A rapid protein structure alignment algorithm based on a text modeling technique

Abstract

Structural alignment of proteins is widely used in various fields of structural biology. In order to further improve the quality of alignment, we describe an algorithm for structural alignment based on text modelling techniques. The technique firstly superimposes secondary structure elements of two proteins and then, models the 3D-structure of the protein in a sequence of alphabets. These sequences are utilized by a step-by-step sequence alignment procedure to align two protein structures. A benchmark test was organized on a set of 200 non-homologous proteins to evaluate the program and compare it to state of the art programs, e.g. CE, SAL, TM-align and 3D-BLAST. On average, the results of all-against-all structure comparison by the program have a competitive accuracy with CE and TM-align where the algorithm has a high running speed like 3D-BLAST.

Keywords: protein structure alignment; sequence alignment; text modeling.

Figure 1

Three sample relative position of residues and their defined labels

Figure 2

Structure superposition steps between two proteins. (a) Matching SSEs sequences; (b) Refine matched SSEs based on geometrical properties; (c) Create Relative Residue Position Sequence for query and reference proteins

Figure 3

Alignment of identical words inside a pair of matched SSEs for 1GLP:B and 2GST:B PDB chains. The first and fourth lines are amino acids sequences and the second and third lines are relative residue position sequences.

Figure 4

Alignment of the word ‘ivs’ from 1GLP:B PDB chain that is matched with two identical words in 2GST:B PDB chain. Considering connectivity of the aligned words, the word ‘ivs’ at position 42 of 2GST:B is aligned.