Machine learning designs non-hemolytic antimicrobial peptides-Reference-Cited by-同舟云学术

Machine learning designs non-hemolytic antimicrobial peptides

Published:2021 Issue: Volume: Page:
ISSN:2041-6520
Container-title:Chemical Science
language:en
Short-container-title:Chem. Sci.

Author:

Capecchi Alice¹²³⁴⁵^ORCID,Cai Xingguang¹²³⁴⁵^ORCID,Personne Hippolyte¹²³⁴⁵^ORCID,Köhler Thilo⁶⁷⁵⁸⁹,van Delden Christian⁶⁷⁵⁸⁹,Reymond Jean-Louis¹²³⁴⁵^ORCID

Affiliation:

1. Department of Chemistry

2. Biochemistry and Pharmaceutical Sciences

3. University of Bern

4. 3012 Bern

5. Switzerland

6. Department of Microbiology and Molecular Medicine

7. University of Geneva

8. Service of Infectious Diseases

9. University Hospital of Geneva

Abstract

Machine learning models trained with experimental data for antimicrobial activity and hemolysis are shown to produce new non-hemolytic antimicrobial peptides active against multidrug-resistant bacteria.

Funder

H2020 European Research Council

Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung

Publisher

Royal Society of Chemistry (RSC)

Subject

General Chemistry

Link

http://pubs.rsc.org/en/content/articlepdf/2021/SC/D1SC01713F

Reference54 articles.

1. Computational Methods in Drug Discovery

2. Applications of machine learning in drug discovery and development