Weekly BioML Digest [March 02, 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)

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

• Conditional diffusion with locality-aware modal alignment for generating diverse protein conformational ensembles
  Wang, Baoli, Wang, Chenglin, Chen, Jingyang, Liu, Danlin, Sun, Changzhi, Zhang, Jie, Zhang, Kai, Li, Honglin — Nature Machine Intelligence, 2026-02-25
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• Equivariant diffusion solution for inorganic crystal structure determination from powder X-ray diffraction data
  Yu, Dongfang, Zhu, Zhewen, Leng, Fucheng, Zhu, Yizhou — Nature Communications, 2026-02-27
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• Disentangling coevolutionary constraints for modeling protein conformational heterogeneity
  Li, Shimian, Zhang, Chengwei, Kong, Lupeng, Xue, Yue, Liu, Sirui, Gao, Yi Qin — Communications Chemistry, 2026-02-26
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• Trimbody with rigid AI-designed scaffolds enables atomic-resolution cryo-EM structure determination of small proteins
  Song, Jinyang, Qi, Lei, Li, Yongyue, Zhang, Xue, He, Yushu, Zhang, Zhengshi, He, Dongfang, Gu, Mengjun, Guan, Yuyao, Fang, Hao, Hou, Xuben, Li, Zengpeng, Wang, Wei — Nature Communications, 2026-02-24
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• SPECTRE: A Multimodal Spectral Transformer for Small Molecule Annotation.
  Wang-tu Xu, Byeol Ryu, Anthony Tong, H. H. Mao, Hyunwoo Kim, J. J. Zhao, Chen Zhang, Yiran Xu, Mingxun Wang, William H. Gerwick, G. W. Cottrell — Journal of chemical information and modeling, 2026-02-25
  abs

• VFMol: A Discrete Flow Matching Variational Autoencoder for Molecular Graph Generation.
  Yanglan Gan, Jieli Su, Kaili Wang, Guangwei Xu, Guobing Zou — Journal of chemical information and modeling, 2026-02-26
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• Hot-Spot-Guided Generative Deep Learning for Drug-Like PPI Inhibitor Design
  Sun, Heqi, Li, Jiayi, Zhang, Yufang, Lin, Shenggeng, Chen, Junwei, Tan, Hong, Wang, Ruixuan, Mao, Xueying, Zhao, Jianwei, Li, Rongpei, Wei, Dong-Qing — Interdisciplinary Sciences: Computational Life Sciences, 2026-03-01
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• Multimodal learning on heterogeneous subgraphs and LLMs representation for MHC-peptide binding affinity prediction
  Li, Ruimeng, Wang, Ying, Li, Haozhou, Zhou, Biyi, Peng, Qinke — BMC Bioinformatics, 2026-02-28
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• Leveraging learned representations and multitask learning for lysine methylation site discovery
  Charih, François, Boulter, Mullen, Biggar, Kyle K., Green, James R. — Scientific Reports, 2026-02-23
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• CPE-Pro: A Structure-Sensitive Deep Learning Method for Protein Representation and Origin Evaluation
  Gou, Wenrui, Ge, Wenhui, Tan, Yang, Li, Mingchen, Fan, Guisheng, Yu, Huiqun — Interdisciplinary Sciences: Computational Life Sciences, 2026-03-01
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• BEST: Basic Embedding Search Tool Enhancing Discovery of Novel Enzyme
  Wu, Yuxuan, Yi, Xiao, Tan, Yang, Yu, Huiqun, Fan, Guisheng, Zheng, Gaowei — Interdisciplinary Sciences: Computational Life Sciences, 2026-03-01
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• ChemTorch: A Deep Learning Framework for Benchmarking and Developing Chemical Reaction Property Prediction Models.
  Jasper De Landsheere, A. Zamyatin, Johannes Karwounopoulos, Esther Heid — Journal of chemical information and modeling, 2026-02-25
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• molSimplify 2.0: Improved Structure Generation for Automating Discovery in Inorganic Molecular and Reticular Chemistry.
  Gianmarco G. Terrones, Roland G St Michel, Jacob W Toney, Akash K Ball, Yiran Wang, Aaron G Garrison, Aditya Nandy, Ralf Meyer, Freya Edholm, Changhwan Oh, Sebastian G Pujet, Daniel B. K. Chu, Davut Muhammetgulyyev, Heather J. Kulik — Journal of chemical information and modeling, 2026-02-25
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• Graph-based transformer to predict the octanol–water partition coefficient
  Grigorev, Vyacheslav, Serov, Nikita, Gimadiev, Timur, Poyezzhayeva, Assima, Sidorov, Pavel — Journal of Cheminformatics, 2026-02-27
  abs

