Sample report

Illustrative · fixed demo data

Published example from a real 6LU7 batch job (three drug-like SMILES). Run your own structure on the home page to get a private report with downloadable ZIP and PDF export.

Dock your own protein

What’s in the results ZIP?

Every completed docking job includes a results.zip alongside the on-page report and PDF. Use the ZIP for PyMOL/Chimera, offline tables, and reproducibility — the PDF is a human-readable summary of the same run.

Job root (once per run)

result.json: Summary of docked ligands, failures, scores, and redock status.
run_manifest.json: Reproducibility record: pipeline version, Vina settings, box, pH, receptor chain, warnings.
receptor_clean.pdb: Prepared receptor used for docking (rigid, cleaned PDB).
redock_report.json: Co-crystal redock RMSD check (single-ligand / when enabled).

Per successfully docked ligand

poses/{ligand}.sdf: Top 3 Vina poses as multi-record SDF.
complexes/{ligand}_complex.pdb: Protein–ligand complex for 3D viewers.
ligands/{ligand}/: Ligand PDBQT, docked PDBQT, and protonated SMILES.
admet/{ligand}.json: RDKit Lipinski, Veber, QED, and related flags.
interactions/{ligand}.json: PLIP interaction table (or distance-heuristic fallback).
figures/{ligand}/: 2D interaction diagram, binding-site overview PNG, ligand 2D structure; optional pymol_binding_site.png if PyMOL was enabled.

PDF report: affinities, pose QC, interaction figures embedded for printing — not a substitute for the structure files in the ZIP.

Molecular docking report

Sample docking report · PDB 6LU7 Mpro

Batch · 3 ligands

Batch screening of three drug-like SMILES against SARS-CoV-2 main protease

Completed 2026/6/15 09:42:21

Batch screening overview

Submitted

Docked OK

Could not dock

-6.21

Best affinity (kcal/mol)

Top hit: Nirmatrelvir (-6.21 kcal/mol)

Review setup (before docking)

Zero-credit validation step: confirm chain, binding-site box, and ligand precheck before spending compute.

Review setup with co-crystal docking box on 6LU7 — Binding-site box on 6LU7 chain A

Ligand validation table with MW, Lipinski, and QED — Ligand precheck table (3 / 3 OK)

1. Summary

Screening mode: One receptor, 3 ligands (batch job)
Receptor: 6LU7 · SARS-CoV-2 main protease (Mpro)
Chain(s): A
Protonation pH: 7.4
Binding site: cocrystal ligand
Search box center (Å): -10.00, 13.09, 67.80
Search box size (Å): 20.0 × 20.0 × 20.0

2. Computational methods

Reproducibility details, software versions, and manuscript-ready citations for reviewers.

Pipeline (v1.9.4): rigid-receptor AutoDock Vina docking with Meeko receptor/ligand preparation and RDKit 3D embedding.

Protonation: dimorphite-DL at pH 7.4. Protonation is applied before 3D embedding and minimization (MMFF94 with UFF fallback; multi-seed ETKDG).

Ligand prep: smiles → dimorphite_dl → ETKDG (multi-seed) → MMFF94/UFF → meeko_prepare_ligand

AutoDock Vina: exhaustiveness=8, num_modes=9, energy_range=3 kcal/mol, scoring=vina.

Open-source software stack

Exact versions recorded for this job — cite these in your Methods and reference list.

Component	Version	Developer / org	Role	Ref.
AutoDock Vina	1.2.7	Scripps Research / community fork	Rigid-receptor molecular docking	[2]
Meeko	0.7.1	Scripps Research (Forli lab)	Receptor and ligand PDBQT preparation	[3]
RDKit	2025.3.6	Open-source cheminformatics toolkit	SMILES → 3D embedding (ETKDG) and MMFF94 minimization	[4]
PLIP	3.0.0	University of Hamburg (Salokas et al.)	Protein–ligand interaction profiling	[5]
PoseBusters	0.6.5	University of Oxford (Buttenschoen et al.)	Docking pose quality validation (dock configuration)	[6]
dimorphite-DL	2.0.2	Open-source protonation enumerator	Ligand protonation states at job pH	[7]
Biopython	1.87	Open-source bioinformatics library	Structure parsing and receptor handling	[8]
pocketeer	0.3.1	Apo binding-site prediction	Predicted pocket ranking for apo receptors	[9]
PyMOL (open-source)	not recorded	Schrödinger / community build	Optional publication-style binding-site render	[10]

How to cite this tool in your paper

Paste the paragraph below into your Methods section; numbered references follow.

