J Chem Inf Model - Identification of 1,2,5-oxadiazoles as a new class of SENP2 inhibitors using structure based virtual screening.

Tópicos

{ compound(1573) activ(1297) structur(1058) }
{ bind(1733) structur(1185) ligand(1036) }
{ result(1111) use(1088) new(759) }
{ howev(809) still(633) remain(590) }
{ clinic(1479) use(1117) guidelin(835) }
{ can(981) present(881) function(850) }
{ activ(1452) weight(1219) physic(1104) }
{ extract(1171) text(1153) clinic(932) }
{ perform(999) metric(946) measur(919) }
{ import(1318) role(1303) understand(862) }
{ system(1976) rule(880) can(841) }
{ take(945) account(800) differ(722) }
{ method(984) reconstruct(947) comput(926) }
{ risk(3053) factor(974) diseas(938) }
{ state(1844) use(1261) util(961) }
{ high(1669) rate(1365) level(1280) }
{ use(1733) differ(960) four(931) }
{ detect(2391) sensit(1101) algorithm(908) }
{ can(774) often(719) complex(702) }
{ data(1737) use(1416) pattern(1282) }
{ measur(2081) correl(1212) valu(896) }
{ sequenc(1873) structur(1644) protein(1328) }
{ patient(2315) diseas(1263) diabet(1191) }
{ studi(2440) review(1878) systemat(933) }
{ problem(2511) optim(1539) algorithm(950) }
{ research(1085) discuss(1038) issu(1018) }
{ visual(1396) interact(850) tool(830) }
{ spatial(1525) area(1432) region(1030) }
{ health(3367) inform(1360) care(1135) }
{ signal(2180) analysi(812) frequenc(800) }
{ analysi(2126) use(1163) compon(1037) }
{ process(1125) use(805) approach(778) }
{ model(3404) distribut(989) bayesian(671) }
{ imag(1947) propos(1133) code(1026) }
{ inform(2794) health(2639) internet(1427) }
{ imag(1057) registr(996) error(939) }
{ method(1219) similar(1157) match(930) }
{ featur(3375) classif(2383) classifi(1994) }
{ imag(2830) propos(1344) filter(1198) }
{ network(2748) neural(1063) input(814) }
{ imag(2675) segment(2577) method(1081) }
{ motion(1329) object(1292) video(1091) }
{ assess(1506) score(1403) qualiti(1306) }
{ treatment(1704) effect(941) patient(846) }
{ surgeri(1148) surgic(1085) robot(1054) }
{ framework(1458) process(801) describ(734) }
{ error(1145) method(1030) estim(1020) }
{ chang(1828) time(1643) increas(1301) }
{ learn(2355) train(1041) set(1003) }
{ concept(1167) ontolog(924) domain(897) }
{ algorithm(1844) comput(1787) effici(935) }
{ method(1557) propos(1049) approach(1037) }
{ data(1714) softwar(1251) tool(1186) }
{ design(1359) user(1324) use(1319) }
{ control(1307) perform(991) simul(935) }
{ model(2220) cell(1177) simul(1124) }
{ care(1570) inform(1187) nurs(1089) }
{ general(901) number(790) one(736) }
{ search(2224) databas(1162) retriev(909) }
{ featur(1941) imag(1645) propos(1176) }
{ case(1353) use(1143) diagnosi(1136) }
{ data(3963) clinic(1234) research(1004) }
{ studi(1410) differ(1259) use(1210) }
{ system(1050) medic(1026) inform(1018) }
{ model(2341) predict(2261) use(1141) }
{ perform(1367) use(1326) method(1137) }
{ studi(1119) effect(1106) posit(819) }
{ blood(1257) pressur(1144) flow(957) }
{ record(1888) medic(1808) patient(1693) }
{ model(3480) simul(1196) paramet(876) }
{ monitor(1329) mobil(1314) devic(1160) }
{ ehr(2073) health(1662) electron(1139) }
{ research(1218) medic(880) student(794) }
{ patient(2837) hospit(1953) medic(668) }
{ model(2656) set(1616) predict(1553) }
{ data(2317) use(1299) case(1017) }
{ age(1611) year(1155) adult(843) }
{ medic(1828) order(1363) alert(1069) }
{ cost(1906) reduc(1198) effect(832) }
{ group(2977) signific(1463) compar(1072) }
{ sampl(1606) size(1419) use(1276) }
{ gene(2352) biolog(1181) express(1162) }
{ data(3008) multipl(1320) sourc(1022) }
{ first(2504) two(1366) second(1323) }
{ intervent(3218) particip(2042) group(1664) }
{ activ(1138) subject(705) human(624) }
{ time(1939) patient(1703) rate(768) }
{ patient(1821) servic(1111) care(1106) }
{ use(2086) technolog(871) perceiv(783) }
{ health(1844) social(1437) communiti(874) }
{ structur(1116) can(940) graph(676) }
{ cancer(2502) breast(956) screen(824) }
{ use(976) code(926) identifi(902) }
{ drug(1928) target(777) effect(648) }
{ implement(1333) system(1263) develop(1122) }
{ survey(1388) particip(1329) question(1065) }
{ estim(2440) model(1874) function(577) }
{ decis(3086) make(1611) patient(1517) }
{ method(1969) cluster(1462) data(1082) }
{ method(2212) result(1239) propos(1039) }

Resumo

