Sinossi
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.
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
L'autore
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.
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Protein Structure Prediction And Algorithms To Minimize Docking Energy
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LAP LAMBERT Academic Publishing Nov 2016, 2016
ISBN 10: 3330001569
ISBN 13: 9783330001565
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Taschenbuch. Condizione: Neu. 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. Codice articolo 9783330001565
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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Chatterjee AyanAyan 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 In. Codice articolo 158246798
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Protein Structure Prediction And Algorithms To Minimize Docking Energy
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Taschenbuch. Condizione: Neu. Protein Structure Prediction And Algorithms To Minimize Docking Energy | Ayan Chatterjee (u. a.) | Taschenbuch | 228 S. | Englisch | 2016 | LAP LAMBERT Academic Publishing | EAN 9783330001565 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu. Codice articolo 107938458
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Protein Structure Prediction And Algorithms To Minimize Docking Energy
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Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. 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.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 228 pp. Englisch. Codice articolo 9783330001565
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Protein Structure Prediction And Algorithms To Minimize Docking Energy
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LAP LAMBERT Academic Publishing, 2016
ISBN 10: 3330001569
ISBN 13: 9783330001565
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Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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. Codice articolo 9783330001565
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