QSAR study and molecular docking of benzimidazole derivatives as potent activators of AMP-activated protein kinase

Abstract3D-QSAR and molecular docking methods were performed on a set of 74 benzimidazole derivatives previously studied as activators of the AMP-activated protein kinase (AMPK), a protein that plays a key role in the regulation of cellular energy balance. Relative enzyme activity (REA) of 74 compounds was quantitatively modelled using multiple linear regression (MLR) and neuronal networks (NN). The proposed QSAR model provided statistically significant results (rMLR=0.89; rNN=0.95 and rCV=0.90) and was validated using the leave-one-out method. The general binding mode of benzimidazole derivatives to the AMPK binding site was explored using molecular docking, with a focus on the most active molecules of our set, compounds 19 and 25

QSAR-driven screening uncovers and designs novel pyrimidine-4,6-diamine derivatives as potent JAK3 inhibitors

This study presents a robust and integrated methodology that harnesses a range of computational techniques to facilitate the design and prediction of new inhibitors targeting the JAK3/STAT pathway. This methodology encompasses several strategies, including QSAR analysis, pharmacophore modeling, ADMET prediction, covalent docking, molecular dynamics (MD) simulations, and the calculation of binding free energies (MM/GBSA). An efficacious QSAR model was meticulously crafted through the employment of multiple linear regression (MLR). The initial MLR model underwent further refinement employing an artificial neural network (ANN) methodology aimed at minimizing predictive errors. Notably, both MLR and ANN exhibited commendable performance, showcasing R2 values of 0.89 and 0.95, respectively. The model's precision was assessed via leave-one-out cross-validation (CV) yielding a Q2 value of 0.65, supplemented by rigorous Y-randomization. , The pharmacophore model effectively differentiated between active and inactive drugs, identifying potential JAK3 inhibitors, and demonstrated validity with an ROC value of 0.86. The newly discovered and designed inhibitors exhibited high inhibitory potency, ranging from 6 to 8, as accurately predicted by the QSAR models. Comparative analysis with FDA-approved Tofacitinib revealed that the new compounds exhibited promising ADMET properties and strong covalent docking (CovDock) interactions. The stability of the new discovered and designed inhibitors within the JAK3 binding site was confirmed through 500 ns MD simulations, while MM/GBSA calculations supported their binding affinity. Additionally, a retrosynthetic study was conducted to facilitate the synthesis of these potential JAK3/STAT inhibitors. The overall integrated approach demonstrates the feasibility of designing novel JAK3/STAT inhibitors with robust efficacy and excellent ADMET characteristics that surpass Tofacitinib by a significant margin

In-silico screening based on molecular simulations of 3,4-disubstituted pyrrolidine sulfonamides as selective and competitive GlyT1 inhibitors

A systematic in-silico study based on molecular modeling techniques was conducted on thirty 3,4-disubstituted pyrrolidine sulfonamides derivatives to identify the drug candidate for treating schizophrenia and impairments associated with NMDA receptor hypofunction, through selective and competitive inhibition of GlyT1. QSAR analysis demonstrates that geometric and constitutional descriptors have a key function in human GlyT1 activity. The in-silico study concluded that the most active ligand labeled C19 was predicted to be a non-toxic inhibitor, with a desired ADME-Toxicity profile and a significant probability to penetrate the central nervous system (CNS). Molecular docking simulations confirmed that the C19 compound was docked to the active sites of drosophila melanogaster dopamine transporter (DAT) protein, creating a variety of chemical bonds towards TYR 124, ASP 475, GLU 480, ALA 479, and VAL 120 amino acids residues. The molecular dynamic (MD) technique combined with the MMGBSA approach confirmed that produced intermolecular interactions for the (DAT protein–C19 ligand) complex remain so stable during 100 ns of MD simulation time. Consequently, the C19 ligand is highly recommended for the treatment of schizophrenia and other disabilities linked to the hypofunction of glutaminergic NMDA receptors

3D-QSAR, ADME-Tox In Silico Prediction and Molecular Docking Studies for Modeling the Analgesic Activity against Neuropathic Pain of Novel NR2B-Selective NMDA Receptor Antagonists

