Prado Prado, Francisco JavierGonzález Díaz, HumbertoSantana Penín, María LourdesUriarte Villares, Eugenio2021-08-182021-08-182007Prado-Prado, F.J.; Gonzàlez-Dìaz, H.; Santana, L.; Uriarte, E. QSAR & Network-based multi-species activity models for antifungals, in Proceedings of the 11th International Electronic Conference on Synthetic Organic Chemistry, 1–30 November 2007, MDPI: Basel, Switzerland, doi:10.3390/ecsoc-11-013723-906980-19-7http://hdl.handle.net/10347/26827The 11th International Electronic Conference on Synthetic Organic Chemistry session Computational ChemistryThere are many pathogen microbial species with very different antimicrobial drugs susceptibility. In this work, we selected pairs of antifungal drugs with similar/dissimilar species predicted-activity profile and represented it as a large network, which may be used to identify drugs with similar mechanism of action. Computational chemistry prediction of the biological activity based on quantitative structure-activity relationships (QSAR) susbtantialy increases the potentialities of this kind of networks avoiding time and resources consming experiments. Unfortunately, almost QSAR models are unspecific or predict activity against only one species. To solve this problem we developed here a multi-species QSAR classification model, which outputs were the inputs of the above-mentioned network. Overall model classification accuracy was 87.0% (161/185 compounds) in training, 83.4% (50/61) in validation, and 83.7% for 288 additional antifungal compounds used to extent model validation for network construction. The network predicted has 59 nodes (compounds), 648 edges (pairs of compounds with similar activity), low coverage density d = 37.8%, and distribution more close to normal than to exponential. These results are more characteristic of a not-overestimated random network, clustering different drug mechanisms of actions, than of a less useful power-law network with few mechanisms (network hubs)eng© 2007 The author(s). Published by MDPI, Basel, Switzerland. Open AccessMolecular descriptorMarkov modelNetworksQSARCo-expression networkProbabilityAntimicrobialsAntifungalsbook part10.3390/ecsoc-11-01372open access