Case Study
Protein-Ligand Interaction Modeling Service

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Protein-Ligand Interaction Modeling Service
Interaction Profiling · SAR Analysis

Protein–Ligand Interaction Modeling for Mechanistic & SAR Insights

Go beyond binding poses. Elucidate interaction fingerprints, quantify non-covalent forces, and derive structure–activity relationships with our specialized interaction modeling workflows.

Interaction fingerprinting Contact analysis Energy decomposition SAR-driven design
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Interaction Fingerprint (IFP)
Convert 3D binding modes into binary fingerprints for rapid similarity and clustering.
📊
Per-residue and per-interaction energy breakdown (van der Waals, electrostatics, H-bond).
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Water & Solvent Analysis
Assess water-mediated interactions and displaceable waters for lead optimization.
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SAR Correlation
Map interaction patterns to activity data to guide rational analog design.

Protein–Ligand Interaction Modeling Service Coverage

Binding mode

Interaction Fingerprinting

Generate binary or weighted interaction fingerprints for H-bonds, hydrophobic contacts, ionic interactions, and π-stacking. Enable rapid similarity searching, clustering, and diversity analysis across compound sets.

Energetics

Per-Residue Energy Decomposition

Decompose binding free energy into residue-wise contributions (van der Waals, electrostatics, solvation). Identify hotspots and critical residues for potency and selectivity.

Solvent

Water & Solvent Analysis

Map water molecules in the binding site, assess their thermodynamic profiles, and identify displaceable waters to guide rational lead optimization and affinity improvement.

SAR

Structure–Activity Relationship (SAR) Correlation

Map interaction patterns to experimental activity data. Uncover activity cliffs, identify key interaction motifs, and prioritize compounds for synthesis.

Selectivity

Selectivity & Cross-Reactivity Profiling

Compare interaction fingerprints and energy decompositions across related targets to guide selectivity design and minimize off-target effects.

Dynamic

MD-Based Interaction Analysis

Analyze interaction stability and dynamics from molecular dynamics trajectories, including contact occupancies, hydrogen bond lifetimes, and water residence times.

Core Calculation Methods

Fingerprinting

Interaction Fingerprint (IFP) Generation

Using PLIF, SIFt, or custom pharmacophore-based fingerprints to encode protein-ligand interactions into robust descriptors for chemoinformatics and machine learning.

Energy

MM-GBSA & MM-PBSA Decomposition

End-point free energy methods with residue-wise decomposition to quantify per-residue contributions and solvation effects.

Water

WaterMap & Solvent Thermodynamics

Grid-based water analysis to compute enthalpic and entropic contributions of water molecules in the binding site.

Contact

Geometric Contact & Distance Analysis

Detailed analysis of interatomic distances, angles, and occupancies for all non-covalent interactions.

Dynamics

MD Trajectory Interaction Analysis

Extract interaction fingerprints, H-bond occupancies, and water residence times from molecular dynamics simulations.

Visualization

2D & 3D Interaction Diagrams

Automated generation of publication-quality interaction diagrams with color-coded interaction types and residue labels.

Real Research Scenarios We Solve

Scenario 1

Selectivity Optimization

Challenge: Lead compound shows off-target activity against a related kinase.
Solution: Cross-target interaction profiling identifies a unique hydrophobic pocket; guide design of selective analogs with 50x selectivity.

Scenario 2

Hit-to-Lead Prioritization

Challenge: 50 hits from screening; limited capacity for synthesis.
Solution: IFP clustering + SAR correlation prioritizes 5 chemotypes with optimal interaction profiles and activity.

Scenario 3

Binding Mode Validation

Challenge: Docking poses inconsistent with mutagenesis data.
Solution: Interaction fingerprinting and energy decomposition identify the most plausible binding mode consistent with experimental data.

Scenario 4

Fragment Linking & Growing

Challenge: Two fragments bind in adjacent pockets; linking strategy unclear.
Solution: Interaction analysis identifies optimal vectors and linker geometries for fragment merging.

Scenario 5

Residue Hotspot Mapping

Challenge: Identify which residues drive binding affinity for a series.
Solution: Per-residue energy decomposition across analogs pinpoints critical hotspots for optimization.

Scenario 6

Selectivity Against Off-Targets

Challenge: Compound shows activity against a related family member.
Solution: Interaction fingerprint comparison reveals differences in a key subpocket, guiding selective design.

Why Work with CD ComputaBio for Interaction Modeling?

Our team combines deep expertise in computational chemistry with a focus on actionable insights. We don't just generate data – we interpret it in the context of your project goals, delivering clear recommendations for design and optimization.

Method ExpertiseWe master a wide range of interaction analysis tools: PLIF, SIFt, WaterMap, MM-GBSA, MD-based interaction analysis, and more.
Project IntegrationWe integrate interaction modeling with docking, MD, and free energy calculations for a complete picture of binding.
Decision-ReadyReports include prioritized lists, hot spot maps, and design suggestions – not just raw data.

Our Interaction Modeling Workflow

1

Structure & Ligand Preparation

Curate protein and ligand structures, assign protonation, tautomers, and optimize geometry.

2

Docking & Pose Generation

Generate high-quality binding poses using flexible docking protocols.

3

Interaction Fingerprinting & Scoring

Compute interaction fingerprints, energy decomposition, and solvent analysis.

4

SAR & Prioritization

Correlate interaction patterns with activity data to prioritize compounds and identify optimization vectors.

5

Interactive Visualization & Report

Deliver interactive 3D visualizations, 2D interaction diagrams, and a comprehensive technical report.

Inputs

  • Protein structure (PDB, homology model, or AlphaFold)
  • Ligand set (SDF, SMILES, or Mol2) – from a few to hundreds of compounds
  • Binding site definition (or co-crystallized ligand)
  • Activity data (optional, for SAR correlation)
  • Specific questions: hotspot identification, selectivity, water analysis, etc.

Deliverables

  • Interaction fingerprint (IFP) matrix and similarity analysis
  • Per-residue energy decomposition plots and tables
  • WaterMap / solvent analysis (if applicable)
  • Detailed contact lists (H-bonds, hydrophobic, π-stacking, salt bridges)
  • SAR correlation plots and prioritized compound lists
  • Interactive 3D visualization files (PyMOL, Schrödinger)
  • Comprehensive technical report with methods and interpretation

Recent Interaction Modeling Projects

IFP-based SAR analysis

Goal: rationalize activity cliffs.
Approach: docking + IFP clustering + activity mapping → identified key H-bond as activity switch.

Selectivity profiling

Goal: improve kinase selectivity.
Approach: per-residue decomposition across 5 kinases → designed selective analog with 50x selectivity.

Water displacement strategy

Goal: boost potency.
Approach: WaterMap + docking → replaced a water with a methyl group → 8x affinity gain.

Frequently Asked Questions

What is the difference between docking and interaction modeling?

Docking focuses on generating binding poses and ranking by affinity. Interaction modeling goes further: it quantifies and classifies the specific interactions (H-bonds, hydrophobic, etc.), decomposes energy, and correlates with SAR, providing deeper mechanistic insight.

Can you perform interaction modeling for covalent inhibitors?

Yes. We can analyze covalent adducts and include the covalent bond in interaction fingerprints and energy decomposition, offering a complete picture of binding.

Do I need activity data for interaction modeling?

Not necessarily. However, if you have activity data, we can perform SAR correlation analysis to map interaction patterns to potency, which is invaluable for lead optimization.

How long does an interaction modeling project take?

Typical projects range from 2–4 weeks depending on library size and complexity. Rapid turnaround is available for urgent projects.

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