The DOI matches its Crossref record; 62 of the 62 references it cites were found in a registry or an index.
In silico optimization of a guava antimicrobial peptide enables combinatorial exploration for peptide design
Open accessAbstract
Plants are extensively used in traditional medicine, and several plant antimicrobial peptides have been described as potential alternatives to conventional antibiotics. However, after more than four decades of research no plant antimicrobial peptide is currently used for treating bacterial infections, due to their length, post-translational modifications or high dose requirement for a therapeutic effect . Here we report the design of antimicrobial peptides derived from a guava glycine-rich peptide using a genetic algorithm. This approach yields guavanin peptides, arginine-rich α-helical peptides that possess an unusual hydrophobic counterpart mainly composed of tyrosine residues. Guavanin 2 is characterized as a prototype peptide in terms of structure and activity. Nuclear magnetic resonance analysis indicates that the peptide adopts an α-helical structure in hydrophobic environments. Guavanin 2 is bactericidal at low concentrations, causing membrane disruption and triggering hyperpolarization. This computational approach for the exploration of natural products could be used to design effective peptide antibiotics.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Gapped BLAST and PSI-BLAST: a new generation of protein database search programs
Altschul, S. (1997) · Nucleic Acids Research · doi:10.1093/nar/25.17.3389 · Cited by 73,302
PROCHECK: a program to check the stereochemical quality of protein structures
Laskowski, R. A., MacArthur, M. W., Moss, D. S., & Thornton, J. M. (1993) · Journal of Applied Crystallography · doi:10.1107/s0021889892009944 · Cited by 24,581
A simple method for displaying the hydropathic character of a protein
Kyte, J., & Doolittle, R. F. (1982) · Journal of Molecular Biology · doi:10.1016/0022-2836(82)90515-0 · Cited by 22,843
NMRPipe: A multidimensional spectral processing system based on UNIX pipes
Delaglio, F., Grzesiek, S., Vuister, G., Zhu, G., Pfeifer, J., & Bax, A. (1995) · Journal of Biomolecular NMR · doi:10.1007/bf00197809 · Cited by 15,965
Electrostatics of nanosystems: Application to microtubules and the ribosome
Baker, N. A., Sept, D., Joseph, S., Holst, M. J., & McCammon, J. A. (2001) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.181342398 · Cited by 7,172
MOLMOL: A program for display and analysis of macromolecular structures
Koradi, R., Billeter, M., & Wüthrich, K. (1996) · Journal of Molecular Graphics · doi:10.1016/0263-7855(96)00009-4 · Cited by 7,163
Wiederstein, M., & Sippl, M. J. (2007) · Nucleic Acids Research · doi:10.1093/nar/gkm290 · Cited by 5,909
Antimicrobial peptides: pore formers or metabolic inhibitors in bacteria?
Brogden, K. A. (2005) · Nature Reviews Microbiology · doi:10.1038/nrmicro1098 · Cited by 5,829
Comparative Protein Structure Modeling Using Modeller
Eswar, N., Webb, B., Marti‐Renom, M. A., Madhusudhan, M. S., Eramian, D., Shen, M., Pieper, U., & Sali, A. (2006) · Current Protocols in Bioinformatics · doi:10.1002/0471250953.bi0506s15 · Cited by 4,478
Comparative Protein Structure Modeling Using MODELLER
Webb, B., & Sali, A. (2016) · Current Protocols in Bioinformatics · doi:10.1002/cpbi.3 · Cited by 4,316
Cited by
Peptide Design Principles for Antimicrobial Applications
Torres, M. D. T., Sothiselvam, S., Lu, T. K., & de la Fuente-Nunez, C. (2019) · Journal of Molecular Biology · doi:10.1016/j.jmb.2018.12.015 · Cited by 438
Self-citationDiscovering highly potent antimicrobial peptides with deep generative model HydrAMP
Szymczak, P., Możejko, M., Grzegorzek, T., Jurczak, R., Bauer, M., Neubauer, D., Sikora, K., Michalski, M., Sroka, J., Setny, P., et al. (2023) · Nature Communications · doi:10.1038/s41467-023-36994-z · Cited by 231
Accelerating antibiotic discovery through artificial intelligence
Melo, M. C. R., Maasch, J. R. M. A., & de la Fuente-Nunez, C. (2021) · Communications Biology · doi:10.1038/s42003-021-02586-0 · Cited by 234
Self-citationLima, P. G., Oliveira, J. T. A., Amaral, J. L., Freitas, C. D. T., & Souza, P. F. N. (2021) · Life Sciences · doi:10.1016/j.lfs.2021.119647 · Cited by 170
Innate Inspiration: Antifungal Peptides and Other Immunotherapeutics From the Host Immune Response
Mercer, D. K., & O'Neil, D. A. (2020) · Frontiers in Immunology · doi:10.3389/fimmu.2020.02177 · Cited by 50
Metadata
- Authors
- Porto, W. F., Irazazabal, L., Alves, E. S. F., Ribeiro, S. M., Matos, C. O., Pires, Á. S., Fensterseifer, I. C. M., Miranda, V. J., Haney, E. F., Humblot, V., Torres, M. D. T., Hancock, R. E. W., Liao, L. M., Ladram, A., Lu, T. K., de la Fuente-Nunez, C., & Franco, O. L.
- Venue
- Nature Communications
- Published
- 2018-04-16
- Volume
- 9
- Issue
- 1
- Pages
- 1490-1490
- ISSN
- 2041-1723 (ISSN-L)
- OpenAlex
- W2796712624
- Cited by
- 284
- References
- 62
- FWCI
- 16.24
- Type
- journal article
- Language
- en
- Open access
- gold
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: In silico optimization of a guava antimicrobial peptide enables combinatorial exploration for peptide design. https://app.cochat.ai/papers/10.1038/s41467-018-03746-3
- The paper
- Porto, W. F., Irazazabal, L., Alves, E. S. F., Ribeiro, S. M., Matos, C. O., Pires, Á. S., Fensterseifer, I. C. M., Miranda, V. J., Haney, E. F., Humblot, V., Torres, M. D. T., Hancock, R. E. W., Liao, L. M., Ladram, A., Lu, T. K., de la Fuente-Nunez, C., & Franco, O. L. (2018). In silico optimization of a guava antimicrobial peptide enables combinatorial exploration for peptide design. Nature Communications. https://doi.org/10.1038/s41467-018-03746-3
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
