Unlocking diverse molecular binding modes using latent feature sampling

Zenodo (CERN European Organization for Nuclear Research) 2026 Dataset Open access

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Authors: Houtim Lai, Peng Zhou, Huaxian Jia, kun Xie, Geyan Ye, Wei Liu, Alexander Ng, Xiangxiang Zeng
DOI: 10.5281/zenodo.18617574
Cited by: 0

Abstract

Data related to the paper "Unlocking diverse molecular binding modes using latent feature sampling". Detailed descriptions are available at https://github.com/Tencent/DynaHelix. benchmark.zip contains input files and MSA for FoldBench benchmarks covering antigen–antibody, protein–protein, and protein–dsDNA tasks. casp1516.tar.gz stores the predicted structures of CASP15 and CASP16 generated by DynaHelix. ckpt.zip holds the model checkpoint weights. summary.zip includes raw metric data calculated for all predicted structures.

Fields of Study & Subjects

Computational Drug Discovery Methods Protein Structure and Dynamics Protein Interaction Studies and Fluorescence Analysis

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
12 February 2026
Language
EN
Document type
Dataset