Protein ligands

2P2IdbBasse M.-J., Betzi S., Morelli X., Roche P., 2P2Idb v2: update of a structural database dedicated to orthosteric modulation of protein–protein interactions. Database, 2016, Article No baw007. Abstract
AffinDBBlock P., Sotriffer C. A., Dramburg I., Klebe G., AffinDB: a freely accessible database of affinities for protein–ligand complexes from the PDB. Nucleic Acids Research, 2006, 34, D522-D526. Abstract
ASDHuang Z., Zhu L., Cao Y., Wu G., Liu X., Chen Y., Wang Q., Shi T., Zhao Y., Wang Y., Li W., Li Y., Chen H., Chen G., Zhang J., ASD: a comprehensive database of allosteric proteins and modulators. Nucleic Acids Research, 2011, 39, D663–D669. Abstract
BATMAN-TCMKong X., Liu C., Zhang Z., Cheng M., Mei Z., Li X., Liu P., Diao L., Ma Y., Jiang P., Kong X., Nie S., Guo Y., Wang Z., Zhang X., Wang Y., Tang L., Guo S., Liu Z., Li D., BATMAN-TCM 2.0: an enhanced integrative database for known and predicted interactions between traditional Chinese medicine ingredients and target proteins. Nucleic Acids Research, 2024, 52, D1110–D1120. Abstract
Binding DBGilson M. K., Liu T., Baitaluk M., Nicola G., Hwang L., Chong J., BindingDB in 2015: A public database for medicinal chemistry, computational chemistry and systems pharmacology. Nucleic Acids Research, 2016, 44, D1045–D1053. Abstract
BioLiPZhang C., Zhang X., Freddolino P. L., Zhang Y., BioLiP2: an updated structure database for biologically relevant ligand–protein interactions. Nucleic Acids Research, 2024, 52, D404–D412. Abstract
cBinderDBDu J., Yan X., Liu Z., Cui L., Ding P., Tan X., Li X., Zhou H., Gu Q., Xu J., cBinderDB: a covalent binding agent database. Bioinformatics, 2017, 33, 1258-1260. Abstract
ChemBioPortLiu L., Rovers E., Schapira M., ChemBioPort: an online portal to navigate the structure, function and chemical inhibition of the human proteome. Database, 2022, Article No baac088. Abstract
Chemical Probes PortalAntolin A. A., Sanfelice D., Crisp A., Villasclaras Fernandez E., Mica I. L., Chen Y., Collins I., Edwards A., Müller S., Al-Lazikani B., Workman P., The Chemical Probes Portal: an expert review-based public resource to empower chemical probe assessment, selection and use. Nucleic Acids Research, 2023, 51, D1492–D1502. Abstract
ChemProtKringelum J., Kjaerulff S. K., Brunak S., Lund O., Oprea T. I., Taboureau T., ChemProt-3.0: a global chemical biology diseases mapping. Database, 2016, Article No bav123. Abstract
CLiBEChen X., Ji Z. L., Zhi D. G., Chen Y. Z., CLiBE: A database of computed ligand binding energy for ligand-receptor complexes and its potential use in the analysis of drug binding competitiveness. Computers & Chemistry, 2002, 26, 661-666. Abstract
ConsensusPathDBKamburov A., Stelzl U., Lehrach H., Herwig R., The ConsensusPathDB interaction database: 2013 update. Nucleic Acids Research, 2013, 41, D793-D800. Abstract
CovalentInDBDu H., Gao J., Weng G., Ding J., Chai X., Pang J., Kang Y., Li D., Cao D., Hou T., CovalentInDB: a comprehensive database facilitating the discovery of covalent inhibitors. Nucleic Acids Research, 2021, 49, D1122–D1129. Abstract
CovPDBGao M., Moumbock A. F. A., Qaseem A., Xu Q., Günther S., CovPDB: a high-resolution coverage of the covalent protein–ligand interactome. Nucleic Acids Research, 2022, 50, D445–D450. Abstract
