DoGSiteScorer: a web server for automatic binding site prediction, analysis and druggability assessment

Volkamer, Andrea; Kühn, Daniel; Rippmann, Friedrich; Rarey, Matthias

doi:10.1093/bioinformatics/bts310

Cited by 456 publications

(375 citation statements)

References 11 publications

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“…3) In silico protein cavity and active site prediction: AADS (Automated active site identification, docking and scoring from IIT Delhi) [19] an automated active site finder, 3DLigandSite [20] for predicting ligand binding sites and DoGSiteScorer [21] a server for automatic binding site prediction, analysis and druggability assessment were used.…”

Section: Materials and Methodmentioning

confidence: 99%

Understanding the Exacerbating Role of the Metalloproteinase Meprin during AKI, an In Silico Approach

Chatterjee

2016

ILNS

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Acute kidney injury (AKI) is a syndrome characterised by the rapid loss of the kidney's excretory function and is typically diagnosed by the accumulation of end products of nitrogen metabolism (urea and creatinine) or decreased urine output, or both. It is the clinical manifestation of several disorders that affect the kidney acutely. No specific therapies have yet emerged that can attenuate AKI or expedite recovery; thus, the only treatment is supportive therapies and intensive care. The present study was aimed to provide an insight into the importance of a metalloproteinase involved in the pathological conditions of AKI and potentially is a unique target for therapeutic intervention during the disease; Meprin. The data obtained using literature search from PubMed and interaction networks analysis software STRING strongly support the concept that meprin acts as a major matrix degrading enzyme in the kidney, and thus creating an environment that leads to impairment in cellular function rather than cellular stability in response to AKI. The present study discerns the structure of meprin alpha subunit using in silico tools SWISS-MODE, Phyre2 web server and identify the active site and critical amino acid residues in the active site using AADS (IIT Delhi), 3DLigandSite and DoGSiteScorer. Further it is documented that actinonin, a naturally occurring antibacterial agent as a pharmacologically active intervention for the metalloproteinase's α subunit by blocking its active sites from the environment which was validated using molecular docking algorithms of SWISS-DOCK and FlexX. INTRODUCTION:

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Section: Materials and Methodmentioning

confidence: 99%

Understanding the Exacerbating Role of the Metalloproteinase Meprin during AKI, an In Silico Approach

Chatterjee

2016

ILNS

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“…The obtained RMSD values indicated that in both cases, the models and the templates had similar folds. Analysis of putative binding pockets using DoGSiteScorer [59] Here, it should be noted that the presence of a binding pocket does not necessarily imply that a target protein is druggable. However, the binding volume is one of the important cavity properties that influence the druggability of a particular target protein, of which most of druggable proteins have volumes of between 500-1000 Å3 [60].…”

Section: Structural Modelingmentioning

confidence: 99%

Sarcocystis neurona Protein Kinases: Computational Identification, Evolutionary Analysis and Putative Inhibitor Docking

Murungi

Kariithi

2017

Preprint

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Abstract:The apicomplexan parasite, Sarcocystis neurona causes the degenerative neurological equine protozoal myeloencephalitis (EPM) disease of horses. Due to its host range expansion, S. neurona is an emerging threat that requires close monitoring. In apicomplexans, protein kinases (PKs) have been implicated in a myriad of critical functions such as host cell invasion, cell cycle progression and host immune responses evasion. Here, we used various bioinformatics methods to define the kinome of S. neurona and phylogenetic relatedness of its PKs to other apicomplexans. Further, three-dimensional (3D) homology models for selected S. neurona putative PKs were constructed and evaluated for inhibitor docking. We identified 92 putative PKs clustering within the AGC, CAMK, CK1, CMGC, STE, TKL, aPK and OPK groups. Although containing the universally conserved PKA (AGC group), S. neurona kinome was devoid of PKB and PKC, but contained the six apicomplexan conserved CDPKs (CAMK group). The OPK group was represented by ROPKs 19A, 27, 30, 33, 35 and 37, but was devoid of the virulence-associated ROPKs 5, 6, 18 and 38. Two out of the three S. neurona CK1 enzymes had high sequence similarities to T. gondii TgCK1-α and TgCK1-β and the Plasmodium PfCK1. Docking of four inhibitors onto homology models of putative ROP27 and PKA indicated that inhibition of S. neurona PKs is feasible, but needs to be experimentally tested. The essentiality of apicomplexan PKs makes the elucidation of S. neurona kinome a key milestone for development of novel therapeutics for EPM.

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“…Subsequently, it analyzes the geometric and physicochemical properties of these pockets and estimates druggability with aid of a support vector machine. Thus, the method provides valuable information for target assessment [9].…”

Section: Binding Pocket Predictionmentioning

confidence: 99%

In silico Characterization and Docking of ?-Conotoxin Mr1.7a from Conus marmoreus Targeting Neuronal nAChR ?3?2

2016

IJSR

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DoGSiteScorer: a web server for automatic binding site prediction, analysis and druggability assessment

Abstract: rarey@zbh.uni-hamburg.de.

Cited by 456 publications

References 11 publications

Understanding the Exacerbating Role of the Metalloproteinase Meprin during AKI, an <i>In Silico</i> Approach

Understanding the Exacerbating Role of the Metalloproteinase Meprin during AKI, an <i>In Silico</i> Approach

<em>Sarcocystis neurona</em> Protein Kinases: Computational Identification, Evolutionary Analysis and Putative Inhibitor Docking

In silico Characterization and Docking of ?-Conotoxin Mr1.7a from Conus marmoreus Targeting Neuronal nAChR ?3?2

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