Weekly BioML Digest [May 25, 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)

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

• Zero-shot de novo peptide sequencing with open posttranslational modification discovery
  Mao, Zeping, Peng, Chao, Chen, Yuling, Wu, Ping, Zhang, Qianqiu, Yu, Yonghan, Zhang, Ruixue, Xin, Lei, Shan, Baozhen, Deng, Haiteng, Li, Ming — Nature Biotechnology, 2026-05-19
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• AI-guided redesign of laboratory-evolved reverse transcriptases enhances prime editing
  Tao, Y. Allen, Sakai, Holt A., Jiang, Allen Y., Krasnow, Nicholas A., Vaganov, Vasilii S., Shim, Brian, Barsdale, Zachary, Pandey, Smriti, Ahmed, Nouraiz, Na, Man, Liao, Ting-Wei, Oye, Keyede, Cristian, Ana, Zhang, Emily, Xu, Joy A., Bulcaen, Mattijs, Liu, David R. — Nature Biotechnology, 2026-05-21
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• Deep learning for predicting patient drug response by transferring gene-level and cell-level knowledge to tumors
  Sung, Inyoung, Bang, Dongmin, Kim, Sun, Lee, Sangseon — npj Precision Oncology, 2026-05-20
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• Interpretable deep learning framework for mapping E3–substrate binding interfaces
  Li, Dianke, Zhang, Yuting, Liu, Yuan, Zhang, Zihao, Qu, Yingjie, Li, Jiajun, Jiang, Linyang, Diao, Lihong, Zhang, Ziding, Zhang, Lingqiang, Cui, Chun-Ping, Li, Dong — Nature Communications, 2026-05-20
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• Advancing generative large language models toward discriminative performance in protein function prediction
  Lv, Ying, Xu, Yifan, Xu, Gang, Ma, Jianpeng — Genome Biology, 2026-05-21
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• DGAT: a dual-graph attention network for inferring spatial protein landscapes from transcriptomics
  Wang, Haoyu, Cody, Brittany, Saavedra, Manuel, Faccioli, Lanuza A. P., Florentino, Rodrigo M., Soto-Gutierrez, Alejandro, Osmanbeyoglu, Hatice Ulku — Nature Communications, 2026-05-21
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• Decoding spatial transcriptomics across multicellular and subcellular resolutions
  Zhao, Chongyue, Liu, Tianhao, Miller, Leigh M., Li, Hongdou, Zhao, Hanqiu, Barnett, Daniel, Yuan, Ruizhi, Zhang, Hua, Wang, Qian, Eddens, Taylor, Torok, Kathryn S., Zhou, Anny Xiaobo, Dai, Zhiyu, Alcorn, John F., Huang, Heng, Chen, Wei — Nature Communications, 2026-05-18
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• HELIX: a scalable model for predicting context-dependent regulation of RNA splicing and isoform usage
  Zhou, Zihan, Wu, Bingqi, Zheng, Xin, Song, Lipu, Zhang, Shuai, Han, Dali, Liu, Zhaoqi, Gao, Yuan — Nature Computational Science, 2026-05-19
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• ProSSF: integrating sequence, structure, and gene ontology for prediction of protein stability, interaction, and function
  Jiang, Tongqiang, Zhu, Yongshan, Liu, Zhenqiao, Yi, Xiaowei, Zhang, Qingchuan, Song, Shaoyi — Molecular Genetics and Genomics, 2026-05-19
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• NN-xTB: density functional accuracy at semi empirical speed with neural network extended tight binding
  Xia, Yufan, Thie, Albert, Soon, Joshua, Barca, Giuseppe M. J. — Nature Communications, 2026-05-20
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• ExPO: an exposure-conditioned neural operator for L1000 signature prediction
  Spadaro, Austin, Sharma, Alok, Dehzangi, Iman — Journal of Cheminformatics, 2026-05-21
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• PlantGFM: A Genomic Foundation Model for Discovery and Creation of Plant Genes
  Changhao Li, Qizhe Zhang, Hanchen Chen, Kepeng Lin, Chengfang Luo, Mengying Yang, Wei Xu, Fan Yao, Jianbing Yan, Qingyong Yang, Xuehai Hu — Advanced Science, 2026-05-20
