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MolTable: An Open Access (Molecule Table) Portal for "Advanced Chemoinformatics Research, Training and Services"

 Combinatorial Chemistry & High Throughput Screening, (Special Issue 2014: Role of Chemoinformatics in Virtual Screening) Editor & Contributor: M Karthikeyan et al .

  1. Role of chemoinformatics methods in knowledge based virtual screening of kinase inhibitors . M Karthikeyan et al .Combinatorial Chemistry & High Throughput Screening, Volume 17 , xx , 2014, 0000-0000 (in press)
  2. ChemScreener :  A distributed computing tool for scaffold based  virtual screening . M Karthikeyan et al .Combinatorial Chemistry & High Throughput Screening, Volume 17 , xx , 2014, 0000-0000 (in press)
  3. A study of applications of machine learning based classification methods for virtual screening of lead molecules. M Karthikeyan et al .Combinatorial Chemistry & High Throughput Screening, Volume 17 , xx , 2014, 0000-0000 (in press)
  4. Protein ligand complex guided approach for virtual screening. M Karthikeyan et al .Combinatorial Chemistry & High Throughput Screening, Volume 17 , xx , 2014, 0000-0000 (in press)
  5. Pharmacophore and docking based virtual screening of validated MTb targets . M Karthikeyan et al .Combinatorial Chemistry & High Throughput Screening, Volume 17 , xx , 2014, 0000-0000 (in press)
  6. Target active site features mediated virtual screening of leads. M Karthikeyan et al .Combinatorial Chemistry & High Throughput Screening, Volume 17 , xx , 2014, 0000-0000 (in press)
  7. Role of  chemical reactivity and transition state modeling for virtual screening. M Karthikeyan et al .Combinatorial Chemistry & High Throughput Screening, Volume 17 , xx , 2014, 0000-0000 (in press)
  8. Simulated   carbon and proton NMR chemical shift based binary fingerprints for virtual screening . M Karthikeyan et al .Combinatorial Chemistry & High Throughput Screening, Volume 17 , xx , 2014, 0000-0000 (in press)
  9. Mega Miner :  A tool for hit identification through text mining using chemoinformatics tools and  cloud computing environment. M Karthikeyan et al .Combinatorial Chemistry & High Throughput Screening, Volume 17 , xx , 2014, 0000-0000 (in press)
  10. Design and Development of ChemInfoCloud :  An Integrated cloud enabled platform for  virtual screening. M Karthikeyan et al .Combinatorial Chemistry & High Throughput Screening, Volume 17 , xx , 2014, 0000-0000 (in press)

 

 Selected Key Publications:

  1. Muthukumarasamy Karthikeyan1 , Renu Vyas Chemical Structure Representations and Applications in Computational Toxicity Computational Toxicology : Volume I Methods in Molecular Biology  (2012)   Volume: 929 , 167-192  |  DOI: 10.1007/978-1-62703-050-2_8 (URL)
  2. Distributed Chemical Computing Using ChemStar: Open Source Java RMI Architecture applied to Large Scale Molecular Data from PubChem. (2008) J. Chem. Inf. Model., 48 (4), 691-703.
  3.  Harvesting Chemical Information from the Internet Using a Distributed Approach: ChemXtreme (2006) J. Chem. Inf. Model., 46 (2), 452 -46 1.
  4. General Melting Point Prediction Based on a Diverse Compound Data Set and Artificial Neural Networks. (2005) J. Chem. Inf. Model.; 45(3) pp 581 - 590. (Update 22 may 2011: Dataset-2 12618 entries Range  Model (unpublished))
  5. Encoding and Decoding Graphical Chemical Structures as Two-Dimensional (PDF417) Barcodes M. (2005) J. Chem. Inf. Model.; 45(3) pp 572 - 580
  6. Chemoinformatics A tool for modern drug discovery, (2002) Intl. J. Inf. Tech Mgmt. 1, (1), 69-82. [DOI: 10.1504/IJITM.2002.001188]

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NCL-Pune, India. NCL-Pune, India.

