Accelerating molecular discovery through data and physical sciences: Applications to peptide-membrane interactions

作者：Cipcigan Flaviu^*; Carrieri Anna Paola; Pyzer Knapp Edward O; Krishna Ritesh; Hsiao Ya Wen; Winn Martyn; Ryadnov Maxim G; Edge Colin; Martyna Glenn; Crain Jason

来源：Journal of Chemical Physics, 2018, 148(24): 241744.

DOI：10.1063/1.5027261

Simulation and data analysis have evolved into powerful methods for discovering and understanding molecular modes of action and designing new compounds to exploit these modes. The combination provides a strong impetus to create and exploit new tools and techniques at the interfaces between physics, biology, and data science as a pathway to new scientific insight and accelerated discovery. In this context, we explore the rational design of novel antimicrobial peptides (short protein sequences exhibiting broad activity against multiple species of bacteria). We show how datasets can be harvested to reveal features which inform newdesign concepts. We introduce newanalysis and visualization tools: a graphical representation of the k-mer spectrum as a fundamental property encoded in antimicrobial peptide databases and a data-driven representation to illustrate membrane binding and permeation of helical peptides. Published by AIP Publishing.

• 出版日期2018-6-28
• 单位IBM