API reference#

Property Regression Models#

Data#

Upload and store your datasets on our platform to use with your protein engineering tasks.

openprotein.data.DataAPI(session)

API interface for calling AssayData endpoints

openprotein.data.AssayDataset(session, metadata)

Assay dataset which contains your sequences and measurements which can be used for training predictors.

Jobs#

Retrieve and monitor your jobs.

openprotein.jobs.JobsAPI(session)

API interface to get jobs.

openprotein.jobs.Job(*, job_id, job_type, ...)

Align#

Align your protein sequences or look up multiple sequence alignments.

openprotein.align.AlignAPI(session)

Align API interface for creating alignments and MSAs (multiple sequence alignments) which can be used for other protein tasks.

openprotein.align.MSAFuture(session, job[, ...])

Represents a future for MSA (Multiple Sequence Alignment) results.

Prompt#

Create prompts using sequences and structures to condition our proprietary high-performance PoET foundation models.

openprotein.prompt.PromptAPI(session)

Prompt API providing the interface to create prompts for use with PoET models.

openprotein.prompt.Prompt(session[, job, ...])

Prompt which contains a set of sequences and/or structures used to condition the PoET models.

openprotein.prompt.Query(session, metadata)

Query containing a sequence/structure used to query the PoET-2 model which opens up new workflows.

Foundation models#

Use foundation models to produce embeddings and logits with your protein sequences.

openprotein.embeddings.EmbeddingsAPI(session)

Embeddings API providing the interface for creating embeddings using protein language models.

Models#

The foundation models on our platform are classed appropriately to identify the models and group their functionality.

openprotein.embeddings.PoET2Model(session, ...)

Class for OpenProtein's foundation model PoET 2.

openprotein.embeddings.PoETModel(session, ...)

Class for OpenProtein's foundation model PoET.

openprotein.embeddings.OpenProteinModel(...)

Proprietary protein embedding models served by OpenProtein.

openprotein.embeddings.ESMModel(session, ...)

Class providing inference endpoints for Facebook's ESM protein language models.

Results#

The models produce asynchronous results which are modeled as futures which can be awaited.

openprotein.embeddings.EmbeddingsResultFuture(...)

Future for manipulating results for embeddings-related requests.

openprotein.embeddings.EmbeddingsScoreFuture(...)

Future for manipulating results for embeddings score-related requests.

openprotein.embeddings.EmbeddingsGenerateFuture(...)

Future for manipulating results for embeddings generate-related requests.

Transform#

Transform and reduce your embeddings for use with visualization and training workflows.

SVD#

openprotein.svd.SVDAPI(session)

SVD API providing the interface for creating and using SVD models.

openprotein.svd.SVDModel(session[, job, ...])

SVD model that can be used to create reduced embeddings.

UMAP#

openprotein.umap.UMAPAPI(session)

UMAP API providing the interface to fit and run UMAP visualizations.

openprotein.umap.UMAPModel(session[, job, ...])

UMAP model that can be used to create projected embeddings.

Predictor#

Train predictors from your assay datasets and use them to make predictions on novel sequences.

openprotein.predictor.PredictorAPI(session)

Predictor API providing the interface to train and predict predictors.

openprotein.predictor.PredictorModel(session)

Class providing predict endpoint for fitted predictor models.

openprotein.predictor.PredictionResultFuture(...)

Prediction results represented as a future.

Design#

Design novel protein sequences based on your assay datasets and trained models, optimizing toward your design criteria.

openprotein.design.DesignAPI(session)

Design API providing the interface to design novel proteins based on your design criteria.

openprotein.design.DesignFuture(session[, ...])

A future object that will hold the results of the design job.

Fold#

Make structure predictions on your protein sequences.

openprotein.fold.FoldAPI(session)

Fold API provides a high level interface for making protein structure predictions.

openprotein.fold.Boltz2Model(session, model_id)

Class providing inference endpoints for Boltz-2 structure prediction model which jointly models complex structures and binding affinities.

openprotein.fold.Boltz1xModel(session, model_id)

Class providing inference endpoints for Boltz-1x open-source structure prediction model, which adds the use of inference potentials to improve performance.

openprotein.fold.Boltz1Model(session, model_id)

Class providing inference endpoints for Boltz-1 open-source structure prediction model.

openprotein.fold.AlphaFold2Model(session, ...)

Class providing inference endpoints for AlphaFold2 structure prediction models, based on the implementation by ColabFold.

openprotein.fold.ESMFoldModel(session, model_id)

Class providing inference endpoints for Facebook's ESMFold structure prediction models.

openprotein.fold.FoldResultFuture(session, job)

Fold results represented as a future.

openprotein.fold.FoldComplexResultFuture(...)

Future for manipulating results of a fold complex request.

Models#

Unified access to the models available on our platform.

openprotein.models.ModelsAPI(session)

API-like accessor that groups all available protein models.

openprotein.models.foundation.rfdiffusion.RFdiffusionModel(session)

RFdiffusion model for generating de novo protein structures.