J Chem Inf Model - Evaluation and optimization of virtual screening workflows with DEKOIS 2.0--a public library of challenging docking benchmark sets.

Tópicos

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

Resumo

The application of molecular benchmarking sets helps to assess the actual performance of virtual screening (VS) workflows. To improve the efficiency of structure-based VS approaches, the selection and optimization of various parameters can be guided by benchmarking. With the DEKOIS 2.0 library, we aim to further extend and complement the collection of publicly available decoy sets. Based on BindingDB bioactivity data, we provide 81 new and structurally diverse benchmark sets for a wide variety of different target classes. To ensure a meaningful selection of ligands, we address several issues that can be found in bioactivity data. We have improved our previously introduced DEKOIS methodology with enhanced physicochemical matching, now including the consideration of molecular charges, as well as a more sophisticated elimination of latent actives in the decoy set (LADS). We evaluate the docking performance of Glide, GOLD, and AutoDock Vina with our data sets and highlight existing challenges for VS tools. All DEKOIS 2.0 benchmark sets will be made accessible at http://www.dekois.com.

Resumo Limpo

applic molecular benchmark set help assess actual perform virtual screen vs workflow improv effici structurebas vs approach select optim various paramet can guid benchmark dekoi librari aim extend complement collect public avail decoy set base bindingdb bioactiv data provid new structur divers benchmark set wide varieti differ target class ensur meaning select ligand address sever issu can found bioactiv data improv previous introduc dekoi methodolog enhanc physicochem match now includ consider molecular charg well sophist elimin latent activ decoy set lad evalu dock perform glide gold autodock vina data set highlight exist challeng vs tool dekoi benchmark set will made access httpwwwdekoiscom

