molclaw-interaction-visualizer

name	molclaw-interaction-visualizer
description	**PRIMARY tool for all single-structure interaction analysis.** MCP-exposed protein–ligand / peptide / protein–protein interaction analysis and Schrödinger-style multi-dimensional visualization. Pure Python/NumPy engine covering 9 interaction types with 2D diagram, 3D PyMOL rendering, residue bar, interface heatmap, interface network, and decision-ready CSV/JSON export. Always use this tool first; fall back to ProLIF MCP only for batch docking fingerprint comparison or MD trajectory analysis.
license	MIT license
metadata	{"skill-author":"PJLab","skill-level":"L1-Tool","version":1,"methodology-ref":"L3 Principle 15 (Mandatory image collection — all PNGs must be downloaded), L3 Principle 17 (Residue numbering reconciliation — use --resid_offset), L3 Principle 13 (Computation-first — interaction conclusions must come from tool output)\n"}

Interaction Visualizer — MCP and Local Analysis

Note:

• Local files are not directly accessible by the server. Please upload them to the server using molclaw-file-transfer before execution.
• For PDB file inputs, it is recommended to preprocess them using molclaw-pdbfixer before execution.
• Please refer to skill molclaw-scp-server to complete tool invocation.

[!NOTE] The current MolClaw server exposes this capability as the MCP tool interaction_visualizer. The bundled molclaw_interaction_visualizer.py remains available as an optional local CLI; it does not need to be uploaded to the server.

When To Use This Skill

This is the PRIMARY tool for all single-structure interaction analysis. ProLIF is only needed for batch docking fingerprint comparison or MD trajectory dynamics.

Scenario	Use this skill	Use ProLIF instead
Single complex structure interaction analysis	✅ PRIMARY	Only if this tool unavailable
Peptide or protein-protein interface analysis (single structure)	✅ PRIMARY	Only if this tool unavailable
Need Schrödinger-style 2D interaction diagram	✅	❌
Need PyMOL 3D multi-angle renderings	✅	❌
Need residue role annotations (Hinge/Gatekeeper/DFG)	✅	❌
Need decision-ready JSON with top residues + hot sites	✅	❌
Need partner_site.csv for ligand atom modification diagnosis	✅	❌
Need interaction fingerprint across MD trajectory frames	❌	✅ prolif_md
Need batch docking pose fingerprint comparison (≥ 2 poses)	❌	✅ prolif_docking
Need protein-protein trajectory interface profiling	❌	✅ prolif_protein_protein

Interaction Types Detected

#	Type	Key Geometry	Default Cutoff
1	Hydrogen bond	D-H···A angle ≥ 130°	3.5 Å
2	Hydrophobic contact	C···C distance	4.5 Å
3	π-π stacking (Face-to-Face)	Ring plane ∠ ≤ 35°	5.5 Å
4	π-π stacking (Edge-to-Face)	Ring plane ∠ 50°–90°	6.5 Å
5	Salt bridge	Charge center distance	5.5 Å
6	Cation-π	Cation-centroid + normal ∠	6.0 Å
7	Halogen bond	X···A with A-X-D geometry	3.5 Å
8	Metal coordination	Metal···coordinating atom	3.0 Å
9	van der Waals	Sum of VdW radii + tolerance	+0.5 Å

Three Analysis Modes

• ligand (default): Small-molecule ligand vs protein. Partner identified by HETATM records or --ligand_resname. Produces 2D diagram + residue bar + partner site CSV.
• peptide: One protein chain as partner peptide. Requires --partner_chain. Produces interface heatmap + interface network + residue bar.
• protein: Two full protein chains. Requires --chain_a and --chain_b. Produces interface heatmap + interface network + residue bar.

