J Chem Inf Model - Combinatorial ? computational ? cheminformatics (C3) approach to characterization of congeneric libraries of organic pollutants.

Tópicos

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

Resumo

Congeners are molecules based on the same carbon skeleton but are different by the number of substituents and/or a substitution pattern. Examples are 1-chloronaphthalene, 1,4-dichloronaphthalene, and 1,3,8-trichloronaphthalene. Various persistent organic pollutants (POPs) exist in the environment as families of congeners. Very large numbers of possible congeners make their experimental characterization and risk assessment unfeasible. Computational high-throughput and quantitative structure-property relationship (QSPR) modeling has been limited by the lack of tools and approaches facilitating analysis of such POP families. We present a comprehensive approach that enables modeling of extremely large congeneric libraries. The approach involves three steps: (1) combinatorial generation of a library of congeners, (2) quantum chemical characterization of each structure at the PM6 semiempirical level to obtain molecular descriptors, and (3) analysis of the information generated in step 2. In steps 1-3, we employ combinatorial, computational, and cheminformatics techniques, respectively. Therefore, this hybrid approach is named "Combinatorial ? Computational ? Cheminformatics", or just abbreviated as C(3) (or C-cubed) approach. We demonstrate the usefulness of this approach by generating and characterizing Br- and Cl-substituted congeneric families of 23 typical POPs. The analysis of the resulting set of 1840951 congeners that includes Cl-, Br-, and mixed Br/Cl-substituted species, proves that, based on structural similarities defined by the molecular descriptors' values, the existing QSPR models developed originally for Cl- and Br-substituted congeners can be applied also to mixed Br/Cl-substituted ones. Thus, the C(3) approach may serve as a tool for exploring structural applicability domains of the existing QSPR models for congeneric sets.

Resumo Limpo

congen molecul base carbon skeleton differ number substitu andor substitut pattern exampl chloronaphthalen dichloronaphthalen trichloronaphthalen various persist organ pollut pop exist environ famili congen larg number possibl congen make experiment character risk assess unfeas comput highthroughput quantit structureproperti relationship qspr model limit lack tool approach facilit analysi pop famili present comprehens approach enabl model extrem larg congener librari approach involv three step combinatori generat librari congen quantum chemic character structur pm semiempir level obtain molecular descriptor analysi inform generat step step employ combinatori comput cheminformat techniqu respect therefor hybrid approach name combinatori comput cheminformat just abbrevi c ccube approach demonstr use approach generat character br clsubstitut congener famili typic pop analysi result set congen includ cl br mix brclsubstitut speci prove base structur similar defin molecular descriptor valu exist qspr model develop origin cl brsubstitut congen can appli also mix brclsubstitut one thus c approach may serv tool explor structur applic domain exist qspr model congener set

