小分子药物发现计算方法的现状

IF 5.3 2区材料科学 Q2 MATERIALS SCIENCE, MULTIDISCIPLINARY ACS Applied Nano Materials Pub Date : 2024-10-24 DOI:10.1021/acs.jmedchem.4c02462

Weijun Xu

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引用次数: 0

摘要

2024 年是计算科学令人兴奋的一年，"人工神经网络 "获得了诺贝尔物理学奖，"蛋白质结构预测和设计 "获得了诺贝尔化学奖。鉴于计算机辅助药物设计（CADD）和药物发现中的人工智能（AIDD）的快速发展，编写一份总结其现状和未来发展方向的文件对于《药物化学杂志》的读者来说是非常及时和有意义的。本评论旨在强调这两个领域的最新发展、主要挑战和潜在协同作用，为文献和科学博客中正在进行的讨论做出贡献。

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Current Status of Computational Approaches for Small Molecule Drug Discovery

2024 has been an exciting year for computational sciences, with the Nobel Prize in Physics awarded for “artificial neural network” and the Nobel Prize in Chemistry presented for “protein structure prediction and design”. Given the rapid advancements in Computer-Aided Drug Design (CADD) and Artificial Intelligence in Drug Discovery (AIDD), a document summarizing their current standing and future directions would be timely and relevant to the readership of Journal of Medicinal Chemistry. This piece of commentary aims to highlight recent developments, key challenges, and potential synergies between these fields, contributing to ongoing discussions in the literature and scientific blogs.

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来源期刊

ACS Applied Nano Materials Multiple-

CiteScore

8.30

自引率

3.40%

发文量

1601

期刊介绍： ACS Applied Nano Materials is an interdisciplinary journal publishing original research covering all aspects of engineering, chemistry, physics and biology relevant to applications of nanomaterials. The journal is devoted to reports of new and original experimental and theoretical research of an applied nature that integrate knowledge in the areas of materials, engineering, physics, bioscience, and chemistry into important applications of nanomaterials.