Mullins Jonathan G L
Genome and Structural Bioinformatics, Institute of Life Science, Swansea University Medical School, Singleton Park, Swansea SA2 8PP, U.K.
Moleculomics Ltd, Institute of Life Science, Swansea University Medical School, Singleton Park, Swansea SA2 8PP, U.K.
Biochem Soc Trans. 2022 Apr 29;50(2):747-758. doi: 10.1042/BST20200967.
Over the last decade, for the first time, substantial efforts have been directed at the development of dedicated in silico platforms for drug repurposing, including initiatives targeting cancers and conditions as diverse as cryptosporidiosis, dengue, dental caries, diabetes, herpes, lupus, malaria, tuberculosis and Covid-19 related respiratory disease. This review outlines some of the exciting advances in the specific applications of in silico approaches to the challenge of drug repurposing and focuses particularly on where these efforts have resulted in the development of generic platform technologies of broad value to researchers involved in programmatic drug repurposing work. Recent advances in molecular docking methodologies and validation approaches, and their combination with machine learning or deep learning approaches are continually enhancing the precision of repurposing efforts. The meaningful integration of better understanding of molecular mechanisms with molecular pathway data and knowledge of disease networks is widening the scope for discovery of repurposing opportunities. The power of Artificial Intelligence is being gainfully exploited to advance progress in an integrated science that extends from the sub-atomic to the whole system level. There are many promising emerging developments but there are remaining challenges to be overcome in the successful integration of the new advances in useful platforms. In conclusion, the essential component requirements for development of powerful and well optimised drug repurposing screening platforms are discussed.
在过去十年中，人们首次投入大量精力开发用于药物重新利用的专用计算机模拟平台，包括针对癌症以及隐孢子虫病、登革热、龋齿、糖尿病、疱疹、狼疮、疟疾、结核病和新冠肺炎相关呼吸道疾病等各种病症的项目。本综述概述了计算机模拟方法在应对药物重新利用挑战的具体应用方面取得的一些令人振奋的进展，并特别关注这些努力在开发对参与药物重新利用项目工作的研究人员具有广泛价值的通用平台技术方面所取得的成果。分子对接方法和验证方法的最新进展，以及它们与机器学习或深度学习方法的结合，不断提高重新利用工作的精度。将对分子机制的更好理解与分子途径数据和疾病网络知识进行有意义的整合，正在拓宽发现重新利用机会的范围。人工智能的力量正在被有效地利用，以推动从亚原子到整个系统层面的综合科学取得进展。虽然有许多有前景的新进展，但在成功整合有用平台的新进展方面仍有挑战需要克服。总之，本文讨论了开发强大且优化良好的药物重新利用筛选平台所需的基本组件要求。
