Computer Aided Design of Synthetic Viruses
Lead Research Organisation:
University College London
Department Name: Chemistry
Abstract
The aim of this PhD project is to use atomistic and coarse-grained molecular dynamics simulations together with enhanced-sampling algorithms to design novel artificial peptides that are able to self-assemble in biomimetic nanoparticles. The multiscale models will be used to determine how the size, topology, topography and surface chemistry of the nanoparticles are determined by the peptide sequence and properties. Within the GB group the knowledge gained by the simulations will be used to synthesize the different components hierarchically. At the molecular level, the single building blocks can be synthesised using both solid-phase synthesis or recombinant methodology. At the supramolecular level, the different structures will be formed in water using advanced multiphase mixing units and/or microfluidics. The final structures will be fully characterised using a combination of advanced microscopy (including a new liquid Scanning Transmission Electron Microscopy STEM just acquired by the department), scattering techniques (DLS and MALS) and small angle x-ray scattering (SAXS) and spectroscopic techniques (NMR, Fluorescence, Circular Diachronism and UV/Vis).
People |
ORCID iD |
| Francesco Luigi Gervasio (Primary Supervisor) | |
| Rhys Evans (Student) |
Studentship Projects
| Project Reference | Relationship | Related To | Start | End | Student Name |
|---|---|---|---|---|---|
| EP/N509577/1 | 01/10/2016 | 24/03/2022 | |||
| 1928379 | Studentship | EP/N509577/1 | 01/10/2017 | 31/07/2021 | Rhys Evans |
| Description | The development process for new drug therapies is expensive, involved, and essential, and computational methods play an ever-increasing role in many of the steps. This work presents an exploration into the use of computational techniques and simulation-based methods to aid in the pharmaceutical development process. Focussing on the usage of enhanced sampling techniques including metadynamics, replica-exchange, and combined methods, it investigates their application in various stages in the drug discovery pipeline. It is divided into three main projects, each targeting a specific aspect of the process. Firstly, by establishing and analysing a database of cryptic sites in publicly available protein structures, it provides a significant resource in the field of drug discovery. Cryptic sites are those binding sites that are only visible in the presence of the ligand and exploiting them has the potential to dramatically increase the druggable proteome. The second project involves the development and testing of three novel methods for absolute binding free energy calculations within fragment-based drug design. Intended as a proof of concept, it is demonstrated that these methods each have a specific area in which they excel, with wide applicability in the hit-to-lead optimisation phase. Finally, this work presented an investigation into the use of self-assembling peptides for use in drug delivery. Drug encapsulation promises wide-ranging benefits but is often chieved using synthetic polymers to create self-assembling micelles. In collaboration with experimentalists at UCL, I explore the viability of creating histidine-based peptidic vesicles by studying the structures they produced as well as the impact of sequence choices on their resultant properties. |
| Exploitation Route | The projects that incorporated my PhD all have their own future prospects. Our sEH results presented a breakdown, and an in-depth benchmark, of some novel techniques available in the field of computational, fragment-based drug discovery. Each method covered had use-cases in which it excelled, as determined by the trade-off between cost and accuracy. The next steps would be to take these methods and automate them, such that they could be used within a pharmaceutical pipeline. Our work involving peptides and fibrillar structures presented a novel computational model for the self-assembly of small peptides with applications in the drug delivery and nano-materials fields. |
| Sectors | Pharmaceuticals and Medical Biotechnology |
| Description | Molecular Bionics Lab |
| Organisation | University College London |
| Department | Department of Chemistry |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | Shared initial project with Prof. Battaglia and Dr Carlos Noble Jesus over the course of the PhD. |
| Collaborator Contribution | Shared initial project with Prof. Battaglia and Dr Carlos Noble Jesus over the course of the PhD. |
| Impact | ACS Macro Letters, 2021, Amphiphilic Histidine-Based Oligopeptides Exhibit pH-Reversible Fibril Formation |
| Start Year | 2017 |
| Description | UCB |
| Organisation | UCB Pharma |
| Country | United Kingdom |
| Sector | Private |
| PI Contribution | Method development with potential implications for industrial applications. One publication. |
| Collaborator Contribution | Target selection and guidance on one publication. Ben Cossins (employee of collaborator at the time) was joint author on the paper. |
| Impact | JCTC, May 2020, "Combining Machine Learning and Enhanced Sampling Techniques for Efficient and Accurate Calculation of Absolute Binding Free Energies" |
| Start Year | 2018 |