@article { ISI:000360934400003, title = {ChemScreener: a distributed computing tool for scaffold based virtual screening}, journal = {Combinatorial Chemistry \& High Throughput Screening}, volume = {18}, number = {6}, year = {2015}, month = {JAN}, pages = {544-561}, publisher = {BENTHAM SCIENCE PUBL LTD}, address = {EXECUTIVE STE Y-2, PO BOX 7917, SAIF ZONE, 1200 BR SHARJAH, U ARAB EMIRATES}, abstract = {

In this work we present ChemScreener, a Java-based application to perform virtual library generation combined with virtual screening in a platform-independent distributed computing environment. ChemScreener comprises a scaffold identifier, a distinct scaffold extractor, an interactive virtual library generator as well as a virtual screening module for subsequently selecting putative bioactive molecules. The virtual libraries are annotated with chemophore-, pharmacophore- and toxicophore-based information for compound prioritization. The hits selected can then be further processed using QSAR, docking and other in silico approaches which can all be interfaced within the ChemScreener framework. As a sample application, in this work scaffold selectivity, diversity, connectivity and promiscuity towards six important therapeutic classes have been studied. In order to illustrate the computational power of the application, 55 scaffolds extracted from 161 anti-psychotic compounds were enumerated to produce a virtual library comprising 118 million compounds (17 GB) and annotated with chemophore, pharmacophore and toxicophore based features in a single step which would be non-trivial to perform with many standard software tools today on libraries of this size.

}, keywords = {Scaffold extraction, therapeutic category, virtual library generation, virtual screening}, issn = {1386-2073}, doi = {10.2174/1386207318666150703112242}, author = {Karthikeyan, Muthukumarasamy and Pandit, Deepak and Vyas, Renu} } @article { ISI:000360934400007, title = {Design and development of cheminfocloud: an integrated cloud enabled platform for virtual screening}, journal = {Combinatorial Chemistry \& High Throughput Screening}, volume = {18}, number = {6}, year = {2015}, month = {JAN}, pages = {604-619}, publisher = {BENTHAM SCIENCE PUBL LTD}, address = {EXECUTIVE STE Y-2, PO BOX 7917, SAIF ZONE, 1200 BR SHARJAH, U ARAB EMIRATES}, abstract = {

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.

}, keywords = {Chemoinformatics, cloud computing, machine learning, Molecular docking, OpenVz, sequence alignment, spectra prediction, text mining, virtual screening}, issn = {1386-2073}, doi = {10.2174/1386207318666150703113656}, author = {Karthikeyan, Muthukumarasamy and Pandit, Deepak and Bhavasar, Arvind and Vyas, Renu} } @article { ISI:000360934400006, title = {MegaMiner: a tool for lead identification through text mining using chemoinformatics tools and cloud computing environment}, journal = {Combinatorial Chemistry \& High Throughput Screening}, volume = {18}, number = {6}, year = {2015}, month = {JAN}, pages = {591-603}, publisher = {BENTHAM SCIENCE PUBL LTD}, address = {EXECUTIVE STE Y-2, PO BOX 7917, SAIF ZONE, 1200 BR SHARJAH, U ARAB EMIRATES}, abstract = {

Virtual screening is an indispensable tool to cope with the massive amount of data being tossed by the high throughput omics technologies. With the objective of enhancing the automation capability of virtual screening process a robust portal termed MegaMiner has been built using the cloud computing platform wherein the user submits a text query and directly accesses the proposed lead molecules along with their drug-like, lead-like and docking scores. Textual chemical structural data representation is fraught with ambiguity in the absence of a global identifier. We have used a combination of statistical models, chemical dictionary and regular expression for building a disease specific dictionary. To demonstrate the effectiveness of this approach, a case study on malaria has been carried out in the present work. MegaMiner offered superior results compared to other text mining search engines, as established by F score analysis. A single query term {\textquoteleft}malaria{\textquoteright} in the portlet led to retrieval of related PubMed records, protein classes, drug classes and 8000 scaffolds which were internally processed and filtered to suggest new molecules as potential anti-malarials. The results obtained were validated by docking the virtual molecules into relevant protein targets. It is hoped that MegaMiner will serve as an indispensable tool for not only identifying hidden relationships between various biological and chemical entities but also for building better corpus and ontologies.

