Dataset Information

Virtual Screening Approach to Identifying a Novel and Tractable Series of Pseudomonas aeruginosa Elastase Inhibitors.

ABSTRACT: Novel therapies are required to treat chronic bacterial infections in cystic fibrosis (CF) sufferers. The most common pathogen responsible for these infections is Pseudomonas aeruginosa, which persists within the lungs of CF sufferers despite intensive antibiotic treatment. P. aeruginosa elastase (also known as LasB or pseudolysin) is a key virulence determinant that contributes to the pathogenesis and persistence of P. aeruginosa infections in CF patients. The crucial role of LasB in pseudomonal virulence makes it a good target for the development of an adjuvant drug for CF treatment. Herein we discuss the discovery of a new series of LasB inhibitors by virtual screening and computer assisted drug design (CADD) and their optimization leading to compounds 29 and 39 (K _i = 0.16 μM and 0.12 μM, respectively).

SUBMITTER: Leiris S

PROVIDER: S-EPMC7883467 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Virtual Screening Approach to Identifying a Novel and Tractable Series of Pseudomonas aeruginosa Elastase Inhibitors.

Leiris Simon S Davies David T DT Sprynski Nicolas N Castandet Jérôme J Beyria Lilha L Bodnarchuk Michael S MS Sutton Jonathan M JM Mullins Toby M G TMG Jones Mark W MW Forrest Andrew K AK Pallin T David TD Karunakar Paduri P Martha Sathish Kumar SK Parusharamulu Battu B Ramula Ramesh R Kotha Venkatesh V Pottabathini Narender N Pothukanuri Srinivasu S Lemonnier Marc M Everett Martin M

ACS medicinal chemistry letters 20210115 2

Novel therapies are required to treat chronic bacterial infections in cystic fibrosis (CF) sufferers. The most common pathogen responsible for these infections is Pseudomonas aeruginosa, which persists within the lungs of CF sufferers despite intensive antibiotic treatment. P. aeruginosa elastase (also known as LasB or pseudolysin) is a key virulence determinant that contributes to the pathogenesis and persistence of P. aeruginosa infections in CF patients. The crucial role ...[more]

PMID: 33603968

Similar Datasets

Project description:AimTo identify the critical chemical features, with reliable geometric constraints, that contributes to the inhibition of butyrylcholinesterase (BChE) function.MethodsLigand-based pharmacophore modeling was used to identify the critical chemical features of BChE inhibitors. The generated pharmacophore model was validated using various techniques, such as Fischer's randomization method, test set, and decoy set. The best pharmacophore model was used as a query in virtual screening to identify novel scaffolds that inhibit BChE. Compounds selected by the best hypothesis in the virtual screening were tested for drug-like properties, and molecular docking study was applied to determine the optimal orientation of the hit compounds in the BChE active site. To find the reactivity of the hit compounds, frontier orbital analysis was carried out using density functional theory.ResultsBased on its correlation coefficient (0.96), root mean square (RMS) deviation (1.01), and total cost (105.72), the quantitative hypothesis Hypo1 consisting of 2 HBA, 1 Hy-Ali, and 1 Hy-Ar was selected as the best hypothesis. Thus, Hypo1 was used as a 3D query in virtual screening of the Maybridge and Chembridge databases. The hit compounds were filtered using ADMET, Lipinski's Rule of Five, and molecular docking to reduce the number of false positive results. Finally, 33 compounds were selected based on their critical interactions with the significant amino acids in BChE's active site. To confirm the inhibitors' potencies, the orbital energies, such as HOMO and LUMO, of the hit compounds and 7 training set compounds were calculated. Among the 33 hit compounds, 10 compounds with the highest HOMO values were selected, and this set was further culled to 5 compounds based on their energy gaps important for stability and energy transfer. From the overall results, 5 hit compounds were confirmed to be potential BChE inhibitors that satisfied all the pharmacophoric features in Hypo1.ConclusionThis study pinpoints important chemical features with geometric constraints that contribute to the inhibition of BChE activity. Five compounds are selected as the best hit BchE-inhibitory compounds.

