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Computational Resource for Drug Discovery: Difference between revisions
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'''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. It provides computational resources for researchers in computer-aided [[drug design]], a discussion forum, and resources to maintain [[Wikipedia]] related to drug discovery, predict inhibitors, and predict the [[ADME-Tox]] property of molecules | '''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. It provides computational resources for researchers in computer-aided [[drug design]], a discussion forum, and resources to maintain a [[Wikipedia]] related to drug discovery, predict inhibitors, and predict the [[ADME-Tox]] property of molecules. | ||
One of the major objectives of CRDD is to promote open source [[software]] in the field of [[chemoinformatics]] and [[pharmacoinformatics]]. | One of the major objectives of CRDD is to promote open source [[software]] in the field of [[chemoinformatics]] and [[pharmacoinformatics]]. | ||
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Under CRDD, all the resources related to computer-aided drug design have been collected and compiled. These resources are organized and presented on CRDD so users can get resources from a single source. | Under CRDD, all the resources related to computer-aided drug design have been collected and compiled. These resources are organized and presented on CRDD so users can get resources from a single source. | ||
*Target identification provides | *Target identification provides resources important for searching drug targets with information on [[genome annotation]], [[proteome|proteome annotation]], potential targets, and [[protein structure]] | ||
*Virtual screening compiles | *Virtual screening compiles resources important for virtual screening as QSAR techniques, docking QSAR, chemoinformatics, and [[siRNA]]/[[miRNA]] | ||
*Drug design provides | *Drug design provides resources important for designing drug inhibitors/molecules, such as lead optimization, pharmacoinformatics, ADMET, and clinical informatics | ||
==Community contribution == | ==Community contribution == | ||
A platform has been developed where the community may contribute to the process of drug discovery. | |||
*DrugPedia: A Wikipedia for Drug Discovery is a Wiki created for collecting and compiling information related to computer-aided drug design. It is developed under the umbrella of Open Source Drug Discovery (OSDD) project and covers wide range of subjects around drugs like [[Bioinformatics]], | *DrugPedia: A Wikipedia for Drug Discovery is a Wiki created for collecting and compiling information related to computer-aided drug design. It is developed under the umbrella of the Open Source Drug Discovery (OSDD) project and covers a wide range of subjects around drugs like [[Bioinformatics]], Cheminformatics, clinical informatics etc. | ||
*Indipedia: A Wikipedia for [[India]] is a Wiki for collecting and compiling drug | *Indipedia: A Wikipedia for [[India]] is a Wiki for collecting and compiling drug information related to India. It is intended is to provide comprehensive information about India created for Indians by Indians. It is developed under the umbrella of the Open Source Drug Discovery (OSDD) project. | ||
*The CRDD Forum was launched to discuss the | *The CRDD Forum was launched to discuss the challenges in developing computational resources for drug discovery. | ||
== Indigenous development: software and web services == | == Indigenous development: software and web services == | ||
Beside collecting and compiling resources, CRDD members develop new software and web services. All services developed are free for academic use. The following are a few major tools developed at CRDD.{{ | Beside collecting and compiling resources, CRDD members develop new software and web services. All services developed are free for academic use. The following are a few major tools developed at CRDD.<ref>{{Cite web |title=Computational Resource for Drug Discovery |url=https://encyclopedia.pub/entry/31662 |access-date=2022-11-08 |website=encyclopedia.pub |language=en}}</ref> | ||
