favorable safety profiles after further clinical evaluation.