02240nas a2200193 4500008004100000022001400041245016000055210006900215260007100284300001200355490000700367520142600374100003301800700001701833700002401850700002001874700002301894856012901917 2008 eng d a1549-959600aDistributed chemical computing using chemstar: an open source java remote method invocation architecture applied to large scale molecular data from pubchem0 aDistributed chemical computing using chemstar an open source jav a1155 16TH ST, NW, WASHINGTON, DC 20036 USAbAMER CHEMICAL SOCcAPR a691-7030 v483 a

present the application of a Java remote method invocation (RMI) based open source architecture to distributed chemical computing. This architecture was previously employed for distributed data harvesting of chemical information from the Internet via the Google application programming interface (API; ChemXtreme). Due to its open source character and its flexibility, the underlying server/client framework can be quickly adopted to virtually every computational task that can be parallelized. Here, we present the server/client communication framework as well as an application to distributed computing of chemical properties on a large scale (currently the size of PubChem; about 18 million compounds), using both the Marvin toolkit as well as the open source JOELib package. As an application, for this set of compounds, the agreement of log P and TPSA between the packages was compared. Outliers were found to be mostly non-druglike compounds and differences could usually be explained by differences in the underlying algorithms. ChemStar is the first open source distributed chemical computing environment built on Java RMI, which is also easily adaptable to user demands due to its ``plug-in architecture''. The complete source codes as well as calculated properties along with links to PubChem resources are available on the Internet via a graphical user interface at http://moltable.nel.res.in/chemstar/.

1 aKarthikeyan, Muthukumarasamy1 aKrishnan, S.1 aPandey, Anil, Kumar1 aBender, Andreas1 aTropsha, Alexander uhttps://library.ncl.res.in/content/distributed-chemical-computing-using-chemstar-open-source-java-remote-method-invocation-001742nas a2200121 4500008004100000245006200041210006200103260001300165300001400178520130200192100003301494856009301527 2014 eng d00aDocking and pharmacophore modelling for virtual screening0 aDocking and pharmacophore modelling for virtual screening bSpringer a195 - 2693 a

Protein and ligand molecules as two separate entities appear and behave differently, but what happens when they come together and interact with each other is one of the interesting facts in modern molecular biology and molecular recognition. This interaction can be well explained with the concept of docking which in a simple way can be described as the study of how a molecule can bind to another molecule to result in a stable entity. The two binding molecules can be either a protein and a ligand or a protein and a protein. Irrespective of which two molecules are interacting, a docking process invariably includes two steps—conformational search through various algorithms and scoring or ranking. Even though prolific research has been carried out in this field, yet it is still a topic of current interest as there is a scope for improvement to rationalize binding interactions with biological function using docking program. This chapter focuses on how to set up and perform docking runs using freeware and commercial software. Most of the known docking protocols like induced fit docking, protein–protein docking, and pharmacophore-based docking have been discussed. The use of pharmacophore queries as filters in virtual screening is also demonstrated using suitable examples.

1 aKarthikeyan, Muthukumarasamy uhttps://library.ncl.res.in/content/docking-and-pharmacophore-modelling-virtual-screening02057nas a2200289 4500008004100000022001400041245010400055210006900159260011100228300001200339490000700351520101200358653002101370653002001391653002101411653002201432653001101454653002301465653002301488653001601511653002201527100003301549700001901582700002101601700001501622856013001637 2015 eng d a1386-207300aDesign and development of cheminfocloud: an integrated cloud enabled platform for virtual screening0 aDesign and development of cheminfocloud an integrated cloud enab aEXECUTIVE STE Y-2, PO BOX 7917, SAIF ZONE, 1200 BR SHARJAH, U ARAB EMIRATESbBENTHAM SCIENCE PUBL LTDcJAN a604-6190 v183 a

The power of cloud computing and distributed computing has been harnessed to handle vast and heterogeneous data required to be processed in any virtual screening protocol. A cloud computing platorm ChemInfoCloud was built and integrated with several chemoinformatics and bioinformatics tools. The robust engine performs the core chemoinformatics tasks of lead generation, lead optimisation and property prediction in a fast and efficient manner. It has also been provided with some of the bioinformatics functionalities including sequence alignment, active site pose prediction and protein ligand docking. Text mining, NMR chemical shift (1H, 13C) prediction and reaction fingerprint generation modules for efficient lead discovery are also implemented in this platform. We have developed an integrated problem solving cloud environment for virtual screening studies that also provides workflow management, better usability and interaction with end users using container based virtualization, OpenVz.

