Sci Data - Quantum chemistry structures and properties of 134 kilo molecules.

Tópicos

{ compound(1573) activ(1297) structur(1058) }
{ bind(1733) structur(1185) ligand(1036) }
{ studi(2440) review(1878) systemat(933) }
{ sampl(1606) size(1419) use(1276) }
{ method(984) reconstruct(947) comput(926) }
{ high(1669) rate(1365) level(1280) }
{ decis(3086) make(1611) patient(1517) }
{ model(3480) simul(1196) paramet(876) }
{ method(2212) result(1239) propos(1039) }
{ imag(1057) registr(996) error(939) }
{ imag(2675) segment(2577) method(1081) }
{ surgeri(1148) surgic(1085) robot(1054) }
{ learn(2355) train(1041) set(1003) }
{ design(1359) user(1324) use(1319) }
{ visual(1396) interact(850) tool(830) }
{ drug(1928) target(777) effect(648) }
{ can(774) often(719) complex(702) }
{ featur(3375) classif(2383) classifi(1994) }
{ framework(1458) process(801) describ(734) }
{ algorithm(1844) comput(1787) effici(935) }
{ howev(809) still(633) remain(590) }
{ research(1085) discuss(1038) issu(1018) }
{ import(1318) role(1303) understand(862) }
{ ehr(2073) health(1662) electron(1139) }
{ research(1218) medic(880) student(794) }
{ model(2656) set(1616) predict(1553) }
{ medic(1828) order(1363) alert(1069) }
{ data(3008) multipl(1320) sourc(1022) }
{ cancer(2502) breast(956) screen(824) }
{ use(1733) differ(960) four(931) }
{ activ(1452) weight(1219) physic(1104) }
{ 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) }
{ sequenc(1873) structur(1644) protein(1328) }
{ method(1219) similar(1157) match(930) }
{ imag(2830) propos(1344) filter(1198) }
{ network(2748) neural(1063) input(814) }
{ patient(2315) diseas(1263) diabet(1191) }
{ take(945) account(800) differ(722) }
{ motion(1329) object(1292) video(1091) }
{ assess(1506) score(1403) qualiti(1306) }
{ treatment(1704) effect(941) patient(846) }
{ problem(2511) optim(1539) algorithm(950) }
{ error(1145) method(1030) estim(1020) }
{ chang(1828) time(1643) increas(1301) }
{ concept(1167) ontolog(924) domain(897) }
{ clinic(1479) use(1117) guidelin(835) }
{ extract(1171) text(1153) clinic(932) }
{ method(1557) propos(1049) approach(1037) }
{ data(1714) softwar(1251) tool(1186) }
{ 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) }
{ risk(3053) factor(974) diseas(938) }
{ perform(999) metric(946) measur(919) }
{ 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) }
{ 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) }
{ patient(2837) hospit(1953) medic(668) }
{ data(2317) use(1299) case(1017) }
{ age(1611) year(1155) adult(843) }
{ signal(2180) analysi(812) frequenc(800) }
{ cost(1906) reduc(1198) effect(832) }
{ group(2977) signific(1463) compar(1072) }
{ 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) }
{ analysi(2126) use(1163) compon(1037) }
{ health(1844) social(1437) communiti(874) }
{ structur(1116) can(940) graph(676) }
{ use(976) code(926) identifi(902) }
{ result(1111) use(1088) new(759) }
{ implement(1333) system(1263) develop(1122) }
{ survey(1388) particip(1329) question(1065) }
{ estim(2440) model(1874) function(577) }
{ process(1125) use(805) approach(778) }
{ method(1969) cluster(1462) data(1082) }
{ detect(2391) sensit(1101) algorithm(908) }

Resumo

Computational de novo design of new drugs and materials requires rigorous and unbiased exploration of chemical compound space. However, large uncharted territories persist due to its size scaling combinatorially with molecular size. We report computed geometric, energetic, electronic, and thermodynamic properties for 134k stable small organic molecules made up of CHONF. These molecules correspond to the subset of all 133,885 species with up to nine heavy atoms (CONF) out of the GDB-17 chemical universe of 166 billion organic molecules. We report geometries minimal in energy, corresponding harmonic frequencies, dipole moments, polarizabilities, along with energies, enthalpies, and free energies of atomization. All properties were calculated at the B3LYP/6-31G(2df,p) level of quantum chemistry. Furthermore, for the predominant stoichiometry, C7H10O2, there are 6,095 constitutional isomers among the 134k molecules. We report energies, enthalpies, and free energies of atomization at the more accurate G4MP2 level of theory for all of them. As such, this data set provides quantum chemical properties for a relevant, consistent, and comprehensive chemical space of small organic molecules. This database may serve the benchmarking of existing methods, development of new methods, such as hybrid quantum mechanics/machine learning, and systematic identification of structure-property relationships.

