Weekly BioML Digest [April 27, 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)

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

• Predicting RNA 3D structure and conformers using a pre-trained secondary structure model and structure-aware attention
  Wang, Wenkai, Peng, Zhenling, Yang, Jianyi — Nature Machine Intelligence, 2026-04-21
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• SyntheMol-RL: a flexible reinforcement learning framework for designing easily synthesizable antibiotics
  Swanson, Kyle, Liu, Gary, Catacutan, Denise B, McLellan, Stewart, Arnold, Autumn, Tu, Megan M, Brown, Eric D, Zou, James, Stokes, Jonathan M — Molecular Systems Biology, 2026-04-23
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• In silico discovery of nanobody binders to a G-protein coupled receptor using AlphaFold-Multimer
  Harvey, Edward P., Smith, Jeffrey S., Hurley, Joseph D., Granados, Alyana J., Schmid, Ernst W., Liang-Lin, Jason G., Zhang, Huyang, Meara, Emily M., Wren, Elizabeth K., Paul, Steffanie, Ferguson, Matthew P., Calvillo-Miranda, Victor G., Alcantar, Miguel A., Marks, Debora S., Walter, Johannes C., Kruse, Andrew C., Susa, Katherine J. — Nature Communications, 2026-04-23
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• DeepDrugDiscovery identifies blood–brain barrier permeable autophagy enhancers for Alzheimer’s disease
  Dong, Yu, Xiao, Xianglu, Zhuang, Xu-Xu, Wu, Wenfan, Wang, Zi-Ying, Zhang, Shuang, Li, Jin-Tao, Zhang, Ke, Fu, Wen-Yu, Chen, Jun-Ming, Xiong, Shi Hang, Deng, Shenglong, Li, Krinos, Ma, Chao, Jin, Wangzhen, Jin, Xurui, Cai, Qiwei, Shen, Han-Ming, Li, Min, Su, Huanxing, Wan, Jian-Bo, Yu, Hua, Ouyang, Defang, Ye, Keqiang, Fang, Evandro F., Tan, Chris Soon Heng, Yang, Guang, Niu, Zhangming, Lu, Jia-Hong — Nature Biomedical Engineering, 2026-04-24
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• Structure-informed deep generation enables de novo metabolite annotation in untargeted metabolomics
  Wang, Hongmiao, Zhang, Haosong, Zhu, Zheng-Jiang — Nature Communications, 2026-04-20
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• Repertoire-scale antibody structural prediction informs therapeutic design
  Z. Sang, Yufei Xiang, Wei Huang, Paul R. Sargunas, Yong Joon (Jeffery) Kim, Zirui Feng, Derek J. Taylor, Yi Shi — Science Advances, 2026-04-24
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• Prediction and functional interpretation of inter-chromosomal genome architecture from DNA sequence with TwinC
  Jha, Anupama, Hristov, Borislav, Wang, Xiao, Wang, Sheng, Greenleaf, William J., Kundaje, Anshul, Aiden, Erez Lieberman, Bertero, Alessandro, Noble, William Stafford — Nature Communications, 2026-04-20
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• Mosaic integration of spatial multi-omics with SpaMosaic
  Yan, Xuhua, Fang, Zhaoyu, Ang, Kok Siong, Olst, Lynn van, Edwards, Alex, Watson, Thomas, Zheng, Ruiqing, Zhang, Di, Fan, Rong, Li, Min, Gate, David, Chen, Jinmiao — Nature Genetics, 2026-04-24
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• DposFinder: an interpretable transformer model for predicting phage-derived polysaccharide depolymerases and their host capsular serotypes
  Shen, Yanxiang, Lun, Heyuan, Zhang, Yumeng, Wang, Zhikang, Tai, Cui, Chen, Xiaohua, Song, Jiangning, He, Ping, Ou, Hong-Yu — Genome Medicine, 2026-04-20
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• Convolutional neural networks quantify antibiotic resistance in Mycobacterium tuberculosis with diagnostic grade accuracy and predict treatment response
  Kulkarni, Sanjana G., Green, Anna G., Mann, Brendon C., Malatesta, Samantha, Kulkarni-Goodwin, Suchitra, Cesare, Nina, Mulaudzi, Shandukani, Rawoot, Noorjahn, Warren, Robin M., Jacobson, Karen R., Farhat, Maha R., MIC-ML Consortium — Nature Communications, 2026-04-24
