Articles liés à Prediction of Catalytic Residues in Protein Active...

Prediction of Catalytic Residues in Protein Active Site by SVM: A Structure Based Drug Designing Approach - Couverture souple

Yadav, Brijesh; Varadwaj, Pritish

 
9783846582923: Prediction of Catalytic Residues in Protein Active Site by SVM: A Structure Based Drug Designing Approach
Couverture souple
ISBN 10 : 3846582921 ISBN 13 : 9783846582923
Editeur : LAP LAMBERT Academic Publishing, 2012

Synopsis

In this study,prediction of physiochemical properties of catalytic sites residues using a suitable Artificial Neural Networking (ANN) Backpropagation algorithm coupled with a set of structural proteins with the properties of their amino acid residues. The method has been applied to a set of 100 structural proteins from the Protein Data Bank (PDB.Using Ligplot program for searching of active site residues the identified amino acid residues were classified in 15 different categories based on their physiochemical properties. After classification of active and non active site amino acids, their properties were converted into machine language. Furthermore, we created Neural Network Using Matlab software and generated algorithm for training and testing of data. Thereafter, analysis of results showed that 95% of active site’s physiochemical properties were correctly predicted. It is hoped that this work would help in determining the surface topographic properties for ligand binding sites residues in protein. The computational outcome would be helpful in ligand designing,and structural identification and functional sites Comparison.

Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.

Présentation de l'éditeur

In this study,prediction of physiochemical properties of catalytic sites residues using a suitable Artificial Neural Networking (ANN) Backpropagation algorithm coupled with a set of structural proteins with the properties of their amino acid residues. The method has been applied to a set of 100 structural proteins from the Protein Data Bank (PDB.Using Ligplot program for searching of active site residues the identified amino acid residues were classified in 15 different categories based on their physiochemical properties. After classification of active and non active site amino acids, their properties were converted into machine language. Furthermore, we created Neural Network Using Matlab software and generated algorithm for training and testing of data. Thereafter, analysis of results showed that 95% of active site’s physiochemical properties were correctly predicted. It is hoped that this work would help in determining the surface topographic properties for ligand binding sites residues in protein. The computational outcome would be helpful in ligand designing,and structural identification and functional sites Comparison.

Biographie de l'auteur

Prediction of catalytic residue in protein active site by Artificial Neural Networking is the my master thesis work.I am doing my PhD work in Biology at Indian Veterinary Research Institute.I hope that this work will help structure-based design, and in understanding the structural basis of ligand binding on their target.

Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.

Éditeur
LAP LAMBERT Academic Publishing
Date d'édition
2012
Langue
anglais
ISBN 10 
3846582921
ISBN 13 
9783846582923
Reliure
Broché
Nombre de pages
80
Coordonnées du fabricant
non disponible
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