The Antibody Society

the official website of the antibody society

The Adaptive Immune Receptor Repertoire Community of The Antibody Society

  • LOG IN
  • BECOME A MEMBER
  • About
    • Mission & Activities
    • Directors and Officers
    • The Antibody Society’s Committees
      • AIRR Community Committee
      • Communication & Membership Committee
      • Meetings Committee
    • Sponsors & Partners
  • Society meetings
    • Harnessing Cytokines for Cancer Immunotherapy Symposium
    • Biopharmaceutical Informatics Symposium
    • Emerging Cancer Therapies Leveraging Gamma-Delta Effector T cells Symposium
    • Emerging Immunotherapeutics for Ovarian Cancer Symposium
    • AIRR Community Meetings
    • Antibody Engineering & Therapeutics (US) 2023
      • 2022 Antibody Engineering & Therapeutics
      • 2020 Antibody Engineering & Therapeutics
      • 2019 Antibody Engineering & Therapeutics
      • 2018 Antibody Engineering & Therapeutics
      • What is INN a Name?
        • INN issue updates
    • Antibody Engineering & Therapeutics Europe 2023
    • FOCIS Symposia
  • AIRR Community
    • AIRR News
    • AIRR Publications
    • AIRR Meetings
      • AIRR Community Special Event 2023  – Zooming in to the Community II
      • AIRR Community Meeting VI: “Exploring New Frontiers”
      • AIRR Community Meeting V: “Zooming in to the AIRR Community”
      • AIRR Community Meeting V Pre-Meetings
        • AIRR-seq in the Pandemic
        • AIRR-seq Biological Standards and Workflows
      • AIRR Community Special Event: “Response to COVID-19”
      • AIRR Community Meeting IV: “Bridging the Gaps”
      • AIRR Community Meeting III
        • Day 1
        • Day 2
        • Day 3
        • Day 4
      • AIRR Community Meeting II
      • AIRR Community Meeting I
    • AIRR Community Working Groups
      • Biological Resources Working Group
      • Common Repository Working Group
      • Diagnostics Working Group
      • Germline Database Working Group
      • Legal and Ethics Working Group
      • Software Working Group
      • Standards Working Group
    • AIRR Community Sub-committees
      • Communications Sub-committee
      • Executive Sub-committee
      • Inferred Allele Review Committee
      • Meetings Sub-committee
    • AIRR Data Commons
    • AIRR Community Calendar
    • AIRR Community Webinar Series
    • On AIRR – An AIRR Community Podcast
    • AIRR Community Resources
    • AIRR Community Service Prize 2022
  • Members only
    • Login
    • Note to members
    • Member discount codes
    • 2023 Calendar of Events
    • James S. Huston Antibody Science Talent Award
      • 2021 James S. Huston Antibody Science Talent Award Recipient
      • 2020 James S. Huston Antibody Science Talent Award Recipient
      • JSH Award Criteria
    • Science Writing Competition
      • Science Writing Competition Winners
    • Imaging Competition
    • Research Competitions
      • Research Competition Winners
    • Antibodies in early-stage studies
    • Presentations
  • Upcoming meetings
  • Web Resources
    • Society Publications
    • Antibody News
    • Antibody therapeutics approved or in regulatory review in the EU or US
      • Antibody therapeutics product data
    • Antibodies in late-stage clinical studies
    • Research Resources
    • Education Resources
  • Career Center
    • Career Shorts
  • Learning Center
    • Upcoming Webinars
    • Snakebite antivenoms: Global challenges and progress toward recombinant antibody therapeutics
    • Adaptive Immune Receptor Repertoires
    • Antibody Discovery & Development
    • Commercializing Antibody Therapeutics
    • Antibodies to Watch
    • Antibody Validation
  • COVID-19
    • Guide to “Coronavirus in the Crosshairs”
    • COVID-19 Biologics Tracker
    • Meeting Report: The Diagnostic Landscape for COVID-19
You are here: Home / Archives for bioinformatics

TRUST4 is now certified as AIRR-compliant

March 1, 2023 by Edel Aron

The AIRR Community is excited to announce that TRUST4 has been certified as compliant with the AIRR-C v1.0 standard for AIRR-Seq software tools. TRUST4 (Tcr Receptor Utilities for Solid Tissue 4) is a tool for assembling BCRs and TCRs from bulk and single-cell RNA-Seq data.

In an effort to enable rigorous and reproducible immune repertoire research at the largest scale possible, the AIRR-C Software Working Group has established a standard to validate software tools using the AIRR-C Standards and meeting a series of interoperability and quality criteria. Developers interested in certifying their tools should complete the checklist and submit it to the AIRR-C Software Working Group for evaluation and ratification by its members.

