Small Molecule Approach to RNA Targeting Binder Discovery (SMARTBind) Using Deep Learning Without Structural Input
Creators
- 1. Department of Medicinal Chemistry, Center for Natural Products, Drug Discovery and Development, University of Florida, Gainesville, FL 32610, USA
- 2. Department of Chemistry, The Herbert Wertheim UF Scripps Institute for Biomedical Innovation and Technology, 130 Scripps Way, Jupiter, FL 33458, USA
- 3. Department of Chemistry, The Scripps Research Institute, 130 Scripps Way, Jupiter, FL 33458, USA
- 4. Department of Computer & Information Science & Engineering, University of Florida, Gainesville, FL 32611, USA
Description
This dataset supports SMARTBind (Small Molecule Approaches to RNA Targeting Binder Discovery), a structure-agnostic ligand discovery framework that combines an RNA large language model with contrastive learning and a ligand-specific decoy enhancement strategy.
Overview
The dataset contains model checkpoint and training data for SMARTBind including RNAmigos1 10-fold random-split, Hariboss 10-fold random-split, and Hariboss 5-fold sequence-based-split. All data is organized under the archive file SMARTBind_dataset.zip.
Contents
SMARTBind_weights.zip: Saved checkpoint of 10-fold SMARTBind model.
hariboss_merged_5fd.pkl: SMARTBind training data from the HARIBOSS database under 5-fold sequence-based-split cross-validation.
hariboss_merged_10fd.pkl: SMARTBind training data from the HARIBOSS database under 10-fold random-split cross-validation.
rnamigos_10fd.pkl: SMARTBind training data from the RNAmigos1 under 10-fold random-split cross-validation.
Files
SMARTBind_dataset.zip
Files
(2.6 GB)
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md5:286cc9d2a596d78c94eab03b6856df04
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2.6 GB | Preview Download |