Chemoinformatics approach for building molecular networks from marine organisms - Karthikeyan, Muthukumarasamy; Nimje, Deepika; Pahujani, Rakhi; Tyagi, Kushal; Bapat, Sanket; Vyas, Renu; Padmakumar, Krishna Pillai (Combinatorial Chemistry & High Throughput Screening, 2015)
Natural products obtained from marine sources are considered to be a rich and diverse source of potential drugs. In the present work we demonstrate the use of chemoinformatics approach for the design of new molecules inspired by molecules from marine organisms. Accordingly we have assimilated information from two major scientific domains namely chemoinformatics and biodiversity informatics to develop an interactive marine database named MIMMO (Medicinally Important Molecules from Marine Organisms). The database can be queried for species, molecules, scaffolds, drugs, diseases and associated cumulative biological activity spectrum along with links to the literature resources. Molecular informatics analysis of the molecules obtained from MIMMO was performed to study their chemical space. The distinct skeletal features of the biologically active compounds isolated from marine species were identified. Scaffold molecules and species networks were created to identify common scaffolds from marine source and drug space. An analysis of the entire molecular data revealed a unique list of around 2000 molecules from which ten most frequently occurring distinct scaffolds were obtained.
Keywords: Chemoinformatics; Drug design; marine; virtual library

Design and development of cheminfocloud: an integrated cloud enabled platform for virtual screening - Karthikeyan, Muthukumarasamy; Pandit, Deepak; Bhavasar, Arvind; Vyas, Renu (Combinatorial Chemistry & High Throughput Screening, 2015)
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

MegaMiner: a tool for lead identification through text mining using chemoinformatics tools and cloud computing environment - Karthikeyan, Muthukumarasamy; Pandit, Yogesh; Pandit, Deepak; Vyas, Renu (Combinatorial Chemistry & High Throughput Screening, 2015)
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 `malaria' 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

Role of open source tools and resources in virtual screening for drug discovery - Karthikeyan, Muthukumarasamy; Vyas, Renu (Combinatorial Chemistry & High Throughput Screening, 2015)
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

Assessing therapeutic potential of molecules: molecular property diagnostic suite for tuberculosis - Gaur, A. S.; Bhardwaj, A.; Sharma, A.; John, L.; Vivek, M. R.; Tripathi, N.; Bharatam, P. V.; Kumar, R.; Janardhan, S.; Mori, A.; Banerji, A.; Lynn, A. M.; et al. (Journal of Chemical Sciences, 2017)
Abstract: Molecular Property Diagnostic Suite (MPDS TB) is a web tool (http://mpds.osdd.net) designed to assist the in silico drug discovery attempts towards Mycobacterium tuberculosis (Mtb). MPDS TB tool has nine modules which are classified into data library (1–3), data processing (4–5) and data analysis (6–9). Module 1 is a repository of literature and related information available on the Mtb. Module 2 deals with the protein target analysis of the chosen disease area. Module 3 is the compound library consisting of 110.31 million unique molecules generated from public domain databases and custom designed search tools. Module 4 contains tools for chemical file format conversions and 2D to 3D coordinate conversions. Module 5 helps in calculating the molecular descriptors. Module 6 specifically handles QSAR model development tools using descriptors generated in the Module 5. Module 7 integrates the AutoDock Vina algorithm for docking, while module 8 provides screening filters. Module 9 provides the necessary visualization tools for both small and large molecules. The workflow-based open source web portal, MPDS TB 1.0.1 can be a potential enabler for scientists engaged in drug discovery in general and in anti-TB research in particular. Graphical Abstract: SYNOPSIS: A web-based MPDS TB Galaxy tool is developed for assessing therapeutic potential of molecules. MPDS TB is categorized into Data Library, Data Processing and Data Analysis. It can be a potential enabler for scientists engaged in drug discovery in general and in anti-TB research in particular. [Figure not available: see fulltext.] © 2017, Indian Academy of Sciences.
Keywords: chemical analysis; Chemoinformatics; computational chemistry; Diagnosis; Drug discovery portal; Information analysis; Libraries; Molecular graphics; Molecules; Neglected diseases; Open science; Portals; tuberculosis; Web-based technology; Websites