| Title |
Virtual Screening for Potential Inhibitors of CTX-M-15 Protein of Klebsiella pneumoniae
|
|---|---|
| Published in |
Interdisciplinary Sciences: Computational Life Sciences, April 2017
|
| DOI | 10.1007/s12539-017-0222-y |
| Pubmed ID | |
| Authors |
Tayebeh Farhadi, Atefeh Fakharian, Roman S. Ovchinnikov |
| Abstract |
The Gram-negative bacterium Klebsiella pneumoniae, responsible for a wide variety of nosocomial infections in immuno-deficient patients, involves the respiratory, urinary and gastrointestinal tract infections and septicemia. Extended spectrum β-lactamases (ESBL) belong to β-lactamases capable of conferring antibiotic resistance in Gram-negative bacteria. CTX-M-15, a prevalent ESBL reported from Enterobacteriaceae including K. pneumoniae, was selected as a potent anti-bacterial target. To identify the novel drug-like compounds, structure-based screening procedure was employed against downloaded drug-like compounds from ZINC database. An acronym for "ZINC" is not commercial. The docking free energy values were investigated and compared to the known inhibitor Avibactam. Six best novel drug-like compounds were selected and their hydrogen bindings with the receptor were determined. Based on the binding efficiency mode, three among these six identified most potential inhibitors, ZINC21811621, ZINC93091917 and ZINC19488569, were predicted as potential competitive inhibitors against CTX-M-15 compared to Avibactam. These three inhibitors may provide a framework for the experimental studies to develop anti-Klebsiella novel drug candidates targeting CTX-M-15. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Australia | 1 | 50% |
| United Kingdom | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 41 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 41 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Unspecified | 7 | 17% |
| Student > Master | 7 | 17% |
| Researcher | 4 | 10% |
| Professor > Associate Professor | 3 | 7% |
| Student > Ph. D. Student | 3 | 7% |
| Other | 7 | 17% |
| Unknown | 10 | 24% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 8 | 20% |
| Unspecified | 7 | 17% |
| Immunology and Microbiology | 5 | 12% |
| Medicine and Dentistry | 4 | 10% |
| Pharmacology, Toxicology and Pharmaceutical Science | 2 | 5% |
| Other | 5 | 12% |
| Unknown | 10 | 24% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 05 April 2017.
All research outputs
#18,540,642
of 22,962,258 outputs
Outputs from Interdisciplinary Sciences: Computational Life Sciences
#167
of 297 outputs
Outputs of similar age
#234,955
of 308,921 outputs
Outputs of similar age from Interdisciplinary Sciences: Computational Life Sciences
#5
of 7 outputs
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So far Altmetric has tracked 297 research outputs from this source. They receive a mean Attention Score of 2.8. This one is in the 30th percentile – i.e., 30% of its peers scored the same or lower than it.
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