Computational design of peptide therapeutics containing non-natural amino acids - ON-164

Preferred Disciplines: Chemistry or Biochemistry / Molecular Biology, Graduate degree (MSc or Ph.D.) 
Company: ProteinQure Inc.
Project Length: 4-6 months (1 unit)
Desired start date: ASAP
Location: Toronto, ON
No. of Positions: 1
Preferences: None

About the Company: 

ProteinQure (Toronto based startup) is a software platform for computational peptide drug discovery. We combine quantum computing, molecular simulations and machine learning to do the structure based design of drugs. A physics-based approach is less data-dependent and enable us to develop therapeutics for complicated disease targets. We are one of the top graduates of the Quantum Machine Learning stream at the Creative Destruction Lab incubator (University of Toronto) and have partnerships with several quantum computing hardware providers (Rigetti, IBM, Xanadu, D-Wave and Fujitsu).

Project Description:

ProteinQure is combining cutting-edge computational technologies to assist with the design of protein-based therapeutics.

We have developed methods to rapidly predict protein-protein interactions using accelerated molecular dynamics simulations. These approaches are well-established for peptides and proteins composed of the 20 natural amino acids, but cannot readily be used to study protein-protein interactions involving the types of non-natural amino acids commonly used in early-stage drug discovery. Many simple characteristics of unnatural amino acids, like secondary structure propensity and interaction strength, are poorly understood.

It is the objective of this project to extend the capabilities of our molecular dynamics platform to support common non-natural amino acids (AMBER force field parameters), and peform preliminary validation of these predictions by simulating peptides containing these amino acids. Experimental data for validation will be obtained from peer-reviewed research.

Research Objectives:

  • Selection of non-natural amino acids to prioritize based on reviewing literature and dicussions between Mitacs fellow and ProteinQure
  • Research and execution of a computational protocol to obtain parameters for non-natural amino acids in molecular dynamics simualtions
  • Validation parameters by performing simulations of peptides containing non-natural amino acids in isolation and potentially with a therapeutic target
  • Write computer scripts that automate the computational workflow for general unnnatural amino acid modelling


  • Computational protocols for parameterization will be based on the AMBER antechamber/RESP approach, or an alternative method for producing compatible AMBER force fields (Khoury et al. 2013, R.E.D. Server, etc.). This will involve electronic structure calculations for both alpha/beta conformations of amino acid dipeptides
  • Simulations of peptides containing unnatural amino acids will be performed with implicit or explicit solvent using OpenMM, or our enhanced sampling simulation platform
  • Computer scripting for the workflow will be performed using Python

Expertise and Skills Needed:

    • 3D molecular modelling experience (PyMol, Maestro, Avogadro, etc.)
    • Unix/Linux (command line, remote connections to HPC resources)
    • Familiarity with molecular dynamics, force fields, Python scripting (Preferred)

    For more info or to apply to this applied research position, please

    1. Check your eligibility and find more information about open projects
    2. Interested students need to get the approval from their supervisor and send their CV along with a link to their supervisor’s university webpage by applying through the webform.