Improved prediction of antibody VL-VH orientation.

By Nicholas A. Marze, Sergey Lyskov, Jeffrey J. Gray. 2016

57 citations recorded by the source corpus.

Subfields: Molecular Biology, Radiology, Nuclear Medicine and Imaging

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Molecular Biology

1. Jeffrey J. Gray
2. Brian D. Weitzner
3. Jens Meiler
4. Sergey Lyskov
5. Rhiju Das
6. Jared Adolf-Bryfogle
7. Jeffrey A. Ruffolo
8. David Baker

In Radiology, Nuclear Medicine and Imaging

1. Jeffrey J. Gray
2. Brian D. Weitzner
3. Jeffrey A. Ruffolo
4. Sai Pooja Mahajan
5. Lee-Shin Chu
6. Sergey Lyskov
7. Nicholas A. Marze
8. Daisuke Kuroda

Citations in the corpus

• Modeling and docking antibody structures with Rosetta (2017, background): “For each structural component considered ((light-chain framework (FR L ), heavy-chain framework (FR H ), CDRs L1–3, H1–3), templates are selected by maximum sequence and orientation 27 .”
• Web‐accessible molecular modeling with Rosetta: The Rosetta Online Server that Includes Everyone (ROSIE) (2018, background): “44,45 Due to the increased complexity, modeling the challenging HCDR3 loop is provided as a separate option.”
• Fast, accurate antibody structure prediction from deep learning on massive set of natural antibodies (2022, methodology): “The exception to this trend is ABlooper, which utilizes framework structures from ABodyBuilder and thus achieves a similar OCD value to the grafting-based method.”