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Discovery of antibiotics-derived polymers for gene delivery using combinatorial synthesis and cheminformatics modeling

Paper ID Volume ID Publish Year Pages File Format Full-Text
6008 453 1988 12 PDF Available
Title
Discovery of antibiotics-derived polymers for gene delivery using combinatorial synthesis and cheminformatics modeling
Abstract

We describe the combinatorial synthesis and cheminformatics modeling of aminoglycoside antibiotics-derived polymers for transgene delivery and expression. Fifty-six polymers were synthesized by polymerizing aminoglycosides with diglycidyl ether cross-linkers. Parallel screening resulted in identification of several lead polymers that resulted in high transgene expression levels in cells. The role of polymer physicochemical properties in determining efficacy of transgene expression was investigated using Quantitative Structure–Activity Relationship (QSAR) cheminformatics models based on Support Vector Regression (SVR) and ‘building block’ polymer structures. The QSAR model exhibited high predictive ability, and investigation of descriptors in the model, using molecular visualization and correlation plots, indicated that physicochemical attributes related to both, aminoglycosides and diglycidyl ethers facilitated transgene expression. This work synergistically combines combinatorial synthesis and parallel screening with cheminformatics-based QSAR models for discovery and physicochemical elucidation of effective antibiotics-derived polymers for transgene delivery in medicine and biotechnology.

Keywords
Gene delivery; Rational design; Quantitative structure–Activity relationship (QSAR) models; Aminoglycosides
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Discovery of antibiotics-derived polymers for gene delivery using combinatorial synthesis and cheminformatics modeling
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Publisher
Database: Elsevier - ScienceDirect
Journal: Biomaterials - Volume 35, Issue 6, February 2014, Pages 1977–1988
Authors
, , , , , , ,
Subjects
Physical Sciences and Engineering Chemical Engineering Bioengineering
Get Full-Text Now
Don't Miss Today's Special Offer
Price was $35.95
You save - $31
Price after discount Only $4.95
100% Money Back Guarantee
Full-text PDF Download
Online Support
Any Questions? feel free to contact us