QSAR modeling, molecular docking, dynamic simulation and ADMET study of novel tetrahydronaphthalene derivatives as potent antitubercular agents

Moulishankar, Anguraj; Sundarrajan, T.

doi:10.1186/s43088-023-00451-z

Cited by 6 publications

(2 citation statements)

References 56 publications

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“…Following this dataset division, the QSAR model was constructed employing the multiple linear regression (MLR) method and generally validated according to the chemometric approach [41]. This methodology substantiates the direct correlation between the dependent variable Y and the independent variable X, represented by molecular descriptors [42,43]. In multiple linear regression (MLR) analysis, the mean of the dependent variable Y is dependent on X (descriptor).…”

Section: Qsar Model Developmentmentioning

confidence: 99%

Molecular modeling studies of Pyrazolopyrimidine Derivatives as potent Cyclin Dependent Kinase-2 inhibitors

Chagaleti,

2024

Preprint

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This study addresses the pressing need for innovative cancer treatments in the face of global challenges posed by the widespread occurrence of cancer and increasing treatment resistance. The study looks at cyclin-dependent kinase-2 (CDK2) and uses a methodical computer approach to find possible anticancer compounds with pyrazole and pyrimidine structures. (QSAR) quantitative structure-activity relationship has become crucial in lead optimization over the last three decades. A set of 45 pyrazolopyrimidine derivatives with known IC50 values were used to create and test models using QSARINS software. Model 4, with its high predictive performance (R2 = 0.9100, R2adj = 0.8900, LOF = 0.0394), emerges as the most reliable. The resulting QSAR model proves stable, predictive, and robust, effectively representing the original dataset. Active molecular descriptors are identified for predicting the structure-activity relationship. We used SAR analysis and model equation parameters to create sixty compounds and tested them for their predicted bioactivity using Model 4. These compounds are a series with pyrazolopyrimidine-fused piperidine and hybrid moieties, such as methanethione (20), ethenone (20), and benzamide (20). Among the designed series, 16 compounds exhibited pIC50 values exceeding 7, indicating that they were hit molecules represented as C1-C16. These obtained hit molecules undergo further screening with ADMET, molecular docking, and molecular dynamics simulations. C3 and C7, revealed in docking studies with low-energy conformations and sustained binding during simulations, consistently align their binding modes with the standard drug roscovitine. These compounds emerge as promising leads for targeting CDK2 in the development of groundbreaking cancer therapies.

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Section: Qsar Model Developmentmentioning

confidence: 99%

Molecular modeling studies of Pyrazolopyrimidine Derivatives as potent Cyclin Dependent Kinase-2 inhibitors

Chagaleti,

2024

Preprint

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“…To achieve this objective, we used a computer-based drug-designing approach having aims to identify potential drug candidates and targets against drug-resistant strains of MTB [9]. In this present work, we used computational techniques like atom-based three-dimensional quantitative structure active relationship (3D-QSAR), pharmacophore modeling, molecular docking, pharmacokinetic, dynamic, toxicity study, and molecular dynamic simulation study to identify potential multi-targeted drug candidates used to treat drug-resistant tuberculosis [10][11][12].…”

Section: Introductionmentioning

confidence: 99%

Computational approaches: Atom-based 3D-QSAR, molecular docking, ADME-Tox, MD simulation and DFT to find novel multi-targeted Anti-tubercular agents

Panigrahi,

Sahu

2024

Preprint

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Tuberculosis (TB) has become the biggest threat towards human society due to the rapid rise in resistance of the causative bacteria Mycobacterium tuberculosis (MTB) against the available anti-tubercular drugs. There is an urgent need to design new multi-targeted anti-tubercular agents to overcome the resistance species of MTB through computational design tools. With this aim in the present work, a combination of atom-based three-dimensional quantitative structure-activity relationship (3D-QSAR), six-point pharmacophore (AHHRRR), and molecular docking analysis was performed on a series of fifty-eight anti-tubercular agents. The generated QSAR model showed statistically significant correlation co-efficient R2, Q2, and Pearson r-factor of 0.9521, 0.8589, and 0.8988 respectively indicating good predictive ability. Molecular docking study was performed for the data set of compounds with the two important anti-tubercular target proteins, Enoyl acyl carrier protein reductase (InhA) (PDBID: 2NSD) and Decaprenyl phosphoryl-β-D-Ribose 20-epimerase (DprE1) (PDBID: 4FDO). Using the similarity search principle virtual screening was performed on 237 compounds retrieved from the Pubchem database to identify potent multitargeted anti-tubercular agents. The screened compound, MK3 showed the highest docking score of -9.2 and − 8.3 Kj/mol towards both the target proteins InhA and DprE1 were picked for 100ns molecular dynamic simulation study using GROMACS. From the data generated, the compound MK3 showed thermodynamic stability and effective binding within the active binding pocket of both target proteins without much deviation. The result of the highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO) and energy gap analysis predicts the molecular reactivity and stability of the identified molecule. Based on the result of the above studies the proposed compound MK3 can be successfully used for the development of a novel multi-targeted anti-tubercular agent with high binding affinity and favourable ADME-T properties.

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Pharmacophore, QSAR, molecular docking, molecular dynamics and ADMET study of trisubstituted benzimidazole derivatives as potent anti-tubercular agents

Moulishankar,

Sundarrajan

2024

Chemical Physics Impact

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QSAR modeling, molecular docking, dynamic simulation and ADMET study of novel tetrahydronaphthalene derivatives as potent antitubercular agents

Cited by 6 publications

References 56 publications

Molecular modeling studies of Pyrazolopyrimidine Derivatives as potent Cyclin Dependent Kinase-2 inhibitors

Molecular modeling studies of Pyrazolopyrimidine Derivatives as potent Cyclin Dependent Kinase-2 inhibitors

Computational approaches: Atom-based 3D-QSAR, molecular docking, ADME-Tox, MD simulation and DFT to find novel multi-targeted Anti-tubercular agents

Pharmacophore, QSAR, molecular docking, molecular dynamics and ADMET study of trisubstituted benzimidazole derivatives as potent anti-tubercular agents

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