ProtNN: fast and accurate protein 3D-structure classification in structural and topological space.

ABSTRACT:

Background

Studying the functions and structures of proteins is important for understanding the molecular mechanisms of life. The number of publicly available protein structures has increasingly become extremely large. Still, the classification of a protein structure remains a difficult, costly, and time consuming task. The difficulties are often due to the essential role of spatial and topological structures in the classification of protein structures.

Results

We propose ProtNN, a novel classification approach for protein 3D-structures. Given an unannotated query protein structure and a set of annotated proteins, ProtNN assigns to the query protein the class with the highest number of votes across the k nearest neighbor reference proteins, where k is a user-defined paramete

SUBMITTER: Dhifli W 

PROVIDER: S-EPMC5034655 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature