Specificity of Molecular Fragments Binding to S100B versus S100A1 as Identified by NMR and Site Identification by Ligand Competitive Saturation (SILCS)
Department of Biochemistry and Molecular Biology, University of Maryland School of Medicine, 108 N. Greene St., Baltimore, MD 21201, USA
Center for Biomolecular Therapeutics (CBT), Baltimore, MD 21201, USA
Computer-Aided Drug Design Center, Department of Pharmaceutical Sciences, School of Pharmacy, University of Maryland, Baltimore, MD 21201, USA
Institute for Bioscience and Biotechnology Research (IBBR), Rockville, MD 20850, USA
Author to whom correspondence should be addressed.
Academic Editor: Brullo Chiara
Molecules 2021, 26(2), 381; https://doi.org/10.3390/molecules26020381
Received: 22 December 2020 / Revised: 8 January 2021 / Accepted: 9 January 2021 / Published: 13 January 2021
(This article belongs to the Special Issue Implication of S100 Proteins in Inflammation and Cancer: S100 Proteins as Potential Pharmacological Targets)
S100B, a biomarker of malignant melanoma, interacts with the p53 protein and diminishes its tumor suppressor function, which makes this S100 family member a promising therapeutic target for treating malignant melanoma. However, it is a challenge to design inhibitors that are specific for S100B in melanoma versus other S100-family members that are important for normal cellular activities. For example, S100A1 is most similar in sequence and structure to S100B, and this S100 protein is important for normal skeletal and cardiac muscle function. Therefore, a combination of NMR and computer aided drug design (CADD) was used to initiate the design of specific S100B inhibitors. Fragment-based screening by NMR, also termed “SAR by NMR,” is a well-established method, and was used to examine spectral perturbations in 2D [1H, 15N]-HSQC spectra of Ca2+-bound S100B and Ca2+-bound S100A1, side-by-side, and under identical conditions for comparison. Of the 1000 compounds screened, two were found to be specific for binding Ca2+-bound S100A1 and four were found to be specific for Ca2+-bound S100B, respectively. The NMR spectral perturbations observed in these six data sets were then used to model how each of these small molecule fragments showed specificity for one S100 versus the other using a CADD approach termed Site Identification by Ligand Competitive Saturation (SILCS). In summary, the combination of NMR and computational approaches provided insight into how S100A1 versus S100B bind small molecules specifically, which will enable improved drug design efforts to inhibit elevated S100B in melanoma. Such a fragment-based approach can be used generally to initiate the design of specific inhibitors for other highly homologous drug targets.