July 2018
Volume 59, Issue 9
Open Access
ARVO Annual Meeting Abstract  |   July 2018
In silico Comparison of Chlamydia trachomatis drug binding pocketome vs. human and prioritization of potential drug targets
Author Affiliations & Notes
  • Umashankar Vetrivel
    Centre for Bioinformatics, Kamalnayan Bajaj Institute for Research in Vision and Ophthalmology,Vision Research Foundation, Sankara Nethralaya, India, Chennai, Tamilnadu, India
  • Anupriya Sadhasivam
    Centre for Bioinformatics, Kamalnayan Bajaj Institute for Research in Vision and Ophthalmology,Vision Research Foundation, Sankara Nethralaya, India, Chennai, Tamilnadu, India
  • Footnotes
    Commercial Relationships   Umashankar Vetrivel, None; Anupriya Sadhasivam, None
  • Footnotes
    Support  None
Investigative Ophthalmology & Visual Science July 2018, Vol.59, 2364. doi:
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      Umashankar Vetrivel, Anupriya Sadhasivam; In silico Comparison of Chlamydia trachomatis drug binding pocketome vs. human and prioritization of potential drug targets. Invest. Ophthalmol. Vis. Sci. 2018;59(9):2364.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose : Chlamydia trachomatis (C.t) serovars A, B and C are major causative of infectious blindness. In our earlier study, codon usage and comparative genomics analysis revealed 281 C.t genes to be targetable, host non-specific and essential genes. However, it is crucial to validate these targets for host non-specificity at structural level and non-homology with host microbiome to eliminate off-targeting effects. Moreover, an ideal target must also be a part of pathogen’s key Cellular processes. Hence, in this study, a high throughput structural comparison of drug binding pockets in C.t vs. human, proteome subtraction of C.t vs. normal microflora and in silico functional characterization were performed to prioritize the potential targets.

Methods : High throughput structure predictions of reported C.t targets were performed by ModPipe and I-TASSER tools. Further, P2RANK and PocketMatch algorithms were implemented in High Performance Computing Environment for prediction and comparison of drug binding pockets, respectively. Functional analysis of the targets was performed using BLASTKOALA.

Results : Modpipe and I-TASSER predictions yielded a dataset of 302 protein structures for reported C.t targets (inclusive of segmented regions). Human proteome structural dataset (37,991 proteins) was retrieved from ModBase. P2RANK predicted 1,353 drug binding pockets from C.t dataset and 1,18,751 for human. Further, on 16,06,50,677 pairwise comparisons of C.t vs. Human Pockets, a total of 264 C.t proteins that lack similar pockets in human were identified. Further, these proteins were subjected to proteome subtraction with 81 normal microflora. This resulted in 112 C.t proteins that lack homology with normal microflora. Among these 112 proteins, 42 were found to be characterised. On subsequent functional analysis, 18 potential targets were found to map under different crucial cellular processes like Genetic and Environmental Information Processing, Metabolism of Lipids, amino acids, cofactors and vitamins.

Conclusions : The proposed C.t targets are highly potential as these proteins lack structural similarity with human drug binding pockets, non-homologous to normal microflora and also play role in pathogen’s key cellular processes. Further virtual screening and experimental studies will provide insights on potential modalties for combating C.t infections.

This is an abstract that was submitted for the 2018 ARVO Annual Meeting, held in Honolulu, Hawaii, April 29 - May 3, 2018.

 

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