Resumos Similares

J Chem Inf Model - Pocket-space maps to identify novel binding-site conformations in proteins. ( 0,681210388470666 )
Brief. Bioinformatics - Toward more realistic drug-target interaction predictions. ( 0,657042678654429 )
J Chem Inf Model - ColBioS-FlavRC: a collection of bioselective flavonoids and related compounds filtered from high-throughput screening outcomes. ( 0,637456559112022 )
J Chem Inf Model - P-glycoprotein substrate models using support vector machines based on a comprehensive data set. ( 0,628348912276095 )
J Chem Inf Model - Computational screening for active compounds targeting protein sequences: methodology and experimental validation. ( 0,624677631621263 )
J Chem Inf Model - Best of both worlds: on the complementarity of ligand-based and structure-based virtual screening. ( 0,621034476602842 )
J Chem Inf Model - Predicting myelosuppression of drugs from in silico models. ( 0,620017142485966 )
J Chem Inf Model - Quantitative structure-activity relationship models of chemical transformations from matched pairs analyses. ( 0,616336052709989 )
J Chem Inf Model - A new protocol for predicting novel GSK-3? ATP competitive inhibitors. ( 0,614207078981532 )
J Chem Inf Model - Extraction of discontinuous structure-activity relationships from compound data sets through particle swarm optimization. ( 0,608764879599065 )
J Chem Inf Model - Rationalization of the pKa values of alcohols and thiols using atomic charge descriptors and its application to the prediction of amino acid pKa's. ( 0,599109143569442 )
J Chem Inf Model - SABRE: ligand/structure-based virtual screening approach using consensus molecular-shape pattern recognition. ( 0,596327266489493 )
Int J Neural Syst - Event-related complexity analysis and its application in the detection of facial attractiveness. ( 0,594936618331678 )
J Chem Inf Model - Structure based design, synthesis, pharmacophore modeling, virtual screening, and molecular docking studies for identification of novel cyclophilin D inhibitors. ( 0,593229617426369 )
J Chem Inf Model - Visualization and virtual screening of the chemical universe database GDB-17. ( 0,592041024485338 )
J Chem Inf Model - DrugLogit: logistic discrimination between drugs and nondrugs including disease-specificity by assigning probabilities based on molecular properties. ( 0,591540657875982 )
J Chem Inf Model - MARS: computing three-dimensional alignments for multiple ligands using pairwise similarities. ( 0,586297280237891 )
J Chem Inf Model - Automated design of realistic organometallic molecules from fragments. ( 0,585410160603565 )
J Chem Inf Model - Multiple e-pharmacophore modeling, 3D-QSAR, and high-throughput virtual screening of hepatitis C virus NS5B polymerase inhibitors. ( 0,584348996759919 )
J Chem Inf Model - Alignment-independent comparison of binding sites based on DrugScore potential fields encoded by 3D Zernike descriptors. ( 0,584050229075616 )
J Chem Inf Model - Construction and use of fragment-augmented molecular Hasse diagrams. ( 0,583302422468358 )
J Chem Inf Model - Hsp90 inhibitors, part 2: combining ligand-based and structure-based approaches for virtual screening application. ( 0,582434872690925 )
J Chem Inf Model - Development of a rule-based method for the assessment of protein druggability. ( 0,580119351115321 )
J Chem Inf Model - Profile-QSAR and Surrogate AutoShim protein-family modeling of proteases. ( 0,5782892111884 )
J Chem Inf Model - Discovery of a novel selective kappa-opioid receptor agonist using crystal structure-based virtual screening. ( 0,577751517029136 )
J Chem Inf Model - Exploiting domain knowledge for improved quantitative high-throughput screening curve fitting. ( 0,574884572723679 )
J Chem Inf Model - Discovery of novel histamine H4 and serotonin transporter ligands using the topological feature tree descriptor. ( 0,573729715229166 )
J Chem Inf Model - Modeling drug-induced anorexia by molecular topology. ( 0,573609359624431 )
J Chem Inf Model - Kinase-kernel models: accurate in silico screening of 4 million compounds across the entire human kinome. ( 0,573251715854862 )
J Chem Inf Model - Pharmacophore-based virtual screening and experimental validation of novel inhibitors against cyanobacterial fructose-1,6-/sedoheptulose-1,7-bisphosphatase. ( 0,57317546746179 )
J Chem Inf Model - New Group IV chemical motifs for improved dielectric permittivity of polyethylene. ( 0,570721846359907 )
J Chem Inf Model - Extracting sets of chemical substructures and protein domains governing drug-target interactions. ( 0,570708033214003 )
J Chem Inf Model - Prediction of individual compounds forming activity cliffs using emerging chemical patterns. ( 0,569829556730895 )