CREDOSchreyer A., Blundell T., CREDO: A protein–ligand interaction database for drug discovery. Chemical Biology & Drug Design, 2009, 73, 157-167 Abstract
CysteinomeWu S., Luo (Howard) H., Wang H., Zhao W., Hu Q., Yang Y., Cysteinome: The first comprehensive database for proteins with targetable cysteine and their covalent inhibitors. Biochemical and Biophysical Research Communications, 2016, 478, 1268-1273. Abstract
DockNMineGheyouche E., Launay R., Lethiec J., Labeeuw A., Roze C., Amossé A., Téletchéa S., DockNmine, a web portal to assemble and analyse virtual and experimental interaction data. International Journal of Molecular Sciences, 2019, 20, Article No 5062. Abstract
Drug2GeneRoider H. G., Pavlova N., Kirov I., Slavov S., Slavov T., Uzunov Z., Weiss B., Drug2Gene: an exhaustive resource to explore effectively the drug-target relation network. BMC Bioinformatics, 2014, 15, Article No 68. Abstract
DrugPortProvider: European Bioinformatics Institute
Drug Target CommonsTanoli Z. R., Alam Z., Vähä-Koskela M., Ravikumar B., Malyutina A., Jaiswal A., Tang J., Wennerberg K., Aittokallio T., Drug Target Commons 2.0: a community platform for systematic analysis of drug–target interaction profiles. Database, 2018, Article No bay083. Abstract
DrumPIDKunz M., Liang C., Nilla S., Cecil A., Dandekar T.,The drug-minded protein interaction database (DrumPID) for efficient target analysis and drug development. Database, 2016, Article No baw041. Abstract
EGFRIndbYadav I. S., Singh H., Khan I., Chaudhury A., Raghava G. P. S., Agarwal S. M., EGFRIndb: Epidermal Growth Factor Receptor Inhibitor Database. Anti-Cancer Agents in Medicinal Chemistry, 2014, 14, 928-935. Abstract
EpiDBaseLoharch S., Bhutani I., Jain K., Gupta P., Sahoo D. K., Parkesh R., EpiDBase: a manually curated database for small molecule modulators of epigenetic landscape. Database, 2015, Article No bav013. Abstract
ExCAPE-DBSun J., Jeliazkova N., Chupakin V., Golib-Dzib J.-F., Engkvist O., Carlsson L., Wegner J., Ceulemans H., Georgiev I., Jeliazkov V., Kochev N., Ashby T. J., Chen H., ExCAPE-DB: an integrated large scale dataset facilitating Big Data analysis in chemogenomics. Journal of Cheminformatics, 2017, 9, Article No 17. Abstract
FGDBToti D., Macari G., Barbierato E., Polticelli F., FGDB: a comprehensive graph database of ligand fragments from the Protein Data Bank. Database, 2022, Article No baac044. Abstract
FireDBMaietta P., Lopez G., Carro A., Pingilley B. J., Leon L. G., Valencia A., Tress M. L., FireDB: a compendium of biological and pharmacologically relevant ligands. Nucleic Acids Research, 2014, 42, D267–D272. Abstract
GLIDAOkuno Y., Tamon A., Yabuuchi H., Niijima S., Minowa Y., Tonomura K., Kunimoto R., Feng C., GLIDA: GPCR—ligand database for chemical genomics drug discovery—database and tools update. Nucleic Acids Research, 2008, 36, D907-D912. Abstract
GPCRdbPándy-Szekeres G., Caroli J., Mamyrbekov A., Kermani A. A., Keserű G. M., Kooistra A. J., Gloriam D. E., GPCRdb in 2023: state-specific structure models using AlphaFold2 and new ligand resources. Nucleic Acids Research, 2023, 51, D395–D402. Abstract
