Density functional theory （DFT） was used to calculate a set of molecular descri ptors （properties） for 14 fluoroquinolones with anti-B.fragilis activity. Principal component analysis （PCA） and hierarchical clust...Density functional theory （DFT） was used to calculate a set of molecular descri ptors （properties） for 14 fluoroquinolones with anti-B.fragilis activity. Principal component analysis （PCA） and hierarchical cluster analysis （HCA） were employed in order to reduce dimensionality and investigate which subset of variables should be more effective for classifying fluoroquinolones according to their an-B.fragilis activity degree. The PCA shows that the variables of ELUMO, AEHL, μ, Q2, Q3, Q5, Q6, QB, LogP, MR and MP are responsible for the separation between compounds with higher and lower anti-B.fragilis activities. The HCA results are similar to those obtained with PCA. By using the chemometric results, 4 synthetic compounds were analyzed through PCA and HCA, and 2 of them are proposed as active molecules against B.fragilis, which is consistent with the results of clinic experiments. The methodologies of PCA and HCA provide a reliable rule for classifying new fluoroquinolones with anti-B.fragilis activity.展开更多
Structure-activity relationship techniques were employed to classify fluoroquinolones against S.pneumoniae. Density functional theory （DFT） was used to calculate a set of molecular descriptors （properties） for eig...Structure-activity relationship techniques were employed to classify fluoroquinolones against S.pneumoniae. Density functional theory （DFT） was used to calculate a set of molecular descriptors （properties） for eighteen fluoroquinolones. The descriptors were further analyzed using the principal component analysis （PCA）, hierarchical cluster analysis （HCA） and K-nearest neighbor （KNN） chemometeric method. The PCA and HCA methods are quite efficient to classify the eighteen compounds into two groups （active and inactive） according to their degrees of anti- S.pneumoniae activity. The classified result is consistent with the clinic experimental result. The PCA shows that the variables Q3 （net charge on atom 3）, QA （net charge on ring A）, QB （net charge on ring B）, VOL （molecular volume） and A （surface area） are found to be responsible for the separation between compounds with higher and lower anti-S.pneumoniae.展开更多
Density functional theory （DFT） was used to calculate a set of molecular descriptors （properties） for 14 TIBO derivatives with anti-HIV activity. Principal component analysis （PCA） and hierarchical cluster analy...Density functional theory （DFT） was used to calculate a set of molecular descriptors （properties） for 14 TIBO derivatives with anti-HIV activity. Principal component analysis （PCA） and hierarchical cluster analysis （HCA） were employed in order to reduce dimensionality and investigate which subset of variables should be more effective for classifying TIBO derivatives according to their degree of anti-HIV activity. The PCA showed that the EHOMO, μ, LogP, QA, QB and MR variables are responsible for the separation between compounds with higher and lower anti-HIV activity. The HCA results are similar to those obtained with PCA. By using the chemometric results, four synthetic compounds were analyzed through PCA and HCA and three of them are proposed as active molecules against HIV, which is consistent with the results of clinic experiments. The methodologies of PCA and HCA provide a reliable rule for classifying new TIBO derivatives with anti-HIV activity. The model obtained showed not only statistical significance but also predictive ability.展开更多
基金The project was supported by the National Natural Science Foundation of China (No. 10574096)
文摘Density functional theory （DFT） was used to calculate a set of molecular descri ptors （properties） for 14 fluoroquinolones with anti-B.fragilis activity. Principal component analysis （PCA） and hierarchical cluster analysis （HCA） were employed in order to reduce dimensionality and investigate which subset of variables should be more effective for classifying fluoroquinolones according to their an-B.fragilis activity degree. The PCA shows that the variables of ELUMO, AEHL, μ, Q2, Q3, Q5, Q6, QB, LogP, MR and MP are responsible for the separation between compounds with higher and lower anti-B.fragilis activities. The HCA results are similar to those obtained with PCA. By using the chemometric results, 4 synthetic compounds were analyzed through PCA and HCA, and 2 of them are proposed as active molecules against B.fragilis, which is consistent with the results of clinic experiments. The methodologies of PCA and HCA provide a reliable rule for classifying new fluoroquinolones with anti-B.fragilis activity.
文摘Structure-activity relationship techniques were employed to classify fluoroquinolones against S.pneumoniae. Density functional theory （DFT） was used to calculate a set of molecular descriptors （properties） for eighteen fluoroquinolones. The descriptors were further analyzed using the principal component analysis （PCA）, hierarchical cluster analysis （HCA） and K-nearest neighbor （KNN） chemometeric method. The PCA and HCA methods are quite efficient to classify the eighteen compounds into two groups （active and inactive） according to their degrees of anti- S.pneumoniae activity. The classified result is consistent with the clinic experimental result. The PCA shows that the variables Q3 （net charge on atom 3）, QA （net charge on ring A）, QB （net charge on ring B）, VOL （molecular volume） and A （surface area） are found to be responsible for the separation between compounds with higher and lower anti-S.pneumoniae.
基金The project was supported by the National Natural Science Foundation of China (No. 10574096)
文摘Density functional theory （DFT） was used to calculate a set of molecular descriptors （properties） for 14 TIBO derivatives with anti-HIV activity. Principal component analysis （PCA） and hierarchical cluster analysis （HCA） were employed in order to reduce dimensionality and investigate which subset of variables should be more effective for classifying TIBO derivatives according to their degree of anti-HIV activity. The PCA showed that the EHOMO, μ, LogP, QA, QB and MR variables are responsible for the separation between compounds with higher and lower anti-HIV activity. The HCA results are similar to those obtained with PCA. By using the chemometric results, four synthetic compounds were analyzed through PCA and HCA and three of them are proposed as active molecules against HIV, which is consistent with the results of clinic experiments. The methodologies of PCA and HCA provide a reliable rule for classifying new TIBO derivatives with anti-HIV activity. The model obtained showed not only statistical significance but also predictive ability.
