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.

Tópicos

{ compound(1573) activ(1297) structur(1058) }
{ perform(1367) use(1326) method(1137) }
{ model(2341) predict(2261) use(1141) }
{ drug(1928) target(777) effect(648) }
{ implement(1333) system(1263) develop(1122) }
{ data(1714) softwar(1251) tool(1186) }
{ cancer(2502) breast(956) screen(824) }
{ result(1111) use(1088) new(759) }
{ bind(1733) structur(1185) ligand(1036) }
{ take(945) account(800) differ(722) }
{ howev(809) still(633) remain(590) }
{ use(2086) technolog(871) perceiv(783) }
{ imag(1947) propos(1133) code(1026) }
{ extract(1171) text(1153) clinic(932) }
{ first(2504) two(1366) second(1323) }
{ process(1125) use(805) approach(778) }
{ can(774) often(719) complex(702) }
{ inform(2794) health(2639) internet(1427) }
{ system(1976) rule(880) can(841) }
{ imag(2830) propos(1344) filter(1198) }
{ patient(2315) diseas(1263) diabet(1191) }
{ problem(2511) optim(1539) algorithm(950) }
{ algorithm(1844) comput(1787) effici(935) }
{ method(984) reconstruct(947) comput(926) }
{ search(2224) databas(1162) retriev(909) }
{ risk(3053) factor(974) diseas(938) }
{ studi(1119) effect(1106) posit(819) }
{ model(3480) simul(1196) paramet(876) }
{ ehr(2073) health(1662) electron(1139) }
{ time(1939) patient(1703) rate(768) }
{ analysi(2126) use(1163) compon(1037) }
{ survey(1388) particip(1329) question(1065) }
{ activ(1452) weight(1219) physic(1104) }
{ detect(2391) sensit(1101) algorithm(908) }
{ model(3404) distribut(989) bayesian(671) }
{ data(1737) use(1416) pattern(1282) }
{ measur(2081) correl(1212) valu(896) }
{ imag(1057) registr(996) error(939) }
{ sequenc(1873) structur(1644) protein(1328) }
{ method(1219) similar(1157) match(930) }
{ featur(3375) classif(2383) classifi(1994) }
{ network(2748) neural(1063) input(814) }
{ imag(2675) segment(2577) method(1081) }
{ studi(2440) review(1878) systemat(933) }
{ 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) }
{ clinic(1479) use(1117) guidelin(835) }
{ method(1557) propos(1049) approach(1037) }
{ 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) }
{ featur(1941) imag(1645) propos(1176) }
{ case(1353) use(1143) diagnosi(1136) }
{ data(3963) clinic(1234) research(1004) }
{ studi(1410) differ(1259) use(1210) }
{ perform(999) metric(946) measur(919) }
{ research(1085) discuss(1038) issu(1018) }
{ system(1050) medic(1026) inform(1018) }
{ import(1318) role(1303) understand(862) }
{ visual(1396) interact(850) tool(830) }
{ 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) }
{ data(2317) use(1299) case(1017) }
{ age(1611) year(1155) adult(843) }
{ medic(1828) order(1363) alert(1069) }
{ signal(2180) analysi(812) frequenc(800) }
{ 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) }
{ intervent(3218) particip(2042) group(1664) }
{ activ(1138) subject(705) human(624) }
{ patient(1821) servic(1111) care(1106) }
{ can(981) present(881) function(850) }
{ health(1844) social(1437) communiti(874) }
{ structur(1116) can(940) graph(676) }
{ high(1669) rate(1365) level(1280) }
{ use(976) code(926) identifi(902) }
{ use(1733) differ(960) four(931) }
{ 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

As part of a large medicinal chemistry program, we wish to develop novel selective estrogen receptor modulators (SERMs) as potential breast cancer treatments using a combination of experimental and computational approaches. However, one of the remaining difficulties nowadays is to fully integrate computational (i.e., virtual, theoretical) and medicinal (i.e., experimental, intuitive) chemistry to take advantage of the full potential of both. For this purpose, we have developed a Web-based platform, Forecaster, and a number of programs (e.g., Prepare, React, Select) with the aim of combining computational chemistry and medicinal chemistry expertise to facilitate drug discovery and development and more specifically to integrate synthesis into computer-aided drug design. In our quest for potent SERMs, this platform was used to build virtual combinatorial libraries, filter and extract a highly diverse library from the NCI database, and dock them to the estrogen receptor (ER), with all of these steps being fully automated by computational chemists for use by medicinal chemists. As a result, virtual screening of a diverse library seeded with active compounds followed by a search for analogs yielded an enrichment factor of 129, with 98% of the seeded active compounds recovered, while the screening of a designed virtual combinatorial library including known actives yielded an area under the receiver operating characteristic (AU-ROC) of 0.78. The lead optimization proved less successful, further demonstrating the challenge to simulate structure activity relationship studies.

