Streamlining Antibody Discovery with Data & Machine Learning Solutions

Trusted us
Hero Section Image
Key features
Comprehensive antibody databaseA curated and comprehensive database that integrates antibody data points from all major sources.
Predicition of developability issues with sequencesEmploy sequence and structure-based biophysical descriptors that are correlated with acceptable properities.
Language model based mutational suggestionsPlatform multiple predictors allow to identify mutations that could be beneficial.
Hit picking with multiple clustering methodsUsing multiple clustering methods, you can increase the diversity across orthogonal dimensions.
Data StorageStore your data, analysis results and database search results in one place.
Security above allWe implement the highest security standards to ensure that your data is always safe.
Structural modelingPlatform allows therapeutic antibody lead optimization in the structural context by displaying and edit them as 3D model.
Data supported humanizationContrast your sequence to the closest germline and perform resurfacing using a structural model.
Paratope predictionBased on Deep Learning models Platform predicts paratope directly from sequence.
Antibody - Antigen dockingAnalysis and prediction of antibody poses towards the antigen along with indication of residue in contact.
Visualization of your assay dataMany different visualizations supporting the analyzed data.
Support for library constructionGiven a template binder, explore its positional diversity from NGS and potential paratope hotspots to focus library diversity construction.
Accelerate Your Research Image

Accelerate your research decision-making

Platform modules
Antibody Database

Save time in creating and collating antibody-specific datasets. Benefit from ready-made data collection pipelines that have fresh and regularly updated datasets. Search for antibodies by sequence, text, or sequence, and get all the search results in one place. Compare parameters and find shared attributes across different databases.

Antibody database graph

Large database of immunoglobulin sequences for immunological and machine learning applications available outside the NA Platform.

Learn moreAccentArrowSvg

Numbers present all sequences (heavy and light chains)

Sequence Engineering

Accelerate your antibody engineering project and streamline your decision-making process. Characterize your antibodies using predictive tools covering a wide range of structural, sequence, and developability prediction applications. Our models verify sequences for whole molecules or for individual residues.

Immunogenicity

Immunogenicity

Annotate sequences with predictions of the anti-drug antibodies score from clinical trials datasets collected from all available therapeutics
Developability

Developability

Benchmark the antibody sequence and structural features indicating successful candidates that passed significant milestones in clinical trials
Liabilities

Liabilities

Annotate sequences that may have a negative impact on antibody structure or its other properties.
Language model based mutational suggestions
Changes history
Batch Sequence Annotation

Batch Sequence Annotation module uses four elements that can be used for filtering. These include three generalistic scores calculated directly by our platform 1) liabilities 2) biophysical descriptors and 3) immunogenicity. To account for associated prior experimental knowledge our platform also allows for 4) submission of prior assay/custom predictor values.

First zone of diagramSecond zone of diagramThird zone of diagramFourth zone of diagram

Initial set of sequences

User-supplied assay data

Biophysical assays as well as internal prediction scores associated with your sequences.

Immunogenicity

Predict the Anti Drug Antibody response for your submitted sequences.

Biophysical descriptors

Employ sequences and structure-based biophysical descriptors that are correlated with acceptable developability properties.

Liabilities

Remove sequences with a set of undesirable liabilities specific to your organization.

Sequences without
detectable issues

Hit picking with multiple clustering methods

  • Sequence clustering
  • Structure clustering
  • Paratope clustering
  • Embedding clustering
Prediction of developability issues with sequences
Multiple
Sequence
Annotation
Structure Modeling

Structure Modeling allows therapeutic antibody lead optimization in the structural context. By having structural predictions and machine-learning based annotation in one place, we facilitate making design decisions on your molecules, leveraging the structural context.

Antibody Docking

At NaturalAntibody, we developed algorithms that perform docking in antibody-specific fashion. Leveraging our docking solution, we offer visualizations that provide antibody-specific context. Using our docking solution, users can explore the predicted paratopes and epitopes that should facilitate analysis of the possible binding conformations.

Structure selection mode
User-defined paratopes and epitopes
Security IconSecured for confidential data

Knowing how important the information about the data processed on the platform is, we have made every effort to secure it