Opportunities and challenges for machine learning-assisted enzyme engineering

J Yang, FZ Li, FH Arnold - ACS Central Science, 2024 - ACS Publications
Enzymes can be engineered at the level of their amino acid sequences to optimize key
properties such as expression, stability, substrate range, and catalytic efficiency─ or even to …

Automated in vivo enzyme engineering accelerates biocatalyst optimization

E Orsi, L Schada von Borzyskowski, S Noack… - Nature …, 2024 - nature.com
Achieving cost-competitive bio-based processes requires development of stable and
selective biocatalysts. Their realization through in vitro enzyme characterization and …

Accelerating biocatalysis discovery with machine learning: a paradigm shift in enzyme engineering, discovery, and design

B Markus, K Andreas, K Arkadij, L Stefan, O Gustav… - ACS …, 2023 - ACS Publications
Emerging computational tools promise to revolutionize protein engineering for biocatalytic
applications and accelerate the development timelines previously needed to optimize an …

Active learning-assisted directed evolution

J Yang, RG Lal, JC Bowden, R Astudillo… - Nature …, 2025 - nature.com
Directed evolution (DE) is a powerful tool to optimize protein fitness for a specific application.
However, DE can be inefficient when mutations exhibit non-additive, or epistatic, behavior …

Evolutionary computation in bioinformatics: A survey

Y Zhang, L Cheng, G Chen, D Alghazzawi - Neurocomputing, 2024 - Elsevier
Bioinformatics is a subject that studies life phenomena by using mathematical and
information science theories and techniques. Its main tasks, such as DNA sequence …

A library approach for the de novo high-throughput isolation of humanized VHH domains with favorable developability properties following camelid immunization

P Arras, HB Yoo, L Pekar, C Schröter, T Clarke, S Krah… - MAbs, 2023 - Taylor & Francis
In this study, we generated a novel library approach for high throughput de novo
identification of humanized single-domain antibodies following camelid immunization. To …

Bayesian optimization in drug discovery

L Colliandre, C Muller - High Performance Computing for Drug Discovery …, 2023 - Springer
Drug discovery deals with the search for initial hits and their optimization toward a targeted
clinical profile. Throughout the discovery pipeline, the candidate profile will evolve, but the …

AI/ML combined with next-generation sequencing of VHH immune repertoires enables the rapid identification of de novo humanized and sequence-optimized single …

P Arras, HB Yoo, L Pekar, T Clarke… - Frontiers in Molecular …, 2023 - frontiersin.org
Introduction: In this study, we demonstrate the feasibility of yeast surface display (YSD) and
nextgeneration sequencing (NGS) in combination with artificial intelligence and machine …

Engineering highly active and diverse nuclease enzymes by combining machine learning and ultra-high-throughput screening

N Thomas, D Belanger, C Xu, H Lee, K Hirano, K Iwai… - bioRxiv, 2024 - biorxiv.org
Designing enzymes to function in novel chemical environments is a central goal of synthetic
biology with broad applications. Guiding protein design with machine learning (ML) has the …

Optimisation strategies for directed evolution without sequencing

J James, S Towers, J Foerster… - PLOS Computational …, 2024 - journals.plos.org
Directed evolution can enable engineering of biological systems with minimal knowledge of
their underlying sequence-to-function relationships. A typical directed evolution process …