Pregled bibliografske jedinice broj: 1134297
Antimicrobial activity of quasi-enantiomeric cinchona alkaloid derivatives and prediction model developed by machine learning
Antimicrobial activity of quasi-enantiomeric cinchona alkaloid derivatives and prediction model developed by machine learning // Antibiotics, 10 (2021), 6; 659, 15 doi:10.3390/antibiotics10060659 (međunarodna recenzija, članak, znanstveni)
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Naslov
Antimicrobial activity of quasi-enantiomeric
cinchona alkaloid derivatives and prediction model
developed by machine learning
Autori
Ramić, Alma ; Skočibušić, Mirjana ; Odžak, Renata ; Čipak Gašparović, Ana ; Milković, Lidija ; Mikelić, Ana ; Sović, Karlo ; Primožič, Ines ; Hrenar, Tomica
Izvornik
Antibiotics (2079-6382) 10
(2021), 6;
659, 15
Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni
Ključne riječi
quaternary cinchonidines ; quaternary cinchonines ; antimicrobial activity ; cytotoxicity ; ROS ; activity/PES model ; machine learning
Sažetak
Bacterial infections that do not respond to current treatments are increasing, thus there is a need for the development of new antibiotics. Series of 20 N-substituted quaternary salts of cinchonidine (CD) and their quasi-enantiomer cinchonine (CN) were prepared and their antimicrobial activity was assessed against a diverse panel of Gram-positive and Gram-negative bacteria. All tested compounds showed good antimicrobial potential (minimum inhibitory concentration (MIC) values 1.56 to 125.00 μg/mL), proved to be nontoxic to different human cell lines, and did not influence the production of reactive oxygen species (ROS). Seven compounds showed very strong bioactivity against some of the tested Gram-negative bacteria (MIC for E. coli and K. pneumoniae 6.25 μg/mL ; MIC for P. aeruginosa 1.56 μg/mL). To establish a connection between antimicrobial data and potential energy surfaces (PES) of the compounds, activity/PES models using principal components of the disc diffusion assay and MIC and data towards PES data were built. An extensive machine learning procedure for the generation and cross- validation of multivariate linear regression models with a linear combination of original variables as well as their higher- order polynomial terms was performed. The best possible models with predicted R2(CD derivatives) = 0.9979 and R2(CN derivatives) = 0.9873 were established and presented. This activity/PES model can be used for accurate prediction of activities for new compounds based solely on their potential energy surfaces, which will enable wider screening and guided search for new potential leads. Based on the obtained results, N-quaternary derivatives of Cinchona alkaloids proved to be an excellent scaffold for further optimization of novel antibiotic species.
Izvorni jezik
Engleski
Znanstvena područja
Kemija, Biologija
POVEZANOST RADA
Projekti:
HRZZ-IP-2016-06-3775 - Aktivnošću i in silico usmjeren dizajn malih bioaktivnih molekula (ADESIRE) (Hrenar, Tomica, HRZZ - 2016-06) ( CroRIS)
Ustanove:
Institut "Ruđer Bošković", Zagreb,
Prirodoslovno-matematički fakultet, Zagreb,
Prirodoslovno-matematički fakultet, Split
Profili:
Ana Mikelić (autor)
Tomica Hrenar (autor)
Mirjana Skočibušić (autor)
Renata Odžak (autor)
Ana Čipak Gašparović (autor)
Lidija Milković (autor)
Ines Primožič (autor)
Alma Ramic (autor)
Karlo Sović (autor)
Citiraj ovu publikaciju:
Časopis indeksira:
- Web of Science Core Collection (WoSCC)
- Science Citation Index Expanded (SCI-EXP)
- SCI-EXP, SSCI i/ili A&HCI
- Scopus