=== Development of databases=== | === Development of databases=== | ||
*HMRBase: It is a manually curated [[database]] of [[Hormones]] and their [[Hormone receptors|Receptors]]. It is a compilation of sequence data after extensive manual literature search and from publicly available databases. | *HMRBase: It is a manually curated [[database]] of [[Hormones]] and their [[Hormone receptors|Receptors]]. It is a compilation of sequence data after extensive manual literature search and from publicly available databases. Hombres can be searched on the basis of a variety of data types. Owing to the high impact of [[Endocrine Research|endocrine research]] in the biomedical sciences, the Hmrbase could become a leading data portal for researchers. The salient features of Hombres 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>{{cite journal |last1=Rashid |first1=Mamoon |last2=Singla |first2=Deepak |last3=Sharma |first3=Arun |last4=Kumar |first4=Manish |last5=Raghava |first5=Gajendra PS |title=Hmrbase: a database of hormones and their receptors |journal=BMC Genomics |volume=10 |pages=307 |year=2009 |pmid=19589147 |pmc=2720991 |doi=10.1186/1471-2164-10-307}}</ref> This database integrated in drug media 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>{{cite journal |last1=Singla |first1=Deepak |last2=Sharma |first2=Arun |last3=Kaur |first3=Jasjit |last4=Panwar |first4=Bharat |last5=Raghava |first5=Gajendra PS |title=BIAdb: A curated database of benzylisoquinoline alkaloids |journal=BMC Pharmacology |volume=10 |pages=4 |year=2010 |pmid=20205728 |pmc=2844369 |doi=10.1186/1471-2210-10-4}}</ref> | *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>{{cite journal |last1=Singla |first1=Deepak |last2=Sharma |first2=Arun |last3=Kaur |first3=Jasjit |last4=Panwar |first4=Bharat |last5=Raghava |first5=Gajendra PS |title=BIAdb: A curated database of benzylisoquinoline alkaloids |journal=BMC Pharmacology |volume=10 |pages=4 |year=2010 |pmid=20205728 |pmc=2844369 |doi=10.1186/1471-2210-10-4}}</ref> | ||
* | *Antigen DB: This database contain more than 500 [[antigens]] collected from literature and other immunological resources. These antigens come from 44 important pathogenic species. In Antigen DB, a database entry contains information regarding the sequence, structure, origin, etc. of an antigen with additional information such as B and [[T cells|T-cell]] [[epitopes]], [[Major histocompatibility complex|MHC]] binding, function, gene-expression and post translational modifications, where available. AntigenDB also provides links to major internal and external databases.<ref>{{cite journal |last1=Ansari |first1=H. R. |last2=Flower |first2=D. R. |last3=Raghava |first3=G. P. S. |title=AntigenDB: an immunoinformatics database of pathogen antigens |journal=Nucleic Acids Research |volume=38 |issue=Database issue |pages=D847–53 |year=2009 |pmid=19820110 |pmc=2808902 |doi=10.1093/nar/gkp830}}</ref> | ||
*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. | *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. | ||
*TumorHope: TumorHope is a manually curated comprehensive database of experimentally characterized [[tumor]] homing peptides. These peptides recogninze tumor tissues and tumor associated micro environment, including tumor [[metastasis]]. | *TumorHope: TumorHope is a manually curated comprehensive database of experimentally characterized [[tumor]] homing peptides. These peptides recogninze tumor tissues and tumor associated micro environment, including tumor [[metastasis]]. | ||
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*CRAG: Computational resources for assembling 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) Maintaining SRS and related data, iv) Service to community to assemble their genomes | *CRAG: Computational resources for assembling 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) Maintaining 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]]. | *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]]. | ||
* | *BioTherapy: 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 | ||
