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Has Artificial Intelligence Revolutionized Drug Design and Discovery? | ||
| Trends in Pharmaceutical Sciences and Technologies | ||
| مقالات آماده انتشار، پذیرفته شده، انتشار آنلاین از تاریخ 09 خرداد 1405 | ||
| نوع مقاله: Commentary-Article | ||
| شناسه دیجیتال (DOI): 10.30476/tips.2026.108784.1321 | ||
| نویسندگان | ||
| Manica Negahdaripour* 1؛ Younes Ghasemi2 | ||
| 1Department of Pharmaceutical Biotechnology, School of Pharmacy, Shiraz University of Medical Sciences, Shiraz, Iran. | ||
| 2School of Pharmacy-Karafarin St-Akbarabad | ||
| چکیده | ||
| Artificial intelligence (AI), particularly machine learning (ML) and deep learning (DL), is reshaping bioinformatics and computational biology by enhancing core techniques such as molecular docking, molecular dynamics (MD) simulations, and drug design. This commentary looks at how AI is changing—from specialized, task-focused tools to the broader, long-term dream of artificial general intelligence (AGI). It also examines how these advances are shaping biomedical research and the future of drug discovery. AI-driven tools improve docking accuracy, accelerate MD simulations, and enable generative design of novel compounds, contributing to faster, more cost-effective drug discovery. While breakthroughs such as AlphaFold have revolutionized protein structure prediction, the broader narrative of an AI revolution warrants scrutiny. Critics argue that AI often rebrands existing techniques. Despite substantial progress, challenges such as biological complexity, data bias, and regulatory hurdles persist. AI remains a powerful enhancer rather than a replacement for experimental methods, and its integration with emerging technologies such as quantum computing may catalyze future transformation in drug discovery. | ||
| کلیدواژهها | ||
| AI؛ Computational biology؛ Molecular docking؛ Drug discovery | ||
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