/ Product · FoldRx Pipeline

From sequence to drug candidate.

FoldRx is an automated 8-stage drug discovery pipeline. Paste your protein sequence and receive ranked small-molecule candidates — with ADMET profiles and selectivity scores — directly in your browser. No HPC cluster, no pipeline configuration.

Powered by ESMFold · Fpocket · AutoDock Vina · RDKit · pkCSM

Pipeline stages

1

Sequence input

Paste a raw amino acid sequence or load it from your open sequence file. The pipeline accepts FASTA, UniProt IDs, or PDB identifiers.

2

Protein folding

Structures are predicted using ESMFold on GPU, delivering a pLDDT-scored 3D model in seconds. High-confidence predictions (pLDDT > 0.85) proceed automatically.

3

Pocket detection

Fpocket identifies druggable binding cavities on the folded structure, ranked by druggability score and volume.

4

Ligand docking

AutoDock Vina docks a library of small molecules into each detected pocket. Results include binding affinity (kcal/mol) and pose visualisation.

5

ADMET screening

All compounds are filtered against Lipinski Ro5, PAINS alerts, and simulated ADMET properties (absorption, distribution, metabolism, excretion, toxicity).

6

FEP scoring

Free energy perturbation scoring further discriminates top candidates, providing relative binding free energy estimates to prioritise leads.

7

Selectivity profiling

Off-target docking against a panel of common anti-targets helps flag compounds with poor selectivity before wet-lab testing.

8

Candidate ranking

A weighted composite score combining docking, ADMET, FEP, and selectivity ranks all candidates. Export the shortlist as CSV for your medicinal chemistry team.

Structure confidence

pLDDT 0.88

ESMFold on GPU · ~2s

ADMET pass rate

10 / 15

Lipinski Ro5 + PAINS filter

Top docking score

−8.0 kcal/mol

AutoDock Vina ranking

ADMET and selectivity scores are simulated. Real pkCSM and PocketMiner integration is planned. All results are for research purposes only and do not constitute medical advice.

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Free to use. No HPC or cloud credits needed.

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