Small ubiquitin like modifier (SUMO) specific proteases (SENPs) are cysteine proteases that carry out the proteolytic processing of SUMO from its pro form as well as the deconjugation of SUMO from substrate proteins. SENPs are attractive targets for drug discovery due to their crucial role in the development of various diseases. However, the SENPs inhibitor discovery efforts were limited, and only a few inhibitors or activity based probes have been identified until now. Here, we report a new class of SENP2 inhibitors identified by a combination of structure based virtual screening and quantitative FRET based assay. Our virtual screening protocol initially involves the identification of small molecules that have similar shape and electrostatic properties with the conjugate of SUMO1 C-terminal residues and substrate lysine. Molecular docking was then used to prioritize these small molecules for a FRET based assay that quantifies their SENP2 endopeptidase activity. The initial round of virtual screening followed by FRET based assay has enabled the identification of eight compounds with >40% SENP2 inhibition at 30 ?M compound concentration. Five of these compounds belong to two scaffolds containing a 1,2,5-oxadiazole core that represent a novel class of SENP2 inhibitors. To improve the inhibitory potency and explore the structure-activity relationship of these two 1,2,5-oxadiazole scaffolds, structurally related compounds were identified in another round of virtual screening. The biological assay results confirmed SENP2 inhibitory activity of these two scaffolds. The most potent compound of each scaffold showed an IC50 of 5.9 and 3.7 ?M. Most of the compounds also inhibited closely related isoform SENP1, while no detectable inhibition on other proteases, such as papain and trypsin, was observed. Our study suggests that 1,2,5-oxadiazoles could be used as a starting point for the development of novel therapeutic agents against various diseases targeting SENPs.

Resumo Limpo

small ubiquitin like modifi sumo specif proteas senp cystein proteas carri proteolyt process sumo pro form well deconjug sumo substrat protein senp attract target drug discoveri due crucial role develop various diseas howev senp inhibitor discoveri effort limit inhibitor activ base probe identifi now report new class senp inhibitor identifi combin structur base virtual screen quantit fret base assay virtual screen protocol initi involv identif small molecul similar shape electrostat properti conjug sumo ctermin residu substrat lysin molecular dock use priorit small molecul fret base assay quantifi senp endopeptidas activ initi round virtual screen follow fret base assay enabl identif eight compound senp inhibit m compound concentr five compound belong two scaffold contain oxadiazol core repres novel class senp inhibitor improv inhibitori potenc explor structureact relationship two oxadiazol scaffold structur relat compound identifi anoth round virtual screen biolog assay result confirm senp inhibitori activ two scaffold potent compound scaffold show ic m compound also inhibit close relat isoform senp detect inhibit proteas papain trypsin observ studi suggest oxadiazol use start point develop novel therapeut agent various diseas target senp

Resumos Similares

J Chem Inf Model - Automated recycling of chemistry for virtual screening and library design. ( 0,9614045106763 )
J Chem Inf Model - Locating sweet spots for screening hits and evaluating pan-assay interference filters from the performance analysis of two lead-like libraries. ( 0,955803012094386 )
J Chem Inf Model - Polypharmacology directed compound data mining: identification of promiscuous chemotypes with different activity profiles and comparison to approved drugs. ( 0,953950869176755 )
J Chem Inf Model - TIN-a combinatorial compound collection of synthetically feasible multicomponent synthesis products. ( 0,945340001112577 )
J Chem Inf Model - Identification of novel liver X receptor activators by structure-based modeling. ( 0,940646545145515 )
J Chem Inf Model - G-protein coupled receptors virtual screening using genetic algorithm focused chemical space. ( 0,938912255430584 )
J Chem Inf Model - Increasing the coverage of medicinal chemistry-relevant space in commercial fragments screening. ( 0,93276208017993 )
Curr Comput Aided Drug Des - Development of Chemical Compound Libraries for In Silico Drug Screening. ( 0,932229599218406 )
J Chem Inf Model - Identification of a new class of FtsZ inhibitors by structure-based design and in vitro screening. ( 0,931356075149442 )
J Chem Inf Model - Combining horizontal and vertical substructure relationships in scaffold hierarchies for activity prediction. ( 0,930322384675904 )
