سامانه پشتیبانی خدمات اطلاعات

  اخبار و اعلانات

 آمار

تعداد نشریات158
تعداد شماره‌ها6,230
تعداد مقالات67,764
تعداد مشاهده مقاله115,197,919
تعداد دریافت فایل اصل مقاله89,946,049
Rahimi, Amir, Madadkar-Sobhani, Armin, Touserkani, Rouzbeh, Goliaei, Bahram. (1393). Automatic classification of highly related Malate Dehydrogenase and L-Lactate Dehydrogenase based on 3D-pattern of active sites. , 4(2), 245-260. doi: 10.22059/pbs.2014.52303
Amir Rahimi; Armin Madadkar-Sobhani; Rouzbeh Touserkani; Bahram Goliaei. "Automatic classification of highly related Malate Dehydrogenase and L-Lactate Dehydrogenase based on 3D-pattern of active sites". , 4, 2, 1393, 245-260. doi: 10.22059/pbs.2014.52303
Rahimi, Amir, Madadkar-Sobhani, Armin, Touserkani, Rouzbeh, Goliaei, Bahram. (1393). 'Automatic classification of highly related Malate Dehydrogenase and L-Lactate Dehydrogenase based on 3D-pattern of active sites', , 4(2), pp. 245-260. doi: 10.22059/pbs.2014.52303
Rahimi, Amir, Madadkar-Sobhani, Armin, Touserkani, Rouzbeh, Goliaei, Bahram. Automatic classification of highly related Malate Dehydrogenase and L-Lactate Dehydrogenase based on 3D-pattern of active sites. , 1393; 4(2): 245-260. doi: 10.22059/pbs.2014.52303

Automatic classification of highly related Malate Dehydrogenase and L-Lactate Dehydrogenase based on 3D-pattern of active sites

Progress in Biological Sciences
مقاله 9، دوره 4، شماره 2، اسفند 2014، صفحه 245-260    اصل مقاله (1.49 M)
نوع مقاله: Original Research Papers
شناسه دیجیتال (DOI): 10.22059/pbs.2014.52303
نویسندگان
Amir Rahimi1؛ Armin Madadkar-Sobhani* 2؛ Rouzbeh Touserkani* 3؛ Bahram Goliaei1
1Department of Bioinformatics, Institute of Biochemistry and Biophysics, University of Tehran, Tehran, Iran
2Department of Bioinformatics, Institute of Biochemistry and Biophysics, University of Tehran, Tehran, Iran; Department of Life Sciences, Barcelona Supercomputing Center, Barcelona, Spain
3School of Computer Sciences ,Institute for Research in Fundamental Sciences (IPM), Tehran, Iran
چکیده
Accurate protein function prediction is an important subject in bioinformatics, especially where
sequentially and structurally similar proteins have different functions. Malate dehydrogenase
and L-lactate dehydrogenase are two evolutionary related enzymes, which exist in a wide
variety of organisms. These enzymes are sequentially and structurally similar and share
common active site residues, spatial patterns and molecular mechanisms. Here, we study
various features of the active site cavity of 229 PDB chain entries and try to classify them
automatically by various classifiers including the support vector machine, k nearest neighbour
and random forest methods. The results show that the support vector machine yields the highest
predictive performance among mentioned classifiers. Despite very close and conserved patterns
among Malate dehydrogenases and L-lactate dehydrogenases, the SVM predicts the function
efficiently and achieves 0.973 Matthew’s correlation coefficient and 0.987 F-score. The same
approach can be used in other enzyme families for automatic discrimination between
homologous enzymes with common active site elements, however, acting on different
substrates.
 
کلیدواژه‌ها
active site pattern؛ L-lactate dehydrogenase؛ malate dehydrogenase؛ protein function prediction؛ spatial arrangement
آمار
تعداد مشاهده مقاله: 1,686
تعداد دریافت فایل اصل مقاله: 1,299


سامانه مدیریت نشریات علمی. قدرت گرفته از سیناوب