Predicting Absolute Binding Free Energies for Lipid Exposed Binding Sites
Lead Research Organisation:
University of Oxford
Department Name: Biochemistry
Abstract
The cells in our bodies are surrounded by membranes. Embedded within these membranes are proteins that perform a wide variety of functions including maintaining the cell integrity, acting as receptors for signals, enzymes to catalyse reactions and transporters whose job is to get nutrients into and out of the cell. These membrane proteins in fact make up about 50% of all known drug targets in humans. However, because their function requires them to change shape (conformation) the design of new drugs is still very difficult. This project aims to develop tools, which would accelerate the discovery for classically undruggable, inherently flexible membrane protein targets.
Although membrane proteins are among the most difficult proteins to obtain and characterise, several techniques have been used to progress this field including electron crystallograpny and cryo-electron microscopy. Recent advancement in structure biology field led to an expotential grow of the number of available structures every year since 2005. As of 20th August 2019 there are 938 unique membrane protein structures deposited in the public domain. This provides for the first time an opportunity to not only investigate the mechanism by which these medicines work but also to put future drug design work on a more solid, structural footing, specifically for drugs that act at sites within the membrane. A key computational technique that can extend the information obtained from structural studies and provide much needed information on the underlying dynamics is Molecular Dynamics (MD) Simulations. Effectively, MD simulations allow one to visualize at the atomic level how the protein moves in a realistic membrane environment.
The project builds on the combined expertise of Vertex and Professor Biggin's laboratory. This computational project will develop and apply advanced molecular dynamics and free energy calculations, as well as machine learning (AI) techniques. Both aspects will be key to understanding how various membrane proteins can be targeted in a rational, structural fashion. In addition, the substantial experience of Vertex in terms of developing small molecules for such targets, alongside assay and synthesis expertise, will allow us to validate the computational predictions performed in this project in a prospective manner.
The overall aims of the project are:
1. To develop and validate new methodologies for membrane protein-drug interactions, building on the previous work in the Biggin group, with particular focus on free energy calculations and rapid pose prediction using deep-learning.
2. To assess the dynamic behaviour of target proteins and their interaction with small molecules in bilayer systems that mimic the in vivo composition.
This project is what might call "Discovery science" and is thus one of the MRCs strategic priorities. More importantly, the studentship will involve training the student in advanced simulation and machine learning techniques. They will emerge will excellent and varied quantitative skills, which is currently seen as an MRC Skills Priority.
Although membrane proteins are among the most difficult proteins to obtain and characterise, several techniques have been used to progress this field including electron crystallograpny and cryo-electron microscopy. Recent advancement in structure biology field led to an expotential grow of the number of available structures every year since 2005. As of 20th August 2019 there are 938 unique membrane protein structures deposited in the public domain. This provides for the first time an opportunity to not only investigate the mechanism by which these medicines work but also to put future drug design work on a more solid, structural footing, specifically for drugs that act at sites within the membrane. A key computational technique that can extend the information obtained from structural studies and provide much needed information on the underlying dynamics is Molecular Dynamics (MD) Simulations. Effectively, MD simulations allow one to visualize at the atomic level how the protein moves in a realistic membrane environment.
The project builds on the combined expertise of Vertex and Professor Biggin's laboratory. This computational project will develop and apply advanced molecular dynamics and free energy calculations, as well as machine learning (AI) techniques. Both aspects will be key to understanding how various membrane proteins can be targeted in a rational, structural fashion. In addition, the substantial experience of Vertex in terms of developing small molecules for such targets, alongside assay and synthesis expertise, will allow us to validate the computational predictions performed in this project in a prospective manner.
The overall aims of the project are:
1. To develop and validate new methodologies for membrane protein-drug interactions, building on the previous work in the Biggin group, with particular focus on free energy calculations and rapid pose prediction using deep-learning.
2. To assess the dynamic behaviour of target proteins and their interaction with small molecules in bilayer systems that mimic the in vivo composition.
This project is what might call "Discovery science" and is thus one of the MRCs strategic priorities. More importantly, the studentship will involve training the student in advanced simulation and machine learning techniques. They will emerge will excellent and varied quantitative skills, which is currently seen as an MRC Skills Priority.
People |
ORCID iD |
| Philip Biggin (Primary Supervisor) |
Studentship Projects
| Project Reference | Relationship | Related To | Start | End | Student Name |
|---|---|---|---|---|---|
| MR/R015708/1 | 01/10/2018 | 30/09/2025 | |||
| 2290949 | Studentship | MR/R015708/1 | 01/10/2019 | 31/03/2023 |