 "The true rewards of HONEST work are neither to be SEEN nor HANDLED, They are NOT measured by a GOLD STANDARD nor by any material result. They are not acclaimed by the applause of the crowd. They lie within you; in your own knowledge that you have done your BEST! that you have striven to reach your own STARDARD of your HIGHEST Powers. You will often perhaps always, fail to reach your own IDEAL but comforted ideals are not for attainment; but for pursuit!" - Lord Moynihan

 "Opportunity for Project Fellow / Associate position in Chemoinformatics. Rs. 16,000 - 25,000 p.m. (Masters degree with first class in Chemistry, Computer Science , Bioinformatics) send your resume to the undersigned immediately (before 5 October 2014 ) " * visit periodically this site for Project Fellow positions, PhD candidates can be considered for Research Associate positions in Chemoinformatics.

About Us

We are working in the area of chemoinformatics for the past two decades especially to develop tools for academic/industrial research. In this direction we made several predictive studies related to Drug Discovery Research (QSAR, QSPR and QSTR) . We applied QSPR strategy for predicting Melting point of diverse class of organic molecules  . As part of innovative research we developed a methodology for molecular encoding as barcodes [click]  with truly computable structures for inventory management. In order to handle high data we developed a program ChemXtreme to harvest chemical information  from entire Internet using search engines like Google and extracted data such molecular properties, activities, and toxicity of molecules were converted in to specialized databases. ChemStar(5) is another program developed to handle large amount of molecular data using Distributed computing environment (Ref 4-5) and applied for calculating molecular properties for the entire collection of PubChem database. We also contributed in compiling MSDS datasheets for Central Pollution Control Board-New Delhi. Chemical Data mining of Indian Medicinal Plants and Traditional Chinese medicine from Scientific literature covering past four decades to build DoMINE (in progress).

[ FORWARD and FRONT MATTER]

Text Book : Practical Chemoinformatics , Springer 2014 (ISBN: 978-81-322-1779-4) http://www.springer.com/chemistry/book/978-81-322-1779-4
Ch 1.   
Open-Source Tools, Techniques, and Data in Chemoinformatics . M Karthikeyan and Renu Vyas. Practical Chemoinformatics © Springer India 2014 Pages 1-92 . DOI 10.1007/978-81-322-1780-0_1
Ch 2.    Chemoinformatics Approach for the Design and Screening of focused virtual libraries M Karthikeyan and Renu Vyas. Practical Chemoinformatics © Springer India 2014 . Pages 93-131  DOI 10.1007/978-81-322-1780-0_2
Ch 3.    Machine Learning Methods in Chemoinformatics for Drug Discovery M Karthikeyan and Renu Vyas. Practical Chemoinformatics © Springer India 2014 .Pages 133-194 DOI 10.1007/978-81-322-1780-0_3
Ch 4.    Docking and pharmacophore modeling for virtual screening M Karthikeyan and Renu Vyas. Practical Chemoinformatics © Springer India 2014 .Pages 195-269 DOI 10.1007/978-81-322-1780-0_4
Ch 5.    Active site directed pose prediction programs for efficient filtering of molecules M Karthikeyan and Renu Vyas. Practical Chemoinformatics © Springer India 2014 .Pages 271-316 DOI 10.1007/978-81-322-1780-0_5
Ch 6.    Representation, fingerprinting and modeling of chemical reactions. M Karthikeyan and Renu Vyas. Practical Chemoinformatics © Springer India 2014 .Pages 317-374 DOI 10.1007/978-81-322-1780-0_6
Ch 7.    Predictive methods for Organic Spectral data Simulation. M Karthikeyan and Renu Vyas. Practical Chemoinformatics © Springer India 2014 . Pages 375-414 DOI 10.1007/978-81-322-1780-0_7
Ch 8.    Chemical Text mining for Lead Discovery. M Karthikeyan and Renu Vyas. Practical Chemoinformatics © Springer India 2014 .Pages 415-449. DOI 10.1007/978-81-322-1780-0_8
Ch 9.    Integration of Automated Work flow in Chemoinformatics for drug discovery. M Karthikeyan and Renu Vyas. Practical Chemoinformatics © Springer India 2014 .Pages 451-499. DOI 10.1007/978-81-322-1780-0_9
Ch 10.    Cloud computing Infrastructure development for Chemoinformatics. M Karthikeyan and Renu Vyas. Practical Chemoinformatics © Springer India 2014 . Pages 501-528 .DOI 10.1007/978-81-322-1780-0_10

To create awareness and promote CHEMOINFORMATICS among the academic community and other scientific funding agencies in India, we recently organized an International Conference on Chemoinformatics (Jan 22-24, 2007) at National Chemical Laboratory, first of its kind in the country [photos]  [Read More..]. We also provide academic and industrial training in building chemical-biological databases related to chemoinformatics and other In-house built Databases and commercial databases and Molecular Informatics Tools.