Resumos Similares

J Chem Inf Model - Computer-aided structure-based design of multitarget leads for Alzheimer's disease. ( 0,753795243189553 )
J Chem Inf Model - How diverse are diversity assessment methods? A comparative analysis and benchmarking of molecular descriptor space. ( 0,741394896799109 )
J Chem Inf Model - Chemical genomics approach for GPCR-ligand interaction prediction and extraction of ligand binding determinants. ( 0,741222492102973 )
J Chem Inf Model - An integrated virtual screening approach for VEGFR-2 inhibitors. ( 0,723553527353023 )
J Chem Inf Model - Multiple e-pharmacophore modeling, 3D-QSAR, and high-throughput virtual screening of hepatitis C virus NS5B polymerase inhibitors. ( 0,722747342488854 )
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. ( 0,721808656739379 )
J Chem Inf Model - Structure-based fragment hopping for lead optimization using predocked fragment database. ( 0,720716627284705 )
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. ( 0,720111172316207 )
J Chem Inf Model - Virtual fragment screening: discovery of histamine H3 receptor ligands using ligand-based and protein-based molecular fingerprints. ( 0,719055786016812 )
J Chem Inf Model - Discovery of novel checkpoint kinase 1 inhibitors by virtual screening based on multiple crystal structures. ( 0,718801411407068 )
J Chem Inf Model - Validation of the AmpC ?-lactamase binding site and identification of inhibitors with novel scaffolds. ( 0,71863094308227 )
J Chem Inf Model - Ligand and decoy sets for docking to G protein-coupled receptors. ( 0,711680659918567 )
J Chem Inf Model - Freely available conformer generation methods: how good are they? ( 0,710838448586499 )
J Chem Inf Model - Selecting an optimal number of binding site waters to improve virtual screening enrichments against the adenosine A2A receptor. ( 0,710256658827346 )
J Chem Inf Model - Identification of novel malarial cysteine protease inhibitors using structure-based virtual screening of a focused cysteine protease inhibitor library. ( 0,704627068249307 )
Comput Biol Chem - Potential drug-like inhibitors of Group 1 influenza neuraminidase identified through computer-aided drug design. ( 0,703873180441809 )
J Chem Inf Model - Prediction of new bioactive molecules using a Bayesian belief network. ( 0,703702655831249 )
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. ( 0,701146003400937 )
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. ( 0,698223180108388 )
J Chem Inf Model - Detailed computational study of the active site of the hepatitis C viral RNA polymerase to aid novel drug design. ( 0,696746232119714 )
J Chem Inf Model - Discovery of new inhibitors of Mycobacterium tuberculosis InhA enzyme using virtual screening and a 3D-pharmacophore-based approach. ( 0,696526299694751 )
J Chem Inf Model - Identification of 1,2,5-oxadiazoles as a new class of SENP2 inhibitors using structure based virtual screening. ( 0,695494179925275 )
J Chem Inf Model - Enrichment of chemical libraries docked to protein conformational ensembles and application to aldehyde dehydrogenase 2. ( 0,695219916365043 )
Brief. Bioinformatics - Toward more realistic drug-target interaction predictions. ( 0,692217249731907 )
J Chem Inf Model - Identification of sumoylation inhibitors targeting a predicted pocket in Ubc9. ( 0,691907142057497 )
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. ( 0,691712019597731 )
J Chem Inf Model - Systematic identification of scaffolds representing compounds active against individual targets and single or multiple target families. ( 0,691422185563978 )
J Chem Inf Model - Virtual screening yields inhibitors of novel antifungal drug target, benzoate 4-monooxygenase. ( 0,688753546236428 )
J Chem Inf Model - Visualization and virtual screening of the chemical universe database GDB-17. ( 0,687862168182047 )
J Chem Inf Model - Novel inhibitor discovery through virtual screening against multiple protein conformations generated via ligand-directed modeling: a maternal embryonic leucine zipper kinase example. ( 0,682884583543597 )
J Chem Inf Model - Automated design of realistic organometallic molecules from fragments. ( 0,680072729496807 )
J Chem Inf Model - Structure-based virtual screening approach for discovery of covalently bound ligands. ( 0,679453931969765 )
J Chem Inf Model - Identification of sumoylation activating enzyme 1 inhibitors by structure-based virtual screening. ( 0,678634382735441 )
J Chem Inf Model - Selection of in silico drug screening results for G-protein-coupled receptors by using universal active probes. ( 0,678573236189406 )
J Chem Inf Model - SABRE: ligand/structure-based virtual screening approach using consensus molecular-shape pattern recognition. ( 0,678522795835343 )
