AIMC Topic: Cheminformatics

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Augmenting MACCS Keys with Persistent Homology Fingerprints for Protein-Ligand Binding Classification.

Journal of chemical information and modeling Jul 25, 2025
Machine learning has become an essential tool in computational drug design, enabling models to uncover patterns in molecular data and predict protein-ligand interactions. This study introduces a novel approach by integrating persistence images with M...
Machine Learning Drug Design Neural Networks, Computer Ligands Cheminformatics Protein Binding Proteins
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Machine learning and cheminformatics-based Identification of lichen-derived compounds targeting mutant PBP4 in Staphylococcus aureus.

Molecular diversity Feb 15, 2025
Penicillin-binding protein 4 (PBP4) is essential in imparting significant β-lactam antibiotics resistance in Staphylococcus aureus (S. aureus) and the mutation R200L in PBP4 is linked to β-lactam non-susceptibility in natural strains, complicating tr...
Mutation Molecular Dynamics Simulation Staphylococcus aureus Bacterial Proteins Penicillin-Binding Proteins Lichens Cheminformatics Machine Learning Anti-Bacterial Agents Molecular Docking Simulation
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HiRXN: Hierarchical Attention-Based Representation Learning for Chemical Reaction.

Journal of chemical information and modeling Feb 3, 2025
In recent years, natural language processing (NLP) techniques, including large language modeling (LLM), have contributed significantly to advancements in organic chemistry research. Chemical reaction representations provide a link between NLP models ...
Cheminformatics Machine Learning Natural Language Processing
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HDAC3_VS_assistant: cheminformatics-driven discovery of histone deacetylase 3 inhibitors.

Molecular diversity Dec 23, 2024
Histone deacetylase 3 (HDAC3) inhibitors keep significant therapeutic promise for treating oncological, neurodegenerative, and inflammatory diseases. In this work, we developed robust QSAR regression models for HDAC3 inhibitory activity and acute tox...
Humans Histone Deacetylases Histone Deacetylase Inhibitors Machine Learning Molecular Docking Simulation Mice Cheminformatics Animals Quantitative Structure-Activity Relationship Drug Discovery
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Molecular tweaking by generative cheminformatics and ligand-protein structures for rational drug discovery.

Bioorganic chemistry Oct 28, 2024
The purpose of this review is two-fold: (1) to summarize artificial intelligence and machine learning approaches and document the role of ligand-protein structures in directing drug discovery; (2) to present examples of drugs from the recent literatu...
Humans Artificial Intelligence Machine Learning Cheminformatics Molecular Structure Drug Discovery Proteins Ligands
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Chemoinformatics for corrosion science: Data-driven modeling of corrosion inhibition by organic molecules.

Molecular informatics Oct 15, 2024
This paper reviews the application of machine learning to the inhibition of corrosion by organic molecules. The methodologies considered include quantitative structure-property relationships (QSPR) and related data-driven approaches. The characterist...
Cheminformatics Corrosion Organic Chemicals Machine Learning Quantitative Structure-Activity Relationship
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Deciphering Molecular Embeddings with Centered Kernel Alignment.

Journal of chemical information and modeling Sep 25, 2024
Analyzing machine learning models, especially nonlinear ones, poses significant challenges. In this context, centered kernel alignment (CKA) has emerged as a promising model analysis tool that assesses the similarity between two embeddings. CKA's eff...
Cheminformatics Algorithms Models, Molecular Neural Networks, Computer Machine Learning
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Research Progresses and Applications of Knowledge Graph Embedding Technique in Chemistry.

Journal of chemical information and modeling Sep 20, 2024
A knowledge graph (KG) is a technique for modeling entities and their interrelations. Knowledge graph embedding (KGE) translates these entities and relationships into a continuous vector space to facilitate dense and efficient representations. In the...
Databases, Chemical Humans Cheminformatics Neural Networks, Computer Drug Discovery
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MolPipeline: A Python Package for Processing Molecules with RDKit in Scikit-learn.

Journal of chemical information and modeling Sep 17, 2024
The open-source package scikit-learn provides various machine learning algorithms and data processing tools, including the Pipeline class, which allows users to prepend custom data transformation steps to the machine learning model. We introduce the ...
Machine Learning Software Cheminformatics Algorithms Programming Languages
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Molecular similarity in chemical informatics and predictive toxicity modeling: from quantitative read-across (q-RA) to quantitative read-across structure-activity relationship (q-RASAR) with the application of machine learning.

Critical reviews in toxicology Sep 3, 2024
This article aims to provide a comprehensive critical, yet readable, review of general interest to the chemistry community on molecular similarity as applied to chemical informatics and predictive modeling with a special focus on read-across (RA) and...
Cheminformatics Structure-Activity Relationship Quantitative Structure-Activity Relationship Machine Learning Animals Humans
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