Abhik Seal Phd Student Indiana University) (Researcher OSDD CSIR) Anshu Bhardwaj Scientist, OSDD Unit Council of Scientific & Industrial Research Delhi, India 23 rd March 2012, Washington DC http://www.osdd.net Open Source Drug Discovery CSIR-led Team India Consortium with Global Partnership Affordable Healthcare for All Cheminformatics and Open Source Drug Discovery: a case study in academic collaboration between the U.S. and India
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Abhik Seal Phd Student Indiana University)
(Researcher OSDD CSIR)
Anshu Bhardwaj Scientist, OSDD Unit
Council of Scientific & Industrial Research Delhi, India
23rd March 2012, Washington DC http://www.osdd.net
Open Source Drug Discovery CSIR-led Team India Consortium with Global Partnership
Affordable Healthcare for All
Cheminformatics and Open Source Drug Discovery: a case study in academic collaboration between the
First Disease Target : Tuberculosis Tuberculosis (TB) is one of leading causes of fatality, ranking second only to HIV as the killer infectious disease of adults worldwide.
Countries that had reported at least one XDR-TB case by end March 2011
Argentina Bhutan France Japan Namibia Republic of Korea ThailandArmenia Cambodia Georgia Kazakhstan Nepal Republic of Moldova TogoAustralia Canada Germany Kenya Netherlands Romania TunisiaAustria Chile Greece Kyrgyzstan Norway Russian Federation UkraineAzerbaijan China India Latvia Pakistan Slovenia United Arab EmiratesBangladesh Colombia Indonesia Lesotho Peru South Africa United KingdomBelgium Czech Republic Iran (Islamic Rep. of) Lithuania Philippines Spain United States of AmericaBotswana Ecuador Ireland Mexico Poland Swaziland UzbekistanBrazil Egypt Israel Mozambique Portugal Sweden Viet NamBurkina Faso Estonia Italy Myanmar Qatar Tajikistan
It commemorates the discovery of TB bacillus (Mycobacterium tuberculosis) through sputum microscopy which is still the diagnostics used to detect TB! No progress whatsoever, and we are discussing 'network communications'
Collaborative tools to accelerate neglected diseases research” in the book “Collaborative Computational Technologies for Biomedical Research”. Wiley and Sons. 2011
From a mathematical point of view, to create an accurate model of a single mammalian cell may require generating and then solving somewhere between 100,000 to one million equations
Within weeks, 830 volunteered to re-annotate the entire M. tuberculosis genome. The work started in December 2009 and was completed by April 2010, packing nearly 300 man-years into 4 months!
Source: Munos B. Can Open-Source Drug R&D Repower Pharmaceutical Innovation? Clin Pharmacol Ther 2010;87:534–536
Source: Hiroaki Kitano Nature Chemical Biology 7, 323–326 (2011)
Social engineering for virtual 'big science' in systems biology
Workflows and the result of the workflows are stored as separate lab note books Lab note book has details of the experiments performed Results of one experiment may be invoked for analysis in another experiment All versions of the workflow and the results are stored Flexibility to execute nested workflows
Custom APIs for exporting results to OSDD’s Open lab note book
ChemBio toolkit : >300 Modules integrated by OSDD Community
S. No Resources Clients 1 KEGG: Kyoto Encyclopedia of Genes and Genomes 60 2 GetEntry: DDBJ sequence search by accessionID 43 3 GPSR : tools 33 4 PDB : Protein Data Bank 30 5 BioModel:mathematical models of biological DB 25 6 Gtps : Gene Trek in Prokaryote Space 8
7 WSDbfetch: retrieve entries from biological dbs using entry identifiers or accession no. 7
8 Gibv: Genome Information Broker for Viruses 7 9 DDBJ :DNA Data bank of Japan 7 10 Mafft: a multiple sequence alignment program 4 11 Fasta:- DDBJ database 4 12 Ensembl : maintains automatic annotation 4 13 VecScreen vector contamination 4 14 OMIM:Online Mendelian Inheritance in man 4 15 Gtop: Gene-product Informatics 3 16 GO: Gene Ontology 3 17 SPS : Splicing Profile based Score 2 18 GIBIS: Genome Information Broker for Insertion Sequence 1 19 RefSeq: database of sequence 1 20 GIB: Genome Information Broker 1 21 GIBEnv- DDBJ database 1 22 TxSearch: Database indexing & searching 1
Cheminformatics: a strong case for community collaborative science
There is now an incredibly rich resource of public information relating compounds, targets, genes, pathways, and diseases. Just for starters there is in the public domain information on:
~30 million compounds and ~500,000 bioassays (PubChem, ChemSpider) ~60 million compound bioactivities (PubChem Bioassay) ~5,000 drugs (DrugBank) ~9 million protein sequences (SwissProt) and ~60,000 3D structures (PDB) ~14 million human nucleotide sequences (EMBL) ~20 million life science publications (PubMED) Multitude of other sets (drugs, toxicogenomics, chemogenomics, metagenomics …)
I have thus chosen ‘Cheminformatics’ to study the vast pool of chemical compounds much more in details and analyze so as to narrow down to potential drug candidate. With the unique combination of IT and Chemistry, I am confident that one can actually derive much more
meaningful information of a chemical entity on this earth. Rajdeep (BioIT) I am organic chemist. I prepared several organic molecules.We go for biological activity,
maximum times it gives negative result. But with help of informatics in chemistry we can predict molecular properties. We can replace many ligands or substituents or functional group easily. And we can design our desirable molecule. ---Chirupulo
I am doing my M.Pharm in pharmaceutical chemistry,and i like cheminformatics that i need
accurate results but soon....and i am really interested in molecular modelling...so I am here. --- Haffy manaf
Cheminformatics deals with information about chems. It combines tools and techniques of IT
for information about chemical entities at the finger tip on click of a mouse. Databases are available for properties of descriptors. Softwares help to calculate molecular properties. Cheminformatics thus come handy tool for learning chemistry.------ Dr Keshav Mohan
Community Speaks: What excites them about Cheminformatics
• Access to Journals for Chemical Structures • Lack of proper communication systems other than skype • Lack of software tools for accelerated drug discovery • Need of high speed internet • Need more experts to teach/train community members • Proper time schedule of IU cheminformatics classes
Challenges in implementation of Cheminformatics projects
Association Search – visualize literature supported associations between any two entities (compound, drug, gene, pathway, disease, side effect). PLoS One, in press.
Semantic Link Association Prediction (SLAP) – find most highly associated entities (compound, drug, gene, pathway, disease, side effect) to any other entity, based on probabilistic weightings of graph edges based on public experimental datasets. Paper in preparation
BioLDA – find most highly associated entities to any other entity based on a complex topic model analysis of the literature (PubMed). PLoS One, 2011, 6 (3), e17243
Inhibition of FAAL and FACL enzymes by acyl-sulfamoyl
analogues
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NNO
CF3
s12
s14 s15
Preclinical development of thiophene containing
trisubstituted methanes
• Five synthetic ‘thiophene containing trisubstituted methanes’, which showed a MIC of <1.56 µg/ml, no cytotoxicity in mammalian cells being synthesised in PPP Mode
Public Private Partnerships as Open Collaborative Endeavors to solve Scientific Challenges