Biomedical subjects

Lluís Amat

Publications and source records attributed to Lluís Amat.

3 recordsLinked to original sources

PubMed2002

Molecular quantum similarity and the fundamentals of QSAR.

A general overview on quantum similarity and applications to QSAR is presented. The concepts regarding quantum similarity from its theoretical foundation and consecutive development, involving mathematical formulation and similarity measures, are presented and complemented with application examples. The practical part, based on the well-known Crammer 31 steroids set, covers approximate quantum similarity calculations, molecular superposition, and statistics. In this way, the reader will find both basic general information and applicability of quantum similarity.

Animals↗

PubMedDate not supplied

Modeling large macromolecular structures using promolecular densities.

A procedure to easily construct fitted density functions is presented. This methodology, based on the promolecule approach, is able to handle large macromolecular systems, such as proteins. The usual procedure dealing with fitted densities has been improved by adding some restrictions, which allow faster calculations. As a main application example, molecular isodensity contours (MIDCOs) are constructed for two proteins, one of them composed of more than 50 000 atoms. MIDCOs, as a visual representation of the molecular density function, and thus an important descriptor of the molecular charge distribution, constitute a powerful tool in the understanding of molecular systems. MIDCOs are presented for both proteins, allowing exploration of their surfaces, as well as analysis of their shapes. Also, as a quantum mechanical calculation example, molecular quantum self-similarity measures are calculated for several proteins.

Computer Simulation↗

PubMedDate not supplied

Molecular quantum similarity analysis of estrogenic activity.

The main objective of this study was to evaluate the capability of 120 aromatic chemicals to bind to the human alpha estrogen receptor (hER alpha) by the use of quantum similarity methods. The experimental data were segregated into two categories, i.e., those compounds with and without estrogenicity activity (active and inactive). To identify potential ligands, semiquantitative structure-activity relationships were developed for the complete set correlating the presence or lack of binding affinity to the estrogen receptor with structural features of the molecules. The structure-activity relationships were based upon molecular similarity indices, which implicitly contain information related to changes in the electron distributions of the molecules, along with indicator variables, accounting for several structural features. In addition, the whole set was split into several chemical classes for modeling purposes. Models were validated by dividing the complete set into several training and test sets to allow for external predictions to be made.

Estrogens, Non-Steroidal↗