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arXiv Open Access 2025

Applying computational protein design to therapeutic antibody discovery -- current state and perspectives

Weronika Bielska Igor Jaszczyszyn Pawel Dudzic Bartosz Janusz Dawid Chomicz +5 lainnya
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Abstrak

Machine learning applications in protein sciences have ushered in a new era for designing molecules in silico. Antibodies, which currently form the largest group of biologics in clinical use, stand to benefit greatly from this shift. Despite the proliferation of these protein design tools, their direct application to antibodies is often limited by the unique structural biology of these molecules. Here, we review the current computational methods for antibody design, highlighting their role in advancing computational drug discovery.

Topik & Kata Kunci

q-bio.BM

Penulis (10)

W

Weronika Bielska

I

Igor Jaszczyszyn

P

Pawel Dudzic

B

Bartosz Janusz

D

Dawid Chomicz

S

Sonia Wrobel

V

Victor Greiff

R

Ryan Feehan

J

Jared Adolf-Bryfogle

K

Konrad Krawczyk

Format Sitasi

APA MLA BibTeX
Bielska, W., Jaszczyszyn, I., Dudzic, P., Janusz, B., Chomicz, D., Wrobel, S. et al. (2025). Applying computational protein design to therapeutic antibody discovery -- current state and perspectives. https://arxiv.org/abs/2503.00913

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Informasi Jurnal
Tahun Terbit
2025
Bahasa
en
Sumber Database
arXiv
Akses
Open Access ✓