Papers by Emilia Daghir-wojtkowiak
Biomarkers in Medicine, 2015
We aimed at evaluation the potential diagnostic role of urinary nucleosides in urogenital tract c... more We aimed at evaluation the potential diagnostic role of urinary nucleosides in urogenital tract cancer. Concentrations of 12 nucleosides determined by LC-MS/MS were subjected to correlation, association and interaction analyses. We identified six pairs of nucleosides differently correlated in the group of patients and controls (p < 0.05). N-2-methylguanosine (odds ratio: 4.82; 95% CI: 1.78-12.93; p = 0.002) and N,N-dimethylguanosine (odds ratio: 5.45; 95% CI: 1.78-16.44; p = 0.003), were significantly associated with the disease risk (p-corrected = 0.004). Interaction between N-2-methylguanosine and adenosine (p-interaction = 0.019) suggested their multiplicative effect on the outcome. Urinary nucleosides, namely N,N-dimethylguanosine and N-2-methylguanosine may have the potential to serve as prognostic biomarkers. Gender-specific differences in urogenital tract cancer are likely to occur.
Combinatorial Chemistry & High Throughput Screening, 2015
Acridinone derivatives as imidazoacridinones and triazoloacridinones are the new potent antitumor... more Acridinone derivatives as imidazoacridinones and triazoloacridinones are the new potent antitumor agents characterized by different mechanisms of action related to their ability to interact with DNA. The analysis undertaken in this study involves searching of QSAR (Quantitative Structure-Activity Relationship) and QSRR (Quantitative Structure- Retention Relationship) models, which would allow to predict the biological activity of acridinones expressed as the ability to stabilize the secondary structure of DNA (ΔT), based on their structural parameters and chromatographic retention data. For this purpose, 20 acridinone derivatives were subjected to chromatographic analyses and molecular modeling, followed by statistical analyses using multiple linear regression method (MLR). As a novelty aspect, except for RP-HPLC approach, hydrophilic interaction chromatography (HILIC) columns were tested. As a result of performed analysis, appropriate QSAR and QSRR models were obtained, and each model was analyzed in terms of prediction of acridinones' ability to interact with DNA. Derived QSAR and QSRR models were characterized as one, with good prediction performance. Conclusively, the proposed connected QSAR and QSRR strategies allow to predict in silico the ability of acridinones to interact with DNA without the necessity of performing any biological experiments under in vitro and in vivo conditions.
Journal of Chromatography A, 2015
The objective of this study was to model the retention of nucleosides and pterins in hydrophilic ... more The objective of this study was to model the retention of nucleosides and pterins in hydrophilic interaction liquid chromatography (HILIC) via QSRR-based approach. Two home-made (Amino-P-C18, Amino-P-C10) and one commercial (IAM.PC.DD2) HILIC stationary phases were considered. Logarithm of retention factor at 5% of acetonitrile (logkACN) along with descriptors obtained for 16 nucleosides and 11 pterins were used to develop QSRR models. We used and compared the predictive performance of three regression techniques: partial least square (PLS), the least absolute shrinkage and selection operator (LASSO), and the LASSO followed by stepwise multiple linear regression. The highest predictive squared correlation coefficient (QLOOCV(2)) in PLS analysis was found for Amino-P-C10 (QLOOCV(2)=0.687) and IAM.PC.DD2 (QLOOCV(2)=0.506) and the lowest for IAM.PC.DD2 (QLOOCV(2)=-0.01). Much higher values were obtained for the LASSO model. The QLOOCV(2) equaled 0.9 for Amino-P-C10, 0.66 for IAM.PC.DD2 and 0.59 for Amino-P-C18. The combination of LASSO with stepwise regression provided models with comparable predictive performance as the LASSO, however with possibility of calculating the standard error of estimates. The use of LASSO itself and in combination with classical stepwise regression may offer greater stability of the developed models thanks to more smooth change of coefficients and reduced susceptibility towards chance correlation. Application of QSRR-based approach, along with the computational methods proposed in this work, may offer a useful approach in the modeling of retention of nucleoside and pterin compounds in HILIC.
Uploads
Papers by Emilia Daghir-wojtkowiak