In silico discovery of druggable targets in Citrobacter koseri using echinoderm metabolites and molecular dynamics simulation

Citrobacter koseri causes infection in people who are immunocompromised. Without effective antibiotics, these infections can become severe and life-threatening, so effective drugs are essential to treat these infections. Utilizing subtractive genomics, 2699 ORFs were predicted and translated into amino acid sequences. Metabolic pathway analysis and subcellular localization helped define the roles of key bacterial proteins. Two druggable proteins, WP_012000829.1 and WP_275157394.1, were discovered as promising targets. Alpha Fold provided 3D structures, and a library of 1600 echinoderm metabolites was docked against these proteins, with Ampicillin, Levofloxacin, and Doxycycline as controls. Notably, CMNPD13085 and CMNPD15632 exhibited the highest binding affinities for WP_012000829.1 and WP_275157394.1, respectively. Molecular dynamics simulations and MM-GBSA binding free energy complemented docking results. However, acknowledging the reliance on computational validations, the study emphasizes the need for essential in-vitro research to transform these potential inhibitors into therapeutic drugs.

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Publication Details

Journal
Scientific Reports
Published
2024-11-05
DOI
https://doi.org/10.1038/s41598-024-77342-5
Citations
3
Primary Topic
Computational Drug Discovery Methods
Type
article
Field-Weighted Citation Impact
1.08

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article

In silico discovery of druggable targets in Citrobacter koseri using echinoderm metabolites and molecular dynamics simulation

Abdullah R. Alanzi, Ramzi A. Mothana, Bayan Abdullah Alhaidhal, Fatimah Mohammed Alsulais
3 citations
Scientific Reports
Computational Drug Discovery Methods
1.08
article

In silico discovery of druggable targets in Citrobacter koseri using echinoderm metabolites and molecular dynamics simulation

Abdullah R. Alanzi, Ramzi A. Mothana, Bayan Abdullah Alhaidhal, Fatimah Mohammed Alsulais
article en
3 citations

Abstract

Citrobacter koseri causes infection in people who are immunocompromised. Without effective antibiotics, these infections can become severe and life-threatening, so effective drugs are essential to treat these infections. Utilizing subtractive genomics, 2699 ORFs were predicted and translated into amino acid sequences. Metabolic pathway analysis and subcellular localization helped define the roles of key bacterial proteins. Two druggable proteins, WP_012000829.1 and WP_275157394.1, were discovered as promising targets. Alpha Fold provided 3D structures, and a library of 1600 echinoderm metabolites was docked against these proteins, with Ampicillin, Levofloxacin, and Doxycycline as controls. Notably, CMNPD13085 and CMNPD15632 exhibited the highest binding affinities for WP_012000829.1 and WP_275157394.1, respectively. Molecular dynamics simulations and MM-GBSA binding free energy complemented docking results. However, acknowledging the reliance on computational validations, the study emphasizes the need for essential in-vitro research to transform these potential inhibitors into therapeutic drugs.

Scientific ReportsVol. 14(1)
King Saud University (SA)
King Saud University
Openalex Percentile: Top 19%
Computational Drug Discovery Methods
1.08
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In silico discovery of druggable targets in Citrobacter koseri using echinoderm metabolites and molecular dynamics simulation — Abdullah R. Alanzi, Ramzi A. Mothana, et al. · Scientific Reports (2024) | TGRS Research Map | TGRS