J Chem Inf Model - Identification of novel androgen receptor antagonists using structure- and ligand-based methods. ( 0,569649139112944 )
J Chem Inf Model - Dynamics of hERG closure allow novel insights into hERG blocking by small molecules. ( 0,569373594312711 )
J Chem Inf Model - Cheminformatics meets molecular mechanics: a combined application of knowledge-based pose scoring and physical force field-based hit scoring functions improves the accuracy of structure-based virtual screening. ( 0,569116235294228 )
J Chem Inf Model - Automatic tailoring and transplanting: a practical method that makes virtual screening more useful. ( 0,568900334644048 )
J Chem Inf Model - Discovery of novel selective serotonin reuptake inhibitors through development of a protein-based pharmacophore. ( 0,568428767512926 )
J Chem Inf Model - Searching for recursively defined generic chemical patterns in nonenumerated fragment spaces. ( 0,566669691822515 )
J Chem Inf Model - MMP-Cliffs: systematic identification of activity cliffs on the basis of matched molecular pairs. ( 0,564261113408402 )
J Chem Inf Model - Predictions of BuChE inhibitors using support vector machine and naive Bayesian classification techniques in drug discovery. ( 0,564118289361838 )
J Chem Inf Model - Discovery of a7-nicotinic receptor ligands by virtual screening of the chemical universe database GDB-13. ( 0,562605843490793 )
J Chem Inf Model - Dissecting kinase profiling data to predict activity and understand cross-reactivity of kinase inhibitors. ( 0,562593247199236 )
J Chem Inf Model - Development of Ecom50 and retention index models for nontargeted metabolomics: identification of 1,3-dicyclohexylurea in human serum by HPLC/mass spectrometry. ( 0,562541434630659 )
J Chem Inf Model - Scanning structure-activity relationships with structure-activity similarity and related maps: from consensus activity cliffs to selectivity switches. ( 0,559805918599862 )
Brief. Bioinformatics - Identify drug repurposing candidates by mining the protein data bank. ( 0,559775257052846 )
Brief. Bioinformatics - Comprehensive overview and assessment of computational prediction of microRNA targets in animals. ( 0,559352609021617 )
J Chem Inf Model - QSAR modeling of imbalanced high-throughput screening data in PubChem. ( 0,557094517000071 )
J Chem Inf Model - Prediction of compound potency changes in matched molecular pairs using support vector regression. ( 0,556832211533458 )
J Chem Inf Model - DiSCuS: an open platform for (not only) virtual screening results management. ( 0,556708586739463 )
J Chem Inf Model - Assessing molecular docking tools for relative biological activity prediction: a case study of triazole HIV-1 NNRTIs. ( 0,556554617855488 )
J Chem Inf Model - Identification of sumoylation activating enzyme 1 inhibitors by structure-based virtual screening. ( 0,555556578817245 )
J Chem Inf Model - Exploiting structural information in patent specifications for key compound prediction. ( 0,554983134369731 )
J Chem Inf Model - The valence state combination model: a generic framework for handling tautomers and protonation states. ( 0,554166994422667 )
J Chem Inf Model - Freely available conformer generation methods: how good are they? ( 0,553875742015838 )
J Chem Inf Model - Emerging pattern mining to aid toxicological knowledge discovery. ( 0,551905449987936 )
J Chem Inf Model - CELLmicrocosmos 2.2 MembraneEditor: a modular interactive shape-based software approach to solve heterogeneous membrane packing problems. ( 0,551292656567579 )
J Chem Inf Model - Development of a minimal kinase ensemble receptor (MKER) for surrogate AutoShim. ( 0,551267724337371 )
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. ( 0,551246043101198 )
J Chem Inf Model - Identification of novel S-adenosyl-L-homocysteine hydrolase inhibitors through homology-model-based virtual screening, synthesis, and biological evaluation. ( 0,551129656960247 )
J Chem Inf Model - Automated recycling of chemistry for virtual screening and library design. ( 0,550516967103586 )
Sci Data - The species translation challenge-a systems biology perspective on human and rat bronchial epithelial cells. ( 0,550454419018728 )
J Chem Inf Model - Rapid scanning structure-activity relationships in combinatorial data sets: identification of activity switches. ( 0,550283048603775 )
J Chem Inf Model - Computational repositioning and experimental validation of approved drugs for HIF-prolyl hydroxylase inhibition. ( 0,549983280927513 )
J Chem Inf Model - Conditional probabilistic analysis for prediction of the activity landscape and relative compound activities. ( 0,548985090704073 )
