Protein Function Prediction Using Neighbor Counting with Dynamic Threshold from Protein-Protein Interaction Network
Md. Khaled Ben Islam,
Julia Rahman,
Md. Al Mehedi Hasan,
Mohammed Nasser
Issue:
Volume 3, Issue 1, February 2015
Pages:
1-5
Received:
10 January 2015
Accepted:
26 January 2015
Published:
2 February 2015
Abstract: In recent years, a large number of proteins of different organisms have been discovered but due to high experimental cost and uncertain time boundary, yet it is not possible to find out all of the functionalities of those proteins. With the recent advent of huge protein-protein interactions, it becomes an opportunity to computationally predict a protein’s functionality based on its interacting partners. In this work, we mainly try to find out a way by which we can predict functionality of a target protein with low computational complexity. We propose a simple approach for protein function prediction based on Classical Neighbor Counting method. We also investigate the functional dependency of a protein to its direct neighbors in the interaction network. We find that when majority of its interacting partners have more experimentally known annotation, then more accurately we can predict a protein’s functionality using Neighbor Counting technique.
Abstract: In recent years, a large number of proteins of different organisms have been discovered but due to high experimental cost and uncertain time boundary, yet it is not possible to find out all of the functionalities of those proteins. With the recent advent of huge protein-protein interactions, it becomes an opportunity to computationally predict a pr...
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In-Silico Evaluation of the Capsid Proteins of FMDV as Potential Vaccine Candidates
F. M. N. Hassan,
Md. Shaifur Rahman,
K. M. T. Rahman,
Sharmin S. Sumi,
Md. F. Islam,
Md. Badrul Alam,
Md. Giasuddin,
Khondoker M. Hossain
Issue:
Volume 3, Issue 1, February 2015
Pages:
6-20
Received:
23 November 2014
Accepted:
2 March 2015
Published:
9 March 2015
Abstract: In this study, the capsid proteins of four major serotypes of Foot and Mouth Disease Virus (FMDV) were assessed as the vaccine candidates. Different protein sequences regarding FMDV capsid of O, A, Asia 1 and C type were identified from NCBI Genome Database and UniprotKB. Phylogenetic tree of the four serotypes was developed using ClustalW software. HMMTOP, RANKPEP, Swiss-Model and Vaxign software were used for comparing the capsid proteins in terms of their feasibility as vaccine candidates. The virus and viral serotype were identified from the cultured disease sample using RT-PCR. Our results revealed that different capsid proteins of the four serotypes vary in their suitability to be considered as peptide vaccine components. Viral protein 1 (VP1) for Asia 1 serotype represented the best result as a vaccine candidate. The VP1 region of Asia 1 serotype amplified based on the result of dry lab analysis. Our findings provide a future indication of multivalent vaccine development against FMDV.
Abstract: In this study, the capsid proteins of four major serotypes of Foot and Mouth Disease Virus (FMDV) were assessed as the vaccine candidates. Different protein sequences regarding FMDV capsid of O, A, Asia 1 and C type were identified from NCBI Genome Database and UniprotKB. Phylogenetic tree of the four serotypes was developed using ClustalW software...
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