DiffPro, a novel framework that integrates a Latent Diffusion Model (LDM) as a structural prior, confirms that the diffusion prior successfully regularizes the latent space, mitigating task representation collapse and enabling robust, high-precision predictions for combination therapy design.
Shu-Ting Jin, Xu Guo, An-Qi Huang et al.· Proceedings of the 32nd ACM...· 0 citations
Diagnostics reveal that RL on PLMs is governed by two reward properties: verifiability, whether the reward is a fixed environment or a learned surrogate vulnerable to distribution shift, and coverage, the fraction of sequence space giving an informative gradient.
Hanqun Cao, Hongrui Zhang, Junde Xu et al.· Proceedings of the 32nd ACM...· 0 citations
Reinforcement learning (RL) is increasingly applied to Protein Language Models (PLMs), yet its effectiveness varies across tasks, and standard metrics such as pass@k can rise even when the model's solvable problem set is shrinking. We introduce two capability-level diagnostics. The Expansion-Shrinkage Ratio (ESR) measu...
Hanqun Cao, Hongrui Zhang, Junde Xu et al.· Proceedings of the 32nd ACM...· 0 citations
MultiGeo is a DTA prediction framework that explicitly leverages multiple protein conformations rather than a single snapshot, and introduces a disagreement-aware gating mechanism that adaptively fuses this ensemble representation with the dominant structure only when the additional conformers provide complementary inf...
Rui-Da Zeng, Cheng Guo, Ya-Jie Meng et al.· Proceedings of the Thirty-Fi...· 0 citations
Accurate prediction of drug-target binding affinity (DTA) is a key task in virtual screening. However, current computational methods face a key challenge: sequence-based approaches often fail to capture critical spatial information, while structure-based models rely on computationally expensive 3D coordinates, which re...
Junlin Xu, Ye Yuan, Menglong Hu et al.· IEEE journal of biomedical a...· 0 citations
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