Mice deficient in Schnurri-3 (SHN3; also known as HIVEP3) display increased bone formation, but harnessing this observation for therapeutic benefit requires an improved understanding of how SHN3 functions in osteoblasts. Here we identified SHN3 as a dampener of ERK activity that functions in part downstream of WNT signaling in osteoblasts. A D-domain motif within SHN3 mediated the interaction with and inhibition of ERK activity and osteoblast differentiation, and knockin of a mutation in Shn3 that abolishes this interaction resulted in aberrant ERK activation and consequent osteoblast hyperactivity in vivo. Additionally, in vivo genetic interaction studies demonstrated that crossing to Lrp5 -/-mice partially rescued the osteosclerotic phenotype of Shn3 -/-mice; mechanistically, this corresponded to the ability of SHN3 to inhibit ERK-mediated suppression of GSK3β. Inducible knockdown of Shn3 in adult mice resulted in a high-bone mass phenotype, providing evidence that transient blockade of these pathways in adults holds promise as a therapy for osteoporosis. IntroductionAdult bone mass reflects the balance between production of bone by osteoblasts and resorption of bone by osteoclasts, and disturbance of this balance results in bone pathology such as osteoporosis. As osteoblasts have a limited ability to directly perceive the thickness of the bone they overlay, they rely on the ability to integrate extracellular cues to appropriately adjust the rate of bone formation. One such extracellular cue, the WNT/ β-catenin pathway, is well established as a positive regulator of osteoblast differentiation, appearing to divert early progenitors away from a chondrocyte fate into becoming osteoblasts (1, 2). Deletion or inhibition of individual WNT signaling components results in dysregulation of osteoblast activity and differentiation and, by extension, altered anabolic bone formation in mice (3). Under basal conditions, cytosolic β-catenin undergoes constitutive ubiquitination and proteasome-dependent degradation via the destruction complex that consists of adenomatous polyposis coli (APS), Axin, CK1α, and glycogen synthase kinase 3-β (GSK3β) (4). A subset of ligands of the WNT family binds to the 7-pass transmembrane receptor Frizzled and the single-pass low-density lipoprotein receptor-related protein 5 (LRP5) or LRP6. This inhibits the constitutive phosphorylation of β-catenin by GSK3β, which in turn prevents β-catenin ubiquitination and proteasome-dependent degradation. Subsequently, β-catenin translocates into the nucleus to activate its transcrip-

Active sites may be regarded as layers of residues, whereby the residues that interact directly with substrate also interact with residues in a second shell, and these in turn interact with residues in a third shell. These residues in the second and third layers may have distinct roles in maintaining the essential chemical properties of the first-shell catalytic residues, particularly their spatial arrangement relative to the substrate binding pocket, and their electrostatic and dynamic properties. The extent to which these remote residues participate in catalysis and precisely how they affect first-shell residues remains unexplored. In order to better understand the roles of second- and third-shell residues in catalysis, we used THEMATICS to identify residues in the second- and third-shells of the Co-type nitrile hydratase from Pseudomonas putida (ppNHase) that may be important for catalysis. Five of these predicted residues, plus three additional, conserved residues that were not predicted, have been conservatively mutated, and their effects studied both kinetically and structurally. All of these eight residues have no direct contact with the active site metal ion or bound substrate. These results demonstrate that three of the predicted second-shell residues, α-Asp164, β-Glu56, and β-His147, and one predicted third-shell residue β-His71, have significant effects on the catalytic efficiency of the enzyme. One of the predicted residues, α-Glu168, and the three residues not predicted, α-Arg170, α-Tyr171, and β-Tyr215, do not show any significant effects on the catalytic efficiency of the enzyme.

Understanding the catalytic efficiency and specificity of enzymes is a fundamental question of major practical and conceptual importance in biochemistry. Although progress in biochemical and structural studies has enriched our knowledge of enzymes, the role in enzyme catalysis of residues that are not nearest neighbors of the reacting substrate molecule is largely unexplored experimentally. Here computational active site predictors, THEMATICS and POOL, were employed to identify functionally important residues that are not in direct contact with the reacting substrate molecule. These predictions then guided experiments to explore the active sites of two isomerases, Pseudomonas putida ketosteroid isomerase (KSI) and human phosphoglucose isomerase (PGI), as prototypes for very different types of predicted active sites. Both KSI and PGI are members of EC 5.3 and catalyze similar reactions, but they represent significantly different degrees of remote residue participation, as predicted by THEMATICS and POOL. For KSI, a compact active site of mostly first-shell residues is predicted, but for PGI, an extended active site in which residues in the first, second, and third layers around the reacting substrate are predicted. Predicted residues that have not been previously tested experimentally were investigated by site-directed mutagenesis and kinetic analysis. In human PGI, single-point mutations of the predicted second- and third-shell residues K362, H100, E495, D511, H396, and Q388 show significant decreases in catalytic activity relative to that of the wild type. The results of these experiments demonstrate that, as predicted, remote residues are very important in PGI catalysis but make only small contributions to catalysis in KSI.

A scoring method for the prediction of catalytically important residues in enzyme structures is presented and used to examine the participation of distal residues in enzyme catalysis. Scores are based on the Partial Order Optimum Likelihood (POOL) machine learning method, using computed electrostatic properties, surface geometric features, and information obtained from the phylogenetic tree as input features. Predictions of distal residue participation in catalysis are compared with experimental kinetics data from the literature on variants of the featured enzymes; some additional kinetics measurements are reported for variants of Pseudomonas putida nitrile hydratase (ppNH) and for Escherichia coli alkaline phosphatase (AP). The multilayer active sites of P. putida nitrile hydratase and of human phosphoglucose isomerase are predicted by the POOL log ZP scores, as is the single-layer active site of P. putida ketosteroid isomerase. The log ZP score cutoff utilized here results in over-prediction of distal residue involvement in E. coli alkaline phosphatase. While fewer experimental data points are available for P. putida mandelate racemase and for human carbonic anhydrase II, the POOL log ZP scores properly predict the previously reported participation of distal residues.