Weekly BioML Digest [June 01, 2026]

Machine Learning × Computational Biology paper compilation

Hey! It's your weekly digest of machine learning papers in CompBio and Drug Discovery.

Feedback? Email me at biomldigest@gmail.com.

📚 Peer-Reviewed Journals (Top 20)

582 matched filters -> 20 selected after LLM relevance + novelty ranking.

• High-fidelity genome and prime editing enabled by the AI-designed openCRISPR-1
  Hwang, Hye-Yeon, Yi, Hwalin, Gwon, Yuju, Jeon, Eunju, Kim, Daesik — Genome Medicine, 2026-05-26
  abs

• Navigating high-order protein fitness landscapes via deep learning on directed evolution trajectories
  Chen Song, Liang Ma, Lingfeng Xue, Yingfan Xu, Qihan Zhang, Yuxi Liu, Chen Song, Yihan Lin — Proceedings of the National Academy of Sciences, 2026-05-26
  abs

• FLOWR: flow matching for structure-aware de novo, interaction- and fragment-based ligand generation
  Cremer, Julian, Irwin, Ross, Tibo, Alessandro, Janet, Jon Paul, Olsson, Simon, Clevert, Djork-Arné — Nature Computational Science, 2026-05-28
  abs

• CholBindNet as an interpretable neural network for cholesterol-binding site classification
  Hernandez, Alexis, Bhatt, Aashish, Revilla, Ivan, Levine, Jacob Ede, Kosaraju, Sai Chandra, Luo, Yun Lyna — Communications Chemistry, 2026-05-29
  abs

• Generalizable mutation-effect prediction across adaptive immune recognition via unified multimodal framework
  Han, Rong, Zhang, Yumeng, Liu, Xiaohong, Fu, Lei, Pan, Tong, Xu, Jing, Wang, Xiaoyu, Zhang, Peidong, Chen, Xuanzhong, Lei, Jiesi, Lan, Wuyang, Ji, Changwei, Cui, Shuguang, Wu, Song, Song, Jiangning, Chen, Ting, Wang, Guangyu — Nature Machine Intelligence, 2026-05-27
  abs

• Multiomics and deep learning dissect regulatory syntax in human development
  Liu, Betty B., Jessa, Selin, Kim, Samuel H., Ng, Yan Ting, Higashino, Soon Il, Marinov, Georgi K., Chen, Derek C., Parks, Benjamin E., Li, Li, Nguyen, Tri C., Wang, Austin T., Wang, Sean K., Tan, Meng How, Tan, Serena Y., Kosicki, Michael, Pennacchio, Len A., Ben-David, Eyal, Pasca, Anca M., Kundaje, Anshul, Farh, Kyle K. H., Greenleaf, William J. — Nature, 2026-05-28
  abs

• SOFisher: reinforcement learning-guided experiment designs for spatial omics
  Li, Zhuo, Wu, Weiran, Han, Chuangyi, Cui, Yan, Lu, Tian, Ke, Rongqin, Sun, Jian, Yuan, Zhiyuan — Nature Communications, 2026-05-25
  abs

• A deep mutational scanning-informed protein language model predicts SARS-CoV-2 evolution dynamics with spatiotemporal resolution
  Yang, Sijie, Luo, Xiaowei, Luo, Jiejian, Jian, Fanchong, Cao, Yunlong — Nature Microbiology, 2026-05-27
  abs

• AI ‐Driven Protein‐to‐Aptamer Design Using a Transformer Architecture With Cross‐Model and Structural Validation
  Min‐Kung Hsu, Yu-Jing Zeng, Ya-Chi Lin, Po‐Jui Chen, Hsian-Yu Wang — Journal of the Chinese Chemical Society, 2026-05-27
  abs

• PRIME: An evaluation framework for protein representation inference and generalization in viral mutation space
  Gibson, Kaetlyn, Li, Po-E, Li, Valerie, Dix, Martha, Hung, Li-Wei, Stelle, George Widgery, Babinski, Michal, Chain, Patrick, Hu, Bin — BMC Genomics, 2026-05-30
  abs

• Fine-tuning sequence-to-expression models on personal genome and transcriptome data
  Rastogi, Ruchir, Reddy, Aniketh Janardhan, Chung, Ryan, Ioannidis, Nilah M. — Genome Biology, 2026-05-25
  abs

