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bioRxiv · 10.1101/2022.07.29.502060

In Silico Proteomics Approach Towards the Identification of Potential Novel Drug Targets Against Cryptococcus gattii

Robin, T. B.·Rani, N. A.·Ahmed, N.·Prome, A. A.·Bappy, M. N. I.·Ahmed, F.
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Abstract

Cryptococcosis is a condition caused by inhaling Cryptococcus gattii, the tiny fungus from the environment. It is thought that the pathogen C. gattii is clinically more virulent than C. neoformans and could be a vicious agent in coming decades. It can enter the hosts brain and harm human peripheral blood mononuclear cells DNA (PBMCs). It is vital to investigate potential alternative medications to treat this disease since global antifungal resistance preventing Cryptococci infections is on the rise, leading to treatment failure. In order to find effective novel drug targets for C. gattii, a comprehensive novel approach has been used in conjunction with in silico analysis. Among 6561 proteins of C. gattii we have found three druggable proteins (XP 003194316.1, XP 003197297.1, XP 003197520.1) after completing a series of steps including exclusion of paralogs, human homologs, non-essential and human microbiome homologs proteins. These three proteins are involved in pathogen specific pathways, and can be targeted for drugs to eliminate the pathogen from the host. The subcellular locations and their interactions with a high number of proteins also demonstrate their eligibility as potential drug targets. We have approached their secondary, tertiary model and docked them with 21 potential antifungal plant metabolites. From the molecular docking analysis, we found Amentoflavone, Baicalin, Rutin and Viniferin to be the most effective drugs to stop such proteins because of their increased binding affinity. Correspondingly, the drugs showed proper ADME properties and also analyzed to be safe (Figure 9, Table 6). Moreover, these potential drugs can successfully be used in the treatment of Cryptococcosis caused by the fungus Cryptococcus gattii. In vivo trail is highly recommended for further prospection. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=185 SRC="FIGDIR/small/502060v1_fig9.gif" ALT="Figure 9"> View larger version (29K): org.highwire.dtl.DTLVardef@1e1d79borg.highwire.dtl.DTLVardef@122e30org.highwire.dtl.DTLVardef@19667eaorg.highwire.dtl.DTLVardef@18063a6_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFigure 9:C_FLOATNO SwissADME properties of top metabolites C_FIG O_TBL View this table: org.highwire.dtl.DTLVardef@e46d5org.highwire.dtl.DTLVardef@14c66b3org.highwire.dtl.DTLVardef@ea8b0eorg.highwire.dtl.DTLVardef@4f4bc8org.highwire.dtl.DTLVardef@1f85c8e_HPS_FORMAT_FIGEXP M_TBL O_FLOATNOTable 06:C_FLOATNO O_TABLECAPTIONTop metabolites with toxicity prediction C_TABLECAPTION C_TBL

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Robin, T. B., Rani, N. A., Ahmed, N., Prome, A. A., Bappy, M. N. I., Ahmed, F.. 2022-08-01. In Silico Proteomics Approach Towards the Identification of Potential Novel Drug Targets Against Cryptococcus gattii. https://doi.org/10.1101/2022.07.29.502060

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