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A classical virtual combinatorial chemistry approach (CombiChem) was applied for combinatorial generation of 5590 novel structurally-similar 6-fluoroquinolone analogs by using a virtual synthetic pathway with selected primary (43) and secondary amines (130). The obtained virtual combinatoriallibrary was filtered using an in-house developed set of cheminformatics drug-likeness filters with pre-integrated Boolean options (TRUE/FALSE) for compounds reductionlselection. The retained number (304) of fluoroquinolone analogs (with TRUE outcome) defines the drug-like chemical space (CombiData). Quantitative structure-activity relationships (QSAR) study on these 304 virtually generated 6-fluoroquinolone analogs with unknown activity values was performed using a pre-built five-parameter multiple linearregression (MLR) model developed on a set of compounds with experimentally determined activity values (R" = 0.8417, R".cv= 0.7884). The obtained activity values for the unknown compounds together with the model results were used to define the applicability domain (AD). The obtainedAD offers a good graphical representation and establishment of structure-activityrelationships (SAR) which could be used for design of new 6-fluoroquinolones with possible better activity. Uporabili smo klasični pristop kombinatorične kemije (CombiChem), s katerim smo generirali 5590 novih, strukturnopodobnih 6-fluorokinolonskih analogov z virtualno sintezo z izbranimi primarnimi (43) in sekundarnimi (130) aminskimi substituenti. Tako dobljeno virtualno kombinatorično knjižnico smo filtirali z uporabo našega niza filtrov podobnosti- z -učinkovinami (drug-likeness) z vgrajenimi Booleovimi algebrajskimi operatorji (True/False) za redukcijo/selekcijo niza spojin. Preostali (304) fluorokinolonski analogi z opcijo True definirajo učinkovinam podobni kemijski prostor (CombiData). Kvantitativne relacije med strukturo in učinkovitostjo (QSAR) na teh virtualnih 304 6-fluorokinolonih z neznanimi vrednostmi za biološko aktivnost smo izračunali z vnaprej razvitim pet-parametrskim modelom na osnovi multiple linearne regresije (MLR) na nizu spojin z eksperimentalno določenimi aktivnostmi (Rtr = 0.8417, Rtr-cv= 0.7884). Dobljene vrednosti za aktivnosti neznanih spojin skupaj z rezultati iz modela smo uporabili za definicijo domene aplikabilnosti (AD). Tako dobljena domena aplikabilnosti nudi dobro grafično reprezentacijo in vpogled v relacije struktura-aktivnost za ta niz virtualnih molekul, kar je možno uporabiti za načrtovanje novih 6-fluorokinolonov s potencialno boljšo biološko aktivnostjo. |
