AIMC Topic: Drug Discovery

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MGNDTI: A Drug-Target Interaction Prediction Framework Based on Multimodal Representation Learning and the Gating Mechanism.

Journal of chemical information and modeling Aug 13, 2024
Drug-Target Interaction (DTI) prediction facilitates acceleration of drug discovery and promotes drug repositioning. Most existing deep learning-based DTI prediction methods can better extract discriminative features for drugs and proteins, but they ...
Pharmaceutical Preparations Caenorhabditis elegans Deep Learning Proteins Animals Drug Discovery Humans
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Transformers for Molecular Property Prediction: Lessons Learned from the Past Five Years.

Journal of chemical information and modeling Aug 13, 2024
Molecular Property Prediction (MPP) is vital for drug discovery, crop protection, and environmental science. Over the last decades, diverse computational techniques have been developed, from using simple physical and chemical properties and molecular...
Machine Learning Drug Discovery Deep Learning
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Perspectives on current approaches to virtual screening in drug discovery.

Expert opinion on drug discovery Aug 12, 2024
INTRODUCTION: For the past two decades, virtual screening (VS) has been an efficient hit finding approach for drug discovery. Today, billions of commercially accessible compounds are routinely screened, and many successful examples of VS have been re...
Drug Discovery High-Throughput Screening Assays Machine Learning Drug Design Small Molecule Libraries Humans
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Discovery of potential antidiabetic peptides using deep learning.

Computers in biology and medicine Aug 12, 2024
Antidiabetic peptides (ADPs), peptides with potential antidiabetic activity, hold significant importance in the treatment and control of diabetes. Despite their therapeutic potential, the discovery and prediction of ADPs remain challenging due to lim...
Deep Learning Hypoglycemic Agents Peptides Humans Drug Discovery Neural Networks, Computer
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Recent progress in artificial intelligence and machine learning for novel diabetes mellitus medications development.

Current medical research and opinion Aug 8, 2024
Diabetes mellitus, stemming from either insulin resistance or inadequate insulin secretion, represents a complex ailment that results in prolonged hyperglycemia and severe complications. Patients endure severe ramifications such as kidney disease, vi...
Hypoglycemic Agents Diabetes Mellitus Humans Artificial Intelligence Drug Discovery Drug Development Machine Learning
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Predicting Drug-Target Interactions Via Dual-Stream Graph Neural Network.

IEEE/ACM transactions on computational biology and bioinformatics Aug 8, 2024
Drug target interaction prediction is a crucial stage in drug discovery. However, brute-force search over a compound database is financially infeasible. We have witnessed the increasing measured drug-target interactions records in recent years, and t...
Neural Networks, Computer Algorithms Computational Biology Humans Drug Discovery Proteins Pharmaceutical Preparations Deep Learning
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Identification of Active Molecules against Thrombocytopenia through Machine Learning.

Journal of chemical information and modeling Aug 7, 2024
Thrombocytopenia, which is associated with thrombopoietin (TPO) deficiency, presents very limited treatment options and can lead to life-threatening complications. Discovering new therapeutic agents against thrombocytopenia has proven to be a challen...
Machine Learning Algorithms Computer Simulation Humans Thrombocytopenia Drug Discovery Megakaryocytes Blood Platelets
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A Computational Framework for Predicting Novel Drug Indications Using Graph Convolutional Network With Contrastive Learning.

IEEE journal of biomedical and health informatics Aug 6, 2024
Inferring potential drug indications plays a vital role in the drug discovery process. It can be time-consuming and costly to discover novel drug indications through biological experiments. Recently, graph learning-based methods have gained popularit...
Humans Neural Networks, Computer Drug Discovery Machine Learning Deep Learning Algorithms Computational Biology
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Protein ligand binding site prediction using graph transformer neural network.

PloS one Aug 6, 2024
Ligand binding site prediction is a crucial initial step in structure-based drug discovery. Although several methods have been proposed previously, including those using geometry based and machine learning techniques, their accuracy is considered to ...
Binding Sites Protein Binding Algorithms Proteins Databases, Protein Drug Discovery Neural Networks, Computer Ligands Machine Learning
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Combining machine learning, molecular dynamics, and free energy analysis for (5HT)-2A receptor modulator classification.

Journal of molecular graphics & modelling Aug 5, 2024
The 5-Hydroxytryptamine (5HT)-2A receptor, a key target in psychoactive drug development, presents significant challenges in the design of selective compounds. Here, we describe the construction, evaluation and validation of two machine learning (ML)...
Protein Binding Molecular Dynamics Simulation Receptor, Serotonin, 5-HT2A Thermodynamics Molecular Docking Simulation Drug Discovery Humans Machine Learning
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