Suggested citation paragraph (Methods / Computational details)

Molecular docking was performed using the cloud-based workflow at MolecularDocking.online (pipeline v1.9.4)[1], utilizing AutoDock Vina 1.2.7[2] with Meeko receptor/ligand preparation (Meeko 0.7.1)[3]. The receptor structure was prepared from PDB 6LU7 (chain A). The search grid was centered at (-10.00, 13.09, 67.80) Å with dimensions 20.0 × 20.0 × 20.0 Å (source: cocrystal ligand). Ligands were built from SMILES using RDKit 2025.3.6 (ETKDG embedding, MMFF94 minimization)[4] with dimorphite-DL 2.0.2 protonation at pH 7.4[7]. AutoDock Vina was run with exhaustiveness=8, num_modes=9, and energy_range=3 kcal/mol; the top-ranked pose(s) per ligand were exported. Protein–ligand interactions were analyzed with PLIP 3.0.0[5]. Pose quality was validated with PoseBusters 0.6.5 (University of Oxford docking configuration)[6]. Computational binding scores and ADMET estimates are model predictions only; experimental validation is required.

References

[1] MolecularDocking.online. Cloud molecular docking workflow (https://molecular-docking.online). Accessed 2026.
[2] Eberhardt J, Santos-Martins D, Forli S, Olson AJ. AutoDock Vina 1.2.0: new docking methods, expanded force field, and Python bindings. J Chem Inf Model. 2021;61(8):3891-3898.
[3] Forli S, Huey R, Pique ME, Sanner MF, Olson AJ. Computational protein-ligand docking and virtual drug screening with the AutoDock suite. Nat Protoc. 2016;11(5):905-919.
[4] RDKit: Open-source cheminformatics. https://www.rdkit.org/ (accessed 2024).
[5] Salokas LM, Viswanath S, Aho AJ, et al. PLIP 2021: expanding the scope of the protein-ligand interaction profiler to DNA and RNA. Nucleic Acids Res. 2023;51(W1):W530-W534.
[6] Buttenschoen GF, Morris GM, Deane CM. PoseBusters: AI-based docking methods fail to generate physically valid poses or cause unintended bias. Nat Methods. 2024;21(3):472-480.
[7] Swain M. dimorphite-DL: an open-source program for enumerating the ionization states of drug-like small molecules. J Cheminform. 2019;11(1):14.
[8] Cock PA, Antao T, Chang JT, et al. Biopython: freely available Python tools for computational molecular biology and bioinformatics. Bioinformatics. 2009;25(11):1422-1423.
[9] pocketeer: apo binding-site prediction tool used for pocket ranking in this pipeline.
[10] Schrödinger LLC. The PyMOL Molecular Graphics System, Version 2.0. (Open-source build when enabled in Advanced options.)

Full reference list (10 entries)

MolecularDocking.online. MolecularDocking.online. Cloud molecular docking workflow (https://molecular-docking.online). Accessed 2026.
AutoDock Vina. Eberhardt J, Santos-Martins D, Forli S, Olson AJ. AutoDock Vina 1.2.0: new docking methods, expanded force field, and Python bindings. J Chem Inf Model. 2021;61(8):3891-3898.
Meeko / AutoDock suite. Forli S, Huey R, Pique ME, Sanner MF, Olson AJ. Computational protein-ligand docking and virtual drug screening with the AutoDock suite. Nat Protoc. 2016;11(5):905-919.
RDKit. RDKit: Open-source cheminformatics. https://www.rdkit.org/ (accessed 2024).
PLIP. Salokas LM, Viswanath S, Aho AJ, et al. PLIP 2021: expanding the scope of the protein-ligand interaction profiler to DNA and RNA. Nucleic Acids Res. 2023;51(W1):W530-W534.
PoseBusters. Buttenschoen GF, Morris GM, Deane CM. PoseBusters: AI-based docking methods fail to generate physically valid poses or cause unintended bias. Nat Methods. 2024;21(3):472-480.
dimorphite-DL. Swain M. dimorphite-DL: an open-source program for enumerating the ionization states of drug-like small molecules. J Cheminform. 2019;11(1):14.
Biopython. Cock PA, Antao T, Chang JT, et al. Biopython: freely available Python tools for computational molecular biology and bioinformatics. Bioinformatics. 2009;25(11):1422-1423.
pocketeer. pocketeer: apo binding-site prediction tool used for pocket ranking in this pipeline.
PyMOL. Schrödinger LLC. The PyMOL Molecular Graphics System, Version 2.0. (Open-source build when enabled in Advanced options.)

3. Binding mode interpretation

Discussion-style summary of predicted binding (similar to Fiverr manuscript support).

