Large-scale analysis of AlphaFold structures reveals organism-specific physicochemical signatures

Large-scale AlphaFold structure analysis reveals organism-specific physicochemical signatures reconstructed via DE-STRESS metrics across 48 proteomes and PDB structures.

Michael J. Stam

Published Oct 4, 2026 · 0 citations

Learning Latent Protein Languages for Autoregressive Generation

Learned latent protein languages improve autoregressive generation scaling, speed, and quality versus amino-acid and coordinate token models.

Mahdi Pourmirzaei, Farzaneh Esmaili, Amir Ziashahabi, Mohammadreza Pourmirzaei and 1 more

Published Oct 2, 2026 · ▲ 5 on Hugging Face · Code

Bonobo: Efficient Library-Scale Generation for De Novo Antibody Design

Sebastian Ober, Nick Bhattacharya, Phillip M Maffettone, Calvin McCarter and 1 more

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

Epitope-Conditioned Nanobody CDR Design via Retrieval-Augmented Protein Language Models

Mohammad Amaan Sayeed, Boulbaba Ben Amor

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

Joint protein, mRNA, DNA sequence design and optimization with nucleotide-level Potts models

Blazej Banaszewski, Lars J Dornfeld, Dexiong Chen, Karsten Borgwardt and 1 more

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

Energy-Adaptive Equivariant State Space Models for Noise-Robust Protein Structure Representation

Zhongyue Zhang, Runze Ma, Yanjie Huang, Shuangjia Zheng

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

Efficient and Accurate Zero Shot Generation of Symmetric Protein Complexes

Rory Gao, Yuanzhou Chen, Prajit Rajkumar, Wei Wang

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

PaxBench: A Multimodal Sequence Benchmark for Protein Abundance Prediction

Ke Zhai, Oscar J Charles, Helena A Saunders, Conrad Bessant

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

Can Folding Models Tell Binders from Bluffers? Evidence from POISK: The Patent-Derived Antibody Dataset

Daria Tupikina, Andrea Roncoli, Alexander Bujotzek, Brennan Abanades Kenyon

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

FoldAbS: Repurposing the Protein Folding Model as a Foundation Encoder for Antibody Screening

Jun Wu, FANDI WU, Xinyuan Zhu, Dawei Huang and 4 more

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

MSConsensus: A Hundred-Million-Scale, Batch-Effect–Suppressed Dataset and Benchmark for Proteomics Machine Learning

Christopher Grams, Chang Liu, Michael Papka, Yu Gao

Atlanta Poster Session 1, Wed, Dec 9, 10:00 AM–1:00 PM, Hall C1 · Published 2026

CryoAtlas: A Large Curated Dataset and Unified Benchmark for Cryo-EM Atomic Model Building

Mingrui Li, Minzhang Li, Weichen Qin, Yufan Xie and 5 more

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

Plausible Biomolecular Structure Prediction via Physics-informed Reinforcement Learning

Tai Dang, Hieu Tran, Long-Hung Pham, Sang Truong and 3 more

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

Expert-guided Bayesian optimization for sustainable protein formulation

Anna Thomas, Georgios Zaverdinos, Petros Mandalis, Andreas Orfanoudakis and 8 more

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

Anchored Protein Engineering

Chi Zhang, Maria Rosaria Briglia, Litu Rout, Jeffrey Ouyang-Zhang and 4 more

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

Bigger Isn’t Better: Why the Indiscriminate Scaling of Foundation Models Can’t Solve Biology

Kathryne Metcalf, Lorin Crawford, Mary L Gray, Kevin K Yang and 1 more

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

DUIL: Deep Unsupervised Inverse Learning for in situ Macromolecular Morphology Identification

Mostofa Rafid Uddin, Seonghui Min, Mahek Vora, Qifeng Wu and 2 more

Atlanta Poster Session 2, Wed, Dec 9, 4:30 PM–7:30 PM, Hall C1 · Published 2026

KnowEvo: Knowledge Evolution for Protein Optimization

Zijie Xing, Xingyue Liu, Runze Wang, Luoming Hu and 1 more

Paris Poster Session 1, Wed, Dec 9, 12:30 PM–2:30 PM, Paris Poster Hall · Published 2026

Benchmarking sequence-to-ensemble predictors on UNICORNEdb, a UniProt-grouped database of PDB-derived conformational ensembles

William F Vanderbilt-Fried, Luka Butskhrikidze, Benjamin P Brown, Hassane Mchaourab and 1 more

Paris Poster Session 1, Wed, Dec 9, 12:30 PM–2:30 PM, Paris Poster Hall · Published 2026

Spectral Feedback for Test-Time Alignment of Protein Diffusion Models

Spectral Feedback iteratively selects protein tokens to re-mask and resample using sparse Fourier edit-set value functions, improving inverse-folding stability by up to 32.3% at test time.

Shai Dickman, Mert Cemri, Landon Butler, Kannan Ramchandran

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

ProteinOPD: Towards Effective and Efficient Preference Alignment for Protein Design

ProteinOPD balances multi-objective protein preferences via on-policy distillation from preference-specific teachers, preserving designability with 8x training speedup over RL methods.

