317
Kumar, S., Bhola, A., & Tiwari, A. K. (2015). Classification of enzyme functional classes and
subclasses using support vector machine. In: 2015 1st International Conference on Futuristic
trend in Computational Analysis and Knowledge Management (ABLAZE-2015).
Latino, D. A. R. S., Zhang, Q. Y., & Aires-De-Sousa, J. (2008). Genome-scale classification of
metabolic reactions and assignment of EC numbers with self-organizing maps. Bioinformatics,
24(19), 2236–2244.
Lee, H. C. (2006). Structure and enzymatic functions of human CD38. Molecular Medicine, 12,
317–323.
Longo, M., & Combes, D. (1999). Thermostability of modified enzymes: A detailed study. Journal
of Chemical Technology and Biotechnology, 74, 25–32.
Markley, J. L. (1975). Observation of histidine residues in proteins by means of nuclear magnetic
resonance spectroscopy. Accounts of Chemical Research, 8, 70–80.
Martınez Cuesta, S., Furnham, N., & Thornton, J. M. (2014). The evolution of enzyme function in
the isomerases. Current Opinion in Structural Biology, 26, 121–130.
Meadows, D. H., & Jardetzky, O. (1986). Nuclear magnetic resonance studies of the structure and
binding sites of enzymes IV. Cytidine 30-monophosphate binding to ribonuclease. Proceedings
of the National Academy of Sciences, 61, 406–413.
Meshitsuka, S., Smith, G. M., & Mildvan, A. S. (1981). Proton NMR studies of the histidine residues of rabbit muscle pyruvate kinase and of its phosphoenol pyruvate complex. The Journal
of Biological Chemistry, 256, 4460–4465.
Monasterio, O. (2014). Nomenclature for the applications of nuclear magnetic resonance to the
study of enzymes. Perspectives on Science, 1, 88–97.
Monasterio, O., Nova, E., Lopez-Brauet, A., & Lagos, R. (1995). Tubulin–tyrosine ligase catalyzes
covalent binding of mfluorotyrosine to tubulin. Kinetic and 19F-NMR Studies. FEBS Letters,
374, 165–168.
Nasibov, E., & Kandemir-Cavas, C. (2009). Efficiency analysis of KNN and minimum distancebased classifiers in enzyme family prediction. Computational Biology and Chemistry, 33(6),
461–464.
Ong, S. A., Lin, H. H., Chen, Y. Z., Li, Z. R., & Cao, Z. (2007). Efficacy of different protein
descriptors in predicting protein functional families. BMC Bioinformatics, 8, 300.
Petsko, G. A., & Ringe, D. (2004). Protein structure and function. London, UK: New Science
Press. 195pp.
Rahman, S. A., Cuesta, S. M., & Thornton, J. M. (2014). EC-BLAST: A tool to automatically
search and compare enzyme reactions. Nature Methods, 11, 171–174.
Rausch, C., Weber, T., Kohlbacher, O., Wohlleben, W., & Huson, D. H. (2005). Specificity prediction of adenylation domains in nonribosomal peptide synthetases (NRPS) using transductive
support vector machines (TSVMs). Nucleic Acids Research, 33(18), 5799–5808.
Redfield, A. G., Mclntosh, L. P., & Dahlquist, F. W. (1989). Use of 13C and 15N isotope labels
for proton nuclear magnetic resonance and nuclear Overhauser effect. Structural and dynamic
studies of larger proteins and nucleic acids. Archivos de Biología y Medicina Experimentales,
22, 129–138.
Rhodes, G. (2000). Crystallography made crystal clear. San Diego, CA: Academic Press, 269pp.
Rhodes, G. (2006). Crystallography made crystal clear–A guide for users of macromolecular models (3rd ed.). London, UK: Academic Press Publications.
Robinson, P. K. (2015). Enzymes: Principles and biotechnological applications. Essays in
Biochemistry, 59, 1–41.
Rost, B. (2002). Enzyme function less conserved than anticipated. Journal of Molecular Biology,
318(2), 595–608.
Schumacher, G., Sizmann, D., & Haug, H. (1986). Penicillin acylase from E. coli: Unique gene–
protein relation. Nucleic Acids Research, 14(14), 5713–5727.
Shah, I., & Hunter, L. (1997). Predicting enzyme function from sequence: A systematic appraisal.
Proceedings of the International Conference on Intelligent Systems for Molecular Biology, 5,
276–283.
