Computational and artificial intelligence-based methods for antibody development

J Kim, M McFee, Q Fang, O Abdin, PM Kim - Trends in pharmacological …, 2023 - cell.com
Due to their high target specificity and binding affinity, therapeutic antibodies are currently
the largest class of biotherapeutics. The traditional largely empirical antibody development …

Antibody structure and function: the basis for engineering therapeutics

ML Chiu, DR Goulet, A Teplyakov, GL Gilliland - Antibodies, 2019 - mdpi.com
Antibodies and antibody-derived macromolecules have established themselves as the
mainstay in protein-based therapeutic molecules (biologics). Our knowledge of the structure …

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 …

Coarse-grained protein models and their applications

S Kmiecik, D Gront, M Kolinski, L Wieteska… - Chemical …, 2016 - ACS Publications
The traditional computational modeling of protein structure, dynamics, and interactions
remains difficult for many protein systems. It is mostly due to the size of protein …

The immune epitope database and analysis resource in epitope discovery and synthetic vaccine design

W Fleri, S Paul, SK Dhanda, S Mahajan, X Xu… - Frontiers in …, 2017 - frontiersin.org
The task of epitope discovery and vaccine design is increasingly reliant on bioinformatics
analytic tools and access to depositories of curated data relevant to immune reactions and …

Computational optimization of antibody humanness and stability by systematic energy-based ranking

A Tennenhouse, L Khmelnitsky, R Khalaila… - Nature biomedical …, 2024 - nature.com
Conventional methods for humanizing animal-derived antibodies involve grafting their
complementarity-determining regions onto homologous human framework regions …

Machine-designed biotherapeutics: opportunities, feasibility and advantages of deep learning in computational antibody discovery

W Wilman, S Wróbel, W Bielska… - Briefings in …, 2022 - academic.oup.com
Antibodies are versatile molecular binders with an established and growing role as
therapeutics. Computational approaches to developing and designing these molecules are …

Serverification of molecular modeling applications: the Rosetta Online Server that Includes Everyone (ROSIE)

S Lyskov, FC Chou, SO Conchuir, BS Der, K Drew… - PloS one, 2013 - journals.plos.org
The Rosetta molecular modeling software package provides experimentally tested and
rapidly evolving tools for the 3D structure prediction and high-resolution design of proteins …

NanoNet: Rapid and accurate end-to-end nanobody modeling by deep learning

T Cohen, M Halfon… - Frontiers in …, 2022 - frontiersin.org
Antibodies are a rapidly growing class of therapeutics. Recently, single domain camelid
VHH antibodies, and their recognition nanobody domain (Nb) appeared as a cost-effective …

RosettaAntibodyDesign (RAbD): A general framework for computational antibody design

J Adolf-Bryfogle, O Kalyuzhniy, M Kubitz… - PLoS computational …, 2018 - journals.plos.org
A structural-bioinformatics-based computational methodology and framework have been
developed for the design of antibodies to targets of interest. RosettaAntibodyDesign (RAbD) …