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Release NotesπŸ”—

Apheris Hub 1.1.0πŸ”—

  • Release date: 2025-12-05

ApherisFold Application: 0.28.0πŸ”—

  • OpenFold3
    • openfold3:0.28.0
  • Boltz-2
    • boltz2:0.28.0
  • Mock Model
    • mock:0.28.0

HighlightsπŸ”—

The Apheris Hub 1.1.0 release introduces major architectural improvements with Kubernetes-native deployment and coordinator mode, enabling more flexible and secure enterprise deployments. This release marks a significant shift in deployment architecture, moving away from Docker API dependencies to support Kubernetes orchestration.

New FeaturesπŸ”—

  • Kubernetes-Native Deployment with Helm Charts: The Hub now offers first-class support for Kubernetes deployments via Helm charts, designed for production environments in pharmaceutical and enterprise settings. This deployment method allows seamless integration with existing Kubernetes infrastructure, provides better scalability, and eliminates dependencies on the Docker API. Cloud-based (AWS EKS) Kubernetes deployments are fully supported with comprehensive documentation while we are still maintaining support for simplified Docker-based deployments through auxiliary deployment scripts.
  • Hub Coordinator Mode: Introduced a new architectural pattern where the Hub operates in coordinator mode, decoupling model lifecycle management from the Hub itself. In this mode, models and their wrappers can be deployed and managed independently, with the Hub discovering and coordinating access to already-running models. This removes the requirement for docker.sock access, addressing critical security concerns in enterprise environments, and enables better alignment with orchestration technologies like Kubernetes and job schedulers like Slurm.
  • Model Weight Management: Added comprehensive support for selecting between multiple available model weight sets within a single model deployment. Users can now select from different weight configurations (that in the future can be public weights, fine-tuned weights or federated weights) through both the UI and API. A new /weights endpoint allows querying available weight sets, with each set including metadata like version and description for easy identification.

Breaking ChangesπŸ”—

  • Deployment Mode Changes: CloudFormation and single Docker container deployment methods are no longer maintained. Supported deployment flows are now limited to Kubernetes with Helm charts (for production and development) and auxiliary Docker scripts (for local evaluation). Users relying on deprecated deployment methods must migrate to one of the supported options.
  • Docker API Dependency Removed: The Hub no longer requires or uses Docker API integration for managing model lifecycles. Model installation, starting, and stopping through the Docker API has been removed.
  • PostgreSQL Database Required: SQLite is no longer supported as the backend database. The Hub now requires PostgreSQL for improved performance and better concurrency and state handling.
  • Weight Version Parameter Required: The /predict endpoint now requires a weightVersion parameter to specify which model weights to use. Requests without this parameter will fail. This change enables multi-weight support but requires updates to existing inference scripts.
  • Chain IDs Type Enforcement: The chain_ids field in inference requests now strictly requires an array of strings (string[]). Previously accepted weak typing like single strings is no longer supported to prevent ambiguous interpretations.

EnhancementsπŸ”—

  • Inference and Query Building:

    • Added validation to prevent duplicate chain IDs within a query.
    • Implemented prevention of duplicate file attachments in query builder.
    • Added validation requiring at least one query per inference request.
    • Improved JSON request parameter validations including maximum query limits.
    • Fixed enter key behavior in query builder to prevent unintended actions.
    • Trimmed whitespace from sequences and SMILES inputs automatically.

  • Results and Visualization:

    • Fixed SMILES to CCD code toggle functionality in ligand chain configuration.
    • Added ligand atom pLDDT coloring in molecular viewer.
    • Improved PAE/PDE plot legend to reflect actual displayed data.

  • Generic User Interface Improvements:

    • Added clear button to search input fields.
    • Fixed issues with CodeMirror panels overlapping modals.
    • Added visual indication of the number of running and pending jobs per model version.

