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MODEL QSAR SENYAWA FLUOROKUINOLON BARU SEBAGAI ZAT ANTIBAKTERI Salmonella thypimurium Eva Vaulina, Ponco Iswanto
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Modelling of novel Fluoroquinolone derivates as antibacterial compund of Salmonella thypimurium was conducted. The research was done as an initial step in discovering some new Fluoroquinolone compounds which have higher activity to Salmonella thypimurium. There are 16 compunds that use as the material of the research and they already have antibacterial activity data that expressed in Minimal Inhibitory Concentration (MIC, mg/mL). Calculation was performed by semiempirical AM1 method. The QSAR model was determined by multilinear regression analysis, with Log MIC as dependent variable and the independent variables are atomic net charges of C5 (qC5) and C7 (qC7), dipole moment (m), polarizability (a), n-octanol-water coefficien partition (Log P), molecular weight (Mw), and surface area of van der Waals (AvdW). The relationship between Log MIC and the descriptors which performed by statistical analysis is:(Log MIC) = -2.119 + 34.541(qC5) – 19.748(qC7) – 0.919polar + 1.170logP + 0.111(Mw) – 0.003(Avdw), with n =16, r = 0.907, r2 = 0.822, SD = 0.288, F calc = 6.938, F table = 3.374 , F calc/F table = 2.056 and PRESS = 0.749. The research can obtain the new coumpounds that modified from compound number 16 (etil fluoroquinolone, MIC prediction = 0.0354 mg/mL), (etil fluoroquinlone fosfate, 2.84. 10-19mg/mL), and (isopropyl fluoroquinlone, 0.1085 mg/mL), and compound number 2 (m-nitro fluoroquinolone sulfonat, 1.32. 10-11mg/mL). This results can be suggested to synthesis step.
Title: MODEL QSAR SENYAWA FLUOROKUINOLON BARU SEBAGAI ZAT ANTIBAKTERI Salmonella thypimurium Eva Vaulina, Ponco Iswanto
Description:
Modelling of novel Fluoroquinolone derivates as antibacterial compund of Salmonella thypimurium was conducted.
The research was done as an initial step in discovering some new Fluoroquinolone compounds which have higher activity to Salmonella thypimurium.
There are 16 compunds that use as the material of the research and they already have antibacterial activity data that expressed in Minimal Inhibitory Concentration (MIC, mg/mL).
Calculation was performed by semiempirical AM1 method.
The QSAR model was determined by multilinear regression analysis, with Log MIC as dependent variable and the independent variables are atomic net charges of C5 (qC5) and C7 (qC7), dipole moment (m), polarizability (a), n-octanol-water coefficien partition (Log P), molecular weight (Mw), and surface area of van der Waals (AvdW).
The relationship between Log MIC and the descriptors which performed by statistical analysis is:(Log MIC) = -2.
119 + 34.
541(qC5) – 19.
748(qC7) – 0.
919polar + 1.
170logP + 0.
111(Mw) – 0.
003(Avdw), with n =16, r = 0.
907, r2 = 0.
822, SD = 0.
288, F calc = 6.
938, F table = 3.
374 , F calc/F table = 2.
056 and PRESS = 0.
749.
The research can obtain the new coumpounds that modified from compound number 16 (etil fluoroquinolone, MIC prediction = 0.
0354 mg/mL), (etil fluoroquinlone fosfate, 2.
84.
10-19mg/mL), and (isopropyl fluoroquinlone, 0.
1085 mg/mL), and compound number 2 (m-nitro fluoroquinolone sulfonat, 1.
32.
10-11mg/mL).
This results can be suggested to synthesis step.
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