Exciting update! Our work on antibody developability is now published in @CommsBio. Take a look from https://t.co/ksrpFsn7Ep Also, feel free to take a sneaky peak on our Springer communications blog post if you fancy a brief summary of the study

The MGMS Adaptive Immune Receptor conference, two weeks ago in Oxford, highlighted the incredible advances that have been made in computational structure-based antibody design & development, but also the challenges remaining Some of my key takeaways 👇

New opening for a PhD student in my lab, co-supervised with @F_Lund_Johansen . This position is ERC-funded and focuses on novel experimental technologies for antibody-antigen binding screening 📷

🗞️A read-only pdf version of ou review on "Adaptive Immune Receptor Repertoire Analysis" is available here as per the editor: https://t.co/jo15ly1XWz Hope you enjoy the reading! @victorgreiff @vanessajmh @HabibBashour @KhangLeQuy @PBarennes @puneet021192

Absolutely thrilled to see our immune repertoire review out this week: fantastic collaboration with @mariottienca @vanessajmh @HabibBashour @KhangLeQuy @puneet021192!

New this week: Adaptive immune receptor repertoire (AIRR) analysis @mariottienca @UiO_LifeSci @UniOslo_MED @victorgreiff outline the approaches and challenges in AIRR analysis and present future developments toward predicting adaptive immune responses. https://t.co/iPE8wcuyfh

(1/7) Curious about what a blood sample can reveal about humoral immunity? Our latest work combined sequencing methods and mass spectrometry to explore BCR and antibody repertoires and assess their synergistic potential. https://t.co/kGQEgTm93q

(10/10) Our code and datasets will be fully available soon on GitHub and Zenodo. Feel free to check for updates: https://t.co/c6kL86R8Fm and

(9/10) We acknowledge the immense contributions and valuable advice of all our co-authors at the Greiff lab @victorgreiff , including Rahmad Akbar @mchernigovskaia @KhangLeQuy @ISnapkov and @puneet021192

(8/10) We thank @HelmsleyTrust @UniOslo @UiO_LifeSci @ireceptor_plus Norwegian Cancer Society @forskningsradet @stiftkgj for the generous funding and senior colleagues @jfgumarc @SandveGeir @AndersenJT and collaborators @adaptyvbio @naturalantibody

(7/10) Importantly, we evaluated the suitability of cutting-edge structure prediction tools for developability tasks and conducted molecular dynamics simulations to validate the accuracy of structural DP calculated on predicted data.

(6/10) Combining high-throughput antibody sequencing data with structural modeling revealed that the human-engineered antibodies were localized within the natural developability landscape, highlighting the relevance of natural antibodies in therapeutic mAbs design.

(5/10) We found that the native developability landscapes exhibited variations across species and antibody chain types. And, structure DPs were harder to predict than sequence DPs using non-exhaustive machine learning algorithms.

(4/10) For our study, we utilized a dataset comprising over two million natural and human-engineered antibodies, alongside their predicted structures and constructed a developability atlas encompassing 40 sequence and 46 structure computationally determined DPs.

(3/10) Our study explores the plasticity of DPs, including redundancy, sensitivity and predictability within the native antibody repertoire. We also investigate how human-engineered antibodies relate to the native developability landscape.

(2/10) Antibody developability reflects the feasibility for therapeutic development based on antibody sequence and structure physicochemical developability parameters (DPs). While challenging to optimize, the native antibody repertoire offers valuable developability insights.

(1/10) Our work on antibody developability is out! We present a cartography of the developability landscapes of the native and human-engineered antibodies. This study was a team effort of @HabibBashour @EvaSmorodina @pariset_matteo , and @Jahn_Zhong https://t.co/kIMBjziQAi

(1/8)🎉A fresh preprint in which we present LIgO — a powerful tool to simulate adaptive immune receptor (AIR) and repertoire (AIRR) data for the development and benchmarking of AIRR-based ML 🧵⬇️ https://t.co/0iif0WbUP2

Beyond excited to share the pre-print of the work I did during my time at the Cerutti lab at @HMar_research. Big thanks to co-first authors @HabibBashour and Martyna Filipska, who have made this possible with the guidance of Andrea Cerutti, @victorgreiff and @GMagri_Immuno!

New preprint from the ImmunoLingo convergence environment: “ImmunoLingo: Linguistics-based formalization of the antibody language”. We asked: how to define the language of antibody sequences for more efficient antibody therapeutics design? 1/7 https://t.co/KL1QJC6RSi