tooluniverse-protein-structure-prediction

name	tooluniverse-protein-structure-prediction
description	Protein 3D structure prediction from sequence — ESMFold de novo prediction, AlphaFold database retrieval, experimental structures from RCSB, ProtVar variant impact assessment, ProtParam sequence properties. Use for structure prediction when no experimental structure exists, fold-confidence scoring, and structure-guided variant interpretation.

Protein Structure Prediction and Analysis

End-to-end workflow for protein structure prediction starting from a sequence or UniProt accession. Combines ESMFold de novo prediction, AlphaFold database retrieval, experimental structure benchmarking from RCSB, ProtVar variant impact assessment, and ProtParam sequence property calculation.

KEY PRINCIPLES:

1. Sequence first — obtain or verify the protein sequence before prediction
2. ESMFold for fast de novo — works directly on sequence (up to ~800 residues); no database lookup needed
3. AlphaFold for reference — retrieve precomputed AlphaFold model for comparison; use qualifier parameter (UniProt accession)
4. Quality before interpretation — always report pLDDT scores; do not interpret low-confidence regions as folded
5. Experimental validation — compare predictions to RCSB experimental structures when available
6. ProtVar for variants — use when the question involves mutations or SNVs affecting structure
7. English-first queries — use English protein names in all tool calls; respond in the user's language

LOOK UP, DON'T GUESS

When uncertain about any scientific fact, SEARCH databases first rather than reasoning from memory. A database-verified answer is always more reliable than a guess.

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COMPUTE, DON'T DESCRIBE

When analysis requires computation (statistics, data processing, scoring, enrichment), write and run Python code via Bash. Don't describe what you would do — execute it and report actual results. Use ToolUniverse tools to retrieve data, then Python (pandas, scipy, statsmodels, matplotlib) to analyze it.

When to Use

Apply when users ask:

• "Predict the structure of this sequence: [FASTA]"
• "What does the AlphaFold model for [protein] look like?"
• "How confident is the AlphaFold prediction for [protein]?"
• "Is there an experimental structure for [protein] and how does it compare to AlphaFold?"
• "How does mutation [variant] affect the structure of [protein]?"
• "What are the physicochemical properties of [protein] sequence?"
• "Predict the structure of this novel protein" / "I have a new sequence, can you model it?"

Not for (use tooluniverse-protein-structure-retrieval instead): retrieval-only tasks where user provides a PDB ID or wants to browse experimental structures without prediction.

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Input Parameters

Parameter	Required	Description	Example
sequence	Yes (for ESMFold)	Amino acid sequence (single-letter FASTA)	MVLSPADKTNVK...
uniprot_id	Yes (for AlphaFold)	UniProt accession	P04637, P69905
variant	No	Variant notation for structural impact	P04637 R175H, TP53 R175H
max_length	No	ESMFold limit: ~800 residues recommended	—

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Workflow Overview

Phase 0: Input preparation (sequence retrieval if needed)
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Phase 1: Sequence properties (ProtParam_calculate)
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Phase 2: De novo prediction (ESMFold_predict_structure)
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Phase 3: AlphaFold reference (alphafold_get_prediction + alphafold_get_summary)
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Phase 4: Experimental structure comparison (RCSBAdvSearch_search_structures, RCSBData_get_entry)
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Phase 5: Variant structural impact (ProtVar_map_variant + ProtVar_get_function) [if variant provided]
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Phase 6: Quality synthesis and interpretation

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Phase 0: Input Preparation

Objective: Obtain or verify the protein sequence needed for ESMFold prediction.

If sequence is already provided

Use it directly for ESMFold_predict_structure. Check length:

• 1-400 residues: full prediction, high confidence expected
• 400-800 residues: prediction supported, may be slower

• 800 residues: ESMFold may fail or produce lower quality; recommend using AlphaFold instead

If only protein name or UniProt ID is provided

Retrieve sequence from UniProt_get_entry_by_accession:

• accession: UniProt accession
• Extract the sequence.value field from the response

Note: If only a name is given (not accession), first resolve with UniProt_search or MyGene_query_genes to get the UniProt accession, then fetch the sequence.

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Phase 1: Sequence Properties

Objective: Calculate physicochemical properties before prediction to contextualize results.

