Joe Greener
I am a group leader at the MRC Laboratory of Molecular Biology working on improving molecular simulations. My group page is here and my entry on the LMB website is here. I am currently looking to grow the group. You can also find me on X, Bluesky and GitHub.
My interests include molecular simulation, protein structures, software development and open science. Currently my work aims to improve the force fields used to simulate biomolecules with machine learning techniques. I am also interested in developing new types of machine learning force fields.
Previously I was a research fellow (postdoc) in the Bioinformatics Group at University College London (UCL) and a PhD student in the Structural Bioinformatics Group at Imperial College London.
Publications
Greener JG. Reversible molecular simulation for training classical and machine learning force fields, arXiv (2024) - link - code
Wang Y, Takaba K, Chen MS, Wieder M, Xu Y, Zhu T, Zhang JZH, Nagle A, Yu K, Wang X, Cole DJ, Rackers JA, Cho K, Greener JG, Eastman P, Martiniani S and Tuckerman ME. On the design space between molecular mechanics and machine learning force fields, arXiv (2024) - link
Yu CWH, Fischer ES, Greener JG, Yang J, Zhang Z, Freund SMV and Barford D. Molecular mechanism of Mad2 conformational conversion promoted by the Mad2-interaction motif of Cdc20, bioRxiv (2024) - link
Greener JG. Differentiable simulation to develop molecular dynamics force fields for disordered proteins, Chemical Science 15, 4897-4909 (2024) - link - code
Roesch E, Greener JG, MacLean AL, Nassar H, Rackauckas C, Holy TE and Stumpf MPH. Julia for biologists, Nature Methods 20, 655-664 (2023) - link
Greener JG and Jamali K. Fast protein structure searching using structure graph embeddings, bioRxiv (2022) - link - code - server
Greener JG*, Kandathil SM*, Moffat L and Jones DT. A guide to machine learning for biologists, Nature Reviews Molecular Cell Biology 23, 40-55 (2022) - link - open link
Kandathil SM, Greener JG, Lau AM and Jones DT. Ultrafast end-to-end protein structure prediction enables high-throughput exploration of uncharacterized proteins, Proceedings of the National Academy of Sciences 119(4), e2113348119 (2022) - link - code
Moffat L, Greener JG and Jones DT. Using AlphaFold for Rapid and Accurate Fixed Backbone Protein Design, bioRxiv (2021) - link
Greener JG and Jones DT. Differentiable molecular simulation can learn all the parameters in a coarse-grained force field for proteins, PLoS ONE 16(9), e0256990 (2021) - link - code
Greener JG*, Desai N*, Kandathil SM and Jones DT. Near-complete protein structural modelling of the minimal genome, arXiv 2007.06623 (2020) - link
Greener JG, Selvaraj J and Ward BJ. BioStructures.jl: read, write and manipulate macromolecular structures in Julia, Bioinformatics 36(14), 4206-4207 (2020) - link - open link - code
Greener JG*, Kandathil SM* and Jones DT. Deep learning extends de novo protein modelling coverage of genomes using iteratively predicted structural constraints, Nature Communications 10:3977 (2019) - link - website - code
Kandathil SM, Greener JG and Jones DT. Recent Developments in Deep Learning Applied to Protein Structure Prediction, Proteins 87(12), 1179-1189 (2019) - link
Kandathil SM, Greener JG and Jones DT. Prediction of inter-residue contacts with DeepMetaPSICOV in CASP13, Proteins 87(12), 1092-1099 (2019) - link - code
Greener JG*, Moffat L* and Jones DT. Design of metalloproteins and novel protein folds using variational autoencoders, Scientific Reports 8:16189 (2018) - link - code
Craven GB, Affron DP, Allen CE, Matthies S, Greener JG, Morgan RML, Tate EW, Armstrong A and Mann DJ. High-Throughput Kinetic Analysis for Target-Directed Covalent Ligand Discovery, Angewandte Chemie International Edition 57(19), 5257-5261 (2018) - link
Greener JG and Sternberg MJE. Structure-based prediction of protein allostery, Current Opinion in Structural Biology 50, 1-8 (2018) - link
Greener JG, Filippis I and Sternberg MJE. Predicting protein dynamics and allostery using multi-protein atomic distance constraints, Structure 25, 546-558 (2017) - link - code
Greener JG and Sternberg MJE. AlloPred: prediction of allosteric pockets on proteins using normal mode perturbation analysis, BMC Bioinformatics 16:335 (2015) - link - website - code
Software
Some software I have written or contributed to:
Molly.jl - molecular simulation in Julia
Progres - fast protein structure searching
BioStructures.jl - a Julia package to read, write and manipulate macromolecular structures
mmterm - view proteins and trajectories in the terminal
Bio3DView.jl - view macromolecular structures from Julia
pdb-benchmarks - benchmarking common tasks on proteins in various languages and packages
cgdms - differentiable molecular simulation of proteins with a coarse-grained potential
AtomsBase.jl - a Julian abstract interface for atomic structures
Biopython - biology tools in Python
There is more software associated with a few of the papers listed above.
Talks
MolSSI workshop on Julia for Computational Molecular and Materials Science (Oct 2024) - slides
Computational Molecular Science 2024 (Sep 2024) - slides
JuliaCon 2024 (Jul 2024) - video - slides
Enzyme Conference 2024 (Mar 2024) - video - slides
Talks and practical at SINEQ summer school, École des ponts ParisTech (Sep 2023) - slides - notebook
Talk at Institute of Genetics and Cancer, University of Edinburgh (Mar 2023) - slides
Enzyme Conference 2023 (Feb 2023) - video - slides
Crick Christmas Lecture 2022 (Dec 2022) - slides
JuliaMolSim minisymposium at JuliaCon 2022 (Jul 2022) - video - slides
8th Annual CCP-BioSim Conference invited talk (Jun 2022) - slides
Lennard Jones Centre (May 2022) - video - slides
Scientific Machine Learning Webinar Series (Mar 2022) - video - slides
Microsoft Research New England ML Ideas Lunch (Mar 2021) - slides
Imperial College Computational Biology Society (Nov 2020) - slides
KQ Codes Technical Social (Jan 2020) - slides.
3DSIG meeting at ISMB (Jul 2019) - video - slides.
London Julia Meetup group (Jun 2019) - slides.
Friday Wrap talk at Institute of Structural and Molecular Biology (May 2019) - slides.
3DSIG meeting at ISMB (Jul 2016).
Bioinformatics London Meetup group (Apr 2016).
Awards
Warren DeLano Structural Bioinformatics and Computational Biophysics Award for best presentation at 3DSIG 2016.
Awarded ISMB/ECCB Travel Fellowship to attend ISMB 2019 by 3DSIG and ISCB.
Prize for highest mark in MSc class (2014).
Runner-up prize for best presentation at Imperial College London Department of Life Sciences Research Day (2017).