Persistent homology and its generators applied to protein folding

• Grant number: 18/20659-0
• Support Opportunities: Scholarships abroad - Research Internship - Master's degree
• Start date: January 01, 2019
• End date: June 30, 2019
• Field of knowledge: Physical Sciences and Mathematics - Mathematics - Geometry and Topology
• Principal Investigator: Marcio Fuzeto Gameiro
• Grantee: Carlos Henrique Venturi Ronchi
• Supervisor: Konstantin Mischaikow
• Host Institution: Instituto de Ciências Matemáticas e de Computação (ICMC). Universidade de São Paulo (USP). São Carlos , SP, Brazil
• Institution abroad: Rutgers The State University of New Jersey, New Brunswick, United States
• Associated to the scholarship: 17/14678-0 - Persistent homology generators and applications, BP.MS

Abstract

Persistent homology is a growing area inside computational topology. Recently the researchers have been trying to apply these new topological tools to real world problems, from material sciences to the study of proteins. The protein folding problem concerns in knowing how stable a protein is under the action of proteolysis, that means, how easily a protein breaks into smaller polypeptides or amino acids. Persistent homology can be applied to the carbon sequence of the protein to get the persistence diagram, which will give a topological fingerprint, a topological information of the protein. Together with persistent homology, machine learning is used to determine the stability of the protein.