Flexible, scalable, and ready for ligand screening, protein–ligand modeling, and hit optimization.
At Creative Proteomics, we deliver fast and reliable molecular docking solutions to support your virtual screening, binding mode prediction, and structure-activity analysis. Our multi-engine platform handles proteins, peptides, and complex ligands-even from predicted structures like AlphaFold2.
Molecular docking is a powerful computational technique used to predict the preferred orientation of a ligand when bound to a protein or other biomolecular target. This in silico modeling approach simulates the interactions between small molecules and macromolecular structures (proteins, nucleic acids, etc.), enabling researchers to estimate binding affinities, understand molecular mechanisms, and prioritize drug candidates before investing in wet-lab validation.
Whether you're screening compound libraries, studying protein-ligand recognition, or identifying novel scaffolds, molecular docking offers an efficient, cost-effective entry point. Our service helps clients:
Molecular docking shortens the design-build-test cycle by enabling in silico hypothesis testing with high structural fidelity.
If you're exploring computational tools for molecular interaction studies, molecular docking is most effective when:
Docking may be complemented by molecular dynamics or QSAR modeling when targets are highly flexible or poorly characterized.
Not sure which approach fits best? Our scientific team will assess your project and recommend the ideal computational pipeline.
Multi-Engine Integration — Accuracy Meets Flexibility
We integrate AutoDock Vina, Schrödinger Glide, MOE, and SwissDock, allowing clients to choose between speed, precision, or library size optimization. This ensures accurate binding predictions across diverse targets.
Structure-Free Compatibility — From Sequence to Structure
No solved crystal structure? No problem. We support docking based on AlphaFold2 or homology-modeled structures, including unknown binding pocket prediction and structural refinement workflows.
Broad Ligand Support — Small Molecules, Peptides, Metals
Our platform accommodates small molecules, cyclic peptides, natural products, and metal-coordinated compounds. All ligands are processed with pH-based protonation, conformer generation, and stereochemistry checks.
Flexible Docking Options — Rigid or Induced-Fit Modeling
Docking workflows support both rigid and flexible configurations, with user-defined side-chain flexibility and adaptive conformational sampling—ideal for modeling induced-fit and allosteric binding.
High-Throughput Capability — Screen 10,000+ Compounds
Optimized for large-scale virtual screening, our system docks up to 10,000 ligands per batch with customizable exhaustiveness. Results are ranked and filtered for downstream testing or SAR analysis.
Target Structure Preparation
Supports crystal, cryo-EM, AlphaFold2 models, or FASTA sequences. Includes structure refinement, protonation, and binding site detection via SiteMap, CASTp, or custom input.
Ligand Preparation
Accepts SMILES, MOL2, SDF, or 2D sketches. Performs tautomer/ionization prediction, stereoisomer generation, and conformer optimization at physiological pH.
Docking Simulation
Flexible or rigid docking using AutoDock Vina, Glide, MOE, or custom scoring. Supports batch docking from 1 to 10,000+ ligands with adjustable exhaustiveness.
Scoring & Filtering
Ranks poses by binding energy, shape, and pharmacophore fit. Filters hits by clustering, ADMET, ligand efficiency, and chemical diversity.
Output & Visualization
Provides ranked poses (PDB/MOL2), annotated interactions, and 2D/3D diagrams. Compatible with PyMOL/Chimera; includes summary report.
Dock and rank thousands of compounds against defined targets to accelerate hit identification and chemical library triaging.
Predict binding modes, key residues, and molecular interactions (e.g., H-bonds, π–π stacking) for mechanistic insight and structural validation.
Compare analogs, evaluate substitutions, and prioritize scaffolds based on binding affinity and predicted selectivity.
Dock short peptides, macrocycles, or antibody fragments to protein surfaces to guide design of PPI inhibitors or molecular glues.
Identify non-canonical or hidden pockets for modulating target activity beyond the active site—ideal for kinase and PPI targets.
Simulate how substrates, cofactors, or ions position within catalytic sites to support enzyme engineering and metabolic pathway design.
