Naslov
Chemometric estimation of inhibitory activity of benzimidazole derivatives by linear least squares and artificial neural networks modelling

Autori
Podunavac-Kuzmanović, Sanja ; Kovačević, Strahinja ; Jevrić, Lidija ; Jokić, Stela

Vrsta, podvrsta i kategorija rada
Sažeci sa skupova, sažetak, znanstveni

Izvornik
17th International Conference on Climate Change and Global Warming / - , 2015, X-x

Skup
17th International Conference on Climate Change and Global Warming

Mjesto i datum
Stockholm, Švedska, 13.07.2015. - 14.07.2015

Vrsta sudjelovanja
Poster

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
Antibacterial ; benzimidazoles ; chemometric ; QSAR

Sažetak
The subject of this paper is to correlate antibacterial behavior of benzimidazole derivatives with their molecular characteristics using chemometric QSAR (Quantitative Structure–Activity Relationships) approach. QSAR analysis has been carried out on the inhibitory activity of benzimidazole derivatives against Staphylococcus aureus. The data were processed by linear least squares (LLS) and artificial neural network (ANN) procedures. The LLS mathematical models have been developed as a calibration models for prediction of the inhibitory activity. The quality of the models was validated by leave one out (LOO) technique and by using external data set. High agreement between experimental and predicted inhibitory acivities indicated the good quality of the derived models.

Izvorni jezik
Engleski

Znanstvena područja
Kemijsko inženjerstvo, Biotehnologija

POVEZANOST RADA