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Insight into natural inhibitors and bridging docking to dynamic simulation against sugar Isomerase (SIS) domain protein

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Abstract

The pathogen Legionella longbeachae is a causative agent of legionellosis. The antibiotic resistance is the major problem of this modern world. Thus, selective pressure warrants the need for identification of newer drug target. In current study, subtractive proteomics approach screen out SIS (sugar isomerase) domain protein as an attractive receptor molecule for rational drug design. This protein is involved in lipopolysaccharide biosynthesis and catalyzes the isomerization of sedoheptulose 7-phosphate in d-glycero-d-manno-heptose 7-phosphate. Molecular docking revealed compound 1 (2-(6-(N,N-dimethyl sulfamoyl)pipridin-4-yl)pyrazin-2-yl)imidazol-3-ium-1-ide) as the potent inhibitor having GOLD fitness score of 69. The complex is affirmed by half-site effect via simulation analysis. Complex stability was investigated via several approaches that follows dynamic simulation and binding energies. Trajectory analysis revealed slight change in ring positioning of inhibitor inside the active pocket during 130 ns (nanosecond). Interestingly, it was affirmed via binding interactions’ density distribution. Hence, radial distribution function (RDF) inferred that SER55 and SER83 are the major residues that take part in hydrogen bonding and complex stability. Furthermore, an indigenously developed method axial frequency distribution (AFD) has revealed that ligand moved closer to the active site with both the residues SER55 and SER83 binding to the ligand. The phenomena was observed via rotating motion with respect to receptor center cavity. Thus, inhibitor movement towards allosteric site was observed at the end of simulations. Finally, binding free energy calculations by MMPB/GBSA predicts high compound affinity for the complex. Hence, findings from the current study will aid in the novel drug discovery and future experimental studies.

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Funding

This study was supported financially by Pak US STCP (2017/360) and Higher Education Commission (HEC), Pakistan.

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  1. Faisal Ahmad and Zartasha Shabaz contributed equally to this work.

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  1. Computational Biology Lab, National Center for Bioinformatics, Quaid-i-Azam University, Islamabad, Pakistan

    Faisal Ahmad, Zartasha Shabaz & Syed Sikander Azam

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  1. Faisal Ahmad
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Ahmad, F., Shabaz, Z. & Azam, S.S. Insight into natural inhibitors and bridging docking to dynamic simulation against sugar Isomerase (SIS) domain protein. J Mol Model 26, 221 (2020). https://doi.org/10.1007/s00894-020-04475-5

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