MAPS Database: Medicinal plant Activities,Phytochemical and Structural Database

Drug development from natural sources is an important and fast developing area. Natural sources (plants) have been used to cure a range of diseases for Thousands of years. Different online medicinal plant databases provide information about classifications, activities, phytochemicals and structure of phytochemicals in different formats. These databases do not cover all aspects of medicinal plants. MAPS (Medicinal plant Activities, Phytochemicals & structural database) has been constructed with uniqueness that it combines all information in one web resource and additionally provides test targets on which particular plant found to be effective with reference to the original paper as well. MAPS database is user friendly information resource, including the data of > 500 medicinal plants. This database includes phytochemical constituents, their structure in mol format, different activities possessed by the medicinal plant with the targets reported in literature.

Availability

http://www.mapsdatabase.com     

MPDB 1.0: a medicinal plant database of Bangladesh

The term of medicinal plants include a various types of plants used in herbalism with medicinal activities. These plants are considered as rich resources of ingredients which can be used as complementary and alternative medicines and, also in drug developments and synthesis. In addition, some plants regarded as valuable origin of nutrition. Thus, all these plants are recommended as therapeutic agents. Information related to medicinal plants and herbal drugs accumulated over the ages are scattered and unstructured which make it prudent to develop a curated database for medicinal plants. MPDB 1.0 database is dedicated to provide the first window to find the plants around Bangladesh claimed to have medicinal and/or nutritive values by accumulating data from the published literatures. This database contains 406 medicinal plants with their corresponding scientific, family and local names as well as utilized parts for treatment from different districts of Bangladesh. Information regarding ailments is available for 353 plants. In addition, we have found active compounds for 78 plants with their corresponding PubMed ID.

Availability

www.medicinalplantbd.net     

InDiaMed: A Comprehensive Database of Indian Medicinal plants for Diabetes

According to International Diabetes Federation (IDF), India has 62.4 million people with diabetes and by 2030 it is predicted that the number will rise to 100 million. Studies claim that there are around 410 experimentally proven Indian medicinal plants which have anti-diabetic activity, of which the mechanism of action of 109 plants has been elucidated or reported. So, the need of the hour is to explore the claims of Indian medicinal flora and open up the facets of many Indian plants which are being examined for their beneficial role in diabetes. So, we created a database (InDiaMed) of Indian medicinal plants that captures their role in anti-diabetic activity. InDiaMed''s features include chemical, pharmacological, biochemical and geographical information of the medicinal plant, scientifically relevant information of the plant, and the coherent research done on it in the field of diabetes. The database also includes the list of poly-herbal formulations which are used for treatment of diabetes in India.

Availability

http://www.indiamed.info     

Phyto-mellitus: A phyto-chemical database for diabetes

Herbs are the base used for treatment in Ayurveda. We describe a database named Phyto-Mellitus with information on plants traditionally used for diabetes with their chemical constituents. The active principles of these plants are antioxidant and free radical scavenging.

Availability

http://www.bicmlacw.org/bt/     

Enhancing protein-vitamin binding residues prediction by multiple heterogeneous subspace SVMs ensemble

Background

Vitamins are typical ligands that play critical roles in various metabolic processes. The accurate identification of the vitamin-binding residues solely based on a protein sequence is of significant importance for the functional annotation of proteins, especially in the post-genomic era, when large volumes of protein sequences are accumulating quickly without being functionally annotated.

Results

In this paper, a new predictor called TargetVita is designed and implemented for predicting protein-vitamin binding residues using protein sequences. In TargetVita, features derived from the position-specific scoring matrix (PSSM), predicted protein secondary structure, and vitamin binding propensity are combined to form the original feature space; then, several feature subspaces are selected by performing different feature selection methods. Finally, based on the selected feature subspaces, heterogeneous SVMs are trained and then ensembled for performing prediction.

Conclusions

The experimental results obtained with four separate vitamin-binding benchmark datasets demonstrate that the proposed TargetVita is superior to the state-of-the-art vitamin-specific predictor, and an average improvement of 10% in terms of the Matthews correlation coefficient (MCC) was achieved over independent validation tests. The TargetVita web server and the datasets used are freely available for academic use at http://csbio.njust.edu.cn/bioinf/TargetVita or http://www.csbio.sjtu.edu.cn/bioinf/TargetVita.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2105-15-297) contains supplementary material, which is available to authorized users.     

Safety and Immunogenicity of Heterologous Prime-Boost Immunisation with Plasmodium falciparum Malaria Candidate Vaccines,ChAd63 ME-TRAP and MVA ME-TRAP,in Healthy Gambian and Kenyan Adults

Background

Heterologous prime boost immunization with chimpanzee adenovirus 63 (ChAd63) and Modified vaccinia Virus Ankara (MVA) vectored vaccines is a strategy recently shown to be capable of inducing strong cell mediated responses against several antigens from the malaria parasite. ChAd63-MVA expressing the Plasmodium falciparum pre-erythrocytic antigen ME-TRAP (multiple epitope string with thrombospondin-related adhesion protein) is a leading malaria vaccine candidate, capable of inducing sterile protection in malaria naïve adults following controlled human malaria infection (CHMI).