HDACiDBMurugan K., Sangeetha S., Ranjitha S., Vimala A., Al-Sohaibani S., Rameshkumar G., HDACiDB: a database for histone deacetylase inhibitors. Drug Design, Development and Therapy, 2015, 9, 2257–2264. Abstract
Hic-UpKleywegt G. J., Henrick K., Dodson E. J., van Aalten D. M. F., Pound-wise but penny-foolish – How well do micromolecules fare in macromolecular refinement? Structure, 2003, 11, 1051-1059. Request
HITYan D., Zheng G., Wang C., Chen Z., Mao T., Gao J., Yan Y., Chen X., Ji X., Yu J., Mo S., Wen H., Han W., Zhou M., Wang Y., Wang J., Tang K., Cao Z., HIT 2.0: an enhanced platform for Herbal Ingredients’ Targets. Nucleic Acids Research, 2022, 50, D1238–D1243. Abstract
HProteome-BSiteSim J., Kwon S., Seok C., HProteome-BSite: predicted binding sites and ligands in human 3D proteome. Nucleic Acids Research, 2023, 51, D403–D408. Abstract
HSPMdbSingh P., Unik B., Puri A., Nagpal G., Singh B., Gautam A., Sharma D., HSPMdb: a computational repository of heat shock protein modulators. Database, 2020, Article No baaa003. Abstract
IMIDBalaji S., Mcclendon C., Chowdhary R., Liu J. S., Zhang J., IMID: integrated molecular interaction database. Bioinformatics, 2012, 28, 747-749. Abstract
iPPI-DBLabbé C. M., Kuenemann M., Zarzycka B., Vriend G., Nicolaes G. A. F., Lagorce D., Miteva M. A., Villoutreix B. O., Sperandio O., iPPI-DB: an online database of modulators of protein–protein interactions. Nucleic Acids Research, 2016, 44, D542–D547. Abstract
Ki DatabaseRoth B. L., Lopez E., Patel S., Kroeze W. L., The multiplicity of serotonin receptors: uselessly diverse molecules or an embarrassment of riches? Neuroscientist, 2000, 6, 252-262. Abstract
KOFFINorval L. W., Krämer S. D., Gao M., Herz T., Li J., Rath C., Wöhrle J., Günther S., Roth G., KOFFI and Anabel 2.0-a new binding kinetics database and its integration in an open-source binding analysis software. Database, 2019, Article No baz101. Abstract
LabWorm Receptor LigandsAuthors: Yoav Bauman, Roy Granit, Alon Vitenshtein
LIGANDGoto S., Okuno Y., Hattori M., Nishioka T., Kanehisa M., LIGAND: Database of chemical compounds and reactions in biological pathways. Nucleic Acids Research, 2002, 30, 402-404. Abstract
Ligand ExpoFeng Z., Chen L., Maddula H., Akcan O., Oughtred R., Berman H. M., Westbrook J., Ligand Depot: a data warehouse for ligands bound to macromolecules. Bioinformatics, 2004, 20, 2153–2155. Abstract
MATADORGünther S., Kuhn M., Dunkel M., Campillos M., Senger C., Petsalaki E., Ahmed J., Garcia Urdiales E., Gewiess A, Juhl Jensen L., Schneider R., Skoblo R., Russell R. B., Bourne P. E., Bork P., Preissner R., SuperTarget and Matador: resources for exploring drug-target relationships. Nucleic Acids Research, 2008, 36, D919–D922. Abstract
MetrabaseMak L., Marcus D., Howlett1 A., Yarova G., Duchateau G., Klaffke W., Bender A., Glen R. C., Metrabase: a cheminformatics and bioinformatics database for small molecule transporter data analysis and (Q)SAR modeling. Journal of Cheminformatics, 2015, 7, Article No 31. Abstract
Molecular Libraries ProgramPublications
MTLDChen C., Wu M., Cen S., Wu J., Zhou J., MTLD, a Database of Multiple Target Ligands, the updated version. Molecules, 2017, 22, Article No 1375. Abstract
