All-Atom Protein MD Simulation

From Static Crystal to Dynamic Ensemble. All-Atom. Microsecond-Scale. Drug-Design Ready.
Explicit-Solvent MD Enhanced Sampling Ensemble Docking

Microsecond-scale trajectories that reveal cryptic pockets, allosteric pathways, and druggable conformations invisible in crystal structures.

Why All-Atom Protein MD Simulation Is the Critical Foundation

Crystal structures deliver a single frozen snapshot; biology operates as an ensemble. Seed-stage biotechs designing against static models miss cryptic pockets that open only during dynamics. Pharma teams need conformational landscapes to rationalize SAR outliers and guide fragment-to-lead expansion. We run explicit-solvent, all-atom simulations to generate ensemble docking inputs, FEP-ready conformers, and allosteric maps.

What Sets the Platform Apart

Microsecond Scale

GROMACS/AMBER HPC delivers 1–10 μs production runs for standard targets, capturing slow domain motions and loop rearrangements.

Cryptic Pocket Discovery

Trajectory analysis identifies transient pockets and allosteric sites absent in crystal structures, scored by druggability classifiers.

Direct Docking Integration

Representative conformers feed directly into ensemble docking and virtual screening, improving hit rates vs. single-structure docking.

Technology Suite

Contents

All-Atom Protein MD Simulation

Key Features:

MD trajectory ensemble of a protein target with validated conformational snapshots for docking.
  • Explicit Solvent & Periodic Boundary — TIP3P/TIP4P-Ew water models with neutralizing ions and physiological salt concentration in fully periodic boxes.
  • Optimized Force Fields — CHARMM36m, AMBER ff19SB, and OPLS-AA/L parameters validated against NMR J-coupling and B-factor distributions.
  • Microsecond Production — HPC-optimized GROMACS/AMBER runs on NVIDIA A100/H100 clusters, reaching 1–10 μs for 50k–500k atom systems.
  • Quality Assurance — RMSD, Rg, RMSF, secondary structure, and energy drift monitoring with automated checkpointing.

Ideal For: Kinase activation loop dynamics; protease flap motion; antibody CDR sampling; PPI interface breathing.

What We Offer:
Production-grade trajectories with validated force-field choices and statistical quality reports. Seed-stage biotechs receive ensemble PDBs ready for docking without managing HPC queues. Pharma teams get raw trajectories and analysis scripts for internal integration.

Conformational Sampling & Pocket Dynamics

Key Features:

Conformational landscape revealing cryptic pockets and allosteric pathways on a protein surface.
  • Enhanced Sampling — Accelerated MD (aMD), Gaussian accelerated MD (GaMD), and metadynamics to overcome high energy barriers and sample rare events.
  • Cryptic Pocket Detection — Pocket volume tracking (Fpocket/POVME) across trajectories to identify transient druggable volumes.
  • Markov State Models (MSM) — Automated conformational clustering and kinetic network reconstruction to quantify state populations and transition rates.
  • Allosteric Pathway Mapping — Dynamic cross-correlation and residue interaction network analysis to reveal allosteric communication wires.

Ideal For: Undruggable targets with shallow active sites; allosteric inhibitor programs; protein-ligand residence time optimization.

What We Offer:
A conformational landscape report with pocket opening frequencies, allosteric hotspot maps, and representative cluster centers. For lead optimization, we flag which substitutions stabilize desired conformations.

Trajectory-Driven Drug Design Integration

Key Features:

MD-driven drug design workflow linking trajectory snapshots to ensemble docking and free energy calculations.
  • Ensemble Preparation for Docking — 50–200 representative conformers extracted from clusters or PCA projections for ensemble docking.
  • FEP/MM-PBSA Pipeline Handoff — Trajectory snapshots formatted as input for binding free energy calculations with consistent force fields.
  • Experimental Data Correlation — Back-calculation of NMR chemical shifts, HDX-MS protection factors, and SAXS profiles for model validation.
  • Custom Restraint Generation — Distance and torsion restraints from MD ensembles to guide protein structure refinement.

Ideal For: Structure-based campaigns requiring conformational flexibility; virtual screening against flexible targets; integrative structural biology projects combining computation and crystallography.

