Apheris Hub - Known Issues

Below, we list known issues with Apheris Hub. If available, we list a workaround to help troubleshoot the issue.

This list will be constantly evolving with input from our different users and with the evolution of our product in future releases.

Known Issues with Apheris Hub 1.4

OpenFold3

Issue	Description	Additional information
Potential Memory Leak with OpenFold3 Benchmarks	When running benchmarks with OpenFold3, some jobs may fail due to a potential memory leak.	This issue is currently under investigation.

Prediction and Processing

Issue	Description	Additional information
ColabFold Server Rate Limiting	The public ColabFold server applies rate limiting, which can significantly slow down processing of even simple queries.	If you encounter slower than anticipated query times it is likely due to using the public ColabFold server. Please wait a few minutes and try again or use MSAs from file if the model supports it.
Delayed Execution on Shared GPU	When we have a single GPU being shared between two running model versions, parallel jobs can be started on each of those models. However, because they share the same GPU, the execution can be blocked and delayed.	Additionally, the UI shows the delayed requests as "Running" instead of "Pending", as they are waiting for the GPU to become available.
No validation that MSA file sequence and sequence provided in queries match	Queries containing unknown residues (X character) at the beginning of sequences, particularly when combined with ligands like HEM, may cause MSA generation errors.	Future releases will improve the validations being performed before a user submitting a prediction run known to fail.
Nonstandard residues between parentheses are not supported	Including nonstandard residues in parentheses causes the MSA to crash. Generally, these should be converted to X before sending to an MSA server.	Future releases will add support for Nonstandard residues.
Cancelling a Job May Not Stop Inference Execution	Cancelling a prediction request or benchmark updates its status in the UI but may not fully stop the underlying inference job. In some cases the job can continue running and the request status may revert to "running" or "done" after cancellation.

Benchmarking

Issue	Description	Additional information
Boltz-2 and Protenix Benchmarks May Omit Ligand Metrics	Benchmark runs using Boltz-2 or Protenix may sometimes omit ligand metrics in the results, particularly for predictions with less accurate atom distances.
Cancel Button Available on Terminally Failed Benchmarks	The Cancel button remains visible and clickable on a benchmark that has already terminally failed with no running jobs. Clicking it shows a cancellation confirmation but has no meaningful effect.

Fine-Tuning

Issue	Description	Additional information
Dataset Generation Fails for SDF Files with Explicit Hydrogens	Fine-tuning dataset generation fails when SDF files contain explicit hydrogen atoms. SDF files with explicit hydrogens are not currently supported and will cause the dataset generation phase to fail.	Remove explicit hydrogens from SDF files before uploading them for fine-tuning. Tools such as RDKit or Open Babel can be used to strip hydrogens from SDF files (e.g., using RDKit's RemoveHs() or Open Babel's -d option).

User Interface

Issue	Description	Additional information
PAE Filter Issues on Window Resize	When resizing the browser window or zooming out while viewing results, the PAE filter selection may appear and disappear unexpectedly. Clicking deselect may not work consistently.	If you experience this issue, try avoiding window resize operations while working with PAE plots.
Cannot Switch Users After Logout	After logging out, logging back in with the same organization automatically signs in as the previous user. It is not possible to select a different user without clearing the browser cache or using a new window.	Clear browser cache or use an incognito/private window to log in as a different user within the same organization.
"Set Up New Prediction" Button May Not Restore Query Correctly	On the results page, clicking "Set up new prediction" to rebuild a query from an existing result may not work correctly when the original model used is no longer available.	If the button does not work as expected, set up the prediction manually using the Predict page.
Unexpected Logout While Actively Using the UI	Users may be unexpectedly logged out and redirected to the login screen while actively working in the UI.	This issue is currently under investigation.

Form and Input Handling

Issue	Description	Additional information
Invalid CIF Upload Accepted Without Error Status	When uploading an invalid CIF file to a fine-tune dataset, the API returns a success status instead of an error. The frontend works around this by checking the response body, but the API response code is misleading.

Installation and Configuration

Issue	Description	Additional information
Port Allocation	The installation script uses a fixed port (8080) which may already be in use on some systems.	As a workaround, ensure port 8080 is available before installation or modify the port in the installation script.
Single GPU Limitation with Multiple Models	When deploying the Hub using Kubernetes and Helm on a machine with only one GPU, only one model (OpenFold3 or Boltz-2) can be started at a time.	Use a machine with multiple GPUs, enable fractional GPU usage, or run one model at a time. This limitation should be considered when planning your deployment infrastructure.
Bash Version Check Missing in Deploy Script	The deploy_apherisfold script requires GNU Bash version 4.0 or higher but does not check this requirement before execution. Running the script with an older version or a different shell results in cryptic error messages.	Ensure you are using GNU Bash version 4.0 or higher before running the deployment script. Verify your bash version with bash --version.