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• Generative approaches to kinetic parameter inference in metabolic networks via latent space exploration
  Choudhury, Subham, Toumpe, Ilias, Gabouj, Oussama, Behler, Jakob Sebastian, Hatzimanikatis, Vassily, Miskovic, Ljubisa — Nature Communications, 2026-04-20
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• TransBindpMHCI: a transformer-based model for pan-specific MHC-I peptide binding prediction
  Xu, Hu, Ni, Yuanli, Chai, Zixuan, Cui, Xuan, Lei, Xia, Liu, Limei, Shan, Juanjuan, Qian, Cheng — BMC Bioinformatics, 2026-04-20
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• Context-aware multi-property antibody predictor: a novel framework integrating text and protein language models
  Giancardo, Luca, Yilmaz, Melih, Lee, Edward, Ren, Ke, Zhao, Yue, Trang, Gordon, Sonmez, Kemal, Guo, Lan, Cheng, Nina — npj Systems Biology and Applications, 2026-04-25
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• Gelm: graph-based Tanimoto similarity grouping pretraining and entropy-guided conformer selection finetuning for large language models
  Chen, Zhuo, Wang, Sihan, Chen, Linjiang, Du, Wenjie, Wang, Yang — Science China Information Sciences, 2026-04-20
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• Geometry-aware graph attention networks to explain single-cell chromatin states and gene expression with SEAGALL
  Malagoli, Gabriele, Hanel, Patrick, Danese, Anna, Wolf, Guy, Colomé-Tatché, Maria — Genome Biology, 2026-04-23
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• Full-DIA enables complete single-cell proteomics from diaPASEF using deep learning
  Song, Jian, Momenzadeh, Amanda, Liu, Hebin, Shen, Chengpin, Meyer, Jesse G., Wu, Xiaohui — Genome Biology, 2026-04-21
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• ChemScreener: an active learning enabled hit discovery workflow with WDR5 inhibitor case study
  Shen, Lingling, Fang, Jian, Liu, Lulu, Wang, Rena, Jenkins, Jeremy L., Wang, He — Journal of Cheminformatics, 2026-04-20
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• MPRDR: A Multi-Path Relational Drug Repurposing Framework Grounded in Graph-Theoretic Principles
  Pharsana Parveen M, Stanis Arul Mary A — International Journal of Drug Delivery Technology, 2026-04-23
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• Generalizable deep-learning-based mRNA-protein interaction prediction strongly depends on protein diversity
  Yu, Yu-Huai, Hong, Han-Ting, Yang, Tzu-Hsien — Journal of Cheminformatics, 2026-04-21
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• Reindeer: a protein-ligand feature generator software for machine learning algorithms
  Rayka, Milad, Naghavi, S. Shahab — BMC Bioinformatics, 2026-04-22
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🧬 Preprints (arXiv + bioRxiv)

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

• 📄 scpFormer: A Foundation Model for Unified Representation and Integration of the Single-Cell Proteomics
  Qifeng Zhou, Lei Yu, Yuzhi Guo, Yuwei Miao, Hehuan Ma, Wenliang Zhong, Lin Xu, Junzhou Huang — arXiv, 2026-04-21
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• 🧬 Adapting Co-Folding Models for Structure-Based Protein-Protein Docking Through Flow Matching
  Xu, D.; Chu, L.-S.; Gray, J. J. — bioRxiv, 2026-04-24
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• 🧬 Protein structure-informed deep learning enables species-specific codon optimization
  Jin, W.; Tan, W.; Li, H.; Ji, X.; Li, M.; Zhang, D.; Xu, J. — bioRxiv, 2026-04-24
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• 🧬 CellChem: Cellular transcriptional responses reshape molecular representation space for efficient and multi-scale drug discovery
  Chen, J.; Lin, L.; Wang, Y.; Lin, Y.; Li, Y.; Zhang, W.; Fu, Y.; Xie, J.; Zhu, J.; Sun, C.; Shi, G.; Wang, Z.; Lin, H.; Wang, L.; Deng, M.; Lai, L.; Pei, J. — bioRxiv, 2026-04-24
