Evidence map›Paper›PMID 27134887›Full record

ArticleJournal of clinical and diagnostic research : JCDR2016

Virtual Screening of Phytochemicals to Novel Target (HAT) Rtt109 in Pneumocystis Jirovecii using Bioinformatics Tools.

Ramya Sugumar, Abhinand Ponneri Adithavarman, Anusha Dakshinamoorthi, Darling Chellathai David, Padmavathi Kannan Ragunath

Open access · goldAbstract read
In one paragraph

Article in Journal of clinical and diagnostic research : JCDR, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.5field-weighted citation impact, top 30% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 4 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 1 institution in 1 country.

Ramya SugumarAssistant Professor, Department of Pharmacology, Sri Ramachandra University , Tamil Nadu, India .
Abhinand Ponneri AdithavarmanPh.D Research Scholar, Deapartment of Bioinformatics, Sri Ramachandra University , Tamil Nadu, India .
Anusha DakshinamoorthiAssociate Professor, Department of Pharmacology, Sri Ramachandra University , Tamil Nadu, India .
Darling Chellathai DavidAssociate Professor, Department of Pharmacology, Sri Ramachandra University , Tamil Nadu, India .
Padmavathi Kannan RagunathAssociate Professor, Department of Pharmacology, Sri Ramachandra University , Tamil Nadu, India .
Sri Ramachandra Institute of Higher Education and Research · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionPneumocystis 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.

aimTo screen phytochemicals against (HAT) Rtt109 using bioinformatics tool. MATERIALS AND

methodsThe 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.

resultsTertiary 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.

conclusionBaicalin 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.

Indexed as

BaicalinMolecular dockingPneumonia

Identifiers

PMID27134887
PMCPMC4843273
OpenAlexW2340303969

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.