Project description:BackgroundPseudomonas aeruginosa (PA) is a common cause of respiratory infection and morbidity. Pseudomonas elastase is an important virulence factor regulated by the lasR gene. Whether PA elastase activity is associated with worse clinical outcomes in ICU patients is unknown.Research questionIs there an association between PA elastase activity and worse host outcomes in a cohort of ICU patients?MethodsPA respiratory isolates from 238 unique ICU patients from two tertiary-care centers within the University of Pittsburgh Medical Center health system were prospectively collected and screened for total protease and elastase activity, biofilm production, antimicrobial resistance, and polymicrobial status. The association between pathogen characteristics and 30-day and 90-day mortality was calculated using logistic regression. For subgroup analysis, two patterns of early (≤72 h) and late sample (>72 h) collection from the index ICU admission were distinguished using a finite mixture model. Lung inflammation and injury was evaluated in a mouse model using a PA high elastase vs low elastase producer.ResultsPA elastase activity was common in ICU respiratory isolates representing 75% of samples and was associated with increased 30-day mortality (adjusted OR [95% CI]: 1.39 [1.05-1.83]). Subgroup analysis demonstrated that elastase activity was a risk factor for 30- and 90-day mortality in the early sample group, whereas antimicrobial resistance was a risk factor for 90-day mortality in the late sample group. Whole genome sequencing of high and low elastase producers showed that predicted loss-of-function lasR genotypes were less common among high elastase producers. Mice infected with a high elastase producer showed increased lung bacterial burden and inflammatory profile compared with mice infected with a low elastase producer.InterpretationElastase activity is associated with 30-day ICU mortality. A high elastase producing clinical isolate confers increased lung tissue inflammation compared with a low elastase producer in vivo.

Project description:AmpC is a group I, class C -lactamase present in most Enterobacteriaceae and in Pseudomonas aeruginosa and other nonfermenting gram-negative bacilli. The β-lactam class of antibiotics is one of the most important structural classes of antibacterial compounds and act by inhibiting the bacterial D ,D - transpeptidases that are responsible for the final step of peptidoglycan cross-linking. Our main aim in the study is to screen possible inhibitors against AmpC / β - lactamase (an enzyme responsible for antimicrobial activity in Pseudomonas aeruginosa), through virtual screening of 1364 NCI (National Cancer Institute) diversity set II compounds. Homology Model of AmpC / β - lactamase was constructed using MODELLER and the Model was validated using PROCHECK and Verify 3D programs to obtain a stable structure, which was further used for virtual screening of NCI (National Cancer Institute) diversity set II compounds through molecular Docking studies using Autodock. The amino acid sequence of the β - lactamase was also subjected to ScanProsite web server to find any pattern present in the sequence. After the prediction of 3-dimensional model of AmpC/ β-lactamase, the possible Active sites ofβ - lactamase were determined using LIGSITE(csc) and CastP web servers simultaneously. The Docked complexes were validated and Enumerated based on the Autodock Scoring function to pick out the best inhibitor based on Autodock energy score. Thus from the entire 1364 NCI diversity set II compounds which were Docked, the best four docking solutions were selected (ZINC12670903, ZINC17465965, ZINC11681166 and ZINC13099024). Further the Complexes were analyzed through LIGPLOT for their interaction for the 4 best docked NCI diversity set II compounds. Thus from the Complex scoring and binding ability it is deciphered that these NCI diversity set II compounds could be promising inhibitors for Pseudomonas aeruginosa using AmpC /β - lactamase as Drug target yet pharmacological studies have to confirm it.

Dataset Information

Virtual Screening Approach to Identifying a Novel and Tractable Series of Pseudomonas aeruginosa Elastase Inhibitors.

Publications

Virtual Screening Approach to Identifying a Novel and Tractable Series of <i>Pseudomonas aeruginosa</i> Elastase Inhibitors.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets