Comput Math Methods Med - Comparison of two methods forecasting binding rate of plasma protein.

Tópicos

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{ model(3480) simul(1196) paramet(876) }
{ bind(1733) structur(1185) ligand(1036) }
{ sequenc(1873) structur(1644) protein(1328) }
{ studi(1119) effect(1106) posit(819) }
{ drug(1928) target(777) effect(648) }
{ data(1737) use(1416) pattern(1282) }
{ measur(2081) correl(1212) valu(896) }
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{ age(1611) year(1155) adult(843) }
{ medic(1828) order(1363) alert(1069) }
{ signal(2180) analysi(812) frequenc(800) }
{ cost(1906) reduc(1198) effect(832) }
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{ gene(2352) biolog(1181) express(1162) }
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{ detect(2391) sensit(1101) algorithm(908) }

Resumo

By introducing the descriptors calculated from the molecular structure, the binding rates of plasma protein (BRPP) with seventy diverse drugs are modeled by a quantitative structure-activity relationship (QSAR) technique. Two algorithms, heuristic algorithm (HA) and support vector machine (SVM), are used to establish linear and nonlinear models to forecast BRPP. Empirical analysis shows that there are good performances for HA and SVM with cross-validation correlation coefficients Rcv(2) of 0.80 and 0.83. Comparing HA with SVM, it was found that SVM has more stability and more robustness to forecast BRPP.

Resumo Limpo

introduc descriptor calcul molecular structur bind rate plasma protein brpp seventi divers drug model quantit structureact relationship qsar techniqu two algorithm heurist algorithm ha support vector machin svm use establish linear nonlinear model forecast brpp empir analysi show good perform ha svm crossvalid correl coeffici rcv compar ha svm found svm stabil robust forecast brpp

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