Iterative simulation, artificial intelligence and machine learning-guided design of tide aptamers based on structural characterisation of conotoxin/nAChR interactions

Abstract

The aim of our multidisciplinary research program is to bring together expertise in peptide chemistry, protein biochemistry, structural biology, computational machine learning and artificial intelligence to establish the mechanism of action (MOA) of conotoxins against the human muscle type nicotinic acetylcholine receptor (nAChR). We will then use this information to guide the development of anti-toxin cyclic peptide aptamers as medical countermeasures (MCMs) that can bind to adult muscle nAChRs.

Document Details

Document Type
DoD Grant Award
Publication Date
Dec 19, 2022
Source ID
HDTRA12210001

Entities

People

  • Andrew G Jamieson

Organizations

  • Defense Threat Reduction Agency
  • University of Glasgow

Tags

Fields of Study

  • Chemistry

Readers

  • Molecular and Cellular Biochemistry
  • Neural Network Machine Learning.
  • Neuroscience

Technology Areas

  • AI & ML
  • AI & ML - DoD AI Strategy