AIMC Journal:
Journal of chemical information and modeling

Showing 171 to 180 of 934 articles

AABBA Graph Kernel: Atom-Atom, Bond-Bond, and Bond-Atom Autocorrelations for Machine Learning.

Journal of chemical information and modeling Nov 24, 2024
Graphs are one of the most natural and powerful representations available for molecules; natural because they have an intuitive correspondence to skeletal formulas, the language used by chemists worldwide, and powerful, because they are highly expres...
Models, Molecular Machine Learning
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Improved Prediction of Ligand-Protein Binding Affinities by Meta-modeling.

Journal of chemical information and modeling Nov 22, 2024
The accurate screening of candidate drug ligands against target proteins through computational approaches is of prime interest to drug development efforts. Such virtual screening depends in part on methods to predict the binding affinity between liga...
Ligands Deep Learning Databases, Protein Molecular Docking Simulation Proteins Protein Binding
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The Application of Machine Learning in Doping Detection.

Journal of chemical information and modeling Nov 22, 2024
Detecting doping agents in sports poses a significant challenge due to the continuous emergence of new prohibited substances and methods. Traditional detection methods primarily rely on targeted analysis, which is often labor-intensive and is suscept...
Doping in Sports Humans Metabolomics Machine Learning Substance Abuse Detection Biomarkers
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Matini-Net: Versatile Material Informatics Research Framework for Feature Engineering and Deep Neural Network Design.

Journal of chemical information and modeling Nov 21, 2024
In this study, we introduced Matini-Net, which is a versatile framework for feature engineering and automated architecture design for materials informatics research using deep neural networks. Matini-Net provides the flexibility to design feature-bas...
Informatics Materials Science Neural Networks, Computer Deep Learning
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Exploring the Potential of Adaptive, Local Machine Learning in Comparison to the Prediction Performance of Global Models: A Case Study from Bayer's Caco-2 Permeability Database.

Journal of chemical information and modeling Nov 20, 2024
Machine learning (ML) techniques are being widely implemented to fill the gap in simple molecular design guidelines for newer therapeutic modalities in the extended and beyond rule of five chemical space (eRo5, bRo5). These ML techniques predict mole...
Permeability Machine Learning Humans Caco-2 Cells Databases, Factual Algorithms
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ConfRank: Improving GFN-FF Conformer Ranking with Pairwise Training.

Journal of chemical information and modeling Nov 20, 2024
Conformer ranking is a crucial task for drug discovery, with methods for generating conformers often based on molecular (meta)dynamics or sophisticated sampling techniques. These methods are constrained by the underlying force computation regarding r...
Molecular Dynamics Simulation Machine Learning Molecular Conformation Drug Discovery
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CPIScore: A Deep Learning Approach for Rapid Scoring and Interpretation of Protein-Ligand Binding Interactions.

Journal of chemical information and modeling Nov 19, 2024
Protein-ligand binding affinity prediction is a crucial and challenging task in the field of drug discovery. However, traditional simulation-based computational approaches are often prohibitively time-consuming, limiting their practical utility. In t...
Small Molecule Libraries Ligands Deep Learning Proteins Protein Binding Drug Discovery
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ProAffinity-GNN: A Novel Approach to Structure-Based Protein-Protein Binding Affinity Prediction via a Curated Data Set and Graph Neural Networks.

Journal of chemical information and modeling Nov 18, 2024
Protein-protein interactions (PPIs) are crucial for understanding biological processes and disease mechanisms, contributing significantly to advances in protein engineering and drug discovery. The accurate determination of binding affinities, essenti...
Neural Networks, Computer Databases, Protein Models, Molecular Proteins Protein Binding Protein Interaction Mapping Protein Conformation
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Transparent Machine Learning Model to Understand Drug Permeability through the Blood-Brain Barrier.

Journal of chemical information and modeling Nov 18, 2024
The blood-brain barrier (BBB) selectively regulates the passage of chemical compounds into and out of the central nervous system (CNS). As such, understanding the permeability of drug molecules through the BBB is key to treating neurological diseases...
Permeability Models, Biological Machine Learning Pharmaceutical Preparations Humans Blood-Brain Barrier
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A Divide-and-Conquer Approach to Nanoparticle Global Optimisation Using Machine Learning.

Journal of chemical information and modeling Nov 15, 2024
Global optimization of the structure of atomic nanoparticles is often hampered by the presence of many funnels on the potential energy surface. While broad funnels are readily encountered and easily exploited by the search, narrow funnels are more di...
Machine Learning Metal Nanoparticles Thermodynamics Models, Molecular Nanoparticles
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