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Author Spotlight: Streamlining Protein Target Prediction and Validation via Molecular Docking and CETSA
Published on: February 23, 2024
In Silico Core Proteomics and Molecular Docking Approaches for the Identification of Novel Inhibitors against
Abdur Rehman1, Xiukang Wang2, Sajjad Ahmad3
1Department of Bioinformatics and Biotechnology, Government College University Faisalabad, Faisalabad 38000, Pakistan.
Abstract:
Streptococcus pyogenes is a significant pathogen that causes skin and upper respiratory tract infections and non-suppurative complications, such as acute rheumatic fever and post-strep glomerulonephritis. Multidrug resistance has emerged in S. pyogenes strains, making them more dangerous and pathogenic. Hence, it is necessary to identify and develop therapeutic methods that would present novel approaches to S. pyogenes infections. In the current study, a subtractive proteomics approach was employed to core proteomes of four strains of S. pyogenes using several bioinformatic software tools and servers. The core proteome consists of 1324 proteins, and 302 essential proteins were predicted from them. These essential proteins were analyzed using BLASTp against human proteome, and the number of potential targets was reduced to 145. Based on subcellular localization prediction, 46 proteins with cytoplasmic localization were chosen for metabolic pathway analysis. Only two cytoplasmic proteins, i.e., chromosomal replication initiator protein DnaA and two-component response regulator (TCR), were discovered to have the potential to be novel drug target candidates. Three-dimensional (3D) structure prediction of target proteins was carried out via the Swiss Model server. Molecular docking approach was employed to screen the library of 1000 phytochemicals against the interacting residues of the target proteins through the MOE software. Further, the docking studies were validated by running molecular dynamics simulation and highly popular binding free energy approaches of MM-GBSA and MM-PBSA. The findings revealed a promising candidate as a novel target against S. pyogenes infections.
Insights
This study identified two novel drug targets, DnaA and TCR, in *Streptococcus pyogenes* to combat multidrug-resistant infections. Phytochemical screening revealed promising candidates for new therapeutic strategies against this significant pathogen.
Area of Science:
- Microbiology
- Computational Biology
- Drug Discovery
Background:
- *Streptococcus pyogenes* causes serious infections and is increasingly multidrug-resistant.
- Novel therapeutic approaches are crucial to combat *S. pyogenes* infections.
Purpose of the Study:
- To identify novel drug targets and potential phytochemical inhibitors against *Streptococcus pyogenes* using a subtractive proteomics approach.
Main Methods:
- Subtractive proteomics and bioinformatic analyses were used to identify essential proteins in *S. pyogenes*.
- Proteins were filtered based on human proteome homology and subcellular localization.
- 3D structure prediction, molecular docking, molecular dynamics, and MM-GBSA/MM-PBSA were employed to screen phytochemicals.
Main Results:
- A core proteome of 1324 proteins was identified, with 302 essential proteins predicted.
- Two cytoplasmic proteins, DnaA and TCR, were identified as potential drug targets.
- Molecular docking identified promising phytochemical candidates against DnaA and TCR.
Conclusions:
- Chromosomal replication initiator protein DnaA and two-component response regulator (TCR) are promising novel drug targets for *S. pyogenes*.
- Phytochemicals show potential as therapeutic agents against *S. pyogenes* infections.
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