What We Offer:
A downstream-ready data package: ensemble PDBs, docking grids, FEP input files, and experimental correlation reports. Zero-formatting handoffs to your internal teams.

Platform Instrumentation

Core Instruments

Instrument Capability
NVIDIA DGX H100 Microsecond-scale all-atom MD with 500k+ atom systems
GROMACS/AMBER HPC Cluster Parallel replica sampling and ensemble trajectory generation
NVIDIA RTX A6000 Cluster Real-time trajectory visualization and interactive analysis
Bruker AVANCE NEO 800 MHz NMR chemical shift validation of simulated conformations
PerkinElmer EnVision Nexus Biochemical assay readout for MD-predicted activity correlation
Waters ACQUITY UPLC H-Class Purity profiling of analogs selected from ensemble docking

Standardized Workflow

Project Workflow

A milestone-driven execution system from structure to dynamic ensemble.

01 Target Review Week 1
02 System Setup Week 1–2
03 Production MD Week 2–4
04 Analysis & Ranking Week 4
05 Downstream Handoff Week 4–6

01 Target Review

  • Structure assessment and force-field selection
  • Simulation scope (apo, holo, or complex)
  • Deliverable: Simulation plan + force-field rationale

02 System Setup

  • Protein preparation, protonation, and ligand parameterization
  • Solvation box and ionization
  • Deliverable: Equilibrated system + quality metrics

03 Production MD

  • Equilibration and production run (1–10 μs)
  • Enhanced sampling (if required)
  • Deliverable: Raw trajectory + sampling diagnostics

04 Analysis & Ranking

  • Trajectory quality check and clustering
  • Pocket dynamics and cryptic site mapping
  • Deliverable: Conformational report + representative PDBs

05 Downstream Handoff

Sample Requirements

  • Protein Structure: PDB/AF model or experimental structure
  • Ligands/Cofactors: SDF/MOL2 with specified protonation states (if any)
  • Simulation Scope: Apo dynamics, holo stability, or protein-protein complex interface sampling
  • Experimental Data: Prior NMR/HDX-MS/SAXS for validation (optional)

Standard Deliverables

  • Production trajectory (raw + processed)
  • Representative conformational ensemble (50–200 PDBs)
  • Pocket dynamics and cryptic site analysis report
  • RMSF, B-factor, and secondary structure evolution plots
  • Ensemble docking and FEP-ready input files
  • Final technical report with structural recommendations

Frequently Asked Questions

Case Study

Case Study: All-Atom MD Mapping of hPPA2 Dynamics and Pathogenic Mutations

Goal: Benchmark all-atom MD for resolving the conformational ensemble of human hPPA2 wild-type and four disease mutants, quantifying how pathogenic substitutions perturb global dynamics and catalytic function.

Key Data:

  • From static to dynamic ensemble: Multi-microsecond all-atom MD captured two major conformational clusters (I and II) and time-dependent drift across phase space, transitioning a rigid homology model into a functionally relevant ensemble.
  • Conserved allosteric motion: Coarse-grained NMA revealed a shared low-frequency rocking mode of dimeric subunits across eukaryotic PPases, implicating inter-subunit communication in allosteric regulation.
  • Mutation-induced dysfunction: Pathogenic variants altered active-site loop flexibility and metal coordination; Gln294Pro caused M1 ion displacement and loss of inter-subunit contact fidelity, directly linking dynamic disruption to catalytic impairment.

Why it matters: This independent study provides third-party validation that all-atom MD resolves functionally critical motions and pathogenic allostery beyond crystallographic snapshots. The demonstrated capacity to quantify mutation-induced dynamic perturbations and expose transient conformational substates offers a rigorous benchmark for enzyme mechanism studies—supporting the methodological depth of our all-atom protein simulation capabilities.

PCA projection of WT hPPA2 MD trajectory

Figure 1. PCA projection (PC2 vs. PC1) of the WT hPPA2 MD trajectory colored by simulation progression (blue: first 100 frames; purple: last 100 frames). (Bezpalaya E.; et al. 2025)

Reference

Bezpalaya E, et al. Conformational Dynamics of Mitochondrial Inorganic Pyrophosphatase hPPA2 and Its Changes Caused by Pathogenic Mutations. Life (Basel). 2025 Jan 15;15(1):100.

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From crystal structure to dynamic ensemble — without building an HPC department.
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