Computational methods and opportunities for phosphorylation network medicine.

摘要: Protein phosphorylation, one of the most ubiquitous post-translational modifications (PTM) proteins, is known to play an essential role in cell signaling and regulation. With increasing understanding complexity redundancy signaling, there a growing recognition that targeting entire network or system could be necessary advantageous strategy for treating cancer. kinases, proteins add phosphate group substrate during phosphorylation events, have become largest groups ‘druggable’ targets cancer therapeutics recent years. Kinase inhibitors are being regularly used clinics treatment. This therapeutic paradigm shift research partly due generation availability high-dimensional proteomics data. Generation this data, turn, enabled by increased use mass-spectrometry (MS)-based other high-throughput platforms as well companion public databases computational tools. review briefly summarizes current state progress on phosphoproteomics identification, quantification, platform related characteristics. We existing database resources, tools, methods inference, ultimately demonstrate connection therapeutics. Finally, many opportunities exist bioinformaticians biostatisticians based developments limitations emerging technologies.