Lourdes Santana
University of Santiago de Compostela
245 Papers
1.6K Citations
Lourdes Santana is an academic researcher from University of Santiago de Compostela. The author has contributed to research in topics: Chemistry & Quantitative structure–activity relationship. The author has an hindex of 43, co-authored 242 publications. Previous affiliations of Lourdes Santana include University of Vigo & University of Santiago, Chile.
Chat about Author
Papers
Synthesis and Vasorelaxant Activity of New Coumarin and Furocoumarin Derivatives
TL;DR: A new series of coumarins and furocoumarins relax smooth vascular muscle with a profile similar to that of khellin and at a greater potency, suggesting that these compounds have a potential interest for the development of new and more efficient vasodilator drugs.
In silico studies toward the discovery of new anti-HIV nucleoside compounds with the use of TOPS-MODE and 2D/3D connectivity indices. 1. Pyrimidyl derivatives.
TL;DR: A QSAR model for the most active compounds was developed with the combined use of 2D and 3D connectivity indices, and this model explains 88% of the variance in the activity of these compounds in MT4 assay.
Quantitative structure-activity relationship and complex network approach to monoamine oxidase A and B inhibitors.
Lourdes Santana,Humberto González-Díaz,Elias Quezada,Eugenio Uriarte,Matilde Yáñez,Dolores Viña,Francisco Orallo +6 more
TL;DR: A new model for the prediction of the MAO-A and -B inhibitor activity by the use of combined complex networks and QSAR methodologies was obtained and the theoretical prediction was compared with the experimental activity data.
Synthesis and evaluation of antioxidant and trypanocidal properties of a selected series of coumarin derivatives.
Roberto Figueroa Guíñez,Maria João Matos,Saleta Vazquez-Rodriguez,Lourdes Santana,Eugenio Uriarte,Claudio Olea-Azar,Juan Diego Maya +6 more
TL;DR: In addition to the trypanocidal activity, this compound proved to have a very interesting antioxidant profile, as well as no cytotoxicity, which encouraged the authors to study the future structural optimization of this scaffold.
Probabilistic neural network model for the in silico evaluation of anti-HIV activity and mechanism of action.
TL;DR: A theoretical model that discriminates between active and nonactive drugs against HIV-1 with four different mechanisms of action for the active drugs and indicates that this approach may represent a powerful tool for modeling large databases in QSAR with applications in medicinal chemistry.