Simulate molecular dynamics Workflow Blueprint

Obtain or build the molecular structure (e.g., from PDB or SMILES) and select an appropriate force field (e.g., AMBER, CHARMM, OPLS). Assign atom types, charges, and bond parameters, then solvate the system in a periodic box with explicit water and ions to neutralize charge.

Why Exscientia: Exscientia provides de novo molecular design and lead optimization, which aligns with preparing molecular systems and force field parameters in computational chemistry workflows.

Run energy minimization (steepest descent or conjugate gradient) to remove bad contacts. Then perform equilibration in two phases: NVT (constant volume, temperature) to heat the system, followed by NPT (constant pressure, temperature) to adjust density and pressure.

Why Hugging Face Spaces: Hugging Face Spaces can deploy ML models and run AI pipelines, which can be adapted to orchestrate energy minimization and equilibration steps if integrated with MD engines.

Remove position restraints and run the main simulation for the desired timescale (e.g., 10–1000 ns) using an integrator like leap-frog or Verlet. Set appropriate time step (1–2 fs), apply periodic boundary conditions, and use a thermostat (e.g., Nosé-Hoover) and barostat (e.g., Parrinello-Rahman) for constant T and P.

Why Mitratech TAP Workflow Automation: Hugging Face Spaces can run AI pipelines with agents and multi-step workflows, potentially managing the execution of production MD simulations if connected to GPU-accelerated engines.

Load the trajectory and compute key metrics: root-mean-square deviation (RMSD), radius of gyration (Rg), hydrogen bond occupancy, and secondary structure (for proteins). Also calculate dynamic properties like mean-square displacement (MSD) and diffusion coefficients.

Why Glean AI: Glean AI offers enterprise-wide search, knowledge retrieval, and automated data analysis, which can assist in analyzing trajectory data for structural and dynamic properties.

Render representative snapshots and movies of the trajectory using visualization software. Overlay initial and final structures to check for large conformational changes. Validate against experimental data (e.g., NMR, X-ray) if available.

Why Dotmatics Scientific Intelligence Platform: Dotmatics Scientific Intelligence Platform provides data management and AI-driven prediction, which can support visualization and validation of simulation results in a scientific context.

If the simulation involves ligand binding or conformational change, run enhanced sampling methods (e.g., umbrella sampling, metadynamics, or MM-PBSA) to compute free energy differences. Post-process trajectories to extract binding free energies or potential of mean force (PMF).

Why Aqemia: Aqemia specializes in binding affinity prediction and lead optimization, directly matching the need for free energy or binding affinity extraction.