Proteins as Enzymes
Kumar, S., Bhola, A., & Tiwari, A. K. (2015). Classification of enzyme functional classes and
subclasses using support vector machine. In: 2015 1st International Conference on Futuristic
trend in Computational Analysis and Knowledge Management (ABLAZE-2015).
Latino, D. A. R. S., Zhang, Q. Y., & Aires-De-Sousa, J. (2008). Genome-scale classification of
metabolic reactions and assignment of EC numbers with self-organizing maps. Bioinformatics,
24(19), 2236–2244.
Lee, H. C. (2006). Structure and enzymatic functions of human CD38. Molecular Medicine, 12,
317–323.
Longo, M., & Combes, D. (1999). Thermostability of modified enzymes: A detailed study. Journal
of Chemical Technology and Biotechnology, 74, 25–32.
Markley, J. L. (1975). Observation of histidine residues in proteins by means of nuclear magnetic
resonance spectroscopy. Accounts of Chemical Research, 8, 70–80.
Martınez Cuesta, S., Furnham, N., & Thornton, J. M. (2014). The evolution of enzyme function in
the isomerases. Current Opinion in Structural Biology, 26, 121–130.
Meadows, D. H., & Jardetzky, O. (1986). Nuclear magnetic resonance studies of the structure and
binding sites of enzymes IV. Cytidine 30-monophosphate binding to ribonuclease. Proceedings
of the National Academy of Sciences, 61, 406–413.
Meshitsuka, S., Smith, G. M., & Mildvan, A. S. (1981). Proton NMR studies of the histidine residues of rabbit muscle pyruvate kinase and of its phosphoenol pyruvate complex. The Journal
of Biological Chemistry, 256, 4460–4465.
Monasterio, O. (2014). Nomenclature for the applications of nuclear magnetic resonance to the
study of enzymes. Perspectives on Science, 1, 88–97.
Monasterio, O., Nova, E., Lopez-Brauet, A., & Lagos, R. (1995). Tubulin–tyrosine ligase catalyzes
covalent binding of mfluorotyrosine to tubulin. Kinetic and 19F-NMR Studies. FEBS Letters,
374, 165–168.
Nasibov, E., & Kandemir-Cavas, C. (2009). Efficiency analysis of KNN and minimum distancebased classifiers in enzyme family prediction. Computational Biology and Chemistry, 33(6),
461–464.
Ong, S. A., Lin, H. H., Chen, Y. Z., Li, Z. R., & Cao, Z. (2007). Efficacy of different protein
descriptors in predicting protein functional families. BMC Bioinformatics, 8, 300.
Petsko, G. A., & Ringe, D. (2004). Protein structure and function. London, UK: New Science
Press. 195pp.
Rahman, S. A., Cuesta, S. M., & Thornton, J. M. (2014). EC-BLAST: A tool to automatically
search and compare enzyme reactions. Nature Methods, 11, 171–174.
Rausch, C., Weber, T., Kohlbacher, O., Wohlleben, W., & Huson, D. H. (2005). Specificity prediction of adenylation domains in nonribosomal peptide synthetases (NRPS) using transductive
support vector machines (TSVMs). Nucleic Acids Research, 33(18), 5799–5808.
Redfield, A. G., Mclntosh, L. P., & Dahlquist, F. W. (1989). Use of 13C and 15N isotope labels
for proton nuclear magnetic resonance and nuclear Overhauser effect. Structural and dynamic
studies of larger proteins and nucleic acids. Archivos de Biología y Medicina Experimentales,
22, 129–138.
Rhodes, G. (2000). Crystallography made crystal clear. San Diego, CA: Academic Press, 269pp.
Rhodes, G. (2006). Crystallography made crystal clear–A guide for users of macromolecular models (3rd ed.). London, UK: Academic Press Publications.
Robinson, P. K. (2015). Enzymes: Principles and biotechnological applications. Essays in
Biochemistry, 59, 1–41.
Rost, B. (2002). Enzyme function less conserved than anticipated. Journal of Molecular Biology,
318(2), 595–608.
Schumacher, G., Sizmann, D., & Haug, H. (1986). Penicillin acylase from E. coli: Unique gene–
protein relation. Nucleic Acids Research, 14(14), 5713–5727.
Shah, I., & Hunter, L. (1997). Predicting enzyme function from sequence: A systematic appraisal.
Proceedings of the International Conference on Intelligent Systems for Molecular Biology, 5,
276–283.
Proteins as Enzymes