J Chem Inf Model - Identification of a novel inhibitor of dengue virus protease through use of a virtual screening drug discovery Web portal. ( 0,930159098963646 )
J Chem Inf Model - From activity cliffs to activity ridges: informative data structures for SAR analysis. ( 0,928507243461973 )
J Chem Inf Model - In silico enzymatic synthesis of a 400,000 compound biochemical database for nontargeted metabolomics. ( 0,927872345019389 )
J Chem Inf Model - Selection of in silico drug screening results for G-protein-coupled receptors by using universal active probes. ( 0,927213600169528 )
J Chem Inf Model - De novo design of drug-like molecules by a fragment-based molecular evolutionary approach. ( 0,925497109677207 )
J Chem Inf Model - Ligand- and structure-based virtual screening for clathrodin-derived human voltage-gated sodium channel modulators. ( 0,92384155568636 )
J Chem Inf Model - Natural product-like virtual libraries: recursive atom-based enumeration. ( 0,923779548912266 )
J Chem Inf Model - Identifying compound-target associations by combining bioactivity profile similarity search and public databases mining. ( 0,922080777219376 )
J Chem Inf Model - Mining the ChEMBL database: an efficient chemoinformatics workflow for assembling an ion channel-focused screening library. ( 0,921430554037448 )
J Chem Inf Model - Identification of sumoylation activating enzyme 1 inhibitors by structure-based virtual screening. ( 0,920488945782209 )
J Chem Inf Model - Identification of multitarget activity ridges in high-dimensional bioactivity spaces. ( 0,920295127546387 )
J Chem Inf Model - Identification of novel serotonin transporter compounds by virtual screening. ( 0,920281497487571 )
J Chem Inf Model - Discovery of a7-nicotinic receptor ligands by virtual screening of the chemical universe database GDB-13. ( 0,91950695344683 )
J Chem Inf Model - Compound set enrichment: a novel approach to analysis of primary HTS data. ( 0,918974417558638 )
J Chem Inf Model - Conditional probabilistic analysis for prediction of the activity landscape and relative compound activities. ( 0,916782706043969 )
J Chem Inf Model - Identification of novel malarial cysteine protease inhibitors using structure-based virtual screening of a focused cysteine protease inhibitor library. ( 0,915562992327179 )
J Chem Inf Model - Target-independent prediction of drug synergies using only drug lipophilicity. ( 0,915498117690912 )
J Chem Inf Model - Compound optimization through data set-dependent chemical transformations. ( 0,915397672684704 )
J Chem Inf Model - Novel method for pharmacophore analysis by examining the joint pharmacophore space. ( 0,914015820632716 )
J Chem Inf Model - QSAR classification model for antibacterial compounds and its use in virtual screening. ( 0,913545147386759 )
J Chem Inf Model - Application of computer-aided drug repurposing in the search of new cruzipain inhibitors: discovery of amiodarone and bromocriptine inhibitory effects. ( 0,91322013567678 )
J Chem Inf Model - Visualization and virtual screening of the chemical universe database GDB-17. ( 0,91174596838221 )
J Chem Inf Model - Novel mycosin protease MycP1 inhibitors identified by virtual screening and 4D fingerprints. ( 0,911619200161136 )
J Chem Inf Model - How diverse are diversity assessment methods? A comparative analysis and benchmarking of molecular descriptor space. ( 0,911552444007213 )
J Chem Inf Model - Introduction of target cliffs as a concept to identify and describe complex molecular selectivity patterns. ( 0,909932641864774 )
J Chem Inf Model - Enrichment of chemical libraries docked to protein conformational ensembles and application to aldehyde dehydrogenase 2. ( 0,908406902101444 )
J Chem Inf Model - Capturing structure-activity relationships from chemogenomic spaces. ( 0,907131981897025 )
J Chem Inf Model - Prediction of new bioactive molecules using a Bayesian belief network. ( 0,906594736030275 )
J Chem Inf Model - Enumeration of 166 billion organic small molecules in the chemical universe database GDB-17. ( 0,906394073574578 )
J Chem Inf Model - Searching for recursively defined generic chemical patterns in nonenumerated fragment spaces. ( 0,905303934696009 )
J Chem Inf Model - Automatic tailoring and transplanting: a practical method that makes virtual screening more useful. ( 0,900308350332119 )
J Chem Inf Model - Visual characterization and diversity quantification of chemical libraries: 1. creation of delimited reference chemical subspaces. ( 0,90015400192098 )