Resumo Limpo

part larg medicin chemistri program wish develop novel select estrogen receptor modul serm potenti breast cancer treatment use combin experiment comput approach howev one remain difficulti nowaday fulli integr comput ie virtual theoret medicin ie experiment intuit chemistri take advantag full potenti purpos develop webbas platform forecast number program eg prepar react select aim combin comput chemistri medicin chemistri expertis facilit drug discoveri develop specif integr synthesi computeraid drug design quest potent serm platform use build virtual combinatori librari filter extract high divers librari nci databas dock estrogen receptor er step fulli autom comput chemist use medicin chemist result virtual screen divers librari seed activ compound follow search analog yield enrich factor seed activ compound recov screen design virtual combinatori librari includ known activ yield area receiv oper characterist auroc lead optim prove less success demonstr challeng simul structur activ relationship studi

Resumos Similares

J Chem Inf Model - Identification of novel malarial cysteine protease inhibitors using structure-based virtual screening of a focused cysteine protease inhibitor library. ( 0,90684511334475 )
J Chem Inf Model - TIN-a combinatorial compound collection of synthetically feasible multicomponent synthesis products. ( 0,881801555058083 )
J Chem Inf Model - How diverse are diversity assessment methods? A comparative analysis and benchmarking of molecular descriptor space. ( 0,874967655309902 )
J Chem Inf Model - Identification of 1,2,5-oxadiazoles as a new class of SENP2 inhibitors using structure based virtual screening. ( 0,873563925495481 )
J Chem Inf Model - Polypharmacology directed compound data mining: identification of promiscuous chemotypes with different activity profiles and comparison to approved drugs. ( 0,870855190953463 )
J Chem Inf Model - Application of computer-aided drug repurposing in the search of new cruzipain inhibitors: discovery of amiodarone and bromocriptine inhibitory effects. ( 0,869210266794283 )
J Chem Inf Model - Automated recycling of chemistry for virtual screening and library design. ( 0,869053124574863 )
J Chem Inf Model - Identification of a novel inhibitor of dengue virus protease through use of a virtual screening drug discovery Web portal. ( 0,867985369345936 )
J Chem Inf Model - A multivariate chemical similarity approach to search for drugs of potential environmental concern. ( 0,865332306111357 )
J Chem Inf Model - Combining horizontal and vertical substructure relationships in scaffold hierarchies for activity prediction. ( 0,865051865972395 )
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. ( 0,863693522488695 )
J Chem Inf Model - Capturing structure-activity relationships from chemogenomic spaces. ( 0,863143061175808 )
J Chem Inf Model - G-protein coupled receptors virtual screening using genetic algorithm focused chemical space. ( 0,86281953830992 )
J Chem Inf Model - Identification of novel liver X receptor activators by structure-based modeling. ( 0,861999054173095 )
Curr Comput Aided Drug Des - Development of Chemical Compound Libraries for In Silico Drug Screening. ( 0,860573762251676 )
J Chem Inf Model - QSAR classification model for antibacterial compounds and its use in virtual screening. ( 0,860351257633204 )
J Chem Inf Model - Natural product-like virtual libraries: recursive atom-based enumeration. ( 0,859738599131581 )
J Chem Inf Model - Feasibility of using molecular docking-based virtual screening for searching dual target kinase inhibitors. ( 0,858399652904313 )
J Chem Inf Model - Compound optimization through data set-dependent chemical transformations. ( 0,857303621569289 )
J Chem Inf Model - Discovery of a7-nicotinic receptor ligands by virtual screening of the chemical universe database GDB-13. ( 0,85683288831654 )
J Chem Inf Model - Exploring polypharmacology using a ROCS-based target fishing approach. ( 0,856831621619724 )
J Chem Inf Model - Identification of multitarget activity ridges in high-dimensional bioactivity spaces. ( 0,855179305537482 )
J Chem Inf Model - Selection of in silico drug screening results for G-protein-coupled receptors by using universal active probes. ( 0,853796191147971 )
J Chem Inf Model - De novo design of drug-like molecules by a fragment-based molecular evolutionary approach. ( 0,853422860317438 )
J Chem Inf Model - Visual characterization and diversity quantification of chemical libraries: 1. creation of delimited reference chemical subspaces. ( 0,852257433933747 )
J Chem Inf Model - Target-independent prediction of drug synergies using only drug lipophilicity. ( 0,852230887269825 )
J Chem Inf Model - In silico enzymatic synthesis of a 400,000 compound biochemical database for nontargeted metabolomics. ( 0,850864708070027 )
J Chem Inf Model - Discovery of inhibitors of Schistosoma mansoni HDAC8 by combining homology modeling, virtual screening, and in vitro validation. ( 0,849692628462004 )