10aChemoinformatics10acloud computing10amachine learning10aMolecular docking10aOpenVz10asequence alignment10aspectra prediction10atext mining10avirtual screening1 aKarthikeyan, Muthukumarasamy1 aPandit, Deepak1 aBhavasar, Arvind1 aVyas, Renu uhttps://library.ncl.res.in/content/design-and-development-cheminfocloud-integrated-cloud-enabled-platform-virtual-screening-000636nas a2200145 4500008004100000022001400041245007900055210006900134260011100203300001200314490000700326100003300333700001500366856010900381 2015 eng d a1386-207300aDesign and development of new chemoinformatics tools for virtual screening0 aDesign and development of new chemoinformatics tools for virtual aEXECUTIVE STE Y-2, PO BOX 7917, SAIF ZONE, 1200 BR SHARJAH, U ARAB EMIRATESbBENTHAM SCIENCE PUBL LTDcJAN a526-5270 v181 aKarthikeyan, Muthukumarasamy1 aVyas, Renu uhttps://library.ncl.res.in/content/design-and-development-new-chemoinformatics-tools-virtual-screening-003539nas a2200289 4500008004100000022001400041245013400055210006900189260000800258300001400266490000700280520258100287653001002868653002102878653001602899653001402915653001602929653002202945653002202967100001802989700002803007700002003035700001503055700001803070700003303088856012803121 2020 eng d a1386-207300aDesign of novel drug-like molecules using informatics rich secondary metabolites analysis of Indian medicinal and aromatic plants0 aDesign of novel druglike molecules using informatics rich second cJAN a1113-11310 v233 a

Background: Several medicinal plants are being used in Indian medicine systems from ancient times. However, in most cases, the specific molecules or the active ingredients responsible for the medicinal or therapeutic properties are not yet known. Objective: This study aimed to report a computational protocol as well as a tool for generating novel potential drug candidates from the bioactive molecules of Indian medicinal and aromatic plants through the chemoinformatics approach. Methods: We built a database of the Indian medicinal and aromatic plants coupled with associated information (plant families, plant parts used for the medicinal purpose, structural information, therapeutic properties, etc.) We also developed a Java-based chemoinformatics open-source tool called DoMINE (Database of Medicinally Important Natural products from plantaE) for the generation of virtual library and screening of novel molecules from known medicinal plant molecules. We employed chemoinformatics approaches to in-silico screened metabolites from 104 Indian medicinal and aromatic plants and designed novel drug-like bioactive molecules. For this purpose, 1665 ring containing molecules were identified by text mining of literature related to the medicinal plant species, which were later used to extract 209 molecular scaffolds. Different scaffolds were further used to build a focused virtual library. Virtual screening was performed with cluster analysis to predict drug-like and lead-like molecules from these plant molecules in the context of drug discovery. The predicted drug-like and lead-like molecules were evaluated using chemoinformatics approaches and statistical parameters, and only the most significant molecules were proposed as the candidate molecules to develop new drugs. Results and Conclusion: The supra network of molecules and scaffolds identifies the relationship between the plant molecules and drugs. Cluster analysis of virtual library molecules showed that novel molecules had more pharmacophoric properties than toxicophoric and chemophoric properties. We also developed the DoMINE toolkit for the advancement of natural product-based drug discovery through chemoinformatics approaches. This study will be useful in developing new drug molecules from the known medicinal plant molecules. Hence, this work will encourage experimental organic chemists to synthesize these molecules based on the predicted values. These synthesized molecules need to be subjected to biological screening to identify potential molecules for drug discovery research.

10aDrugs10amedicinal plants10aMetabolites10ascaffolds10atext mining10avirtual libraries10avirtual screening1 aKarade, Divya1 aVijayasarathi, Durairaj1 aKadoo, Narendra1 aVyas, Renu1 aIngle, P., K.1 aKarthikeyan, Muthukumarasamy uhttps://library.ncl.res.in/content/design-novel-drug-molecules-using-informatics-rich-secondary-metabolites-analysis-indian