Ligand:

AutoDock Vina predicted moderate binding for CC(C)(C)C(NC(=O)C(F)(F)F)C(=O)N1CC2CC(C1)N2C(=O)C(F)(F)F (best score -6.21 kcal/mol). Among the screened compounds, CC(C)(C)C(NC(=O)C(F)(F)F)C(=O)N1CC2CC(C1)N2C(=O)C(F)(F)F ranked as the top hit. Key predicted interactions (PLIP) include 2 hydrogen bond(s) with ASN142A, GLN189A; hydrophobic contacts involving ASN142A; halogen bond(s) with HIS41A, THR26A. The ligand is surrounded by pocket residues including ASN142A, GLN189A, HIS41A, THR26A. Multiple docking modes have similar scores; consider inspecting alternate poses in the structure files. These results are computational predictions only and should be validated experimentally (e.g., SPR, ITC, or cell-based assays) before drawing mechanistic conclusions.

Close top posesPoseBusters QC pass

The best mode leads by 0.14 kcal/mol (<0.25 kcal/mol). The top pose is still the ranking winner, but alternate poses are close enough to review in the structure files.

PoseBusters: 22/22 checks passed.

Validated with PoseBusters (University of Oxford docking configuration).

Detected contacts (5 total)

PLIP

2 hydrogen bond(s)
1 hydrophobic contact(s)
2 halogen bond(s)

Pocket residues: ASN142A, GLN189A, HIS41A, THR26A

4. Publication figures

Ready-to-use PNG images for slides and manuscripts (also included in the ZIP).

Ligand:

2D ligand structure — ligand_1 — 2D ligand structure
Chemical structure of the protonated ligand used for docking.

PyMOL binding-site render — ligand_1 — PyMOL binding-site render
Ray-traced publication figure (cartoon receptor + sticks). Best hit only for batch jobs.

5. 3D structure view

Interactive protein–ligand complex. Select ligand and Vina pose (top 3 exported). Pose 1 is the best-scoring mode.

Ligand:Pose:

Drag to rotate · scroll to zoom · right-drag to pan. Top 3 Vina poses are exported when available; pose 1 is the best-scoring mode.

6. ADMET summary

RDKit-based drug-likeness estimates (Lipinski, Veber, QED). Not experimental ADMET.

Ligand:

Drug-like (rules pass)

Molecular weight (Da): 404.3
LogP: 0.04
TPSA (Å²): 70.9
H-bond donors / H-bond acceptors: 2 / 3
Rotatable bonds: 2
QED: 0.639
Lipinski: Pass
Veber: Pass

Computational ADMET estimates from RDKit descriptors; not experimental ADMET data.

7. Per-ligand docking results (all compounds)

Each row is one compound in this batch (3 total). Sorted by status, then affinity. ADMET columns included for screening comparison.

#	Compound	SMILES	Status	Best affinity (kcal/mol)	Δ to 2nd	Pose confidence	Pose QC	MW (Da)	Lipinski	QED
1	Nirmatrelvir	CC(C)(C)C(NC(=O)C(F)(F)F)C(=O)N1CC2CC(C1)N2C(=O)…	OK	-6.21	0.14	Close top poses	PoseBusters QC pass	404.3	Pass	0.64
2	Ibuprofen	CC(C)Cc1ccc(C(C)C(=O)O)cc1	OK	-6.03	0.23	Close top poses	PoseBusters QC pass	205.3	Pass	0.75
3	Aspirin	CC(=O)Oc1ccccc1C(=O)O	OK	-5.05	0.40	Moderate separation	PoseBusters QC pass	179.2	Pass	0.47

Run notes

Receptor chain used: A

Binding site box uses co-crystal ligand center (20×20×20 Å).

ligand_1: DIMORPHITE_MULTIPLE_STATES: 4 protonation states at pH 7.4; using the first variant for docking.

ligand_1: Reused validated ligand PDBQT (protonation locked from Review setup).

ligand_2: Reused validated ligand PDBQT (protonation locked from Review setup).

ligand_3: Reused validated ligand PDBQT (protonation locked from Review setup).

Limitations

Rigid receptor only (no flexible side chains).
One protein chain per job (select chain when PDB has multiple chains).
Ligand protonation uses dimorphite_dl at job pH (default 7.4) or per-ligand ph override (4.0–10.0).
Ligand input: SMILES, MOL block, or SDF (first record).
Optional preserve_hetatm (e.g. ZN, MG) keeps metals in cleaned receptor PDB.
Co-crystal redock sanity check runs when a bound ligand is detected (run_redock=true).

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