Considering atomic property vector and atomic correlative function, the 3-dimensional structural vector of atomic property correlation （3D-VAPC）, a novel descriptor,is defined to characterize a 3-dimensional molecul...Considering atomic property vector and atomic correlative function, the 3-dimensional structural vector of atomic property correlation （3D-VAPC）, a novel descriptor,is defined to characterize a 3-dimensional molecular structure by introducing self-adaptability regulation mechanism and the idea of orientating to customers. Characterizing the structures of 25 bisphenol A compounds by this vector, the QSAR models of three kinds of estrogen activities （ER affinities, gene induction and cell proliferation） have high multiple correlation coefficient （Rcum^2=0.933, 0.813, 0.959） and cross verification coefficient （Qcum^2=0.847, 0.953, 0.798） by support vector machine （SVM）, which suits for nonlinear circumstances. The above results show that the models successfully express the correlation between structure and three kinds of estrogen activities. Therefore, 3D-VAPC exactly reflects the molecular structural information and SVM method correctly describes the correlation between information and property of the compounds.展开更多
Gout is caused by the deposition of uric acid as monosodium urate（MSU）. Chronic hyperuricemia is the necessary condition for MSU deposition, which arises from over-production and/or under-excretion of uric acid. Ren...Gout is caused by the deposition of uric acid as monosodium urate（MSU）. Chronic hyperuricemia is the necessary condition for MSU deposition, which arises from over-production and/or under-excretion of uric acid. Renal under-excretion of uric acid accounts for greater than 90% of the patients with hyperuricemia, making URAT1 inhibitors, which act through uricosuric effect a promising class of urate-lowering therapy（ULT）. This review aims at the summary and discussion of the latest development of URAT1 inhibitors for the treatment of hyperuricemia and gout and providing an insight into their structure-activity relationship（SAR）, which will be helpful to the design of URAT1 inhibitors for both academic research and pharmaceutical industry. The current development pipeline of URAT1 inhibitors is promising and encouraging.展开更多
In this document, we present new techniques for near-lossless and lossy compression of SAR imagery saved in PNG and binary formats of magnitude and phase data based on the application of transforms, dimensionality red...In this document, we present new techniques for near-lossless and lossy compression of SAR imagery saved in PNG and binary formats of magnitude and phase data based on the application of transforms, dimensionality reduction methods, and lossless compression. In particular, we discuss the use of blockwise integer to integer transforms, subsequent application of a dimensionality reduction method, and Burrows-Wheeler based lossless compression for the PNG data and the use of high correlation based modeling of sorted transform coefficients for the raw floating point magnitude and phase data. The gains exhibited are substantial over the application of different lossless methods directly on the data and competitive with existing lossy approaches. The methods presented are effective for large scale processing of similar data formats as they are heavily based on techniques which scale well on parallel architectures.展开更多
The support vector classification （SVC） was employed to make a model for classification of antifungal activities of 1-（1H-1,2,4-triazole-l-yl）-2-（2,4-difluorophenyl）-3-substituted-2-propanols triazole derivative...The support vector classification （SVC） was employed to make a model for classification of antifungal activities of 1-（1H-1,2,4-triazole-l-yl）-2-（2,4-difluorophenyl）-3-substituted-2-propanols triazole derivatives. The compounds with high antifungal activities and those with low antifungal activities were compared on the basis of the following molecular descriptors： net atomic charge on the atom N connecting with R, dipole moment and heat of formation, By using the SVC, a mathematical model was constructed, which can predict the antifungal activities of the triazole derivatives, with an accuracy of 91% on the basis of the leave-one-out cross-validation （LOOCV） test, The results indicate that the performance of the SVC model can exceed that of the principal component analysis （PCA） and K-Nearest Neighbor （KNN） models for this real world data set.展开更多
基金This work was supported by the Natural Science Foundation of CQ CSTC (No. 2006BB5177)
文摘Considering atomic property vector and atomic correlative function, the 3-dimensional structural vector of atomic property correlation （3D-VAPC）, a novel descriptor,is defined to characterize a 3-dimensional molecular structure by introducing self-adaptability regulation mechanism and the idea of orientating to customers. Characterizing the structures of 25 bisphenol A compounds by this vector, the QSAR models of three kinds of estrogen activities （ER affinities, gene induction and cell proliferation） have high multiple correlation coefficient （Rcum^2=0.933, 0.813, 0.959） and cross verification coefficient （Qcum^2=0.847, 0.953, 0.798） by support vector machine （SVM）, which suits for nonlinear circumstances. The above results show that the models successfully express the correlation between structure and three kinds of estrogen activities. Therefore, 3D-VAPC exactly reflects the molecular structural information and SVM method correctly describes the correlation between information and property of the compounds.
基金Supported by Key Projects of Tianjin Science and Technology Support Plan(16YFZCSY00910)Natural Science Foundation of Shandong Province(ZR2015BM028)
文摘Gout is caused by the deposition of uric acid as monosodium urate（MSU）. Chronic hyperuricemia is the necessary condition for MSU deposition, which arises from over-production and/or under-excretion of uric acid. Renal under-excretion of uric acid accounts for greater than 90% of the patients with hyperuricemia, making URAT1 inhibitors, which act through uricosuric effect a promising class of urate-lowering therapy（ULT）. This review aims at the summary and discussion of the latest development of URAT1 inhibitors for the treatment of hyperuricemia and gout and providing an insight into their structure-activity relationship（SAR）, which will be helpful to the design of URAT1 inhibitors for both academic research and pharmaceutical industry. The current development pipeline of URAT1 inhibitors is promising and encouraging.
文摘In this document, we present new techniques for near-lossless and lossy compression of SAR imagery saved in PNG and binary formats of magnitude and phase data based on the application of transforms, dimensionality reduction methods, and lossless compression. In particular, we discuss the use of blockwise integer to integer transforms, subsequent application of a dimensionality reduction method, and Burrows-Wheeler based lossless compression for the PNG data and the use of high correlation based modeling of sorted transform coefficients for the raw floating point magnitude and phase data. The gains exhibited are substantial over the application of different lossless methods directly on the data and competitive with existing lossy approaches. The methods presented are effective for large scale processing of similar data formats as they are heavily based on techniques which scale well on parallel architectures.
基金Project supported by the National Natural Science Foundation of China （Grant Nos.20373040, 20503015）
文摘The support vector classification （SVC） was employed to make a model for classification of antifungal activities of 1-（1H-1,2,4-triazole-l-yl）-2-（2,4-difluorophenyl）-3-substituted-2-propanols triazole derivatives. The compounds with high antifungal activities and those with low antifungal activities were compared on the basis of the following molecular descriptors： net atomic charge on the atom N connecting with R, dipole moment and heat of formation, By using the SVC, a mathematical model was constructed, which can predict the antifungal activities of the triazole derivatives, with an accuracy of 91% on the basis of the leave-one-out cross-validation （LOOCV） test, The results indicate that the performance of the SVC model can exceed that of the principal component analysis （PCA） and K-Nearest Neighbor （KNN） models for this real world data set.