J Chem Inf Model - Combining ligand- and structure-based approaches for the discovery of new inhibitors of the EPHA2-ephrin-A1 interaction. ( 0,67718581430776 )
J Chem Inf Model - FINDSITE(comb): a threading/structure-based, proteomic-scale virtual ligand screening approach. ( 0,676087783831165 )
J Chem Inf Model - Novel method for pharmacophore analysis by examining the joint pharmacophore space. ( 0,675290352403642 )
Sci Data - Quantum chemistry structures and properties of 134 kilo molecules. ( 0,675071125747564 )
J Chem Inf Model - Boosting virtual screening enrichments with data fusion: coalescing hits from two-dimensional fingerprints, shape, and docking. ( 0,673364209219348 )
J Chem Inf Model - Prediction of activity cliffs using support vector machines. ( 0,671693327713056 )
J Chem Inf Model - SHAFTS: a hybrid approach for 3D molecular similarity calculation. 1. Method and assessment of virtual screening. ( 0,671581893542272 )
J Chem Inf Model - Rapid scanning structure-activity relationships in combinatorial data sets: identification of activity switches. ( 0,671516389058887 )
J Chem Inf Model - Best of both worlds: on the complementarity of ligand-based and structure-based virtual screening. ( 0,670186140425645 )
J Chem Inf Model - Identification and validation of novel PERK inhibitors. ( 0,669348979564182 )
J Chem Inf Model - Identification of a novel inhibitor of dengue virus protease through use of a virtual screening drug discovery Web portal. ( 0,668896298832989 )
J Chem Inf Model - G-protein coupled receptors virtual screening using genetic algorithm focused chemical space. ( 0,66622197165329 )
J Chem Inf Model - Ligand Classifier of Adaptively Boosting Ensemble Decision Stumps (LiCABEDS) and its application on modeling ligand functionality for 5HT-subtype GPCR families. ( 0,66573553167613 )
J Chem Inf Model - Ligand- and structure-based virtual screening for clathrodin-derived human voltage-gated sodium channel modulators. ( 0,665617585535741 )
J Chem Inf Model - Target-specific support vector machine scoring in structure-based virtual screening: computational validation, in vitro testing in kinases, and effects on lung cancer cell proliferation. ( 0,665586081207956 )
J Chem Inf Model - Identification of novel S-adenosyl-L-homocysteine hydrolase inhibitors through homology-model-based virtual screening, synthesis, and biological evaluation. ( 0,665354837127808 )
J Chem Inf Model - Visual characterization and diversity quantification of chemical libraries: 1. creation of delimited reference chemical subspaces. ( 0,665241836143947 )
J Chem Inf Model - Identification of novel serotonin transporter compounds by virtual screening. ( 0,664955344544733 )
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. ( 0,664238875992043 )
J Chem Inf Model - Automated recycling of chemistry for virtual screening and library design. ( 0,663996506325626 )
J Chem Inf Model - In silico target predictions: defining a benchmarking data set and comparison of performance of the multiclass Na?ve Bayes and Parzen-Rosenblatt window. ( 0,663325658073316 )
J Chem Inf Model - Polypharmacology directed compound data mining: identification of promiscuous chemotypes with different activity profiles and comparison to approved drugs. ( 0,663116296969273 )
J Chem Inf Model - Feasibility of using molecular docking-based virtual screening for searching dual target kinase inhibitors. ( 0,661859844197418 )
J Chem Inf Model - A multivariate chemical similarity approach to search for drugs of potential environmental concern. ( 0,661526394079615 )
J Chem Inf Model - Capturing structure-activity relationships from chemogenomic spaces. ( 0,66080965068267 )
J Chem Inf Model - REPROVIS-DB: a benchmark system for ligand-based virtual screening derived from reproducible prospective applications. ( 0,660785589742861 )
J Chem Inf Model - Application of computer-aided drug repurposing in the search of new cruzipain inhibitors: discovery of amiodarone and bromocriptine inhibitory effects. ( 0,660504262599638 )
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. ( 0,660451998102002 )
J Chem Inf Model - BioSM: metabolomics tool for identifying endogenous mammalian biochemical structures in chemical structure space. ( 0,660353211322802 )
J Chem Inf Model - Virtual drug screen schema based on multiview similarity integration and ranking aggregation. ( 0,659611982502274 )
Brief. Bioinformatics - State-of-the-art technology in modern computer-aided drug design. ( 0,659536947311284 )
J Chem Inf Model - How to improve docking accuracy of AutoDock4.2: a case study using different electrostatic potentials. ( 0,658817067638219 )
