“Proteome-WideScreening to Discover Potential Druggable Proteins in Anaplasma phagocytophilum:A Comprehensive Subtractive ProteomicsApproach” Introduction:Anaplasma phagocytophilumis a Gram-negative, obligate intracellular (1,2,4,6), zoonotic (3) bacterium of theorder Rickettsiales, family Anaplasmataceae (2,6,8) that is transmitted by ticks of the genes Ixodes. On thebasis of recent studies, it is reported that there is no direct human to human transferoccurs. A. phagocytophilum isnot only causing infections in humans, different infectious cases alsoreported in dogs, horses, cats, sheep, cattle, reindeer, roe deer,moose, and other domestic ruminants (1,2,5,7).
In vertebral host A.phagocytophilum infects granulocytes, and in tick midgut, hemocytes andsalivary glands are the targets (4,8). Anaplasma phagocytophilum is responsiblefor causing Human Granulocytic Anaplasmosis (HGA), which is known as atick-borne disease in the United States (2,4,5), Europe (2,4,5), Asia (2,5) andAfrica (4,5), and tick-borne fever (TBF) in small ruminants (2,7).
Accordingto the prior studies in endemic areas almost 30% population of human has been exposedto this potential pathogen. Since 1995 about 15,952 cases of HGA has beenreported worldwide. Although the no. of cases increased with a 12-fold rate in2001 to 2011 (9,10).
Inhumans, the symptoms of A. phagocytophilum infectionsinclude fever, headache, myalgias (1,7), arthralgias (1) and malaise (7) where as in manycases infections are asymptomatic. Nevertheless, HGA infections may perhapslead to acute illness and death in many immunocompromised individuals. (9) A. phagocytophilum’s lifecycle based on two morphological forms, the dense one; in which are infectiveand reticulated cells; which is a replicative stage.
The whole genome of A. phagocytophilum is comparativelysmall approximately 1.55 Mb with a less number of proteins in it (4) A. phagocytophilum hasdeveloped effective molecular mechanisms that help out it in causing infectionin ticks as well as in vertebral hosts that cooperatively work together in maintaininginfectivity, growth, persistence, and endurance of bacterium. These evolutionarystrategies comprise, remodeling of the cytoskeleton, inhibition of cellapoptosis, exploitation of the immune reaction, and utilization of proteins ofcause infection and exploitation of tick and vertebral host gene expression, butthe activity of A.
phagocytophilum are not limited to thesestrategies (5) A considerable factorfor powerful therapy against pathogenic diseases is the identification ofpotential drug targets and to achieve these targets Subtractive Proteomic approach is supposeto be an enlightening technique by which potential drug targets can be moreeasily identified, which are likely to be vital for a pathogen, but not foundin host (11). Objective of Study:The objective ofthis research is:· Toidentify A. phagocytophilum proteins,those play role in viability of bacterium. · To design potential drug against A.phagocytophilum,as A.
phagocytophilumcause infection in humans as well as animals but vaccines are not available forprevention and control of pathogenic infectionand transmission. Research Plan: In this study, by usingcomputational approaches based on Isolation of Bacterial sequence, BLAST-P, DEG analysis, CD-HIT and KAAS andKEGG analysis, we will identify specific drug targets. Furthermore,determination of virulent proteins, their druggability and secondarycharacteristics will help to select potential drug target which will subject toMolecular modeling then finally perform its Virtual screening todiscover putative drug against Anaplasma phagocytophilum. Methodology:v Stage I: Protein datasetsminingAnaplasmaphagocytophilum’s whole proteome sequence will recoverfrom the National Center for Biotechnology Information (NCBI) database in FASTAformat (12,13). v Stage II: Subtractive analysisIdentification of non-homologuesFor the identification of non-homologue in total of 1073 proteinsequences of A. phagocytophilum,NCBI Basic Local Alignment Search Tool protein(BLAST-P) analysis will carried out against Homo sapiens (13,14). Recognition ofBacterial essential genesSequences contain non homologues to Homo sapiens willsubject to DEG (Database of Essential Genes) analysis to separate out theessential bacterial protein sequences (12,15).
Elimination of ParalogsTo eliminate theparalogs or duplicate sequences, the recognized essential genes will forward toCD-HIT (Cluster Database at HighIdentity with Tolerance) web server. The parameters will remaindefault except the limit which will set to 60% sequence uniqueness (12,15). Elimination ofOrthologsProtein sequences obtained by CD-HIT will subject to KAAS (KEGG AutomaticAnnotation Server) analysis for the elimination of orthologs of Homo sapiens(13,16). Determination of Uniquepathways and their proteinsTo identify the unique pathways of A. phagocytophilumthat are unlikely to the Homo sapiens, KEGG Pathway (Kyoto Encyclopedia of Genes and Genomes) willperform.
Furthermore, non human ortholog sequences will subject to KEGG Mapperin order to identify proteins involve in unique pathways of pathogen (13,16). v Stage III: Characterization ofpotential target proteinsDetectionof Virulent proteinsVirulent Pred online analysis tool (i.e Position-specific iteratedBLAST to generate the possible matches with Position Specific Scoring Matrixalgorithm by five-fold cross-validation technique) will be done for therecognition of virulent proteins.
(18). Druggableproteins investigationTotal of 4323non-redundant protein sequences in DrugBank are present. Druggability of ourtarget proteins will study against all drug targets exist in DrugBank database.Potential targets will be select on the basis of bit score >100 and e-value<0.005 (14,15). Prediction of subcellular localizationLocalization ofdruggable proteins will be carried out by using any of the given online serverssuch as PSORTb (12,13), CELLO (12,13,17), PSLpred (17), and SOSUI (19).Molecularfeatures of target proteinProtParamProteomics server for molecular weight, isoelectric point, negatively andpositively charged amino acid residues, extinction coefficients, aliphaticindex, instability index, grand average of hydropathicity, where as TiedMixture Hidden Markov Model v2.0 server for presence of transmembrane helicalregions and SignalP v4.
1 server for the identification of signal peptides willbe used (17,21). Secondary structure predictionSelf-Optimized Prediction Method with Alignment server (SOPMA) willperform to identify the secondary characteristics of Target proteins (20).Homologymodeling and optimizationForhomology modeling, BlastP against PDB database will be carried out to discovera suitable template. In MODELLER 9.12 (13) by using python scripts, a 3D modelwill be generated which will further validate by Ramachandran plot (18), PROSA(12) and Procheck (13).Prediction of activesiteProtein domains perdition is considered to be critical and itsrecognition of 3D structural domains and active site residues is important toidentify the interaction of protein with other molecules.
Therefore, ComputedAtlas of Surface Topography of Proteins (CASTp) server and/or FTSite serverwill perform to identify active site residues (22).Virtualscreeningidockserver and /or AutoDock Vina will be utilized for Molecular docking analysis ofthe potential druggable target with then no. of ligands (12,15). Drug likeness of ligandsMolSoftserver (http://www.molsoft.
com/mprop/) and/or PubChem database (https://pubchem.ncbi.nlm.
nih.gov/)will be utilized to predict the drug likeness of possible ligands (18). References:1.
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