  • Model Wrapper Enhancements:

    • Improved typing of API responses removing null types and making fields consistently optional.
    • Enhanced CIF validation response typing for better frontend integration.
    • Improved error messages when invalid sequences are submitted.
    • Enhanced error surfacing when GPUs are configured incorrectly.
  • Documentation:
    • Updated Query Builder documentation for multi-ligand inference support.

Apheris Hub 1.0.0πŸ”—

  • Release date: 2025-10-28

ApherisFold Application: 0.22.0πŸ”—

  • OpenFold3
    • openfold3:0.22.0
  • Boltz-2
    • boltz2:0.22.0
  • Mock Model
    • mock:0.22.0

HighlightsπŸ”—

The Apheris Hub 1.0.0 release marks a significant milestone with the introduction of a graphical Query Builder and structure prediction evaluation capability. This release focuses on improving user experience for non-technical users while adding powerful features for model performance assessment, including full-screen visualization modes and support for structure comparison workflows. Additionally, infrastructure improvements enable better troubleshooting through support ZIP exports and more robust model management capabilities.

New FeaturesπŸ”—

  • Query Builder for Inference: Introduced a graphical Query Builder that allows users to construct inference requests without writing JSON manually. The builder supports adding multiple queries, selecting molecule types from dropdowns (Protein, Ligand, DNA, RNA), defining chain IDs and sequences, and attaching external assets. Users can seamlessly switch between the graphical builder and JSON editor, with automatic validation to prevent errors.
  • Full-Screen 3D Molecular Viewer: Added ability to maximize the molecular viewer to utilize full screen space for detailed structural inspection. The Full-Screen Molecular Viewer includes the 3D viewer, PAE/PDE plot, and sequence bar, with options to minimize individual components as needed.
  • Evaluation with Structure Superposition: Enabled comparison of predicted structures against ground-truth experimental structures. When a ground-truth structure is provided with the inference request, the system automatically performs structure alignment and calculates key metrics including Average pLDDT, Ligand RMSD, Ligand-Protein Interaction LDDT, Protein CΞ± GDT-HA, Protein CΞ± GDT-TS, Protein CΞ± LDDT, Protein CΞ± RMSD. The aligned structures are displayed as overlays in different colors within the molecular viewer. Check the documentation for Evaluation Examples.
  • Easy export of diagnostic and configuration data to a ZIP file: Added a Support ZIP Archive feature that allows users to download a compressed file containing structured diagnostic and configuration data - from the Apheris Hub Docker container - to streamline external support and debugging.
  • ColabFold MSA Server Configuration: Extended MSA server configuration to support ColabFold servers in addition to the existing Foldify server support. Users can now configure their own private ColabFold server or use the public ColabFold server for MSA generation. When configuring inference runs, users can select which MSA server to use from their configured options, allowing them to compare performance between different servers or integrate their existing ColabFold infrastructure. Check the documentation sections Configurable MSA Server and MSA Usage to know more about this new feature.

Breaking ChangesπŸ”—

  • Model Version Naming Simplification: Removed the -public-colabfold suffix from model versions. All models now use a single version naming scheme (e.g., boltz2:0.22.0 instead of boltz2:0.22.0-public-colabfold). Users should update any scripts or configurations that reference the old version naming convention. MSA server selection is now managed through the MSA configuration interface rather than through model version selection.
  • Application Renaming: The application has been renamed from "Apheris Co-folding" to "ApherisFold" to better reflect its focus on protein structure prediction.

EnhancementsπŸ”—

  • Inference Runs / Results:

    • Added real-time updates for humanized time displays (e.g., "2 minutes ago") that refresh every 30 seconds.
    • Enabled persistence of last used model version, so the inference form remembers previously selected models.
    • Added exact match search capability for job IDs, improving result filtering when searching by job identifier.
    • Fixed pLDDT coloring to work correctly across all model types.

