Publications & Patents (Chemoinformatics and Drug Discovery)


Publications (Selected)

  • Exploring Energy Profiles of Protein-Protein Interactions (PPIs) Using DFT Method, S Bapat, R Vyas, M Karthikeyan, Letters in Drug Design & Discovery 16 (6), 670-677, 2019
  • Synthesis, Biological Evaluation and Molecular Modeling Studies of Novel Chromone/Aza-Chromone Fused α-Aminophosphonates as Src Kinase Inhibitors,S Bapat, N Viswanadh, M Mujahid, AN Shirazi, RK Tiwari, K Parang, NISCAIR-CSIR, India, 2019
  • Identification of potent chromone embedded [1, 2, 3]-triazoles as novel anti-tubercular agents,V Nalla, A Shaikh, S Bapat, R Vyas, M Karthikeyan, P Yogeeswari, D Sriram, M Muthukrishnan, Royal Society open science 5 (4), 171750,2,2018
  • Transition metal free regio-selective C–H hydroxylation of chromanones towards the synthesis of hydroxyl-chromanones using PhI(OAc)2 as the oxidant N. Viswanadh, Ganesh S. Ghotekar, Mahesh B. Thoke, R. Velayudham, Aslam C. Shaikh, M. Karthikeyan and M. Muthukrishnan* Chem. Commun., 2018, 54, 2252-2255 DOI:10.1039/C7CC08588E
  • Identification of potent chromone embedded [1,2,3]-triazoles as novel anti-tubercular agents ViswanadhNalla, AslamShaikh, Sanket Bapat, RenuVyas, M. Karthikeyan, P. Yogeeswari, D. Sriram, M. Muthukrishnan Royal Society open science. 5: 171750. 4 April 2018
  • Assessing therapeutic potential of molecules: molecular property diagnostic suite for tuberculosis (MPDSTB) Journal of Chemical Sciences May 2017, Volume 129, Issue 5, pp 515–531. Anamika Singh et al..M KarthikeyanM .. GN Sastry*
  • Application of Genetic Programming (GP) Formalism for Building Disease Predictive Models from Protein-Protein Interactions (PPI) Data Published in: IEEE/ACM Transactions on Computational Biology and Bioinformatics (Volume: PP, Issue: 99 ) Date of Publication: 26 October 2016 Print ISSN: 1545-5963
  • Building and analysis of protein-protein interactions related to diabetes mellitus using support vector machine, biomedical text mining and network analysis RenuVyas, , ,SanketBapat,EshaJain, MuthukumarasamyKarthikeyan,SanjeevTambe, Bhaskar D. Kulkarni
  • CHEMENGINE: harvesting 3D chemical structures of supplementary data from PDF files Muthukumarasamykarthikeyan ORCID ID profile and RenuVyas Journal of Cheminformatics 2016 8:73 DOI: 10.1186/s13321-016-0175-x
  • Spirochromone-chalcone conjugates as antitubercular agents: synthesis, bio evaluation and molecular modeling studies M Muthukrishnan, Mohammad Mujahid, PerumalYogeeswari, SriramDharmarajan, MuraliBasavanag, Erik Díaz-Cervantes, Luis Bahena, Juvencio Robles, Rajesh G. Gonnade, Karthikeyan M and RenuVyas, RSC Advances., 2015, DOI: 10.1039/C5RA21737G
  • Role of Open Source Tools and Resources in Virtual Screening for Drug Discovery,Combinatorial chemistry & high throughput screening 18(6): 528 – 543 (2015) MuthukumarasamyKarthikeyan and RenuVyas. DOI:10.2174/1386207318666150703111911
  • CHEMSCREENER:A Distributed Computing Tool for Scaffold based Virtual Screening,Combinatorial chemistry & high throughput screening 18(6): 544 – 561 (2015) MuthukumarasamyKarthikeyan, Deepak Pandit and RenuVyas. DOI: 10.2174/1386207318666150703112242
  • Prediction of Bioactive Compounds Using Computed NMR Chemical Shifts,Combinatorial chemistry & high throughput screening 18(6): 562 – 576 (2015)MuthukumarasamyKarthikeyan, PattuparambilRamanpillaiRajamohanan and RenuVyas. DOI: 10.2174/1386207318666150703113312
