Cystatin B and SOD1: Protein–Protein Interaction and Possible Relation to Neurodegeneration

Cystatin B (CSTB), an inhibitor of the cysteine proteases, belongs to the cathepsin family and it is known to interact with a number of proteins involved in cytoskeletal organization. CSTB has an intrinsic tendency to form aggregates depending on the redox environment. The gene encoding for CSTB is frequently mutated in association with the rare neurodegenerative condition progressive myoclonus epilepsy. Increased levels of CSTB have been observed in the spinal cord of transgenic mice modeling SOD1-linked familial amyotrophic lateral sclerosis, a fatal neurodegenerative disease affecting motoneurons. In the present study, we have investigated the relationship occurring between the expression of SOD1 and CSTB either wild-type or double-cysteine substitution mutant (Cys 3 and Cys 64). Whether or not there is a physical interaction between the two proteins was also investigated in overexpression experiments using a human neuroblastoma cell line and mouse-immortalized motoneurons. Here we report evidences for a reciprocal influence of CSTB and SOD1 at the gene expression level and for a direct interaction of the two proteins.     

Heat Shock Protein 90-α Mediates Aldo-Keto Reductase 1B10 (AKR1B10) Protein Secretion through Secretory Lysosomes

Aldo-keto reductase 1B10 (AKR1B10) protein is a new tumor biomarker in humans. Our previous studies have shown that AKR1B10 is secreted through a lysosome-mediated nonclassical pathway, leading to an increase in the serum of breast cancer patients. This study illuminates the regulatory mechanism of AKR1B10 secretion. The cytosolic AKR1B10 associates with and is translocated to lysosomes by heat shock protein 90α (HSP90α), a chaperone molecule. Ectopic expression of HSP90α significantly increased the secretion of endogenous AKR1B10 and exogenous GFP-AKR1B10 fusion protein when cotransfected. Geldanamycin, a HSP90α inhibitor, dissociated AKR1B10-HSP90α complexes and significantly reduced AKR1B10 secretion in a dose-dependent manner. We characterized the functional domain in AKR1B10 and found that helix 10 (amino acids 233–240), located at the C terminus, regulates AKR1B10 secretion. Targeted point mutations recognized that amino acids Lys-233, Glu-236, and Lys-240 in helix 10 mediate the interaction of AKR1B10 with HSP90α. Together, our data suggest that HSP90α mediates AKR1B10 secretion through binding to its helix 10 domain. This finding is significant in exploiting the use of AKR1B10 in cancer clinics.     

Nix Protein Positively Regulates NF-��B Activation in Gliomas

Previous reports indicate that the NIX/BNIP3L gene acts as a pro-apoptotic factor by interacting with BCL2 and BCL-XL, playing an important role in hypoxia-dependent cell death and acting as a tumor suppressor. However, many studies also showed that NIX is linked to a protective role and cell survival in cancer cells. Nuclear factor-κB (NF-κB) can attenuate apoptosis in human cancers in response to chemotherapeutic agents and ionizing radiation. We observed an absence of i-κBα (NF-κB activation inhibitor) expression, but a greater expression of Nix and p-NF-κB proteins in the Nix-wt U251 cells, which was not observed in the Nix-kn cells under hypoxic conditions. Using electrophoretic mobility shift assay (EMSA) and luciferase detection, the activation of NF-κB was detected only in the Nix-wt U251 cells with hypoxia. These data imply that Nix protein might play a role in the positive regulation of the NF-κB pathway. Moreover, 46 cases of glioma also showed high levels of Nix protein expression, which was always accompanied by high p-NF-κB expression. Patients with Nix (+) showed less tissue apoptosis behavior in glioblastoma (GBM), unlike that observed in the Nix-negative patients (−). The same apoptotic tendency was also identified in anaplastic astrocytoma (AA) groups, but not in astrocytoma (AS). On analyzing the Kaplan-Meier curve, better tumor-free survival was observed only in cases of astrocytoma, and not in AA and GBM. Thus, our study indicates that Nix protein might have multiple functions in regulating glioma behaviors. In the low-grade gliomas (astrocytoma) with low expression of NF-κB, the cell death-inducing function that occurs through a Bax mechanism might predominate and act as a tumor suppressor. While in the malignant gliomas (AA and GBM), with higher expression of the NIX gene and with activity of the NF-κB pathway, the oncogene function of Nix was predominant.     

