Machine learning for biologics: opportunities for protein engineering, developability, and formulation

H Narayanan, F Dingfelder, A Butté, N Lorenzen… - Trends in …, 2021 - cell.com
Successful biologics must satisfy multiple properties including activity and particular
physicochemical features that are globally defined as developability. These multiple …

Antibody display technologies: selecting the cream of the crop

B Valldorf, SC Hinz, G Russo, L Pekar, L Mohr… - Biological …, 2022 - degruyter.com
Antibody display technologies enable the successful isolation of antigen-specific antibodies
with therapeutic potential. The key feature that facilitates the selection of an antibody with …

Logomaker: beautiful sequence logos in Python

A Tareen, JB Kinney - Bioinformatics, 2020 - academic.oup.com
Sequence logos are visually compelling ways of illustrating the biological properties of DNA,
RNA and protein sequences, yet it is currently difficult to generate and customize such logos …

Antibody design using LSTM based deep generative model from phage display library for affinity maturation

K Saka, T Kakuzaki, S Metsugi, D Kashiwagi… - Scientific reports, 2021 - nature.com
Molecular evolution is an important step in the development of therapeutic antibodies.
However, the current method of affinity maturation is overly costly and labor-intensive …

Deep dive into machine learning models for protein engineering

Y Xu, D Verma, RP Sheridan, A Liaw, J Ma… - Journal of chemical …, 2020 - ACS Publications
Protein redesign and engineering has become an important task in pharmaceutical research
and development. Recent advances in technology have enabled efficient protein redesign …

A compact vocabulary of paratope-epitope interactions enables predictability of antibody-antigen binding

R Akbar, PA Robert, M Pavlović, JR Jeliazkov… - Cell Reports, 2021 - cell.com
Antibody-antigen binding relies on the specific interaction of amino acids at the paratope-
epitope interface. The predictability of antibody-antigen binding is a prerequisite for de novo …

Current advances in biopharmaceutical informatics: guidelines, impact and challenges in the computational developability assessment of antibody therapeutics

R Khetan, R Curtis, CM Deane, JT Hadsund, U Kar… - MAbs, 2022 - Taylor & Francis
Therapeutic monoclonal antibodies and their derivatives are key components of clinical
pipelines in the global biopharmaceutical industry. The availability of large datasets of …

The immuneML ecosystem for machine learning analysis of adaptive immune receptor repertoires

M Pavlović, L Scheffer, K Motwani, C Kanduri… - Nature Machine …, 2021 - nature.com
Adaptive immune receptor repertoires (AIRR) are key targets for biomedical research as
they record past and ongoing adaptive immune responses. The capacity of machine …

High-throughput screening, next generation sequencing and machine learning: advanced methods in enzyme engineering

R Vanella, G Kovacevic, V Doffini… - Chemical …, 2022 - pubs.rsc.org
Enzyme engineering is an important biotechnological process capable of generating
tailored biocatalysts for applications in industrial chemical conversion and biopharma …

Directed evolution of aptamer discovery technologies

D Wu, CKL Gordon, JH Shin… - Accounts of Chemical …, 2022 - ACS Publications
Conspectus Although antibodies are a powerful tool for molecular biology and clinical
diagnostics, there are many emerging applications for which nucleic acid-based aptamers …