Resumo Limpo

comput de novo design new drug materi requir rigor unbias explor chemic compound space howev larg unchart territori persist due size scale combinatori molecular size report comput geometr energet electron thermodynam properti k stabl small organ molecul made chonf molecul correspond subset speci nine heavi atom conf gdb chemic univers billion organ molecul report geometri minim energi correspond harmon frequenc dipol moment polariz along energi enthalpi free energi atom properti calcul blypgdfp level quantum chemistri furthermor predomin stoichiometri cho constitut isom among k molecul report energi enthalpi free energi atom accur gmp level theori data set provid quantum chemic properti relev consist comprehens chemic space small organ molecul databas may serv benchmark exist method develop new method hybrid quantum mechanicsmachin learn systemat identif structureproperti relationship

Resumos Similares

J Chem Inf Model - Virtual screening yields inhibitors of novel antifungal drug target, benzoate 4-monooxygenase. ( 0,892197331059972 )
J Chem Inf Model - Identification of sumoylation activating enzyme 1 inhibitors by structure-based virtual screening. ( 0,8744111049573 )
J Chem Inf Model - Molecular modeling of potential anticancer agents from African medicinal plants. ( 0,873979575047447 )
J Chem Inf Model - Identification of novel S-adenosyl-L-homocysteine hydrolase inhibitors through homology-model-based virtual screening, synthesis, and biological evaluation. ( 0,871216407093577 )
J Chem Inf Model - Virtual fragment screening: discovery of histamine H3 receptor ligands using ligand-based and protein-based molecular fingerprints. ( 0,870266937609457 )
J Chem Inf Model - Polypharmacology directed compound data mining: identification of promiscuous chemotypes with different activity profiles and comparison to approved drugs. ( 0,867844176770505 )
J Chem Inf Model - FINDSITE(comb): a threading/structure-based, proteomic-scale virtual ligand screening approach. ( 0,865890037185812 )
J Chem Inf Model - Selection of in silico drug screening results for G-protein-coupled receptors by using universal active probes. ( 0,865673422793503 )
J Chem Inf Model - Enrichment of chemical libraries docked to protein conformational ensembles and application to aldehyde dehydrogenase 2. ( 0,864551315400728 )
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. ( 0,861104894123525 )
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. ( 0,860158168297647 )
J Chem Inf Model - Identification of 1,2,5-oxadiazoles as a new class of SENP2 inhibitors using structure based virtual screening. ( 0,859903351549615 )
J Chem Inf Model - Identification of novel liver X receptor activators by structure-based modeling. ( 0,859336821756222 )
J Chem Inf Model - Structure based design, synthesis, pharmacophore modeling, virtual screening, and molecular docking studies for identification of novel cyclophilin D inhibitors. ( 0,856152133071142 )
J Chem Inf Model - Detailed computational study of the active site of the hepatitis C viral RNA polymerase to aid novel drug design. ( 0,855928173709104 )
J Chem Inf Model - Identification of novel serotonin transporter compounds by virtual screening. ( 0,85453611557245 )
J Chem Inf Model - Multiple e-pharmacophore modeling, 3D-QSAR, and high-throughput virtual screening of hepatitis C virus NS5B polymerase inhibitors. ( 0,853554981202156 )
J Chem Inf Model - Identification of a novel inhibitor of dengue virus protease through use of a virtual screening drug discovery Web portal. ( 0,852681809368862 )
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. ( 0,851193775763994 )
J Chem Inf Model - SABRE: ligand/structure-based virtual screening approach using consensus molecular-shape pattern recognition. ( 0,849992588388603 )
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. ( 0,848643448934032 )
J Chem Inf Model - Discovery of novel checkpoint kinase 1 inhibitors by virtual screening based on multiple crystal structures. ( 0,84763198880232 )
Curr Comput Aided Drug Des - Development of Chemical Compound Libraries for In Silico Drug Screening. ( 0,841948893059354 )
J Chem Inf Model - Structure-based virtual screening approach for discovery of covalently bound ligands. ( 0,840278507027187 )
J Chem Inf Model - Discovery of a7-nicotinic receptor ligands by virtual screening of the chemical universe database GDB-13. ( 0,838989984752004 )
J Chem Inf Model - Novel method for pharmacophore analysis by examining the joint pharmacophore space. ( 0,837294060327664 )
J Chem Inf Model - Identification of inhibitors against p90 ribosomal S6 kinase 2 (RSK2) through structure-based virtual screening with the inhibitor-constrained refined homology model. ( 0,836703573649749 )
J Chem Inf Model - Novel mycosin protease MycP1 inhibitors identified by virtual screening and 4D fingerprints. ( 0,836344153797189 )
