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Updated: Mar 21, 2026
Assays for Validating Histone Acetyltransferase Inhibitors
Published on: August 6, 2020
Virtual Screening of Phytochemicals to Novel Target (HAT) Rtt109 in Pneumocystis Jirovecii using Bioinformatics Tools
Ramya Sugumar1, Abhinand Ponneri Adithavarman2, Anusha Dakshinamoorthi3
1Assistant Professor, Department of Pharmacology, Sri Ramachandra University , Tamil Nadu, India .
Introduction:
Pneumocystis jirovecii is a fungus that causes Pneumocystis pneumonia in HIV and other immunosuppressed patients. Treatment of Pneumocystis pneumonia with the currently available antifungals is challenging and associated with considerable adverse effects. There is a need to develop drugs against novel targets with minimal human toxicities. Histone Acetyl Transferase (HAT) Rtt109 is a potential therapeutic target in Pneumocystis jirovecii species. HAT is linked to transcription and is required to acetylate conserved lysine residues on histone proteins by transferring an acetyl group from acetyl CoA to form e-N-acetyl lysine. Therefore, inhibitors of HAT can be useful therapeutic options in Pneumocystis pneumonia.
Aim:
To screen phytochemicals against (HAT) Rtt109 using bioinformatics tool.
Materials And Methods:
The tertiary structure of Pneumocystis jirovecii (HAT) Rtt109 was modeled by Homology Modeling. The ideal template for modeling was obtained by performing Psi BLAST of the protein sequence. Rtt109-AcCoA/Vps75 protein from Saccharomyces cerevisiae (PDB structure 3Q35) was chosen as the template. The target protein was modeled using Swiss Modeler and validated using Ramachandran plot and Errat 2. Comprehensive text mining was performed to identify phytochemical compounds with antipneumonia and fungicidal properties and these compounds were filtered based on Lipinski's Rule of 5. The chosen compounds were subjected to virtual screening against the target protein (HAT) Rtt109 using Molegro Virtual Docker 4.5. Osiris Property Explorer and Open Tox Server were used to predict ADME-T properties of the chosen phytochemicals.
Results:
Tertiary structure model of HAT Rtt 109 had a ProSA score of -6.57 and Errat 2 score of 87.34. Structure validation analysis by Ramachandran plot for the model revealed 97% of amino acids were in the favoured region. Of all the phytochemicals subjected to virtual screening against the target protein (HAT) Rtt109, baicalin exhibited highest binding affinity towards the target protein as indicated by the Molegro score of 130.68 and formed 16 H-bonds. The ADME-T property prediction revealed that baicalin was non-mutagenic, non-tumorigenic and had a drug likeness score of 0.87.
Conclusion:
Baicalin has good binding with Rtt 109 in Pneumocystis jirovecii and can be considered as a novel and valuable treatment option for Pneumocystis pneumonia patients after subjecting it to invivo and invitro studies.
Insights
This study identified baicalin as a promising new treatment for Pneumocystis pneumonia. Baicalin shows strong binding to the target protein Rtt109 in Pneumocystis jirovecii, suggesting potential therapeutic benefits.
Area of Science:
- Biochemistry
- Computational Biology
- Pharmacology
Background:
- Pneumocystis pneumonia (PCP) poses a significant challenge in immunosuppressed individuals.
- Current antifungal treatments for PCP are limited by adverse effects.
- Novel therapeutic targets, such as Histone Acetyl Transferase (HAT) Rtt109 in Pneumocystis jirovecii, are needed.
Purpose of the Study:
- To screen phytochemicals against the HAT Rtt109 target using bioinformatics tools.
- To identify potential novel drug candidates for PCP treatment.
Main Methods:
- Homology modeling was used to generate the tertiary structure of Pneumocystis jirovecii HAT Rtt109.
- Phytochemicals were identified via text mining and filtered using Lipinski's Rule of 5.
- Virtual screening and ADME-T property prediction were performed using Molegro Virtual Docker, Osiris Property Explorer, and Open Tox Server.
Main Results:
- The validated Rtt109 model showed good structural integrity.
- Baicalin demonstrated the highest binding affinity to HAT Rtt109 with a Molegro score of 130.68 and 16 hydrogen bonds.
- Baicalin exhibited favorable drug-like properties, being non-mutagenic, non-tumorigenic, with a drug likeness score of 0.87.
Conclusions:
- Baicalin shows significant binding affinity to Pneumocystis jirovecii Rtt109.
- Baicalin represents a potential novel therapeutic agent for PCP.
- Further in vivo and in vitro studies are warranted to validate baicalin's efficacy and safety.
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