| dc.creator | Braga, R S | |
| dc.creator | Vendrame, R | |
| dc.creator | Galvão, D S | |
| dc.date | | |
| dc.date | 2015-11-27T12:22:48Z | |
| dc.date | 2015-11-27T12:22:48Z | |
| dc.date.accessioned | 2018-03-29T00:54:36Z | |
| dc.date.available | 2018-03-29T00:54:36Z | |
| dc.identifier | Journal Of Chemical Information And Computer Sciences. v. 40, n. 6, p. 1377-85 | |
| dc.identifier | 0095-2338 | |
| dc.identifier | | |
| dc.identifier | http://www.ncbi.nlm.nih.gov/pubmed/11128096 | |
| dc.identifier | http://repositorio.unicamp.br/jspui/handle/REPOSIP/194646 | |
| dc.identifier | 11128096 | |
| dc.identifier.uri | http://repositorioslatinoamericanos.uchile.cl/handle/2250/1294879 | |
| dc.description | Recently a new methodology, called electronic indices methodology (EIM), based on local density of state calculations (LDOS) using topological and semiempirical methods, was proposed to identify the biological activity of polycyclic aromatic hydrocarbons (PAHs). In this work we apply the concepts of the EIM approach to classify the progestational activity of 21 17alpha-acetoxyprogesterones (steroid hormones) (APs). The EIM approach pointed to a few descriptors, which correctly classify the active/inactive compounds of this class (approximately 90%). We show that these descriptors arise naturally from principal component analysis (PCA) and neural network (NN) calculations. Moreover, using only the parameters from EIM, instead of a large set of descriptors that have been used before to describe the biological activity of these hormones, we slightly improve and simplify PCA and NN results. Finally, the molecular region related to the chemical activity of these hormones naturally appears in our theoretical analysis, from the local density of states of the frontier orbitals. This shows the generality of the principles of EIM approach, and confirms that the combination of these distinct methodologies can be an efficient and powerful tool in the structure-activity studies of many different classes of compounds. | |
| dc.description | 40 | |
| dc.description | 1377-85 | |
| dc.language | eng | |
| dc.relation | Journal Of Chemical Information And Computer Sciences | |
| dc.relation | J Chem Inf Comput Sci | |
| dc.rights | fechado | |
| dc.rights | | |
| dc.source | PubMed | |
| dc.subject | Hydrogen-ion Concentration | |
| dc.subject | Hydroxyprogesterones | |
| dc.subject | Molecular Structure | |
| dc.subject | Neural Networks (computer) | |
| dc.subject | Structure-activity Relationship | |
| dc.title | Structure--activity Relationship Studies Of Substituted 17alpha-acetoxyprogesterone Hormones. | |
| dc.type | Artículos de revistas | |