J Chem Inf Model - Freely available conformer generation methods: how good are they? ( 0,835323187054117 )
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. ( 0,833060651651603 )
J Chem Inf Model - G-protein coupled receptors virtual screening using genetic algorithm focused chemical space. ( 0,832104232855259 )
J Chem Inf Model - Validation of the AmpC ?-lactamase binding site and identification of inhibitors with novel scaffolds. ( 0,831880343450701 )
J Chem Inf Model - Complementarity between in silico and biophysical screening approaches in fragment-based lead discovery against the A(2A) adenosine receptor. ( 0,831693995609862 )
J Chem Inf Model - Target-independent prediction of drug synergies using only drug lipophilicity. ( 0,831065471006663 )
J Chem Inf Model - Conditional probabilistic analysis for prediction of the activity landscape and relative compound activities. ( 0,827932418393689 )
J Chem Inf Model - Automatic tailoring and transplanting: a practical method that makes virtual screening more useful. ( 0,826580450605086 )
J Chem Inf Model - TIN-a combinatorial compound collection of synthetically feasible multicomponent synthesis products. ( 0,825735852650846 )
J Chem Inf Model - Visualization and virtual screening of the chemical universe database GDB-17. ( 0,825521579082338 )
J Chem Inf Model - Introduction of target cliffs as a concept to identify and describe complex molecular selectivity patterns. ( 0,824013773920001 )
J Chem Inf Model - Feasibility of using molecular docking-based virtual screening for searching dual target kinase inhibitors. ( 0,821259105269719 )
J Chem Inf Model - Searching for recursively defined generic chemical patterns in nonenumerated fragment spaces. ( 0,819577763065553 )
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. ( 0,81865664776485 )
J Chem Inf Model - Identifying compound-target associations by combining bioactivity profile similarity search and public databases mining. ( 0,818134463181251 )
J Chem Inf Model - QSAR classification model for antibacterial compounds and its use in virtual screening. ( 0,817537093471667 )
J Chem Inf Model - Automated recycling of chemistry for virtual screening and library design. ( 0,816737855298681 )
J Chem Inf Model - Mining the ChEMBL database: an efficient chemoinformatics workflow for assembling an ion channel-focused screening library. ( 0,814410203272134 )
J Chem Inf Model - Discovery of inhibitors of Schistosoma mansoni HDAC8 by combining homology modeling, virtual screening, and in vitro validation. ( 0,813914897665873 )
J Chem Inf Model - Natural product-like virtual libraries: recursive atom-based enumeration. ( 0,813383424607169 )
J Chem Inf Model - Hot spot analysis for driving the development of hits into leads in fragment-based drug discovery. ( 0,811398446152222 )
J Chem Inf Model - Identification of compounds with potential antibacterial activity against Mycobacterium through structure-based drug screening. ( 0,81114537600147 )
J Chem Inf Model - Identification of novel malarial cysteine protease inhibitors using structure-based virtual screening of a focused cysteine protease inhibitor library. ( 0,811144217078371 )
J Chem Inf Model - Combining horizontal and vertical substructure relationships in scaffold hierarchies for activity prediction. ( 0,811133005097402 )
J Chem Inf Model - Application of computer-aided drug repurposing in the search of new cruzipain inhibitors: discovery of amiodarone and bromocriptine inhibitory effects. ( 0,81054158982758 )
J Chem Inf Model - In silico enzymatic synthesis of a 400,000 compound biochemical database for nontargeted metabolomics. ( 0,810467297129332 )
J Chem Inf Model - Compound set enrichment: a novel approach to analysis of primary HTS data. ( 0,809968811216012 )
J Chem Inf Model - Identification of novel potential antibiotics against Staphylococcus using structure-based drug screening targeting dihydrofolate reductase. ( 0,809725928476158 )
J Chem Inf Model - From activity cliffs to activity ridges: informative data structures for SAR analysis. ( 0,808897373100217 )
J Chem Inf Model - Ligand- and structure-based virtual screening for clathrodin-derived human voltage-gated sodium channel modulators. ( 0,808054699123484 )
J Chem Inf Model - Identification of a new class of FtsZ inhibitors by structure-based design and in vitro screening. ( 0,807807588020261 )
Brief. Bioinformatics - State-of-the-art technology in modern computer-aided drug design. ( 0,807534508469175 )
J Chem Inf Model - Application of docking and QM/MM-GBSA rescoring to screen for novel Myt1 kinase inhibitors. ( 0,806961934704126 )
J Chem Inf Model - Identification of multitarget activity ridges in high-dimensional bioactivity spaces. ( 0,805217975795845 )
J Chem Inf Model - Pharmacophore-based virtual screening and experimental validation of novel inhibitors against cyanobacterial fructose-1,6-/sedoheptulose-1,7-bisphosphatase. ( 0,805171219813204 )