Input Source Mapping

Parameter	Source Guidance
--complex	Pre-merged complex PDB from docking output, Boltz-2/Chai-1 predicted structure, MD extracted frame, or crystal structure
--receptor	Protein PDB from molclaw-protein-structure-retrieve → molclaw-pdbfixer, or predicted structure
--ligand	Docking pose file from molclaw-quickvina-docking (.pdbqt), molclaw-karmadock-tool (.sdf), an externally supplied DiffDock SDF, or any .mol/.mol2/.xyz
--partner_pdb	Partner protein PDB for peptide/protein modes (from molclaw-extract-chains or separate structure)
--resid_offset	PDB→UniProt offset computed from sequence alignment (L3 Principle 17)
--residue_roles_json	User-provided or literature-derived residue functional annotations
--score	Docking affinity from upstream docking tool (kcal/mol)
--smiles	Ligand SMILES from user input or molecule retrieval

MCP Invocation

response = await client.session.call_tool(
    "interaction_visualizer",
    arguments={
        "mode": "ligand",
        "receptor_path": "/server/path/receptor_fixed.pdb",
        "ligand_path": "/server/path/docking_pose.pdbqt",
        "resid_offset": 0,
        "score": -8.3,
        "skip_pymol3d": True
    }
)
result = client.parse_result(response)
output_dir = result["output_dir"]
key_files = result["key_files"]

mode is required and must be one of ligand, peptide, or protein. Input paths must be server-side paths; use molclaw-file-transfer for local input files.

Bundled Local CLI Usage Patterns

Pattern 1: Single Complex File (Ligand Mode)

For a pre-merged complex PDB containing both protein and ligand:

python molclaw_interaction_visualizer.py \
    --complex complex.pdb \
    --mode ligand \
    --ligand_resname LIG \
    --out_dir viz_out \
    --resid_offset 0 \
    --title "EGFR–Erlotinib" \
    --score -8.3 \
    --smiles "C=Cc1cccc(Nc2ncnc3cc(OCCOC)c(OCCOC)cc23)c1"

Pattern 2: Separate Receptor + Ligand Files (Auto-Merge)

When receptor and ligand come from different upstream tools (e.g., PDBFixer output + docking pose PDBQT/SDF). The script automatically converts the ligand format and merges into a single complex.

python molclaw_interaction_visualizer.py \
    --receptor receptor_fixed.pdb \
    --ligand docking_pose_best.sdf \
    --mode ligand \
    --out_dir viz_out \
    --resid_offset 574 \
    --residue_roles_json roles.json \
    --title "CDK2–Compound_7" \
    --score -9.1 \
    --delta_score -1.2

Supported ligand formats for auto-merge: .sdf, .mol, .mol2, .pdb, .pdbqt, .xyz.

Pattern 3: Peptide–Protein Interface

python molclaw_interaction_visualizer.py \
    --complex complex.pdb \
    --mode peptide \
    --partner_chain B \
    --out_dir viz_out \
    --title "PD1–PeptideBinder"

Pattern 4: Protein–Protein Interface (Separate Files)

python molclaw_interaction_visualizer.py \
    --receptor chain_A.pdb \
    --partner_pdb chain_B.pdb \
    --mode protein \
    --chain_a A \
    --chain_b B \
    --out_dir viz_out \
    --title "IL6–IL6R interface"

Pattern 5: Quick CSV-Only (Skip All Plots)

For agent-only consumption when visualizations are not needed:

python molclaw_interaction_visualizer.py \
    --complex complex.pdb \
    --mode ligand \
    --ligand_resname LIG \
    --out_dir viz_out \
    --skip_diagram2d --skip_bar --skip_heatmap --skip_network --skip_pymol3d

