Date of Award

2017

Publication Type

Master Thesis

Degree Name

M.Sc.

Department

Computer Science

Supervisor

Mukhopadhyay, Asish

Supervisor

Aneja, Yash

Rights

info:eu-repo/semantics/openAccess

Abstract

The alignment of two protein structures is a fundamental problem in structural bioinformatics.Their structural similarity carries with it the connotation of similar functional behavior that couldbe exploited in various applications. A plethora of algorithms, including one by us, is a testamentto the importance of the problem. In this thesis, we propose a novel approach to measure theeectiveness of a sample of four such algorithms, DALI, TM-align, CE and EDAlignsse, for de-tecting structural similarities among proteins. The underlying premise is that structural proximityshould translate into spatial proximity. To verify this, we carried out extensive experiments withve dierent datasets, each consisting of proteins from two to six dierent families.In further addition to our work, we have focused on the area of computational methods foraligning multiple protein structures. This problem is known for its np-complete nature. Therefore,there are many ways to come up with a solution which can be better than the existing ones or atleast as good as them. Such a solution is presented here in this thesis. We have used a heuristicalgorithm which is the Progressive Multiple Alignment approach, to have the multiple sequencealignment. We used the root mean square deviation (RMSD) as a measure of alignment quality andreported this measure for a large and varied number of alignments. We also compared the executiontimes of our algorithm with the well-known algorithm MUSTANG for all the tested alignments.

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