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MY RESEARCH PUBLICATIONS

1.    P. Srinivasan, A. Sudha, A. Shahul Hameed, S. Prasanth Kumar and M. Karthikeyan, 2011. Screening of medicinal plant compounds against NS5B polymerase of hepatitis C virus (HCV) using molecular docking studies. Journal of Pharmacy Research 4(1): pp.136-140.

2.      S. Prasanth Kumar, P. Srinivasan, Saumya K. Patel, Ravi Kapopara and Yogesh T. Jasrai, 2011. In silico development of inhibitors against pantothenate synthetase of Mycobacterium tuberculosis. Journal of Advanced Bioinformatics and Research 2(2): pp. 142-148.

3.    Saumya K. Patel, S. Prasanth Kumar, Himanshu A. Pandya, Yogesh T. Jasrai and Mehul I. Patni, 2011. 2D-QSAR analysis of dihydrofolate reductase (DHFR) inhibitors with activity in Toxoplasma gondii and Lactobacillus casei. Journal of Advanced Bioinformatics and Research 2(2): pp.161-166.

4.  S. K. Patel, S. Prasanth Kumar, Y. T. Jasrai, H. A. Pandya and R. M. Rawal, 2011. Computational analysis of naturally occurring marine compounds (NOMC) targeting gap junctions and cell adhesive molecules for the identification of anticancer drug targets. The Journal of Computational Intelligence in Bioinformatics 4(2): pp. 161-171.

5.   S. Prasanth Kumar, 2011. Organic Virtual Library (ORVIL) – A combinatorial library construction based on organic constituents and without scaffold hopping. International Journal of Applied Research on Information Technology and Computing 2(2): pp.57-62.

6.   S. Prasanth Kumar and Muthusamy Meenatchi, 2011. Virtual quantification of protein stability using applied kinetic and thermodynamic parameters. IIOAB Letters 1: pp.21-28.

7.    Ravi Kapopara, S. Prasanth Kumar, Saumya K. Patel, Dhananjay K. Sadhu, Yogesh T. Jasrai, Himanshu A. Pandya and Rakesh M. Rawal, 2011. Virtual screening of natural bioactives in combating cancer through epigenetic modulation. South Asian Journal of Experimental Biology 1(5-S1): pp.12-16.

8.      Pappu Srinivasan, Sivakumar Prasanth Kumar, Muthusamy Karthikeyan, Jeyaram Jeyakanthan, Yogesh T. Jasrai, Himanshu A. Pandya, Rakesh M. Rawal and Saumya K. Patel, 2011. Epitope-based immunoinformatics and molecular docking studies of nucleocapsid protein and ovarian tumor domain of Crimean-Congo hemorrhagic fever virus. Frontiers in Bioinformatics and Computational Biology 2(72): 1-9. doi: 10.3389/fgene.2011.00072. PMID: 22303367; PMC3268625.

                                                                                            

9.   S. Prasanth Kumar, Ravi G. Kapopara, Saumya K. Patel, Mehul I. Patni, Yogesh T. Jasrai, Himanshu A. Pandya and Rakesh M. Rawal, 2011. Molecular descriptor enhancement of a common structure towards the development of α-glucosidase and α-amylase inhibitors for post-prandial hyperglycemia (PPHG). Asian Journal of Biomedical and Pharmaceutical Sciences 1(3): pp.01-12.

10. S. Prasanth Kumar, Ravi G. Kapopara, Yogesh. T. Jasrai and Rakesh M. Rawal, 2012. Computational studies on the interaction of core histone tail domains with CpG island.  International Journal of Pharma and Biosciences 3(1): pp. B581-590.

11.  S. Prasanth Kumar, Ravi G. Kapopara, Saumya K. Patel, Himanshu A. Pandya and Yogesh T. Jasrai, 2012. Conformational Ensemble of Digoxin and Digitoxin and its Interamolecular Energy in Torsional Space. International Journal of Pharmacy and Biological Sciences 2(2): pp. 57-66.  

12.  S. Prasanth Kumar, Ravi G. Kapopara, Mehul I. Patni, Himanshu A. Pandya, Yogesh T. Jasrai and Saumya K. Patel. Exploring the Polymerase Activity of Chikungunya Viral non structural Protein 4 (nsP4) using Molecular Modeling, e-Pharmacophore and Docking Studies. International Journal of Pharmacy and Life Sciences 3(6): pp. 1752-1765.

