Protein Structure Prediction And Algorithms To Minimize Docking Energy

Ayan Chatterjee

ISBN 10: 3330001569 / ISBN 13: 9783330001565

Published by LAP LAMBERT Academic Publishing Nov 2016, 2016

About this Item

This item is printed on demand - it takes 3-4 days longer - Neuware -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. 228 pp. Englisch.

Seller Inventory # 9783330001565

Bibliographic Details

• Title: Protein Structure Prediction And Algorithms To Minimize Docking Energy
• Publisher: LAP LAMBERT Academic Publishing Nov 2016
• Publication Date: 2016
• Language: English
• ISBN 10: 3330001569
• ISBN 13: 9783330001565
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 220W x 150H x 14D millimeters 220 millimeters width by 150 millimeters height by 14 millimeters depth
• Weight: 358 grams

About this title

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.

About the Author

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.