Homology modeling meets site-directed mutagenesis: An ideal combination to elucidate the topology of 17β-HSD2
Graphical abstract
Introduction
Knowledge of the 3D-structure and binding site topology of an enzyme is an essential prerequisite for an effective structure-based drug design and the facilitated design of biochemical experiments.
17β-Hydroxysteroid dehydrogenase type 2 (17β-HSD2, EC1.1.1.51) [1,2] is a homodimeric enzyme, which belongs to the short-chain dehydrogenase/reductase (SDR) superfamily. The protein is localized in the endoplasmic reticulum, and its mRNA is widely expressed in various human peripheral tissues [[3], [4], [5], [6], [7]]. Using NAD+ as cofactor, 17β-HSD2 has a predominant 17β-oxidative activity catalyzing the conversion of highly active 17β-hydroxy forms of estrogens and androgens (i.e., estradiol (E2), testosterone (T), and dihydrotestosterone) into their less active keto forms (i.e., estrone (E1), Δ4-androstene-3,17-dione (Δ4-Ae), and 5α-androstanedione, respectively). Furthermore, the enzyme also possesses a 20α- and a weak 3β-oxidase activity [8].
Several research groups successfully characterized the substrate and cofactor specificities of 17β-HSD2 [9] and developed potent 17β-HSD2 inhibitors using ligand-based strategies [10]. In addition, Bagi et al. [11] have shown by in vivo experiments using a monkey model, that 17β-HSD2 inhibition leads to increasing E2 concentration in the bones and thus might be useful for the treatment of osteoporosis. This result was confirmed recently in a mouse and a rat model [12, 13].
However, only for some of all the 17β-HSD2 amino acid residues the role in enzyme functionality is evident: Ser219, Tyr232, and Lys236, for example, constitute the SDR-conserved catalytic triad [14], while Glu116 was reported as not being essential for the catalytic activity of 17β-HSD2 [9].
As 17β-HSD2 is strongly associated with the membrane of the endoplasmic reticulum [2] through its N-terminal end [15], purification of the full-length enzyme is very difficult and up to now, only one research group was able to successfully purify the full-length 17β-HSD2 in its enzymatically active form [2]. However, the 3D-crystal structure of 17β-HSD2 still remains unknown. This impedes structure-based drug design studies, limits a precise design of biochemical experiments, and prevents a structure comparison between 17β-HSD2 and already crystallized 17β-HSDs, an essential step for selectivity investigations.
Whereas Engeli et al. recently used a homology model approach to explain the mutation-based loss of function of 17β-HSD3 [16,17], the aim of the study here was to generate a good quality homology model of 17β-HSD2 to get insight in the enzyme's topology. For this, a broad set of 17β-HSD2 homology models was generated using automatized and manual multi-template approaches. Representative 17β-HSD2-NAD+-E2 ternary models were evaluated and a final refined 17β-HSD2 model could be obtained. Based on this model, functionally essential residues in the cofactor and substrate binding sites were identified and their role in the structure confirmed using mutant proteins generated by site-directed mutagenesis. The comparison of the biological activity of the wild type enzyme with the one of the mutants validated the very good quality of the 17β-HSD2 homology model.
Section snippets
Automatized homology modeling
The protein structures used in the automatized homology modeling are shown in Table S1 in Supporting Information. The automatized web-servers used for the 17β-HSD2 homology models were e.g., M4T v3.0, [18] I-tasser [19], MUSTER [20], MODELLER (accessible through the MPI Bioinformatics Toolkit) [21], SWISS-MODEL [22,23], or Yasara [24].
Multi-fragment “patchwork” approach homology modeling
The protein structures used in the multi-fragment homology modeling are shown in Table S2 in Supporting Information. All template 3D-structures were superimposed
Automatized homology modeling
A BLAST search against the PDB database for proteins related to human 17β-HSD2 revealed that the best hit within those being crystallized, was human 17β-HSD14, showing 33 % sequence identity, while the next top ten hits were microbial enzymes with sequence identities below 30 %. 17β-HSD2 homology models were generated after pairwise alignment and modeled using automatized web-servers based on threading- and multiple-template strategies. Several raw models with well-constructed Rossmann fold
Discussion
Using the multi-fragment “patchwork” homology modeling approach, we built a model for the human 17β-HSD2 enzyme and verified it using the known substrates E2 and T as well as inhibitor 1 in a docking study.
In order to prove postulated interactions and features of the model, selected mutants with single amino acid exchanges were generated and enzymatically analyzed with respect to E2 and T turnover. For most of the mutants the enzymatic activities observed were quite similar regardless of which
Conclusion
Homology modeling is a very useful tool to elucidate the topology of an enzyme when the 3D-structure of a protein is not available. By applying a multi-fragment "patchwork" homology modeling strategy, this study presents the first homology model of 17β-HSD2 in complex with the cofactor NAD+ and the substrate estradiol. Verification of postulated ligand-protein interactions by mutant analysis evidenced that the generated model is of very good quality and allows the identification of several key
Author contributions
SMO, SW, GM, and MN designed the study and the experiments. CS, MN, SW, GM, and PB performed the experiments and analyzed the data. CS, MN, SMO, RH, JA, SW, and GM wrote the manuscript.
All authors approved the final version of the manuscript.
CRediT authorship contribution statement
Christoph P. Sager: Methodology, Validation, Formal analysis, Writing - review & editing. Susanne Weber: Methodology, Formal analysis, Investigation, Writing - original draft, Writing - review & editing. Matthias Negri: Conceptualization, Methodology, Software, Investigation, Writing - original draft. Pauline Banachowicz: Investigation, Methodology, Resources. Gabriele Möller: Conceptualization, Validation, Investigation, Writing - original draft, Writing - review & editing. Jerzy Adamski:
Declaration of Competing Interest
The authors reported no declarations of interest.
Acknowledgments
This work was supported by the Deutsche Forschungsgemeinschaft (DFG), Germany. Grants numbers: HA1315/12-1 and AD 127/10-1. The authors thank Prof. Peter Kolb for reading the manuscript and helpful discussions concerning the homology model.
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These authors contributed equally to this work.