NRLiSt BDBLagarde N., Ben Nasr N., Jérémie A., Guillemain H., Laville V., Labib T., Zagury J.-F., Montes M., NRLiSt BDB, the manually curated nuclear receptors ligands and structures benchmarking database. Journal of Medicinal Chemistry, 2014, 57, 3117–3125. Abstract
PathGuideBader G. D., Cary M. P., Sander C., Pathguide: a pathway resource list. Nucleic Acids Research, 2006, 34, D504-D506. Abstract
PDBeChemProvider: European Bioinformatics Institute
PHAROSNguyen D.-T., Mathias S., Bologa C., Brunak S., Fernandez N., Gaulton A., Hersey A., Holmes J., Jensen L. J., Karlsson A., Liu G., Ma’ayan A., Mandava G., Mani S., Mehta S., Overington J., Patel J., Rouillard A. D., Schürer S., Sheils T., Simeonov A., Sklar L. A., Southall N., Ursu O., Vidovic D., Waller A., Yang J., Jadhav A., Oprea T. I., Guha R., Pharos: Collating protein information to shed light on the druggable genome. Nucleic Acids Research, 2017, 45, D995-D1002. Abstract
PLBDLingė D., Gedgaudas M., Merkys A., Petrauskas V., Vaitkus A., Grybauskas A., Paketurytė V., Zubrienė A., Zakšauskas A., Mickevicǐūtė A., Smirnovienė J., Baranauskienė L., Čapkauskaitė E., Dudutienė V., Urniezǐus E., Konovalovas A., Kazlauskas E., Shubin K., Schiöth H. P., Chen W.-Y., Ladbury J. E., Grazǔlis S., Matulis D., PLBD: protein–ligand binding database of thermodynamic and kinetic intrinsic parameters. Database, 2023, Article No baad040. Abstract
PLICAnand P., Nagarajan D., Mukherjee S., Chandra N., PLIC: protein–ligand interaction clusters. Database, 2014, Article No bau029. Abstract
PMI-DBZhao T., Liu J., Zeng X., Wang W., Li S., Zang T., Peng J., Yang Y., Prediction and collection of protein–metabolite interactions. Briefings in Bioinformatics, 2021, 22, Article No bbab014. Abstract
PoSSuMdsIto J., Ikeda K., Yamada K., Mizuguchi K., Tomii K., PoSSuM v.2.0: data update and a new function for investigating ligand analogs and target proteins of small-molecule drugs. Nucleic Acids Research, 2015, 43, D392-D398. Abstract
PPDMsKruger F. A., Gaulton A., Nowotka M., Overington J. P., PPDMs—a resource for mapping small molecule bioactivities from ChEMBL to Pfam-A protein domains. Bioinformatics, 2015, 31, 776-778. Abstract
PrePCITrudeau S. J., Hwang H., Mathur D., Begum K., Petrey D., Murray D., Honig B., PrePCI: A structure- and chemical similarity-informed database of predicted protein compound interactions. Protein Science, 2023, 32, Article No e4594. Abstract
ProBiS-Dock DatabaseKonc J., Lešnik S., Škrlj B., Janežič D., 2021, ProBiS-Dock Database: A web server and interactive web repository of small ligand–protein binding sites for drug design. Journal of Chemical Information and Modeling, 2021, 61, 4097–4107. Abstract
ProtChemSIKalinina O. V., Wichmann O., Apic G., Russell R. B., ProtChemSI: a network of protein–chemical structural interactions. Nucleic Acids Research, 2012, 40, D549–D553. Abstract
PTSDing P., Yan X., Liu z., Du J., Du Y., Lu Y., Wu D., Xu Y., Zhou H., Gu Q., Xu J., PTS: a pharmaceutical target seeker. Database, 2017, Article No bax095. Abstract
S2RSLDBNastasi G., Miceli C., Pittalà V., Modica M. N., Prezzavento O., Romeo G., Rescifina A., Marrazzo A., Amata E., S2RSLDB: a comprehensive manually curated, internet-accessible database of the sigma-2 receptor selective ligands. Journal of Cheminformatics, 2017, 9, Article No 3. Abstract