• EnzymeTuning improves enzyme-constrained metabolic modeling and proteome abundance prediction through deep learning
  Wang, Xueting, Wang, Yongbo, Zhuang, Yingping, Wang, Guan, Lu, Hongzhong — Nature Communications, 2026-05-27
  abs

• Accurate quantification in proteomics with QuantUMS
  Grossmann, Justus L., Kistner, Franziska, Sinn, Ludwig R., Szyrwiel, Lukasz, Rappsilber, Juri, Demichev, Vadim — Nature Biotechnology, 2026-05-27
  abs

• PhosSight: A Unified Deep Learning Framework Boosting and Accelerating Phosphoproteome Identification to Enable Biological Discoveries
  Ben Wang, Zhiyuan Cheng, Chengying She, Hongwei Zhao, Jiahui Zhang, Lin Lv, Zhihao Yan, Hongwen Zhu, Lizhuang Liu, Yan Fu, Xinpei Yi — Advanced Science, 2026-05-27
  abs

• A dataset of 1.2 million molecules with DFT-level quantum chemical annotations for molecular representation learning
  Wang, Haoyu, Zhang, Ziyan, Gong, Haipeng — Communications Chemistry, 2026-05-26
  abs

• Scaling antibody language models improves structure aware representation for antibody engineering
  Bai, Shengyuan, Liu, Zijing, Feng, Bin, Zhang, Jiying, Li, Yu — Communications Biology, 2026-05-25
  abs

• ProtSeqGen: a novel deep learning model for protein sequence design
  Gao, Qiang, Li, Zhijin, Deng, Yang, Ji, Zhiwei — BMC Bioinformatics, 2026-05-26
  abs

• End-to-end molecular structure elucidation from multimodal NMR spectra images using vision transformers
  Chao Han, Xiaolin Pan, Yingkai Zhang — Chemical Science, 2026-05-26
  abs

• Multilabel prediction of virus target proteins via multimodal graph representation learning
  Kuang‐Fu Ma, Kaiyuan Liu, Yu Xin, Rong Liu — PLOS Computational Biology, 2026-05-26
  abs

• Identifying potential ligand-receptor interactions by integrating LSTM network and the attention mechanism for cell-cell communication prediction
  Deng, Yingwei, Chen, Min, Gao, Pengfei, Luo, Ruogu, Li, Zejun, Yao, Yuhua — Journal of Translational Medicine, 2026-05-25
  abs

🧬 Preprints (arXiv + bioRxiv)

75 matched filters -> 20 selected after LLM relevance + novelty ranking.

• 🧬 Evolutionary transfer learning enables organism-wide inference of mammalian enhancer landscapes
  Qiu, C.; Daza, R. M.; Welsh, I. C.; Patwardhan, R. P.; Martin, B. K.; Li, T.; Yang, S.; Mannens, C. C. A.; De Winter, S.; Kempynck, N.; Taylor, M. L.; Fulton, O.; Le, T.-M.; O'Day, D. R.; Lalanne, J.-B.; Domcke, S.; Murray, S. A.; Aerts, S.; Trapnell, C.; Shendure, J. — bioRxiv, 2026-05-27
  abs

• 📄 AMix-2: Establishing Protein as a Native Modality in Large Language Models
  Keyue Qiu, Yixin Wu, Lihao Wang, Yawen Ouyang, Jixiang Yu, Zihan Zhou, Changze Lv, Dongyu Xue, Yuxuan Song, Xinbo Zhang, Hao Wang, Jiangtao Feng, Zhiqiang Gao, Lijun Wu, Xiaoqing Zheng, Ka-Chun Wong, Lei Bai, Ya-Qin Zhang, Wei-Ying Ma, Dahua Lin, Bowen Zhou, Hao Zhou — arXiv, 2026-05-29
  abs

• 📄 mRNAutilus: Multi-Objective-Guided Discrete Generation of mRNA with Optimized Therapeutic Properties
  Sawan Patel, Sophia Tang, Yesol Kim, Yinuo Zhang, Divya Srijay, Ping-Jung Lin, Shambhavi Shubham, Fengmei Pi, Cedric Wu, Sherwood Yao, Pranam Chatterjee — arXiv, 2026-05-29
  abs

