Will it gel? Successful computational prediction of peptide gelators using physicochemical properties and molecular fingerprints.

ABSTRACT: The self-assembly of low molecular weight gelators to form gels has enormous potential for cell culturing, optoelectronics, sensing, and for the preparation of structured materials. There is an enormous "chemical space" of gelators. Even within one class, functionalised dipeptides, there are many structures based on both natural and unnatural amino acids that can be proposed and there is a need for methods that can successfully predict the gelation propensity of such molecules. We have successfully developed computational models, based on experimental data, which are robust and are able to identify in silico dipeptide structures that can form gels. A virtual computational screen of 2025 dipeptide candidates identified 9 dipeptides that were synthesised and tested. Every one of the 9

SUBMITTER: Gupta JK 

PROVIDER: S-EPMC6016447 | biostudies-literature | 2016 Jul

REPOSITORIES: biostudies-literature