* | *HiveBio: HIV Bioinformatics (HIVbio) site contains various types of information on [[Human immunodeficiency virus|Human Immunodeficiency Virus]] (HIV) life cycle and Infection. | ||
* | *GDP bio: GDP bio (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. | ||
* | *AminoFAST: Functional Annotation Tools for Amino Acids (AminoFAST) 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. | ||
=== Web services for chemoinformatics === | === Web services for chemoinformatics === | ||
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*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. | *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 [[Cyclin-dependent kinase|CDK]] library, it is a web interface for predicting descriptors of chemicals using CDK library. | *WebCDK: A web interface for [[Cyclin-dependent kinase|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 | *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 | ||
=== Prediction and analysis of drug targets === | === Prediction and analysis of drug targets === | ||
*RNApred: Prediction of RNAbinding proteins from ints amino acid sequence.<ref>{{cite journal |last1=Kumar |first1=M |last2=Gromiha |first2=MM |last3=Raghava |first3=GP |title=SVM based prediction of RNA-binding proteins using binding residues and evolutionary information |journal=[[Journal of Molecular Recognition]] |pages= 303–13|year=2010 |pmid=20677174 |doi=10.1002/jmr.1061 |volume=24 |issue=2}}</ref> | *RNApred: Prediction of RNAbinding proteins from ints amino acid sequence.<ref>{{cite journal |last1=Kumar |first1=M |last2=Gromiha |first2=MM |last3=Raghava |first3=GP |title=SVM based prediction of RNA-binding proteins using binding residues and evolutionary information |journal=[[Journal of Molecular Recognition]] |pages= 303–13|year=2010 |pmid=20677174 |doi=10.1002/jmr.1061 |volume=24 |issue=2|s2cid=12677753 }}</ref> | ||
*ProPrint: Prediction of interaction between proteins from their amino acid sequence.<ref>Rashid, M. and Raghava, G. P. S. (2010) A simple approach for predicting protein–protein interactions. Current Protein & Peptide Science (In Press).</ref> | *ProPrint: Prediction of interaction between proteins from their amino acid sequence.<ref>Rashid, M. and Raghava, G. P. S. (2010) A simple approach for predicting protein–protein interactions. Current Protein & Peptide Science (In Press).</ref> | ||
*DomPrint: Domprint is a domain-domain interaction (DDI) prediction server. | *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. | *MycoPrint: MycoPrint is a web interface for exploration of the interactome of ''Mycobacterium tuberculosis ''H37Rv (Mtb) predicted by "Domain Interaction Mapping" (DIM) method. | ||
*ATPint: A server for predicting [[Adenosine triphosphate|ATP]] interacting residues in proteins.<ref>{{cite journal |last1=Chauhan |first1=JS |last2=Mishra |first2=NK |last3=Raghava |first3=GP |title=Identification of ATP binding residues of a protein from its primary sequence |journal=BMC Bioinformatics |volume=10 |pages=434 |year=2009 |pmid=20021687 |pmc=2803200 |doi=10.1186/1471-2105-10-434}}</ref> | *ATPint: A server for predicting [[Adenosine triphosphate|ATP]] interacting residues in proteins.<ref>{{cite journal |last1=Chauhan |first1=JS |last2=Mishra |first2=NK |last3=Raghava |first3=GP |title=Identification of ATP binding residues of a protein from its primary sequence |journal=BMC Bioinformatics |volume=10 |pages=434 |year=2009 |pmid=20021687 |pmc=2803200 |doi=10.1186/1471-2105-10-434}}</ref> | ||
*FADpred: Identification of [[Flavin adenine dinucleotide|FAD]] interacting residues in proteins.<ref>{{cite journal |last1=Mishra |first1=Nitish K. |last2=Raghava |first2=Gajendra P. S. |title=Prediction of FAD interacting residues in a protein from its primary sequence using evolutionary information |journal=BMC Bioinformatics |volume=11 |pages=S48 |year=2010 |pmid=20122222 |doi=10.1186/1471-2105-11-S1-S48 |pmc=3009520}}</ref> | *FADpred: Identification of [[Flavin adenine dinucleotide|FAD]] interacting residues in proteins.<ref>{{cite journal |last1=Mishra |first1=Nitish K. |last2=Raghava |first2=Gajendra P. S. |title=Prediction of FAD interacting residues in a protein from its primary sequence using evolutionary information |journal=BMC Bioinformatics |volume=11 |pages=S48 |year=2010 |issue=Suppl 1 |pmid=20122222 |doi=10.1186/1471-2105-11-S1-S48 |pmc=3009520}}</ref> | ||
