Directed Evolution of Proteins via Bayesian Optimization in Embedding Space

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F24%3A00383592" target="_blank" >RIV/68407700:21230/24:00383592 - isvavai.cz</a>

Result on the web

<a href="https://doi.org/10.1109/BIBM62325.2024.10822356" target="_blank" >https://doi.org/10.1109/BIBM62325.2024.10822356</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/BIBM62325.2024.10822356" target="_blank" >10.1109/BIBM62325.2024.10822356</a>

Result language

angličtina

Original language name

Directed Evolution of Proteins via Bayesian Optimization in Embedding Space

Original language description

Directed evolution is an iterative laboratory process of designing proteins with improved function by iteratively synthesizing new protein variants and evaluating their desired property with expensive and time-consuming biochemical screening. Machine learning methods can help select informative or promising variants for screening to increase their quality and reduce the amount of necessary screening. In this paper, we present a novel method for machine-learning-assisted directed evolution of proteins which combines Bayesian optimization with informative representation of protein variants extracted from a pre-trained protein language model. We demonstrate that the new representation based on the sequence embeddings significantly improves the performance of Bayesian optimization yielding better results with the same number of conducted screening in total. At the same time, our method outperforms the state-of-the-art machine-learning-assisted directed evolution methods with regression objective.

Czech name

—

Czech description

—

Type

D - Article in proceedings

CEP classification

—

OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

<a href="/en/project/EF16_019%2F0000765" target="_blank" >EF16_019/0000765: Research Center for Informatics</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Publication year

2024

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

Proceedings - 2024 IEEE International Conference on Bioinformatics and Biomedicine

ISBN

979-8-3503-8622-6

ISSN

2156-1125

e-ISSN

2156-1133

Number of pages

8

Pages from-to

91-98

Publisher name

IEEE Institute of Electrical and Electronics Engineers Inc.

Place of publication

Rio de Janeiro

Event location

Lisbon

Event date

Dec 3, 2024

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

001446153500024