Computational Modelling of Dapsone Interaction With Dihydropteroate Synthase in Mycobacterium leprae; Insights Into Molecular Basis of Dapsone Resistance in Leprosy

Abstract

The molecular basis for determination of resistance to anti-leprosy drugs is the presence of point mutations within the genes of Mycobacterium leprae (M. leprae) that encode active drug targets. The downstream structural and functional implications of these point mutations on drug targets were scarcely studied. In this study, we utilized computational tools to develop native and mutant protein models for 5 point mutations at codon positions 53 and 55 in 6-hydroxymethyl-7, 8-dihydropteroate synthase (DHPS) of M. leprae, an active target for dapsone encoded by folp1 gene, that confer resistance to dapsone. Molecular docking was performed to identify variations in dapsone interaction with mutant DHPS in terms of hydrogen bonding, hydrophobic interactions, and energy changes. Schrodinger Suite 2014-3 was used to build homology models and in performing molecular docking. An increase in volume of the binding cavities of mutant structures was noted when compared to native form indicating a weakening in interaction (60.7 Å(3) in native vs. 233.6 Å(3) in Thr53Ala, 659.9 Å(3) in Thr53Ile, 400 Å(3) for Thr53Val, 385 Å(3) for Pro55Arg, and 210 Å(3) for Pro55Leu). This was also reflected by changes in hydrogen bonds and decrease in hydrophobic interactions in the mutant models. The total binding energy (ΔG) decreased significantly in mutant forms when compared to the native form (-51.92 Kcal/mol for native vs. -35.64, -35.24, -46.47, -47.69, and -41.36 Kcal/mol for mutations Thr53Ala, Thr53Ile, Thr53Val, Pro55Arg, and Pro55Leu, respectively. In brief, this analysis provided structural and mechanistic insights to the degree of dapsone resistance contributed by each of these DHPS mutants in leprosy.

Computer-aided synthesis of dapsone-phytochemical conjugates against dapsone-resistant Mycobacterium leprae

“…Point mutations in the folP1 gene-encoded DHPS, at codons 53 and 55 positions for Thr53 and Pro55, respectively ( Fig. 1), are characteristic molecular signatures of DDS-resistance 2,11,12 . Recently, rifampicin was reported to be ineffective against Ml 13,14 .…”

Molecular docking and simulation study for synthesis of alternative dapsone derivative as a newer antileprosy drug in multidrug therapy

“…5 In this study, five mutants, that is, three at 53 position (T53I, T53A, and T53V) and two at 55 position (P55R and P55L) were generated using BIOVIA DSV. 5 In this study, five mutants, that is, three at 53 position (T53I, T53A, and T53V) and two at 55 position (P55R and P55L) were generated using BIOVIA DSV.…”

“…14,15 Indeed, several potential compounds were predicted to be inactive; eventually, those are skipped, and active compounds determined computationally could be prioritized for synthesis. 5,20 The threedimensional structure of MlDHPS is not available in Protein Data Bank (PDB), therefore a rational three-dimensional structure was generated and validated by series of model validation parameters. Moreover, the advanced network-based (systems pharmacology) computational models and system biology are currently used in drug development.…”

“…1,2 Moreover, dapsone (4,4′-diaminodiphenylsulfone [DDS]), an analog of para-aminobenzoic acid, inhibits dihydropteroate synthase (DHPS) in thwarting the condensation of 6-hydroxymethyl-7,8-dihydropterinpyrophosphate for the synthesis of 7,8-dihydropteroate and pyrophosphate in the folic acid synthesis pathway of Ml. 3 Indeed, a point mutation in the DHPS confers resistance to dapsone, [4][5][6] encoded by the gene folp1 of Ml. 7 In detail, dapsone resistance in Ml had been indicated in codons 53 and 55, coding threonine (Thr53), and proline (Pro55).…”

“…Herein, MlDHPS served as the suitable target for the development of compatible antileprosy agent (s), because it is absent in eukaryotes. 5,20 The threedimensional structure of MlDHPS is not available in Protein Data Bank (PDB), therefore a rational three-dimensional structure was generated and validated by series of model validation parameters. Furthermore, the mode of recognition of DDs against wild-type (Wt) and mutant-type (Mt) of MlDHPSs was comprehensively explored through molecular docking attempts, molecular dynamic (MD) simulations, and binding free energy estimation for the synthesis of an effective DD.…”