Drug-like screening, molecular docking, molecular dynamics simulations, and binding free energies on the interaction of pyrazole derivatives as inhibitors of lysosomal storage disorders and anticancer activity

Discover Chemistry., Journal Year: 2024, Volume and Issue: 1(1)

Published: Oct. 2, 2024

Language: Английский

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Design of some potent non-toxic autoimmune disorder inhibitors based on 2D-QSAR, CoMFA, molecular docking, and molecular dynamics investigations

Intelligent Pharmacy, Journal Year: 2024, Volume and Issue: 2(5), P. 688 - 706

Published: Jan. 1, 2024

Current clinical research suggests that inhibitors of protein arginine deiminase 4 (PAD4), major histocompatibility complex (MHC) class II HLA-DQ-ALPHA chain, and thyrotropin receptor (or TSH receptor) which are biological therapeutic interest, may show potential in treating rheumatoid arthritis, type 1 diabetes, Graves' disease other autoimmune disorder. In the present study, a comprehensive analysis was conducted on collection 32 compounds concerning their anti-rheumatoid arthritis activity as PAD4. This represents first instance these were computationally examined, employing an in-silico approach considered 2D-3D QSAR modeling, molecular docking further validated through dynamics ADMET properties assessment. A credible 2D (Q_LOOˆ2 = 0.6611 Rˆ2 0.7535) model constructed verified using external validation test set, Y-randomization, variance inflation factor (VIF), mean effect (MF), William's plot applicability domain (AD). Ligand-based alignment implemented 3D-QSAR examination. The outcomes demonstrated CoMFA (uvepls) (Q2LOO 0.5877; R2 0.9983) possess remarkable stability foresight. internal indicated MIFs display superior predictive capability compared to COMFA (ffdsel). Structural criteria determined by contour maps simulations strategically employed develop 10 new, non-toxic with increased efficacy. Docking tests done newly developed illustrate binding mechanism identify critical interaction residues inside active region (PDB id: 3BLU). addition, results selected designed sites diabetes (6DFX), (4QT5) 3BLU) selectivity. simulation free energy calculations MM/GBSA technique confirmed proposed compound D4 (3BLU) site. summary, our investigation might give considerable insight into future design development new inhibitors.

Language: Английский

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Ligand-Based Design of Novel Quinoline Derivatives as Potential Anticancer Agents: An In-Silico Virtual Screening Approach

Molecules, Journal Year: 2024, Volume and Issue: 29(2), P. 426 - 426

Published: Jan. 15, 2024

In this study, using the Comparative Molecular Field Analysis (CoMFA) approach, structure-activity relationship of 33 small quinoline-based compounds with biological anti-gastric cancer activity in vitro was analyzed 3D space. Once geometric and energy structure target chemical library has been optimized their steric electrostatic molecular field descriptions computed, ideal 3D-QSAR model is generated matched Partial Least Squares regression (PLS) algorithm. The accuracy, statistical precision, predictive power developed were confirmed by a range internal external validations, which interpreted robust correlation coefficients (RTrain2=0.931; Qcv2=0.625; RTest2=0.875). After carefully analyzing contour maps produced trained model, it discovered that certain structural characteristics are beneficial for enhancing properties Quinoline derivatives. Based on information, total five new quinoline developed, improved drug-like bioavailability measured POM calculations. To further explore potential these compounds, docking dynamics simulations performed an aqueous environment 100 nanoseconds, specifically targeting serine/threonine protein kinase. Overall, findings study can serve as starting point experiments view to identification design next-generation drug therapy against cancer.

Language: Английский

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DFT and molecular simulation validation of the binding activity of PDEδ inhibitors for repression of oncogenic k-Ras

PLoS ONE, Journal Year: 2024, Volume and Issue: 19(3), P. e0300035 - e0300035

Published: March 8, 2024

The development of effective drugs targeting the K-Ras oncogene product is a significant focus in anticancer drug development. Despite lack successful Ras signaling inhibitors, recent research has identified PDEδ, KRAS transporter, as potential target for inhibiting oncogenic pathway. This study aims to investigate interactions between eight inhibitors (deltarazine, deltaflexin 1 and 2, its analogues) PDEδ understand their binding modes. will utilize computational techniques such density functional theory (DFT) molecular electrostatic surface (MESP), docking, site analyses, dynamic (MD) simulations, electronic structure computations, predictions free energy. Molecular simulations be used predict conformations pharmacophoric features active examined structures. energies determined using MMPB(GB)SA method compared with observed potency values tested compounds. approach enhance understanding selective mechanism, which could contribute novel signaling.

