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How to run an AlphaFold+ job

Overview of the steps required to launch the AlphaFold+ analysis and where to retrieve the results.

What is the Alphafold+ analysis

AlphaFold+ is based on the latest official release of DeepMind’s AlphaFold2 (v2.3.2) and extends it with an integrated reporting module. It predicts the 3D structure of proteins or protein complexes and generates a clear, browser-viewable report summarizing prediction confidence and model ranking.

How to run an AlphaFold+ job

The AlphaFold+ application requires an amino acid sequence. Upload a .fasta file or use an amino acid sequence. 

  • Step 1. On the LensAI™ Home Page, click "Run Analysis"
    LensAI Run Analysis

  • Step 2. Locate the AlphaFold+ analysis and click "Run Job"

  • Step 3. Inside the run configuration, select the dataset
    LensAI Select Dataset

Caution: The dataset must be chosen, not the .fasta file itself.

Caution: The .fasta file must follow some rules.

  1. Sequences cannot contain 'new lines'

  2. The file name cannot contain a space
  3. Fasta headers cannot contain spaces

  • Step 4. Define the output dataset logical name
    LensAI Dataset Name

Caution: The name of the output dataset should not contains any space. Underscore is accepted.

  • Step 5. Optionally configure the other inputs

    • model_preset: Preset model configuration
      • Monomer: Suitable for predicting the structure of single protein chains.
      • Monomer PTM: Includes predicted alignment error and pLDDT confidence scores for assessing the accuracy of specific regions.
      • Multimer: Designed for protein complexes involving multiple chains or interactions.
    • number of seeds per multimermodel: Define the number of seeds per prediction, 5 being the default when running multimer systems. Decreasing this value will drop the accuracy.
    • models_to_relax: The models to run the final relaxation step on (all, best, none)
    • msa_range: Limit the range of MSA. Adjust the preset MSA range for generating the quality report. This setting allows users to focus on specific sequence portions of interest, with a narrower range enhancing analysis accuracy by targeting relevant data. Conversely, a broader range offers a comprehensive overview, beneficial for understanding structural context. Balance the selected range with available computational resources, as larger ranges may demand more processing time and memory.
  • Step 6. Optionally provide experiment details under the General Run Metadata Inputs
    LensAI General Metadata
  • Step 7. Click "Run Job" to launch the application
  • Step 8. Monitor the state and the results of the analysis in the "Applications" page under the "History" tab
    LensAI Job History