Automated descriptors for high-throughput screening of peptide self-assembly
Rajaram Baskaran, Raj Kumar and van Teijlingen, Alexander and Tuttle, Tell (2025) Automated descriptors for high-throughput screening of peptide self-assembly. Faraday Discussions. ISSN 1359-6640 (https://doi.org/10.1039/D4FD00201F)
![]() |
Text.
Filename: AAM-FaradayDiscussions-d4fd00201f-Tuttle.pdf
Accepted Author Manuscript Restricted to Repository staff only until 1 January 2099. Download (21MB) | Request a copy |
Abstract
We present five automated descriptors: Aggregate Detection Index (ADI); Sheet Formation Index (SFI); Vesicle Formation Index (VFI); Tube Formation Index (TFI); and Fiber Formation Index (FFI), that have been designed for analysing peptide self-assembly in molecular dynamics simulations. These descriptors, implemented as Python modules within a Conda environment, enhance analytical precision and enable the development of screening methods tailored to specific structural targets rather than general aggregation. Initially tested on the FF dipeptide, the descriptors were validated using a comprehensive dipeptide dataset. This approach facilitates the identification of promising self-assembling moieties with nanoscale properties directly linked to macroscale functions, such as hydrogel formation.
ORCID iDs
Rajaram Baskaran, Raj Kumar

-
-
Item type: Article ID code: 92194 Dates: DateEvent28 January 2025Published28 January 2025Published Online23 January 2025AcceptedSubjects: Science > Chemistry Department: Faculty of Science > Pure and Applied Chemistry
Technology and Innovation Centre > BionanotechnologyDepositing user: Pure Administrator Date deposited: 26 Feb 2025 15:31 Last modified: 07 Mar 2025 02:03 Related URLs: URI: https://strathprints.strath.ac.uk/id/eprint/92194