INTRODUCTION: High-throughput fluorescence imaging (HTFI) is revolutionizing drug discovery by enabling rapid and precise detection of biological targets and cellular processes. Recent advances in fluorescence imaging technologies now provide unprece...
INTRODUCTION: The field of Natural Language Processing (NLP) within the life sciences has exploded in its capacity to aid the extraction and analysis of data from scientific texts in recent years through the advancement of Artificial Intelligence (AI...
IEEE journal of biomedical and health informatics
Jun 1, 2025
Predicting interactions between drugs and their targets is vital for drug discovery and repositioning. Conventional techniques are slow and labor-intensive, while deep learning algorithms offer efficient solutions. However, deep learning often focus ...
Identifying novel drugs that can interact with target proteins is a highly challenging, time-consuming, and costly task in drug discovery and development. Numerous machine learning-based models have recently been utilized to accelerate the drug disco...
Journal of chemical information and modeling
May 26, 2025
The fusion of traditional chemical descriptors with graph neural networks (GNNs) offers a compelling strategy for enhancing ligand-based virtual screening methodologies. A comprehensive evaluation revealed that the benefits derived from this integrat...
International journal of molecular sciences
May 19, 2025
Molecular optimization plays a pivotal role in many domains since it holds promise for improving the properties of lead molecules. The advent of artificial intelligence (AI)-driven molecular optimization has revolutionized lead optimization workflows...
International journal of molecular sciences
May 19, 2025
Antibody-drug conjugates (ADCs) are promising cancer therapeutics, but optimizing their cytotoxic payloads remains challenging. We present DumplingGNN, a novel hybrid Graph Neural Network architecture for predicting ADC payload activity and toxicity....
Machine learning (ML) is increasingly valuable for predicting molecular properties and toxicity in drug discovery. However, toxicity-related end points have always been challenging to evaluate experimentally with respect to translation due to the re...
BACKGROUND: Identifying GPCR-compound interactions (GCI) plays a significant role in drug discovery and chemogenomics. Machine learning, particularly deep learning, has become increasingly influential in this domain. Large molecular models, due to th...
The modernization and globalization of traditional Chinese medicine (TCM) face challenges such as unclear active compounds and inadequate quality control. Taking Xuefu Zhuyu Oral Liquid (XZOL) as an example, this study proposed an artificial intellig...
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