Bundled Local CLI Parameter Reference

Parameter	Type	Default	Description
--complex	str	—	Single PDB/PDBQT file containing receptor + partner
--receptor	str	—	Receptor-only file (used with --ligand or --partner_pdb; alternative to --complex)
--ligand	str	—	Ligand-only file (.sdf/.mol/.mol2/.pdb/.pdbqt/.xyz); used with --receptor in ligand mode
--partner_pdb	str	—	Partner protein PDB for peptide/protein modes when receptor and partner are separate files
--merged_out	str	OUT_DIR/auto_merged.pdb	Path to save the auto-merged complex (when using --receptor + --ligand/--partner_pdb)
--mode	str	ligand	Analysis mode: ligand, peptide, or protein
--ligand_resname	str	—	(ligand mode) Restrict partner to a specific HETATM residue name
--partner_chain	str	—	(peptide mode) Chain ID of the peptide partner
--chain_a	str	—	(protein mode) Receptor chain ID
--chain_b	str	—	(protein mode) Partner chain ID
--out_dir	str	viz_out	Output directory (created if missing)
--resid_offset	int	0	Added to receptor resid in CSV output for PDB→UniProt mapping (L3 Principle 17)
--title	str	""	Common title prefix for all figures

Output Files and Download Policy

Ligand Mode Outputs

Output File	Format	Download Policy	Consumed By
interactions_{label}.csv	CSV	A — MUST download	L2-08 consensus ranking, L2-05 optimization diagnosis
interactions_{label}_residue_summary.csv	CSV	A — MUST download	Residue-level SAR analysis
interactions_{label}_partner_site.csv	CSV	A — MUST download	Ligand modification hotspot identification
diagram2d_{label}.png	PNG	A — MUST download (L3 P15)	Report, user presentation
residue_bar_{label}.png	PNG	A — MUST download (L3 P15)	Report
scene_{label}.pml	PML script	B — record path in log	PyMOL manual inspection
pymol_{label}_{front,side,top}.png	PNG	A — MUST download (if generated)	Report 3D views
summary_{label}.json	JSON	A — MUST download	Agent decision loop integration

Peptide / Protein Mode Additional Outputs

Output File	Format	Download Policy	Consumed By
interface_heatmap_{label}.png	PNG	A — MUST download (L3 P15)	Interface quality evaluation
interface_network_{label}.png	PNG	A — MUST download (L3 P15)	Interface topology analysis

CSV Column Specification

interactions_{label}.csv — Per-Interaction Detail

Column	Description
type	Normalized interaction type (HBond, SaltBridge, PiStacking, CationPi, Halogen, Metal, Hydrophobic, VdW)
subtype	Direction/variant (LigDonor, ProtDonor, FaceToFace, EdgeToFace, etc.)
rec_res	Receptor residue label (e.g., MET769A)
rec_resid_pdb	Receptor residue number in PDB numbering
rec_resid_mapped	Receptor residue number after applying --resid_offset (for UniProt mapping)
rec_res_class	Residue classification (hydrophobic, aromatic, polar, positive, negative)
rec_atom	Receptor atom name(s) involved
partner_atom	Partner atom name(s) involved
distance_A	Interaction distance in Ångströms
angle_deg	Relevant geometry angle in degrees (if applicable)
strength_hint	Qualitative label: strong / moderate / weak / packing / contact

*_residue_summary.csv — Per-Residue Rollup

One row per contacting residue, columns for each interaction type count, total count, and minimum distance.

*_partner_site.csv — Ligand Atom Hotspot (Ligand Mode Only)

One row per ligand atom involved in interactions, columns for each interaction type count. Use this to identify:

• Atoms to preserve: high total count → critical pharmacophore points
• Atoms to modify: low or zero count → optimization candidates

Interpreting summary_{label}.json (Agent Decision Integration)

{
  "mode": "ligand",
  "label": "LIG",
  "n_interactions": 42,
  "n_contact_residues": 15,
  "interaction_type_counts": {
    "HBond": 3, "SaltBridge": 1, "PiStacking": 2,
    "CationPi": 0, "Halogen": 0, "Metal": 0,
    "Hydrophobic": 8, "VdW": 15
  },
  "top_residues": [
    {"res": "MET769A"    
         
         
       
  
   
       
         
       
       
  
    ... 

