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LatentDE: Latent-based Directed Evolution accelerated by Gradient Ascent for Protein Sequence Design
Thanh Tran, Nhat Khang Ngo, Duy Nguyen, Truong Son Hy
[paper]
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Assessing interaction recovery of predicted protein-ligand poses
Frederic Dreyer, David Errington, Cedric Bouysset, Constantin Schneider
[paper]
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Improving Inverse Folding models at Protein Stability Prediction without additional Training or Data
Oliver Dutton, Sandro Bottaro, Michele Invernizzi, Istvan Redl, Albert Chung, Falk Hoffmann, Louie Henderson, Stefano Ruschetta, Fabio Airoldi, Benjamin M J Owens, Patrik Foerch, Carlo Fisicaro, Kamil Tamiola
[paper]
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Improving Antibody Design with Force-Guided Sampling in Diffusion Models
Paulina Kulyte, Francisco Vargas, Simon Mathis, Yuguang Wang, Jose Miguel Hernandez-Lobato, Pietro Liò
[paper]
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Equivariant Blurring Diffusion for Multiscale Generation of Molecular Conformer
Jiwoong Park, Yang Shen
[paper]
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Active Learning for Affinity Prediction of Antibodies
Alexandra Gessner, Sebastian Ober, Owen Vickery, Dino Oglic, Talip Ucar
[paper]
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IgBlend: Unifying 3D Structure and Sequence for Antibody LLMs
Cedric Malherbe, Talip Ucar
[paper]
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Learning the Language of Protein Structures
Jeremie DONA, Benoit Gaujac, Timothy Atkinson, Liviu Copoiu, Thomas Pierrot, Thomas Barrett
[paper]
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moPPIt: De Novo Generation of Motif-Specific Binders with Protein Language Models
Tong Chen, Yinuo Zhang, Zachary Quinn, Pranam Chatterjee
[paper]
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Improving generalisability of 3D binding affinity models in low data regimes
Julia Buhmann, Ward Haddadin, Alan Bilsland, Lukáš Pravda, Hagen Triendl
[paper][preprint]
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Active Learning for Energy-Based Antibody Optimization and Enhanced Screening
Kairi Furui, Masahito Ohue
[paper]
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Conditional Enzyme Generation Using Protein Language Models with Adapters
Jason Yang, Aadyot Bhatnagar, Jeffrey Ruffolo, Ali Madani
[paper][preprint]
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Improving Structural Plausibility in 3D Molecule Generation via Property-Conditioned Training with Distorted Molecules
Lucy Vost, Vijil Chenthamarakshan, Payel Das, Charlotte Deane
[paper]
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Understanding Protein-DNA Interactions by Paying Attention to Protein and Genomics Foundation Models
Dhruva Abhijit Rajwade, Erica Wang, Aryan Satpathy, Alexander Brace, Hongyu Guo, Arvind Ramanathan, Shengchao Liu, Animashree Anandkumar
[paper]
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SPECTRE: A Spectral Transformer for Molecule Identification
Wangdong Xu
[paper]
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FlowPacker: protein side-chain packing with torsional flow matching
Jin Sub Lee, Philip Kim
[paper]
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Similarity-Quantized Relative Difference Learning for Improved Molecular Activity Prediction
Karina Zadorozhny, Kangway Chuang, Bharath Sathappan, Ewan Wallace, Vishnu Sresht, Colin Grambow
[paper]
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HERMES: Holographic Equivariant neuRal network model for Mutational Effect and Stability prediction
Gian Marco Visani, Michael Pun, William Galvin, Eric Daniel, Kevin Borisiak, Utheri Wagura, Armita Nourmohammad
[paper]
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Adapting protein language models for structure-conditioned design
Jeffrey Ruffolo, Aadyot Bhatnagar, Joel Beazer, Stephen Nayfach, Jordan Russ, Emily Hill, Riffat Hussain, Joseph Gallagher, Ali Madani
[paper][preprint]
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Allo-Allo: Data-efficient prediction of allosteric sites
Tianze Dong, Christopher Kan, Kapil Devkota, Rohit Singh
[paper][preprint]