13.  Saumya Patel, S. Prasanth Kumar and Mehul Patni, 2012. Statistical and Biocomputational Studies on Spondyloarthritis. Tatiana Melnic (Ed), LAP LAMBERT Academic Publishing GmbH & Co. KG, Saarbrűcken, Germany, ISBN: 978-3-659-14306-9.

14.  S. Prasanth Kumar, Saumya K. Patel and Himanshu A. Pandya, 2012. Normal and binding mode analysis of breast cancer resistance protein. Alina Covali (Ed), LAP LAMBERT Academic Publishing GmbH & Co. KG, Saarbrűcken, Germany, ISBN: 978-3-659-15312-9.

15.  Saumya Patel, Prasanth Kumar and Yogesh T. Jasrai, 2012. Molecular Optimization of Calcineurin Inhibitors for Prion Disease: A Pharmacophore Study. Tatiana Melnic (Ed), LAP LAMBERT Academic Publishing GmbH & Co. KG, Saarbrűcken, Germany, ISBN: 978-3-659-15895-7.

16.  S. Prasanth Kumar. CpGP dynamics- The dynamics of CpG island and promoter to validate nucleosomal gene expression. International Journal of Bio-Science and Bio-Technology 4(2): pp. 11-26. Program is accessible at http://cpgpdynamics.webs.com.

17.  S. Prasanth Kumar. Docking and in silico bioavailability analysis of CDK6 flavonol inhibitors and its analogues for acute lymphoblastic leukemia. The Journal of Computational Intelligence in Bioinformatics, Accepted.

18.  S. Prasanth Kumar, Saumya K. Patel, Yogesh T. Jasrai,  Himanshu A. Pandya and P. Srinivasan, 2012. Biocomputational analysis of citrullinated fillagrin sequence repeats for rheumatoid arthritis. Electronic Journal of Biology, 8(2):29-33.

ABSTRACTS PUBLICATION AND POSTERS PRESENTATION:

1. Poster Presented and Recognized as Best Research Work in the 4th Seminar on Modern Laboratory Techniques in Molecular Biology on the topic “in silico Epitope-based Immunoinformatics and Molecular Docking Studies of Nucleocapsid Protein (NP) and Ovarian Tumor (OTU) Domain of Crimean-Congo Haemorrhagic Fever Virus (CCHFV)” held at Gujarat Cancer and Research Institute (GCRI), Ahmedabad on Feb 28, 2011.

2. Presented a work on “Initiation of Eukaryotic Genome Replication: Interaction of RFC and Brd4 proteins” in Tamil National Scientific Conference, held at Alagappa University between Sept 11-13, 2009 and published ISBN-93-80043-33-3

3. S. Prasanth Kumar, Ravi G. Kapopara, Saumya K. Patel, Yogesh T. Jasrai, Himanshu A. Pandya and Rakesh M. Rawal. Emergence of Indian Tomato Yellow Leaf Curl Viral (TYLCV) Disease:  Insights from Evolutionary Divergence and Molecular Prospects of Coat Protein. (Proceedings of the National Symposium on Evolving Paradigm to Improve Productivity from Dynamic Management and Value Addition for Plant Genetic Resources, Theme: Bioinformatics and Use of Newer Technologies, pp. 158).

4. Ravi G. Kapopara, S. Prasanth Kumar, Yogesh T. Jasrai, Himanshu A. Pandya and Rakesh M. Rawal. Management of Diabetes by Developing New Alpha Glucosidase Inhibitors (AGIs). (Proceedings of the National Symposium on Evolving Paradigm to Improve Productivity from Dynamic Management and Value Addition for Plant Genetic Resources, Theme: Bioinformatics and Use of Newer Technologies, pp. 162).

5. Saumya K. Patel, S. Prasanth Kumar, Ravi G. Kapopara, Yogesh T. Jasrai and Himanshu A. Pandya. Plant Bioactive Driven Fragment-based Drug Designing and Epitope-baesd Immunoinformatics Study of EspC protein of Mycobacterium tuberculosis. (Proceedings of the National Symposium on Evolving Paradigm to Improve Productivity from Dynamic Management and Value Addition for Plant Genetic Resources, Theme: Bioinformatics and Use of Newer Technologies, pp. 166).

6. Mehul I. Patni, S. Prasanth Kumar, Saumya K. Patel, Yogesh T. Jasrai and Himanshu A. Pandya. 2D-QSAR Analysis of ACE Inhibitors with Activity in Oryctolagus cuniculus and Rattus norvegicus. (Proceedings of the National Symposium on Evolving Paradigm to Improve Productivity from Dynamic Management and Value Addition for Plant Genetic Resources, Theme: Bioinformatics and Use of Newer Technologies, pp. 167).

