Literature DB >> 28472272

modlAMP: Python for antimicrobial peptides.

Alex T Müller1, Gisela Gabernet1, Jan A Hiss1, Gisbert Schneider1.   

Abstract

SUMMARY: We have implemented the lecular esign aboratory's nti icrobial eptides package ( ), a Python-based software package for the design, classification and visual representation of peptide data. modlAMP offers functions for molecular descriptor calculation and the retrieval of amino acid sequences from public or local sequence databases, and provides instant access to precompiled datasets for machine learning. The package also contains methods for the analysis and representation of circular dichroism spectra.
AVAILABILITY AND IMPLEMENTATION: The modlAMP Python package is available under the BSD license from URL http://doi.org/10.5905/ethz-1007-72 or via pip from the Python Package Index (PyPI). CONTACT: gisbert.schneider@pharma.ethz.ch. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
© The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

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Year:  2017        PMID: 28472272     DOI: 10.1093/bioinformatics/btx285

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  21 in total

1.  Molecular Scaffold Hopping via Holistic Molecular Representation.

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2.  In Vitro and In Vivo Antibiotic Capacity of Two Host Defense Peptides.

Authors:  Iván Arenas; Marco Antonio Ibarra; Felix L Santana; Elba Villegas; Robert E W Hancock; Gerardo Corzo
Journal:  Antimicrob Agents Chemother       Date:  2020-06-23       Impact factor: 5.191

3.  Concerted Rolling and Penetration of Peptides during Membrane Binding.

Authors:  Jacob M Remington; Jonathon B Ferrell; Severin T Schneebeli; Jianing Li
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4.  PDAUG: a Galaxy based toolset for peptide library analysis, visualization, and machine learning modeling.

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Journal:  BMC Bioinformatics       Date:  2022-05-28       Impact factor: 3.307

5.  Identification of antimicrobial peptides from the human gut microbiome using deep learning.

Authors:  Yue Ma; Zhengyan Guo; Binbin Xia; Yuwei Zhang; Xiaolin Liu; Ying Yu; Na Tang; Xiaomei Tong; Min Wang; Xin Ye; Jie Feng; Yihua Chen; Jun Wang
Journal:  Nat Biotechnol       Date:  2022-03-03       Impact factor: 68.164

6.  Large-Scale Screening of Antifungal Peptides Based on Quantitative Structure-Activity Relationship.

Authors:  Jin Zhang; Longbing Yang; Zhuqing Tian; Wenjing Zhao; Chaoqin Sun; Lijuan Zhu; Mingjiao Huang; Guo Guo; Guiyou Liang
Journal:  ACS Med Chem Lett       Date:  2021-12-08       Impact factor: 4.345

7.  HAPPENN is a novel tool for hemolytic activity prediction for therapeutic peptides which employs neural networks.

Authors:  Patrick Brendan Timmons; Chandralal M Hewage
Journal:  Sci Rep       Date:  2020-07-02       Impact factor: 4.379

Review 8.  Membrane Active Peptides and Their Biophysical Characterization.

Authors:  Fatma Gizem Avci; Berna Sariyar Akbulut; Elif Ozkirimli
Journal:  Biomolecules       Date:  2018-08-22

Review 9.  Epinecidin-1, a highly potent marine antimicrobial peptide with anticancer and immunomodulatory activities.

Authors:  Alireza Neshani; Hosna Zare; Mohammad Reza Akbari Eidgahi; Azad Khaledi; Kiarash Ghazvini
Journal:  BMC Pharmacol Toxicol       Date:  2019-05-28       Impact factor: 2.483

10.  In silico design and optimization of selective membranolytic anticancer peptides.

Authors:  Gisela Gabernet; Damian Gautschi; Alex T Müller; Claudia S Neuhaus; Lucas Armbrecht; Petra S Dittrich; Jan A Hiss; Gisbert Schneider
Journal:  Sci Rep       Date:  2019-08-02       Impact factor: 4.379

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