TEMA-ENM model parameters: bilinear attention network for ghrelin receptor agonist/antagonist classification

Abstract

Trained model parameters for the manuscript TEMA-ENM: An Interpretable Attention-Topology Framework Separates Affinity- and Efficacy-Associated Residue Signals in the Ghrelin Receptor (RSC Digital Discovery, under review). This record contains parameters only: the BiLSTM-BAN backbone pre-trained on BindingDB (49,199 pairs over 2,623 targets, epoch 94), and the ten GHSR fine-tuned checkpoints (seeds 42-51) used for every stability analysis in the paper. README.md gives the per-seed epoch, test AUROC and AUPRC, md5 checksums, the architecture, and the commands to reproduce the attention read-out. Source code, the curated GHSR dataset and the leakage-controlled partitions are not in this record. They are on GitHub at https://github.com/CHIHX12/interpretable-attention-topology-drug-discovery and in the accompanying software record. The separation is deliberate: the GHSR dataset carries a ShareAlike obligation inherited from ChEMBL and cannot be released under a NonCommercial licence, whereas these parameters are our own work and are released for noncommercial use. Licence: CC BY-NC 4.0, with the additional terms in MODEL-WEIGHTS-TERMS.md. Access is granted for academic research, teaching, verification and reproduction of the published results, method development and open benchmarking. Commercial use requires a separate licence.