  • Model Management:

    • Added automatic timeout handling for pending inference requests to prevent queue blockage.
    • Implemented automatic timeout for accepted jobs that remain in accepted state too long.
    • Added automatic cancellation of pending requests when a model is uninstalled.
    • Improved container lifecycle management by removing stale "created" containers before retry attempts.

  • MSA Configuration:

    • Enabled configuration of ColabFold MSA servers in addition to Foldify servers.
    • Added default public ColabFold MSA server configuration for evaluation purposes.
    • Improved MSA configuration validation to prevent editing of preconfigured system servers.
    • Improved wording and user guidance around MSA options in the inference form.

  • Infrastructure and Logs:

    • Increased database connection pool size and timeout values to handle concurrent write operations better.
    • Enhanced archive endpoint to include input assets alongside job outputs for complete result packages.
    • Improved error message formatting and capitalization for better readability.

  • User Interface - Generic:

    • Redesigned previous inputs modal to handle large numbers of attachments gracefully.
    • Improved tag display in results view with better overflow handling.
    • Prevented premature result loading when jobs are still running to avoid "file not found" errors.
    • Fixed action button behavior to prevent closing settings panels unexpectedly.
    • Updated asset upload interface with clearer wording and improved MSA-specific guidance.

  • Model Wrapper:

    • Enabled by-file MSA support for OpenFold3, allowing users to upload pre-generated MSA files.
    • Added query generation and validation API endpoint for structure file processing.
    • Standardized pLDDT values to 0-100 range across all models for consistency.

Apheris Hub 0.3.1πŸ”—

  • Release date: 2025-09-12

ApherisFold Application: 0.11.1πŸ”—

  • Boltz-2
    • boltz2:0.11.1
    • boltz2:0.11.1-public-colabfold
  • Mock Model
    • mock:0.11.1
    • mock:0.11.1-public-colabfold
  • OpenFold3
    • openfold3:0.11.1-public-colabfold

HighlightsπŸ”—

The Apheris Hub 0.3.1 release introduces significant enhancements to the Apheris Hub with focus on protein structure analysis and user experience improvements.

New FeaturesπŸ”—

  • MSA Server Configuration: Users can now use different Multiple Sequence Alignment (MSA) servers for structure prediction.

MSA Server Options:

  • Pre-Generated MSA: The base models assume the user will upload pre-generated MSA files; this is the most local option, making no calls outside the Hub to any MSA server.
  • Apheris-hosted Foldify: The base model now supports using a Foldify server, and for a limited time, comes pre-configured with an Apheris-hosted option for free, intended only for evaluation use. This server should be treated as a public MSA server, and users should take the same precautions when using it as they would, for example, the public ColabFold Server.
  • Self-hosted Foldify: You can also configure the Hub to use your own internally hosted Foldify server; adding ColabFold servers is coming soon. Please contact Apheris for support in setting up your own Foldify server via support@apheris.com.
  • Public ColabFold: Until support is available for configuring access to ColabFold servers, there is a public-colab-fold model option that generates MSAs via the public ColabFold server, which is not hosted by Apheris.
  • Real-time Model Installation Feedback: Added progress indicators for model installation, showing percentage completion and status updates in real-time. If installation issues occur, error messages are displayed with troubleshooting information available in model settings.
  • Structure Visualization with Mol: Migrated to Mol for rendering 3D molecules, delivering enhanced visualization and interaction capabilities.

EnhancementsπŸ”—

  • Improved 3D Molecule Visualization:

    • Adopted Mol* for rendering 3D molecules, providing better visualization capabilities and performance.
    • Enhanced molecule coloring and added Chemical Component Dictionary (CCD) code lookups for improved annotation.
    • Removed background from molecule viewer and added hover information for better visualization.
    • Added legend and units for matrix view to improve data interpretation.

