The stem cell factor (SCF)/c-Kit receptor tyrosine kinase complex—with its significant roles in hematopoiesis and angiogenesis—is an attractive target for rational drug design. There is thus a need to map, in detail, the SCF/c-Kit interaction sites and the mechanisms that modulate this interaction. While most residues in the direct SCF/c-Kit binding interface can be identified from the existing crystal structure of the complex, other residues that affect binding through protein unfolding, intermolecular interactions, allosteric or long-distance electrostatic effects cannot be directly inferred. Here, we describe an efficient method for protein-wide epitope mapping using yeast surface display. A library of single SCF mutants that span the SCF sequence was screened for decreased affinity to soluble c-Kit. Sequencing of selected clones allowed the identification of mutations that reduce SCF binding affinity to c-Kit. Moreover, the screening of these SCF clones for binding to a structural antibody helped identify mutations that result in small or large conformational changes in SCF. Computational modeling of the experimentally identified mutations showed that these mutations reduced the binding affinity through one of the three scenarios: through SCF destabilization, through elimination of favorable SCF/c-Kit intermolecular interactions, or through allosteric changes. Eight SCF variants were expressed and purified. Experimentally measured in vitro binding affinities of these mutants to c-Kit confirmed both the yeast surface display selection results and the computational predictions. This study has thus identified the residues crucial for c-Kit/SCF binding and has demonstrated the advantages of using a combination of computational and combinatorial methods for epitope mapping.
Bibliographical noteFunding Information:
We are grateful to Jason Shirian for helpful comments on the manuscript. The authors thank Dr. Alon Zilka for his technical assistance. FACS and Proteon experiments were performed at the NIBN proteomics unit. This work was supported by the European Research Council “Ideas program” ERC-2013-StG (contract grant number: 336041) to Niv Papo. Julia M. Shifman acknowledges the support from the Israel Science Foundation (1873/15). Mickey Kosloff acknowledges the support by grants from the Israel Science Foundation (grant numbers 1454/13, 1959/13, and 2155/15) and from the Ministry of Science, Technology and Space, Israel, and the Ministry of Foreign affairs, Italy (3-10704).
© 2016 Elsevier Ltd
- binding affinity
- combinatorial selection
- computational protein design
- protein engineering
- protein–protein interactions