Deep neural network-based feature selection with local false discovery rate estimation

Cao, Zixuan; Sun, Xiaoya; Fu, Yan

doi:10.1007/s10489-024-05944-7

Appl Intell

2024

DOI: 10.1007/s10489-024-05944-7

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Deep neural network-based feature selection with local false discovery rate estimation

Zixuan Cao,

Xiaoya Sun,

Yan Fu

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Antimicrobial Peptides as Broad-Spectrum Therapeutics: Computational Analysis to Identify Universal Physical-Chemical Features Responsible for Multitarget Activity

Medvedeva,

Vasnetsov,

Vasnetsov

et al. 2024

J. Phys. Chem. Lett.

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Antimicrobial peptides (AMPs) hold significant potential as broad-spectrum therapeutics due to their ability to target a variety of different pathogens, including bacteria, fungi, and viruses. However, the rational design of these peptides requires the molecular understanding of properties that enable such broad-spectrum activity. In this study, we present a computational analysis that utilizes machine-learning methods to distinguish peptides with single-target activity from those with activity against multiple pathogens. By optimizing a feature-selection procedure, the most relevant physical-chemical properties, such as dipeptide compositions, solvent accessibility, charge distributions, and optimal hydrophobicity, that differentiate between narrow-spectrum and broad-spectrum peptides are identified. Possible molecular scenarios responsible for the universality of these features are discussed. These findings provide valuable insights into the molecular mechanisms and rational design of multitarget AMPs.

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Antimicrobial Peptides as Broad-Spectrum Therapeutics: Computational Analysis to Identify Universal Physical-Chemical Features Responsible for Multitarget Activity

Medvedeva,

Vasnetsov,

Vasnetsov

et al. 2024

J. Phys. Chem. Lett.

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show abstract

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Deep neural network-based feature selection with local false discovery rate estimation

Cited by 1 publication

References 27 publications

Antimicrobial Peptides as Broad-Spectrum Therapeutics: Computational Analysis to Identify Universal Physical-Chemical Features Responsible for Multitarget Activity

Antimicrobial Peptides as Broad-Spectrum Therapeutics: Computational Analysis to Identify Universal Physical-Chemical Features Responsible for Multitarget Activity

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