GCAC: galaxy workflow system for predictive model building for virtual screening.

BACKGROUND: Traditional drug discovery approaches are time-consuming, tedious and expensive. Identifying a potential drug-like molecule using high throughput screening (HTS) with high confidence is always a challenging task in drug discovery and cheminformatics. A small percentage of molecules that pass the clinical trial phases receives FDA approval. This whole process takes 10-12 years and millions of dollar of investment. The inconsistency in HTS is also a challenge for reproducible results. Reproducible research in computational research is highly desirable as a measure to evaluate scientific claims and published findings. This paper describes the development and availability of a knowledge based predictive model building system using the R Statistical Computing Environment and its ensured reproducibility using Galaxy workflow system. RESULTS: We describe a web-enabled data mining analysis pipeline which employs reproducible research approaches to confront the issue of availability of tools in high throughput virtual screening. The pipeline, named as "Galaxy for Compound Activity Classification (GCAC)" includes descriptor calculation, feature selection, model building, and screening to extract potent candidates, by leveraging the combined capabilities of R statistical packages and literate programming tools contained within a workflow system environment with automated configuration. CONCLUSION: GCAC can serve as a standard for screening drug candidates using predictive model building under galaxy environment, allowing for easy installation and reproducibility. A demo site of the tool is available at http://ccbb.jnu.ac.in/gcac.

Design, synthesis, in-silico and biological evaluation of novel donepezil derivatives as multi-target-directed ligands for the treatment of Alzheimer's disease.

A novel series of donepezil based multi-functional agents "(E)-5,6-dimethoxy-2-(4-(4-substituted piperazin-1-yl)benzylidene)-2,3-dihydro-1H-inden-1-ones" have been designed and synthesized as potential anti-Alzheimer's agents. In-vitro studies revealed that these compounds demonstrated moderate to good AChE and Aß aggregation inhibitory activity. These derivatives are also endowed with admirable antioxidant activity. Among the entire series compounds IP-9, IP-13 and IP-15 appeared as most active multi-functional agents and displayed marked AChE inhibitory, Aß disaggregation and antioxidant activity. Studies indicate that IP-13 and IP-15 showed better AChE inhibitory activity than the standard drug donepezil and IP-9, IP-13 as well as IP-15 exhibited better Aß aggregation inhibitory activity than curcumin. These compounds (IP-9, IP-13 and IP-15) successfully diminished H2O2 induced oxidative stress in SH-SY5Y cells and displayed excellent neuroprotective activity against H2O2 as well as Aß induced toxicity in SH-SY5Y cells in a concentration dependent manner. Moreover, these derivatives did not exert any significant toxicity in neuronal SH-SY5Y cells in cytotoxicity assay. To elucidate the plausible binding mode of the compounds IP-9, IP-13 and IP-15, molecular docking studies and molecular dynamics (MD) simulation studies were also performed and the results indicate their significant interactions with the active sites of AChE as well as Aß1-42 peptide. Thus, the present study evidently showed that IP-9, IP-13 and IP-15 are potent multi-functional agents against Alzheimer's disease and might serve as promising lead candidates for anti-Alzheimer drug development.

Ethnobotanical perspective of antimalarial plants: traditional knowledge based study.

BACKGROUND: Considering the demand of antimalarial plants it has become essential to find and locate them for their optimal extraction. The work aims to find plants with antimalarial activities which were used by the local people; to raise the value of traditional knowledge system (TKS) prevalent in the study region; to compile characteristics of local plants used in malaria treatment (referred as antimalarial plants) and to have its spatial distribution analysis to establish a concept of geographical health. METHODS: Antimalarial plants are listed based on literature survey and field data collected during rainy season, from 85 respondents comprised of different ethnic groups. Ethno-medicinal utilities of plants was extracted; botanical name, family, local name, part used, folklore, geographical location and image of plants were recorded after cross validating with existing literatures. The interview was trifurcated in field, Vaidya/Hakims and house to house. Graphical analysis was done for major plants families, plant part used, response of people and patients and folklore. Mathematical analysis was done for interviewee's response, methods of plant identification and people's preferences of TKS through three plant indices. RESULTS: Fifty-one plants belonging to 27 families were reported with its geographical attributes. It is found plant root (31.75 %) is used mostly for malaria treatment and administration mode is decoction (41.2 %) mainly. The study area has dominance of plants of family Fabaceae (7), Asteraceae (4), Acanthaceae (4) and Amaranthaceae (4). Most popular plants found are Adhatoda vasica, Cassia fistula and Swertia chirata while  % usage of TKS is 82.0 % for malaria cure. CONCLUSION: The research findings can be used by both scientific community and common rural people for bio-discovery of these natural resources sustainably. The former can extract the tables to obtain a suitable plant towards finding a suitable lead molecule in a drug discovery project; while the latter can meet their local demands of malaria, scientifically.