Methodology

We conducted two Phase Ib dose escalation clinical trials assessing the safety and immunogenicity of ChAd63-MVA ME-TRAP in 46 healthy malaria exposed adults in two African countries with similar malaria transmission patterns.

Results

ChAd63-MVA ME-TRAP was shown to be safe and immunogenic, inducing high-level T cell responses (median >1300 SFU/million PBMC).

Conclusions

ChAd63-MVA ME-TRAP is a safe and highly immunogenic vaccine regimen in adults with prior exposure to malaria. Further clinical trials to assess safety and immunogenicity in children and infants and protective efficacy in the field are now warranted.

Trial Registration

Pactr.org PACTR2010020001771828 http://www.pactr.org/ Pactr.org PACTR201008000221638 http://www.pactr.org/ ClinicalTrials.gov {"type":"clinical-trial","attrs":{"text":"NCT01373879","term_id":"NCT01373879"}}NCT01373879 {"type":"clinical-trial","attrs":{"text":"NCT01373879","term_id":"NCT01373879"}}NCT01373879 ClinicalTrials.gov {"type":"clinical-trial","attrs":{"text":"NCT01379430","term_id":"NCT01379430"}}NCT01379430 {"type":"clinical-trial","attrs":{"text":"NCT01379430","term_id":"NCT01379430"}}NCT01379430     

miRPlant: an integrated tool for identification of plant miRNA from RNA sequencing data

Background

Small RNA sequencing is commonly used to identify novel miRNAs and to determine their expression levels in plants. There are several miRNA identification tools for animals such as miRDeep, miRDeep2 and miRDeep*. miRDeep-P was developed to identify plant miRNA using miRDeep’s probabilistic model of miRNA biogenesis, but it depends on several third party tools and lacks a user-friendly interface. The objective of our miRPlant program is to predict novel plant miRNA, while providing a user-friendly interface with improved accuracy of prediction.

Result

We have developed a user-friendly plant miRNA prediction tool called miRPlant. We show using 16 plant miRNA datasets from four different plant species that miRPlant has at least a 10% improvement in accuracy compared to miRDeep-P, which is the most popular plant miRNA prediction tool. Furthermore, miRPlant uses a Graphical User Interface for data input and output, and identified miRNA are shown with all RNAseq reads in a hairpin diagram.

Conclusions

We have developed miRPlant which extends miRDeep* to various plant species by adopting suitable strategies to identify hairpin excision regions and hairpin structure filtering for plants. miRPlant does not require any third party tools such as mapping or RNA secondary structure prediction tools. miRPlant is also the first plant miRNA prediction tool that dynamically plots miRNA hairpin structure with small reads for identified novel miRNAs. This feature will enable biologists to visualize novel pre-miRNA structure and the location of small RNA reads relative to the hairpin. Moreover, miRPlant can be easily used by biologists with limited bioinformatics skills.miRPlant and its manual are freely available at http://www.australianprostatecentre.org/research/software/mirplant or http://sourceforge.net/projects/mirplant/.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2105-15-275) contains supplementary material, which is available to authorized users.     

DNA Replication Error-Induced Extinction of Diploid Yeast

Genetic defects in DNA polymerase accuracy, proofreading, or mismatch repair (MMR) induce mutator phenotypes that accelerate adaptation of microbes and tumor cells. Certain combinations of mutator alleles synergistically increase mutation rates to levels that drive extinction of haploid cells. The maximum tolerated mutation rate of diploid cells is unknown. Here, we define the threshold for replication error-induced extinction (EEX) of diploid Saccharomyces cerevisiae. Double-mutant pol3 alleles that carry mutations for defective DNA polymerase-δ proofreading (pol3-01) and accuracy (pol3-L612M or pol3-L612G) induce strong mutator phenotypes in heterozygous diploids (POL3/pol3-01,L612M or POL3/pol3-01,L612G). Both pol3-01,L612M and pol3-01,L612G alleles are lethal in the homozygous state; cells with pol3-01,L612M divide up to 10 times before arresting at random stages in the cell cycle. Antimutator eex mutations in the pol3 alleles suppress this lethality (pol3-01,L612M,eex or pol3-01,L612G,eex). MMR defects synergize with pol3-01,L612M,eex and pol3-01,L612G,eex alleles, increasing mutation rates and impairing growth. Conversely, inactivation of the Dun1 S-phase checkpoint kinase suppresses strong pol3-01,L612M,eex and pol3-01,L612G,eex mutator phenotypes as well as the lethal pol3-01,L612M phenotype. Our results reveal that the lethal error threshold in diploids is 10 times higher than in haploids and likely determined by homozygous inactivation of essential genes. Pronounced loss of fitness occurs at mutation rates well below the lethal threshold, suggesting that mutator-driven cancers may be susceptible to drugs that exacerbate replication errors.     

