Javascript must be enabled to continue!
Exploring Phytochemical Compounds Against Pseudomonas Aeruginosa Using QSAR, Molecular Dynamics, and Free Energy Landscape
View through CrossRef
Abstract
Pseudomonas aeruginosa
is a versatile opportunistic bacterium that presents a considerable risk in medical environments because of its strong adaptability and resistance to multiple medications. Targeting the LasR quorum sensing system, which plays a crucial role in controlling virulence factors and biofilm formation, is a key intervention point. In this study,
in silico
molecular docking, machine learning‐based Quantitative Structure‐Activity Relationship (QSAR) techniques along with molecular dynamics simulation were employed to screen phytochemical compounds for their ability to inhibit the LasR QS system, a key regulator of virulence in
Pseudomonas aeruginosa
. This study screened 1652 phytochemicals using the ML‐based QSAR model to identify 52 phytochemicals that had better activity than the control (N‐{[3,5‐dibromo‐2‐(methoxymethoxy)phenyl]methyl}‐2‐nitrobenzamide). The
in silico
molecular docking approach that targeted LasR identified compounds
5281647
,
57331045
, and
5281672
with high binding affinity and hydrogen bonds that were comparable to the control (docking score=−10.3 kcal/mol and hydrogen bonds=4). In the 200 ns post‐molecular dynamics simulation,
5281647
exhibited a stable RMSD of 0.25 nm, which was comparable to the control. The maximum number of hydrogen bonds was exhibited by
57331045
, while
5281647
and
5281672
consistently exhibited four hydrogen bonds. Overall, the Principal component analysis (PCA) and Free Energy Landscape (FEL) analyses of the complexes demonstrated that these three compounds were in stable states. In comparison to the control (ΔG
TOTAL
=−39.58 kcal/mol), the cumulative binding free energy (ΔG
TOTAL
) for
5281647
and
57331045
was −39.95 kcal/mol and −39.25 kcal/mol, respectively. This further confirms the superior binding affinity of the two compounds. Both
5281647
and
57331045
were identified as potent inhibitors of the LasR transcription factor, which is essential for the quorum sensing of
Pseudomonas aeruginosa
, in the present investigation. These findings underscore the importance of further exploration and optimization of phytochemicals for combating bacterial infections, offering promising avenues for future drug discovery efforts targeting this resilient pathogen.
Title: Exploring Phytochemical Compounds Against
Pseudomonas Aeruginosa
Using QSAR, Molecular Dynamics, and Free Energy Landscape
Description:
Abstract
Pseudomonas aeruginosa
is a versatile opportunistic bacterium that presents a considerable risk in medical environments because of its strong adaptability and resistance to multiple medications.
Targeting the LasR quorum sensing system, which plays a crucial role in controlling virulence factors and biofilm formation, is a key intervention point.
In this study,
in silico
molecular docking, machine learning‐based Quantitative Structure‐Activity Relationship (QSAR) techniques along with molecular dynamics simulation were employed to screen phytochemical compounds for their ability to inhibit the LasR QS system, a key regulator of virulence in
Pseudomonas aeruginosa
.
This study screened 1652 phytochemicals using the ML‐based QSAR model to identify 52 phytochemicals that had better activity than the control (N‐{[3,5‐dibromo‐2‐(methoxymethoxy)phenyl]methyl}‐2‐nitrobenzamide).
The
in silico
molecular docking approach that targeted LasR identified compounds
5281647
,
57331045
, and
5281672
with high binding affinity and hydrogen bonds that were comparable to the control (docking score=−10.
3 kcal/mol and hydrogen bonds=4).
In the 200 ns post‐molecular dynamics simulation,
5281647
exhibited a stable RMSD of 0.
25 nm, which was comparable to the control.
The maximum number of hydrogen bonds was exhibited by
57331045
, while
5281647
and
5281672
consistently exhibited four hydrogen bonds.
Overall, the Principal component analysis (PCA) and Free Energy Landscape (FEL) analyses of the complexes demonstrated that these three compounds were in stable states.
In comparison to the control (ΔG
TOTAL
=−39.
58 kcal/mol), the cumulative binding free energy (ΔG
TOTAL
) for
5281647
and
57331045
was −39.