  • User Interface Improvements:

    • Added unique naming for downloaded results to prevent filename conflicts and improve organization.
    • Redesigned the job form for a more intuitive user experience.
    • Added job ID display in result list for easier tracking.
    • Enhanced offline connection status indication for better user feedback when connectivity is lost.
    • Duration formatting improved to show minutes and seconds instead of just seconds.
    • Updated model naming conventions to clearly reflect MSA server options. Models now indicate whether they use the public ColabFold server, providing transparency about external dependencies.

  • Inference Runs / Results Improvements:

    • Enhanced sequence selection highlighting for precise amino acid selection.
    • Added catching of MMSeqs2 MSA server errors from Boltz-2 model.

Bug FixesπŸ”—

  • UI and Configuration

    • Improved error formatting for MSA linting.
    • Updated schema validation to properly handle MSA field requirements.

  • Inference Runs / Results Improvements:

    • Clarified error messages for mock model inference results when non-default inputs are used.
    • Fixed OpenFold3 pLDDT vectors for improved accuracy.

Apheris Hub 0.2.1πŸ”—

  • Release date: 2025-08-22

ApherisFold Application: 0.10.1πŸ”—

  • Boltz-2
    • boltz2:0.10.1-private-msa
    • boltz2:0.10.1-public-msa
  • Mock Model
    • mock:0.10.1-private-msa
    • mock:0.10.1-public-msa
  • OpenFold3
    • openfold3:0.10.1-public-msa

HighlightsπŸ”—

  • Enhancements
    • Detection of API connection loss on the UI
  • Bug Fixes
    • Labels are now shown on the PAE/PDE Plot
    • ColabFold server unavailability error messages are clearer when using Boltz-2

Apheris Hub 0.2.0πŸ”—

  • Release date: 2025-08-08

ApherisFold Application: 0.9.0πŸ”—

  • Boltz-2
    • boltz2:0.9.0-private-msa
    • boltz2:0.9.0-public-msa
  • Mock Model
    • mock:0.9.0-private-msa
    • mock:0.9.0-public-msa
  • OpenFold3
    • openfold3:0.9.0-public-msa

HighlightsπŸ”—

The Apheris Hub provides local access to AI-based drug discovery applications. Applications deployed in the Apheris Hub are designed to run entirely locally or in your private cloud or on-prem environments - such that no data ever leaves your environment. They integrate into enterprise R&D stacks and extend rather than replace existing scientific workflows.

Applications in the Apheris Hub focus on a set of drug discovery tasks and are based on one or more foundation models.

Our first application is focused on Co-Folding, starting with inference - including input validation, and batch execution either programmatically via an API or manually with a scientist-friendly GUI.

The Apheris Co‑Folding Application is a secure, locally hosted tool for using co‑folding models on sensitive proprietary data. By running Boltz-2 and OpenFold3 on in‑house targets, researchers can assess model accuracy in their specific domain and easily integrate these models into their wider workflows. The product provides visualization tools, streamlined data preparation support, and generates auditable, reproducible records for use in regulated environments.

Upcoming ImprovementsπŸ”—

Our first release is designed to support early evaluation and adoption of OpenFold3, and we are already making many improvements for follow-up releases. We are investing in more powerful visualizations, more models, job management, and supporting fine-tuning locally and via secure federation.

We plan to release additional support for data preparation, benchmarking, and fine-tuning in our early pipeline. We can already support integrating these models into your existing benchmarking pipelines, but we'd like to add more to ensure the biggest impact on your benchmarking efforts. We'd love to hear any feedback you have around this as well. Please feel free to reach out with feature requests, comments, or suggestions at support@apheris.com.

In future versions, we will allow pointing to an existing private MSA server for OpenFold3. However, today Apheris can also help you set up a private MSA server if you wish. In that case, please contact us at support@apheris.com.

For the first release, submitting additional jobs will put those jobs in a queue. The GPU is fully consumed per job; parallelism and multi-GPU support will come with follow-up releases. The current architecture was built for simplicity in deployment and configuration with more flexibility and scalability coming very soon.