What is new ? 

ChemInfoCloud (2012)  ChemRobot: Harvest Chemical Data from Images (LINK)

Government Sponsored Projects:

 Working in Molecular Informatics (Application of HPC tools using distributed and cloud computing architecture to handle large scale molecular data ~100 millions+ defining virtual chemical space of selected protein targets or therapeutic category, Organic reaction modeling using QM & QC and extension to biological systems (INSPIRE Project 12 FYP 2012-17), predictive QSAR (properties, toxicity, activity) , artificial neural networks and other machine learning tools, textmining, Visual computing for molecular informatics and application in drug design, lead optimization, materials, Education, Research and Management). Inventory and automation for sample tracking (NORMS 12 FYP 2012-17), chemical risk assessment and hazard analysis (Industrial Safety Processess modeling and simulations). Millions of docking being performed in a HPC enviroment to understand protein-ligand interactions by insilico studies (Figure). Practical Chemoinformatics (from Springer) highlights the power of programming computers for chemoinformatics applications.

 Compute Molecular Descriptors using Moltable Portal! [Click]

  International Conference on Chemoinformatics

  1.  International Conference on Chemoinformatics, 23-25 January 2007, National Chemical Laboratory, Pune

Relevant Publications: (Big Data Challenges in Chemoinformatics: 10 billion web pages, 80 million molecules, 40 million Docking, Chemically intelligent Digital Eye)

  1.  Muthukumarasamy Karthikeyan1 , Renu Vyas Chemical Structure Representations and Applications in Computational Toxicity Computational Toxicology : Volume I Methods in Molecular Biology  (2012)   Volume: 929 , 167-192  |  DOI: 10.1007/978-1-62703-050-2_8 (Springer)
  2.  Distributed Chemical Computing Using ChemStar: Open Source Java RMI Architecture applied to Large Scale Molecular Data from PubChem. (2008) J. Chem. Inf. Model., 48 (4), 691-703.
    (American Chemical Society)
  3.  Harvesting Chemical Information from the Internet Using a Distributed Approach: ChemXtreme (2006) J. Chem. Inf. Model., 46 (2), 452 -461. (American Chemical Society)
  4.  General Melting Point Prediction Based on a Diverse Compound Data Set and Artificial Neural Networks. (2005) J. Chem. Inf. Model.; 45(3) pp 581 - 590. (American Chemical Society)
  5.  Encoding and Decoding Graphical Chemical Structures as Two-Dimensional (PDF417) Barcodes M. (2005) J. Chem. Inf. Model.; 45(3) pp 572 - 580 (American Chemical Society)
  6. Chemoinformatics A tool for modern drug discovery, (2002) Intl. J. Inf. Tech Mgmt. 1, (1), 69-82. [DOI: 10.1504/IJITM.2002.001188]
  7. ChemInfoCloud, ChemScreener, Mega Miner (2014)

  8. ChemRobot: Harvest Chemical Data from Images (LINK)

  9. Text Book : Practical Chemoinformatics , Springer 2014 (ISBN: 978-81-322-1779-4) http://www.springer.com/chemistry/book/978-81-322-1779-4

 

Muthukumarasamy Karthikeyan Ph.D, MBA

DST BOYSCAST FELLOW & DBT OVERSEAS ASSOCIATE, Visiting Scientist (UNC-CH, USA)

For Complete Profile:[CV-PDF]

[LinkedIn]

[ResearchGate]

[Official website/Resume]

Address for Correspondance:

Muthukumarasamy Karthikeyan Ph.D, MBA

Principal Scientist, (CHEMOINFORMATICS)

Digital Information Resource Center (DIRC) & Centre of Excellence in Scientific Computing
CSIR-National Chemical Lab. Pune - 411 008, INDIA
Email: karthincl@gmail.com, m.karthikeyan@ncl.res.in
Ph: (O) +91-(0)-20 2590-2483 (M-F: 9.00AM-5.30PM IST) Mobile: +91-(0)-976-742-7981 
URL:
http://moltable.ncl.res.in/

 [click to read PhD thesis (Organic Synthesis)  Pune University ]  [MBA: Marketing Generic Drugs in India (IGNOU)] &&  [Expertise: MSc Computer Science (FOSS) : ChemRobot: Visual Computing for Molecular Informatics (Anna University)]