A new encoding scheme for protein structure representation

Given the rapidly increasing quantity of genomic and proteomic data that is now easily available even to a casual observer, the new challenge is in making sense out of the vast quantities of data. Efficient and reliable analysis of protein 3D structures is identified as a major challenge in this post genomic era. Whether the objective of the analysis is for protein classification, protein similarity search, protein structure prediction, discovery of protein structural motifs, or assignment of a functional class to a newly discovered protein, a key aspect in the analysis is the representation used to encode the protein 3D structural information. In this work, we introduce a family of string encodings as an effective descriptor for protein 3D structures. We show how the choice of parameters affects the performance and compare the result with other related research.