Length variation analysis of protein domain superfamilies amongst sequence homologues

Abstract

Protein domains are the functional and evolutionary units of protein structure and are independent in their functionality and folding pattern. Over millions of years, they tend to accumulate many mutations which can cause a change in their length and structure thereby increasing their functional diversity. Domain comparisons have shown that structural variation is influenced by the number, length and location of insertions and deletions of residues and these length variations can range from two-three residues to two-fold of the domain size. Length variations at the protein domain level have been known to cause functional impacts like, increasing structural stability, diversifying substrate specificity etc. In this thesis, I have studied length variations within protein domains from sequence, structure and dynamics perspective. Starting from a seed set of PASS2 database, which contains alignments of distantly related protein domains (grouped as protein superfamilies as per SCOP hierarchy), homologous sequences of the seed set were collected from the sequence space systematically. For running this automated search over 731 superfamilies (~7500 protein domains), a pipeline was developed which gathered and validated homologues having length variations. These when processed led to identifying indels and in creation of a comprehensive resource of length variant protein domains at superfamily level which will help users trace length variations/indels in their protein domain of interest. The structural significance of a twenty residue insert in a DNA polymerase, terminal deoxynucleotidyl transferase, was investigated using modeling and molecular dynamics simulation for an in-depth perspective on effect of length variation at functional level of protein. This thesis attempts to create a knowledgebase and provide pointers regarding presence of indels across various protein domain superfamilies, their effects on the structure and function of proteins which can further help in protein engineering and drug targeting.