https://orcid.org/0000-0002-1558-0250
Abstract
Aim: Due to antibiotic resistance and the lack of investment in antimicrobial R&D, quantitative structure–activity relationship (SAR) methods appear as an ideal approach for the discovery of new antibiotics. Result & methodology: Molecular topology and linear discriminant analysis were used to construct a model to predict activity against Escherichia coli. This model establishes new SARs, of which, molecular size and complexity (Nclass), stand out for their discriminant power. This model was used for the virtual screening of the Index Merck database, with results showing a high success rate as well as a moderate restriction. Conclusion: The model efficiently finds new active compounds. The topological index Nclass can act as a filter in other quantitative structure–activity relationship models predicting activity against E. coli.
Supplementary data
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Financial & competing interests disclosure
The authors disclose funding from the Universidad CEU Cardenal Herrera (grant INDI 16/27, grant INDI 17/31 and grant INDI 18/34) and the ESI International Chair@CEU-UCH. The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.
No writing assistance was utilized in the production of this manuscript.