Machine Learning in Structural Biology

3D alignment of cryogenic electron microscopy density maps by minimizing their Wasserstein distance

Aryan Tajmir Riahi, Geoffrey Woollard, Frederic Poitevin, Anne Condon, Khanh Dao Duc

[paper]

3D Reconstruction of Protein Complex Structures Using Synthesized Multi-View AFM Images

Jaydeep Rade, Soumik Sarkar, Anwesha Sarkar, Adarsh Krishnamurthy

[paper] [preprint]

A Benchmark Framework for Evaluating Structure-to-Sequence Models for Protein Design

Jeffrey Chan, Seyone Chithrananda, David Brookes, Sam Sinai

A Federated Learning benchmark for Drug-Target Interaction

Filip Svoboda, Gianluca Mittone, Nicholas Lane, Pietro Lió

[paper]

Adversarial Attacks on Protein Language Models

Ginevra Carbone, Francesca Cuturello, Luca Bortolussi, Alberto Cazzaniga

[paper] [preprint]

Agile Language Transformers for Recombinant Protein Expression Optimization

Jeliazko Jeliazkov, Maxim Shapovalov, Diego del Alamo, Matt Sternke, Joel Karpiak

[paper]

Allele-conditional attention mechanism for HLA-peptide complex binding affinity prediction

Rodrigo Hormazabal, Doyeong Hwang, Kiyoung Kim, Sehui Han, Kyunghoon Bae, Honglak Lee

Antibody optimization enabled by artificial intelligence predictions of binding affinity and naturalness

Sharrol Bachas, Goran Rakocevic, David Spencer, Anand Sastry, Robel Haile, John Sutton, George Kasun, Andrew Stachyra, Jahir Gutierrez, Edriss Yassine, Borka Medjo, Vincent Blay, Christa Kohnert, Jennifer Stanton, Alexander Brown, Nebojsa Tijanic, Cailen McCloskey, Rebecca Viazzo, Rebecca Consbruck, Hayley Carter, Simon Gottreich-Levine, Shaheed Abdulhaqq, Jacob Shaul, Abigail Ventura, Randal Olson, Engin Yapici, Joshua Meier, Sean McClain, Matthew Weinstock, Gregory Hannum, Ariel Schwartz, Miles Gander, Roberto Spreafico

[preprint]

APPRAISE: ranking engineered proteins by target binding propensity using pair-wise, competitive structure modeling and physics-informed analysis

Xiaozhe Ding, Xinhong Chen, Erin Sullivan, Tim Miles, Viviana Gradinaru

ChemSpacE: Interpretable and Interactive Chemical Space Exploration

Yuanqi Du, Xian Liu, Nilay Shah, Shengchao Liu, Jieyu Zhang, Bolei Zhou

[preprint]

Conditional Invariances for Conformer Invariant Protein Representations

Balasubramaniam Srinivasan, Vassilis Ioannidis, Soji Adeshina, Mayank Kakodkar, George Karypis, Bruno Ribeiro

[paper] [preprint]

Conditional neural processes for molecules

Miguel Garcia-Ortegon, Andreas Bender, Sergio Bacallado

[paper] [preprint]

ContactNet: Geometric-Based Deep Learning Model for Predicting Protein-Protein Interactions

Matan Halfon, Dina Schneidman, Tomer Cohen, raanan fattal

[paper]

Contrasting drugs from decoys

Samuel Sledzieski, Rohit Singh, Lenore J Cowen, Bonnie Berger

[paper] [preprint]

Deep Local Analysis estimates effects of mutations on protein-protein interactions

Yasser Mohseni Behbahani, Elodie Laine, Alessandra Carbone

[paper] [preprint]

Designing Biological Sequences via Meta-Reinforcement Learning and Bayesian Optimization

Leo Feng, Padideh Nouri, Aneri Muni, Yoshua Bengio, Pierre-Luc Bacon

[paper] [preprint]

DiffDock: Diffusion Steps, Twists, and Turns for Molecular Docking

Gabriele Corso, Hannes Stärk, Bowen Jing, Regina Barzilay, Tommi Jaakkola

[paper] [preprint]

Diffusion probabilistic modeling of protein backbones in 3D for the motif-scaffolding problem

Jason Yim, Brian L Trippe, Doug Tischer, David Baker, Tamara Broderick, Regina Barzilay, Tommi Jaakkola

[paper] [preprint]

Does Inter-Protein Contact Prediction Benefit from Multi-Modal Data and Auxiliary Tasks?

