Literature DB >> 18510993

Effect of deleterious nsSNP on the HER2 receptor based on stability and binding affinity with herceptin: a computational approach.

R Rajasekaran1, C George Priya Doss, C Sudandiradoss, K Ramanathan, Rituraj Purohit, Rao Sethumadhavan.   

Abstract

In this study, we identified the most deleterious non-synonymous SNP of ERBB2 (HER2) receptors by its stability and investigated its binding affinity with herceptin. Out of 135 SNPs, 10 are nsSNPs in the coding region, in which one of the nsSNP (SNPid rs4252633) is commonly found to be damaged by I-Mutant 2.0, SIFT and PolyPhen servers. With this effort, we modelled the mutant HER2 protein based on this deleterious nsSNP (rs4252633). The modeled mutant showed less stability than native HER 2 protein, based on both total energy of the mutant and stabilizing residues in the mutant protein. This is due to a deviation between the mutant and the native HER2, having an RMSD of about 2.81 A. Furthermore, we compared the binding efficiency of herceptin with native and mutant HER2 receptors. We found that herceptin has a high binding affinity with mutant HER2 receptor, with a binding energy of -24.40 kcal/mol, as compared to the native type, which has a binding energy of -15.26 kcal/mol due to six-hydrogen bonding and two salt bridges exist between herceptin and the mutant type, whereas the native type establishes four hydrogen bonds and two salt bridges with herceptin. This analysis portrays that mutant type has two additional hydrogen bonds with herceptin compared with the native type. Normal mode analysis also showed that the two amino acids, namely Asp596 and Glu598 of mutant HER2, forming additional hydrogen bonding with herceptin, had a slightly higher flexibility than the native type. Based on our investigations, we propose that SNPid rs4252633 could be the most deleterious nsSNP for HER2 receptor, and that herceptin could be the best drug for mutant compared to the native HER2 target.

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Year:  2008        PMID: 18510993     DOI: 10.1016/j.crvi.2008.03.004

Source DB:  PubMed          Journal:  C R Biol        ISSN: 1631-0691            Impact factor:   1.583


  11 in total

1.  Computational detection of deleterious SNPs and their effect on sequence and structural level of the VHL gene.

Authors:  R Rajasekaran; C Sudandiradoss; C George Priya Doss; Anshuman Singh; Rao Sethumadhavan
Journal:  Mamm Genome       Date:  2008-10-03       Impact factor: 2.957

2.  Exploring the structural and functional impact of the ALK F1174L mutation using bioinformatics approach.

Authors:  Anish Kumar; K Ramanathan
Journal:  J Mol Model       Date:  2014-06-21       Impact factor: 1.810

Review 3.  On the role of electrostatics in protein-protein interactions.

Authors:  Zhe Zhang; Shawn Witham; Emil Alexov
Journal:  Phys Biol       Date:  2011-05-13       Impact factor: 2.583

4.  In silico analysis of drug-resistant mutant of neuraminidase (N294S) against oseltamivir.

Authors:  V Karthick; V Shanthi; R Rajasekaran; K Ramanathan
Journal:  Protoplasma       Date:  2012-03-06       Impact factor: 3.356

5.  A comprehensive in silico analysis of the functional and structural impact of SNPs in the IGF1R gene.

Authors:  S A de Alencar; Julio C D Lopes
Journal:  J Biomed Biotechnol       Date:  2010-06-23

6.  An In Silico Evaluation of Deleterious Nonsynonymous Single Nucleotide Polymorphisms in the ErbB3 Oncogene.

Authors:  Dhwani Raghav; Vinay Sharma
Journal:  Biores Open Access       Date:  2013-06

7.  Stability of domain structures in multi-domain proteins.

Authors:  Ramachandra M Bhaskara; Narayanaswamy Srinivasan
Journal:  Sci Rep       Date:  2011-07-18       Impact factor: 4.379

8.  ERBB2 in cat mammary neoplasias disclosed a positive correlation between RNA and protein low expression levels: a model for erbB-2 negative human breast cancer.

Authors:  Sara Santos; Cláudia S Baptista; Rui M V Abreu; Estela Bastos; Irina Amorim; Ivo G Gut; Fátima Gärtner; Raquel Chaves
Journal:  PLoS One       Date:  2013-12-26       Impact factor: 3.240

9.  In Silico Analysis of SNPs in PARK2 and PINK1 Genes That Potentially Cause Autosomal Recessive Parkinson Disease.

Authors:  Yousuf Hasan Yousuf Bakhit; Mohamed Osama Mirghani Ibrahim; Mutaz Amin; Yousra Abdelazim Mirghani; Mohamed Ahmed Salih Hassan
Journal:  Adv Bioinformatics       Date:  2016-12-29

10.  Extrapolating the effect of deleterious nsSNPs in the binding adaptability of flavopiridol with CDK7 protein: a molecular dynamics approach.

Authors:  C George Priya Doss; N Nagasundaram; Chiranjib Chakraborty; Luonan Chen; Hailong Zhu
Journal:  Hum Genomics       Date:  2013-04-05       Impact factor: 4.639

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