Bioinformatics molecular dynamics and docking pipeline analysis for high-throughput genome analysis and drug discovery oriented to personalized pain therapy in non-responsive patients.

Abstract

Event Abstract Back to Event Bioinformatics molecular dynamics and docking pipeline analysis for high-throughput genome analysis and drug discovery oriented to personalized pain therapy in non-responsive patients. Silvia Santoro1, Pasqualina D'Ursi1, Nadia Galluccio1, Martina Landini1, Alessandra Mezzelani1, Alessandro Orro1, John Hatton1, Matteo Gnocchi1, Andrea Manconi1 and Luciano Milanesi1* 1 Institute for Biomedical Technologies CNR, Italy Some functions of the nervous system are pain transduction and pain perception. These functions are directly involved in many chronic diseases due to the pain condition to which they are associated. Peripheral and central nervous system are the main targets of pain therapy. Pain therapy uses variety of drugs in relationship of severity of the illness and the degree of the patient’s response. The individual variability in response to drugs depends on different variables such as pathological (timing and severity), physiological (age, gender and weight), genetic and environmental aspects involved in pharmacokinetics and pharmacodynamics. Although patients can be classified as poor, intermediate, normal or extensive responders, 30% of patients do not respond to pain treatments. Our aim is to collect and analyse DNA samples in terminal patients to define their drug response phenotype. A bioinformatics analysis of the GWA DNA samples will be performed to identify mutations in candidate genes. A molecular dynamic study will be used to investigate the misfolding structures and the molecular docking will be applied for testing the binding activity of the drugs in use. Variants with low binding affinity will be submitted to virtual screening to identify all the potential leads by using the ZINC database of UCSF with over 21 million ligands. We have developed the molecular dynamics and docking pipeline analysis based on the High-Performance and Distributed Computing (eg. GPU and GRID clusters) to perform large scale of analysis. Data will be collected in a portal infrastructure organised in three layers: a Portal layer, an Application layer and a Data layer. The Application layer is a variety of java portlets, each of which allow the end user, depending on its permissions, to add and retrieve records stored in the Data layer. The Data layer will be subdivided into three layers: the first is a database that interacts with the Portal layer, the second contains all patients clinical data, the third and last contains personal data of the patients. The infrastructure will use a unique retrieval system that randomly codes patients information to prevent users to obtain a correlation between pathologies and personal data of the patients. This procedure will be used to support high-throughput genome analysis and drug discovery oriented to personalized pain therapy in non-responsive patients. Keywords: neuroinformatics, bioinformatics, Grid Computing, infrastructure, Pain Perception Conference: Neuroinformatics 2013, Stockholm, Sweden, 27 Aug - 29 Aug, 2013. Presentation Type: Poster Topic: Clinical neuroscience Citation: Santoro S, D'Ursi P, Galluccio N, Landini M, Mezzelani A, Orro A, Hatton J, Gnocchi M, Manconi A and Milanesi L (2013). Bioinformatics molecular dynamics and docking pipeline analysis for high-throughput genome analysis and drug discovery oriented to personalized pain therapy in non-responsive patients.. Front. Neuroinform. Conference Abstract: Neuroinformatics 2013. doi: 10.3389/conf.fninf.2013.09.00100 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 13 May 2013; Published Online: 11 Jul 2013. * Correspondence: Dr. Luciano Milanesi, Institute for Biomedical Technologies CNR, Milan, Italy, luciano.milanesi@itb.cnr.it Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Silvia Santoro Pasqualina D'Ursi Nadia Galluccio Martina Landini Alessandra Mezzelani Alessandro Orro John Hatton Matteo Gnocchi Andrea Manconi Luciano Milanesi Google Silvia Santoro Pasqualina D'Ursi Nadia Galluccio Martina Landini Alessandra Mezzelani Alessandro Orro John Hatton Matteo Gnocchi Andrea Manconi Luciano Milanesi Google Scholar Silvia Santoro Pasqualina D'Ursi Nadia Galluccio Martina Landini Alessandra Mezzelani Alessandro Orro John Hatton Matteo Gnocchi Andrea Manconi Luciano Milanesi PubMed Silvia Santoro Pasqualina D'Ursi Nadia Galluccio Martina Landini Alessandra Mezzelani Alessandro Orro John Hatton Matteo Gnocchi Andrea Manconi Luciano Milanesi Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.