activity
20242026
most citedMolFORM: Multi-modal Flow Matching for Structure-Based Drug Design

1 citations · 1 across the 2 of their papers we have counts for

collaborators

5 papers

cs.CE20261 cited

MolFORM: Multi-modal Flow Matching for Structure-Based Drug Design

Jie Huang, Daiheng Zhang

Structure-based drug design (SBDD) seeks to generate molecules that bind effectively to protein targets by leveraging their 3D structural information. While diffusion-based generat…

cs.CE2026

STRIDE: Post-Training LLMs to Reason and Refine Bio-Sequences via Edit Trajectories

Daiheng Zhang, Shiyang Zhang, Sizhuang He +3

Discrete biological sequence optimization often requires goal-directed, parser-valid edits to an existing protein or molecule. Diffusion models support iterative refinement but do…

cs.LG2025

Elucidating the Design Space of Multimodal Protein Language Models

Cheng-Yen Hsieh, Xinyou Wang, Daiheng Zhang +5

Multimodal protein language models (PLMs) integrate sequence and token-based structural information, serving as a powerful foundation for protein modeling, generation, and design.…

cs.LG2025

Leveraging Multi-modal Representations to Predict Protein Melting Temperatures

Daiheng Zhang, Yan Zeng, Xinyu Hong +1

Accurately predicting protein melting temperature changes (Delta Tm) is fundamental for assessing protein stability and guiding protein engineering. Leveraging multi-modal protein…

cs.LG2024

Rectified Flow For Structure Based Drug Design

Daiheng Zhang, Chengyue Gong, Qiang Liu

Deep generative models have achieved tremendous success in structure-based drug design in recent years, especially for generating 3D ligand molecules that bind to specific protein…