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BRUSELAS: A HPC based software architecture for drug discovery on - - PowerPoint PPT Presentation

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BRUSELAS: A HPC based software architecture for drug discovery on large molecular databases Antonio-Jess Banegas-Luna Horacio Prez-Snchez Alberto Caballero Bioinformatics and High Performance Computing Research Group (BIO-HPC)

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Nombre de la presentación Nombre del profesor - Tlf: (+34) 968 00 00 00 - mail@pdi.ucam.edu

Thursday, November 30th 2017 Universidad Católica San Antonio de Murcia - Tlf: (+34) 968 27 88 00 info@ucam.edu - www.ucam.edu

BRUSELAS: A HPC based software architecture for drug discovery on large molecular databases

Antonio-Jesús Banegas-Luna Horacio Pérez-Sánchez Alberto Caballero Bioinformatics and High Performance Computing Research Group (BIO-HPC) Universidad Católica San Antonio de Murcia (UCAM)

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  • 1. Introduction
  • Virtual Screening (VS) is the use of high performance computing to analyze

large databases of chemical compounds in order to identify possible drug candidates.

  • In-vivo screening
  • Expensive in time, money and manpower.
  • Not feasible verifying all the known compounds.
  • In-silico screening or Virtual screening
  • In-silico search of drug-like candidates.
  • Performed before in-vivo screening.
  • Saves time, money and manpower.

Bioinformatics and High Performance Research Group (BIO-HPC) - http://bio-hpc.eu.

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  • 2. Why VS is a Big-Data issue?

Bioinformatics and High Performance Research Group (BIO-HPC) - http://bio-hpc.eu.

  • Compound

properties

  • Biological

activities

  • Publications
  • Ligands
  • Targets
  • Software
  • Statistics
  • VS vs Experimental
  • Validation
  • In vivo testing
  • Predictions
  • Compounds
  • Conformers
  • Interactions
  • Space on disk
  • Computation time
  • Processes
  • Multithreading
  • Heuristics
  • Drug designing
  • New predictions
  • Extensive to other

diseases

  • Populate

databases

5Vs of Big Data

Variety Volume Velocity Veracity Value

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  • 3. Proposed solution: Drawbacks & needs

Bioinformatics and High Performance Research Group (BIO-HPC) - http://bio-hpc.eu.

Difficult integration of VS tools Multiple task to handle Several combinations to explore Low flexibility in experiments Easy tooling integration Easy interpretation of results High level of customization Accuracy & Speed

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  • 3. Proposed solution: BRUSELAS

Bioinformatics and High Performance Research Group (BIO-HPC) - http://bio-hpc.eu.

  • BRUSELAS: Balanced Rapid and Unrestricted Server for Extensive Ligand-

Aimed Screening. http://bio-hpc.ucam.edu/Bruselas

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  • 4. BRUSELAS Experiment configuration

Bioinformatics and High Performance Research Group (BIO-HPC) - http://bio-hpc.eu.

  • Experiment configuration
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  • 4. BRUSELAS Result explorer

Bioinformatics and High Performance Research Group (BIO-HPC) - http://bio-hpc.eu.

  • Result explorer
  • Download Smiles of query
  • Download results in mol2/CSV formats
  • Share results by email
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  • 4. BRUSELAS Result explorer

Bioinformatics and High Performance Research Group (BIO-HPC) - http://bio-hpc.eu.

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  • 4. BRUSELAS Compound explorer

Bioinformatics and High Performance Research Group (BIO-HPC) - http://bio-hpc.eu.

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Nombre de la presentación Nombre del profesor - Tlf: (+34) 968 00 00 00 - mail@pdi.ucam.edu

  • 4. BRUSELAS Outlook and future works

Bioinformatics and High Performance Research Group (BIO-HPC) - http://bio-hpc.eu.

Advanced HPC techniques

Find new drug candidates

Application to

  • ther scopes,

e.g. farming, nutraceutical or cosmetics

Combination with AI and genetics

New features and compounds

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Nombre de la presentación Nombre del profesor - Tlf: (+34) 968 00 00 00 - mail@pdi.ucam.edu

  • 4. BRUSELAS Collaborations

Bioinformatics and High Performance Research Group (BIO-HPC) - http://bio-hpc.eu.

  • We search for groups and companies to collaborate in publications and its

application to real projects.

  • Contact:

Antonio J. Banegas ajbanegas@gmail.com Horacio Pérez Sánchez hperez@ucam.edu

  • https://www.bsc.es/hpc-europa3-hosts
  • Next H2020 Health
  • Tetramax
  • SBIR
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  • 5. HPC projects in BIO-HPC

Bioinformatics and High Performance Research Group (BIO-HPC) - http://bio-hpc.eu.

  • 2017 Eurolab-4-HPC Business Prototyping Project Proposals: Call 2017. Funded by Horizon

H2020-FETHPC-2014 (GA 671610).

  • 2016 Eurolab-4-HPC Business Prototyping Project Proposals: Call 2016. Funded by Horizon

H2020-FETHPC-2014 (GA 671610).

  • 2015 TETRACOM Technology Transfer in Computing Systems (funded by the European Union

Commission Framework Programme 7 - Contract No. 609491), “Advanced Computational Drug Discovery Technologies using High Performance Computing Architectures (ACDDTHPC)”.

  • 2013 PRACE Distributed European Computing Initiative (DECI-10), “Novel Anticoagulants”.

500000 GPU hours supercomputing time.

  • 2011 HPC-Europa2, “High Throughput in-silico screening in HPC architectures for the

discovery of new inhibitors against blood diseases”. 25000 hours supercomputing time.

  • 2010 CESGA - Singular Science And Technology Infrastructure, “High Throughput in-silico

screening in HPC architectures for the discovery of new inhibitors against blood diseases”. 200000 hours supercomputing time.

  • 2010 Distributed European Infrastructure Supercomputing Applications, “BLOODINH”. PI:

Wolfgang Wenzel. 2M hours supercomputing time.

  • 2008 Marie Curie FP7 IEF “INSILICODRUGDISCOVER”, ID:220147.
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  • 6. References

 J. Bajorath, “Integration of virtual and high-throughput screening”, Nat. Rev. Drug. Discov. 1(11), 882-894 (2002).  H. Pérez-Sánchez, V. Rezaei, V. Mezhuyev, D. Man, J. Peña-García, H. Den-Haan, S. Gesing, “Developing science gateways for drug discovery in a grid environment”, Springerplus, 5(1), 1300 (2016)  D. Laney, “3D Data management: controlling data volume, velocity and variety”, Appl.

  • Deliv. Strateg, Internet (February 2001):1–4 (2001)

 W.P. Walters, M.T. Stahl and M.A. Murcko, "Virtual Screening-An Overview", Drug Discovery Today, 3, 160-178 (1998)  W.H. Shin, X. Zhu, M. Bures, D. Kihara, "Three-dimensional compound comparison methods and their application in drug discovery", Molecules, 20(7), 12841-12862 (2015)  DIA-DB, http://bio-hpc.ucam.edu/dia-db/index.php, Bioinformatics and High Performance Computing Research Group (2015)  A.S. Reddy, S.P. Pati, P.P. Kumar, H.N. Pradeep, G.N. Sastry, "Virtual screening in drug discovery

  • a computational perspective", Current Protein & Peptide Science, 8(4), 329-351 (2007)

Bioinformatics and High Performance Research Group (BIO-HPC) - http://bio-hpc.eu.