使用 MIND-S 预测、解释和评估翻译后修饰的协议。

Protocol for the prediction, interpretation, and mutation evaluation of post-translational modification using MIND-S.

机构信息

NIH BRIDGE2AI Center at UCLA & NHLBI Integrated Cardiovascular Data Science Training Program at UCLA, Suite 1-609, MRL Building, 675 Charles E. Young Dr. South, Los Angeles, CA 90095-1760, USA; Medical Informatics Program, University of California at Los Angeles (UCLA), Los Angeles, CA 90095, USA; Department of Physiology, UCLA School of Medicine, Suite 1-609, MRL Building, 675 Charles E. Young Dr., Los Angeles, CA 90095-1760, USA.

NIH BRIDGE2AI Center at UCLA & NHLBI Integrated Cardiovascular Data Science Training Program at UCLA, Suite 1-609, MRL Building, 675 Charles E. Young Dr. South, Los Angeles, CA 90095-1760, USA; Department of Physiology, UCLA School of Medicine, Suite 1-609, MRL Building, 675 Charles E. Young Dr., Los Angeles, CA 90095-1760, USA.

出版信息

STAR Protoc. 2023 Dec 15;4(4):102682. doi: 10.1016/j.xpro.2023.102682. Epub 2023 Nov 18.

DOI:10.1016/j.xpro.2023.102682

PMID:37979178

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10694567/

Abstract

Post-translational modifications (PTMs) serve as key regulatory mechanisms in various cellular processes; altered PTMs can potentially lead to human diseases. We present a protocol for using MIND-S (multi-label interpretable deep-learning approach for PTM prediction-structure version), to study PTMs. This protocol consists of step-by-step guide and includes three key applications of MIND-S: PTM predictions based on protein sequences, important amino acids identification, and elucidation of altered PTM landscape resulting from molecular mutations. For complete details on the use and execution of this protocol, please refer to Yan et al (2023)..

摘要