J Chem Inf Model - Application of the 4D fingerprint method with a robust scoring function for scaffold-hopping and drug repurposing strategies.

Tópicos

{ compound(1573) activ(1297) structur(1058) }
{ drug(1928) target(777) effect(648) }
{ measur(2081) correl(1212) valu(896) }
{ search(2224) databas(1162) retriev(909) }
{ model(2656) set(1616) predict(1553) }
{ result(1111) use(1088) new(759) }
{ gene(2352) biolog(1181) express(1162) }
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{ data(1737) use(1416) pattern(1282) }
{ assess(1506) score(1403) qualiti(1306) }
{ problem(2511) optim(1539) algorithm(950) }
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{ method(984) reconstruct(947) comput(926) }
{ visual(1396) interact(850) tool(830) }
{ group(2977) signific(1463) compar(1072) }
{ featur(3375) classif(2383) classifi(1994) }
{ model(2220) cell(1177) simul(1124) }
{ general(901) number(790) one(736) }
{ featur(1941) imag(1645) propos(1176) }
{ studi(1410) differ(1259) use(1210) }
{ imag(2830) propos(1344) filter(1198) }
{ treatment(1704) effect(941) patient(846) }
{ learn(2355) train(1041) set(1003) }
{ howev(809) still(633) remain(590) }
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{ monitor(1329) mobil(1314) devic(1160) }
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{ process(1125) use(805) approach(778) }
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{ detect(2391) sensit(1101) algorithm(908) }

Resumo

Two factors contribute to the inefficiency associated with screening pharmaceutical library collections as a means of identifying new drugs: [1] the limited success of virtual screening (VS) methods in identifying new scaffolds; [2] the limited accuracy of computational methods in predicting off-target effects. We recently introduced a 3D shape-based similarity algorithm of the SABRE program, which encodes a consensus molecular shape pattern of a set of active ligands into a 4D fingerprint descriptor. Here, we report a mathematical model for shape similarity comparisons and ligand database filtering using this 4D fingerprint method and benchmarked the scoring function HWK (Hamza-Wei-Korotkov), using the 81 targets of the DEKOIS database. Subsequently, we applied our combined 4D fingerprint and HWK scoring function VS approach in scaffold-hopping and drug repurposing using the National Cancer Institute (NCI) and Food and Drug Administration (FDA) databases, and we identified new inhibitors with different scaffolds of MycP1 protease from the mycobacterial ESX-1 secretion system. Experimental evaluation of nine compounds from the NCI database and three from the FDA database displayed IC50 values ranging from 70 to 100 ?M against MycP1 and possessed high structural diversity, which provides departure points for further structure-activity relationship (SAR) optimization. In addition, this study demonstrates that the combination of our 4D fingerprint algorithm and the HWK scoring function may provide a means for identifying repurposed drugs for the treatment of infectious diseases and may be used in the drug-target profile strategy.

Resumo Limpo

two factor contribut ineffici associ screen pharmaceut librari collect mean identifi new drug limit success virtual screen vs method identifi new scaffold limit accuraci comput method predict offtarget effect recent introduc d shapebas similar algorithm sabr program encod consensus molecular shape pattern set activ ligand d fingerprint descriptor report mathemat model shape similar comparison ligand databas filter use d fingerprint method benchmark score function hwk hamzaweikorotkov use target dekoi databas subsequ appli combin d fingerprint hwk score function vs approach scaffoldhop drug repurpos use nation cancer institut nci food drug administr fda databas identifi new inhibitor differ scaffold mycp proteas mycobacteri esx secret system experiment evalu nine compound nci databas three fda databas display ic valu rang m mycp possess high structur divers provid departur point structureact relationship sar optim addit studi demonstr combin d fingerprint algorithm hwk score function may provid mean identifi repurpos drug treatment infecti diseas may use drugtarget profil strategi

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