More details can be found at the website AIRR Software WG – Guidance for AIRR Software Tools.

All compliant tools will be issued a badge and listed on the website AIRR Software WG – List of Tools Certified as Compliant. The list currently includes SONAR, ImmuneDB, Scirpy, Immcantation, CompAIRR, ImmuneML and Dandelion in addition to TRUST4.

Filed Under: AIRR Community Tagged With: Adaptive Immune Receptor Repertoire Community, bioinformatics, Data Standards, diagnostics

Application of Machine Learning and Informatics in Antibody and Protein Research

March 10, 2022 by The Antibody Society

Antibody Engineering & Therapeutics, held in December 2021, offered many opportunities to hear exciting and informative presentations by experts in the field. We are pleased to present here a summary of a plenary lecture by Prof. Charlotte Deane (University of Oxford), kindly written by Dr. Czeslaw Radziejewski.

Application of Machine Learning and Informatics in Antibody and Protein Research
Charlotte Deane, Professor of Structural Bioinformatics, Department of Statistics, University of Oxford

Machine learning relies heavily on the availability of large databases. Three databases for antibody research were developed in Prof. Dean’s lab: OAS (Observed Antibody Space),[1] SAbDab (Structural Antibody Database),[2] and Thera-SAbDab (database of immunotherapeutic variable domain sequences). OAS contains about 2 billion redundant antibody sequences across diverse immune states, organisms, and individuals. SAbDab is a fully automated self-updating collection of publicly available antibody structure data. It contains 5650 structures, but about 1000 truly non-redundant structures, 4213 antigen-antibody complexes and 890 structures of nanobodies. Thera-SabDob contains 696 structures as of October 2021. In addition, the lab has a CoV-AbDab database that contains sequences and structures for coronavirus antibodies for SARS-CoV-2, SARS-CoV-1 and MERS-CoV. This database contains about 5000 data points. The lab developed the SAbPred suite of tools for antibody prediction, comprising AntibodyBuilder, SPHINX, SCALOP, PEARS, ANARCI, ABangle, Hu-mAb SAAB+,TAP, Epitope Profiling SPACE and Ab-Ligaty. SCALOP, ABodybuilder, SPHINX are designed for building antibody models. ABlooper tool builds complementary-determining region (CDR) structures. ABangle is a tool for calculating and analyzing the VH-VL orientation in antibodies. TAP (Therapeutic Antibody Profiler) considers the drug-like properties of therapeutic antibodies.[3] It evaluates variable domains in antibody of interest using five developability criteria derived from post clinical Phase 1 antibody therapeutics. Epitope Profiling-SPACE and Paratyping Ab-Ligity can used to determine if two antibodies with divergent sequences can bind to the same epitope.[4] ANARCI is a tool for annotating antibody sequences and Hu-Mab is a computational tool for antibody humanization. Dlab is a deep learning method for virtual screening of antibody sequences that can bind specific antigens.

Professor Deane provided examples of using some of her computational tools. Antibody humanization is currently inefficient, as it is carried out experimentally in a largely trial and error process. Applying machine learning to an edited OAS database (with redundancies removed) led to classifiers that could distinguish between human and non-human antibody variable domain sequences. These classifiers were used to create the computational humanization tool Hu-mAb. Available sequences of therapeutic antibodies from different stages of development were subjected to Hu-mAb analysis. The high Hu-mAb scores correlated with low observed immunogenicity of an antibody and low scores correlated with higher observed immunogenicity. Twenty-five experimentally humanized antibody sequences for which rodent or rabbit precursor sequences were available were assessed by Hu-mAb. Most of the mutations that Hu-mAb generated were either the same or chemically similar for VH (77% and 85%, respectively) and for VL (59% and 58%, respectively). Hu-mAb suggested overall fewer mutations and fewer mutations to VH-VL interface than the experimental approach, therefore such humanized antibodies would more likely have preserved structure and function.

The Therapeutic Antibody Profiler evaluates properties thought to determine antibody developability, including CDRH3 or total CDR length; patches of surface hydrophobicity across CDR vicinity; patches of positive charges and negative charges across CDR vicinity; and structural Fv charge symmetry. These properties are related to aggregation, viscosity, poor expression and polyspecificity of antibody molecules.[5] TAP was applied in a study that used 137 post Phase 1 therapeutic models,14000 representative Human Antibody Models and 2 datasets of MedImmune Developability Failures. The study revealed that therapeutic antibodies tend to have shorter CDRH3 and smaller hydrophobic patches than natural ones. However, positive and negative patches of natural and therapeutic antibodies have similar profiles and Fv charge symmetry is also very similar. Both therapeutic and natural antibodies have an aversion to strongly oppositely charged VH and VL chains.