• De Novo Structure Prediction from Tandem Mass Spectra: Algorithms, Benchmarks, and Limitations
  Mark Yu. Schneider, Daniil D. Kholmanskikh, K. Romanov, Elena A. Perekina, Sergei A. Nikolenko, R. Lukin, Ivan V. Golov — Molecules, 2026-02-25
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• PON-Del predictor for sequence retaining protein deletions.
  Haoyang Zhang, Muhammad Kabir, Mauno Vihinen — PLoS computational biology, 2026-02-25
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• scRDiT: Generating Single-cell RNA-seq Data by Diffusion Transformers and Accelerating Sampling
  Dong, Shengze, Cui, Zhuorui, Liu, Ding, Lei, Jinzhi — Interdisciplinary Sciences: Computational Life Sciences, 2026-03-01
  abs

• Protein language models enable accurate viral host range prediction
  Beltrán, Jorge F., Belén, Lisandra Herrera, Parraguez-Contreras, Fernanda, Yañez, Alejandro J. — Scientific Reports, 2026-02-25
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• Enhancing CAR-T cell activity prediction via fine-tuning protein language models with generated CAR sequences
  Yoshida, Kei, Hisada, Shoji, Takase, Ryoichi, Okuma, Atsushi, Ishida, Yoshihito, Kawara, Taketo, Miura-Yamashita, Takuya, Ito, Daisuke — BMC Bioinformatics, 2026-02-25
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• BiToxNet: a deep learning framework integrating multimodal features for accurate identification of neurotoxic peptides and proteins
  Wang, Feng, Xie, Peilin, Lin, Xingqiao, Guan, Jiahui, Liu, Chang, He, Xuxin, Lee, Tzong-Yi, Wei, Leyi, Liu, Xiangrong, Yao, Lantian — BMC Biology, 2026-02-26
  abs

🧬 Preprints (arXiv + bioRxiv)

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

• 📄 Zatom-1: A Multimodal Flow Foundation Model for 3D Molecules and Materials
  Alex Morehead, Miruna Cretu, Antonia Panescu, Rishabh Anand, Maurice Weiler, Tynan Perez, Samuel Blau, Steven Farrell, Wahid Bhimji, Anubhav Jain, Hrushikesh Sahasrabuddhe, Pietro Lio, Tommi Jaakkola, Rafael Gomez-Bombarelli, Rex Ying, N. Benjamin Erichson, Michael W. Mahoney — arXiv, 2026-02-24
  abs

• 🧬 MolX: A Geometric Foundation Model for Protein-Ligand Modelling
  Liu, J.; Pan, T.; Guo, X.; Ran, Z.; Hao, Y.; Yang, Y.; Ng, A. P.; Pan, S.; Song, J.; Li, F. — bioRxiv, 2026-03-01
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• 🧬 Deep learning framework ChIANet predicts protein-mediated chromatin architecture across functional contexts
  Luo, H.; Wen, R.; Tang, L.; Chen, L.; Li, M. — bioRxiv, 2026-02-25
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• 🧬 ARCH3D: A foundation model for global genome architecture
  Galioto, N.; Stansbury, C.; Gorodetsky, A. A.; Rajapakse, I. — bioRxiv, 2026-02-25
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• 📄 CryoNet.Refine: A One-step Diffusion Model for Rapid Refinement of Structural Models with Cryo-EM Density Map Restraints
  Fuyao Huang, Xiaozhu Yu, Kui Xu, Qiangfeng Cliff Zhang — arXiv, 2026-02-25
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• 🧬 A General Framework for Injecting BiophysicalPriors into Protein Embeddings
  Feldman, J.; Maechler, A.; Wang, D.; Shakhnovich, E. — bioRxiv, 2026-02-23
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• 📄 De novo molecular structure elucidation from mass spectra via flow matching
  Ghaith Mqawass, Tuan Le, Fabian Theis, Djork-Arné Clevert — arXiv, 2026-02-23
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• 📄 Regressor-guided Diffusion Model for De Novo Peptide Sequencing with Explicit Mass Control
  Shaorong Chen, Jingbo Zhou, Jun Xia — arXiv, 2026-02-23
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• 🧬 ProChoreo: de novo Binder Design from Conformational Ensembles with Generative Deep Learning
  Ding, S.; Zhang, Y. — bioRxiv, 2026-02-27
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• 🧬 Improved multimodal protein language model-driven universal biomolecules-binding protein design with EiRA
  Zeng, W.; Zou, H.; Li, X.; Dou, Y.; Wang, X.; Peng, S. — bioRxiv, 2026-02-24
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• 📄 Inference-time optimization for experiment-grounded protein ensemble generation
  Advaith Maddipatla, Anar Rzayev, Marco Pegoraro, Martin Pacesa, Paul Schanda, Ailie Marx, Sanketh Vedula, Alex M. Bronstein — arXiv, 2026-02-27
  abs

