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Biochemical Parameters Based Structural Classification of HIV Proteins

Anubha Dubey, Dr. Usha Chouhan

Abstract


Solution NMR spectroscopy, X-ray crystallography, fiber diffraction, neutron diffraction are the fundamental structure determination methods in the development of many scientific fields. The methods also revealed the structure and functioning of many biological molecules, including vitamins, drugs, proteins and nucleic acids such as DNA. X-ray crystallography is still the chief method for characterizing the atomic structure of new materials and in discerning materials that appear similar by other experiments. Looking towards the importance of the structure determination methods the HIV enzyme secondary structures is taken to classify and predict on the basis of their biochemical and physicochemical methods like resolution, Ph, temperature, number of non hydrogen atoms and other parameters by machine learning techniques. Machine learning techniques are fast and economical and predict better results of classification and prediction. The accuracies of all the predicted parameters are predicted as 96.5217%.

Keywords


Accuracy, Classification, Prediction Resolution, Temperature

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References


http://en.wikipedia.org/wiki/Secondary_structure#Secondary_structure

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A.Dubey, B.Pant and Neeru Adlakha,”SVM Model for Amino Acid Composition based Classification of HIV1 Groups”. IEEE digital library published.

A.Dubey, B.Pant and Usha Chouhan,” SVM Model for Classification of Structural and Regulatory Proteins of HIV1 and HIV2 Journal of Advanced Bioinformatics Applications and Research ISSN 0976-2604 Vol 2, Issue 1, 2011, pp 84-88

A.Dubey, B.Pant and Usha Chouhan,” Machine learning model for HIV1 and HIV2 enzyme secondary structure classification “J. Comput. Method. Mol. Design, 2011, 1 (2): 1-8

http://www.cs.waikato.ac.nz/~ml/weka/


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