Biotechnological
Communication
Biosci. Biotech. Res. Comm. 9(1):
Computational approach for sequence alignment of capsid proteins of human herpes virus
Vipan K Sohpal
Department of Chemical Engineering, Beant College of Engineering & Technology, Gurdaspur 143521, Punjab, India
ABSTRACT
Sequence alignment is a prerequisite for biological sequence data analysis. In this paper, a systematic approach used to analyze the four proteins from Viral Capsid of Human Herpes Virus (HSV) which cause cytomegalovirus, brain inflammation, and lifelong infection. It is not viable to extend the relationship between
KEY WORDS: HUMAN HERPES VIRUS, SEQUENCE ALIGNMENT, MAT LAB AND SCORING MATRICES
INTRODUCTION
A wealth of molecular data concerning the function and structure of proteins and nucleic acids is available in the form of DNA, RNA, and protein sequences. Score from the sequence alignment has become an essential and widely used tool for understanding the function- ing and phylogenetically divergent of different strains. Various scoring matrices (PAM, BLOSUM, and Gonnet) applications are used with
ARTICLE INFORMATION:
*Corresponding Author:
Received 13th Feb, 2016
Accepted after revision 23rd March, 2016 BBRC Print ISSN:
Online ISSN:
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Vipan K Sohpal
and drug design. For this purpose optimization of scor- ing, matrices are used. The data extract using Bioinfor- matics toolbox of Matrix Laboratory have been used for a functional task of providing annotation of biologically relevant information from a nucleotide or proteomic sequence. It provides a powerful interface for the analy- sis and mining of genomic information while seamlessly handling the nonscientific complexities of interfacing with hardware, computational clusters, software pack- ages, raw data, and file formats. Genome and proteome analysis performed using bioinformatics toolbox that extends MATLAB to provide an integrated software environment. An open prototype idea and extendable environment for MATLAB using efficient processing and statistical functions, a template for improving or creat- ing and analyzing biological data.
In literature review our main focus was on the three principles that are necessary for studying and investigat- ing the sequence alignment and phylogenetic analysis of human herpes virus. Firstly bioinformatics analyses, sequence alignment and phylogenetic analysis from bio- logical databases sources have been studied. Secondly approaches, particularly with reference to herpes Virus have been attempted. At last the systematic analysis of the bioinformatics tools and softwares have also com- monly been used for sequence alignment.
Biopipe framework that allows the researchers to focus on their specific biological analysis and avoid to deals with issues like data access and parsing and job manage- ment (Shawn, 2003). A new program has been developed for creating multiple alignments of protein sequences, of the algorithm and showing MUSCLE to achieve the highest scores reported to date on four alignment accu- racy benchmarks (Edgar, 2004). It integrates the sources for genome annotation, inference of molecular interac- tions across species, and
The Molecular Evolutionary Genetics Analysis soft- ware is a desktop application designed for comparative analysis of homologous gene sequences either from mul- tigene families or from different species with a special emphasis on inferring evolutionary relationships and patterns of DNA and protein evolution. MEGA provides many convenient facilities for the assembly of sequence data sets from files or
tools for visual presentation of the results obtained in the form of interactive phylogenetic trees and evolution- ary distance matrices, (Kumar, et al., 2004; 2008).
Statistical score has been used for assessing the qual- ity of multiple sequence alignments, where the quality assessment is based on counting the number of sig- nificantly conserved positions in the alignment using importance sampling method in conjunction with sta- tistical profile analysis framework (Virpi, 2006). Align- ing Sequences by minimum description length in which alignment algorithm uses minimum description length to encode and explore alternative expressions. The expression with the shortest encoding provides the best overall alignment (Conery, 2007).
These authors have worked on dynamic use of mul- tiple parameter sets in sequence alignment. They have used an alignment algorithm to allow dynamic use of multiple parameter sets with different levels of strin- gency in computation of an optimal alignment of two sequences. Various workers have also developed tech- niques to assess the scores using splitting the BLOSUM score into numbers of biological significance. Kalign is an accurate and fast multiple sequence alignment algorithm. They developed Kalign, a method employing the
MAFFT has been used for improvement in accuracy of multiple sequence alignment. These new options of MAFFT showed higher accuracy than currently available methods including TCoffee version 2 and CLUSTAL W in benchmark tests consisting of alignments of more than 50 sequences.Herpes simplex virus type 2 UL56 interacts with the ubiquitin ligase and increases ubiquitination, (Katoh, 2005 and Ushijima, 2008).
The above work was concentrated on
ine cap analysis of gene expression (CAGE), chromatin
From previously literature on optimization of scor- ing matrices using bioinformatics tools, reveals that a significant work has not been published. This paper is an attempt to blend wet biological lab data analysis and utilization of recently developed software for sequence alignment. The accuracy of sequence alignment is func- tion of comparison of particular sequences for local and global alignment scores.
MATERIAL AND METHODS
Firstly the Protein sequence data of
Vipan K Sohpal
RESULTS AND DISCUSSION
The developed algorithmic technique and statistic of sequence alignment helped to make optimal alignment and act as a valuable tool in bioinformatics for valid alignment. Optimal alignment serves to judge the simi- larity of sequence aligned. The statistical assessment of optimal alignment score makes sequence alignment less dependent on gap penalty choice. The alignment of HSV strain performed on different scoring matrix of PAM using
The 1769 protein of both strain
FIGURE 1: Major Capsid Protein of
Vipan K Sohpal
FIGURE 2: Capsid Protein of
and gap extension. The higher the alignment score, the better the alignment accuracy. Figure 1 indicates that alignment score for various PAM scoring matrices of Major capsid protein
optimized score for major capsid protein is 5.0995e3 at 10 PAM value. The 1769 protein of
FIGURE 3: Small Capsid Protein of
Vipan K Sohpal
FIGURE 4: Capsid Portal Protein of
tively same score but lower than
The Capsid protein of HSV virus is controlled by
3at 10 PAM.
alignment of
CONCLUSION
Global alignment score versus PAM matrices profile can use to analysis the optimum score at particular PAM matrices. The optimized scores for major capsid protein, capsid protein and small capsid protein are 4.374 e3, 1.1235 e3 3.523e2 respectively at PAM value of 10. From the result, it found that lower PAM matrix is suitable for
Vipan K Sohpal
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