Computation Resources for Drug Discovery (CRDD)

From DrugPedia: A Wikipedia for Drug discovery

Current revision

Computational Resources for Drug Discovery (CRDD) is one of the important silico modules of Open Source for Drug Discovery (OSDD). The CRDD web portal provides computer resources related to drug discovery on a single platform. Following are major features of CRDD; I) computational resources for researchers in the field of computer-aided drug design, ii) discussion form to discuss their problem with other members, iii) maintain wikipedia related to drug discovery, iv) developing database related to medicine; v) prediction of inhibitors and vi) prediction of ADMET property of molecules. One of the major objectives of CRDD is to promote open source software in the field of chemoinformatics and pharmacoinformatics. All are welcome to participate in this novel mission. Following are major features of CRDD

[edit] Resource compilation

Under CRDD, all the resources related to computer-aided drug designs have been collected and compiled. These resources were classify and presented on CRDD so users can got resources from single source.

[edit] Target identification

In this category all the resources important for searching drug targets have been saved under following classes, Genome Annotation, Proteome Annotation, Potential Targets, Protein Structure

[edit] Virtual screening

In this category all the resources important for virtual screening have been compiled under following classes, QSAR Techniques, Docking QSAR, Chemoinformatics, siRNA/miRNA

[edit] Drug design

In this category all the resources important for designing drug inhibitors/molecules have been classify under following classes, Lead Optimization, Pharmainformatics, ADMET, Clinical Informatics

[edit] Community contribution

Under this category platform has been developed where community may contribute in the process of drug discovery. Following are major

[edit] DrugPedia: A Wikipedia for Drug Discovery

Drugpedia is a wikipedia created for collecting and compiling information related to computer-aided drug design. The aim of Drugpedia is to provide comprehensive information about drugs. It is developed under the umbrella of Open Source Drug Discovery (OSDD) project. It covers wide range of subjects around drugs like Bioinformatics, Cheminfiormatics, clinical informatics etc.

[edit] Indipedia: A wikipedia for India

Indipedia is a wikipedia created for collecting and compiling information related to India. The aim of Indipedia is to provide comprehensive information about India created for Indians by Indians. It is developed under the umbrella of Open Source Drug Discovery (OSDD) project.

[edit] CRDD Forum

CRDD Forum CRDD forum was launched to discuss the challenge in developing computational resources for drug discovery.

[edit] Indigenous Development : Software and Web Services

Beside collecting and compiling resources, CRDD members are actively involved in developing new software and web services. All services developed are free for academic use. CRDD team is working hard to develop the Open Sources software in the field of chemoinformatics/pharmainformatics. CRDD team have dream that in coming years the public will have a platform from where they can contribute in the process of drug discovery. The following are a few major tools developed at CRDD.

[edit] Development of Databases

• HMRBase: It is a manually curated database of Hormones and their Receptors. It is a compilation of sequence data after extensive manual literature search and from publicly available databases. HMRbase can be searched on the basis of a variety of data types. Owing to the high impact of endocrine research in the biomedical sciences, the Hmrbase could become a leading data portal for researchers. The salient features of Hmrbase are hormone-receptor pair-related information, mapping of peptide stretches on the protein sequences of hormones and receptors, Pfam domain annotations, categorical browsing options, online data submission (Ref BMC Genomics 2009, 10:307). This database integrated in drugpedia so public can contribute.
• BIAdb: A Database for Benzylisoquinoline Alkaloids. The Benzylisoquinoline Alkaloid Database is an attempt to gather the scattered information related to the BIA's. Many BIA's show therapeutic properties and can be considered as potent drug candidates. This database will also serve researchers working in the field of synthetic biology, as developing medicinally important alkaloids using synthetic process are one of important challenges. This database integrated in drugpedia so public can contribute [Ref BMC Pharmacology 2010, 10:4
• AntigenDB: This database contain more than 500 antigens collected from literature and other immunological resources. These antigens come from 44 important pathogenic species. In AntigenDB, a database entry contains information regarding the sequence, structure, origin, etc. of an antigen with additional information such as B and T-cell epitopes, MHC binding, function, gene-expression and post translational modifications, where available. AntigenDB also provides links to major internal and external databases (Ref Nucleic Acids Res. 2010: D847-53.
• PolysacDB: The PolysacDB is dedicated to provide comprehensive information about antigenic polysaccharides of microbial origin (bacterial and fungal), antibodies against them, proposed epitopes, structural detail, proposed functions, assay system, cross-reactivity related information and much more. It is a manually curated database where most of data has been collected from PubMed and PubMed Central literature databases.

[edit] Software Developed

MycoTB: In order to assist scientific community, we extended flexible system concept for building standalone software MycoTB for Windows Users. MycoTB is one of the computer program developed under OSDD/CRDD programme. This software allow user to built their own flexible system on their personal computers to mange and annotate whole proteome of MycoTB.

[edit] Resources created

• CRAG: Computational Resources for Assembling of Genomes (CRAG) has been to assist the users in assembling of genomes from short read sequencing (SRS). Following major objective; i) Collection and compilation of computation resources, ii) Brief Description of genome assemblers, iii) Maintaing SRS and related data, iv) Service to community to assemble their genomes
• CRIP: Computational Resources for predicting protein-macromolecular interactions (CRIP) developed to provide resources related interaction. This site maintain large number of resources on interaction world of proteins that includes, protein-protein, protein-DNA, Protein-Ligand, Protein-RNA.