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CryoSPIN: Improving Ab-Initio Cryo-EM Reconstruction with Semi-Amortized Pose Inference
Shayan Shekarforoush, David Lindell, Marcus Brubaker, David Fleet
[paper]
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GFlowNet Pretraining with Inexpensive Rewards
Mohit Pandey, Gopeshh Subbaraj, Artem Cherkasov, Emmanuel Bengio
[paper]
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Benchmarking text-integrated protein language model embeddings and embedding fusion on diverse downstream tasks
Young Su Ko
[paper][preprint]
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RNAgrail: graph neural network and diffusion model for RNA 3D structure prediction
Marek Justyna
[paper]
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The OMG dataset: An Open MetaGenomic corpus for mixed-modality genomic language modeling
Yunha Hwang, Andre Cornman, Jacob West-Roberts, Martin Beracochea, Sergey Ovchinnikov, Simon Roux, Antonio Camargo, Milot Mirdita
[paper]
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Functional Alignment of Protein Language Models via Reinforcement Learning with Experimental Feedback
Nathaniel Blalock, Srinath Seshadri, Philip Romero, Agrim Babbar, Sarah Fahlberg
[paper]
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Antibody Library Design by Seeding Linear Programming with Inverse Folding and Protein Language Models
Conor Hayes, Andre Goncalves, Steven Magana-Zook, Ahmet Solak, Daniel Faissol, Mikel Landajuela
[paper]
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EpiGraph: Recommender-Style Graph Neural Networks for Highly Accurate Prediction of Conformational B-Cell Epitopes
Jung-Eun Shin, Yen-Lin Chen, Nathan Rollins, Thomas Hopf, Jordan Anderson, Michael Cianci, Daniela Cipolletta, Jyothsna Visweswaraiah, Yi Xing, Colin Lipper, Kevin Otipoby, Nathan Higginson-Scott, Ryan Peckner
[paper]
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MF-LAL: Drug Compound Generation Using Multi-Fidelity Latent Space Active Learning
Peter Eckmann, Dongxia Wu, Germano Heinzelmann, Michael Gilson, Rose Yu
[paper]
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Higher-Order Message Passing for Glycan Representation Learning
Roman Joeres, Daniel Bojar
[paper]
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LOCAS: Multi-label mRNA Localization with Supervised Contrastive Learning
Abrar Abir, Md Toki Tahmid, M. Saifur Rahman
[paper]
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Does Structural Information Improve ESM3 for Protein Binding Affinity Prediction?
Thomas Loux, Dianzhuo Wang
[paper]
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Unified Sampling and Ranking for Protein Docking with DFMDock
Lee-Shin Chu, Sudeep Sarma, Jeffrey Gray
[paper][preprint]
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Expanding Automated Multiconformer Ligand Modeling to Macrocycles and Fragments
Jessica Flowers
[paper][preprint]
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Protein Sequence Domain Annotation using Language Models
Arpan Sarkar, Kumaresh Krishnan, Sean Eddy
[paper]
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ProtComposer: Compositional Protein Structure Generation with 3D Ellipsoids
Hannes Stärk, Bowen Jing, Tomas Geffner, Jason Yim, Tommi Jaakkola, Arash Vahdat, Karsten Kreis
[paper]
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Rapid protein structure assessment via a forward model for NMR spectra
Benjamin Harding, Chad Rienstra, Hannah Wayment-Steele, Ziling Hu, Frank Delaglio, Rajat Garg, Katherine Henzler-Wildman, Timothy Grant
[paper]
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PropEn: Optimizing Proteins with Implicit Guidance
Natasa Tagasovska, Vladimir Gligorijevic, Kyunghyun Cho, Andreas Loukas
[paper][preprint]
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Bayesian Optimisation for Protein Sequence Design: Gaussian Processes with Zero-Shot Protein Language Model Prior Mean
Carolin Benjamins, Shikha Surana, Oliver Bent, Marius Lindauer, Paul Duckworth
[paper]
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Bio-xLSTM: Generative modeling, representation and in-context learning of biological and chemical sequences
Niklas Schmidinger, Lisa Schneckenreiter, Philipp Seidl, Johannes Schimunek, Sohvi Luukkonen, Pieter-Jan Hoedt, Johannes Brandstetter, Andreas Mayr, Sepp Hochreiter, Guenter Klambauer
[paper][preprint]
