CD ComputaBio offers comprehensive Enzyme Active Site Modeling to accelerate the design of potent and selective inhibitors. We combine binding‑site characterization, pocket flexibility analysis, water‑network mapping, and ensemble docking to deliver actionable structural insights for hit‑to‑lead and lead optimization campaigns.
We generate pocket volume maps (SiteMap, DoGSiteScorer), electrostatic potential surfaces, and lipophilic potential contours to highlight favorable regions for non‑polar, polar, and charged substituents.
Using WaterMap and 3D‑RISM, we compute the thermodynamic signatures of active‑site water molecules, identifying high‑energy waters that can be displaced by ligand functional groups to improve affinity.
We generate receptor ensembles from MD simulations or multiple crystal structures and dock ligands against each conformation, capturing backbone and side‑chain flexibility that affects binding.
We align and compare active sites across related enzymes (e.g., kinase families, proteases, cytochrome P450s) to identify selectivity‑determining residues and design inhibitors that exploit these differences.
Using MM‑GBSA/PBSA and per‑residue decomposition, we identify which active‑site residues contribute most to inhibitor binding, guiding mutation strategies and SAR interpretation.
For covalent inhibitors, we perform covalent docking (CovDock) with reaction‑aware scoring to model bond formation geometry and optimize warhead placement relative to catalytic residues.
We run explicit‑solvent MD simulations to sample protein conformational space, then cluster trajectories to generate a representative ensemble for ensemble docking and SAR analysis.
By docking inhibitors into multiple enzyme targets (e.g., kinase paralogs, protease isoforms), we map selectivity determinants and guide design of selective inhibitors.
For lead optimization, we apply FEP+ to compute relative binding free energies between analogues with near‑chemical accuracy, prioritizing synthesis candidates.
We assess available structures (PDB, cryo‑EM, or homology models), prepare the protein with correct protonation, cofactors, and water networks, and define the binding site.
We run SiteMap and WaterMap to characterize the active site volume, hydrophobicity, and water thermodynamics, identifying displaceable waters and key interaction hotspots.
We generate conformational ensembles via explicit‑solvent MD or use multiple crystal structures to capture receptor flexibility for ensemble docking.
We dock inhibitor libraries using consensus docking (Glide, GOLD, Vina), rescore with MM‑GBSA, and validate poses against co‑crystallized ligands or known SAR.
We compute interaction fingerprints, per‑residue energy decomposition, and cross‑target docking to extract selectivity drivers and SAR patterns.
We deliver a comprehensive report with pocket maps, water analysis, docking poses, interaction diagrams, selectivity profiles, and prioritized design suggestions.
| Project challenge | Recommended modeling | Key outputs | Decision support |
|---|---|---|---|
| Design a selective kinase inhibitor | Ensemble docking + cross‑family selectivity mapping | Selectivity pocket maps, differential IFP, hinge‑binding analysis | Guide substituent placement to exploit gatekeeper differences |
| Optimize a lead series with flat SAR | WaterMap + FEP+ + MM‑GBSA decomposition | Displaceable water sites, per‑residue energy, ΔΔG predictions | Prioritize analogues that displace high‑energy waters |
| Rationalize activity cliffs in a congeneric series | Induced‑fit docking + ensemble scoring | Pose overlay, strain energy, water‑bridge frequency | Identify conformational or water‑network shifts |
| Develop covalent inhibitors for a cysteine protease | Covalent docking + warhead geometry optimization | Covalent pose, bond‑formation energy, kinetic accessibility | Select warhead type and attachment vector |
We combine cutting‑edge computational tools with medicinal chemistry expertise to translate structural data into inhibitor design strategies. Our reports are decision‑ready, publication‑quality, and tailored to your project needs.
Active‑site modeling goes beyond docking by characterizing pocket properties, water thermodynamics, and conformational ensembles, providing a deeper understanding of the factors that drive inhibitor binding and selectivity.
We can generate high‑quality homology models using AlphaFold2 or template‑based methods, and validate them with docking enrichment and MD simulations to ensure reliability.
Yes. We use specialized covalent docking protocols (CovDock, DOCKovalent) that account for bond‑formation geometry and reaction chemistry to predict covalent binding modes.
We combine WaterMap, 3D‑RISM, and explicit‑solvent MD to characterize water thermodynamics, distinguishing structural waters from displaceable waters that can be targeted for affinity gains.
A standard project (pocket analysis, ensemble docking, water mapping, report) for 20–50 compounds takes 1–3 weeks. Complex projects with FEP+ or extensive MD may require 3–5 weeks.
Share your target and compound series. Our team will design an active‑site modeling workflow that delivers clear, decision‑ready insights for your inhibitor design project.
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