Research & Reviews Journal of

Bioinformatics

STM JOURNALSScientific Technical Medical

(RRJoBI)

Jan - April 2014

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Research & Reviews: A Journal of Bioinformatics

Research & Reviews: A Journal of Bioinformatics

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Industrial Tribology Machine Dynamics & Maintenance

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Editorial Board

Dr. Afroz AlamAssistant Professor (S.G.) Department of

Bioinformatics, Karunya University, Coimbatore,

Tamil Nadu, India.

Dr. Bharat Bhusan Subudhi Associate Professor, School of

Pharmaceutical Sciences, Siksha O Anusandhan University,

Bhubaneswar, India.

Dr. Lakshmi AnnamalaiAssociate Professor, Phytomatics

Laboratory Center for Bioinformatics School of Life Sciences

Pondicherry University, India.

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University of Hyderabad, Hyderabad, Andhra Pradesh, India.

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Dr. Amita VermaHead Deptarment of Pharmaceutical

Sciences, SHIATS-Demeed University, Allahabad, India.

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Centre Department of Life Science & Bioinformatics Assam University,

Silchar, Assam, India.

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Hyderabad, Hyderabad, India.

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College, Maliba Campus, Surat, Gujarat, India.

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Bangalore, India.

Dr. S. K. M. HabeebAssistant Professor, Department of

Bioinformatics, School of Bioengineering, Kattankulathur Campus,

SRM University, India

Dr. Sandeep Gupta

Research Scientist (NDSSL) Virginia Polytechnic Institute and State

University, Pratt Drive.

I take the privilege to present the print version for the [Volume 1 Issue (1)] of Journal of

Bioinformatics. The intension of JoBI is to create an atmosphere that stimulates creativeness,

research and growth in the area of Bioinformatics.

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eminent Scientists and Engineers in every field. JoBI provides an outlet for Research findings and

reviews in areas of Bioinformatics found to be relevant for National and International recent

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the advancement and dissemination of Research results that support high level learning, teaching and

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ups/ reviewing and providing constructive comments for the advancement of the journals. With

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Research/Reviews findings for our customers base.

I hope you will enjoy reading this issue and we welcome your feedback on any aspect of the Journal.

Dr. Archana Mehrotra

Director

STM Journals

Director's Desk

STM JOURNALS

1. Computational Analysis of Microarray Gene Expression Profiling in Leishmania donovani and Leishmania major Ganesh Chandra Sahoo, Sindhuprava Rana, Manas Ranjan Dikhit, Md Yousuf Ansari, Pradeep Das 1

2. Computational Investigation of nsSNPs of PRSS1 Gene Ekta Kumari, Dhwani Raghaw, Jitendra Singh Rathore 15

3. Detection and Comparative Analysis of Uber-operons of FabZ gene Responsible for Fatty Acid Biosynthesis in Nostoc Punctiforme CyanobacteriumLakshmi P.T.V., Sathya Priya, Annamalai A. 23

4. Insilico Modelling and Comparative Docking Studies of EWS-FLI1 Responsible for Ewing Sarcoma in Human Beings Lakshmi PTV, Pragna Lakshmi T, Annamalai A 36

ContentsResearch & Reviews: A Journal of Bioinformatics

RRJoBI (2014)© STM Journals 2014. All Rights Reserved

Research & Reviews: A Journal of Bioinformatics

Volume 1, Issue 1

www.stmjournals.com

Computational Analysis of Microarray Gene Expression

Profiling in Leishmania donovani and Leishmania major

Ganesh Chandra Sahoo1, 2

*, Sindhuprava Rana1, Manas Ranjan Dikhit

1,

Md Yousuf Ansari1, 2

, Pradeep Das1, 2

1Biomedical Informatics Centre, RMRIMS, (ICMR), Agam Kuan, Patna, India

2Pharmacoinformatics Department, NIPER, Industrial Area, Hajipur, India

Abstract Leishmaniasis is one of the most deadly diseases in which the human genes are affected and gets altered expression. The genes of Leishmania species which are responsible for

causing leishmaniasis are not known yet. The objective behind this study is to know

about the genes which are differentially expressed (DE) when macrophage of mice is

infected with Leishmania donovani and Leishmania major. It also aims to know the

similarities of these DE genes from human genes and predict the genes responsible for leishmaniasis in human. Microarray data analyses allow us to monitor thousands of

genes simultaneously. The analyses of microarray data using statistical methods

predict the differentially expressed genes in diseased state. Clustering of these genes and functional analysis through GO database accentuate the predictions.

Keywords: Differentially Expressed (DE), Automated Robust Microarray Data

Analysis (ARMADA), Perfect Match (PM), Gene Ontology (GO), Clustering

RRJoBI (2014)© STM Journals 2014. All Rights Reserved

Research & Reviews: A Journal of Bioinformatics

Volume 1, Issue 1

www.stmjournals.com

Computational Investigation of nsSNPs of PRSS1 Gene

Ekta Kumari*, Dhwani Raghaw, Jitendra Singh Rathore

Department: School of Biotechnology, Gautam Buddha University, Greater Noida,

Gautam Buddha Nagar, U.P., India

Abstract This research is done for the prioritizing of SNPs of a gene PRSS1 causing hereditary

pancreatitis. In this analysis, the authors found out some nsSNPs as less stable,

deleterious, probably damaging retain high risk score. It was also predicted that SIFT is fast SNPs server with comparison of PolyPhen2. By Doing its energy calculation and

stability prediction, we can also determine the stability of mutant protein, that is ok whether this substitution is stable and heritable as it causes the hereditary pancreatitis.

