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Template Processing

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OpenFold3 NIM supports template-guided structure prediction using pre-existing protein structures in CIF format. This page explains how templates are processed and used to guide predictions.

Overview

Template-guided prediction allows you to use other structures (experimental or predicted) to improve the accuracy of your structure predictions. The OpenFold3 NIM uses a simplified CIF direct mode that automatically processes template structures without requiring pre-computed alignments.

How Template Processing Works

When you provide structural templates, the NIM automatically performs the following steps:

Chain Extraction

The system parses each CIF file and extracts all protein chains along with their amino acid sequences.

Sequence Alignment

Each template chain is aligned to your query sequence using sequence alignment algorithms. This identifies which regions of the template correspond to your query protein.

Chain Scoring

Each template chain is scored using the formula:

score = sequence_identity × coverage

The variables are:

  • sequence_identity: Fraction of identical residues between template and query
  • coverage: Fraction of the query sequence covered by the alignment

Template Selection

For each CIF file:

  • If a chain_id is specified, that specific chain is validated against the minimum score threshold
  • If no chain_id is specified, the chain with the highest score is automatically selected
  • The selected chain must have a score above the minimum threshold (default: 0.1, configurable through CIF_DIRECT_MIN_SCORE)
  • If no chain meets the threshold, the template is excluded

Structure Guidance

Selected templates are used during the diffusion process to guide the model toward structures similar to the provided templates.

Best Practices

When to Use Templates

Templates are most effective when:

  • You have structures of homologous proteins (more than 30% sequence identity)
  • Experimental structures are available for similar protein sequences
  • You want to constrain predictions to a specific conformation
  • High-accuracy predictions from other tools are available

Template Selection

For best results:

  • High sequence identity: Use templates with more than 40% identity to your query
  • Good coverage: Templates should cover most of your query sequence
  • Structure quality: Prefer high-resolution experimental structures
  • Multiple templates: Provide 1-4 diverse templates when available

Multi-Chain CIF Files

When using CIF files containing multiple chains:

  • By default, the system automatically selects the best matching chain based on sequence similarity
  • You can optionally specify which chain to use through the chain_id field in the template
  • Each template file contributes at most one chain
  • Provide multiple CIF files if you want templates from multiple chains

Template Requirements

Format

  • Templates must be in CIF format (.cif files)
  • PDB format is not currently supported

Content

  • Template files must contain valid protein structure coordinates
  • Standard amino acid residues should be properly annotated
  • Chain identifiers should be present in the CIF file

Limitations

  • Templates are only supported for protein molecules
  • DNA, RNA, and ligand templates are not currently supported
  • Each protein molecule can have multiple templates

Configuration

The template processing behavior can be customized using environment variables:

CIF_DIRECT_MIN_SCORE

Controls the minimum score threshold for chain selection (default: 0.1). Refer to Template Configuration Options for details.