  • Protein Ligand Complex Guided Approach for Virtual Screening,Combinatorial chemistry & high throughput screening 18(6): 577 – 590 (2015) MuthukumarasamyKarthikeyan, Deepak Pandit and RenuVyas. DOI: 10.2174/1386207318666150703112620
  • Megaminer: A Tool for Lead Identification Through Text Mining Using Chemoinformatics Tools and Cloud Computing Environment,Combinatorial chemistry & high throughput screening 18(6): 591 – 603 (2015)MuthukumarasamyKarthikeyan, YogeshPandit, Deepak Pandit and RenuVyas. DOI: 10.2174/1386207318666150703113525
  • Design and Development of cheminfocloud: An Integrated Cloud Enabled Platform for Virtual Screening,Combinatorial chemistry & high throughput screening 18(6): 604 – 619 (2015) MuthukumarasamyKarthikeyan, Deepak Pandit, ArvindBhavasar and RenuVyas. DOI: 10.2174/1386207318666150703113656
  • Pharmacophore and Docking Based Virtual Screening of Validated Mycobacterium tuberculosis Targets,Combinatorial chemistry & high throughput screening 18(7): 624 – 637 (2015) RenuVyas, MuthukumarasamyKarthikeyan, Ganesh Nainaru and MuruganMuthukrishnan. DOI: 10.2174/1386207318666150703112759
  • Role of Chemical Reactivity and Transition State Modeling for Virtual Screening,Combinatorial chemistry & high throughput screening 18(7): 638 – 657 (2015) MuthukumarasamyKarthikeyan, RenuVyas, Sanjeev S. Tambe, DeepthiRadhamohan and Bhaskar D Kulkarni.DOI: 10.2174/1386207318666150703113135
  • A Study of Applications of Machine Learning Based Classification Methods for Virtual Screening of Lead Molecules,Combinatorial chemistry & high throughput screening 18(7): 658 – 672 (2015) RenuVyas, SanketBapat, Esha Jain, Sanjeev S. Tambe, MuthukumarasamyKarthikeyan and Bhaskar D Kulkarni. DOI: 10.2174/1386207318666150703112447
  • Chemoinformatics Approach for Building Molecular Networks from Marine Organisms,Combinatorial chemistry & high throughput screening 18(7): 673 – 684 (2015) MuthukumarasamyKarthikeyan, DeepikaNimje, RakhiPahujani, KushalTyagi, SanketBapat, RenuVyas and Krishna PillaiPadmakumar. DOI: 10.2174/1386207318666150703112950
  • Pharmacokinetic Modeling of Caco-2 Cell Permeability Using Genetic Programming (GP) Method RenuVyas, PurvaGoel, M. Karthikeyan, S.S. Tambe, B.D. Kulkarni Letters in Drug Design & Discovery VOLUME: 11 ISSUE: 9 2014 Page: [1112 - 1118] Pages: 7 DOI: 10.2174/1570180811666140610213438
  • M Karthikeyan, S Krishnan, Anil Kumar Pandey, Andreas Bender, AlexanderTropsha Distributed Chemical Computing Using CHEMSTAR:Open Source Java RMI Architecture applied to Large Scale Molecular Data from pubchem. (2008) J. Chem. Inf. Model., (American Chemical Society) 48 (4), 691-703.
  • M Karthikeyan, S Krishnan, Anil Kumar Pandey, Andreas Bender Harvesting Chemical Information from the Internet Using a Distributed Approach: CHEMXTREME (2006) J. Chem. Inf. Model., (American Chemical Society) 46 (2), 452 -46 1.
  • M Karthikeyan, Robert C Glen, Andreas Bender General Melting Point Prediction Based on a Diverse Compound Data Set and Artificial Neural Networks. (2005) J. Chem. Inf. Model.; (American Chemical Society) 45(3) pp 581 - 590.
  • M Karthikeyan, Andreas Bender Encoding and Decoding Graphical Chemical Structures as Two-Dimensional (PDF417) Barcodes M. (2005) J. Chem. Inf. Model.; (American Chemical Society) 45(3) pp 572 - 580
  • MuthukumarasamyKarthikeyan, Subramanian Krishnan Chemoinformatics A tool for modern drug discovery, (2002) Intl. J. Inf. Tech Mgmt. 1, (1), 69-82. [DOI: 10.1504/IJITM.2002.001188]


