J Chem Inf Model - AlzPlatform: an Alzheimer's disease domain-specific chemogenomics knowledgebase for polypharmacology and target identification research.

Tópicos

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

Resumo

Alzheimer's disease (AD) is one of the most complicated progressive neurodegeneration diseases that involve many genes, proteins, and their complex interactions. No effective medicines or treatments are available yet to stop or reverse the progression of the disease due to its polygenic nature. To facilitate discovery of new AD drugs and better understand the AD neurosignaling pathways involved, we have constructed an Alzheimer's disease domain-specific chemogenomics knowledgebase, AlzPlatform (www.cbligand.org/AD/ ) with cloud computing and sourcing functions. AlzPlatform is implemented with powerful computational algorithms, including our established TargetHunter, HTDocking, and BBB Predictor for target identification and polypharmacology analysis for AD research. The platform has assembled various AD-related chemogenomics data records, including 928 genes and 320 proteins related to AD, 194 AD drugs approved or in clinical trials, and 405,188 chemicals associated with 1,023,137 records of reported bioactivities from 38,284 corresponding bioassays and 10,050 references. Furthermore, we have demonstrated the application of the AlzPlatform in three case studies for identification of multitargets and polypharmacology analysis of FDA-approved drugs and also for screening and prediction of new AD active small chemical molecules and potential novel AD drug targets by our established TargetHunter and/or HTDocking programs. The predictions were confirmed by reported bioactivity data and our in vitro experimental validation. Overall, AlzPlatform will enrich our knowledge for AD target identification, drug discovery, and polypharmacology analyses and, also, facilitate the chemogenomics data sharing and information exchange/communications in aid of new anti-AD drug discovery and development.

Resumo Limpo

alzheim diseas ad one complic progress neurodegener diseas involv mani gene protein complex interact effect medicin treatment avail yet stop revers progress diseas due polygen natur facilit discoveri new ad drug better understand ad neurosign pathway involv construct alzheim diseas domainspecif chemogenom knowledgebas alzplatform wwwcbligandorgad cloud comput sourc function alzplatform implement power comput algorithm includ establish targethunt htdock bbb predictor target identif polypharmacolog analysi ad research platform assembl various adrel chemogenom data record includ gene protein relat ad ad drug approv clinic trial chemic associ record report bioactiv correspond bioassay refer furthermor demonstr applic alzplatform three case studi identif multitarget polypharmacolog analysi fdaapprov drug also screen predict new ad activ small chemic molecul potenti novel ad drug target establish targethunt andor htdock program predict confirm report bioactiv data vitro experiment valid overal alzplatform will enrich knowledg ad target identif drug discoveri polypharmacolog analys also facilit chemogenom data share inform exchangecommun aid new antiad drug discoveri develop

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