J Chem Inf Model - Identifying compound-target associations by combining bioactivity profile similarity search and public databases mining. ( 0,849354679756379 )
J Chem Inf Model - Novel mycosin protease MycP1 inhibitors identified by virtual screening and 4D fingerprints. ( 0,847709395116431 )
J Chem Inf Model - Enrichment of chemical libraries docked to protein conformational ensembles and application to aldehyde dehydrogenase 2. ( 0,845778552383103 )
J Chem Inf Model - Identification of sumoylation activating enzyme 1 inhibitors by structure-based virtual screening. ( 0,845160275985192 )
J Chem Inf Model - Ligand- and structure-based virtual screening for clathrodin-derived human voltage-gated sodium channel modulators. ( 0,844322068756258 )
J Chem Inf Model - Mining the ChEMBL database: an efficient chemoinformatics workflow for assembling an ion channel-focused screening library. ( 0,844231764817738 )
J Chem Inf Model - Increasing the coverage of medicinal chemistry-relevant space in commercial fragments screening. ( 0,844216756653247 )
J Chem Inf Model - Identification of a new class of FtsZ inhibitors by structure-based design and in vitro screening. ( 0,843892855471091 )
J Chem Inf Model - Virtual fragment screening: discovery of histamine H3 receptor ligands using ligand-based and protein-based molecular fingerprints. ( 0,842335857582768 )
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. ( 0,841048211018427 )
J Chem Inf Model - Fragment-based lead discovery and design. ( 0,839846145260243 )
J Chem Inf Model - Identification of novel serotonin transporter compounds by virtual screening. ( 0,838767424134281 )
J Chem Inf Model - Virtual screening yields inhibitors of novel antifungal drug target, benzoate 4-monooxygenase. ( 0,836521724189708 )
J Chem Inf Model - Prediction of individual compounds forming activity cliffs using emerging chemical patterns. ( 0,835068518818083 )
J Chem Inf Model - Searching for recursively defined generic chemical patterns in nonenumerated fragment spaces. ( 0,834981347869673 )
J Chem Inf Model - Prediction of new bioactive molecules using a Bayesian belief network. ( 0,834731533850087 )
J Chem Inf Model - Conditional probabilistic analysis for prediction of the activity landscape and relative compound activities. ( 0,834076661653157 )
J Chem Inf Model - Similarity boosted quantitative structure-activity relationship--a systematic study of enhancing structural descriptors by molecular similarity. ( 0,831277443045295 )
J Chem Inf Model - Novel method for pharmacophore analysis by examining the joint pharmacophore space. ( 0,83094479256541 )
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. ( 0,829913893088121 )
J Chem Inf Model - From activity cliffs to activity ridges: informative data structures for SAR analysis. ( 0,829803263642668 )
J Chem Inf Model - Discovery of new selective human aldose reductase inhibitors through virtual screening multiple binding pocket conformations. ( 0,829799322956963 )
J Chem Inf Model - Discovery of novel checkpoint kinase 1 inhibitors by virtual screening based on multiple crystal structures. ( 0,829168651929105 )
J Chem Inf Model - Design of a three-dimensional multitarget activity landscape. ( 0,828252643824601 )
J Chem Inf Model - Ligand-based virtual screening approach using a new scoring function. ( 0,827941787389539 )
J Chem Inf Model - Identification of novel potential antibiotics against Staphylococcus using structure-based drug screening targeting dihydrofolate reductase. ( 0,827888264141086 )
J Chem Inf Model - Identification of compounds with potential antibacterial activity against Mycobacterium through structure-based drug screening. ( 0,82673496235569 )
J Chem Inf Model - Compound set enrichment: a novel approach to analysis of primary HTS data. ( 0,826189512613675 )
J Chem Inf Model - Automatic tailoring and transplanting: a practical method that makes virtual screening more useful. ( 0,826099694541886 )
J Chem Inf Model - Visualization and virtual screening of the chemical universe database GDB-17. ( 0,824000371210557 )
J Chem Inf Model - ZINClick: a database of 16 million novel, patentable, and readily synthesizable 1,4-disubstituted triazoles. ( 0,821990540820185 )
J Chem Inf Model - Rationalizing the role of SAR tolerance for ligand-based virtual screening. ( 0,821891439880279 )
J Chem Inf Model - Effective screening strategy using ensembled pharmacophore models combined with cascade docking: application to p53-MDM2 interaction inhibitors. ( 0,821000239807965 )
J Chem Inf Model - Enumeration of 166 billion organic small molecules in the chemical universe database GDB-17. ( 0,820626984995517 )
J Chem Inf Model - Computational repositioning and experimental validation of approved drugs for HIF-prolyl hydroxylase inhibition. ( 0,819111042579168 )
