arXiv:2507. 03209v2 Announce Type: replace-cross Abstract: The discovery of new ionizable lipids for efficient lipid nanoparticle (LNP)-mediated RNA delivery remains a major bottleneck in RNA therapeutics development.
By Asal Mehradfar, Mohammad Shahab Sepehri, Jose Miguel Hernandez-Lobato, Glen S. Kwon, Mahdi Soltanolkotabi, Salman Avestimehr, Morteza Rasoulianboroujeni
arXiv:2505. 20346v3 Announce Type: replace-cross Abstract: Function-guided protein design is a crucial task with significant applications in drug discovery and enzyme engineering.
By Jiahao Kuang, Nuowei Liu, Jie Wang, Changzhi Sun, Tao Ji, Yuanbin Wu
The paper introduces NSA-Bench, a public benchmark for predicting nano self‑assembly (NSA) between molecular pairs, framing it as a binary classification problem. It presents NSA‑Net, a multimodal learning framework that fuses graph topology, sequence semantics, and physicochemical descriptors to predict self‑assembly, achieving high ROC‑AUC scores and outperforming existing baselines. The study also demonstrates how NSA‑Net’s predictions can guide experimental formulation refinement through an NSA‑Agent case study.
By Quan Hao, Mengyue Fan, Zifan Dong, Jianduo Zhao, Changhao Xiao, Shangqing Jiao, Hao Zhang, Yudong Wang, Fei Xia, Jigang Wang, Liguo Zhang, Chong Qiu
The paper introduces LambdaDockScore, a protein‑protein docking scoring function that leverages the LambdaLoss loss from Learning‑to‑Rank to improve pose ranking. By fine‑tuning the energy prediction head of DFMDock on 2.9 million decoy poses from the DIPS dataset, LambdaDockScore outperforms the state‑of‑the‑art EuDockScore on CAPRI benchmark targets, achieving higher accuracy in top‑1 and top‑5 predictions. It also enhances ranking for antibody‑antigen and protein‑protein complexes with extreme binding interface sizes.
By Richard Zhu, Darren Xu, Lee-Shin Chu, Jeffrey J. Gray
arXiv:2605. 01625v3 Announce Type: replace Abstract: Proteins are inherently multiscale physical systems whose functional properties emerge from coordinated structural organization across multiple spatial resolutions, ranging from atomic interactions to global fold topology.
By Viet Thanh Duy Nguyen, John K. Johnstone, Truong-Son Hy
arXiv:2606. 31126v1 Announce Type: new Abstract: Predicting biomolecular properties from limited labeled data is a central bottleneck in protein engineering and small-molecule design.
By Davy Guan, Lu Zhang, Asiri Wijesinghe, Allen Zhu, He Zhao, Helen Power, F. Hafna Ahmed, Andrew Warden, Cheng Soon Ong, Daniel M. Steinberg