}, keywords = {Chemoinformatics, cloud computing, malaria, text mining, virtual screening}, issn = {1386-2073}, doi = {10.2174/1386207318666150703113525}, author = {Karthikeyan, Muthukumarasamy and Pandit, Yogesh and Pandit, Deepak and Vyas, Renu} } @article { ISI:000360934400004, title = {Prediction of bioactive compounds using computed NMR chemical shifts}, journal = {Combinatorial Chemistry \& High Throughput Screening}, volume = {18}, number = {6}, year = {2015}, month = {JAN}, pages = {562-576}, publisher = {BENTHAM SCIENCE PUBL LTD}, address = {EXECUTIVE STE Y-2, PO BOX 7917, SAIF ZONE, 1200 BR SHARJAH, U ARAB EMIRATES}, abstract = {

NMR based chemical shifts are an important diagnostic parameter for structure elucidation as they capture rich information related to conformational, electronic and stereochemical arrangement of functional groups in a molecule which is responsible for its activity towards any biological target. The present work discusses the importance of computing NMR chemical shifts from molecular structures. The NMR chemical shift data (experimental or computed) was used to generate fingerprints in binary formats for mapping molecular fragments (as descriptors) and correlating with the bioactivity classes. For this study, chemical shift data derived binary fingerprints were computed for 149 classes and 4800 bioactive molecules. The sensitivity and selectivity of fingerprints in discriminating molecules belonging to different therapeutic categories was assessed using a LibSVM based classifier. An accuracy of 82\% for proton and 94\% for carbon NMR fingerprints were obtained for anti-psoriatic and anti-psychotic molecules demonstrating the effectiveness of this approach for virtual screening.

}, keywords = {Chemical shift, fingerprints, NMR, similarity searching, virtual screening}, issn = {1386-2073}, doi = {10.2174/1386207318666150703113312}, author = {Karthikeyan, Muthukumarasamy and Rajamohanan, Pattuparambil Ramanpillai and Vyas, Renu} } @article { ISI:000360934400005, title = {Protein ligand complex guided approach for virtual screening}, journal = {Combinatorial Chemistry \& High Throughput Screening}, volume = {18}, number = {6}, year = {2015}, month = {JAN}, pages = {577-590}, publisher = {BENTHAM SCIENCE PUBL LTD}, address = {EXECUTIVE STE Y-2, PO BOX 7917, SAIF ZONE, 1200 BR SHARJAH, U ARAB EMIRATES}, abstract = {

The target ligand association data is a rich source of information which is not exploited enough for drug design efforts in virtual screening. A java based open-source toolkit for Protein Ligand Network Extraction (J-ProLiNE) focused on protein-ligand complex analysis with several features integrated in a distributed computing network has been developed. Sequence alignment and similarity search components have been automated to yield local, global alignment scores along with similarity and distance scores. 10000 proteins with co-crystallized ligands from pdb and MOAD databases were extracted and analyzed for revealing relationships between targets, ligands and scaffolds. Through this analysis, we could generate a protein ligand network to identify the promiscuous and selective scaffolds for multiple classes of proteins targets. Using J-ProLiNE we created a 507 x 507 matrix of protein targets and native ligands belonging to six enzyme classes and analyzed the results to elucidate the protein-protein, protein-ligand and ligand-ligand interactions. In yet another application of the J-ProLiNE software, we were able to process kinase related information stored in US patents to construct disease-gene-ligand-scaffold networks. It is hoped that the studies presented here will enable target ligand knowledge based virtual screening for inhibitor design.

