AIMC Topic: Drug Discovery

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The Impact of Supervised Learning Methods in Ultralarge High-Throughput Docking.

Journal of chemical information and modeling Apr 10, 2023
Structure-based virtual screening methods are, nowadays, one of the key pillars of computational drug discovery. In recent years, a series of studies have reported docking-based virtual screening campaigns of large databases ranging from hundreds to ...
Databases, Factual Molecular Docking Simulation Machine Learning Supervised Machine Learning Ligands Drug Discovery
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Artificial intelligence assisted identification of potential tau aggregation inhibitors: ligand- and structure-based virtual screening, in silico ADME, and molecular dynamics study.

Molecular diversity Apr 6, 2023
Alzheimer's disease (AD) is a severe, growing, multifactorial disorder affecting millions of people worldwide characterized by cognitive decline and neurodegeneration. The accumulation of tau protein into paired helical filaments is one of the major ...
Molecular Dynamics Simulation Drug Evaluation, Preclinical Drug Discovery Protein Binding tau Proteins Protein Aggregates Alzheimer Disease Ligands Humans Artificial Intelligence Computer Simulation Molecular Docking Simulation
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Effectively Identifying Compound-Protein Interaction Using Graph Neural Representation.

IEEE/ACM transactions on computational biology and bioinformatics Apr 3, 2023
Effectively identifying compound-protein interactions (CPIs) is crucial for new drug design, which is an important step in silico drug discovery. Current machine learning methods for CPI prediction mainly use one-demensional (1D) compound/protein str...
Amino Acid Sequence Neural Networks, Computer Machine Learning Drug Discovery Proteins
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Enhancing Drug-Drug Interaction Prediction Using Deep Attention Neural Networks.

IEEE/ACM transactions on computational biology and bioinformatics Apr 3, 2023
Drug-drug interactions are one of the main concerns in drug discovery. Accurate prediction of drug-drug interactions plays a key role in increasing the efficiency of drug research and safety when multiple drugs are co-prescribed. With various data so...
Neural Networks, Computer Drug Discovery Drug Interactions
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Reverse tracking from drug-induced transcriptomes through multilayer molecular networks reveals hidden drug targets.

Computers in biology and medicine Mar 31, 2023
Identifying molecular targets of a drug is an essential process for drug discovery and development. The recent in-silico approaches are usually based on the structure information of chemicals and proteins. However, 3D structure information is hard to...
Gene Regulatory Networks Proteins Transcriptome Machine Learning Drug Discovery
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A Systematic Review of Deep Learning Methodologies Used in the Drug Discovery Process with Emphasis on In Vivo Validation.

International journal of molecular sciences Mar 31, 2023
The discovery and development of new drugs are extremely long and costly processes. Recent progress in artificial intelligence has made a positive impact on the drug development pipeline. Numerous challenges have been addressed with the growing explo...
Drug Discovery Deep Learning Artificial Intelligence Neural Networks, Computer Algorithms
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BiComp-DTA: Drug-target binding affinity prediction through complementary biological-related and compression-based featurization approach.

PLoS computational biology Mar 31, 2023
Drug-target binding affinity prediction plays a key role in the early stage of drug discovery. Numerous experimental and data-driven approaches have been developed for predicting drug-target binding affinity. However, experimental methods highly rely...
Amino Acid Sequence Drug Development Proteins Neural Networks, Computer Drug Discovery
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De novo drug design based on Stack-RNN with multi-objective reward-weighted sum and reinforcement learning.

Journal of molecular modeling Mar 30, 2023
CONTEXT: In recent decades, drug development has become extremely important as different new diseases have emerged. However, drug discovery is a long and complex process with a very low success rate, and methods are needed to improve the efficiency o...
Drug Discovery Reward Neural Networks, Computer Drug Design
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A compact review of progress and prospects of deep learning in drug discovery.

Journal of molecular modeling Mar 28, 2023
BACKGROUND: Drug discovery processes, such as new drug development, drug synergy, and drug repurposing, consume significant yearly resources. Computer-aided drug discovery can effectively improve the efficiency of drug discovery. Traditional computer...
Neural Networks, Computer Deep Learning Machine Learning Drug Design Drug Discovery Molecular Docking Simulation
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Deep Learning-Based Modeling of Drug-Target Interaction Prediction Incorporating Binding Site Information of Proteins.

Interdisciplinary sciences, computational life sciences Mar 26, 2023
Chemogenomics, also known as proteochemometrics, covers various computational methods for predicting interactions between related drugs and targets on large-scale data. Chemogenomics is used in the early stages of drug discovery to predict the off-ta...
Machine Learning Drug Discovery Deep Learning Ligands Proteins Binding Sites
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