Model small molecule binding to microbial or viral proteins (e.g., Mpro, DNA gyrase) to support infectious disease therapeutic screening.
| Required Item | Accepted Formats | Description |
| Protein Target | PDB file, FASTA, UniProt ID | Provide a 3D structure or sequence; if unavailable, we offer AlphaFold2/homology modeling. |
| Ligand Structure(s) | MOL2, SDF, SMILES, PubChem CID | Single ligand or compound library; we support batch docking with 2D/3D input. |
| Binding Site Info | Residue list, grid box, or N/A | Optional. Specify known binding pocket or request blind docking/site prediction. |
| Docking Preferences | Text instructions or template | Optional. Indicate preferred docking engine, exhaustiveness, flexibility mode, etc. |
| Required Item | Accepted Formats | Description |
| Method | Requires Target Structure | Handles Flexibility | Computational Cost | Ideal Use Case |
| Molecular Docking | ⭐⭐ | Structure-based screening; binding mode prediction | ||
| Molecular Dynamics (MD) | ⭐⭐⭐⭐⭐ | Refining docking results; studying conformational stability | ||
| Pharmacophore Modeling | ⭐⭐ | Hit discovery when structural data is limited | ||
| Ligand-Based Virtual Screening (LBVS) | ⭐⭐ | Similarity-based filtering with known active compounds | ||
| QSAR / 3D-QSAR | ⭐⭐⭐ | Predicting compound activity with prior experimental data | ||
| Free Energy Calculations (e.g., MM/PBSA) | ⭐⭐⭐⭐ | Quantitative ranking of top hits after docking | ||
| AlphaFold2 / Homology Modeling | ⭐⭐⭐ | Generating docking-ready structures from sequences |
Title: Molecular docking analysis of protein Filamin A with thioazo compounds
Journal: Bioinformation (2023) DOI: 10.6026/97320630019099
Background
Docking Workflow
Structure Preparation: Protein structure was downloaded from PDB and prepared (water removal, addition of hydrogens, charge assignment via AutoDock Tools).
Ligand Modeling: Thioazo compounds were geometry-optimized and converted to 3D PDB files before docking.
Docking Execution: AutoDock Vina was used with a customized grid; nine poses generated per compound, ranked by predicted binding energy.
Key Findings
Molecular docking analysis of compounds (1-3) against Protein filamin A of Homo sapiens
Molecular docking analysis of compounds (4-6) against Protein filamin A of Homo sapiens
Can I use docking if I don't have a crystal structure of my protein?
Yes. If you only have a protein sequence or UniProt ID, we can generate a reliable 3D structure using AlphaFold2 or homology modeling before initiating docking.
I have dozens of compounds. Do I need to pre-filter them myself?
No. You can submit the entire compound list in SDF, MOL2, or SMILES format. We offer in silico filtering based on size, drug-likeness, or chemical diversity before docking, if needed.
How many docking poses will I receive per ligand?
By default, we provide the top 5–10 ranked binding poses per compound. This can be adjusted based on your analysis needs or screening goals.
What if I want to follow up docking with molecular dynamics or QSAR analysis?
We can support that. Our team offers seamless integration of docking output into MD simulations, MM/PBSA analysis, or QSAR model construction.
Is docking reliable for predicting actual binding in vitro?
Docking is best used as a predictive or filtering tool. While it cannot replace experimental validation, it significantly improves hit quality and prioritization when integrated with downstream assays.
What if my ligand contains unusual atoms or metal centers?
We support coordination complexes and metal-containing ligands (e.g., Zn²⁺, Mg²⁺) and will apply appropriate partial charges and parameters. Please highlight these compounds during submission.
Can I specify the binding site if I already know it?
Yes. You can define the binding pocket using residue numbers or coordinate box boundaries. Otherwise, we will perform binding site prediction or blind docking as appropriate.
What if my compound is a peptide or macrocycle?
We support docking of peptides, macrocyclic ligands, and semi-flexible molecules. Specific docking settings (e.g., ring sampling) will be adjusted to suit your compound class.
Is batch docking of >10,000 compounds possible?
Yes. We offer high-throughput virtual screening services and can handle large compound libraries with appropriate computational scaling. Please inquire for volume-based pricing.
What docking software do you use, and can I choose?
We support multiple docking engines (e.g., AutoDock Vina, Schrödinger Glide, MOE) and can tailor the engine based on your preferences, compound class, or previous project compatibility.
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