AI Medical Compendium Journal:
Journal of molecular graphics & modelling

Showing 1 to 10 of 42 articles

Generating a vast chemical space for high polar surface area triphenylamine polymers by machine learning-DFT calculations assisted reverse engineering for photovoltaics.

Journal of molecular graphics & modelling May 14, 2025
The total polar surface area (TPSA) is a crucial parameter in photovoltaic (PV) materials, as it directly influences their solubility, processability, and device performance. This study leverages machine learning-assisted reverse engineering to gener...
Models, Molecular Polymers Aniline Compounds Solar Energy Machine Learning Algorithms Density Functional Theory
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Supervised machine learning and molecular docking modeling to identify potential Anti-Parkinson's agents.

Journal of molecular graphics & modelling May 9, 2025
Parkinson's disease is a neurodegenerative condition that affects the brain's neurons, and causes malfunction of nerve cells and their death. A neurotransmitter called dopamine interacts with the part of the brain in charge of coordination and moveme...
Molecular Docking Simulation Protein Binding Humans Machine Learning Ligands Parkinson Disease Antiparkinson Agents Supervised Machine Learning Receptor, Adenosine A2A
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Interpretable machine learning and graph attention network based model for predicting PAMPA permeability.

Journal of molecular graphics & modelling Apr 13, 2025
Parallel artificial membrane permeability assay (PAMPA) is widely used in the early phases of drug discovery as it is quite robust and offers high throughput. It serves as a platform for assessing the permeability and absorption of pharmaceutical com...
Machine Learning Drug Discovery Permeability Membranes, Artificial
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Molecular property prediction based on graph contrastive learning with partial feature masking.

Journal of molecular graphics & modelling Mar 17, 2025
Molecular representation learning facilitates multiple downstream tasks such as molecular property prediction (MPP) and drug design. Recent studies have shown great promise in applying self-supervised learning (SSL) to cope with the data scarcity in ...
Drug Design Machine Learning Algorithms
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Computational discovery of novel PI3KC2α inhibitors using structure-based pharmacophore modeling, machine learning and molecular dynamic simulation.

Journal of molecular graphics & modelling Mar 15, 2025
PI3KC2α is a lipid kinase associated with cancer metastasis and thrombosis. In this study, we present a novel computational workflow integrating structure-based pharmacophore modeling, machine learning (ML), and molecular dynamics (MD) simulations to...
Ligands Protein Kinase Inhibitors Phosphatidylinositol 3-Kinases Molecular Dynamics Simulation Phosphoinositide-3 Kinase Inhibitors Pharmacophore Machine Learning Molecular Docking Simulation Drug Discovery Protein Binding Humans
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DeepTree-AAPred: Binary tree-based deep learning model for anti-angiogenic peptides prediction.

Journal of molecular graphics & modelling Feb 24, 2025
Anti-angiogenic peptides (AAPs) show important potential in tumor therapy by limiting the growth and metastasis of tumor cells. Accurate prediction of AAPs is of very positive significance for the therapeutic efficacy of tumors. The high cost of wet ...
Computational Biology Angiogenesis Inhibitors Peptides Deep Learning Humans Algorithms
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Supercapacitor Materials Database Generated using Web Scrapping and Natural Language Processing.

Journal of molecular graphics & modelling Feb 13, 2025
Electrochemical energy storage plays a vital role in achieving environmental sustainability. Supercapacitors emerge as promising alternatives to batteries due to their high-power density and extended lifespan. Extensive scholarly research has been co...
Databases, Factual Natural Language Processing Electric Power Supplies Internet Electric Capacitance Electrodes
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DFT and machine learning integration to predict efficiency of modified metal-free dyes in DSSCs.

Journal of molecular graphics & modelling Feb 6, 2025
Power conversion efficiency (PCE) prediction in dye-sensitized solar cells (DSSCs) increasingly relies on computation and machine learning, lowering experimental demands and accelerating materials discovery. In this work we incorporated quantum-chemi...
Machine Learning Density Functional Theory Coloring Agents Solar Energy Models, Molecular
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Estimating AChE inhibitors from MCE database by machine learning and atomistic calculations.

Journal of molecular graphics & modelling Nov 14, 2024
Acetylcholinesterase (AChE) is one of the most successful targets for the treatment of Alzheimer's disease (AD). Inhibition of AChE can result in preventing AD. In this context, the machine-learning (ML) model, molecular docking, and molecular dynami...
Databases, Chemical Molecular Dynamics Simulation Binding Sites Ligands Humans Acetylcholinesterase Molecular Docking Simulation Machine Learning Protein Binding Cholinesterase Inhibitors
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QSPR modeling to predict surface tension of psychoanaleptic drugs using the hybrid DA-SVR algorithm.

Journal of molecular graphics & modelling Oct 23, 2024
A robust Quantitative Structure-Property Relationship (QSPR) model was presented to predict the surface tension property of psychoanaleptic (psychostimulant and antidepressant) drugs. A dataset of 112 molecules was utilized, and three feature selecti...
Algorithms Support Vector Machine Quantitative Structure-Activity Relationship Surface Tension Models, Molecular Least-Squares Analysis
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