AI Medical Compendium Journal:
SAR and QSAR in environmental research

Showing 1 to 10 of 46 articles

Modelling of intrinsic membrane permeability of drug molecules by explainable ML-based q-RASPR approach towards better pharmacokinetics and toxicokinetics properties.

SAR and QSAR in environmental research Apr 7, 2025
Drug discovery's success lies in potent inhibition against a target and optimum pharmacokinetic and toxicokinetic properties of drug molecules. Membrane permeability is a crucial factor in determining the absorption, distribution, metabolism, and exc...
Machine Learning Algorithms Cell Membrane Permeability Permeability Pharmacokinetics Quantitative Structure-Activity Relationship Pharmaceutical Preparations Toxicokinetics
View on PubMed DOI

Binding mechanism of inhibitors to DFG-in and DFG-out P38α deciphered using multiple independent Gaussian accelerated molecular dynamics simulations and deep learning.

SAR and QSAR in environmental research Mar 20, 2025
P38α has been identified as a key target for drug design to treat a wide range of diseases. In this study, multiple independent Gaussian accelerated molecular dynamics (GaMD) simulations, deep learning (DL), and the molecular mechanics generalized Bo...
Quantitative Structure-Activity Relationship Drug Design Mitogen-Activated Protein Kinase 14 Protein Binding Molecular Dynamics Simulation Deep Learning
View on PubMed DOI

Enhanced in silico QSAR-based screening of butyrylcholinesterase inhibitors using multi-feature selection and machine learning.

SAR and QSAR in environmental research Feb 21, 2025
Butyrylcholinesterase inhibition offers one of the formulated solutions to tackle the aggravating symptoms of dementia that downgrades to cholinergic neuronal loss in Alzheimer's disease. We developed a QSAR model to facilitate the identification of ...
Humans Machine Learning Algorithms Computer Simulation Cholinesterase Inhibitors Quantitative Structure-Activity Relationship Drug Discovery Butyrylcholinesterase
View on PubMed DOI

Uncovering blood-brain barrier permeability: a comparative study of machine learning models using molecular fingerprints, and SHAP explainability.

SAR and QSAR in environmental research Jan 8, 2025
This study illustrates the use of chemical fingerprints with machine learning for blood-brain barrier (BBB) permeability prediction. Employing the Blood Brain Barrier Database (B3DB) dataset for BBB permeability prediction, we extracted nine differen...
Quantitative Structure-Activity Relationship Machine Learning Algorithms Support Vector Machine Permeability Blood-Brain Barrier
View on PubMed DOI

Unveiling key drivers of hepatocellular carcinoma: a synergistic approach with network pharmacology, machine learning-driven ligand discovery and dynamic simulations.

SAR and QSAR in environmental research Jan 3, 2025
Hepatocellular carcinoma (HCC) ranks fourth in cancer-related mortality worldwide. This study aims to uncover the genes and pathways involved in HCC through network pharmacology (NP) and to discover potential drugs via machine learning (ML)-based lig...
Humans Machine Learning Drug Discovery Liver Neoplasms Molecular Docking Simulation Glycogen Synthase Kinase 3 beta Network Pharmacology Molecular Dynamics Simulation Ligands Carcinoma, Hepatocellular Quantitative Structure-Activity Relationship Proto-Oncogene Proteins c-akt
View on PubMed DOI

Enhanced prediction of beta-secretase inhibitory compounds with mol2vec technique and machine learning algorithms.

SAR and QSAR in environmental research Dec 20, 2024
A comprehensive computational strategy that combined QSAR modelling, molecular docking, and ADMET analysis was used to discover potential inhibitors for β-secretase 1 (BACE-1). A dataset of 1,138 compounds with established BACE-1 inhibitory activitie...
Algorithms Molecular Docking Simulation Molecular Dynamics Simulation Machine Learning Quantitative Structure-Activity Relationship Enzyme Inhibitors Amyloid Precursor Protein Secretases
View on PubMed DOI

A deep learning model based on the BERT pre-trained model to predict the antiproliferative activity of anti-cancer chemical compounds.

SAR and QSAR in environmental research Nov 28, 2024
Identifying new compounds with minimal side effects to enhance patients' quality of life is the ultimate goal of drug discovery. Due to the expensive and time-consuming nature of experimental investigations and the scarcity of data in traditional QSA...
Cell Proliferation Quantitative Structure-Activity Relationship Deep Learning Cell Line, Tumor Drug Discovery Antineoplastic Agents Humans
View on PubMed DOI

Molecular mechanism underlying effect of D93 and D289 protonation states on inhibitor-BACE1 binding: exploration from multiple independent Gaussian accelerated molecular dynamics and deep learning.

SAR and QSAR in environmental research Nov 8, 2024
BACE1 has been regarded as an essential drug design target for treating Alzheimer's disease (AD). Multiple independent Gaussian accelerated molecular dynamics simulations (GaMD), deep learning (DL), and molecular mechanics general Born surface area (...
Quantitative Structure-Activity Relationship Drug Design Deep Learning Hydrogen Bonding Molecular Dynamics Simulation Protons Amyloid Precursor Protein Secretases Aspartic Acid Endopeptidases
View on PubMed DOI

Deciphering Cathepsin K inhibitors: a combined QSAR, docking and MD simulation based machine learning approaches for drug design.

SAR and QSAR in environmental research Oct 9, 2024
Cathepsin K (CatK), a lysosomal cysteine protease, contributes to skeletal abnormalities, heart diseases, lung inflammation, and central nervous system and immune disorders. Currently, CatK inhibitors are associated with severe adverse effects, there...
Molecular Docking Simulation Drug Design Molecular Dynamics Simulation Machine Learning Quantitative Structure-Activity Relationship Cathepsin K
View on PubMed DOI

A SAR and QSAR study on 3CLpro inhibitors of SARS-CoV-2 using machine learning methods.

SAR and QSAR in environmental research Jul 30, 2024
The 3C-like Proteinase (3CLpro) of novel coronaviruses is intricately linked to viral replication, making it a crucial target for antiviral agents. In this study, we employed two fingerprint descriptors (ECFP_4 and MACCS) to comprehensively character...
Support Vector Machine Quantitative Structure-Activity Relationship Cysteine Endopeptidases Betacoronavirus Coronavirus 3C Proteases SARS-CoV-2 Antiviral Agents Protease Inhibitors Machine Learning COVID-19
View on PubMed DOI
Popular Topics
Popular Journals