Protein Structure Prediction And Algorithms To Minimize Docking Energy - Couverture souple

Chatterjee, Ayan; Roy, Uttam Kumar

 
9783330001565: Protein Structure Prediction And Algorithms To Minimize Docking Energy
Couverture souple
ISBN 10 : 3330001569 ISBN 13 : 9783330001565
Editeur : LAP LAMBERT Academic Publishing, 2016

Synopsis

Computational Drug Design is important as it reduces conventional research deadline and cost. Here we have considered structure based drug design where we have identified a protein target and performed optimization study to find a molecule or ligand that suitably fits in the target pocket. Different docking strategies are considered to make it more efficient with evolutionary algorithms. Our algorithm assumes a variable length tree structure which represents a drug molecule and arranges essential functional groups in different positions of that drug. Once the geometry of the drug is obtained, its docking energy is minimized. We have also considered several intermolecular forces for more accuracy. Results show that PSO performs better than the earlier methods. We have prepared a set of molecules having energy less than a threshold value. All these molecules are the potential drugs for a particular protein. These set of molecules will help the biologists or pharmacists to choose the best drug for a particular disease with very less effort. We have also incorporated different tool based study and do performance analysis of AutoDock & AutoDock Vina.

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

Présentation de l'éditeur

Computational Drug Design is important as it reduces conventional research deadline and cost. Here we have considered structure based drug design where we have identified a protein target and performed optimization study to find a molecule or ligand that suitably fits in the target pocket. Different docking strategies are considered to make it more efficient with evolutionary algorithms. Our algorithm assumes a variable length tree structure which represents a drug molecule and arranges essential functional groups in different positions of that drug. Once the geometry of the drug is obtained, its docking energy is minimized. We have also considered several intermolecular forces for more accuracy. Results show that PSO performs better than the earlier methods. We have prepared a set of molecules having energy less than a threshold value. All these molecules are the potential drugs for a particular protein. These set of molecules will help the biologists or pharmacists to choose the best drug for a particular disease with very less effort. We have also incorporated different tool based study and do performance analysis of AutoDock & AutoDock Vina.

Biographie de l'auteur

Ayan Chatterjee, ME: Studied Masters of Engineering at Jadavpur University. Senior Software Developer & Designer at Tata Consultancy Services LTD, India.Overseas Experience: TDC & YOUSEE Projects, Denmark. Research Interest: Bio-Informatics, Evolutionary Algorithms & Networking.

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
2016
Langue
anglais
ISBN 10 
3330001569
ISBN 13 
9783330001565
Reliure
Broché
Nombre de pages
228
Coordonnées du fabricant
non disponible
Personne responsable
KreGa Onlinehandel GmbH
4950000000000
info@krega-onlinehandel.de

Birkenweg 31
Brakel
33034
Allemagne