Molecular Pathways Involved in Prostate Carcinogenesis: Insights from Public Microarray Datasets

Background

Prostate cancer is currently the most frequently diagnosed malignancy in men and the second leading cause of cancer-related deaths in industrialized countries. Worldwide, an increase in prostate cancer incidence is expected due to an increased life-expectancy, aging of the population and improved diagnosis. Although the specific underlying mechanisms of prostate carcinogenesis remain unknown, prostate cancer is thought to result from a combination of genetic and environmental factors altering key cellular processes. To elucidate these complex interactions and to contribute to the understanding of prostate cancer progression and metastasis, analysis of large scale gene expression studies using bioinformatics approaches is used to decipher regulation of core processes.

Methodology/Principal Findings

In this study, a standardized quality control procedure and statistical analysis (http://www.arrayanalysis.org/) were applied to multiple prostate cancer datasets retrieved from the ArrayExpress data repository and pathway analysis using PathVisio (http://www.pathvisio.org/) was performed. The results led to the identification of three core biological processes that are strongly affected during prostate carcinogenesis: cholesterol biosynthesis, the process of epithelial-to-mesenchymal transition and an increased metabolic activity.

Conclusions

This study illustrates how a standardized bioinformatics evaluation of existing microarray data and subsequent pathway analysis can quickly and cost-effectively provide essential information about important molecular pathways and cellular processes involved in prostate cancer development and disease progression. The presented results may assist in biomarker profiling and the development of novel treatment approaches.     

New Regulators of Clathrin-Mediated Endocytosis Identified in Saccharomyces cerevisiae by Systematic Quantitative Fluorescence Microscopy

Despite the importance of clathrin-mediated endocytosis (CME) for cell biology, it is unclear if all components of the machinery have been discovered and many regulatory aspects remain poorly understood. Here, using Saccharomyces cerevisiae and a fluorescence microscopy screening approach we identify previously unknown regulatory factors of the endocytic machinery. We further studied the top scoring protein identified in the screen, Ubx3, a member of the conserved ubiquitin regulatory X (UBX) protein family. In vivo and in vitro approaches demonstrate that Ubx3 is a new coat component. Ubx3-GFP has typical endocytic coat protein dynamics with a patch lifetime of 45 ± 3 sec. Ubx3 contains a W-box that mediates physical interaction with clathrin and Ubx3-GFP patch lifetime depends on clathrin. Deletion of the UBX3 gene caused defects in the uptake of Lucifer Yellow and the methionine transporter Mup1 demonstrating that Ubx3 is needed for efficient endocytosis. Further, the UBX domain is required both for localization and function of Ubx3 at endocytic sites. Mechanistically, Ubx3 regulates dynamics and patch lifetime of the early arriving protein Ede1 but not later arriving coat proteins or actin assembly. Conversely, Ede1 regulates the patch lifetime of Ubx3. Ubx3 likely regulates CME via the AAA-ATPase Cdc48, a ubiquitin-editing complex. Our results uncovered new components of the CME machinery that regulate this fundamental process.     

A database for allergenic proteins and tools for allergenicity prediction

The AllergenPro database has developed a web-based system that will provide information about allergen in microbes, animals and plants. The database has three major parts and functions:(i) database list; (ii) allergen search; and (iii) allergenicity prediction. The database contains 2,434 allergens related information readily available in the database such as on allergens in rice microbes (712 records), animals (617 records) and plants (1,105 records). Furthermore, this database provides bioinformatics tools for allergenicity prediction. Users can search for specific allergens by various methods and can run tools for allergenicity prediction using three different methods.

Availability

The database is available for free at http://www.niab.go.kr/nabic/     

Mammalian Mitochondrial ncRNA Database

Mammalian Mitochondrial ncRNA is a web-based database, which provides specific information on non-coding RNA in mammals. This database includes easy searching, comparing with BLAST and retrieving information on predicted structure and its function about mammalian ncRNAs.

Availability

The database is available for free at http://www.iitm.ac.in/bioinfo/mmndb/     

Kiwi: a tool for integration and visualization of network topology and gene-set analysis

Background

The analysis of high-throughput data in biology is aided by integrative approaches such as gene-set analysis. Gene-sets can represent well-defined biological entities (e.g. metabolites) that interact in networks (e.g. metabolic networks), to exert their function within the cell. Data interpretation can benefit from incorporating the underlying network, but there are currently no optimal methods that link gene-set analysis and network structures.

Results

Here we present Kiwi, a new tool that processes output data from gene-set analysis and integrates them with a network structure such that the inherent connectivity between gene-sets, i.e. not simply the gene overlap, becomes apparent. In two case studies, we demonstrate that standard gene-set analysis points at metabolites regulated in the interrogated condition. Nevertheless, only the integration of the interactions between these metabolites provides an extra layer of information that highlights how they are tightly connected in the metabolic network.

Conclusions

Kiwi is a tool that enhances interpretability of high-throughput data. It allows the users not only to discover a list of significant entities or processes as in gene-set analysis, but also to visualize whether these entities or processes are isolated or connected by means of their biological interaction. Kiwi is available as a Python package at http://www.sysbio.se/kiwi and an online tool in the BioMet Toolbox at http://www.biomet-toolbox.org.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-014-0408-9) contains supplementary material, which is available to authorized users.