Machine learning for antimicrobial peptide identification and design

F Wan, F Wong, JJ Collins… - Nature Reviews …, 2024 - nature.com
Artificial intelligence (AI) and machine learning (ML) models are being deployed in many
domains of society and have recently reached the field of drug discovery. Given the …

[HTML][HTML] Recent progress in the discovery and design of antimicrobial peptides using traditional machine learning and deep learning

J Yan, J Cai, B Zhang, Y Wang, DF Wong, SWI Siu - Antibiotics, 2022 - mdpi.com
Antimicrobial resistance has become a critical global health problem due to the abuse of
conventional antibiotics and the rise of multi-drug-resistant microbes. Antimicrobial peptides …

ToxinPred 3.0: An improved method for predicting the toxicity of peptides

AS Rathore, S Choudhury, A Arora, P Tijare… - Computers in Biology …, 2024 - Elsevier
Toxicity emerges as a prominent challenge in the design of therapeutic peptides, causing
the failure of numerous peptides during clinical trials. In 2013, our group developed …

Artificial intelligence-driven antimicrobial peptide discovery

P Szymczak, E Szczurek - Current Opinion in Structural Biology, 2023 - Elsevier
Antimicrobial peptides (AMPs) emerge as promising agents against antimicrobial resistance,
providing an alternative to conventional antibiotics. Artificial intelligence (AI) revolutionized …

Bacteria-specific feature selection for enhanced antimicrobial peptide activity predictions using machine-learning methods

H Teimouri, A Medvedeva… - Journal of Chemical …, 2023 - ACS Publications
There are several classes of short peptide molecules, known as antimicrobial peptides
(AMPs), which are produced during the immune responses of living organisms against …

Prediction of antifungal activity of antimicrobial peptides by transfer learning from protein pretrained models

F Lobo, MS González, A Boto… - International Journal of …, 2023 - mdpi.com
Peptides with antifungal activity have gained significant attention due to their potential
therapeutic applications. In this study, we explore the use of pretrained protein models as …

[HTML][HTML] The role and future prospects of artificial intelligence algorithms in peptide drug development

Z Chen, R Wang, J Guo, X Wang - Biomedicine & Pharmacotherapy, 2024 - Elsevier
Peptide medications have been more well-known in recent years due to their many benefits,
including low side effects, high biological activity, specificity, effectiveness, and so on. Over …

Design of target specific peptide inhibitors using generative deep learning and molecular dynamics simulations

S Chen, T Lin, R Basu, J Ritchey, S Wang… - Nature …, 2024 - nature.com
We introduce a computational approach for the design of target-specific peptides. Our
method integrates a Gated Recurrent Unit-based Variational Autoencoder with Rosetta …

Antimicrobial peptides as drugs with double response against Mycobacterium tuberculosis coinfections in lung cancer

G Polinário, LMDG Primo, MABC Rosa… - Frontiers in …, 2023 - frontiersin.org
Tuberculosis and lung cancer are, in many cases, correlated diseases that can be confused
because they have similar symptoms. Many meta-analyses have proven that there is a …

Long extrachromosomal circular DNA identification by fusing sequence-derived features of physicochemical properties and nucleotide distribution patterns

AF Abbasi, MN Asim, S Ahmed, A Dengel - Scientific Reports, 2024 - nature.com
Long extrachromosomal circular DNA (leccDNA) regulates several biological processes
such as genomic instability, gene amplification, and oncogenesis. The identification of …