Characterization of Protein–Protein Interfaces

We analyze the characteristics of protein–protein interfaces using the largest datasets available from the Protein Data Bank (PDB). We start with a comparison of interfaces with protein cores and non-interface surfaces. The results show that interfaces differ from protein cores and non-interface surfaces in residue composition, sequence entropy, and secondary structure. Since interfaces, protein cores, and non-interface surfaces have different solvent accessibilities, it is important to investigate whether the observed differences are due to the differences in solvent accessibility or differences in functionality. We separate out the effect of solvent accessibility by comparing interfaces with a set of residues having the same solvent accessibility as the interfaces. This strategy reveals residue distribution propensities that are not observable by comparing interfaces with protein cores and non-interface surfaces. Our conclusions are that there are larger numbers of hydrophobic residues, particularly aromatic residues, in interfaces, and the interactions apparently favored in interfaces include the opposite charge pairs and hydrophobic pairs. Surprisingly, Pro-Trp pairs are over represented in interfaces, presumably because of favorable geometries. The analysis is repeated using three datasets having different constraints on sequence similarity and structure quality. Consistent results are obtained across these datasets. We have also investigated separately the characteristics of heteromeric interfaces and homomeric interfaces.     

Predicting Protein–Protein Interfaces that Bind Intrinsically Disordered Protein Regions

A long-standing goal in biology is the complete annotation of function and structure on all protein–protein interactions, a large fraction of which is mediated by intrinsically disordered protein regions (IDRs). However, knowledge derived from experimental structures of such protein complexes is disproportionately small due, in part, to challenges in studying interactions of IDRs. Here, we introduce IDRBind, a computational method that by combining gradient boosted trees and conditional random field models predicts binding sites of IDRs with performance approaching state-of-the-art globular interface predictions, making it suitable for proteome-wide applications. Although designed and trained with a focus on molecular recognition features, which are long interaction-mediating-elements in IDRs, IDRBind also predicts the binding sites of short peptides more accurately than existing specialized predictors. Consistent with IDRBind's specificity, a comparison of protein interface categories uncovered uniform trends in multiple physicochemical properties, positioning molecular recognition feature interfaces between peptide and globular interfaces.     

Protein–Protein and Protein–Membrane Associations in the Lignin Pathway

Supramolecular organization of enzymes is proposed to orchestrate metabolic complexity and help channel intermediates in different pathways. Phenylpropanoid metabolism has to direct up to 30% of the carbon fixed by plants to the biosynthesis of lignin precursors. Effective coupling of the enzymes in the pathway thus seems to be required. Subcellular localization, mobility, protein–protein, and protein–membrane interactions of four consecutive enzymes around the main branch point leading to lignin precursors was investigated in leaf tissues of Nicotiana benthamiana and cells of Arabidopsis thaliana. CYP73A5 and CYP98A3, the two Arabidopsis cytochrome P450s (P450s) catalyzing para- and meta-hydroxylations of the phenolic ring of monolignols were found to colocalize in the endoplasmic reticulum (ER) and to form homo- and heteromers. They moved along with the fast remodeling plant ER, but their lateral diffusion on the ER surface was restricted, likely due to association with other ER proteins. The connecting soluble enzyme hydroxycinnamoyltransferase (HCT), was found partially associated with the ER. Both HCT and the 4-coumaroyl-CoA ligase relocalized closer to the membrane upon P450 expression. Fluorescence lifetime imaging microscopy supports P450 colocalization and interaction with the soluble proteins, enhanced by the expression of the partner proteins. Protein relocalization was further enhanced in tissues undergoing wound repair. CYP98A3 was the most effective in driving protein association.     

