Datasets:

hssling
/

pd-discovery-benchmark-dashboard

symbol stringlengths 4 6	module stringlengths 18 43	role stringlengths 26 62	target_to_intervention_score_100 float64 64 97	tractability_class stringclasses 2 values	model stringlengths 39 77	primary_assay stringlengths 41 68	chembl_target_id stringlengths 9 13 ⌀	pdb_count int64 0 165	alphafold_url stringlengths 40 44	recommended_next_experiment stringclasses 10 values
SNCA	alpha-synuclein aggregation and propagation	central PD pathology target	97	highest-priority intervention target	SNCA triplication/A53T iPSC dopaminergic neurons or alpha-synuclein PFF model	pS129 alpha-synuclein, aggregate load, synaptic/neurite phenotypes	CHEMBL6152	165	https://alphafold.ebi.ac.uk/entry/P37840	Use alpha-synuclein PFF or SNCA-mutant iPSC dopaminergic neurons with pS129 aggregation, synaptic, and viability endpoints.
GLP1R	metabolic and GLP-1 receptor signalling	repurposing target with phase 2 PD signals	94	highest-priority intervention target	dopaminergic neuron stress model with metabolic/inflammatory co-culture	neuronal survival, inflammatory cytokines, mitochondrial respiration	CHEMBL1784	56	https://alphafold.ebi.ac.uk/entry/P43220	Test GLP-1 agonists in metabolic/inflammatory stress co-culture with neuronal survival, cytokines, and mitochondrial respiration endpoints.
LRRK2	LRRK2 kinase and lysosomal stress	genetically anchored kinase target	90	highest-priority intervention target	LRRK2 G2019S or R1441C iPSC-derived dopaminergic neurons	phospho-Rab10/Rab12, lysosomal morphology, neurite survival	CHEMBL1075104	0	https://alphafold.ebi.ac.uk/entry/A0A7P0Z4D9	Test best-supported LRRK2 inhibitors in G2019S iPSC dopaminergic neurons using phospho-Rab10, lysosome, mitochondrial, and neurite endpoints.
GBA1	GBA1 lysosome/autophagy	lysosomal enzyme and PD risk gene	90	highest-priority intervention target	GBA1-mutant iPSC dopaminergic neurons and macrophage/microglia-like cells	glucocerebrosidase activity, lysosomal pH, alpha-synuclein burden	CHEMBL2179	0	https://alphafold.ebi.ac.uk/entry/A0A0G2JLB3	Test GCase modulators in GBA1-mutant iPSC dopaminergic neurons using GCase activity, lysosomal pH, alpha-synuclein, and survival endpoints.
SLC6A3	dopaminergic synapse	dopamine transporter marker and dopaminergic phenotype readout	88	highest-priority intervention target	iPSC dopaminergic neuron maturation/readout assay	DAT expression/function, dopamine uptake, neuron identity QC	CHEMBL238	7	https://alphafold.ebi.ac.uk/entry/Q01959	Run target-specific perturbation in iPSC dopaminergic neuron maturation/readout assay using DAT expression/function, dopamine uptake, neuron identity QC.
TLR2	innate immune signalling	Reactome-highlighted innate immune receptor	85.6	highest-priority intervention target	iPSC-derived microglia and neuron-microglia co-culture	TNF/IL6/IL1B release, NF-kB activation, neuronal toxicity	CHEMBL3301399	7	https://alphafold.ebi.ac.uk/entry/O60603	Validate immune modulation in iPSC-derived microglia/neuron co-culture using cytokines, NF-kB/stress markers, and neuronal toxicity.
IL17A	IL-17 inflammatory signalling	Reactome-highlighted cytokine pathway node	82	highest-priority intervention target	microglia/astrocyte inflammatory co-culture	IL-17 response genes, cytokine release, neuronal stress markers	CHEMBL3390822	36	https://alphafold.ebi.ac.uk/entry/Q16552	Validate immune modulation in iPSC-derived microglia/neuron co-culture using cytokines, NF-kB/stress markers, and neuronal toxicity.
PINK1	mitochondrial quality control	mitophagy kinase and recessive PD gene	78.7	highest-priority intervention target	PINK1 knockout iPSC dopaminergic neurons	mitophagy reporter, mitochondrial membrane potential, ATP/ROS	CHEMBL3337330	3	https://alphafold.ebi.ac.uk/entry/Q9BXM7	Use iPSC dopaminergic neurons with mitochondrial stress and mitophagy/respiration/ROS assays.
NTRK1	NTRK/neurotrophin signalling	Reactome-highlighted trophic signalling node	78	highest-priority intervention target	dopaminergic neuron survival/trophic support model	neurite length, survival, phospho-ERK/AKT	CHEMBL2815	0	https://alphafold.ebi.ac.uk/entry/A0A6Q8PF65	Run target-specific perturbation in dopaminergic neuron survival/trophic support model using neurite length, survival, phospho-ERK/AKT.
MAPK1	MAP kinase activation	Reactome-highlighted signalling hub	78	highest-priority intervention target	stress-response assay in neurons and microglia	phospho-ERK, inflammatory/stress response, toxicity counterscreen	CHEMBL4040	0	https://alphafold.ebi.ac.uk/entry/Q499G7	Run target-specific perturbation in stress-response assay in neurons and microglia using phospho-ERK, inflammatory/stress response, toxicity counterscreen.
NOD2	NOD1/2 inflammatory signalling	Reactome-highlighted innate immune sensor	75	strong validation target	iPSC-derived microglia or monocyte-derived macrophages	NOD ligand response, cytokines, inflammasome-related markers	CHEMBL1293266	0	https://alphafold.ebi.ac.uk/entry/A0A3S6A229	Validate immune modulation in iPSC-derived microglia/neuron co-culture using cytokines, NF-kB/stress markers, and neuronal toxicity.
NDUFS3	mitochondrial oxidative phosphorylation	complex I pathway marker from pilot omics	66.5	strong validation target	iPSC dopaminergic neuron mitochondrial stress model	Seahorse OCR, complex I activity, ATP/ROS	CHEMBL6067008	0	https://alphafold.ebi.ac.uk/entry/E9PS48	Use iPSC dopaminergic neurons with mitochondrial stress and mitophagy/respiration/ROS assays.
LAMP2	lysosome/autophagy	lysosomal/autophagy marker	66.5	strong validation target	iPSC dopaminergic neurons with lysosomal stress	LC3/p62 flux, lysosomal pH, autophagosome clearance	CHEMBL5465542	0	https://alphafold.ebi.ac.uk/entry/A0A9L9PXQ4	Run target-specific perturbation in iPSC dopaminergic neurons with lysosomal stress using LC3/p62 flux, lysosomal pH, autophagosome clearance.
MYD88	innate immune signalling	TLR adaptor in Reactome MyD88/MAL cascade	64.2	strong validation target	iPSC-derived microglia inflammatory challenge	NF-kB reporter, cytokine release, rescue of co-culture toxicity	CHEMBL5919	0	https://alphafold.ebi.ac.uk/entry/A0A0A0MSI9	Validate immune modulation in iPSC-derived microglia/neuron co-culture using cytokines, NF-kB/stress markers, and neuronal toxicity.
PRKN	mitochondrial quality control	E3 ligase and recessive PD gene	64	strong validation target	PRKN knockout iPSC dopaminergic neurons	mitophagy reporter, ubiquitination, mitochondrial stress survival	null	0	https://alphafold.ebi.ac.uk/entry/A0A669KBE3	Use iPSC dopaminergic neurons with mitochondrial stress and mitophagy/respiration/ROS assays.