7. Vishal H. Desai, Chirag N. Patel, Vijay P. Mehta, S. Prasanth Kumar, Yogesh T. Jasrai and Himanshu A. Pandya. Bioinformatic analysis on Maize sugary1 gene (Proceedings of the National Symposium on Evolving Paradigm to Improve Productivity from Dynamic Management and Value Addition for Plant Genetic Resources, Theme: Budding Researchers, pp. 173).

ABSTRACTS PUBLISHED IN THE NATIONAL SYMPOSIUM

ABSTRACTS PUBLISHED IN THE Proceedings of the National Symposium on Evolving Paradigm to Improve Productivity from Dynamic Management and Value Addition for Plant Genetic Resources, held at Department of Botany, Gujarat University, Ahmedabad- 380 009 between Oct 13-15, 2011.

Download these abstracts in PDF format here: http://www.slideshare.net/prasanthperceptron/soft-copy-of-abstracts

Code: IO- 2 Emergence of Indian Tomato Yellow Leaf Curl Viral (TYLCV) Disease:  Insights from Evolutionary Divergence and Molecular Prospects of Coat Protein

(Young Scientist Awarded Presentation)


DOWNLOAD THE PRESENTATION HERE:
http://www.slideshare.net/prasanthperceptron/s-prasanth-kumar-young-scientist-awarded-presentation

S. Prasanth Kumar¹, Ravi G. Kapopara^1, Saumya K. Patel¹, Yogesh T. Jasrai*, Himanshu A. Pandya¹ and Rakesh M. Rawal²

¹Bioinformatics Laboratory, Department of Botany, University School of Sciences,Gujarat University, Ahmedabad- 380 009. ²Division of Medicinal Chemistry and Pharmacogenomics, Department of Cancer  Biology, The Gujarat Cancer & Research Institute (GCRI), Ahmedabad- 380 016.

ABSTRACT

Tomato leaf curl disease (TLCD) is manifested by yellowing of leaf lamina with upward leaf curl, leaf distortion, shrinking of the leaf surface and stunted plant growth caused by tomato yellow leaf curl virus (TYLCV). In the present study, we explored the evolutionary and molecular prospects of viral coat protein derived from an isolate of Vadodara district, Gujarat (ToLCGV-[Vad]). We found that the amino acids in coat protein required for systemic infection, viral particle formation and insect transmission to host cells were sufficiently diverged. Modeling of coat protein revealed a topology similar to characteristic Geminate viral particle consisting of antiparallel β-barrel motif with N-terminus α-helix. The molecular interaction of coat protein with the plant DNA required for host cell arrest and propagation of viral particle was studied. We further emphasized the role of loops in coat protein structure as molecular recognition interface.

Keywords: Tomato leaf curl disease, Tomato yellow leaf curl virus, Geminate viral particle, Evolution, Modeling.

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Code: IO-6 Management of Diabetes by Developing New Alpha Glucosidase Inhibitors (AGIs)

Ravi G. Kapopara*¹ S. Prasanth Kumar¹, Yogesh T. Jasrai¹, Himanshu A. Pandya¹ and Rakesh M. Rawal²

¹Bioinformatics Laboratory, Department of Botany, University School of Sciences, Gujarat University, Ahmedabad- 380 009. ²Division of Medicinal Chemistry and Pharmacogenomics, Department of Cancer  Biology, The Gujarat Cancer & Research Institute (GCRI), Ahmedabad- 380 016.

ABSTRACT

The most challenging goal in the management of diabetic patient is to achieve normal blood glucose levels caused by post-prandial hyperglycemia (PPHG) or hyperinsulinemia, the individual risk factor contributes to the development of macrovascular complications. Synthetic hypoglycemic agents are available which has its own limitations and serious side-effects. The present study deals about the development of a common small molecular structure by enhancing the molecular descriptors required for binding with α-glucosidase and α-amylase enzymes, the two major targets of PPHG and to develop a monosaccharide-type inhibitor with many insights derived from pharmacophore studies, molecular alignment and molecular docking studies of known inhibitors. A hypothesis was designed which suggest the essential and/or minimal requirement of molecular descriptors to be an efficient binder of these two hydrolytic enzymes and subsequently, molecules with naturally occurring flavonoid structural architecture obeying the hypothesis was developed and evaluated in silico.

