AIMC Topic: Drug Discovery

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A Knowledge-Guided Graph Learning Approach Bridging Phenotype- and Target-Based Drug Discovery.

Advanced science (Weinheim, Baden-Wurttemberg, Germany) Mar 6, 2025
Discovering therapeutic molecules requires the integration of both phenotype-based drug discovery (PDD) and target-based drug discovery (TDD). However, this integration remains challenging due to the inherent heterogeneity, noise, and bias present in...
Phenotype Humans SARS-CoV-2 Machine Learning Drug Discovery Neural Networks, Computer COVID-19 COVID-19 Drug Treatment
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DIG-Mol: A Contrastive Dual-Interaction Graph Neural Network for Molecular Property Prediction.

IEEE journal of biomedical and health informatics Mar 6, 2025
Molecular property prediction is a key component of AI-driven drug discovery and molecular characterization learning. Despite recent advances, existing methods still face challenges such as limited ability to generalize, and inadequate representation...
Neural Networks, Computer Algorithms Graph Neural Networks Drug Discovery Molecular Structure
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Multimodal Drug Target Binding Affinity Prediction Using Graph Local Substructure.

IEEE journal of biomedical and health informatics Mar 6, 2025
Predicting the binding affinity of drug target is essential to reduce drug development costs and cycles. Recently, several deep learning-based methods have been proposed to utilize the structural or sequential information of drugs and targets to pred...
Pharmaceutical Preparations Deep Learning Computational Biology Humans Algorithms Protein Binding Proteins Drug Discovery
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Property-Guided Few-Shot Learning for Molecular Property Prediction With Dual-View Encoder and Relation Graph Learning Network.

IEEE journal of biomedical and health informatics Mar 6, 2025
Molecular property prediction is an important task in drug discovery. However, experimental data for many drug molecules are limited, especially for novel molecular structures or rare diseases which affect the accuracy of many deep learning methods t...
Drug Discovery Deep Learning Machine Learning Algorithms Humans
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BINDTI: A Bi-Directional Intention Network for Drug-Target Interaction Identification Based on Attention Mechanisms.

IEEE journal of biomedical and health informatics Mar 6, 2025
The identification of drug-target interactions (DTIs) is an essential step in drug discovery. In vitro experimental methods are expensive, laborious, and time-consuming. Deep learning has witnessed promising progress in DTI prediction. However, how t...
Computational Biology Proteins Drug Discovery Deep Learning Humans Neural Networks, Computer
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AEGNN-M:A 3D Graph-Spatial Co-Representation Model for Molecular Property Prediction.

IEEE journal of biomedical and health informatics Mar 6, 2025
Improving the drug development process can expedite the introduction of more novel drugs that cater to the demands of precision medicine. Accurately predicting molecular properties remains a fundamental challenge in drug discovery and development. Cu...
Drug Discovery Deep Learning Humans Neural Networks, Computer Cell Line, Tumor
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Prediction of Drug-Target Interactions With High- Quality Negative Samples and a Network-Based Deep Learning Framework.

IEEE journal of biomedical and health informatics Mar 6, 2025
Identification of drug-target interactions (DTIs) plays a crucial role in drug discovery. Compared to traditional experimental methods, computer-based methods for predicting DTIs can significantly reduce the time and financial burdens of drug develop...
Gene Ontology Deep Learning Computational Biology Neural Networks, Computer Proteins Humans Drug Discovery Pharmaceutical Preparations
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TARSL: Triple-Attention Cross-Network Representation Learning to Predict Synthetic Lethality for Anti-Cancer Drug Discovery.

IEEE journal of biomedical and health informatics Mar 6, 2025
Cancer is a multifaceted disease that results from co-mutations of multi biological molecules. A promising strategy for cancer therapy involves in exploiting the phenomenon of Synthetic Lethality (SL) by targeting the SL partner of cancer gene. Since...
Machine Learning Computational Biology Neoplasms Drug Discovery Synthetic Lethal Mutations Humans Antineoplastic Agents
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iScore: A ML-Based Scoring Function for De Novo Drug Discovery.

Journal of chemical information and modeling Mar 4, 2025
In the quest for accelerating de novo drug discovery, the development of efficient and accurate scoring functions represents a fundamental challenge. This study introduces iScore, a novel machine learning (ML)-based scoring function designed to predi...
Neural Networks, Computer Machine Learning Drug Discovery Proteins Protein Binding Ligands
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Harnessing machine learning for rational drug design.

Advances in pharmacology (San Diego, Calif.) Mar 3, 2025
A crucial part of biomedical research is drug discovery, which aims to find and create innovative medical treatments for a range of illnesses. However, there are intrinsic obstacles to the traditional approach of discovering novel medications, includ...
Drug Design Humans Machine Learning Drug Discovery Animals
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