Use OmegaFold

Official Neurosnap webserver for accessing OmegaFold online.

Overview

OmegaFold is an advanced computational tool for high-resolution de novo protein structure prediction directly from primary amino acid sequences. Unlike traditional methods that depend on multiple sequence alignments (MSAs), OmegaFold utilizes a novel combination of a protein language model and a geometry-inspired transformer model trained on protein structures. This approach enables accurate predictions for proteins lacking homologous sequences, such as orphan proteins and rapidly evolving antibodies, thereby filling a critical gap in structural biology.

Neurosnap Overview

The OmegaFold online webserver allows anybody with a Neurosnap account to run and access OmegaFold, no downloads required. Information submitted through this webserver is kept confidential and never sold to third parties as detailed by our strong terms of service and privacy policy.

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Features

  • Predicts high-resolution protein structures directly from primary sequences without the need for multiple sequence alignments.
  • Employs a protein language model combined with a geometry-inspired transformer for enhanced prediction accuracy.
  • Demonstrates comparable performance to AlphaFold2 on recently released structures.
  • Effective for proteins with limited or no homologous sequences, including orphan proteins and fast-evolving antibodies.

Statistics

Neurosnap periodically calculates runtime statistics based on job execution data. These estimates provide a general guideline for how long your job may take, but actual runtimes can vary significantly depending on factors like input size or settings used.

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API Request

Access OmegaFold using the Neurosnap API by sending a request using any programming language with HTTP support. To safely generate an API key, visit the API tab of your overview page.

Job Note

Provide a name or description for your job to help you organize and track its results. This input is solely for organizational purposes and does not impact the outcome of the job.

Configuration & Options

Service Inputs

The amino acid sequences corresponding to the proteins you want to generate to predict disordered regions for.

Increased cycles tend to produce more accurate predictions but will also greatly increases prediction time (similar to recycles in AlphaFold2). The recommended default is 10.

Specify whether you want to use version 2 or version 1 of the OmegaFold model.

Ready to submit your job?

Once you're done just hit the submit button below and let us do the rest.

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