Predict binding modes, rank compound libraries, and prioritize hits using state-of-the-art docking algorithms, flexible receptor handling, and consensus scoring. Accelerate your drug discovery pipeline with our expert docking solutions.
Screen large compound libraries to identify promising hits that fit your target's binding site with favorable interactions.
Rank analogs by predicted binding affinity and interaction profiles to guide synthesis and testing efforts.
Generate reliable binding poses to understand key interactions and guide rational design decisions.
| Application Scenario | Recommended Method | Receptor Flexibility | Scoring | Typical Output |
|---|---|---|---|---|
| High-throughput docking (Vina, Glide HTVS) | Rigid / soft | Empirical / knowledge-based | Ranked hit list, poses |
| Standard precision (SP) + MM-GBSA | Side-chain flexibility | Consensus (multiple scoring) | Prioritized analogs, interaction maps |
| Extra precision (XP) / GOLD | Induced-fit / flexible | ChemScore, GoldScore, PLP | Detailed binding pose, H-bond, hydrophobic contacts |
| Covalent docking (CovDock, GOLD) | Flexible | Custom covalent scoring | Covalent bond formation, binding mode |
Choose the right approach: Based on library size, target knowledge, computational budget, and decision stage.
Process protein structure: add hydrogens, assign protonation states, define binding site, optimize water molecules.
Generate 3D conformers, assign ionization states, tautomers, and prepare for docking or virtual screening.
Run docking simulations using selected algorithms, scoring functions, and optional consensus scoring for robust ranking.
Analyze binding modes, interactions, and apply rescoring (MM-GBSA, MM-PBSA) for improved ranking.
Combine docking scores, interaction fingerprints, and structural insights to prioritize compounds for experimental testing.
Deliver a comprehensive report with ranked compounds, binding poses, interaction diagrams, and actionable recommendations.
| Library Category | Available Collections & Specifications |
|---|---|
| Bioactive Compound Libraries |
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| Natural Product Libraries |
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| Drug-Like Compound Libraries |
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| Fragment Libraries |
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Research Summary: This study demonstrates how molecular docking is integrated into a rational drug design pipeline targeting Interleukin-1 Receptor-Associated Kinase 4 (IRAK4), a critical target for cancer and autoimmune diseases. The researchers initially utilized molecular docking and molecular dynamics (MD) simulations to analyze the binding modes of known active compounds within the IRAK4 binding pocket. By employing MM-PBSA calculations, they identified key residues essential for stable binding, providing a structural foundation for subsequent optimization.
Based on these structural insights, a 3D-QSAR model was developed to correlate molecular features with biological activity. This model served as a predictive guide for designing novel IRAK4 inhibitors with enhanced theoretical potency. This case exemplifies the "analysis-modeling-design" closed-loop approach, where docking serves as a core tool to drive the discovery of small-molecule inhibitors through rigorous computational validation.
Research Summary: This research expands the application of protein-ligand docking into the field of nanomaterials by exploring fullerenes as potential inhibitors of the SARS-CoV-2 Main Protease (Mpro). Through molecular docking, the authors predicted that C60 and C70 fullerenes could fit precisely into the active site of the protease. These findings were further validated using molecular dynamics simulations and MM-GBSA binding free energy calculations to ensure the stability of the carbon-based structures within the protein environment.
The computational results revealed that these carbon nanomaterials bind to Mpro through exceptional shape complementarity and strong Van der Waals interactions. Remarkably, their binding affinity outperformed Masitinib, a known small-molecule inhibitor, and remained stable regardless of the protonation states of catalytic residues. This work provides an innovative computational pathway for exploring non-traditional molecules, such as nanomaterials, as potent antiviral agents.
References:
Goal: identify novel scaffolds.
Workflow: 100k compounds docked β consensus scoring β 50 hits selected for testing.
Goal: understand SAR.
Workflow: induced-fit docking β MM-GBSA rescoring β interaction analysis β synthesized 20 analogs.
Goal: design covalent inhibitors.
Workflow: covalent docking β reversible screening β covalent warhead optimization.
Rigid docking treats the protein as fixed, while flexible docking allows side-chain or backbone movement to accommodate ligand binding. Flexible docking is more computationally expensive but yields more realistic poses, especially for induced-fit cases.
We use high-throughput docking protocols with parallelization and tiered screening (HTVS β SP β XP) to efficiently process millions of compounds without sacrificing accuracy for top hits.
Yes. We offer covalent docking using specialized algorithms (CovDock, GOLD) that account for bond formation and can prioritize covalent binders from screening libraries.
We employ a variety of scoring functions including empirical (Glide, Vina), knowledge-based (GOLD, PLP), and physics-based (MM-GBSA, MM-PBSA) for consensus ranking and improved hit selection.
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