Literature DB >> 14517612

Determination of amino acid pairs in human p53 protein sensitive to mutations/variants by means of a random approach.

Guang Wu1, Shaomin Yan.   

Abstract

This is the continuation of our studies using random approaches to analyse the p53 protein family. In this data-based theoretical analysis, we use the random approach to analyse the amino acid pairs in human p53 protein in order to determine which amino acid pairs are more sensitive to 190 human p53 mutations/variants. The rationale of this study is based on our hypothesis and findings that a harmful mutation is more likely to occur at randomly unpredictable amino acid pairs, and a harmless mutation is more likely to occur at randomly predictable amino acid pairs. This is because we argue that the randomly predictable amino acid pairs should not be deliberately evolved, whereas the randomly unpredictable amino acid pairs should be deliberately evolved with a connection to protein function. The results show, for example, that 93.16% of 190 mutations/variants occur at randomly unpredictable amino acid pairs. Thus, the randomly unpredictable amino acid pairs are more sensitive to mutations/variants in human p53 protein. The results also suggest that the human p53 protein has a tendency for the occurrence of mutation/variants.

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Year:  2003        PMID: 14517612     DOI: 10.1007/s00894-003-0155-8

Source DB:  PubMed          Journal:  J Mol Model        ISSN: 0948-5023            Impact factor:   1.810


  10 in total

1.  Frequency and Markov chain analysis of amino acid sequences of mouse p53.

Authors:  G Wu
Journal:  Hum Exp Toxicol       Date:  2000-09       Impact factor: 2.903

2.  The SWISS-PROT protein sequence database and its supplement TrEMBL in 2000.

Authors:  A Bairoch; R Apweiler
Journal:  Nucleic Acids Res       Date:  2000-01-01       Impact factor: 16.971

Review 3.  TP53: a key gene in human cancer.

Authors:  D P Guimaraes; P Hainaut
Journal:  Biochimie       Date:  2002-01       Impact factor: 4.079

4.  Patterns of p53 G-->T transversions in lung cancers reflect the primary mutagenic signature of DNA-damage by tobacco smoke.

Authors:  P Hainaut; G P Pfeifer
Journal:  Carcinogenesis       Date:  2001-03       Impact factor: 4.944

Review 5.  Hepatocellular carcinoma: from gene to public health.

Authors:  R Montesano; P Hainaut; C P Wild
Journal:  J Natl Cancer Inst       Date:  1997-12-17       Impact factor: 13.506

6.  5-Methylcytosine as an endogenous mutagen in the human LDL receptor and p53 genes.

Authors:  W M Rideout; G A Coetzee; A F Olumi; P A Jones
Journal:  Science       Date:  1990-09-14       Impact factor: 47.728

7.  Specific P53 mutations are associated with de novo resistance to doxorubicin in breast cancer patients.

Authors:  T Aas; A L Børresen; S Geisler; B Smith-Sørensen; H Johnsen; J E Varhaug; L A Akslen; P E Lønning
Journal:  Nat Med       Date:  1996-07       Impact factor: 53.440

8.  Analysis of distributions of amino acids in the primary structure of tumor suppressor p53 family according to the random mechanism.

Authors:  Guang Wu; Shao-Min Yan
Journal:  J Mol Model       Date:  2002-05       Impact factor: 1.810

9.  Effects of p53 mutants on wild-type p53-mediated transactivation are cell type dependent.

Authors:  K Forrester; S E Lupold; V L Ott; C H Chay; V Band; X W Wang; C C Harris
Journal:  Oncogene       Date:  1995-06-01       Impact factor: 9.867

10.  Analysis of the most representative tumour-derived p53 mutants reveals that changes in protein conformation are not correlated with loss of transactivation or inhibition of cell proliferation.

Authors:  K Ory; Y Legros; C Auguin; T Soussi
Journal:  EMBO J       Date:  1994-08-01       Impact factor: 11.598

  10 in total
  7 in total

1.  Determination of mutation trend in proteins by means of translation probability between RNA codes and mutated amino acids.

Authors:  Guang Wu; Shaomin Yan
Journal:  Biochem Biophys Res Commun       Date:  2005-09-26       Impact factor: 3.575

Review 2.  Mutation trend of hemagglutinin of influenza A virus: a review from a computational mutation viewpoint.

Authors:  Guang Wu; Shao-Min Yan
Journal:  Acta Pharmacol Sin       Date:  2006-05       Impact factor: 6.150

3.  Reasoning of spike glycoproteins being more vulnerable to mutations among 158 coronavirus proteins from different species.

Authors:  Guang Wu; Shaomin Yan
Journal:  J Mol Model       Date:  2004-12-09       Impact factor: 1.810

4.  Potential targets for anti-SARS drugs in the structural proteins from SARS related coronavirus.

Authors:  Guang Wu; Shaomin Yan
Journal:  Peptides       Date:  2004-06       Impact factor: 3.750

5.  Prediction of amino acid pairs sensitive to mutations in the spike protein from SARS related coronavirus.

Authors:  Guang Wu; Shaomin Yan
Journal:  Peptides       Date:  2003-12       Impact factor: 3.750

6.  Prediction of mutations engineered by randomness in H5N1 hemagglutinins of influenza A virus.

Authors:  G Wu; S Yan
Journal:  Amino Acids       Date:  2007-11-02       Impact factor: 3.520

7.  Prediction of mutations engineered by randomness in H5N1 neuraminidases from influenza A virus.

Authors:  G Wu; S Yan
Journal:  Amino Acids       Date:  2007-08-28       Impact factor: 3.520

  7 in total

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