Arghamitra Talukder, Rujie Yin, Yang Shen, Yuning You

[paper]

Dynamic-backbone protein-ligand structure prediction with multiscale generative diffusion models

Zhuoran Qiao, Weili Nie, Arash Vahdat, Thomas Miller, Anima Anandkumar

[preprint]

End-to-end accurate and high-throughput modeling of antibody-antigen complexes

Tomer Cohen, Dina Schneidman

[paper]

EquiFold: Protein Structure Prediction with a Novel Coarse-Grained Structure Representation

Jae Hyeon Lee, Payman Yadollahpour, Andrew Watkins, Nathan Frey, Andrew Leaver-Fay, Stephen Ra, Vladimir Gligorijevic, Kyunghyun Cho, Aviv Regev, Richard Bonneau

[paper] [preprint]

EvoOpt: an MSA-guided, fully unsupervised sequence optimization pipeline for protein design

Hideki Yamaguchi, Yutaka Saito

[paper]

Explainable Deep Generative Models, Ancestral Fragments, and Murky Regions of the Protein Structure Universe

Eli Draizen, Cameron Mura, Philip Bourne

[paper] [preprint]

ExpressUrself: A spatial model for predicting recombinant expression from mRNA sequence

Michael P Dunne, Javier Caceres-Delpiano

[paper]

Fast and Accurate Antibody Structure Prediction without Sequence Homologs

Jiaxiang Wu, Fandi Wu, Biaobin Jiang, Wei Liu, Peilin Zhao

[paper] [preprint]

Fast protein structure searching using structure graph embeddings

Joe Greener, Kiarash Jamali

[paper] [preprint]

Heterogeneous reconstruction of deformable atomic models in Cryo-EM

Youssef Nashed, Ariana Peck, Julien Martel, Axel Levy, Bongjin Koo, Gordon Wetzstein, Nina Miolane, Daniel Ratner, Frederic Poitevin

[paper] [preprint]

Holographic-(V)AE: an end-to-end SO(3)-Equivariant (Variational) Autoencoder in Fourier Space

Gian Marco Visani, Michael Pun, Armita Nourmohammad

[paper] [preprint]

Identifying endogenous peptide receptors by combining structure and transmembrane topology prediction

Felix Teufel, Jan Christian Refsgaard, Christian Toft Madsen, Carsten Stahlhut, Mads Grønborg, Dennis Madsen, Ole Winther

[paper] [preprint]

Improving Molecular Pretraining with Complementary Featurizations

Yanqiao Zhu, Dingshuo Chen, Yuanqi Du, Yingze Wang, Qiang Liu, Shu Wu

[paper] [preprint]

Improving Molecule Properties Through 2-Stage VAE

Chenghui Zhou, Barnabas Poczos

[paper]

Improving Protein Subcellular Localization Prediction with Structural Prediction & Graph Neural Networks

Geoffroy Dubourg-Felonneau, Arash Abbasi, Eyal Akiva, Lawrence Lee

[paper]

Investigating graph neural network for RNA structural embedding

vaitea opuu, Helene Bret

[paper]

Investigating the conformational landscape of AlphaFold2-predicted protein kinase structures

Carmen Al Masri, Francesco Trozzi, Marcel Patek, Anna Cichonska, Balaguru Ravikumar, Rayees Rahman

Large-scale self-supervised pre-training on protein three-dimensional structures

Ilya Senatorov

Latent Space Diffusion Models of Cryo-EM Structures

Karsten Kreis, Tim Dockhorn, Zihao Li, Ellen Zhong

[preprint]

Learning Free Energy Pathways through Reinforcement Learning of Adaptive Steered Molecular Dynamics

Nicholas Ho, John Kevin Cava, John Vant, Ankita Shukla, Jacob Miratsky, Pavan Turaga, Ross Maciejewski, Abhishek Singharoy

[paper] [preprint]

Learning from physics-based features improves protein property prediction

Amy Wang, Ava Soleimany, Alex X Lu, Kevin Yang

[paper]

Ligand-aware protein sequence design using protein self contacts

Jody Mou, Benjamin Fry, Chun-Chen Yao, Nicholas Polizzi

[paper]

Lightweight Equivariant Graph Representation Learning for Protein Engineering

Bingxin Zhou, · Kai Yi, Xinye Xiong, Pan Tan, Liang Hong, Yuguang Wang

[paper] [preprint]

Masked inverse folding with sequence transfer for protein representation learning

Kevin Yang, Niccoló Zanichelli, Hugh Yeh

[preprint]

Membrane and microtubule rapid instance segmentation with dimensionless instance segmentation by learning graph representations of point clouds

Robert Kiewisz, Tristan Bepler

[paper]

Metal3D: Accurate prediction of transition metal ion location via deep learning

Simon Dürr

[preprint]

MLPfold: Identification of transition state ensembles in molecular dynamics simulations using machine learning

Preetham Venkatesh

[paper]

ModelAngelo: Automated Model Building in Cryo-EM Maps

Kiarash Jamali, Dari Kimanius, Sjors Scheres

[paper] [preprint]

Online Inference of Structure Factor Amplitudes for Serial X-ray Crystallography

Kevin Dalton, Doeke Hekstra

[paper]

Peptide-MHC Structure Prediction With Mixed Residue and Atom Graph Neural Network

Antoine Delaunay, Yunguan Fu, Alberto Bégué, Robert McHardy, Bachir Djermani, Liviu Copoiu, Michael Rooney, Andrey Tovchigrechko, Marcin Skwark, Nicolas Lopez Carranza, Maren Lang, Karim Beguir, Ugur Sahin

[paper] [preprint]

Physics aware inference for the cryo-EM inverse problem: anisotropic network model heterogeneity, global pose and microscope defocus