Computational Prediction of Protein–Protein Interactions

Recently a number of computational approaches have been developed for the prediction of protein–protein interactions. Complete genome sequencing projects have provided the vast amount of information needed for these analyses. These methods utilize the structural, genomic, and biological context of proteins and genes in complete genomes to predict protein interaction networks and functional linkages between proteins. Given that experimental techniques remain expensive, time-consuming, and labor-intensive, these methods represent an important advance in proteomics. Some of these approaches utilize sequence data alone to predict interactions, while others combine multiple computational and experimental datasets to accurately build protein interaction maps for complete genomes. These methods represent a complementary approach to current high-throughput projects whose aim is to delineate protein interaction maps in complete genomes. We will describe a number of computational protocols for protein interaction prediction based on the structural, genomic, and biological context of proteins in complete genomes, and detail methods for protein interaction network visualization and analysis.     

Protein 4.1B in mouse islets of Langerhans and β-cell tumorigenesis

Protein 4.1 family proteins are thought to interact with membrane proteins and membrane skeletons. Immunohistochemical studies by light and electron microscopy were performed on mouse pancreas with a specific antibody against protein 4.1B. Specific protein 4.1B immunolabeling was observed on endocrine cells in the islets of Langerhans. Protein 4.1B localized along the plasma membranes facing adjacent cells. By immunoelectron microscopy, the immunolabeling of the cells was restricted to the cytoplasmic side just beneath their plasma membrane, including the membranes adjacent to neighboring cells, while the plasma membranes facing endothelial cells were not immunolabeled for protein 4.1B. The immunolocalization of E-cadherin was similar, if not identical, to that of protein 4.1B supporting the idea that protein 4.1B may be functionally interconnected with adhesion molecules. In a transgenic mouse model of pancreatic -cell carcinogenesis (Rip1Tag2), the loss of protein 4.1B expression coincided with the phenotypic transition from adenoma to carcinoma. Therefore, we propose a role of protein 4.1B as a connecting and/or signaling molecule between membrane architecture, cell adhesion, and tumor cell invasion in mouse pancreatic endocrine cells.     

Protein–Protein Interactions in DNA Base Excision Repair

The system of base excision repair (BER) ensures correction of the most abundant DNA damages in mammalian cells and plays an important role in maintaining genome stability. Enzymes and protein factors participate in the multistage BER in a coordinated fashion, which ensures repair efficiency. The suggested coordination mechanisms are based on formation of protein complexes stabilized via either direct or indirect DNA-mediated interactions. The results of investigation of direct interactions of the proteins participating in BER with each other and with other proteins are outlined in this review. The known protein partners and sites responsible for their interaction are presented for the main participants as well as quantitative characteristics of their affinity. Information on the mechanisms of regulation of protein–protein interactions mediated by DNA intermediates and posttranslational modification is presented. It can be suggested based on all available data that the multiprotein complexes are formed on chromatin independent of the DNA damage with the help of key regulators of the BER process – scaffold protein XRCC1 and poly(ADP-ribose) polymerase 1. The composition of multiprotein complexes changes dynamically depending on the DNA damage and the stage of BER process.     

The NF-κB RelB Protein Is an Oncogenic Driver of Mesenchymal Glioma

High-grade gliomas, such as glioblastomas (GBMs), are very aggressive, invasive brain tumors with low patient survival rates. The recent identification of distinct glioma tumor subtypes offers the potential for understanding disease pathogenesis, responses to treatment and identification of molecular targets for personalized cancer therapies. However, the key alterations that drive tumorigenesis within each subtype are still poorly understood. Although aberrant NF-κB activity has been implicated in glioma, the roles of specific members of this protein family in tumorigenesis and pathogenesis have not been elucidated. In this study, we show that the NF-κB protein RelB is expressed in a particularly aggressive mesenchymal subtype of glioma, and loss of RelB significantly attenuated glioma cell survival, motility and invasion. We find that RelB promotes the expression of mesenchymal genes including YKL-40, a marker of the MES glioma subtype. Additionally, RelB regulates expression of Olig2, a regulator of cancer stem cell proliferation and a candidate marker for the cell of origin in glioma. Furthermore, loss of RelB in glioma cells significantly diminished tumor growth in orthotopic mouse xenografts. The relevance of our studies for human disease was confirmed by analysis of a human GBM genome database, which revealed that high RelB expression strongly correlates with rapid tumor progression and poor patient survival rates. Thus, our findings demonstrate that RelB is an oncogenic driver of mesenchymal glioma tumor growth and invasion, highlighting the therapeutic potential of inhibiting the noncanonical NF-κB (RelB-mediated) pathway to treat these deadly tumors.     

