Acta pharmacologica Sinica
Mar 11, 2025
The GluN1/GluN3A receptor, a unique excitatory glycine receptor recently identified in the central nervous system, challenges traditional perspectives of N-methyl-D-aspartate (NMDA) receptor diversity and glycinergic signaling. Its role in emotional ...
Drug discovery today
Mar 11, 2025
Rheumatoid arthritis (RA) presents a significant challenge in clinical management because of the dearth of effective drugs despite advances in understanding its mechanisms. Drug repurposing has emerged as a promising strategy to address this gap, off...
Molecular pharmaceutics
Mar 7, 2025
The optimization of absorption, distribution, metabolism, and excretion (ADME) profiles of compounds is critical to the drug discovery process. As such, machine learning (ML) models for ADME are widely used for prioritizing the design and synthesis o...
Biomolecules & biomedicine
Mar 7, 2025
Artificial intelligence (AI) has become a powerful tool in biochemistry, greatly enhancing research capabilities by enabling the analysis of complex datasets, predicting molecular interactions, and accelerating drug discovery. As AI continues to evol...
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...
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...
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...
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...
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...
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...