ABlooper [6] uses similar architecture as AlphaFold. It predicts structures of all six CDR loops and estimates the accuracy of prediction. The root-mean-square deviation from AlphaFold2 for CDRH3 prediction (2.87A) were comparable with ABlooper (2.49 A). Unlike AlphaFold2, ABlooper generates a series of predicted structures from which a prediction of accuracy can be estimated. If the predicted structures are widely divergent, then the quality of prediction is low. ABlooper is also much faster than other deep learning methods such as AlphaFold (100 structures predicted in 5 second vs one structure in 20 min). All tools are available freely for academic institutions.

  1. Olsen TH, Boyles F, Deane CM. Observed Antibody Space: A diverse database of cleaned, annotated, and translated unpaired and paired antibody sequences. Protein Sci. 2022 Jan;31(1):141-146. doi: 10.1002/pro.4205.
  2. Schneider C, Raybould MIJ, Deane CM. SAbDab in the age of biotherapeutics: updates including SAbDab-nano, the nanobody structure tracker. Nucleic Acids Res. 2022 Jan 7;50(D1):D1368-D1372. doi: 10.1093/nar/gkab1050.
  3. Raybould MIJ, Deane CM. The Therapeutic Antibody Profiler for Computational Developability Assessment. Methods Mol Biol. 2022;2313:115-125. doi: 10.1007/978-1-0716-1450-1_5.
  4. Wong et al. Ab-Ligity: identifying sequence-dissimilar antibodies that bind to the same epitope. MAbs 2021. DOI: 10.1080/19420862.2021.1873478.
  5. Khetan et al. Current advances in biopharmaceutical informatics: guidelines, impact and challenges in the computational developability assessment of antibody therapeutics. MAbs 2022. DOI: 10.1080/19420862.2021.2020082.
  6. Abanades B, Georges G, Bujotzek A, Deane CM. ABlooper: Fast accurate antibody CDR loop structure prediction with accuracy estimation. Bioinformatics. 2022 Jan 31:btac016. doi: 10.1093/bioinformatics/btac016.

Filed Under: Bioinformatics Tagged With: bioinformatics, machine learning

Learn about Modeling Biologic Molecules on January 27th!

January 12, 2022 by Janice Reichert

Registration is open for our next webinar, “Modeling Biologic Molecules“, to be held Thursday January 27, 2022, 11am ET / 5pm CET.

The speakers are Dr. Monica Fernández-Quintero and Prof. Klaus R. Liedl.

Modeling in Chemistry obviously depends on a strong link to reality. Even though the mathematical description of chemistry has been possible for almost 100 years, realistic modelling has only recently become available due to the recent massive increase of computing power following Moore’s law. Still, appropriate statistics, initial conditions and boundaries pose considerable challenges. Nowadays, methodological advances and progress in hardware allows the observation of biological systems for relevant time periods. Hence, dynamic processes like reorientations, folding and binding can be seen in atomistic resolution leading to completely new insights.

Describing an antibody’s binding site using only one single static structure limits the understanding and characterization of the antibody’s function and properties, whereas various biophysical properties are governed by its dynamics, e.g., antibody-antigen binding. This limitation is even more pronounced when no experimentally determined structure is available or the crystal structure is distorted by packing effects, which can result in misleading antibody paratope structures. To improve antibody structure prediction and to take the strongly correlated CDR loop and interface movements into account, antibody paratopes should be described as interconverting states in solution with varying probabilities. These kinetically characterized paratope ensembles with their respective state probabilities allow the identification of the dominant conformation in solution, which frequently has been shown to coincide with the binding competent conformation. Therefore, the definition of kinetically and functionally relevant states, so-called paratope states, can be successfully used to improve the accuracy and enhance the predictivity of antibody-antigen docking.

Register for this webinar here!

Filed Under: Antibody discovery, Antibody therapeutic, Bioinformatics Tagged With: antibody discovery, antibody therapeutics, bioinformatics

Three newly certified AIRR-compliant software tools: ImmuneML, CompAIRR and Dandelion

December 9, 2021 by Pam Borghardt

The AIRR Community is excited to announce that three tools have recently been certified as compliant with the AIRR-C v1.0 standard for AIRR-Seq software tools. These are ImmuneML – an ecosystem for machine learning analysis of adaptive immune receptor repertoires, CompAIRR – a tool for ultra-fast comparison of adaptive immune receptor repertoires by exact and approximate sequence matching, and Dandelion – a tool for analyzing single cell BCR/V(D)J 10x Genomics data. 

