CD ComputaBio provides Protein Molecular Dynamics Simulation to help researchers investigate conformational ensembles, binding thermodynamics, allosteric communication, and stability of proteins. By combining explicit-solvent MD, enhanced sampling, and rigorous free-energy methods, we deliver actionable insights for drug discovery, protein engineering, and mechanistic biology.
Unbiased MD, enhanced sampling (aMD, metadynamics, RE) to explore conformational landscapes, identify metastable states, and assess protein stability.
Compute binding free energies using MM-GBSA, FEP+, and thermodynamic integration to rank ligands, evaluate selectivity, and guide lead optimization.
Identify allosteric sites, signal propagation pathways, and correlated motions that underpin protein function and regulation.
Specialized protocols for membrane-embedded proteins: lipid bilayer assembly, equilibration, and analysis of protein-lipid contacts and conformational changes.
Assess binding pose stability, ligand residence time, and unbinding pathways using unbiased MD or metadynamics-based approaches.
Evaluate the impact of mutations on protein stability, folding, and function. Predict stabilizing mutations and design variants with improved properties.
| Application Scenario / Project Need | Recommended MD Method | Large / Long Systems | Enhanced Sampling | Typical Output |
|---|---|---|---|---|
| Binding pose validation & stability | Explicit solvent MD (AMBER/CHARMM) | ✔ (up to 500k atoms) | — | RMSD, RMSF, ligand-protein contacts, interaction energy |
| Relative binding affinity (FEP) | FEP+ / TI / MM-GBSA | — | — | ΔΔG ranking, scaffold hopping suggestions |
| Allosteric pathway mapping | Unbiased MD + network analysis | ✔ | aMD / metadynamics | Correlation maps, community networks, allosteric sites |
| Membrane protein dynamics | Membrane-embedded MD (POPC/POPE) | ✔ | — | Lipid interactions, conformational changes, tilt angles |
| Protein stability & folding | Unbiased MD / replica exchange | ✔ | REMD / metadynamics | Free energy landscapes, folding pathways, stability metrics |
| Mutational effect & design | MD + ΔΔG calculations | — | — | Stability prediction, design guidance, variant ranking |
Build simulation system: protein structure preparation (PDB, homology model, AlphaFold), solvation, ions, membrane (if applicable), force field selection.
Relax the system through minimization and equilibration (NVT, NPT) to reach stable temperature and pressure.
Execute production simulations on GPU-accelerated clusters with trajectory saving for downstream analysis.
Comprehensive analysis: RMSD, RMSF, PCA, clustering, hydrogen bonds, SASA, free energy calculations, and network analysis.
Translate MD data into biological insights: conformational changes, binding thermodynamics, allosteric networks, and actionable hypotheses.
MD simulations require careful system preparation, force-field selection, convergence assessment, and expert interpretation. We deliver reliable, biologically meaningful results that guide your experimental decisions.
We routinely perform simulations from nanoseconds to microseconds. With enhanced sampling (aMD, metadynamics), we can effectively reach millisecond-equivalent timescales for conformational transitions.
We use validated membrane models (POPC, POPE, etc.) and specialized protocols for embedding, equilibration, and analysis of lipid-protein interactions and conformational changes.
Yes. We offer FEP+ and thermodynamic integration to predict relative binding affinities, with rigorous protocol design, convergence analysis, and error estimation.
Standard analysis includes RMSD, RMSF, Rg, SASA, hydrogen bonds, PCA, clustering, and MM-GBSA. Custom analysis (Markov state models, pathway analysis, etc.) can be added.
Share your protein target, research question, and desired outcomes. Our team will design a tailored MD workflow and deliver a practical report for your next experimental or design decision.
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