J Chem Inf Model - Discovery and design of tricyclic scaffolds as protein kinase CK2 (CK2) inhibitors through a combination of shape-based virtual screening and structure-based molecular modification. ( 0,899356281379979 )
J Chem Inf Model - Discovery of new selective human aldose reductase inhibitors through virtual screening multiple binding pocket conformations. ( 0,899236545165728 )
J Chem Inf Model - SABRE: ligand/structure-based virtual screening approach using consensus molecular-shape pattern recognition. ( 0,899048345576204 )
J Chem Inf Model - Navigating high-dimensional activity landscapes: design and application of the ligand-target differentiation map. ( 0,898976715744819 )
J Chem Inf Model - Scaffold diversity of exemplified medicinal chemistry space. ( 0,898499768815959 )
J Chem Inf Model - Prediction of individual compounds forming activity cliffs using emerging chemical patterns. ( 0,89554854550505 )
J Chem Inf Model - Virtual screening yields inhibitors of novel antifungal drug target, benzoate 4-monooxygenase. ( 0,894912299137342 )
J Chem Inf Model - Extending the activity cliff concept: structural categorization of activity cliffs and systematic identification of different types of cliffs in the ChEMBL database. ( 0,893999351761638 )
J Chem Inf Model - Molecular topology analysis of the differences between drugs, clinical candidate compounds, and bioactive molecules. ( 0,892968886021373 )
J Chem Inf Model - Docking ligands into flexible and solvated macromolecules. 7. Impact of protein flexibility and water molecules on docking-based virtual screening accuracy. ( 0,89255134349268 )
J Chem Inf Model - Scaffold-focused virtual screening: prospective application to the discovery of TTK inhibitors. ( 0,890464112193152 )
J Chem Inf Model - Design of multitarget activity landscapes that capture hierarchical activity cliff distributions. ( 0,890321206311612 )
J Chem Inf Model - Similarity boosted quantitative structure-activity relationship--a systematic study of enhancing structural descriptors by molecular similarity. ( 0,888187418200017 )
J Chem Inf Model - Design of a three-dimensional multitarget activity landscape. ( 0,888128375899547 )
J Chem Inf Model - Discovery of novel histamine H4 and serotonin transporter ligands using the topological feature tree descriptor. ( 0,887634801290641 )
J Chem Inf Model - Atom pair 2D-fingerprints perceive 3D-molecular shape and pharmacophores for very fast virtual screening of ZINC and GDB-17. ( 0,88755106227973 )
J Chem Inf Model - Scanning structure-activity relationships with structure-activity similarity and related maps: from consensus activity cliffs to selectivity switches. ( 0,886903868967123 )
J Chem Inf Model - Neighborhood-based prediction of novel active compounds from SAR matrices. ( 0,886739019679307 )
J Chem Inf Model - Fragment-based lead discovery and design. ( 0,883730967039283 )
J Chem Inf Model - FINDSITE(comb): a threading/structure-based, proteomic-scale virtual ligand screening approach. ( 0,88366564785705 )
J Chem Inf Model - Fighting high molecular weight in bioactive molecules with sub-pharmacophore-based virtual screening. ( 0,883655831634585 )
J Chem Inf Model - Identification of compounds with potential antibacterial activity against Mycobacterium through structure-based drug screening. ( 0,883077873085423 )
J Chem Inf Model - Identification of novel potential antibiotics against Staphylococcus using structure-based drug screening targeting dihydrofolate reductase. ( 0,878679837849714 )
J Chem Inf Model - A multivariate chemical similarity approach to search for drugs of potential environmental concern. ( 0,877947396696738 )
J Chem Inf Model - Multitarget structure-activity relationships characterized by activity-difference maps and consensus similarity measure. ( 0,877229839231739 )
J Chem Inf Model - Structure-based design and screen of novel inhibitors for class II 3-hydroxy-3-methylglutaryl coenzyme A reductase from Streptococcus pneumoniae. ( 0,875697331654021 )
J Chem Inf Model - Integrating medicinal chemistry, organic/combinatorial chemistry, and computational chemistry for the discovery of selective estrogen receptor modulators with Forecaster, a novel platform for drug discovery. ( 0,873563925495481 )
J Chem Inf Model - Systematic assessment of compound series with SAR transfer potential. ( 0,873242319457466 )