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Retrieval Augmented Protein Language Models for Protein Structure Prediction
Peter Lee, Xavier Cheng, Eric Xingyi, Le Song
[paper]
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CompassDock: A Comprehensive Accurate Assessment Approach for Deep Learning-Based Molecular Docking in Inference and Fine-Tuning
Ahmet Sarigun, Vedran Franke, Bora Uyar, Altuna Akalin
[paper][preprint]
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BoostMD: Accelerating Molecular Sampling using ML Force Field Feature
Lars Schaaf, Ilyes Batatia, Christoph Brunken, Thomas Barrett, Jules Tilly
[paper]
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DockFormer: Efficient Multi-Modal Receptor-Ligand Interaction Prediction using Pair Transformer
Ben Shor, Dina Schneidman
[paper]
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Cryo-EM images are intrinsically low dimensional
Luke Evans, Octavian-Vlad Murad, Lars Dingeldein, Pilar Cossio, Roberto Covino, Marina Meila
[paper]
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Open-source Tools for CryoET Particle Picking Machine Learning Competitions
Kyle Harrington, Zhuowen Zhao, Jonathan Schwartz, Saugat Kandel, Utz Ermel, Mohammadreza Paraan, Clinton Potter, Bridget Carragher
[paper]
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Protein Language Model Fitness is a Matter of Preference
Cade Gordon, Amy Lu, Pieter Abbeel
[paper]
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Balancing Locality and Reconstruction in Protein Structure Tokenizer
Jiayou Zhang, Barthélémy Meynard, Jing Gong, Xavier Cheng, Eric Xing, Le Song
[paper]
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What has AlphaFold3 learned about antibody and nanobody docking, and what remains unsolved?
Fatima Hitawala, Jeffrey Gray
[paper]
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HelixFlow, SE(3)–equivariant Full-atom Design of Peptides With Flow-matching Models
Xuezhi Xie, Pedro A Valiente, Jisun Kim, Jin Sub Lee, Philip Kim
[paper]
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MolMix: A Simple Yet Effective Baseline for Multimodal Molecular Representation Learning
Andrei Manolache, Dragos-Constantin Tantaru, Mathias Niepert
[paper]
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Integrating Macromolecular X-ray Diffraction Data with Variational Inference
luis aldama, Kevin Dalton, Doeke Hekstra
[paper]
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Fine-Tuning Discrete Diffusion Models via Reward Optimization: Applications to DNA and Protein Design
Chenyu Wang, Masatoshi Uehara, Yichun He, Amy Wang, Tommaso Biancalani, Avantika Lal, Tommi Jaakkola, Sergey Levine, Hanchen Wang, Aviv Regev
[paper][preprint]
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Low-N OpenFold fine-tuning improves peptide design without additional structures
Theo Sternlieb, Jakub Otwinowski, Sam Sinai, Jeffrey Chan
[paper]
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SPRINT Enables Interpretable and Ultra-Fast Virtual Screening against Thousands of Proteomes
Andrew McNutt, Abhinav Adduri, Caleb Ellington, Monica Dayao, Eric Xing, Hosein Mohimani, David Koes
[paper]
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Ranking protein-peptide binding affinities with protein language models
Charles Chalas, Michael Dunne, Michael Dunne, charles chalas
[paper]
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Generating and scoring stable proteins using joint structure and sequence modeling
Yehlin Cho, Justas Dauparas, Kotaro Tsuboyama, Gabriel Rocklin, Sergey Ovchinnikov
[paper]
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FusOn-pLM: A Fusion Oncoprotein-Specific Language Model via Adjusted Rate Masking
Sophia Vincoff, Shrey Goel, Kseniia Kholina, Rishab Pulugurta, Pranay Vure, Pranam Chatterjee
[paper]
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Systems-Structure-Based Drug Design
Vincent Zaballa, Elliot Hui
[paper]
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Learning the language of protein-protein interactions with ESM-Multimer
Varun Ullanat, Bowen Jing, Samuel Sledzieski, Dr. Bonnie Berger
[paper]
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Guided Multi-objective Generative AI for Structure-based Drug Design
Amit Kadan, Kevin Ryczko, Erika Lloyd, Adrian Roitberg, Takeshi Yamazaki
