Author

Cailen M. McCloskey

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Synthetic Biology· 2 Bioinformatics· 1 Molecular Biology· 1

Signature Assays, Organisms & Methods

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Approach:deep learning· 4 Research Focus:drug response / drug discovery· 3 Assay:proteomics· 2 Organism:human· 1 Research Focus:protein design· 1 Assay:protein sequence· 1 Assay:protein structure· 1

Frequent Co-Authors

John M. SuttoniD· 4 shared Shaheed A. AbdulhaqqiD· 4 shared Amir Shanehsazzadeh· 3 shared Breanna K. Luton· 3 shared Chelsea Chung· 3 shared Christa Kohnert· 3 shared George W. Kasun· 3 shared Hayley Carter· 3 shared

Activity by Year

2022-2026 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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4 shared papersSynthetic Biology

John M. SuttonORCID

Mutual co-authors in cluster

Author profile →

4 papers

Recent·Most cited

Origin-1: a generative AI platform for de novo antibody design against novel epitopes

Simon Levine, Jonathan Edward King, Jacob Stern, David Grayson, Raymond Wang, Rui Yin, Umberto Lupo, Paulina Kulytė, Ryan M. Brand, Tristan Bertin, Robert Pfingsten, Jovan Cejovic, Chelsea Chung, Breanna K. Luton, Andrew Hagemann, , Amir Shanehsazzadeh

Origin-1 generates high-confidence, specific antibodies against zero-prior epitopes through generative AI, validated with biophysical assays and cryo-EM.

bioRxiv · May 5, 2026 · PreprintMolecular Biology

IgDesign: In vitro validated antibody design against multiple therapeutic antigens using inverse folding

Amir Shanehsazzadeh, Julian Alverio, George W. Kasun, Simon Levine, Ido Calman, Jibran Ahmad Khan, Chelsea Chung, Nicolas Diaz, Breanna K. Luton, Ysis Tarter, Cailen M. McCloskey, Katherine B. Bateman, Hayley Carter, Dalton Chapman, Rebecca Consbruck, , Sharrol T. Bachas

IgDesign designs antibody CDRs using deep learning and validates them in vitro, showing high success rates and improved affinities for multiple therapeutic antigens.

bioRxiv · Dec 8, 2023 · PreprintSynthetic Biology

Unlocking de novo antibody design with generative artificial intelligence

Amir Shanehsazzadeh, Matt McPartlon, George W. Kasun, Andrea K. Steiger, John M. Sutton, Edriss Yassine, Cailen M. McCloskey, Robel Gemechu Haile, Richard W. Shuai, Julian Alverio, Goran Rakočević, Simon Levine, Jovan Cejovic, Jahir M. Gutierrez, Alex Morehead, , Sharrol T. Bachas

Deep generative models combined with high-throughput screening design de novo anti-HER2 antibodies without further optimization, yielding nanomolar binders functionally comparable or superior to trastuzumab.

bioRxiv · Jan 8, 2023 · PreprintSynthetic Biology

Antibody optimization enabled by artificial intelligence predictions of binding affinity and naturalness

Sharrol T. Bachas, Goran Rakocevic, David Spencer, Anand V. Sastry, Robel Gemechu Haile, John M. Sutton, George W. Kasun, Andrew L. Stachyra, Jahir M. Gutierrez, Edriss Yassine, Borka Medjo, Vincent Blay, Christa Kohnert, Jennifer T. Stanton, Alexander Brown, , Roberto Spreafico

Language models trained on high-throughput affinity data predict KD of unseen antibody variants across three orders of magnitude, and a "naturalness" score can be optimised alongside affinity.

bioRxiv · Aug 16, 2022 · PreprintBioinformatics