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• Novel molecular design via a scaffold-aware transformer with multi-scale attention mechanisms
  Park, Junyoung, Yoo, Sunyong — Journal of Cheminformatics, 2026-05-19
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• Harnessing generative AI for predicting and optimizing antimicrobial peptides against drug-resistant infections
  Clemens, Sandra, Löchel, Hannah Franziska, Häußer, Nico, Wannemacher, Felix, Bertrams, Wilhelm, Schmeck, Bernd, Heider, Dominik — npj Antimicrobials and Resistance, 2026-05-22
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• Data Driven Discovery of Reductive Aminases for Arylamine Substrates
  Caroline K. Brennan, M. A. Abdo, R. Scism, Liu Cao, Carlos A. Martinez, Russell D. Lewis — Advanced Synthesis & Catalysis, 2026-05-21
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• Machine learning framework for cost effective deep mutational scanning through targeted substitution profiling
  Morgan, Emily, Govender, Shaylyn, Singh, Prashant, Goodfellow, Ian, Graham, Stephen C., Tastan Bishop, Nigel, Bishop, Özlem Tastan — BMC Bioinformatics, 2026-05-19
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• Molecular arms race classifier for decrypting venom peptide and ion channel interactions
  Favour Achimba, Arezoo Bybordi, Mariam Gelashvili, J. Ramirez, A. Raja, Weigang Qiu, M. Holford — Digital Discovery, 2026-05-19
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• Prediction of HIV-1 sensitivity to broadly neutralizing antibodies using statistical distribution sampling (SDS) technology
  He, Lily, Pan, Kaixin, Shi, Youlin, Li, Kun Peter, Ruan, Yuhua, Li, Dan, Cui, Hengjian — BMC Bioinformatics, 2026-05-18
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• Semantic embedding of variant effect annotations enables rapid and accurate pathogenicity prediction with VUS.Life
  Wu, Jiawei, Stutzman, Marissa, Muriello, Michael, Lincoln, Joy, Basel, Donald G., Gai, Xiaowu — Scientific Reports, 2026-05-23
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• ToxiGuard: an AOP-guided mechanistically interpretable framework for multi-organ toxicity prediction
  Zhao, Caiyun, Wang, Jing, Bo, Xiaochen, He, Song — Archives of Toxicology, 2026-05-20
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🧬 Preprints (arXiv + bioRxiv)

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

• 📄 DCFold: Efficient Protein Structure Generation with Single Forward Pass
  Zhe Zhang, Yuanning Feng, Yuxuan Song, Keyue Qiu, Hao Zhou, Wei-Ying Ma — arXiv, 2026-05-18
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• 🧬 Prediction of Transcription Factor DNA Binding Affinity with High-Throughput Kd Measurements and Deep Learning
  Wang, Z.; Wang, D.; Shen, K.; Luo, J.; Wang, X.; Wu, N.; Lang, Y.; Wang, X.; Ren, J.; Dong, W.; Pan, L.; Li, G.; Li, D.; Xie, C.; Zhang, Z.; Lyu, Y.; Yu, S.; Shan, L.; Zhang, N.; Yan, J.; Chen, M.; Xie, X. S. — bioRxiv, 2026-05-20
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• 🧬 AE-PocketMiner Uses Attention to Simultaneously Predict Cryptic Pockets and Their Allosteric Coupling
  Zhang, S.; Mishra, P.; Kelly, D.; Kumar, R.; Bowman, G. R. — bioRxiv, 2026-05-23
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• 🧬 Comprehensive interaction profiling and machine learning prediction of bacteriophage infectivity across clinically diverse Pseudomonas aeruginosa
  Piya, D.; Noonan, A. J. C.; Selvakumar, H.; Alayouni, M.; Koderi Valappil, S.; Maucourt, F.; Murray, I.; Svab, M.; Bousliman, C.; Heidenblut, M.; Orihuela, B.; Kazakov, A.; Carlson, H.; Yao, Y.; Smith, E.; Roux, S.; Deutschbauer, A.; Inman, J.; Arkin, A. P.; Mutalik, V. K. — bioRxiv, 2026-05-20
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• 📄 AgForce Enables Antigen-conditioned Generative Antibody Design
  Mansoor Ahmed, Murray Patterson — arXiv, 2026-05-20
