| 1. |
- Andersson, Patrik, et al.
(författare)
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General and Class Specific Models for Prediction of Soil Sorption Using Various Physicochemical Descriptors
- 2002
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Ingår i: Journal of Chemical Information and Modeling. - : American Chemical Society (ACS). - 0095-2338. ; 42:6, s. 1450-9
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Tidskriftsartikel (refereegranskat)abstract
- Diverse chemical descriptors were explored for use in QSAR models aimed to screen the soil sorption potential of organic compounds. The descriptors included logP, HyperChem QSARProperties descriptors, a combination of connectivity indices, geometrical, and quantum chemical measures, and two sets from the DRAGON and CODESSA program packages, respectively. Generally, the univariate logP models were capable of capturing most of the variation and give an indication of the sorption potential. The multivariate models required refined variable selection procedures but were shown to include crucial descriptors for modeling compound classes with specific chemical characteristics.
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| 2. |
- Dowaidar, Moataz, et al.
(författare)
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Refinement of a Quantitative Structure–Activity Relationship Model for Prediction of Cell-Penetrating Peptide Based Transfection Systems
- 2017
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Ingår i: International Journal of Peptide Research and Therapeutics. - : Springer Science and Business Media LLC. - 1573-3904 .- 1573-3149. ; 23:1, s. 91-100
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Tidskriftsartikel (refereegranskat)abstract
- Cell-penetrating peptide (CPP) based transfection systems (PBTS) are a promising class of drug delivery vectors. CPPs are short mainly cationic peptides capable of delivering cell non-permeant cargo to the interior of the cell. Some CPPs have the ability to form non-covalent complexes with oligonucleotides for gene therapy applications. In this study, we use quantitative structure–activity relationships (QSAR), a statistical method based on regression data analysis. Here, a fragment QSAR (FQSAR) model is developed to predict new peptides based on standard alpha helical conformers and Assisted Model Building with Energy Refinement molecular mechanics simulations of previous peptides. These new peptides were examined for plasmid transfection efficiency and compared with their predicted biological activity. The best predicted peptides were capable of achieving plasmid transfection with significant improvement compared to the previous generation of peptides. Our results demonstrate that FQSAR model refinement is an efficient method for optimizing PBTS for improved biological activity.
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| 3. |
- Hällbrink, Mattias, et al.
(författare)
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Prediction of Cell-Penetrating Peptides
- 2015
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Ingår i: Cell-Penetrating Peptides. - New York, NY : Springer-Verlag New York. - 9781493928057 - 9781493928064 ; , s. 39-58
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Bokkapitel (refereegranskat)abstract
- The in silico methods for the prediction of the cell-penetrating peptides are reviewed. Those include the multivariate statistical methods, machine-learning methods such as the artificial neural networks and support vector machines, and molecular modeling techniques including molecular docking and molecular dynamics.The applicability of the methods is demonstrated on the basis of the exemplary cases from the literature.
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| 4. |
- Kahn, Iiris, et al.
(författare)
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QSPR Treatment of the Soil Sorption Coefficients of Organic Pollutants
- 2005
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Ingår i: Journal of Chemical Information and Modeling. - : American Chemical Society (ACS). - 1549-9596 .- 1549-960X. ; 45:1, s. 94-105
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Tidskriftsartikel (refereegranskat)abstract
- In this study, general and class-specific QSPR models for soil sorption, logKOC, of 344 organic pollutants (0 < logKOC < 4.94) were developed using a large variety of theoretical molecular descriptors based only on molecular structure. Two general models were obtained. The first model was derived for a structurally representative set of 68 chemicals (R2=0.76, s=0.44), whereas the second involved a total of 344 compounds (R2=0.76, s=0.41). The first was validated using the data for the remaining 276 pollutants (R2=0.70, s=0.45). An additional validation of both models was performed using an independent set of 48 pollutants. Both models predict the logKOC at the level of experimental precision, while the theoretical molecular descriptors appearing in the QSPR models give further insight into the mechanisms of soil sorption. The analysis of the distribution of the residuals of the logKOC values calculated by both general models indicated the need and possible advantages of modeling soil sorption for smaller data sets related to individual classes of chemicals. Accordingly, QSPR models were also developed for 14 chemical classes. The descriptors appearing in these models were discussed as related to the possible interaction mechanisms in soil sorption.
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| 5. |
- Regberg, Jakob, 1986-, et al.
(författare)
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Rational design of a series of novel amphipathic cell-penetrating peptides
- 2014
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Ingår i: International Journal of Pharmaceutics. - : Elsevier BV. - 0378-5173 .- 1873-3476. ; 464:1-2, s. 111-116
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Tidskriftsartikel (refereegranskat)abstract
- A series of novel, amphipathic cell-penetrating peptides was developed based on a combination of the model amphipathic peptide sequence and modifications based on the strategies developed for PepFect and NickFect peptides. The aim was to study the role of amphipathicity for peptide uptake and to investigate if the modifications developed for PepFect peptides could be used to improve the uptake of another class of cell-penetrating peptides. The peptides were synthesized by solid phase peptide synthesis and characterized by circular dichroism spectroscopy. Non-covalent peptide-plasmid complexes were formed by co-incubation of the peptides and plasmids in water solution. The complexes were characterized by dynamic light scattering and cellular uptake of the complexes was studied in a luciferase-based plasmid transfection assay. A quantitative structure-activity relationship (QSAR) model of cellular uptake was developed using descriptors including hydrogen bonding, peptide charge and positions of nitrogen atoms. The peptides were found to be non-toxic and could efficiently transfect cells with plasmid DNA. Cellular uptake data was correlated to QSAR predictions and the predicted biological effects obtained from the model correlated well with experimental data. The QSAR model could improve the understanding of structural requirements for cell penetration, or could potentially be used to predict more efficient cellpenetrating peptides.
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