95 kcal/mol and −39.
25 kcal/mol, respectively.
This further confirms the superior binding affinity of the two compounds.
Both
5281647
and
57331045
were identified as potent inhibitors of the LasR transcription factor, which is essential for the quorum sensing of
Pseudomonas aeruginosa
, in the present investigation.
These findings underscore the importance of further exploration and optimization of phytochemicals for combating bacterial infections, offering promising avenues for future drug discovery efforts targeting this resilient pathogen.
Related Results
Challenging Management of Postoperative Empyema: A Case Report with Literature Review
Challenging Management of Postoperative Empyema: A Case Report with Literature Review
Abstract
Introduction: Pleural empyema is the collection of pus within the pleural cavity, typically arising as a complication of pneumonia, chest trauma, thoracic surgery, or bact...
Metallothionein Protein Modeling from Pseudomonas aeruginosa PAO1 as A Metal Biosorber Candidate
Metallothionein Protein Modeling from Pseudomonas aeruginosa PAO1 as A Metal Biosorber Candidate
Metallothionein is a protein that is well known to play a role in metal metabolism in bacterial cells. Metallothionein is a multifunctional protein that has the potential to be use...
Improving QSAR model predictions using ensembled heterogenous features
Improving QSAR model predictions using ensembled heterogenous features
Quantitative structure–activity relationship (QSAR) models are widely used computational tools in drug discovery for predicting molecular activities and prioritizing compounds for ...
Improving QSAR model predictions using ensembled heterogenous features
Improving QSAR model predictions using ensembled heterogenous features
Quantitative structure–activity relationship (QSAR) models are widely used computational tools in drug discovery for predicting molecular activities and prioritizing compounds for ...
2049. National Trends in Infections caused by Pseudomonas aeruginosa and Carbapenem Resistant Pseudomonas aeruginosa, 2017 – 2020
2049. National Trends in Infections caused by Pseudomonas aeruginosa and Carbapenem Resistant Pseudomonas aeruginosa, 2017 – 2020
Abstract
Background
Pseudomonas aeruginosa is an opportunistic pathogen commonly found in the environment, including water and p...
Prevalence and risk factors of
Pseudomonas aeruginosa
colonization
Prevalence and risk factors of
Pseudomonas aeruginosa
colonization
Abstract
Pseudomonas aeruginosa
(
P. aeruginosa
) is one of the most concerning pathogens d...
การโคลนและลักษณะสมบัติของยีนกลุ่ม rhl ที่เกี่ยวข้องกับการสังเคราะห์แรมโนลิพิดของ Pseudomonas aeruginosa A41
การโคลนและลักษณะสมบัติของยีนกลุ่ม rhl ที่เกี่ยวข้องกับการสังเคราะห์แรมโนลิพิดของ Pseudomonas aeruginosa A41
Pseudomonas sp. A41 ที่แยกจากอ่าวไทย มีความสามารถ1ในการผลิตแรมโนลิพิดจากลักษณะทางสัณฐานวิทยาและสมบัติทางชีวเคมีร่วมกับข้อมูลลำดับนิวคลีโอไทด์ของ 16S rDNA สามารถจำแนกลายพันธุ A41 เป...
การโคลนและลักษณะสมบัติของยีนกลุ่ม rhl ที่เกี่ยวข้องกับการสังเคราะห์โมโนแรมโนลิพิดทางชีวภาพของ Pseudomonas aeruginosa A41 : รายงานผลการวิจัย
การโคลนและลักษณะสมบัติของยีนกลุ่ม rhl ที่เกี่ยวข้องกับการสังเคราะห์โมโนแรมโนลิพิดทางชีวภาพของ Pseudomonas aeruginosa A41 : รายงานผลการวิจัย
Pseudomonas sp. A41 ที่แยกจากน้ำทะเลอ่าวไทย มีความสามารถในการผลิตแรมโนลิพิดจากลักษณะทางสัณฐานวิทยาและสมบัติทางชีวเคมีร่วมกับข้อมูลลำดับนิวคลีโอไทด์ของ 16S rDNA สามารถจำแนกสายพันธุ์...