}, keywords = {Complexes, ligand, protein, scaffolds, sequences, similarity score, virtual screening}, issn = {1386-2073}, doi = {10.2174/1386207318666150703112620}, author = {Karthikeyan, Muthukumarasamy and Pandit, Deepak and Vyas, Renu} } @article { ISI:000360934800003, title = {Role of chemical reactivity and transition state modeling for virtual screening}, journal = {Combinatorial Chemistry \& High Throughput Screening}, volume = {18}, number = {7}, year = {2015}, month = {JAN}, pages = {638-657}, publisher = {BENTHAM SCIENCE PUBL LTD}, address = {EXECUTIVE STE Y-2, PO BOX 7917, SAIF ZONE, 1200 BR SHARJAH, U ARAB EMIRATES}, abstract = {

Every drug discovery research program involves synthesis of a novel and potential drug molecule utilizing atom efficient, economical and environment friendly synthetic strategies. The current work focuses on the role of the reactivity based fingerprints of compounds as filters for virtual screening using a tool ChemScore. A reactant-like (RLS) and a product-like (PLS) score can be predicted for a given compound using the binary fingerprints derived from the numerous known organic reactions which capture the molecule-molecule interactions in the form of addition, substitution, rearrangement, elimination and isomerization reactions. The reaction fingerprints were applied to large databases in biology and chemistry, namely ChEMBL, KEGG, HMDB, DSSTox, and the Drug Bank database. A large network of 1113 synthetic reactions was constructed to visualize and ascertain the reactant product mappings in the chemical reaction space. The cumulative reaction fingerprints were computed for 4000 molecules belonging to 29 therapeutic classes of compounds, and these were found capable of discriminating between the cognition disorder related and anti-allergy compounds with reasonable accuracy of 75\% and AUC 0.8. In this study, the transition state based fingerprints were also developed and used effectively for virtual screening in drug related databases. The methodology presented here provides an efficient handle for the rapid scoring of molecular libraries for virtual screening.

}, keywords = {fingerprints, intermediates, metabolic pathways, product-like score, reactant-like score, reaction, screening, synthesis, virtual screening}, issn = {1386-2073}, doi = {10.2174/1386207318666150703113135}, author = {Karthikeyan, Muthukumarasamy and Vyas, Renu and Tambe, Sanjeev S. and Radhamohan, Deepthi and Kulkarni, Bhaskar D.} } @article { ISI:000360934400002, title = {Role of open source tools and resources in virtual screening for drug discovery}, journal = {Combinatorial Chemistry \& High Throughput Screening}, volume = {18}, number = {6}, year = {2015}, month = {JUL}, pages = {528-543}, publisher = {BENTHAM SCIENCE PUBL LTD}, address = {EXECUTIVE STE Y-2, PO BOX 7917, SAIF ZONE, 1200 BR SHARJAH, U ARAB EMIRATES}, abstract = {

Advancement in chemoinformatics research in parallel with availability of high performance computing platform has made handling of large scale multi-dimensional scientific data for high throughput drug discovery easier. In this study we have explored publicly available molecular databases with the help of open-source based integrated in-house molecular informatics tools for virtual screening. The virtual screening literature for past decade has been extensively investigated and thoroughly analyzed to reveal interesting patterns with respect to the drug, target, scaffold and disease space. The review also focuses on the integrated chemoinformatics tools that are capable of harvesting chemical data from textual literature information and transform them into truly computable chemical structures, identification of unique fragments and scaffolds from a class of compounds, automatic generation of focused virtual libraries, computation of molecular descriptors for structure-activity relationship studies, application of conventional filters used in lead discovery along with in-house developed exhaustive PTC (Pharmacophore, Toxicophores and Chemophores) filters and machine learning tools for the design of potential disease specific inhibitors. A case study on kinase inhibitors is provided as an example.

}, keywords = {Chemoinformatics, kinases, open source, scaffold, virtual screening}, issn = {1386-2073}, doi = {10.2174/1386207318666150703111911}, author = {Karthikeyan, Muthukumarasamy and Vyas, Renu} } @article {47013, title = {Design of novel drug-like molecules using informatics rich secondary metabolites analysis of Indian medicinal and aromatic plants}, journal = {Combinatorial Chemistry \& High Throughput Screening}, volume = {23}, year = {2020}, month = {JAN}, pages = {1113-1131}, type = {Article}, abstract = {

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.

}, keywords = {Drugs, medicinal plants, Metabolites, scaffolds, text mining, virtual libraries, virtual screening}, issn = {1386-2073}, doi = {10.2174/1386207323666200606211342}, author = {Karade, Divya and Vijayasarathi, Durairaj and Kadoo, Narendra and Vyas, Renu and Ingle, P. K. and Karthikeyan, Muthukumarasamy} }