Parkinson's Disease Discovery Benchmark Dashboard

Reusable benchmark, knowledge graph, manuscript resource, and Streamlit dashboard for Parkinson's disease target-to-intervention discovery.

This repository integrates evidence-synthesis priority scores, target tractability, omics/pathway recurrence, ChEMBL compound activity, RDKit physicochemical heuristics, Human Protein Atlas cell-type context, iPSC/stem-cell validation mappings, and publication-ready figures.

Scientific Scope

This is a research and hypothesis-generation resource. It is not clinical decision support, not a prevention guideline, not a treatment recommendation system, and not evidence that any intervention prevents or cures Parkinson's disease.

Main Assets

data/pd_discovery_target_benchmark.csv
data/compound_selectivity_safety_matrix.csv
data/validated_repurposing_candidates.csv
data/do_not_prioritise_or_comparator_compounds.csv
data/experimental_validation_matrix.csv
data/omics_recurrence/pd_multi_dataset_pathway_recurrence.csv
data/pd_discovery_benchmark_knowledge_graph.graphml
data/benchmark_graph_nodes.csv
data/benchmark_graph_edges.csv
figures/benchmark_target_ranking.png
figures/benchmark_evidence_matrix.png
figures/compound_selectivity_safety_triage.png
figures/benchmark_knowledge_graph.png
dashboard/app.py
reports/resource_manuscript_target_to_intervention_benchmark.md

Run The Dashboard

pip install -r requirements.txt
streamlit run dashboard/app.py

Validate The Repository

python scripts/04_validate_resource.py
python -m py_compile dashboard/app.py

GitHub Actions runs these checks on push and pull request.

Rebuild

The complete rebuild expects the upstream folders to sit beside this repository:

PD_AI_Evidence_to_Discovery_Project
PD_Target_to_Intervention_Discovery_Extension

Then run:

python scripts/01_build_benchmark.py
python scripts/02_finalize_resource_outputs.py
Rscript scripts/03_multi_dataset_omics_recurrence.R

Appropriate Reuse

benchmark target-prioritisation and drug-repurposing algorithms;
inspect candidate target, compound, and validation-model links;
design iPSC-derived dopaminergic-neuron or glial co-culture experiments;
compare knowledge-graph scoring methods;
teach reproducible translational bioinformatics.

Citation

Use the metadata in CITATION.cff. If using the dataset mirrors, cite the corresponding Hugging Face or Kaggle landing page together with the commit or dataset version used.

Public Mirrors

GitHub release: https://github.com/hssling/pd-discovery-benchmark-dashboard/releases/tag/v1.0.0
Hugging Face Datasets: https://huggingface.co/datasets/hssling/pd-discovery-benchmark-dashboard
Kaggle Datasets: https://www.kaggle.com/datasets/jkhospital/pd-discovery-benchmark

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