Optimum Search Strategies or Novel 3D Molecular Descriptors: Is there a Stalemate?
The present manuscript describes a novel 3D-QSAR alignment free method (QuBiLS-MIDAS Duplex) based on algebraic bilinear, quadratic and linear forms on the k th two-tuple spatial-(dis)similarity matrix. Generalization schemes for the inter-atomic spatial distance using diverse (dis)-similarity...
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| Tác giả chính: | , , , , , , , , |
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| Định dạng: | Bài trích |
| Ngôn ngữ: | English |
| Thông tin xuất bản: |
2016
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| Chủ đề: | |
| Truy cập trực tuyến: | http://repository.vnu.edu.vn/handle/VNU_123/11502 |
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| Tóm tắt: | The present manuscript describes a novel 3D-QSAR alignment free method (QuBiLS-MIDAS Duplex) based on
algebraic bilinear, quadratic and linear forms on the k
th
two-tuple spatial-(dis)similarity matrix. Generalization schemes for the
inter-atomic spatial distance using diverse (dis)-similarity measures are discussed. On the other hand, normalization approaches
for the two-tuple spatial-(dis)similarity matrix by using simple- and double-stochastic and mutual probability schemes are
introduced. With the aim of taking into consideration particular inter-atomic interactions in total or local-fragment indices, path
and length cut-off constraints are used. Also, in order to generalize the use of the linear combination of atom-level indices to yield
global (molecular) definitions, a set of aggregation operators (invariants) are applied. A Shannon’s entropy based variability
study for the proposed 3D algebraic form-based indices and the DRAGON molecular descriptor families demonstrates superior
performance for the former. A principal component analysis reveals that the novel indices codify structural information
orthogonal to those captured by the DRAGON indices. Finally, a QSAR study for the binding affinity to the corticosteroid-binding globulin using Cramer’s steroid database is performed. From this study, it is revealed that the QuBiLS-MIDAS Duplex
approach yields similar-to-superior performance statistics than all the 3D-QSAR methods reported in the literature reported so
far, even with lower degree of freedom, using both the 31 steroids as the training set and the popular division of Cramer’s
database in training [1-21] and test sets [22-31]. It is thus expected that this methodology provides useful tools for the diversity
analysis of compound datasets and high-throughput screening structure–activity dat |
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