J Chem Inf Model - SABRE: ligand/structure-based virtual screening approach using consensus molecular-shape pattern recognition. ( 0,818964429905913 )
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. ( 0,818716131449786 )
J Chem Inf Model - Characterizing the diversity and biological relevance of the MLPCN assay manifold and screening set. ( 0,818491908529953 )
J Chem Inf Model - Molecular modeling of potential anticancer agents from African medicinal plants. ( 0,818063036691627 )
J Chem Inf Model - Discovery of chemical compound groups with common structures by a network analysis approach (affinity prediction method). ( 0,817861365598978 )
J Chem Inf Model - Structure-based virtual screening approach for discovery of covalently bound ligands. ( 0,817132400529369 )
J Chem Inf Model - Neighborhood-based prediction of novel active compounds from SAR matrices. ( 0,816587216520331 )
J Chem Inf Model - Atom pair 2D-fingerprints perceive 3D-molecular shape and pharmacophores for very fast virtual screening of ZINC and GDB-17. ( 0,815956812502569 )
J Chem Inf Model - Identification of novel S-adenosyl-L-homocysteine hydrolase inhibitors through homology-model-based virtual screening, synthesis, and biological evaluation. ( 0,815426495738658 )
J Chem Inf Model - Scaffold diversity of exemplified medicinal chemistry space. ( 0,812949933983303 )
J Chem Inf Model - Introduction of target cliffs as a concept to identify and describe complex molecular selectivity patterns. ( 0,812942653313109 )
J Chem Inf Model - Hsp90 inhibitors, part 2: combining ligand-based and structure-based approaches for virtual screening application. ( 0,812762004013873 )
J Chem Inf Model - SMIfp (SMILES fingerprint) chemical space for virtual screening and visualization of large databases of organic molecules. ( 0,812374067997801 )
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. ( 0,811476791496263 )
J Chem Inf Model - Molecular topology analysis of the differences between drugs, clinical candidate compounds, and bioactive molecules. ( 0,811431000305222 )
J Chem Inf Model - BioSM: metabolomics tool for identifying endogenous mammalian biochemical structures in chemical structure space. ( 0,811070329026378 )
J Chem Inf Model - FINDSITE(comb): a threading/structure-based, proteomic-scale virtual ligand screening approach. ( 0,810939871709717 )
J Chem Inf Model - Structure based model for the prediction of phospholipidosis induction potential of small molecules. ( 0,809268852089446 )
Brief. Bioinformatics - State-of-the-art technology in modern computer-aided drug design. ( 0,808030048222722 )
J Chem Inf Model - Discovery of novel histamine H4 and serotonin transporter ligands using the topological feature tree descriptor. ( 0,807794199367307 )
J Chem Inf Model - Navigating high-dimensional activity landscapes: design and application of the ligand-target differentiation map. ( 0,807039888896394 )
J Chem Inf Model - Fighting high molecular weight in bioactive molecules with sub-pharmacophore-based virtual screening. ( 0,806820093243718 )
J Chem Inf Model - ColBioS-FlavRC: a collection of bioselective flavonoids and related compounds filtered from high-throughput screening outcomes. ( 0,806728916669975 )
J Chem Inf Model - Multiple e-pharmacophore modeling, 3D-QSAR, and high-throughput virtual screening of hepatitis C virus NS5B polymerase inhibitors. ( 0,806399656327842 )
J Chem Inf Model - Multitarget structure-activity relationships characterized by activity-difference maps and consensus similarity measure. ( 0,804434663237055 )
J Chem Inf Model - Probing the bioactivity-relevant chemical space of robust reactions and common molecular building blocks. ( 0,804206427095351 )
J Chem Inf Model - Systematic identification of scaffolds representing compounds active against individual targets and single or multiple target families. ( 0,80184955864841 )
J Chem Inf Model - Systematic assessment of compound series with SAR transfer potential. ( 0,801256316650998 )
J Chem Inf Model - Searching for substructures in fragment spaces. ( 0,799669970163751 )
J Chem Inf Model - Design of multitarget activity landscapes that capture hierarchical activity cliff distributions. ( 0,797649667646041 )
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. ( 0,794731199159079 )
J Chem Inf Model - An integrated virtual screening approach for VEGFR-2 inhibitors. ( 0,79304783673815 )
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. ( 0,792756557312983 )
J Chem Inf Model - Exploring the biologically relevant chemical space for drug discovery. ( 0,792248556784303 )
J Chem Inf Model - Small-molecule 3D structure prediction using open crystallography data. ( 0,792225511157403 )
J Chem Inf Model - Reranking docking poses using molecular simulations and approximate free energy methods. ( 0,792090462863969 )
J Chem Inf Model - AlzPlatform: an Alzheimer's disease domain-specific chemogenomics knowledgebase for polypharmacology and target identification research. ( 0,791907411239728 )