A new class of selective antagonists of the N-Methyl-D-Aspartate (NMDA) receptor subunit 2B have been developed using molecular modeling techniques. The three-dimensional quantitative structure–activity relationship (3D-QSAR) study, based on comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA) models, indicate that steric, electrostatic and hydrogen bond acceptor fields have a key function in the analgesic activity against neuropathic pain. The predictive accuracy of the developed CoMFA model (Q2 = 0.540, R2 = 0.980, R2 pred = 0.613) and the best CoMSIA model (Q2 = 0.665, R2 = 0.916, R2 pred = 0.701) has been successfully examined through external and internal validation. Based on ADMET in silico properties, L1, L2 and L3 ligands are non-toxic inhibitors of 1A2, 2C19 and 2C9 cytochromes, predicted to passively cross the blood–brain barrier (BBB) and have the highest probability to penetrate the central nervous system (CNS). Molecular docking results indicate that the active ligands (L1, L2 and L3) interact specifically with Phe176, Glu235, Glu236, Gln110, Asp136 and Glu178 amino acids of the transport protein encoded as 3QEL. Therefore, they could be used as analgesic drugs for the treatment of neuropathic pain

In-silico investigations of novel tacrine derivatives potency against Alzheimer's disease

Tacrine was originally used as a palliative treatment for Alzheimer's disease (AD). But early applications soon revealed a number of its side effects on human health. That's why we decided to examine the effectiveness of novel tacrine derivatives known for their potent inhibition of GluN2B-NMDA receptors, to discover the leading candidates for treating AD in terms of safety and molecular stability towards NMDA receptors. As a result, CoMFA and CoMSIA models were generated using 3-dimensional quantitative structure-activity relationships (3D-QSARs) study, indicating that Electrostatic, Hydrophobic, and Steric fields have a vital function in the NMDAR-antagonizing activities. The predictive exactitude of the generated CoMFA model (Q2cv = 0.699, R2 training = 0.980, R2 test = 0.737) and the top model of CoMSIA (Q2cv = 0.646, R2 training = 0.867, R2 test = 0.761) has been successfully tested in both internal and external validations. The pharmacokinetics properties of in-silico ADME-Toxicity confirm the safety of C24 and C27 compounds, which were discovered to be free from any skin allergy toxicity and hepatotoxic effects, and would be able to passively break through the blood-brain barrier and ultimately penetrate the central nervous system with a very good level of absorption (HIA exceeding 95 %). The molecular docking results indicate that non-toxic inhibitors interact specifically with Gln110, Ser132, and Tyr109 amino acid residues as the main active sites of the transport protein encoded as 5EWJ.pdb. At last, the intermolecular mechanisms detected by the examined ligands labeled C24, and C27, revealed excellent levels of molecular stability towards the targeted protein along one hundred nano-seconds of molecular dynamics time.Therefore, C24 and C27 chemical compounds are strongly recommended to treat AD, due to their considerable similarity to drug candidates and high levels of molecular stability

Design of novel anti-cancer agents targeting COX-2 inhibitors based on computational studies

The overexpression of cyclooxygenase-2 (COX-2) was clearly associated with carcinogenesis, and COX-2 as a possible target has long been exploited for cancer therapy. A group of 29 derivatives of 1, 5-diarylpyrazole was used to study its structural requirements using three-dimensional quantitative structure–activity relationship (3D-QSAR), the density functional theory method, molecular docking, and molecular dynamics. Four 3D-QSAR models were developed, and the predictive capability of the four selected models was also successfully tested using different validation methods. The contribution contours of the comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA) models effectively illustrate the relationships between the various chemical characteristics and their biological activities. Using the density functional theory method with the 6-31G (d, p) basis set and the Becke, 3-parameter, Lee-Yang-Parr (B3LYP) function to evaluate chemical reactivity properties, the results obtained from energy gaps of 3.431, 3.446, and 2.727 ev for molecules numbers 21, 22, and 23 indicate that these three molecules have good chemical stability and reactivity and select the most reactive regions in the three molecules studied. Molecular docking results revealed that the active sites of the COX-2 protein (PDB code: 3PGH) were residues ARG222, THR212, HIS386, HIS207, TYR148, and ASP382, in which the most active ligands and now ligands can inhibit the COX-2 enzyme. Based on the various results obtained by molecular modeling, four new compounds (N1, N2, N3, and N4) were proposed with significant predicted activity by different 3D-QSAR models. A molecular docking study and molecular dynamics simulations of the proposed new molecules (N1 and N2) and the most active molecule over 100 ns revealed that all three molecules establish multiple hydrogen interactions with several residues and also exhibit frequent stability throughout the simulation period. As a result, it is strongly recommended to consider the two newly proposed molecules, N1 and N4, as promising candidates for novel anti-cancer agents specifically designed to target COX-2 inhibition

QSAR, DFT studies, docking molecular and simulation dynamic molecular of 2-styrylquinoline derivatives through their anticancer activity