Geoffrey Woollard, Shayan Shekarforoush, Frank Wood, Marcus Brubaker, Khanh Dao Duc

[paper]

Physics-aware Graph Neural Network for Accurate RNA 3D Structure Prediction

Shuo Zhang, Lei Xie, Yang Liu

[paper] [preprint]

Plug & Play Directed Evolution of Proteins with Gradient-based Discrete MCMC

Patrick Emami, Aidan Perreault, Jeffrey Law, David Biagioni, Peter St. John

[paper]

Predicting conformational landscapes of known and putative fold-switching proteins using AlphaFold2

Hannah Wayment-Steele, Sergey Ovchinnikov, Lucy Colwell, Dorothee Kern

[paper] [preprint]

Predicting Immune Escape with Pretrained Protein Language Model Embeddings

Kyle Swanson, Howard Chang, James Zou

[paper] [preprint]

Predicting interaction partners using masked language modeling

Damiano Sgarbossa, Umberto Lupo, Anne-Florence Bitbol

[paper]

Predicting Ligand – RNA Binding Using E3-Equivariant Network and Pretraining

Zhenfeng Deng, Ruichu Gu, Hangrui Bi, Xinyan Wang, Zhaolei Zhang, Han Wen

[paper]

Pretrained protein language model transfer learning: is the final layer representation what we want?

Francesca-Zhoufan Li, Ava Soleimany, Kevin Yang, Alex X Lu

[paper]

Protein Sequence Design in a Latent Space via Model-based Reinforcement Learning

Minji Lee, Luiz Felipe Vecchietti, Hyunkyu Jung, Hyunjoo Ro, Ho Min Kim, Meeyoung Cha

[paper] [preprint]

Protein Structure and Sequence Generation with Equivariant Denoising Diffusion Probabilistic Models

Namrata Anand, Tudor Achim

[preprint]

Protein structure generation via folding diffusion

Kevin Wu, Kevin Yang, Rianne van den Berg, James Zou, Alex X Lu, Ava Soleimany

[preprint]

Protein-Protein Docking with Iterative Transformer

Lee-Shin Chu, Jeffrey Ruffolo, Jeffrey Gray

[paper]

Reconstruction of polymer structures from contact maps with Deep Learning

Atreya Dey

Representation Learning on Biomolecular Structures using Equivariant Graph Attention

Tuan Le, Frank Noe, Djork-Arné Clevert

[paper] [preprint]

Representation of missense variants for predicting modes of action

Guojie Zhong, Yufeng Shen

[paper]

RL Boltzmann Generators for Conformer Generation in Data-Sparse Environments

Yash Patel, Ambuj Tewari

[paper] [preprint]

Seq2MSA: A Language Model for Protein Sequence Diversification

Pascal Sturmfels, Roshan Rao, Robert Verkuil, Zeming Lin, Tom Sercu, Adam Lerer, Alex Rives

[paper]

So ManyFolds, So Little Time: Efficient Protein Structure Prediction With pLMs and MSAs

Thomas D Barrett, Amelia Villegas-Morcillo, Louis Robinson, Benoit Gaujac, Karim Beguir, Arthur Flajolet

[paper] [preprint]

Structure-based Drug Design with Equivariant Diffusion Models

Arne Schneuing, Yuanqi Du, Charles Harris, Arian Jamasb, Ilia Igashov, weitao Du, Tom Blundell, Pietro Lió, Carla Gomes, Max Welling, Michael Bronstein, Bruno Correia

[paper] [preprint]

SWAMPNN: End-to-end protein structures alignment

Jeanne Trinquier, Samantha Petti, Shihao Feng, Johannes Soeding, Martin Steinegger, Sergey Ovchinnikov

[paper]

T-cell receptor specific protein language model for prediction and interpretation of epitope binding (ProtLM.TCR)

Ahmed Essaghir

The geometry of hidden representations of protein language models

Lucrezia Valeriani, Francesca Cuturello, Alessio Ansuini, Alberto Cazzaniga

[paper] [preprint]

Towards automated crystallographic structure refinement with a differentiable pipeline

Minhuan Li, Doeke Hekstra

[paper]

Training self-supervised peptide sequence models on artificially chopped proteins

Gil Sadeh, Zichen Wang, Jasleen Grewal, Huzefa Rangwala, Layne Price

[paper] [preprint]

Unsupervised language models for disease variant prediction

Allan Zhou, Nicholas C. Landolfi, Daniel ONeill

[paper]

Using domain-domain interactions to probe the limitations of MSA pairing strategies

Alex Hawkins-Hooker, David Jones, Brooks Paige

[paper]

Visualizing DNA reaction trajectories with deep graph embedding approaches

Chenwei Zhang, Anne Condon, Khanh Dao Duc

[paper]

What is hidden in the darkness? Characterization of AlphaFold structural space

Janani Durairaj, Joana Maria Soa Pereira, Mehmet Akdel, Torsten Schwede

[preprint]

ZymCTRL: a conditional language model for the controllable generation of artificial enzymes

Noelia Ferruz

[paper]