• 🧬 Contrastive learning for antibody-antigen sequence-to-specificity prediction
  Lee, H.; Castro, K.; Renwick, S.; Stalder, L.; Glanzer, W.; Kumar, R.; Chen, N.; Scheck, A.; Yermanos, A.; Mason, D.; Reddy, S. T. — bioRxiv, 2026-02-26
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• 🧬 Transforming Histology into Virtual Multiplex Immunofluorescence to Decode Prognostic Spatial Immunity in Hepatocellular Carcinoma
  Cai, L.; Jiang, S.; Liang, J.; Liu, F.; Zhang, B.; Reitsam, N. G.; Zeng, Q.; Ma, Y.; Li, Z.; Feng, S.; Hu, M.; Zhang, X.; Zhang, J.; Kather, J. N.; Zhang, Y.; Liang, W. — bioRxiv, 2026-02-26
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• 🧬 Coupling codon and protein constraints decouples drivers of variant pathogenicity
  Chen, R.; Palpant, N.; Foley, G.; Boden, M. — bioRxiv, 2026-02-25
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• 🧬 OriGene: A Self-Evolving Virtual Disease Biologist Automating Therapeutic Target Discovery
  Zhang, Z.; Qiu, Z.; Wu, Y.; Li, S.; Wang, D.; Liu, Y.; Zhou, Z.; Hu, Y.; Chen, Y.; An, D.; Wang, Y.; Li, Y.; Zhong, Z.; Ou, C.; Wang, Z.; Tang, F.; Chen, J. X.; Ma, R.; Li, J.; Wang, X.; Lu, W.; Xue, H.; Zhang, W.; Wei, Z.; Ma, R.; Shi, Z.; Wang, K.; Liu, Q.; Dong, B.; He, Y.; Liu, T.; Gu, J.; Song, S.; Feng, Q.; Zhang, J.; Zhang, B.; Tian, L.; Bai, L.; Gao, Q.; Sun, S.; Zheng, S. — bioRxiv, 2026-02-25
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• 🧬 scDesignPop generates realistic population-scale single-cell RNA-seq for power analysis, benchmarking, and privacy protection
  Dong, C. Y.; Cen, Y.; Song, D.; Li, J. J. — bioRxiv, 2026-02-25
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• 🧬 CellAwareGNN: Single-Cell Enhanced Knowledge Graph Foundation Model for Drug Indication Prediction
  Zhang, X.; Jeong, E.; Yan, C.; Feng, Y.; Lyu, L.; Guo, X.; Chen, Y. — bioRxiv, 2026-02-23
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• 🧬 A Comprehensive Atlas and Machine-Learning Framework for Predicting IDR-Protein Binding Affinity
  Adhikari, S.; Choudhuri, S.; Mondal, J. — bioRxiv, 2026-02-23
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• 🧬 Geometric-Evolutionary Deep Learning Decodes the Human GPCR-Metabolome Interactome and Enables Systematic De-Orphanization
  Sakuma, T.; Otani, Y.; Shimizu, H. — bioRxiv, 2026-02-23
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• 🧬 Random Matrix Theory-guided sparse PCA for single-cell RNA-seq data
  Chardes, V. — bioRxiv, 2026-02-28
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