Agent decision rules:

• top_residues → Verify expected key contacts match the task requirements (e.g., "confirm hinge interaction with Met793").
• hot_partner_sites → Atoms with high total and strong interaction types (HBond, SaltBridge) should be preserved during optimization. Atoms with low total are safe modification candidates.
• interaction_type_counts → A molecule with 0 HBonds to the hinge region is likely a poor kinase inhibitor candidate; flag for re-evaluation.

Residue Numbering Reconciliation (L3 Principle 17 — MANDATORY)

Use --resid_offset N where N = UniProt_number − PDB_number for the protein.

Example: If PDB 1M17 has Met at position 769, but UniProt numbering is Met793, then --resid_offset 24.

All CSV outputs include a rec_resid_mapped column with the offset applied. When reporting results:

• CORRECT: "Interaction visualizer detected HBond at MET769 (PDB) = Met793 (UniProt, offset +24). This confirms the expected hinge interaction."
• WRONG: "Interaction visualizer did not find Met793." (False negative from numbering mismatch.)

For Boltz-2/Chai-1 predicted structures where the offset is non-trivial, compute the offset from sequence alignment BEFORE running this tool.

Strength Hints (Qualitative — NOT Quantitative Energies)

Type	"strong"	"moderate"	"weak" / "packing" / "contact"
HBond	d ≤ 2.9 Å and ∠ ≥ 150°	d ≤ 3.2 Å and ∠ ≥ 130°	otherwise
SaltBridge	d ≤ 4.0 Å	d > 4.0 Å	—
PiStacking	d ≤ 4.5 Å	d > 4.5 Å	—
Hydrophobic	—	—	"packing" (always)
VdW	—	—	"contact" (always)

These are qualitative drug-chemist-style labels. They are NOT quantitative binding energy estimates. Do not use them as substitutes for MM-PBSA or FEP calculations.

Common Failures & Recovery

Failure	Likely Cause	Recovery
No atoms parsed from {path}	Wrong file format, empty file, or binary format given as text	Verify file is valid PDB/PDBQT; check encoding
Partner atom list empty	Ligand resname not found in PDB, or wrong --partner_chain	Check --ligand_resname matches actual HETATM resname in PDB; verify chain IDs
RDKit failed to build ligand mol	Bond perception or sanitization issue with ligand	2D diagram skipped; CSV and all other outputs still produced. Install/upgrade rdkit if needed
2D diagram PNG not generated	RDKit not installed	pip install rdkit; or accept CSV-only output and use --skip_diagram2d
PyMOL images not generated	PyMOL not on system PATH	Install PyMOL (conda install -c conda-forge pymol-open-source); or use --skip_pymol3d
0 interactions detected	Ligand not in binding pocket (bad docking pose) or atoms too far apart	Verify docking pose quality upstream; re-dock with larger box
Auto-merge PDBQT fails	PDBQT has non-standard formatting	Convert PDBQT → PDB first using OpenBabel, then use --ligand pose.pdb
AssertionError: --partner_chain required	Peptide mode invoked without chain specification	Inspect PDB chain IDs and provide --partner_chain

Integration with Upstream Skills

Upstream Skill	Provides	This Skill Uses As
molclaw-quickvina-docking	PDBQT docking pose + affinity score	--ligand (PDBQT) + --score
Externally supplied DiffDock result	SDF docking pose + confidence	--ligand (SDF) + --score; diffdock_auto is not deployed on the current MCP server
molclaw-karmadock-tool	SDF docking pose + score	--ligand (SDF) + --score
molclaw-pdbfixer	Cleaned receptor PDB	--receptor
molclaw-fix-pdb	Fixed PDB structure	--receptor or --complex
molclaw-protein-structure-retrieve	PDB file from RCSB/AlphaFold	--receptor or --complex
molclaw-chai1-predict	Predicted complex structure	--complex
molclaw-boltz2-affinity	Complex CIF + binding probability	--complex (convert CIF→PDB if needed)
molclaw-esmfold	Predicted protein structure	--receptor
molclaw-proteinmpnn-tool	Designed sequence + structure	--complex (protein mode)
molclaw-evobind-tool	Peptide binder + complex	--complex (peptide mode)
molclaw-hdock-tool	Protein-protein or protein-peptide docked complex	--complex with protein mode for protein-protein, or peptide mode with partner_chain from hdock_tool.partner_chains for protein-peptide
molclaw-extract-chains

