4.5 Review

R software for QSAR analysis in phytopharmacological studies

Related references

Note: Only part of the references are listed.
Article Chemistry, Multidisciplinary

Computational identification of natural product inhibitors against EGFR double mutant (T790M/L858R) by integrating ADMET, machine learning, molecular docking and a dynamics approach

Subhash M. Agarwal et al.

Summary: This study screened nearly 150,000 molecules from natural product libraries using different techniques to discover new inhibitors against the T790M/L858R resistant mutation. Three molecules with interactions similar to the co-crystallized complex were selected and underwent molecular dynamics simulation for stability analysis. The results showed that these molecules have comparable binding energy to the native ligand and exhibit potential for inhibiting the double mutated drug-resistant EGFR.

RSC ADVANCES (2022)

Article Biochemistry & Molecular Biology

A molecular modeling approach to identify effective antiviral phytochemicals against the main protease of SARS-CoV-2

Rajib Islam et al.

Summary: The study identified potential inhibitors against SARS-CoV-2 main protease from 40 antiviral phytochemicals via molecular docking and molecular dynamics simulations. A QSAR model was established to predict favorable binding energy, and the selected candidates were found to be safer inhibitors through ADMET analysis. The computational and statistical analysis supported the potential of these phytochemicals as antiviral agents against SARS-CoV-2.

JOURNAL OF BIOMOLECULAR STRUCTURE & DYNAMICS (2021)

Review Biochemical Research Methods

Recent Trends in QSAR in Modelling of Drug-Protein and Protein-Protein Interactions

Smriti Sharma et al.

Summary: The unprecedented growth in the area of QSAR has revolutionized drug discovery by quantitatively correlating chemical structure alterations with changes in biological activity, thus enhancing the potency and efficacy of lead compounds. Recent trends in using 3D-QSAR to understand Protein-Protein Interactions (PPIs) have been explored, along with advancements in chemical Space (CS) and chemography. Validators emphasize the importance of systematically validating models both internally and externally to improve hit rates in experiments, and stress the necessity of choosing methods specific to target-ligand systems.

COMBINATORIAL CHEMISTRY & HIGH THROUGHPUT SCREENING (2021)

Article Biochemistry & Molecular Biology

Deciphering the Interactions of Bioactive Compounds in Selected Traditional Medicinal Plants against Alzheimer's Diseases via Pharmacophore Modeling, Auto-QSAR, and Molecular Docking Approaches

Oluwafemi Adeleke Ojo et al.

Summary: Flavonoid compounds from medicinal plants were evaluated for their inhibitory role on AChE, BChE, and MAO activity, with pharmacophore modeling, auto-QSAR prediction, and molecular studies used. The study produced pharmacophore models that identified active compounds with a high success rate, and machine learning-based models were used to predict bioactivities with promising results. Docking studies revealed potential lead compounds for drug improvement against neurodegenerative diseases.

MOLECULES (2021)

Article Chemistry, Multidisciplinary

QSAR models for insecticidal properties of plant essential oils on the housefly (Musca domestica L.)

P. R. Duchowicz et al.

Summary: The study predicts the fumigant and topical activities of 27 plant-derived essential oils on adult houseflies using Quantitative Structure-Activity Relationship (QSAR) theory. Multivariable linear regression models are developed to describe the insecticidal activity of the complex mixtures analyzed in this study.

SAR AND QSAR IN ENVIRONMENTAL RESEARCH (2021)

Article Biology

Antiviral phytochemicals as potent inhibitors against NS3 protease of dengue virus

Md. Mahbubur Rahman et al.

Summary: The study focused on finding potential inhibitors against the NS3 protease of the dengue virus through systematic screening. Among 40 antiviral phytochemicals, Cyanidin 3-Glucoside, Dithymoquinone, and Glabridin were predicted to be potent inhibitors based on their binding affinity. The ligand-protein complexes were further analyzed through molecular dynamics simulation and binding free energy calculation to investigate their binding stability, indicating potential effectiveness of these inhibitors.