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• 📄 Quotient-Space Diffusion Models
  Yixian Xu, Yusong Wang, Shengjie Luo, Kaiyuan Gao, Tianyu He, Di He, Chang Liu — arXiv, 2026-04-23
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• 📄 An Integrated Deep-Learning Framework for Peptide-Protein Interaction Prediction and Target-Conditioned Peptide Generation with ConGA-PePPI and TC-PepGen
  Chupei Tang, Junxiao Kong, Moyu Tang, Di Wang, Jixiu Zhai, Ronghao Xie, Shangkun Sima, Tianchi Lu — arXiv, 2026-04-20
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• 🧬 EpiRanha: Hunting for Epitope Similarity with a Structure- and Residue-Aware Graph Neural Network
  Francissen, T.; Babukhian, M.; Britze, H.; Wilke, Y.; Spreafico, R.; Demharter, S.; Arts, M. — bioRxiv, 2026-04-23
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• 🧬 Understanding Language Model Scaling on Protein Fitness Prediction
  Hou, C.; Liu, D.; Zafar, A.; Shen, Y. — bioRxiv, 2026-04-20
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• 📄 Multi-Objective Reinforcement Learning for Generating Covalent Inhibitor Candidates
  Renee Gil — arXiv, 2026-04-21
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• 📄 Structure-guided molecular design with contrastive 3D protein-ligand learning
  Carles Navarro, Philipp Tholke, Gianni de Fabritiis — arXiv, 2026-04-21
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• 📄 BioMiner: A Multi-modal System for Automated Mining of Protein-Ligand Bioactivity Data from Literature
  Jiaxian Yan, Jintao Zhu, Yuhang Yang, Qi Liu, Kai Zhang, Zaixi Zhang, Xukai Liu, Boyan Zhang, Kaiyuan Gao, Jinchuan Xiao, Enhong Chen — arXiv, 2026-04-23
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• 🧬 Geometric Theoretical Framework for Dynamic Protein Mutation Detection Models: Defect Awareness and Pathogenicity Prediction
  Shao, H. — bioRxiv, 2026-04-26
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• 🧬 Concordia: Spatial Domain Detection via Augmented Graphs for Population-Level Spatial Proteomics
  Liu, S.; Hsu, L.; Sun, W. — bioRxiv, 2026-04-22
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• 📄 Sheaf Neural Networks on SPD Manifolds: Second-Order Geometric Representation Learning
  Yuhan Peng, Junwen Dong, Yuzhi Zeng, Hao Li, Ce Ju, Huitao Feng, Diaaeldin Taha, Anna Wienhard, Kelin Xia — arXiv, 2026-04-22
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• 📄 Transferable SCF-Acceleration through Solver-Aligned Initialization Learning
  Eike S. Eberhard, Viktor Kotsev, Timm Güthle, Stephan Günnemann — arXiv, 2026-04-23
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• 🧬 Mechanotransduction-Aware Causal Omics on Tissue Scaffolds: A Controlled Mechanochemical Framework for Identifying Disease Genes Beyond Pure Omics Analysis
  Xu, T.; Hu, Z.; Sun, X.; Xiong, M. — bioRxiv, 2026-04-22
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• 🧬 A narrow thermodynamic design window governs selective membrane permeabilization and antiviral activity of amphipathic peptides
  Hilten, N. v.; Maltitz, P. v.; Aschmann, D.; Hoernke, M.; Krebs, M.; Methorst, J.; Kros, A.; Münch, J.; Risselada, H. J. — bioRxiv, 2026-04-22
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• 🧬 Integrating Metabolic Networks into Hybrid Bioprocess Models
  Gotsmy, M.; Guillen-Gosalbez, G. — bioRxiv, 2026-04-24
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• 🧬 SNPic: SNP Topic Modeling for Interpretable Clustering of Complex phenotypes
  Leyi, Z.; Seiler, C.; Speed, D.; Micheroli, R.; Ospelt, C. — bioRxiv, 2026-04-24
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• 📄 Closing the Domain Gap in Biomedical Imaging by In-Context Control Samples
  Ana Sanchez-Fernandez, Thomas Pinetz, Werner Zellinger, Günter Klambauer — arXiv, 2026-04-22
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