Integration with Downstream Consumers

This Skill Produces	Downstream Consumer	How It Is Used
interactions_*.csv	L2-08 Post-Docking Evaluation (Module 2B)	Interaction data for consensus ranking
*_residue_summary.csv	L2-08 Module 4 (SAR analysis)	Per-residue interaction profile for SAR reasoning
*_partner_site.csv	L2-05 Iterative Optimization (Step 2 Diagnose)	Identify ligand atoms to preserve vs modify
summary_*.json	Agent decision loop	Programmatic access to top residues and interaction counts
diagram2d_*.png	L2 Report assembly	Schrödinger-style visual for publication/presentation
residue_bar_*.png	L2 Report assembly	Contact composition overview
interface_heatmap_*.png	L2-09 Peptide Design validation	Interface quality assessment
interface_network_*.png	L2-09, L2-11	Interface topology and selectivity comparison
pymol_*.png	L2 Report assembly	3D structural context

Residue Role Annotation JSON Format

The --residue_roles_json file maps residue labels to functional roles. This enables the 2D diagram to annotate each residue bubble with its pharmacological significance.

{
    "MET769": "Hinge",
    "LEU768": "Hinge",
    "THR766": "Gatekeeper",
    "LYS721": "Catalytic",
    "GLU738": "αC-helix",
    "ASP831": "DFG",
    "PHE832": "DFG",
    "VAL702": "P-loop",
    "LEU820": "Hydrophobic",
    "ALA719": "Hydrophobic"
}

Keys are matched by prefix (3-letter resname + resid), so "MET769" matches MET769A, MET769B, etc.

Common role vocabularies by target class:

• Kinases: Hinge, Gatekeeper, DFG, P-loop, αC-helix, Catalytic, Hydrophobic
• GPCRs: TM1-TM7, ECL1-ECL3, ICL1-ICL3, Orthosteric, Allosteric
• Proteases: Catalytic triad, Oxyanion hole, S1-S4 pockets

Dependencies & Installation

Required (typically in base environment):

• numpy — core geometry computation
• matplotlib — all 2D plot generation (diagram, bar, heatmap, network)

Optional (enables additional output types):

Package	Enables	Install	Without It
rdkit	2D ligand diagram + SDF/MOL2/XYZ input parsing	pip install rdkit or conda install -c conda-forge rdkit	2D diagram skipped; CSV and all other outputs still produced
pymol (open-source)	3D multi-angle ray-traced rendering	conda install -c conda-forge pymol-open-source	3D images skipped; use --skip_pymol3d
Pillow	Image post-processing and compositing	pip install Pillow	Minor formatting differences only

Choosing Between This Skill and ProLIF

Rule: This skill is the default for all single-structure interaction analysis. ProLIF is only used when its unique capabilities (batch, trajectory) are required.

Need	This Skill (PRIMARY)	ProLIF (MCP, supplement)
Single complex structure interaction analysis	✅ default	Only if this tool unavailable
Peptide/protein interface (single structure)	✅ default	Only if this tool unavailable
Schrödinger-style 2D interaction diagram	✅	❌
PyMOL 3D multi-angle renderings	✅	❌
Residue role annotations (Hinge/Gatekeeper/DFG)	✅	❌
Decision-ready JSON with top residues + hot sites	✅	❌
Native --resid_offset for PDB→UniProt mapping	✅	❌
ProLIF MCP server unreachable or down	✅ (local)	❌
Interaction fingerprint across MD trajectory frames	❌	✅ (prolif_md)
Batch docking pose fingerprint comparison (≥ 2 poses)	❌	✅ (prolif_docking)
Protein-protein trajectory interface profiling	❌	✅ (prolif_protein_protein)