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• 🧬 CatIF-RL: Activity-Oriented Enzyme Sequence Design by Steered Inverse Protein Folding
  Li, Y.; Xiong, J.; Zhang, Y.; Cai, T.; Fu, C.; Li, S.; Xu, W.; Lyu, R.; Chen, Z.; Guo, Z.; Gong, X.; Wang, F. — bioRxiv, 2026-05-18
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• 📄 FLAG: Foundation model representation with Latent diffusion Alignment via Graph for spatial gene expression prediction
  Qi Si, Penglei Wang, Yushuai Wu, Yifeng Jiao, Xuyang Liu, Xin Guo, Yuan Qi, Yuan Cheng — arXiv, 2026-05-18
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• 🧬 Rescuing true protein binders from AI hallucinations via zero-shot, ensemble-driven statistical physics scoring
  Chou, C.-H.; Hong, X.; Xu, J. — bioRxiv, 2026-05-18
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• 📄 MSAlign: Aligning Molecule and Mass Spectra Foundation Models for Metabolite Identification
  Paul Krzakala, Gabriel Melo, Camille Lançon, Charlotte Laclau, Rémi Flamary, Etienne Thévenot, Florence d'Alché-Buc — arXiv, 2026-05-19
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• 📄 Generating Physically Consistent Molecules with Energy-Based Models
  Christoph Griesbacher, Lea Bogensperger, Andreas Habring, Thomas Pock — arXiv, 2026-05-18
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• 📄 Generative Pseudo-Force Fields for Molecular Generation
  Stefaan Simon Pierre Hessmann, Khaled Kahouli, Stefan Gugler, Michael Plainer, Frank Noé, Klaus-Robert Müller, Niklas Wolf Andreas Gebauer — arXiv, 2026-05-18
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• 📄 EvoStruct: Bridging Evolutionary and Structural Priors for Antibody CDR Design via Protein Language Model Adaptation
  Mansoor Ahmed, Sujin Lee, Umar Khayaz, Murray Patterson — arXiv, 2026-05-20
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• 📄 ConTact: Contact-First Antibody CDR Design via Explicit Interface Reasoning
  Mansoor Ahmed, Spencer VonBank, Nadeem Taj, Sujin Lee, Naila Jan, Murray Patterson — arXiv, 2026-05-20
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• 📄 Hierarchical Contrastive Learning for Multi-Domain Protein-Ligand Binding
  Shuo Zhang, Rongqi Hong, Huifeng Zhang, Jian K. Liu — arXiv, 2026-05-19
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• 🧬 Deciphering interaction syntax via decoupling intrinsic lineages and niche pressure
  Guo, Q.; Zhong, W.; Zeng, Z.; Nie, Q.; Zhou, P.; Zhang, L. — bioRxiv, 2026-05-20
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• 🧬 PocketBagger: Generalizable pocket druggability prediction via positive-unlabeled learning
  Gingrich, P. W.; Biswas, A.; Mica, I. L.; Brammer, K. M.; Shu, Z.; Maxwell, D. S.; Russell, K. P.; Al-Lazikani, B. — bioRxiv, 2026-05-19
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• 🧬 FlexENN: A Graph Neural Network for Binding Energy Prediction of Globular and Intrinsically Disordered Proteins
  Irshad, M.; Ori-McKenney, K. M.; Dima, R. I. — bioRxiv, 2026-05-18
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• 🧬 Spatiotemporal graph neural networks reveal conformational binding signature in protein dynamics
  Motta, S.; Santini, G.; Mansoor, S.; Nezhad, F. H.; Meli, M.; Pandini, A. — bioRxiv, 2026-05-21
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• 📄 Atom-level Protein Representation Learning Improves Protein Structure Prediction
  Taewon Kim, Hyosoon Jang, Hyunjin Seo, Seonghwan Seo, Hyeongwoo Kim, Wonho Zhung, Mingyeong Shin, Wooyoun Kim, Sungsoo Ahn — arXiv, 2026-05-21
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• 🧬 Overcoming systematic data biases enables accurate prediction of enzyme kcat fold-changes for computational protein design
  Rousset, Y.; Kroll, A.; Lercher, M. — bioRxiv, 2026-05-21
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