Yulin Zhang, He CAO, Zihao Jiang, Chenyi Zi and 5 more

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

Variable-Length Generative Protein Design via Generalized Poisson Flow

GPFlow learns generalized Poisson process rate functions for variable-length protein generation, improving designability and recovering length distributions without fixed-length constraints.

Chaoran Cheng, Zhanghan Ni, Yanru Qu, Yuxin Chen and 3 more

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

LEMON-ZEST: Evolution-Informed Tokenization for Efficient Protein Language Modeling

LEMON-ZEST uses evolution-informed tokenization to embed domain-level biological priors directly into protein language models. Its 200M-parameter LEMON model outperforms 600M to 3B parameter models on remote homology detection despite training on a single H100 GPU for one week. Evolution-informed to

Biswajit Banerjee, Claudia Alvarez Carreno, Anton S Petrov

Atlanta Poster Session 6, Fri, Dec 11, 4:30 PM–7:30 PM, Hall C1 · Published 2026

pCoMole: Pareto-Constrained Molecule Editing with Discrete Flows

pCoMole uses discrete flow matching to edit biomolecular sequences toward Pareto-optimal targets while enforcing hard biochemical and manufacturability constraints. Wet-lab tests show edited eGFP variants retain fluorescence after deletions and substitutions.

Tong Chen, Maximilian Holsman, Lin Zhao, Yinuo Zhang and 1 more

Atlanta Poster Session 2, Wed, Dec 9, 4:30 PM–7:30 PM, Hall C1 · Published 2026

RipplePLM: Structural and Property Decoupling for Protein Mutation Effect Generation

RipplePLM decouples mutation effects into structural contact pathways and biochemical property tokens via direct-distal cross-attention, boosting mutation description ROUGE-L from 22.23 to 35.65.

Liuzhenghao Lv, Yuyang Liu, Yuyang Gao, Li Yuan and 1 more

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

Self-Improvement Imitation with Biologically Guided Search for Protein Design Under Oracle Budgets

SILO uses hierarchical self-improvement imitation with biologically guided stochastic beam search to optimize protein fitness under tight oracle budgets, outperforming baselines across eight landscapes.

Ashima Khanna-Reiter, Dominik G Grimm

Paris Poster Session 2, Wed, Dec 9, 5:00 PM–7:00 PM, Paris Poster Hall · Published 2026

Atom-level Protein Representation Learning Improves Protein Structure Prediction

TriProRep pretrains structure-aware protein representations via joint amino-acid, backbone, and full-atom token recovery, improving homodimer co-folding, interaction prediction, and monomer structure prediction over sequence-only models.

Taewon Kim, Hyosoon Jang, Hyunjin Seo, Seonghwan Seo and 5 more

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

Predicting directional flexibility in proteins

BackFlip-2 predicts directional protein backbone flexibility and dynamic correlations directly from structures via a fast SE(3)-equivariant graph neural network, matching larger ensemble models at orders-of-magnitude lower cost.

Vsevolod Viliuga, Leif Seute, Matteo Tadiello, Nicolas Wolf and 2 more

Paris Poster Session 6, Fri, Dec 11, 2:30 PM–4:30 PM, Paris Poster Hall · Published 2026

How to make the most of your masked language model for protein engineering

Stochastic beam search samples masked protein language models via pseudo-perplexity to flexibly optimize sequences, with in vitro antibody tests showing sampling choices substantially affect engineering success.

Calvin McCarter, Nick Bhattacharya, Sebastian Ober, Hunter Elliott

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

PepSpecBench: A Unified Evaluation Benchmark for Peptide Tandem Mass Spectrometry Prediction

PepSpecBench standardizes peptide MS/MS prediction evaluation via strict backbone-disjoint splits, unified outputs, multi-species tests, and robustness probes, revealing hidden model limitations.

Zhiwen Yang, Pan Liu, yifan Li, Yunhua Zhong and 1 more

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

Structure-aware Reinforcement Learning for Protein Directed Evolution

StructEvo uses structure-aware reinforcement learning with delta-structure fusion and hierarchical actions to outperform state-of-the-art protein directed evolution methods by up to 16.3%.

Zikun Nie, Suyuan Zhao, Yizhen Luo, Siqi Fan and 1 more

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

BioBlobs: Unsupervised Discovery of Functional Substructures for Protein Function Prediction

BioBlobs is an encoder-agnostic framework that compresses proteins into cohesive substructures to predict function and unsupervisedly discovers functional sites like catalytic triads. It matches baselines using only a small residue fraction, recovers experimentally annotated catalytic sites, and sca

Xin(Allen) Wang, Kaiwen Shi, Carlos Oliver

Atlanta Poster Session 1, Wed, Dec 9, 10:00 AM–1:00 PM, Hall C1 · Published 2026

Robust Inference-Time Steering of Protein Diffusion Models via Embedding Optimization

EmbedOpt steers protein diffusion by optimizing conditional embeddings rather than atomic coordinates, improving robustness and cryo-EM fitting performance.

Minhuan Li, Jiequn Han, Pilar Cossio, Luhuan Wu

Atlanta Poster Session 5, Fri, Dec 11, 10:00 AM–1:00 PM, Hall C1 · Published 2026