In this study, a 2D-QSAR (quantitative structure–activity relationship) was performed on 54 new 2-Styrylquinoline derivatives as anticancer substances capable of inhibiting the p53 protein in the cell HCT116++. The 54 2-Styrylquinoline derivatives was calculated applying DFT 6-31G basis to calculate Quantum descriptors, using MM2 for: Topological, Physico-chemical, Geometrical and Constitutional. The study was carried out by performing multiple linear regression (R2 = 0.90), the QSAR model achieved was tested by artificial neural networks method, which is showed high predictability (R2ANN = 0.89). A DFT study was performed to determine the reactivity of the 2-Styrylquinoline derivatives using frontier molecular orbital analysis and analysis of the molecular electrostatic potential (MEP). Derivatives of 2–4 Styrylquinoline are studied for their synthetic accessibility and their similarity to drug. The obtained results show that all the evaluated compounds have similar properties to drug and are accessible to synthesize.A molecular docking analysis was performed for three compounds: 14, 34, and 54, having various reactivities against the p53 HCT116++ protein (identified by PDB ID: 2GEQ). The results showed strong interactions between the three ligands and the 2GEQ protein, the amino acids HIS 176, SER A180, PRO A188 and ARG A178 are the most active sites of the 2GEQ protein, and based on these result we performed a molecular dynamics simulation to evaluate the stability of our complexes. The MD demonstrates the thermodynamic stability of select compounds during 40 and 100 ns, with all three complexes showing a high level of structural stability

3D-QSAR Studies, Molecular Docking, Molecular Dynamic Simulation, and ADMET Proprieties of Novel Pteridinone Derivatives as PLK1 Inhibitors for the Treatment of Prostate Cancer

Overexpression of polo-like kinase 1 (PLK1) has been found in many different types of cancers. With its essential role in cell proliferation, PLK1 has been determined to be a broad-spectrum anti-cancer target. In this study, 3D-QSAR, molecular docking, and molecular dynamics (MD) simulations were applied on a series of novel pteridinone derivatives as PLK1 inhibitors to discover anti-cancer drug candidates. In this work, three models—CoMFA (Q² = 0.67, R² = 0.992), CoMSIA/SHE (Q² = 0.69, R² = 0.974), and CoMSIA/SEAH (Q² = 0.66, R² = 0.975)—of pteridinone derivatives were established. The three models that were established gave Rpred2 = 0.683, Rpred 2= 0.758, and Rpred 2= 0.767, respectively. Thus, the predictive abilities of the three proposed models were successfully evaluated. The relations between the different champs and activities were well-demonstrated by the contour chart of the CoMFA and CoMSIA/SEAH models. The results of molecular docking indicated that residues R136, R57, Y133, L69, L82, and Y139 were the active sites of the PLK1 protein (PDB code: 2RKU), in which the more active ligands can inhibit the enzyme of PLK1. The results of the molecular dynamic MD simulation diagram were obtained to reinforce the previous molecular docking results, which showed that both inhibitors remained stable in the active sites of the PLK1 protein (PDB code: 2RKU) for 50 ns. Finally, a check of the ADME-Tox properties of the two most active molecules showed that molecular N° 28 could represent a good drug candidate for the therapy of prostate cancer diseases

QSAR, ADMET In Silico Pharmacokinetics, Molecular Docking and Molecular Dynamics Studies of Novel Bicyclo (Aryl Methyl) Benzamides as Potent GlyT1 Inhibitors for the Treatment of Schizophrenia

Forty-four bicyclo ((aryl) methyl) benzamides, acting as glycine transporter type 1 (GlyT1) inhibitors, are developed using molecular modeling techniques. QSAR models generated by multiple linear and non-linear regressions affirm that the biological inhibitory activity against the schizophrenia disease is strongly and significantly correlated with physicochemical, geometrical and topological descriptors, in particular: Hydrogen bond donor, polarizability, surface tension, stretch and torsion energies and topological diameter. According to in silico ADMET properties, the most active ligands (L6, L9, L30, L31 and L37) are the molecules having the highest probability of penetrating the central nervous system (CNS), but the molecule 32 has the highest probability of being absorbed by the gastrointestinal tract. Molecular docking results indicate that Tyr124, Phe43, Phe325, Asp46, Phe319 and Val120 amino acids are the active sites of the dopamine transporter (DAT) membrane protein, in which the most active ligands can inhibit the glycine transporter type 1 (GlyT1). The results of molecular dynamics (MD) simulation revealed that all five inhibitors remained stable in the active sites of the DAT protein during 100 ns, demonstrating their promising role as candidate drugs for the treatment of schizophrenia