COMPUTERS IN BIOLOGY AND MEDICINE (2021)

Review Chemistry, Multidisciplinary

QSAR without borders

Eugene N. Muratov et al.

CHEMICAL SOCIETY REVIEWS (2020)

Article Computer Science, Artificial Intelligence

Descriptor Free QSAR Modeling Using Deep Learning With Long Short-Term Memory Neural Networks

Suman K. Chakravarti et al.

FRONTIERS IN ARTIFICIAL INTELLIGENCE (2019)

Review Pharmacology & Pharmacy

Machine learning in chemoinformatics and drug discovery

Yu-Chen Lo et al.

DRUG DISCOVERY TODAY (2018)

Article Biochemical Research Methods

Prediction of Anti-Alzheimer's Activity of Flavonoids Targeting Acetylcholinesterase in silico

Subrata Das et al.

PHYTOCHEMICAL ANALYSIS (2017)

Article Chemistry, Medicinal

Molecular docking, QSAR and ADMET studies of withanolide analogs against breast cancer

Dharmendra K. Yadav et al.

DRUG DESIGN DEVELOPMENT AND THERAPY (2017)

Article Chemistry, Medicinal

Beware of R2: Simple, Unambiguous Assessment of the Prediction Accuracy of QSAR and QSPR Models

D. L. J. Alexander et al.

JOURNAL OF CHEMICAL INFORMATION AND MODELING (2015)

Article Chemistry, Medicinal

QSAR Modeling: Where Have You Been? Where Are You Going To?

Artem Cherkasov et al.

JOURNAL OF MEDICINAL CHEMISTRY (2014)

Review Biochemistry & Molecular Biology

LINEAR QSPR/QSAR MODELS: RIGOROUS EVALUATION OF VARIABLE SELECTION FOR PLS

Kurt Varmuza et al.

COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL (2013)

Review Pharmacology & Pharmacy

QSAR of phytochemicals for the design of better drugs

Supratik Kar et al.

EXPERT OPINION ON DRUG DISCOVERY (2012)

Article Chemistry, Analytical

Feature Selection Methods in QSAR Studies

Mohammad Goodarzi et al.

JOURNAL OF AOAC INTERNATIONAL (2012)

Article Biochemistry & Molecular Biology

In vitro and QSAR studies of cucurbitacins on HepG2 and HSC-T6 liver cell lines

Judit Bartalis et al.

BIOORGANIC & MEDICINAL CHEMISTRY (2011)

Article Biodiversity Conservation

ENMTools: a toolbox for comparative studies of environmental niche models

Dan L. Warren et al.

ECOGRAPHY (2010)

Review Chemistry, Medicinal

Best Practices for QSAR Model Development, Validation, and Exploitation

Alexander Tropsha

MOLECULAR INFORMATICS (2010)

Review Biochemistry & Molecular Biology

Current Mathematical Methods Used in QSAR/QSPR Studies

Peixun Liu et al.

INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES (2009)

Article Biotechnology & Applied Microbiology

Magic shotguns versus magic bullets: selectively non-selective drugs for mood disorders and schizophrenia

BL Roth et al.

NATURE REVIEWS DRUG DISCOVERY (2004)

Article Chemistry, Physical

Synergistic interactions among QSAR descriptors

SC Peterangelo et al.

INTERNATIONAL JOURNAL OF QUANTUM CHEMISTRY (2004)

Article Biochemistry & Molecular Biology

3D QSAR studies on binding affinities of coumarin natural products for glycosomal GAPDH of Trypanosoma cruzi

IRA Menezes et al.

JOURNAL OF COMPUTER-AIDED MOLECULAR DESIGN (2003)

Article Chemistry, Multidisciplinary

QSAR Modeling using chirality descriptors derived from molecular topology

A Golbraikh et al.

JOURNAL OF CHEMICAL INFORMATION AND COMPUTER SCIENCES (2003)