TOPS-MODE based QSARs derived from heterogeneous series of compounds. Applications to the design of new anti-inflammatory compounds.
A new application of TOPological Sub-structural MOlecular DEsign (TOPS-MODE) was carried out in anti-inflammatory compounds using computer-aided molecular design. Two series of compounds, one containing anti-inflammatory and the other containing nonanti-inflammatory compounds were processed by a k-means cluster analysis in order to design the training and prediction sets. A linear classification function to discriminate the anti-inflammatory from the inactive compounds was developed. The model correctly and clearly classified 88% of active and 91% of inactive compounds in the training set. More specifically, the model showed a good global classification of 90%, that is, (399 cases out of 441). While in the prediction set, they showed an overall predictability of 88% and 84% for active and inactive compounds, being the global percentage of good classification of 85%. Furthermore this paper describes a fragment analysis in order to determine the contribution of several fragments towards anti-inflammatory property, also the present of halogens in the selected fragments were analyzed. It seems that the present TOPS-MODE based QSAR is the first alternate general 'in silico' technique to experimentation in anti-inflammatory discovery.
Pérez González
Maykel
M
Unit of Service, Drug Design Department, Experimental Sugar Cane Station Villa Clara-Cienfuegos, Villa Clara, Ranchuelo 53100, Cuba. mpgonzalez76@yahoo.es
Dias
Luiz Carlos
LC
Helguera
Aliuska Morales
AM
Rodríguez
Yanisleidy Morales
YM
de Oliveira
Luciana Gonzaga
LG
Gomez
Luis Torres
LT
Diaz
Humberto Gonzalez
HG
D000893:Anti-Inflammatory Agents / Q000737:chemistry* / Q000494:pharmacology; D016000:Cluster Analysis; D017076:Computer-Aided Design; D015195:Drug Design; D021281:Quantitative Structure-Activity Relationship
D000893:Anti-Inflammatory Agents