We can also know about its RMSD value which helps in protein modeling in a way by

describing its structure features. Prioritizing nsSNPs in the investigation personalized medicine also as every SNPSs id having with their unique amino acid substitution at

unique position. Animal models or cell lines to determine if functionality of the protein has indeed been altered today with the help of nsSNPSs analysis and by calculating its

stability of protein are under selection pressure as it helps us in predicting phenotype

so it may be used in nsSNPs investigation and protein stability prediction in post-biology study.

Keywords: nsSNP, SIFT, mutant protein, protein stability

RRJoBI (2014)© STM Journals 2014. All Rights Reserved

Research & Reviews: A Journal of Bioinformatics

Volume 1, Issue 1

www.stmjournals.com

Detection and Comparative Analysis of Uber-operons of

FabZ gene Responsible for Fatty Acid Biosynthesis in

Nostoc Punctiforme Cyanobacterium

Lakshmi P.T.V.1*

, Sathya Priya1, Annamalai A.

2

1Centre for Bioinformatics, School of Life Sciences, Pondicherry University, Puducherry, India

2Department of Biotechnology, School of Biotechnology and Health Sciences, Karunya University,

Karunya Nagar, Coimbatore , Tamil Nadu, India

Abstract The increasing price of petroleum products has necessitated the development of

alternative fuel energy. The long alkyl chains that represent nature’s ‘petroleum’, are today isolated from microbes, plant and animal oils by amore scalable, controllable

and economic routes.Hence, in this perspective, the present study was aimed at

exploring the uber-operons of FabZ gene responsible for the synthesis of fatty acid in an aquatic nitrogen-fixing and filamentous cyanobacterium called Nostoc punctiforme.

Rearrangement of genomes occur randomly and frequently during evolution. Prokaryotic organisms maintain genes of similar function and that are involved in the

same cellular process in clusters of same transcriptional orientation and regulation.

The uber-operons are the set of functionally related genes maintained in close proximity in the genome, which assist in genome annotation and the discovery of

regulatory elements. Thus, the main objective of the study was to identify the genes

those were associated as uber-operon in the fatty acid pathway of Nostoc punctiforme and also to check for its involvement in different pathways based on the

‘neighbourhoods’ assembly and phylogeny.

Keywords: Biofuel, renewable resources, Fatty acids, Uber-operons,

Cyanobacterium

RRJoBI (2014) 36-45 © STM Journals 2014. All Rights Reserved Page 36

Research & Reviews: A Journal of Bioinformatics

Volume 1, Issue 1

www.stmjournals.com

Insilico Modelling and Comparative Docking Studies

of EWS-FLI1 Responsible for Ewing Sarcoma

in Human Beings

Lakshmi PTV1*, Pragna Lakshmi T

1, Annamalai A

2

1Centre for Bioinformatics, School of Life Sciences, Pondicherry University, Pondicherry

2Department of Biotechnology , School of Biotechnology and Health Sciences,

Karunya University , Karunya Nagar, Coimbatore , Tamilnadu , India

Abstract Ewing’s sarcoma (EWS) is a small round-cell tumor typically arising in the bones, rarely

in soft tissues, of children and adolescents. Patho-genomic translocations involving the EWS gene on chromosome 22 and an ETS-type gene (Fli1) on chromosome 11, are

implicated in more than 95% of Ewing’s sarcomas. A chimeric transcript that consists of

the N-terminus of EWS i.e., Transcriptional Activation Domain is fused to the C-terminal portion of FLI1 i.e., DNA Binding Domain (DBD). In this present study, the structure of

disordered fusion protein, EWS-FLI1 was predicted, modelled and refined. Ligand structures were drawn by using CHEMDRAW and CORINA. Comparative Docking

studies were performed for EWS-FLI1 protein with EMODIN and YK-4-279 by using

SCHRODINGER. Although, EMODIN and YK-4-279 interacted with the protein by establishing the H-Bonds with SER 316, GLN 326, GLN 328, ASP 430 by the former and

with SER 316, ALA 110, and GLN 109 with the later, a common residue of SER 316 was

observed to be interacting. However, the docking score and Glide g score of -6.278203 and -6.100573 were observed for EMODIN and YK-4-279 respectively, which revealed

EMODIN to be much more effective in presenting the highest value. Molecular Dynamics Simulation was performed to analyse the stability of Docked structure of

protein and ligand. For EMODIN, the stabilized structure was formed at 646 ps whereas

for YK-4-279, the stabilized structure was formed at 680 ps and RMSD values for EMODIN was comparatively lower than YK-4-279.

Keywords: Ewing sarcoma, disordered fusion protein, natural ligand, comparison,

molecular dynamic simulation