Macromolecular modeling and design in Rosetta: recent methods and frameworks

JK Leman, BD Weitzner, SM Lewis, J Adolf-Bryfogle… - Nature …, 2020 - nature.com
The Rosetta software for macromolecular modeling, docking and design is extensively used
in laboratories worldwide. During two decades of development by a community of …

Unraveling the role of linker design in proteolysis targeting chimeras: Miniperspective

TA Bemis, JJ La Clair, MD Burkart - Journal of Medicinal …, 2021 - ACS Publications
A current bottleneck in the development of proteolysis targeting chimeras (PROTACs) is the
empirical nature of linker length structure–activity relationships (SARs). A multidisciplinary …

Antibody structure prediction using interpretable deep learning

JA Ruffolo, J Sulam, JJ Gray - Patterns, 2022 - cell.com
Therapeutic antibodies make up a rapidly growing segment of the biologics market.
However, rational design of antibodies is hindered by reliance on experimental methods for …

Broadly neutralizing antibodies target a haemagglutinin anchor epitope

JJ Guthmiller, J Han, HA Utset, L Li, LYL Lan, C Henry… - Nature, 2022 - nature.com
Broadly neutralizing antibodies that target epitopes of haemagglutinin on the influenza virus
have the potential to provide near universal protection against influenza virus infection …

De novo generation of SARS-CoV-2 antibody CDRH3 with a pre-trained generative large language model

H He, B He, L Guan, Y Zhao, F Jiang, G Chen… - Nature …, 2024 - nature.com
Artificial Intelligence (AI) techniques have made great advances in assisting antibody
design. However, antibody design still heavily relies on isolating antigen-specific antibodies …

Nasal delivery of an IgM offers broad protection from SARS-CoV-2 variants

Z Ku, X **e, PR Hinton, X Liu, X Ye, AE Muruato… - Nature, 2021 - nature.com
Resistance represents a major challenge for antibody-based therapy for COVID-19,,–. Here
we engineered an immunoglobulin M (IgM) neutralizing antibody (IgM-14) to overcome the …

Progress and challenges for the machine learning-based design of fit-for-purpose monoclonal antibodies

R Akbar, H Bashour, P Rawat, PA Robert, E Smorodina… - MAbs, 2022 - Taylor & Francis
Although the therapeutic efficacy and commercial success of monoclonal antibodies (mAbs)
are tremendous, the design and discovery of new candidates remain a time and cost …

Computational approaches to therapeutic antibody design: established methods and emerging trends

RA Norman, F Ambrosetti, AMJJ Bonvin… - Briefings in …, 2020 - academic.oup.com
Antibodies are proteins that recognize the molecular surfaces of potentially noxious
molecules to mount an adaptive immune response or, in the case of autoimmune diseases …

Implications of antibody-dependent enhancement of infection for SARS-CoV-2 countermeasures

N Eroshenko, T Gill, MK Keaveney, GM Church… - Nature …, 2020 - nature.com
To the Editor—For certain diseases, patients who have been previously infected by one
strain of a virus and who are later infected by another strain can suffer outcomes that are …

Protein interaction interface region prediction by geometric deep learning

B Dai, C Bailey-Kellogg - Bioinformatics, 2021 - academic.oup.com
Motivation Protein–protein interactions drive wide-ranging molecular processes, and
characterizing at the atomic level how proteins interact (beyond just the fact that they …