AIMC Journal:
Journal of chemical information and modeling

Showing 301 to 310 of 934 articles

Empowering Graph Neural Networks with Block-Based Dual Adaptive Deep Adjustment for Drug Resistance-Related NcRNA Discovery.

Journal of chemical information and modeling Mar 24, 2024
Drug resistance to chemotherapeutic agents remains a formidable challenge in cancer treatment, significantly impacting treatment efficacy. Extensive research has exposed the intimate involvement of noncoding RNAs (ncRNAs) in conferring resistance to ...
Computational Biology Neural Networks, Computer Humans Drug Resistance, Neoplasm Deep Learning RNA, Untranslated
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Discovery of Covalent Lead Compounds Targeting 3CL Protease with a Lateral Interactions Spiking Neural Network.

Journal of chemical information and modeling Mar 23, 2024
Covalent drugs exhibit advantages in that noncovalent drugs cannot match, and covalent docking is an important method for screening covalent lead compounds. However, it is difficult for covalent docking to screen covalent compounds on a large scale b...
Coronavirus 3C Proteases COVID-19 Drug Treatment Protease Inhibitors Protein Binding COVID-19 Humans Deep Learning Molecular Docking Simulation SARS-CoV-2 Antiviral Agents Neural Networks, Computer Drug Discovery
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LGGA-MPP: Local Geometry-Guided Graph Attention for Molecular Property Prediction.

Journal of chemical information and modeling Mar 22, 2024
Molecular property prediction is a fundamental task of drug discovery. With the rapid development of deep learning, computational approaches for predicting molecular properties are experiencing increasing popularity. However, these existing methods o...
Neural Networks, Computer Drug Discovery Deep Learning Models, Molecular
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PROTACable Is an Integrative Computational Pipeline of 3-D Modeling and Deep Learning To Automate the De Novo Design of PROTACs.

Journal of chemical information and modeling Mar 19, 2024
Proteolysis-targeting chimeras (PROTACs) that engage two biological targets at once are a promising technology in degrading clinically relevant protein targets. Since factors that influence the biological activities of PROTACs are more complex than t...
Models, Molecular Drug Design Ubiquitin-Protein Ligases Proteolysis Deep Learning Proteolysis Targeting Chimera
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An Unsupervised Machine Learning Approach for the Automatic Construction of Local Chemical Descriptors.

Journal of chemical information and modeling Mar 18, 2024
Condensing the many physical variables defining a chemical system into a fixed-size array poses a significant challenge in the development of chemical Machine Learning (ML). Atom Centered Symmetry Functions (ACSFs) offer an intuitive featurization ap...
Normal Distribution Molecular Dynamics Simulation Automation Unsupervised Machine Learning
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In Silico Prediction of Oral Acute Rodent Toxicity Using Consensus Machine Learning.

Journal of chemical information and modeling Mar 18, 2024
Acute oral toxicity (AOT) is required for the classification and labeling of chemicals according to the global harmonized system (GHS). Acute oral toxicity studies are optimized to minimize the use of animals. However, with the advent of the three p...
Rats Administration, Oral Mice Toxicity Tests, Acute Rodentia Machine Learning Computer Simulation Animals
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Enhancing Multi-species Liver Microsomal Stability Prediction through Artificial Intelligence.

Journal of chemical information and modeling Mar 18, 2024
Liver microsomal stability, a crucial aspect of metabolic stability, significantly impacts practical drug discovery. However, current models for predicting liver microsomal stability are based on limited molecular information from a single species. T...
Humans Artificial Intelligence Mice Rats Machine Learning Animals Pharmaceutical Preparations Drug Discovery Microsomes, Liver
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Exploring Chemical Reaction Space with Machine Learning Models: Representation and Feature Perspective.

Journal of chemical information and modeling Mar 15, 2024
Chemical reactions serve as foundational building blocks for organic chemistry and drug design. In the era of large AI models, data-driven approaches have emerged to innovate the design of novel reactions, optimize existing ones for higher yields, an...
Models, Chemical Machine Learning
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Self-Supervised Contrastive Molecular Representation Learning with a Chemical Synthesis Knowledge Graph.

Journal of chemical information and modeling Mar 14, 2024
Self-supervised molecular representation learning has demonstrated great promise in bridging machine learning and chemical science to accelerate the development of new drugs. Due to the limited reaction data, existing methods are mostly pretrained by...
Machine Learning Pattern Recognition, Automated
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LinChemIn: Route Arithmetic─Operations on Digital Synthetic Routes.

Journal of chemical information and modeling Mar 13, 2024
Computational tools are revolutionizing our understanding and prediction of chemical reactivity by combining traditional data analysis techniques with new predictive models. These tools extract additional value from the reaction data , but to effecti...
Artificial Intelligence Software Humans
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