TOPS-MODE based QSARs derived from heterogeneous series of compounds. Applications to the design of new herbicides |
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Authors: | Pérez González Maykel Gonzalez Díaz Humberto Molina Ruiz Reinaldo Cabrera Miguel A Ramos de Armas Ronal |
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Affiliation: | Chemical Bioactives Center, Central University of Las Villas, Santa Clara, C. P. 54830, Villa Clara, Cuba. maykel@cbq.uclv.edu.cu |
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Abstract: | A new application of TOPological Sub-structural MOlecular DEsign (TOPS-MODE) was carried out in herbicides using computer-aided molecular design. Two series of compounds, one containing herbicide and the other containing nonherbicide 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 herbicides from the nonherbicide compounds was developed. The model correctly and clearly classified 88% of active and 94% of inactive compounds in the training set. More specifically, the model showed a good global classification of 91%, i.e., (168 cases out of 185). While in the prediction set, they showed an overall predictability of 91% and 92% for active and inactive compounds, being the global percentage of good classification of 92%. To assess the range of model applicability, a virtual screening of structurally heterogeneous series of herbicidal compounds was carried out. Two hundred eighty-four out of 332 were correctly classified (86%). Furthermore this paper describes a fragment analysis in order to determine the contribution of several fragments toward herbicidal 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 herbicides discovery. |
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