J Chem Inf Model - Identification of novel S-adenosyl-L-homocysteine hydrolase inhibitors through homology-model-based virtual screening, synthesis, and biological evaluation. ( 0,871763150752697 )
J Chem Inf Model - Virtual fragment screening: discovery of histamine H3 receptor ligands using ligand-based and protein-based molecular fingerprints. ( 0,867805975985002 )
J Chem Inf Model - Characterizing the diversity and biological relevance of the MLPCN assay manifold and screening set. ( 0,867478333883246 )
J Chem Inf Model - Multiple e-pharmacophore modeling, 3D-QSAR, and high-throughput virtual screening of hepatitis C virus NS5B polymerase inhibitors. ( 0,866798204518476 )
J Chem Inf Model - ColBioS-FlavRC: a collection of bioselective flavonoids and related compounds filtered from high-throughput screening outcomes. ( 0,865925597965538 )
J Chem Inf Model - Rationalizing the role of SAR tolerance for ligand-based virtual screening. ( 0,865836968256775 )
J Chem Inf Model - Application of quantitative structure-activity relationship models of 5-HT1A receptor binding to virtual screening identifies novel and potent 5-HT1A ligands. ( 0,865686543172494 )
J Chem Inf Model - Feasibility of using molecular docking-based virtual screening for searching dual target kinase inhibitors. ( 0,863440641391333 )
Sci Data - Quantum chemistry structures and properties of 134 kilo molecules. ( 0,859903351549615 )
J Chem Inf Model - Structural similarity based kriging for quantitative structure activity and property relationship modeling. ( 0,859260088578055 )
J Chem Inf Model - Discovery of novel checkpoint kinase 1 inhibitors by virtual screening based on multiple crystal structures. ( 0,859223124314861 )
J Chem Inf Model - Systematic identification of scaffolds representing compounds active against individual targets and single or multiple target families. ( 0,858986085768596 )
J Chem Inf Model - Molecular modeling of potential anticancer agents from African medicinal plants. ( 0,855955046844413 )
J Chem Inf Model - How do 2D fingerprints detect structurally diverse active compounds? Revealing compound subset-specific fingerprint features through systematic selection. ( 0,854662060043374 )
J Am Med Inform Assoc - Drug repurposing: mining protozoan proteomes for targets of known bioactive compounds. ( 0,854109551303951 )
J Chem Inf Model - Discovery of inhibitors of Schistosoma mansoni HDAC8 by combining homology modeling, virtual screening, and in vitro validation. ( 0,853189254059841 )
J Chem Inf Model - SMIfp (SMILES fingerprint) chemical space for virtual screening and visualization of large databases of organic molecules. ( 0,853184460258092 )
Comput Biol Chem - The optimization of running time for a maximum common substructure-based algorithm and its application in drug design. ( 0,852475348911556 )
J Chem Inf Model - A new protocol for predicting novel GSK-3? ATP competitive inhibitors. ( 0,850369568010289 )
J Chem Inf Model - Computational repositioning and experimental validation of approved drugs for HIF-prolyl hydroxylase inhibition. ( 0,849083542124454 )
J Chem Inf Model - Similarity searching for potent compounds using feature selection. ( 0,848633592500305 )
J Chem Inf Model - Bioturbo similarity searching: combining chemical and biological similarity to discover structurally diverse bioactive molecules. ( 0,848326255555153 )
J Chem Inf Model - Discovery of chemical compound groups with common structures by a network analysis approach (affinity prediction method). ( 0,846475772054284 )
J Chem Inf Model - BioSM: metabolomics tool for identifying endogenous mammalian biochemical structures in chemical structure space. ( 0,845898898783316 )
J Chem Inf Model - Application of support vector machine to three-dimensional shape-based virtual screening using comprehensive three-dimensional molecular shape overlay with known inhibitors. ( 0,845197820121632 )
J Chem Inf Model - Optimization of molecular representativeness. ( 0,844944995313478 )
J Chem Inf Model - A searchable map of PubChem. ( 0,844553872046477 )
J Chem Inf Model - Freely available conformer generation methods: how good are they? ( 0,843898542611794 )
J Chem Inf Model - Automated design of realistic organometallic molecules from fragments. ( 0,84293842204563 )
J Chem Inf Model - Structure based design, synthesis, pharmacophore modeling, virtual screening, and molecular docking studies for identification of novel cyclophilin D inhibitors. ( 0,842090910974203 )