Tools

ProtParam_calculate:

• sequence: amino acid sequence string (single-letter code)
• Returns: molecular weight, isoelectric point (pI), extinction coefficient, instability index, GRAVY score, amino acid composition

Key Properties to Report

• Molecular weight — size context
• Isoelectric point (pI) — charge at neutral pH
• Instability index — >40 suggests unstable protein; affects prediction quality
• GRAVY score — hydrophobicity; >0 indicates membrane association tendency
• Length — determines ESMFold feasibility

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Phase 2: De Novo Structure Prediction (ESMFold)

Objective: Predict 3D structure from sequence using Meta's ESM-2 language model.

Tools

ESMFold_predict_structure:

• sequence: amino acid sequence string
• Returns: predicted structure in PDB format, per-residue pLDDT confidence scores, pTM score (global fold confidence)

Workflow

1. Call ESMFold_predict_structure with the sequence
2. Parse pLDDT scores:
   • Per-residue confidence array
   • Compute mean pLDDT over all residues
   • Identify low-confidence regions (pLDDT < 50)
3. Parse pTM score (predicted Template Modeling score) — overall fold quality
4. Record the PDB-format coordinate output for downstream visualization

Quality Interpretation

pLDDT Range	Interpretation	Reliability
>90	Very high confidence	Equivalent to experimental quality
70-90	High confidence	Backbone reliable, side chains approximate
50-70	Low confidence	Potentially disordered or flexible region
<50	Very low confidence	Likely intrinsically disordered; do not interpret

pTM Score	Fold Confidence
>0.8	High confidence global fold
0.5-0.8	Moderate; some domains may be uncertain
<0.5	Low global fold confidence

ESMFold vs AlphaFold

• ESMFold: faster, works directly on sequence, good for novel sequences, no database lookup
• AlphaFold: uses multiple sequence alignment (MSA); typically higher accuracy for well-conserved proteins
• Both predict single-chain monomer structures (not complexes in standard mode)

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Phase 3: AlphaFold Reference Model

Objective: Retrieve precomputed AlphaFold2 model for comparison and higher-accuracy reference.

Tools

alphafold_get_prediction:

• qualifier (or alias uniprot_id / uniprot_accession): UniProt accession (e.g., "P04637")
• Returns: AlphaFold model URL, pLDDT scores, model version

alphafold_get_summary:

• qualifier (or alias uniprot_id / uniprot_accession): UniProt accession
• Returns: prediction summary including confidence metrics, model quality

alphafold_get_annotations (optional):

• qualifier: UniProt accession
• Returns: functional region annotations overlaid on structure (binding sites, active sites)

AlphaFill_get_transplants (optional, ligands/cofactors):

• uniprot: UniProt accession (e.g., "P00520" ABL1)
• Returns: ligands, cofactors, and ions transplanted onto the AlphaFold model by homology, with per-transplant local RMSD and source PDB IDs
• When to use it: the apo AlphaFold model omits bound ligands/metals; run this to recover the likely cofactor/ligand/ion environment (e.g., ABL1 → STI/imatinib) for structure-guided binding-site interpretation

Workflow

1. Call alphafold_get_prediction and alphafold_get_summary
2. Extract mean pLDDT and per-residue confidence
3. Compare ESMFold vs AlphaFold pLDDT profiles:
   • Do they agree on low-confidence regions?
   • Large differences may indicate disordered/flexible regions
4. Note the AlphaFold model version (v1/v2/v3/v4)

Decision Logic

• If no UniProt accession available: skip AlphaFold; use ESMFold only
• If protein is a complex or has multiple chains: note that both tools predict single chains
• If AlphaFold confidence is very high (mean pLDDT > 85): recommend using AlphaFold as primary reference

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Phase 4: Experimental Structure Comparison

Objective: Check whether experimental structures exist in PDB and how predictions compare.

Tools

RCSBAdvSearch_search_structures (search by protein/gene name):

• query: protein name or gene symbol
• limit: number of results (default 10)
• Returns: list of PDB entries with resolution, method, title

RCSBData_get_entry (details for a specific PDB ID):

• pdb_id: 4-character PDB identifier
• Returns: metadata including method, resolution, chains, ligands, release date

Workflow

1. Search for experimental structures using protein name
2. Filter for highest-resolution X-ray or cryo-EM structures
3. For the best experimental structure, retrieve entry details
4. Compare to predictions:
   • If experimental structure exists: note coverage, resolution, method
   • Flag regions predicted with high confidence but missing from experimental structure (could be disordered in crystal)
   • Flag regions in experimental structure with low pLDDT (may be crystal artifacts vs true fold)

Fallback

• If RCSB search returns no results: note "no experimental structure found in PDB" and proceed with predictions only
• Suggest checking PDBe as secondary source

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Phase 5: Variant Structural Impact (When Variant Provided)

Objective: Assess how a specific amino acid substitution affects the predicted structure.