sc-PDB-FragDesaphy J., Rognan D., sc-PDB-Frag: a database of protein–ligand interaction patterns for bioisosteric replacements. Journal of Chemical Information and Modeling, 2014, 54, 1908–1918. Abstract
SMMDBMishra S. K., Jain N., Shankar U., Tawani A., Mishra A., Kumar A., SMMDB: a web-accessible database for small molecule modulators and their targets involved in neurological diseases. Database, 2018, Article No bay082. Abstract
STITCHSzklarczyk D., Santos A., von Mering C., Jensen L. J., Bork P., Kuhn M., STITCH 5: augmenting protein–chemical interaction networks with tissue and affinity data. Nucleic Acids Research, 2016, 44, D380–D384. Abstract
SuperLigandsMichalsky E., Dunkel M., Goede A., Preissner R., SuperLigands – a database of ligand structures derived from the Protein Data Bank. BMC Bioinformatics, 2005, 6, Article No 122. Abstract
SuperTargetHecker N., Ahmed J., von Eichborn J., Dunkel M., Macha K., Eckert A., Gilson M. K., Bourne P. E., Preissner R., SuperTarget goes quantitative: update on drug–target interactions.  Nucleic Acids Research, 2012, 40, D1113-D1117. Abstract
SwissBioisostereCuozzo A., Daina A., Perez M. A. S., Michielin O., Zoete V., SwissBioisostere 2021: updated structural, bioactivity and physicochemical data delivered by a reshaped web interface. Nucleic Acids Research, 2022, 50, D1382–D1390. Abstract
SynPharmIreland S. M., Southan C., Dominguez-Monedero A., Harding S. D., Sharman J. L., Davies J. A., SynPharm: A Guide to PHARMACOLOGY database tool for designing drug control into engineered proteins. ACS Omega, 2018, 3, 7993-8002. Abstract
T-ARDISGalletti C., Bota P. M., Oliva B., Fernandez-Fuentes N., Mining drug–target and drug–adverse drug reaction databases to identify target–adverse drug reaction relationships. Database, 2021, Article No baab068. Abstract
TIBLEMalhotra S., Mugumbate G., Blundell T. L., Higueruelo A. P., TIBLE: a web-based, freely accessible resource for small-molecule binding data for mycobacterial species. Database, 2017, Article No bax041. Abstract
TIMBALHigueruelo A. P., Jubb H., Blundell T. L., TIMBAL v2: update of a database holding small molecules modulating protein–protein interactions. Database, 2013, Article No bat039. Abstract
ValidatorDBSehnal D., Svobodová Văreková R., Pravda L., Ionescu C.-M., Geidl S., Horský V., Jaiswal D., Wimmerová M., Kŏca J., ValidatorDB: database of up-to-date validation results for ligands and non-standard residues from the Protein Data Bank. Nucleic Acids Research, 2015, 43, D369-D375. Abstract
YeastpmiLuzarowski M., Vicente R., Kiselev A., Wagner M., Schlossarek D., Erban A., Perez de Souza L., Childs D., Wojciechowska I., Luzarowska U., Górka M., Sokołowska E. M., Kosmacz M., Moreno J. C., Brzezińska A., Vegesna B., Kopka J., Fernie A. R., Willmitzer L., Ewald J. C., Skirycz A., Global mapping of protein–metabolite interactions in Saccharomyces cerevisiae reveals that Ser-Leu dipeptide regulates phosphoglycerate kinase activity. Communications Biology, 2021, 4, 181. Abstract

Last Updated on 06-02-2024 by Piotr Minkiewicz