Language: Английский

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QSAR and machine learning-driven proposition of novel 1,3,4-oxadiazoles and structure-based studies of their antibacterial activities against Xanthomonas oryzae

Theoretical Chemistry Accounts, Journal Year: 2025, Volume and Issue: 144(2)

Published: Feb. 1, 2025

Language: Английский

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Can Kisqali® (Ribociclib) effectively target triple-negative breast cancer? A computational insight on potential mechanisms and therapeutic strategies

Discover Chemistry., Journal Year: 2025, Volume and Issue: 2(1)

Published: May 9, 2025

Language: Английский

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Computational design and molecular insights into acetylcholinesterase inhibitors from Aristolochia indica for Alzheimer’s disease therapy

Discover Chemistry., Journal Year: 2025, Volume and Issue: 2(1)

Published: May 24, 2025

Language: Английский

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QSAR aided design of potent c‐Met inhibitors using molecular docking, molecular dynamics simulation and binding free energy calculation

Chemistry & Biodiversity, Journal Year: 2024, Volume and Issue: unknown

Published: Aug. 30, 2024

Abstract The mesenchymal‐epithelial transition factor (c‐Met) is a tyrosine kinase receptor protein, and excessive cell transformation can lead to cancer. Therefore, there an urgent need develop novel inhibitors by inhibiting the activity of c‐Met protein. In this study, 41 compounds are selected from reported literature, interactions between phenoxy pyridine derivatives tumor‐associated proteins systematically investigated using series computer‐assisted drug design (CADD) methods, aiming predict potential with high activity. Topomer CoMFA (q 2 =0.620, R =0.837) HQSAR =0.684, =0.877) models demonstrate level robustness. Further internal external validation assessments show applicability accuracy. Based on results model, structural fragments higher contribution values identified randomly combined fragment splice technique, result in total 20 predicted activities than template molecules. Molecular docking that these have good van der Waals forces target proteins. molecular dynamics ADMET predictions indicate Y4, Y5, Y14 as inhibitors. Among them, compound exhibits superior stability binding free energy −165.18 KJ/mol. These studies provide reference for future development inhibitory

Language: Английский

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Leveraging class-balancing techniques for predicting c-MET Inhibitors: Descriptor Calculation, Selection, and QSAR Model Optimization using Machine Learning

Research Square (Research Square), Journal Year: 2024, Volume and Issue: unknown

Published: Sept. 11, 2024

The rapid emergence of resistance in cancer chemotherapy is a major challenge the drug discovery cancer, restricting action various important classes inhibitors against EGFR, VEGF, BRAF, alkylating agents, and DNA damaging agents. c-MET plays an role development to cancer. Identifying potent inhibitor can improve therapeutic access existing anti-cancer In current study, we propose novel technique for prediction activity class by using balancing ML classifiers. This study utilizes 3091 molecules with inhibitory concentration value (IC₅₀) publicly available from ChEMBL Database. Using 14 descriptors random oversampling balancing, investigated seven classical models, i.e., decision tree (DT), Adaboost (ABDT), K-nearest neighbors (K-NN), support vector machine (SVM), Bernoulli Naïve Bayes (BNB), forest (RF), linear logistic regression (LLR) c-MET. Of which SVM, LR, RF were top three models providing high predictability after applying techniques performing rigorous.hyperparameter tuning. Even though showed exemplary performance terms ROC-AUC recall metrics, their validation on FDA-approved drugs demonstrated susceptibility false negatives. Owing this, developed consensus mechanism based these models. work large, diverse database screen potential inhibitors, prioritizing molecule be considered further experimental testing. model proved beneficial as design algorithm development.

Language: Английский

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Synergistic activity of nootropic herbs as potent therapeutics for Alzheimer's disease: A cheminformatics, pharmacokinetics, and system pharmacology approach

Journal of Alzheimer s Disease Reports, Journal Year: 2024, Volume and Issue: 8(1), P. 1745 - 1762

Published: March 1, 2024

Alzheimer's disease (AD) is a progressive neurodegenerative disorder, which subdues over 55 million people and finding cure, still remains disenchanting. Indian medicinal herbs notably, Withania somnifera, Bacopa monnieri, Curcuma longa, Clitoria ternatea are traditionally utilized for their memory-enhancing properties. We computationally investigated the therapeutic potential of four nootropic by uncovering molecular mechanisms underlying treatment AD. Cheminformatics, pharmacokinetics, system pharmacology studies were carried out to predict phytocompounds drug-like properties, protein targets, targets functional association enrichment analysis. A comparative study was performed with FDA-approved drugs. Investigation on expression in hippocampus entorhinal cortex AD brain performed. Network constructed depict interaction between phytocompounds, drugs, targets. Through analysis, we found that shared common both FDA drugs under clinical trials. identified active compounds Withaferin A, Withanolide-D, Withanolide-E, Withanolide-G, Humulene epoxide II, can combat Interestingly, enzyme inhibition scores much higher than In addition, regulatory proteins such as AβPP, acetylcholinesterase, BACE1, PTPN1 8, 16, 9, 22 respectively. Nonetheless, AR CYP19A, primary most phytocompounds. Herbal medicines synergistically stimulate multiple rendering holistic integrative treatment, encouraging promising avenue treat

Language: Английский

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