Tools

ProtVar_map_variant:

• variant: string notation like "P04637 R175H" or HGVS notation
• Returns: mapped residue position, genomic coordinates, consequence type, variant accession

ProtVar_get_function:

• accession: UniProt accession
• position: integer residue position
• variant_aa: mutant amino acid (single letter)
• Returns: functional annotations — domain, active site, binding site, conservation score, clinical significance, predicted pathogenicity

Workflow

1. Call ProtVar_map_variant to resolve the variant and confirm position
2. Call ProtVar_get_function with wild-type position to get domain context
3. Assess: is the mutated residue in a critical structural region?
   • Active site / binding site: likely high functional impact
   • Buried hydrophobic core: likely destabilizes fold
   • Surface-exposed, disordered region: less likely to affect overall fold
4. Compare pLDDT at that position (from ESMFold/AlphaFold) to assess if the region is well-predicted

Evidence Grading for Variant Impact

Tier	Evidence
T1	Clinical/functional data for this exact variant (from ProtVar)
T2	Variant at experimentally characterized active site or binding interface
T3	Computational pathogenicity prediction (PolyPhen, SIFT from ProtVar)
T4	Position in predicted structured region only

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Phase 6: Quality Synthesis and Report

Required Report Sections

1. Protein summary — name, length, pI, stability index (from ProtParam)

2. Structure prediction summary table:

   Method	Mean pLDDT	pTM/Global Score	Coverage	Notes
   ESMFold	X.X	X.X	100% (full seq)	—
   AlphaFold	X.X	—	100%	version vN
   Experimental (best)	N/A	N/A	XX%	PDB: XXXX, Xray, X.X A

3. Confidence map — regions of high vs low confidence; highlight disordered regions

4. Experimental structure comparison — does PDB have coverage? How does prediction align?

5. Variant impact (if applicable) — domain context, pathogenicity, structural consequence

6. Recommendations:

   • Which model to use for downstream applications (docking, design, etc.)
   • Regions to treat as unreliable
   • Suggested experimental validation approaches

Quality Minimums

• Report mean pLDDT for both ESMFold and AlphaFold
• Identify all low-confidence regions (pLDDT < 50) by residue range
• Check PDB for experimental structures (at minimum 1 search query)
• Compare at least 2 prediction sources when UniProt accession is available

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Tool Parameter Reference

Tool	Key Parameter	Notes
ESMFold_predict_structure	sequence	Raw amino acid string, no spaces, no FASTA header
alphafold_get_prediction	qualifier or uniprot_id	UniProt accession (e.g., "P04637")
alphafold_get_summary	qualifier or uniprot_id	Same UniProt accession
ProtParam_calculate	sequence	Same sequence string
ProtVar_map_variant	variant	Format: "<UniProt_ID> <AA><pos><AA>" e.g., "P04637 R175H"
ProtVar_get_function	position	Integer residue number

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Fallback Strategies

Situation	Fallback
ESMFold fails (sequence too long > 800 aa)	Use AlphaFold model only; note length limitation
AlphaFold no entry for UniProt ID	Use ESMFold prediction only
RCSB search returns no results	Note no experimental structure; proceed with predictions
No UniProt accession available	Use ESMFold from raw sequence; skip AlphaFold
ProtVar variant not found	Manually assess position from domain annotation in Phase 4

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Databases Integrated

Database	Coverage	What it provides
ESMFold	Any protein sequence (up to ~800 aa)	De novo structure prediction from sequence alone
AlphaFold DB	UniProt reviewed proteins (>200M entries)	Precomputed predictions with per-residue pLDDT
RCSB PDB	~220,000 experimental structures	Ground-truth experimental coordinates for comparison
ProtVar	All UniProt proteins	Variant impact, domain context, clinical annotations
ProtParam	Any sequence	Physicochemical sequence properties

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Limitations

• ESMFold length limit: sequences longer than ~800 residues may fail or have reduced quality
• Single-chain only: both ESMFold and standard AlphaFold predict monomers; complex prediction requires AlphaFold-Multimer (not available via these tools)
• Disordered regions: pLDDT < 50 indicates intrinsically disordered regions (IDRs) — do not interpret these as structured
• No dynamics: predicted structures are static; do not represent conformational flexibility or allosteric changes
• Novel folds: ESMFold may struggle with proteins having no homologs in training data
• AlphaFold DB coverage: some recently characterized proteins may not yet be in the AlphaFold database