• BioTherapi: Bioinformatics for Therapeutic Peptides and Proteins (BioTherapi) developed for researchers working in the field of protein/peptide therapeutics. At present there is no single platform that provide this kind of information. This site include all the relevant information about the use of Peptides/Proteins in drug and synthesis of new peptides. It also cover problems, in their formulation, synthesis and delivery process
• HivBio: HIV Bioinformatics (HIVbio) site contains variou types of information on Human Immunodefeciency Virus (HIV) life cycle and Infection.

• GDPbio: GDPbio (Genome based prediction of Diseases and Personal medicines using Bioinformatics) is the project focussed upon providing various resources related to genome analysis particularly for the prediction of disease susceptibility of a particular individual and personalized medicines development, aiming public health improvement.
• AminoFAT: Functional Annotation Tools for Amino Acids (AminoFAT) server is designed to serve the bioinformatics community. Aim is to develop as many as possible tools to understand function of amino acids in proteins based on protein structure in PDB. The broad knowledge of proteins function would help in the identification of noval drug targets.

[edit] Web services for Chemoinformatics

First time in the world CRDD team has developed open source platform which allows users to predict inhibitors against novel M. Tuberculosis drug targets and other important properties of drug molecules like ADMET. Following are list of few servers.

• MetaPred: A webserver for the Prediction of Cytochrome P450 Isoform responsible for Metabolizing a Drug Molecule. MetaPred Server predict metabolizing CYP isoform of a drug molecule/substrate, based on SVM models developed using CDK descriptors.This server will be helpful for researcher working in the field of drug discovery.This study demonstrates that it is possible to develop free web servers in the field of chemoinformatics. This will encourage other researchers to develop web server for public use, which may lead to decrease the cost of discovering new drug molecules (Ref BMC Pharmacology 2010, 10:8).
• ToxiPred: A server for prediction of aqueous toxicity of small chemical molecules in T. pyriformis.
• KetoDrug:A web server for binding affinity prediction of ketoxazole derivatives against Fatty Acid Amide Hydrolase (FAAH). It is a user friendly web sever for the prediction of binding affinity of small chemical molecules against FAAH.
• KiDoQ: KiDoQ, a web server has been developed to serve scientific community working in the field of designing inhibitors against Dihydrodipicolinate synthase (DHDPS), a potential drug target enzyme of a unique bacterial DAP/Lysine pathway (Ref BMC Bioinformatics 2010, 11:125).

• GDoQ: GDoQ (Prediction of GLMU inhibitors using QSAR and AutoDock) is a open source platform developed for predicting inhibitors against Mycobacterium Tuberculosis (M.Tb) drug target N-acetylglucosamine-1-phosphate uridyltransferase (GLMU) protein. This i a potential drug target involved in bacterial cell wall synthesis. This server uses molecular docking and QSAR strategies to predict inhibitory activity value (IC50) of chemical compounds for GLMU protein.

• ROCR: The ROCR is an R package for evaluating and visualizing classifier performance . It is a flexible tool for creating ROC graphs, sensitivity/specificity curves, area under curve and precision/recall curve. The parametrization can be visualized by coloring the curve according to cutoff.

• WebCDK: A web interface for CDK library, it is a web interface for predicting descriptors of chemicals using CDK library.

• Pharmacokinetics: The Pharmacokinetic data analysis determines the relationship between the dosing regimen and the body's exposure to the drug as measured by the nonlinear concentration time curve. It includes a function, AUC, to calculate area under the curve. It also includes functions for half-life estimation for a biexponential model, and a two phase linear regression

[edit] Prediction and analysis of drug targets

• RNApred: Kumar,M., Gromiha, M.M. and Raghava, G. P. S. (2010) SVM based prediction of RNA-binding proteins using binding residues and evolutionary information. Journal Molecular Recognition (In Press)
• ProPrint:Rashid, M. and Raghava, G. P. S. (2010) A simple approach for predicting protein-protein interactions. Current Protein & Peptide Science (In Press).
• DomPrint: Domprint is a domain-domain interaction (DDI) prediction server.
• MycoPrint: MycoPrint is a web interface for exploration of the interactome of Mycobacterium tuberculosis H37Rv (Mtb) predicted by "Domain Interaction Mapping" (DIM) method.
• ATPint: Chauhan,J.S., Mishra, N.K. and Raghava, G. P. S. (2009) Identification of ATP binding residues of a protein from its primary sequence. BMC Bioinformatics 10:434.
• FADpred: Mishra, N.K. and Raghava, G. P. S. (2010) Prediction of FAD interacting residues in a protein from its primary sequence using evolutionary information. BMC Bioinformatics 11:S48.
• GTPbinder: Chauhan, J. S., Mishra, N. K. and Raghava, G. P. S. (2010) Prediction of GTP interacting residues, dipeptides and tripeptides in a protein from its evolutionary information. BMC Bioinformatics 2010, 11:301.
• NADbinder: Ansari, H. R. and Raghava, G. P. S. (2010) Identification of NAD interacting residues in proteins. BMC Bioinformatics 11:160.
• PreMier: Designing of Mutants of Antibacterial Peptides
• DMAP: DMAP: Designing of Mutants of Antibacterial Peptides
• icaars: Pawar, B. and Raghava, G.P.S (2010) Prediction and classification of aminoacyl tRNA synthetases using PROSITE domains. BMC Genomics 2010, 11:507

[edit] Maintained and Contact

This site is developed and maintained at Institute of Microbial Technology, Chandigarh, by CRDD team under guidance of Gajendra Pal Singh Raghava, for more information contact

• Gajendra P. S. Raghava

Scientist & Head Bioinformatics Centre

Institute of Microbial Technology

Sector 39, Chandigarh , India

[edit] References

[1] Prediction of cytochrome P450 isoform responsible for metabolizing a drug molecule. BMC Pharmacology 2010, 10:8