Summary.
This is the continuation of our studies on the prediction of mutation engineered by randomness in proteins from influenza A virus. In our previous studies, we have demonstrated that randomness plays a role in engineering mutations because the measures of randomness in protein are different before and after mutations. Thus we built a cause-mutation relationship to count the mutation engineered by randomness, and conducted several concept-initiated studies to predict the mutations in proteins from influenza A virus, which demonstrated the possibility of prediction of mutations along this line of thought. On the other hand, these concept-initiated studies indicate the directions forwards the enhancement of predictability, of which we need to use the neural network instead of logistic regression that was used in those concept-initiated studies to enhance the predictability. In this proof-of-concept study, we attempt to apply the neural network to modeling the cause-mutation relationship to predict the possible mutation positions, and then we use the amino acid mutating probability to predict the would-be-mutated amino acids at predicted positions. The results confirm the possibility of use of internal cause-mutation relationship with neural network model to predict the mutation positions and use of amino acid mutating probability to predict the would-be-mutated amino acids.
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Wu G, Yan S (2007c) Prediction of mutations initiated by internal power in H3N2 hemagglutinins of influenza A virus from North America. Int J Pept Res Ther, http://dx.doi.org/10.1007/s10989-007-9104-1
Wu G, Yan S (2007d) Prediction of mutations engineered by randomness in H5N1 neuraminidases from influenza A virus. Amino Acids, http://dx.doi.org/10.1007/s00726-007-0579-z
G Wu S Yan (2007e) Translation probability between RNA codons and translated amino acids, and its applications to protein mutations MH Ostrovskiy (Eds) Leading-edge Messenger RNA Research Communications Nova Science Publishers New York 47–65
R Zhang DQ Wei QS Du KC Chou (2006) ArticleTitleMolecular modeling studies of peptide drug candidates against SARS Med Chem 2 309–314 Occurrence Handle16948478 Occurrence Handle10.2174/157340606776930736 Occurrence Handle1:CAS:528:DC%2BD28XmtFSlt7s%3D
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Authors’ address: G. Wu, Computational Mutation Project, DreamSciTech Consulting, 301, Building 12, Nanyou A-zone, Jiannan Road, Shenzhen, Guangdong Province CN-518054, China
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Wu, G., Yan, S. Prediction of mutations engineered by randomness in H5N1 hemagglutinins of influenza A virus. Amino Acids 35, 365–373 (2008). https://doi.org/10.1007/s00726-007-0602-4
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DOI: https://doi.org/10.1007/s00726-007-0602-4