J Chem Inf Model - De novo design of drug-like molecules by a fragment-based molecular evolutionary approach. ( 0,658669008605083 )
J Chem Inf Model - Molecular modeling on pyrimidine-urea inhibitors of TNF-a production: an integrated approach using a combination of molecular docking, classification techniques, and 3D-QSAR CoMSIA. ( 0,657409010980624 )
J Chem Inf Model - Neighborhood-based prediction of novel active compounds from SAR matrices. ( 0,657338531235287 )
J Chem Inf Model - Discovery of novel tubulin inhibitors via structure-based hierarchical virtual screening. ( 0,656541084511985 )
J Chem Inf Model - Structure based model for the prediction of phospholipidosis induction potential of small molecules. ( 0,653737335542413 )
J Chem Inf Model - Molecular modeling of potential anticancer agents from African medicinal plants. ( 0,653349691295557 )
J Chem Inf Model - Scaffold diversity of exemplified medicinal chemistry space. ( 0,65333400756243 )
J Chem Inf Model - Scanning structure-activity relationships with structure-activity similarity and related maps: from consensus activity cliffs to selectivity switches. ( 0,652487341358774 )
J Chem Inf Model - ChemDoodle 6.0. ( 0,652151744337407 )
J Chem Inf Model - Discovery of a7-nicotinic receptor ligands by virtual screening of the chemical universe database GDB-13. ( 0,652090992154079 )
J Chem Inf Model - Complementarity between in silico and biophysical screening approaches in fragment-based lead discovery against the A(2A) adenosine receptor. ( 0,651660773624063 )
J Chem Inf Model - Natural product-like virtual libraries: recursive atom-based enumeration. ( 0,650406631256538 )
J Chem Inf Model - Plane of best fit: a novel method to characterize the three-dimensionality of molecules. ( 0,650384501660364 )
J Chem Inf Model - Application of docking and QM/MM-GBSA rescoring to screen for novel Myt1 kinase inhibitors. ( 0,650372148052678 )
J Chem Inf Model - Increasing the coverage of medicinal chemistry-relevant space in commercial fragments screening. ( 0,650065434641574 )
J Chem Inf Model - Handling of tautomerism and stereochemistry in compound registration. ( 0,649995902217982 )
J Chem Inf Model - Searching for recursively defined generic chemical patterns in nonenumerated fragment spaces. ( 0,649589734745922 )
J Chem Inf Model - In silico enzymatic synthesis of a 400,000 compound biochemical database for nontargeted metabolomics. ( 0,649121112534081 )
J Chem Inf Model - Conditional probabilistic analysis for prediction of the activity landscape and relative compound activities. ( 0,647518537135299 )
J Chem Inf Model - Similarity boosted quantitative structure-activity relationship--a systematic study of enhancing structural descriptors by molecular similarity. ( 0,647386959603977 )
J Chem Inf Model - Discovery of novel histamine H4 and serotonin transporter ligands using the topological feature tree descriptor. ( 0,647221573450017 )
J Chem Inf Model - TIN-a combinatorial compound collection of synthetically feasible multicomponent synthesis products. ( 0,647155813695754 )
J Chem Inf Model - Noncontiguous atom matching structural similarity function. ( 0,646775589812892 )
J Chem Inf Model - QSAR modeling of imbalanced high-throughput screening data in PubChem. ( 0,646688968069914 )
Curr Comput Aided Drug Des - Development of Chemical Compound Libraries for In Silico Drug Screening. ( 0,6465173458065 )
J Chem Inf Model - Comparison of virtual high-throughput screening methods for the identification of phosphodiesterase-5 inhibitors. ( 0,645901038748574 )
J Chem Inf Model - Target-independent prediction of drug synergies using only drug lipophilicity. ( 0,645272375898609 )
J Chem Inf Model - Development and evaluation of an integrated virtual screening strategy by combining molecular docking and pharmacophore searching based on multiple protein structures. ( 0,645166787664213 )
J Chem Inf Model - Bioturbo similarity searching: combining chemical and biological similarity to discover structurally diverse bioactive molecules. ( 0,645087420925088 )
J Chem Inf Model - Identification of non-macrocyclic small molecule inhibitors against the NS3/4A serine protease of hepatitis C virus through in silico screening. ( 0,64471502501047 )
J Chem Inf Model - Automated selection of compounds with physicochemical properties to maximize bioavailability and druglikeness. ( 0,644586201794158 )
J Chem Inf Model - Navigating high-dimensional activity landscapes: design and application of the ligand-target differentiation map. ( 0,643763219150624 )
J Chem Inf Model - CSBB-ConeExclusion, adapting structure based solution virtual screening to libraries on solid support. ( 0,643444481944887 )