J Chem Inf Model - How diverse are diversity assessment methods? A comparative analysis and benchmarking of molecular descriptor space. ( 0,804901360315196 )
J Chem Inf Model - Capturing structure-activity relationships from chemogenomic spaces. ( 0,804120627141786 )
J Chem Inf Model - Increasing the coverage of medicinal chemistry-relevant space in commercial fragments screening. ( 0,803752137558203 )
J Chem Inf Model - Identification of sumoylation inhibitors targeting a predicted pocket in Ubc9. ( 0,803520485628073 )
J Chem Inf Model - Discovery of novel histamine H4 and serotonin transporter ligands using the topological feature tree descriptor. ( 0,802620402091148 )
J Chem Inf Model - Best of both worlds: on the complementarity of ligand-based and structure-based virtual screening. ( 0,80108914002862 )
J Chem Inf Model - Atom pair 2D-fingerprints perceive 3D-molecular shape and pharmacophores for very fast virtual screening of ZINC and GDB-17. ( 0,800867170541213 )
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. ( 0,800698432813899 )
J Chem Inf Model - Ligand and decoy sets for docking to G protein-coupled receptors. ( 0,800552475031827 )
J Chem Inf Model - How to improve docking accuracy of AutoDock4.2: a case study using different electrostatic potentials. ( 0,799967543058654 )
J Chem Inf Model - Navigating high-dimensional activity landscapes: design and application of the ligand-target differentiation map. ( 0,799819459633727 )
J Chem Inf Model - Visual characterization and diversity quantification of chemical libraries: 1. creation of delimited reference chemical subspaces. ( 0,797823395573224 )
J Chem Inf Model - Development of a minimal kinase ensemble receptor (MKER) for surrogate AutoShim. ( 0,796430927629589 )
J Chem Inf Model - A multivariate chemical similarity approach to search for drugs of potential environmental concern. ( 0,795675197939005 )
J Chem Inf Model - Mechanism-based discovery of novel substrates of haloalkane dehalogenases using in silico screening. ( 0,794873672848498 )
J Chem Inf Model - Design of a three-dimensional multitarget activity landscape. ( 0,79477598462654 )
J Chem Inf Model - De novo design of drug-like molecules by a fragment-based molecular evolutionary approach. ( 0,794347673849032 )
J Chem Inf Model - Fragment-based lead discovery and design. ( 0,793151971143518 )
J Chem Inf Model - Fighting high molecular weight in bioactive molecules with sub-pharmacophore-based virtual screening. ( 0,792675538490628 )
J Chem Inf Model - Structure-based fragment hopping for lead optimization using predocked fragment database. ( 0,791935733039843 )
J Chem Inf Model - Enumeration of 166 billion organic small molecules in the chemical universe database GDB-17. ( 0,790349436935962 )
J Chem Inf Model - Similarity searching for potent compounds using feature selection. ( 0,789873843550434 )
J Chem Inf Model - Chemoisosterism in the proteome. ( 0,789094502815503 )
J Chem Inf Model - Exploration of 3D activity cliffs on the basis of compound binding modes and comparison of 2D and 3D cliffs. ( 0,788826872514122 )
J Chem Inf Model - Detecting drug promiscuity using Gaussian ensemble screening. ( 0,788374602351432 )
J Chem Inf Model - Design of multitarget activity landscapes that capture hierarchical activity cliff distributions. ( 0,787729338786844 )
J Chem Inf Model - Predicting GPCR promiscuity using binding site features. ( 0,787689595682988 )
J Chem Inf Model - Structure-based virtual screening of the nociceptin receptor: hybrid docking and shape-based approaches for improved hit identification. ( 0,786607025732871 )
J Chem Inf Model - Scanning structure-activity relationships with structure-activity similarity and related maps: from consensus activity cliffs to selectivity switches. ( 0,786416799572091 )
J Chem Inf Model - Computational repositioning and experimental validation of approved drugs for HIF-prolyl hydroxylase inhibition. ( 0,785830435729075 )
J Chem Inf Model - Neighborhood-based prediction of novel active compounds from SAR matrices. ( 0,785491740664665 )
J Chem Inf Model - Discovery of novel tubulin inhibitors via structure-based hierarchical virtual screening. ( 0,784676399589119 )
J Chem Inf Model - Scaffold diversity of exemplified medicinal chemistry space. ( 0,784603976686259 )
J Chem Inf Model - Similarity boosted quantitative structure-activity relationship--a systematic study of enhancing structural descriptors by molecular similarity. ( 0,784493457823008 )
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. ( 0,784366318858261 )
J Chem Inf Model - Compound optimization through data set-dependent chemical transformations. ( 0,784138211947528 )
J Chem Inf Model - Comparison of virtual high-throughput screening methods for the identification of phosphodiesterase-5 inhibitors. ( 0,783603224933261 )