Keywords: Post-prandial hyperglycemia, Molecular descriptors, α-glucosidase, α-amylase, Pharmacophore features, Molecular docking, Hypothesis design.
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Code: IP-3 Plant Bioactive Driven Fragment-based Drug Designing and Epitope-based Immunoinformatics Study of  EspC protein of Mycobacterium tuberculosis

Saumya K. Patel¹, S. Prasanth Kumar¹, Ravi G. Kapopara¹, Yogesh T. Jasrai¹ and Himanshu A. Pandya¹

¹Bioinformatics Laboratory, Department of Botany, University School of Sciences, Gujarat University, Ahmedabad- 380 009

ABSTRACT

Multi-drug resistant Mycobacterium tuberculosis is one of the major obstacles for the treatment of tuberculosis. ESX-1 secretion system establishes infection in host cells by secreting virulence factors. Genes belonging to this system are attenuated in currently used BCG vaccine strain and are no longer proven efficacy in treating tuberculosis. In the present study, vasicine, a plant bioactive from Vasaka herb having known antitubercular properties is used to develop inhibitors against a chief component of the ESX-1 secretory pathway, called EspC through fragment-based drug designing approach. Epitope-based immunoinformatics study of EspC protein is also carried out which showed regions of interest for developing vaccines with due consideration across all the genetically heterogeneous inheritance. It is found that designing T-cell epitopes against the C-terminal region of EspC protein will have greater benefits as compared to other regions as it acts as a recognition element for its cognate AAA ATPases and protein interaction.  Hence, designing inhibitors based on plant bioactive with known activity will direct to the generation of potential antitubercular lead molecules. In the other hand, the in vitro expression studies of EspC in individuals with heterogeneous genetic inheritance will helpful in choosing a better region for developing vaccine without any harm to the human.

Key-words: ESX-1 secretion system, Vasaka herb, fragment-based drug designing, immunoinformatics
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Code: IP-4 2D-QSAR Analysis of ACE Inhibitors with Activity in   Oryctolagus cuniculus and Rattus norvegicus 


Mehul I. Patni¹, S. Prasanth Kumar¹, Saumya K. Patel¹,  Yogesh T. Jasrai*¹ and Himanshu A. Pandya¹

¹Bioinformatics Laboratory, Department of Botany, University School of Sciences, Gujarat University, Ahmedabad- 380 009

ABSTRACT

Quinapril, an inhibitor of angiotensin-converting enzyme (ACE), is a known drug prescribed in the treatment of hypertension and congestive heart failure. Due to its side effect such as angioedema, the patient has to discontinue the chemotherapy. In the present study, ACE inhibitors which are structurally similar to Quinapril and had reported biological activity in model organisms such as Oryctolagus Cuniculus and Rattus norvegicus was considered. A 2D-QSAR was modeled based on certain topological and constitutional descriptors along with its biological activity and found best inhibitory molecules. in vitro validation of these inhibitors will be an alternative for effective drug development against  hypertension.

Keywords: Quinapril, ACE inhibitors, hypertension, 2D-QSAR, Descriptors
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Code: JP-5 Bioinformatics analysis on Maize sugary 1 gene


DOWNLOAD THE POSTER IN PPT FORMAT HERE:
http://www.slideshare.net/prasanthperceptron/maize-poster

Vishal H. Desai, Chirag N. Patel, Vijay P. Mehta, S. Prasanth Kumar, Yogesh T. Jasrai and Himanshu A. Pandya

Bioinformatics Laboratory, Department of Botany, Gujarat University,  Ahmedabad-380 009.

ABSTRACT

Maize (Zea mays Linn.) holds a unique position in the global agricultural ground due to its high carbohydrate content. Maize sugary 1 (su1) gene encodes an essential starch debranching enzyme (SBEIIb) which hydrolysis α-(1→6) glycosidic bonds involved in starch biosynthesis. Genetic mutations in this gene contributes for the shrunken and immature kernel phenotypically and accumulation of simple sugars genotypically. In the present study, su1 gene was analyzed using Bioinformatics approaches. We made attempts to search for homologs in other sugar-rich plants. The maize su1 gene was predicted to be the characteristic feature promoting starch content and no evolutionary trace was identified. Further, maize cultivars distributed throughout the world showed a conserved pattern. We also noticed that the contents of GC bases are found to be relatively higher showing signs of highly de-regularized gene structure (CpG island). Conceptual translation of gene sequence provided an insight of ordered structure with a single stretch of disorderness at its N-terminal. Thus, we emphasize that the de-regularized gene structure of su1 makes its own way to diverge from other plant genera and the protein (enzyme) secondary structure level information showed that it is dense with high helix- rich content and a member of isoamylase enzyme family.

Keywords: Sugary 1 gene, Starch debranching enzyme, Bioinformatics, GC content, Disorderness.