Authors: Francisco Torrens, Gloria Castellano
Addresses: Institut Universitari de Ciencia Molecular, Universitat de Valencia, Edifici d'Instituts de Paterna, P. O. Box 22085, E-46071 Valencia, Spain. ' Instituto Universitario de Medio Ambiente y Ciencias Marinas, Universidad Catolica de Valencia San Vicente Martir, Guillem de Castro-94, E-46003 Valencia, Spain
Abstract: Classification algorithms are proposed based on information entropy. The feasibility of mixing a given human immunodeficiency virus (HIV) inhibitor with dissimilar ones is studied. The 31 inhibitors are classified by their structural chemical properties. Many classification algorithms are based on information entropy. An excessive number of results appear compatible with the data and suffer combinatorial explosion. However, after the equipartition conjecture one has a selection criterion. According to this conjecture, the best configuration is that in which entropy production is most uniformly distributed. The structural elements of an inhibitor can be ranked according to their inhibitory activity. In didanosine (ddI) the base is a guanine derivative and the furan contains only one O heteroatom; ddI is selected as reference. In most inhibitors the furan contains one O heteroatom. The analysis is in agreement with principal component analysis and compares well with other classification taken as good based on docking, etc.
Keywords: periodic properties; periodic table; periodic law; classification; information entropy; equipartition conjecture; HIV-1 reverse transcriptase inhibitors; human immunodeficiency virus; HIV inhibitors.
International Journal of Computational Intelligence in Bioinformatics and Systems Biology, 2010 Vol.1 No.3, pp.246 - 273
Published online: 02 Feb 2010 *Full-text access for editors Access for subscribers Purchase this article Comment on this article