Vitamin D Receptor Inhibits Nuclear Factor κB Activation by Interacting with IκB Kinase β Protein

1,25-Dihydroxyvitamin D (1,25(OH)₂D₃) is known to suppress NF-κB activity, but the underlying mechanism remains poorly understood. Here we show that the vitamin D receptor (VDR) physically interacts with IκB kinase β (IKKβ) to block NF-κB activation. 1,25(OH)₂D₃ rapidly attenuates TNFα-induced p65 nuclear translocation and NF-κB activity in a VDR-dependent manner. VDR overexpression inhibits IKKβ-induced NF-κB activity. GST pull-down assays and coimmunoprecipitation experiments demonstrated that VDR physically interacts with IKKβ and that this interaction is enhanced by 1,25(OH)₂D₃. Protein mapping reveals that VDR-IKKβ interaction occurs between the C-terminal portions of the VDR and IKKβ proteins. Reconstitution of VDR^−/− cells with the VDR C terminus restores the ability to block TNFα-induced NF-κB activation and IL-6 up-regulation. VDR-IKKβ interaction disrupts the formation of the IKK complex and, thus, abrogates IKKβ phosphorylation at Ser-177 and abolishes IKK activity to phosphorylate IκBα. Consequently, stabilization of IκBα arrests p65/p50 nuclear translocation. Together, these data define a novel mechanism whereby 1,25(OH)₂D₃-VDR inhibits NF-κB activation.     

Cathepsin B Degrades Amyloid-β in Mice Expressing Wild-type Human Amyloid Precursor Protein

Accumulation of amyloid-β (Aβ), believed to be a key trigger of Alzheimer disease (AD), could result from impaired clearance mechanisms. Previously, we showed that the cysteine protease cathepsin B (CatB) degrades Aβ, most likely by C-terminal truncation, in mice expressing human amyloid precursor protein with familial AD-linked mutations (hAPP_FAD). In addition, the Aβ-degrading activity of CatB is inhibited by its endogenous inhibitor, cystatin C (CysC). Reducing CysC expression markedly lowers Aβ levels by enhancing CatB-mediated Aβ degradation in hAPP_FAD mice. However, because a vast majority of AD patients do not carry familial mutations, we investigated how the CysC-CatB axis affects Aβ levels in mice expressing wild-type hAPP (hAPP_WT). Enhancing CatB activity by CysC deletion significantly lowered total Aβ and Aβ42 levels in hAPP_WT mice, whereas CatB deletion increased Aβ levels. To determine whether neuron-derived CatB degrades Aβ in vivo, we generated transgenic mice overexpressing CatB under the control of a neuron-specific enolase promoter. Enhancing neuronal CatB activity in hAPP_WT mice significantly lowered Aβ42 levels. The processing of hAPP_WT was unaffected by increasing or ablating CatB activity. Thus, the CysC-CatB axis affects degradation of Aβ42 derived from hAPP lacking familial mutations. These findings support the notion that enhancing CatB activity could lower Aβ, especially Aβ42, in AD patients with or without familial mutations.     