In an effort to enable rigorous and reproducible immune repertoire research at the largest scale possible, the AIRR-C Software Working Group has established a standard to validate software tools using the AIRR-C Standards and meeting a series of interoperability and quality criteria. Developers interested in certifying their tools should complete the checklist and submit it to the AIRR-C Software Working Group for evaluation and ratification by its members.

More details can be found at the website AIRR Software WG – Guidance for AIRR Software Tools.

All compliant tools will be issued a badge and listed on the website AIRR Software WG – List of Tools Certified as Compliant. The list includes SONAR, ImmuneDB, Immcantation, ImmuneML, CompAIRR and Dandelion.

Filed Under: AIRR Community Tagged With: Adaptive Immune Receptor Repertoire Community, bioinformatics, Data Standards, diagnostics

Call for Papers on Biopharmaceutical Informatics

January 19, 2021 by Janice Reichert

As evident from papers published in mAbs in recent years, computation is being increasingly used in the discovery and development of antibody-based biologic drugs. To celebrate the rise of biopharmaceutical informatics directed towards antibody R & D, we invite The Antibody Society members, mAbs readers and the broader scientific community to contribute review articles focused on highlighting how computation has enabled their investigations or led them to new ones. The reviews should narrate the state of the art and speculate on new vistas for computational applications in the field.

We are particularly interested in reviews in the following topics:

  • Analyses of immune repertoires and their role in target validation and drug discovery.
  • Analyses of antibody structure-function relationships with emphasis on therapeutic antibody-based biologics.
  • Structure-based design of antibody fragments (e.g., nanobodies) and antibody-based multi-specific molecular formats.
  • Design of antibody libraries for different display strategies and/or with improved developability.
  • Structure-based affinity maturation and optimization of biologic lead candidates.
  • Molecular simulations of antibodies to understand their solution behaviors, such as aggregation, viscosity and physicochemical degradation.
  • Consideration of developability in biologic drug discovery and design.
  • Developability assessments at early-stage development.
  • Specific and non-specific interactions formed by antibodies in vitro and in vivo.
  • Computation in antibody formulations – design of novel excipients.
  • Applications of artificial Intelligence and machine learning towards antibody discovery, development and manufacturing.
  • Progress and challenges in modeling antibodies and multi-specific formats.
  • Predicting chemical degradation in antibody-based biologic drugs.
  • Optimizing antigens for greater immunization success.

Although these topics are especially of interest, we welcome well-written reviews in related areas as well.

Publication charges will be waived for six of the best review articles selected from pre-submission inquiries, which should consist of the title, abstract and general outline of the intended review article.

The deadline for the pre-submission enquiries is February 15, 2021, and the deadline for submission of the completed review articles is June 30, 2021.

Please send pre-submission inquiries to Assistant Editor Dr. Sandeep Kumar (skumarmabs@gmail.com) and Editor-in-Chief Dr. Janice Reichert (reichert.biotechconsulting@gmail.com), and contact us if you have any questions.

Filed Under: Antibody discovery Tagged With: antibody discovery, antibody therapeutics, bioinformatics

Next Page »

mabs

mabs

The Official Journal of The Antibody Society

Career Center

Our Career Center is a premier resource to connect highly qualified talent with matching career opportunities. Visit for details on over 800 jobs!

AIRR Community

AIRR Community

The Adaptive Immune Receptor Repertoire Community is a research-driven group organizing around the use of high-throughput sequencing technologies to study antibody/B-cell and T-cell receptor repertoires.

Recent Posts

  • FDA approves Zynyz™ (retifanlimab-dlwr) for Merkel cell carcinoma March 23, 2023
  • Ultralong CDR H3-based knobs: the smallest antibody fragment March 6, 2023
  • TRUST4 is now certified as AIRR-compliant March 1, 2023

Archives

Follow us online

  • Email
  • LinkedIn
  • Twitter
  • YouTube
  • Home
  • Privacy & Terms of Use
  • About
  • Directors and Officers
  • Advisors
  • Sponsors & Partners
  • Mission & Activities
  • Join the Society
  • Membership Levels
  • Members only
  • Login
  • Antibody therapeutics approved or in regulatory review in the EU or US
  • Meeting reports
  • Presentations
  • Contact

©2015 - scicomvisuals