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Computational screening and molecular dynamic simulation of breast cancer associated deleterious non-synonymous single nucleotide polymorphisms in TP53 gene.

Chitrala KN, Yeguvapalli S - PLoS ONE (2014)

Bottom Line: Among them, TP53 is one of the major genetic risk factor which is known to be mutated in many of the breast tumor types.We have predicted three deleterious coding non-synonymous single nucleotide polymorphisms rs11540654 (R110P), rs17849781 (P278A) and rs28934874 (P151T) in TP53 with a phenotype in breast tumors using computational tools SIFT, Polyphen-2 and MutDB.We have performed molecular dynamics simulations to study the structural and dynamic effects of these TP53 mutations in comparison to the wild-type protein.

View Article: PubMed Central - PubMed

Affiliation: Department of Zoology, Sri Venkateswara University, Tirupati, Andhra Pradesh, India.

ABSTRACT
Breast cancer is one of the most common cancers among the women around the world. Several genes are known to be responsible for conferring the susceptibility to breast cancer. Among them, TP53 is one of the major genetic risk factor which is known to be mutated in many of the breast tumor types. TP53 mutations in breast cancer are known to be related to a poor prognosis and chemo resistance. This renders them as a promising molecular target for the treatment of breast cancer. In this study, we present a computational based screening and molecular dynamic simulation of breast cancer associated deleterious non-synonymous single nucleotide polymorphisms in TP53. We have predicted three deleterious coding non-synonymous single nucleotide polymorphisms rs11540654 (R110P), rs17849781 (P278A) and rs28934874 (P151T) in TP53 with a phenotype in breast tumors using computational tools SIFT, Polyphen-2 and MutDB. We have performed molecular dynamics simulations to study the structural and dynamic effects of these TP53 mutations in comparison to the wild-type protein. Results from our simulations revealed a detailed consequence of the mutations on the p53 DNA-binding core domain that may provide insight for therapeutic approaches in breast cancer.

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Related in: MedlinePlus

Solvent-accessible surface area (SASA) of WT and MT versus time during A) Apo B) Holo simulations for p53C.Black: WT, red: R110P, green: P151T and blue: P278A.
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pone-0104242-g007: Solvent-accessible surface area (SASA) of WT and MT versus time during A) Apo B) Holo simulations for p53C.Black: WT, red: R110P, green: P151T and blue: P278A.

Mentions: SASA is a geometric measure of the extent to which an amino acid interacts with its environment (the solvent and the protein core). It is naturally proportional to the degree to which an amino acid is exposed to these environments [35]. A rise or fall in the SASA designates the change in exposed amino acid residues thereby affecting the tertiary structure of a protein. Results from the analysis of SASA for apo and holo simulations showed a variation among the WT and MTs (Fig. 7a-b). MTs (apo; R110P:117.5916, P151T:118.8266, P278:118.7204, holo; R110P:118.1768, P151T:118.3956, P278A:118.7466) showed a lesser average total SASA compared to the WT (apo; 119.7036, holo; 118.8847). Rg on the other hand, is a parameter to describe the equilibrium conformation of a total system particularly in analyzing the proteins it is an indicative of the level of compaction in the structure, i.e. how the polypeptide chain is folded or unfolded [36]. Rg plot for Cα atoms and protein with time over the course of 10 ns simulations during apo and holo simulations is shown in the Fig. 8a-f and Fig. 9a-f. In the Rg plot for both Cα atoms and protein, we observed a notable fluctuation in MTs compared to the WT. Among the MTs, large deviations in Rg from the WT structure were observed during the apo and holo simulations of R110P (Table 4). These results indicate that compared to other MTs, p53C might have undergone a significant structural transition due to R110P.


Computational screening and molecular dynamic simulation of breast cancer associated deleterious non-synonymous single nucleotide polymorphisms in TP53 gene.

Chitrala KN, Yeguvapalli S - PLoS ONE (2014)

Solvent-accessible surface area (SASA) of WT and MT versus time during A) Apo B) Holo simulations for p53C.Black: WT, red: R110P, green: P151T and blue: P278A.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4126775&req=5

pone-0104242-g007: Solvent-accessible surface area (SASA) of WT and MT versus time during A) Apo B) Holo simulations for p53C.Black: WT, red: R110P, green: P151T and blue: P278A.
Mentions: SASA is a geometric measure of the extent to which an amino acid interacts with its environment (the solvent and the protein core). It is naturally proportional to the degree to which an amino acid is exposed to these environments [35]. A rise or fall in the SASA designates the change in exposed amino acid residues thereby affecting the tertiary structure of a protein. Results from the analysis of SASA for apo and holo simulations showed a variation among the WT and MTs (Fig. 7a-b). MTs (apo; R110P:117.5916, P151T:118.8266, P278:118.7204, holo; R110P:118.1768, P151T:118.3956, P278A:118.7466) showed a lesser average total SASA compared to the WT (apo; 119.7036, holo; 118.8847). Rg on the other hand, is a parameter to describe the equilibrium conformation of a total system particularly in analyzing the proteins it is an indicative of the level of compaction in the structure, i.e. how the polypeptide chain is folded or unfolded [36]. Rg plot for Cα atoms and protein with time over the course of 10 ns simulations during apo and holo simulations is shown in the Fig. 8a-f and Fig. 9a-f. In the Rg plot for both Cα atoms and protein, we observed a notable fluctuation in MTs compared to the WT. Among the MTs, large deviations in Rg from the WT structure were observed during the apo and holo simulations of R110P (Table 4). These results indicate that compared to other MTs, p53C might have undergone a significant structural transition due to R110P.

Bottom Line: Among them, TP53 is one of the major genetic risk factor which is known to be mutated in many of the breast tumor types.We have predicted three deleterious coding non-synonymous single nucleotide polymorphisms rs11540654 (R110P), rs17849781 (P278A) and rs28934874 (P151T) in TP53 with a phenotype in breast tumors using computational tools SIFT, Polyphen-2 and MutDB.We have performed molecular dynamics simulations to study the structural and dynamic effects of these TP53 mutations in comparison to the wild-type protein.

View Article: PubMed Central - PubMed

Affiliation: Department of Zoology, Sri Venkateswara University, Tirupati, Andhra Pradesh, India.

ABSTRACT
Breast cancer is one of the most common cancers among the women around the world. Several genes are known to be responsible for conferring the susceptibility to breast cancer. Among them, TP53 is one of the major genetic risk factor which is known to be mutated in many of the breast tumor types. TP53 mutations in breast cancer are known to be related to a poor prognosis and chemo resistance. This renders them as a promising molecular target for the treatment of breast cancer. In this study, we present a computational based screening and molecular dynamic simulation of breast cancer associated deleterious non-synonymous single nucleotide polymorphisms in TP53. We have predicted three deleterious coding non-synonymous single nucleotide polymorphisms rs11540654 (R110P), rs17849781 (P278A) and rs28934874 (P151T) in TP53 with a phenotype in breast tumors using computational tools SIFT, Polyphen-2 and MutDB. We have performed molecular dynamics simulations to study the structural and dynamic effects of these TP53 mutations in comparison to the wild-type protein. Results from our simulations revealed a detailed consequence of the mutations on the p53 DNA-binding core domain that may provide insight for therapeutic approaches in breast cancer.

Show MeSH
Related in: MedlinePlus