A Critical Assessment of Information-guided Protein–Protein Docking Predictions

The structures of protein complexes are increasingly predicted via protein–protein docking (PPD) using ambiguous interaction data to help guide the docking. These data often are incomplete and contain errors and therefore could lead to incorrect docking predictions. In this study, we performed a series of PPD simulations to examine the effects of incompletely and incorrectly assigned interface residues on the success rate of PPD predictions. The results for a widely used PPD benchmark dataset obtained using a new interface information-driven PPD (IPPD) method developed in this work showed that the success rate for an acceptable top-ranked model varied, depending on the information content used, from as high as 95% when contact relationships (though not contact distances) were known for all residues to 78% when only the interface/non-interface state of the residues was known. However, the success rates decreased rapidly to ∼40% when the interface/non-interface state of 20% of the residues was assigned incorrectly, and to less than 5% for a 40% incorrect assignment. Comparisons with results obtained by re-ranking a global search and with those reported for other data-guided PPD methods showed that, in general, IPPD performed better than re-ranking when the information used was more complete and more accurate, but worse when it was not, and that when using bioinformatics-predicted information on interface residues, IPPD and other data-guided PPD methods performed poorly, at a level similar to simulations with a 40% incorrect assignment. These results provide guidelines for using information about interface residues to improve PPD predictions and reveal a bottleneck for such improvement imposed by the low accuracy of current bioinformatic interface residue predictions.Proteins work in close association with other proteins to mediate the intricate functions of a cell. The atomic resolution of the structure of a protein complex can therefore help one understand a protein''s function in detail. Protein–protein docking (PPD),¹ a computational approach that complements experimental structure determinations, has attracted increasing research interest (1, 2), in part because it remains challenging to determine most structures of protein complexes via experimental techniques (3).To improve the performance of PPD predictions, experimentally derived data (e.g. distances) and information (e.g. the identity of interface residues) have been used either as a filter allowing less plausible docking solutions to be disregarded (4–9) or as a constraint to guide the docking process (10, 11). Various types of data and information have been used to aid PPD (12); these range from distances between, or the relative orientation of, the two interacting proteins to simple identification of the amino acid residues directly involved in the binding of the two proteins (13). Despite considerable success, the caveat for all these data-guided PPD predictions is that the data or information used must be correct in order to avoid spurious results caused by misguiding (12). It is therefore pertinent and important to evaluate the effects of errors in the incorporated data or information on the quality of PPD solutions.We have recently shown that the use of just a few distance constraints can improve the success rates of PPD such that they rival, or are even better than, those of a global search ranked using a sophisticated energy function, and that errors in the distance data significantly decrease the success rates of prediction (11). However, because distance data for interacting proteins are usually hard to obtain, other types of data or information, even if “ambiguous” (10), are increasingly used in PPD predictions (12, 14). In this study, we investigated the effects of incompletely and incorrectly assigned interface/non-interface residues, a major source of the so-called ambiguous data, on information-guided PPD predictions.As illustrated in Fig. 1, the information content of interface/non-interface residues can be rich enough to reveal the identity of every pair of residues in contact, but not their contact distances, or so poor as to reveal the interface/non-interface state of these residues but not their pairing relationship, for one or both of the two interacting proteins. To determine how these different levels of residue information content can help PPD predictions and the extent to which the use of incorrectly assigned residues degrades prediction success rates, we have developed a new interface information-driven PPD method (IPPD) and carried out a series of PPD simulations on a well-tested benchmark dataset. The results showed that when the information content was rich, excellent predictions (success rates for producing an acceptable top-ranked model > 70%) could be made via IPPD or by re-ranking a global search''s solutions using the same interface information, and that, encouragingly, the success of predictions remained respectable (top-ranked success rates > 15%) when the content was poor. However, when enough of the interface residues were incorrectly assigned, as would be the case when using interface residues predicted by a state-of-the-art bioinformatics method such as CPORT (15), few models ranked first by IPPD or other PPD methods, including HADDOCK (10), a popular ambiguous data-driven PPD method, came close to being acceptable. These results suggest that we can greatly increase the power of PPD predictions for practical applications only if the accuracy of current bioinformatics methods for predicting the interface residues of protein complexes can be significantly improved.Open in a separate windowFig. 1.Contact matrix of two interacting proteins, A and B, and the contact vectors of their residues. In the contact matrix, M_ij = 1 or 0, respectively, denotes contact or a lack of contact between residue i in protein A and residue j in protein B. In the contact vectors, V_Ai = 1 or 0, respectively, when residue Ai has, or does not have, at least one contact with any residue of protein B.     