• 📄 SwitchCraft: A Programmatic Framework for Designing State-Switching Proteins
  Bowen Jing, Mihir Bafna, Anisha Parsan, Heyuan Michael Ni, David Kwabi-Addo, Bryan Bryson, Adam Klivans, Bonnie Berger — arXiv, 2026-05-29
  abs

• 📄 PhAME: Phenotype-Aware Molecular Editing via Latent Diffusion
  Łukasz Janisiów, Sebastian Musiał, Bartosz Zieliński, Dawid Rymarczyk, Tomasz Danel — arXiv, 2026-05-27
  abs

• 📄 Geometric Flow Matching for Molecular Conformation Generation via Manifold Decomposition
  Yunqing Liu, Yi Zhou, Wenqi Fan — arXiv, 2026-05-25
  abs

• 📄 Don't Retrain, Just Reuse: Recovering Dual-Target Molecules from Single-Target Diffusion Models
  Qingyuan Zeng, Pengxiang Cai, Zixin Guan, Ziyang Chen, Anglin Liu, Lang Qin, Xinyao Lai, Jintai Chen — arXiv, 2026-05-25
  abs

• 📄 Constrained Flow Optimization via Sequential Fine Tuning for Molecular Design
  Sven Gutjahr, Riccardo De Santi, Luca Schaufelberger, Kjell Jorner, Andreas Krause — arXiv, 2026-05-28
  abs

• 📄 PROTOCOL: Late Interaction Retrieval for Protein Homolog Search
  Gabrielle Cohn, Rohan Gumaste, Minh Hoang, Vihan Lakshman — arXiv, 2026-05-27
  abs

• 🧬 AlphaInterp: Mechanistic Interpretability of AlphaFold 3 Reveals How Evolutionary Information Shapes Protein Structure Prediction
  Feldman, J.; Skolnick, J. — bioRxiv, 2026-05-29
  abs

• 📄 Self-Improvement Imitation with Biologically Guided Search for Protein Design Under Oracle Budgets
  Ashima Khanna, Dominik Grimm — arXiv, 2026-05-26
  abs

• 📄 Periodic Topological Deep Learning for Polymer Design and Discovery
  Yasharth Yadav, Tze Kwang Gerald Er, Atsushi Goto, Kelin Xia — arXiv, 2026-05-26
  abs

• 📄 AtomComposer: Discovering Chemical Space from First Principles with Reinforcement Learning
  Bjarke Hastrup, Francois Cornet, Tejs Vegge, Arghya Bhowmik — arXiv, 2026-05-27
  abs

• 📄 CellBRIDGE: Learning Cellular Trajectories via Interaction-Aware Alignment
  Silas Ruhrberg Estévez, Nicolas Huynh, Tennison Liu, Roderik M. Kortlever, Gerard I. Evan, David L. Bentley, Mihaela van der Schaar — arXiv, 2026-05-28
  abs

• 🧬 PRISMA: A tensor-based framework for deconstructing the genetic architecture of complex diseases, with application to diabetic retinopathy
  Xiong, H.; Xu, W.; Ji, A.; Zhong, L.; Liu, S.; Xie, Z.; Yan, J.; Wu, Z. — bioRxiv, 2026-05-28
  abs

• 🧬 DORA: a dose-response autoencoder for interpretable transcriptome-to-viability prediction
  Wang, S.; Allauzen, A.; Opuu, V.; Nghe, P. — bioRxiv, 2026-05-28
  abs

• 📄 Co-folding model guided by structural proteomics
  Alon Shtrikman, Nitzan Simchi, Michal Ran Shchory, Sagie Brodsky, Eran Seger, Kirill Pevzner — arXiv, 2026-05-25
  abs

• 📄 Measure-to-measure Regression with Transformers
  Matthew Vandergrift, Martha White, Yury Polyanskiy, Philippe Rigollet, Lazar Atanackovic — arXiv, 2026-05-27
  abs

• 🧬 Prioritizing peptides for targeted mass spectrometry experiments using deep learning
  Sonthalia, S.; Dasgupta, P.; Hsu, C.; Wen, B.; MacCoss, M. J.; Noble, W. S. — bioRxiv, 2026-05-26
  abs

• 🧬 SynFit: Synergistic Contrastive Learning for Multi-Objective Protein Fitness Prediction and Optimization
  Tu, T.; Huang, W.; Li, Z.; Ding, K.; Yang, Y.; Luo, Y. — bioRxiv, 2026-05-26
  abs