J Chem Inf Model - Visual characterization and diversity quantification of chemical libraries: 1. creation of delimited reference chemical subspaces. ( 0,548898407706839 )
J Chem Inf Model - Prospects for tertiary structure prediction of RNA based on secondary structure information. ( 0,548773638243087 )
J Chem Inf Model - Novel kinase inhibitors by reshuffling ligand functionalities across the human kinome. ( 0,54824597869111 )
J Chem Inf Model - COSMOsim3D: 3D-similarity and alignment based on COSMO polarization charge densities. ( 0,548205936793215 )
J Chem Inf Model - Hsp90 inhibitors, part 1: definition of 3-D QSAutogrid/R models as a tool for virtual screening. ( 0,547604061829006 )
J Chem Inf Model - Novel method for pharmacophore analysis by examining the joint pharmacophore space. ( 0,547423128762777 )
Brief. Bioinformatics - LncTar: a tool for predicting the RNA targets of long noncoding RNAs. ( 0,54721970646324 )
J Chem Inf Model - Screen3D: a novel fully flexible high-throughput shape-similarity search method. ( 0,546249850559574 )
J Chem Inf Model - Identification of novel amino acid derived CCK-2R antagonists as potential antiulcer agent: homology modeling, design, synthesis, and pharmacology. ( 0,545948313722634 )
Comput Biol Chem - Protein folding simulations of 2D HP model by the genetic algorithm based on optimal secondary structures. ( 0,545900245162149 )
J Chem Inf Model - Mapping monomeric threading to protein-protein structure prediction. ( 0,545788702676541 )
J Chem Inf Model - Quantitative structure-activity relationship models for ready biodegradability of chemicals. ( 0,545760617226337 )
Comput. Biol. Med. - Computational identification of novel histone deacetylase inhibitors by docking based QSAR. ( 0,545514596055185 )
J Chem Inf Model - Fragment-based lead discovery and design. ( 0,545108115095397 )
Comput Math Methods Med - Designing lead optimisation of MMP-12 inhibitors. ( 0,544527461667597 )
J Chem Inf Model - Identification of a novel inhibitor of dengue virus protease through use of a virtual screening drug discovery Web portal. ( 0,544251963759759 )
J Chem Inf Model - AlzPlatform: an Alzheimer's disease domain-specific chemogenomics knowledgebase for polypharmacology and target identification research. ( 0,544070297507536 )
J Chem Inf Model - Identification of multitarget activity ridges in high-dimensional bioactivity spaces. ( 0,543109740020405 )
J Chem Inf Model - Jointly handling potency and toxicity of antimicrobial peptidomimetics by simple rules from desirability theory and chemoinformatics. ( 0,542929221561228 )
J Chem Inf Model - Identification of compounds with potential antibacterial activity against Mycobacterium through structure-based drug screening. ( 0,541785010225073 )
J Chem Inf Model - Determination of toxicant mode of action by augmented top priority fragment class. ( 0,541138071872986 )
J Chem Inf Model - DEGAS: sharing and tracking target compound ideas with external collaborators. ( 0,540898723026251 )
J Chem Inf Model - Similarity searching for potent compounds using feature selection. ( 0,54066992918413 )
J Chem Inf Model - Introduction of target cliffs as a concept to identify and describe complex molecular selectivity patterns. ( 0,54066992918413 )
J Chem Inf Model - Molecular modeling of the 3D structure of 5-HT(1A)R: discovery of novel 5-HT(1A)R agonists via dynamic pharmacophore-based virtual screening. ( 0,540184395564094 )
J Chem Inf Model - On the value of homology models for virtual screening: discovering hCXCR3 antagonists by pharmacophore-based and structure-based approaches. ( 0,539942695924265 )
J Chem Inf Model - New benchmark for chemical nomenclature software. ( 0,539730202331397 )
J Chem Inf Model - Structural similarity based kriging for quantitative structure activity and property relationship modeling. ( 0,539558619994153 )
J Chem Inf Model - REPROVIS-DB: a benchmark system for ligand-based virtual screening derived from reproducible prospective applications. ( 0,539078765161806 )
Comput. Biol. Med. - Predicting biological activity: computational approach using novel distance based molecular descriptors. ( 0,53880841963831 )
J Chem Inf Model - Comparative analysis of QSAR models for predicting pK(a) of organic oxygen acids and nitrogen bases from molecular structure. ( 0,53877673439529 )
J Chem Inf Model - Design of multitarget activity landscapes that capture hierarchical activity cliff distributions. ( 0,538203381161237 )
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. ( 0,537823696188998 )
Sci Data - Quantum chemistry structures and properties of 134 kilo molecules. ( 0,53759875186901 )
J Chem Inf Model - Systematic assessment of compound series with SAR transfer potential. ( 0,537190025535251 )