AIMC Topic: Drug Discovery

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In Silico Prediction of Human and Rat Liver Microsomal Stability via Machine Learning Methods.

Chemical research in toxicology Sep 2, 2022
Liver microsomal stability is an important property considered for the screening of drug candidates in the early stage of drug development. Determination of hepatic metabolic stability can be performed by an in vitro assay, but it requires quite a fe...
Humans Machine Learning Animals Drug Discovery Rats Liver Microsomes, Liver
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Evaluating molecular representations in machine learning models for drug response prediction and interpretability.

Journal of integrative bioinformatics Aug 26, 2022
Machine learning (ML) is increasingly being used to guide drug discovery processes. When applying ML approaches to chemical datasets, molecular descriptors and fingerprints are typically used to represent compounds as numerical vectors. However, in r...
Machine Learning Drug Discovery
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Molecular Design Method Using a Reversible Tree Representation of Chemical Compounds and Deep Reinforcement Learning.

Journal of chemical information and modeling Aug 12, 2022
Automatic design of molecules with specific chemical and biochemical properties is an important process in material informatics and computational drug discovery. In this study, we designed a novel coarse-grained tree representation of molecules (Reve...
Learning Drug Discovery Deep Learning Reinforcement, Psychology
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Inferring Drug-Target Interactions Based on Random Walk and Convolutional Neural Network.

IEEE/ACM transactions on computational biology and bioinformatics Aug 8, 2022
Computational strategies for identifying new drug-target interactions (DTIs) can guide the process of drug discovery, reduce the cost and time of drug development, and thus promote drug development. Most recently proposed methods predict DTIs via int...
Neural Networks, Computer Algorithms Drug Discovery Drug Development Proteins
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CSatDTA: Prediction of Drug-Target Binding Affinity Using Convolution Model with Self-Attention.

International journal of molecular sciences Jul 30, 2022
Drug discovery, which aids to identify potential novel treatments, entails a broad range of fields of science, including chemistry, pharmacology, and biology. In the early stages of drug development, predicting drug-target affinity is crucial. The pr...
Neural Networks, Computer Drug Discovery Drug Development
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Predicting compound-protein interaction using hierarchical graph convolutional networks.

PloS one Jul 21, 2022
MOTIVATION: Convolutional neural networks have enabled unprecedented breakthroughs in a variety of computer vision tasks. They have also drawn much attention from other domains, including drug discovery and drug development. In this study, we develop...
Neural Networks, Computer Drug Discovery Amino Acid Sequence
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A special issue on artificial intelligence for drug discovery.

Bioorganic & medicinal chemistry Jul 14, 2022
Artificial Intelligence Drug Discovery Quantitative Structure-Activity Relationship
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Industrializing AI-powered drug discovery: lessons learned from the computing platform.

Expert opinion on drug discovery Jul 10, 2022
INTRODUCTION: As a mid-size international pharmaceutical company, we initiated 4 years ago the launch of a dedicated high-throughput computing platform supporting drug discovery. The platform named ' was built up on the initial predicate to capitaliz...
Humans Artificial Intelligence Precision Medicine Drug Discovery
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AI-based prediction of new binding site and virtual screening for the discovery of novel P2X3 receptor antagonists.

European journal of medicinal chemistry Jul 1, 2022
Artificial intelligence (AI) has been recognized as a powerful technique that can accelerate drug discovery during the hit compound identification step. However, most simple deep learning models have been used for naive pre-filtering as the predictio...
Artificial Intelligence Molecular Docking Simulation Drug Discovery Protein Binding Molecular Dynamics Simulation Ligands Binding Sites Purinergic P2X Receptor Antagonists
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Exploring Deep Learning of Quantum Chemical Properties for Absorption, Distribution, Metabolism, and Excretion Predictions.

Journal of chemical information and modeling Jun 27, 2022
Quantum mechanical (QM) descriptors of small molecules have wide applicability in understanding organic reactivity and molecular properties, but the substantial compute cost required for QM calculations limits their broad usage. Here, we investigate...
Neural Networks, Computer Animals Drug Discovery Deep Learning Rats Biological Transport
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