AI drug discovery tools and analysis technology: New methods aid in studying the compatibility of Traditional Chinese Medicine

Abstract

Introduction

The compatibility of Traditional Chinese Medicine (TCM) holds the potential for reducing toxicity and enhancing efficacy, serving as a crucial guide for the clinical application of TCM. In recent years, the development of artificial intelligence (AI) drug discovery tools has introduced novel approaches for analyzing the multichemical components of TCM, thereby saving time and efforts in experiments.

Methods

The keywords "Traditional Chinese Medicine" and "Artificial Intelligence", "Traditional Chinese Medicine" and "drug compatibility" were searched across various literature databases, including Web of Science, Google Scholar, PubMed, and Elsevier. Over 100 articles were reviewed, and after narrowing the selection to those focused on compatibility, the chosen studies were carefully analyzed to summarize the latest developments for this review.

Results

The review introduce AI drug discovery tools, including virtual screening, target prediction, ADMET prediction, and data mining, along with their roles in studying TCM compatibility. The results further provide insights of AI's application in TCM combination prediction, TCM compatibility mechanisms, and optimization of TCM compatibility ratio within the TCM compatibility research field.

Discussion

Traditional Chinese Medicine uses holistic formulas involving multiple components, targets, and pathways for disease treatment, but scientific explanations of these formulas are limited. AI aids TCM research by predicting combinations, mechanisms, and optimizing ratios, which improves efficiency and reducing costs. However, AI predictions may not be definitely accurate, and traditional expertise is still essential for validation. Future applications of AI in TCM require improved tools and collaboration between AI and TCM researchers.