  • MuthukumarasamyKarthikeyan ;VyasRenuRemote Monitoring And Controlling Physical Parameters Of A Material Under Transportation Pub. No.: WO2017175243A1 US20190156166A1 International Application No.: Pct/In2017/050130 Publication Date: 12.10.2017 International Filing Date: 04.04.2017 Ipc: G06q 10/08 (2012.01) New Delhi 110 001
  • Remote monitoring and controlling physical parameters of a material under transportation An Internet of Things (IoT) based system for remotely monitoring and controlling various physical parameters for chemical/biological material under transportation in a container is disclosed herein. Due to various circumstances, wither hazardous or infectious, taking proper measures becomes a necessary condition while transporting chemical or biological materials. The sensors attached to the container measure the associated physical parameters and send the data to a remote control system. The dynamic barcode responds to the change in any of the parameters and changes its patterns accordingly. The remote server, based on the received data, instructs a controlling system to control the parameters, thus maintaining the health of the material.
  • MuthukumarasamyKarthikeyan  ; VyasRenu + An automated remote computing method and system by email platform for molecular analysis WO2017072794 (a1) - council scientind res [in] + application number: wo2016 in 50367 20161028 priority number(s): in2015 del 3527 20151030
  • An automated remote computing method and system by email platform for molecular analysis An automated method for remote computing of molecular docking and dynamics from one or more jobs in a network of plurality of users. The invention employs a system to execute the method comprising at least one user device, a remote computing server and a remote database. The job defining action tags are received and scanned by the remote server. A semantic analysis is performed on the jobs to distinguish between customized and non-customized tasks. A data analysis of the jobs is packaged in a compressed format. The user is continually updated of the job status. A public link is generated and sent to the user to download the results. The link is disabled after the downloading of the results to ensure the security of the data. The method avoids any duplication of jobs and can be performed even when the user is offline.
  • MuthukumarasamyKarthikeyan and Deepak Pandit WO 2016181412 A3 ” 2014-INV-0018 . CSIR-NCL, Pune. 2014.
  • Method for encoding and decoding large scale molecular virtual libraries into a barcode Method for encoding and decoding large scale molecular virtual libraries into a barcode Ligand-based drug discovery is often characterized with extraction of scaffolds, linkers and 5 building blocks from large small molecule datasets. Variable sites on scaffolds with attachment sites on building blocks participate in a combinatorial virtual reaction to generate a set of new virtual molecules. This process is time consuming and demands more storage space and is tedious to exchange data digitally. There is practically no quick way to sample molecules without enumerating the virtual library. Therefore, the present invention discloses a method of 10 encoding a virtual library of large scale molecular data into a single barcode. The present invention further discloses a method of decoding the barcode containing large scale data molecules.
  • Muthukumarasamy Karthikeyan WO2014207670A1 , EP3014504B1, US10216910B2, JP6211182B2
  • Simulated carbon and proton nmr chemical shifts based binary fingerprints for virtual screening The invention discloses a method to generate and analyze NMR chemical shift based binary fingerprints for virtual high throughput screening in drug discovery. Further, the invention provides a method to analyze NMR chemical shifts based binary fingerprints that has implications for encoding several properties of a molecule besides the basic framework or scaffold and determine its propensity towards a particular bioactivity class.
  • MuthukumarasamyKarthikeyan 2012092596056 Rapid Recognition And Prediction Of Objects Using Visual Computing And Machine Learning Methods 2013-Ncl-0035 2013-Nf-0090 In
  • MuthukumarasamyKarthikeyan 201304227151 Automatic Harvesting Of Molecular Information Raster Graphics 2011-Ncl-0031 2011-Nf-0140 WoPct/In2012/000567 & 2011-Ncl-0031 2011-Nf-0140 In 2420del2011
  • MuthukumarasamyKarthikeyan 2013052198317 Development Of Visual Imaging Device And Compatible Materials To Recognize Masked Patterns
  • MuthukumarasamyKarthikeyan 2012061564523 Apparatus For Digital Vision To Recognize Chemical Objects From Physical Models
  • MuthukumarasamyKarthikeyan US PATENT: 2014/0301608A1 Chemical Structure Recognition Tool (2014)

-Chemical structure recognition tool

A method of extracting and then reusing/remodeling chemical data from a hand written or digital input image without manual inputs using Chemical Structure Recognition Tool (CSRT) is disclosed herein. It comprises loading said input image, converting said input image into a grayscale image i.e. stretching of loaded input image, converting said grayscale image into a binary image i.e. binarization, smoothing to reduce noise within said binary image, recognizing circle bond to identify presence of a circle inside a ring, predicting OCR region to find zones containing text, image thinning to identify specific shapes within said binary image, edge detection to detect image contrast, detecting double and triple bond, and obtaining output files.