*GTPbinder: Prediction of protein [[Guanosine triphosphate|GTP]] interacting residues.<ref>{{cite journal |last1=Chauhan |first1=JS |last2=Mishra |first2=NK |last3=Raghava |first3=GP |title=Prediction of GTP interacting residues, dipeptides and tripeptides in a protein from its evolutionary information |journal=BMC Bioinformatics |volume=11 |pages=301 |year=2010 |pmid=20525281 |doi=10.1186/1471-2105-11-301 |pmc=3098072}}</ref> | *GTPbinder: Prediction of protein [[Guanosine triphosphate|GTP]] interacting residues.<ref>{{cite journal |last1=Chauhan |first1=JS |last2=Mishra |first2=NK |last3=Raghava |first3=GP |title=Prediction of GTP interacting residues, dipeptides and tripeptides in a protein from its evolutionary information |journal=BMC Bioinformatics |volume=11 |pages=301 |year=2010 |pmid=20525281 |doi=10.1186/1471-2105-11-301 |pmc=3098072}}</ref> | ||
*NADbinder: Prediction of NAD binding residues in proteins.<ref>{{cite journal |last1=Ansari |first1=HR |last2=Raghava |first2=GP |title=Identification of NAD interacting residues in proteins |journal=BMC Bioinformatics |volume=11 |pages=160 |year=2010 |pmid=20353553 |pmc=2853471 |doi=10.1186/1471-2105-11-160}}</ref> | *NADbinder: Prediction of NAD binding residues in proteins.<ref>{{cite journal |last1=Ansari |first1=HR |last2=Raghava |first2=GP |title=Identification of NAD interacting residues in proteins |journal=BMC Bioinformatics |volume=11 |pages=160 |year=2010 |pmid=20353553 |pmc=2853471 |doi=10.1186/1471-2105-11-160}}</ref> | ||
*PreMier: Designing of Mutants of Antibacterial Peptides.<ref>{{cite journal |last1=Agarwal |title=Identification of Mannose Interacting Residues Using Local Composition |journal= | *PreMier: Designing of Mutants of Antibacterial Peptides.<ref>{{cite journal |last1=Agarwal |title=Identification of Mannose Interacting Residues Using Local Composition |journal=PLOS ONE |volume=6 |issue=9 |pages=e24039 |year=2011 |pmid= 21931639|doi=10.1371/journal.pone.0024039|pmc= 3172211|display-authors=etal|bibcode=2011PLoSO...624039A |doi-access=free }} | ||
</ref> | </ref> | ||
*DMAP: DMAP: Designing of Mutants of Antibacterial Peptides | *DMAP: DMAP: Designing of Mutants of Antibacterial Peptides | ||
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*CBtope: Prediction of Conformational B-cell epitope in a sequence from its amino acid sequence.<ref>{{cite journal | last1=Ansari |first1=HR |last2=Raghava| first2=Gajendra PS|title=Identification of conformational B-cell Epitopes in an antigen from its primary sequence|journal= Immunome Research<!--Springer journal, not the predatory Longdom/OMICS one!-->|volume=6|pages=6|year=2010|doi=10.1186/1745-7580-6-6 | pmid=20961417 | pmc=2974664}}</ref> | *CBtope: Prediction of Conformational B-cell epitope in a sequence from its amino acid sequence.<ref>{{cite journal | last1=Ansari |first1=HR |last2=Raghava| first2=Gajendra PS|title=Identification of conformational B-cell Epitopes in an antigen from its primary sequence|journal= Immunome Research<!--Springer journal, not the predatory Longdom/OMICS one!-->|volume=6|pages=6|year=2010|doi=10.1186/1745-7580-6-6 | pmid=20961417 | pmc=2974664}}</ref> | ||
*DesiRM: Designing of Complementary and Mismatch siRNAs for Silencing a Gene .<ref>{{cite journal | last1=Ahmed |first1=F |last2=Raghava| first2=Gajendra PS|title=Designing of Highly Effective Complementary and Mismatch siRNAs for Silencing a Gene | *DesiRM: Designing of Complementary and Mismatch siRNAs for Silencing a Gene .<ref>{{cite journal | last1=Ahmed |first1=F |last2=Raghava| first2=Gajendra PS|title=Designing of Highly Effective Complementary and Mismatch siRNAs for Silencing a Gene | ||
|journal= | |journal=PLOS ONE|volume=6|pages=e23443|year=2011|doi=10.1371/journal.pone.0023443 | pmid=21853133| pmc=3154470 | issue=8|bibcode=2011PLoSO...623443A |doi-access=free }} | ||
</ref> | </ref> | ||
*GenomeABC: A server for Benchmarking of Genome Assemblers. | *GenomeABC: A server for Benchmarking of Genome Assemblers. | ||