Proteochemometric model for predicting the inhibition of penicillin-binding proteins
2015 (English)In: Journal of Computer-Aided Molecular Design, ISSN 0920-654X, E-ISSN 1573-4951, Vol. 29, no 2, 127-141 p.Article in journal (Refereed) Published
Neisseria gonorrhoeae infection threatens to become an untreatable sexually transmitted disease in the near future owing to the increasing emergence of N. gonorrhoeae strains with reduced susceptibility and resistance to the extended-spectrum cephalosporins (ESCs), i.e. ceftriaxone and cefixime, which are the last remaining option for first-line treatment of gonorrhea. Alteration of the penA gene, encoding penicillin-binding protein 2 (PBP2), is the main mechanism conferring penicillin resistance including reduced susceptibility and resistance to ESCs. To predict and investigate putative amino acid mutations causing beta-lactam resistance particularly for ESCs, we applied proteochemometric modeling to generalize N. gonorrhoeae susceptibility data for predicting the interaction of PBP2 with therapeutic beta-lactam antibiotics. This was afforded by correlating publicly available data on antimicrobial susceptibility of wild-type and mutant N. gonorrhoeae strains for penicillin-G, cefixime and ceftriaxone with 50 PBP2 protein sequence data using partial least-squares projections to latent structures. The generated model revealed excellent predictability (R (2) = 0.91, Q (2) = 0.77, Q (Ext) (2) = 0.78). Moreover, our model identified amino acid mutations in PBP2 with the highest impact on antimicrobial susceptibility and provided information on physicochemical properties of amino acid mutations affecting antimicrobial susceptibility. Our model thus provided insight into the physicochemical basis for resistance development in PBP2 suggesting its use for predicting and monitoring novel PBP2 mutations that may emerge in the future.
Place, publisher, year, edition, pages
2015. Vol. 29, no 2, 127-141 p.
Penicillin-binding protein, Neisseria gonorrhoeae, Antimicrobial resistance, Extended-spectrum cephalosporins, Proteochemometric, Data mining
Medical Biotechnology (with a focus on Cell Biology (including Stem Cell Biology), Molecular Biology, Microbiology, Biochemistry or Biopharmacy) Biophysics
IdentifiersURN: urn:nbn:se:uu:diva-245349DOI: 10.1007/s10822-014-9809-0ISI: 000348190700003PubMedID: 25344841OAI: oai:DiVA.org:uu-245349DiVA: diva2:791434