[paper]
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Tradeoffs of alignment-based and protein language models for predicting viral mutation effects
Noor Youssef, Sarah Gurev, Navami Jain, Debora Marks
[paper]
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IgFlow: Flow Matching for De Novo Antibody Design
Sanjay Nagaraj, Amir Shanehsazzadeh, Hyun Park, Jonathan King, Simon Levine
[paper]
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Generating and evaluating diverse sequences for protein backbones
Yo Akiyama, Sergey Ovchinnikov
[paper]
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SuperMetal: A Generative AI Framework for Rapid and Precise Metal Ion Location Prediction in Proteins
Xiaobo Lin, Zhaoqian Su, Yunchao Liu, Jingxian Liu, Xiaohan Kuang, Peter Cummings, Jesse Spencer-Smith, Jens Meiler
[paper]
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Antibody DomainBed: Out-of-Distribution Generalization in Therapeutic Protein Design
Natasa Tagasovska, Ji Won Park, Matthieu Kirchmeyer, Nathan Frey, Andrew Watkins, Aya Ismail, Arian Jamasb, Edith Lee, Tyler Bryson, Stephen Ra, Kyunghyun Cho
[paper][preprint]
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Controllable All-Atom Generation of Protein Sequence and Structure from Sequence-Only Inputs
Amy Lu, Wilson Yan, Kevin Yang, Vladimir Gligorijevic, Kyunghyun Cho, Richard Bonneau, Pieter Abbeel, Nathan Frey
[paper]
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Loop-Diffusion: an equivariant diffusion model for designing and scoring protein loops
Kevin Borisiak, Gian Marco Visani, Armita Nourmohammad
[paper]
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ProteinZen: combining latent and SE(3) flow matching for all-atom protein generation
Alex Li, Tanja Kortemme
[paper]
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Exploring Discrete Flow Matching for 3D De Novo Molecule Generation
Ian Dunn, David Koes
[paper]
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SynFlowNet: Design of Diverse and Novel Molecules with Synthesis Constraints
Miruna Cretu, Charles Harris, Ilia Igashov, Arne Schneuing, Marwin Segler, Bruno Correia, Julien Roy, Emmanuel Bengio, Pietro Lió
[paper]
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RNA-DCGen: Dual Constrained RNA Sequence Generation with LLM-Attack
Haz Sameen Shahgir, Md. Rownok Zahan Ratul, Md Toki Tahmid, Khondker Salman Sayeed, Atif Rahman
[paper][preprint]
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RNA-GPT: Multimodal Generative System for RNA Sequence Understanding
YIJIA XIAO, Edward Sun, Yiqiao Jin, Wei Wang
[paper]
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TomoPicker: Annotation-Efficient Particle Picking in Cellular cryo-electron Tomograms
Mostofa Rafid Uddin, Ajmain Yasar Ahmed, Toki Tahmid, Alam, Min Xu
[paper]
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AptaBLE: An Enhanced Deep Learning Platform for Aptamer Protein Interaction Prediction and Design
Sawan Patel, Sherwood Yao, Zhangzhi Peng, Keith Fraser, Pranam Chatterjee, Adam Friedman, Owen Yao
[paper]
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Capturing Protein Dynamics: Encoding Temporal and Spatial Dynamics from Molecular Dynamics Simulations
Vignesh Bhethanabotla, Amin Tavakoli, Animashree Anandkumar, William Goddard
[paper]
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ProPicker: Promptable Segmentation for Particle Picking in Cryogenic Electron Tomography
Simon Wiedemann, Zalan Fabian, Mahdi Soltanolkotabi, Reinhard Heckel
[paper]
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Estimating protein flexibility via uncertainty quantification of structure prediction models
Charlotte Sweeney, Nele Quast, Fabian Spoendlin, Yee Whye Teh
[paper]
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Generative modeling of protein ensembles guided by crystallographic electron densities
Sai Advaith Maddipatla, Nadav Bojan Sellam, Sanketh Vedula, Ailie Marx, Alex Bronstein
[paper]
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Energy-Based Flow Matching for Molecular Docking
Wenyin Zhou, Christopher Sprague, Hossein Azizpour
[paper]
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Controlling multi-state conformational equilibria of dynamic proteins with Frame2seq
Deniz Akpinaroglu, Dominic Grisingher, Stephanie Crilly, Tanja Kortemme
[paper]