Degradation of Amyloid �� Protein by Purified Myelin Basic Protein

The progressive accumulation of β-amyloid (Aβ) in senile plaques and in the cerebral vasculature is the hallmark of Alzheimer disease and related disorders. Impaired clearance of Aβ from the brain likely contributes to the prevalent sporadic form of Alzheimer disease. Several major pathways for Aβ clearance include receptor-mediated cellular uptake, blood-brain barrier transport, and direct proteolytic degradation. Myelin basic protein (MBP) is the major structural protein component of myelin and plays a functional role in the formation and maintenance of the myelin sheath. MBP possesses endogenous serine proteinase activity and can undergo autocatalytic cleavage liberating distinct fragments. Recently, we showed that MBP binds Aβ and inhibits Aβ fibril formation (Hoos, M. D., Ahmed, M., Smith, S. O., and Van Nostrand, W. E. (2007) J. Biol. Chem. 282, 9952–9961; Hoos, M. D., Ahmed, M., Smith, S. O., and Van Nostrand, W. E. (2009) Biochemistry 48, 4720–4727). Here we show that Aβ40 and Aβ42 peptides are degraded by purified human brain MBP and recombinant human MBP, but not an MBP fragment that lacks autolytic activity. MBP-mediated Aβ degradation is inhibited by serine proteinase inhibitors. Similarly, Cos-1 cells expressing MBP degrade exogenous Aβ40 and Aβ42. In addition, we demonstrate that purified MBP also degrades assembled fibrillar Aβ in vitro. Mass spectrometry analysis identified distinct degradation products generated from Aβ digestion by MBP. Lastly, we demonstrate in situ that purified MBP can degrade parenchymal amyloid plaques as well as cerebral vascular amyloid that form in brain tissue of Aβ precursor protein transgenic mice. Together, these findings indicate that purified MBP possesses Aβ degrading activity in vitro.The progressive accumulation of β-amyloid (Aβ)³ in senile/neuritic plaques and the cerebral vasculature is the hallmark of Alzheimer disease (AD) and is widely used in the pathological diagnosis of the disease. Aβ is generated by proteolytic cleavage of amyloid precursor protein (APP) by β-secretase and γ-secretase (1, 2). The main species of Aβ are 40 and 42 amino acids in length. Aβ42 is much more amyloidogenic than Aβ40 because of its two additional hydrophobic amino acids at the carboxyl-terminal end of the peptide (3). The Aβ42 peptide is the predominant form in senile plaques, forming a β-sheet structure, which is insoluble and resistant to proteolysis.Although increased production of Aβ has been implicated in the onset of familial forms of AD, it has been hypothesized that the more common sporadic forms of AD may be caused by the impaired clearance of Aβ peptides from the CNS. Several major pathways for Aβ clearance have been proposed including receptor-mediated cellular uptake, blood-brain barrier transport into the circulation, and direct proteolytic degradation (4–6). In the latter case, several proteinases or peptidases have been identified that are capable of degrading Aβ, including neprilysin (7, 8), insulin-degrading enzyme (9), the urokinase/tissue plasminogen activator-plasmin system (10), endothelin-converting enzyme (11), angiotensin-converting enzyme (12), gelatinase A (matrix metalloproteinase-2) (13, 14), gelatinase B (matrix metalloproteinase-9) (15), and acylpeptide hydrolase (16). Each of these enzymes has been shown to cleave Aβ peptides at multiple sites (5). However, only neprilysin, insulin-degrading enzyme, endothelin-converting enzyme, and matrix metalloproteinase-9 have been shown to have a significant role in regulating Aβ levels in the brains of experimental animal models (8, 17, 18).The “classic” myelin basic proteins (MBP) are major structural components of myelin sheaths accounting for 30% of total myelin protein. There are four different major isoforms generated from alternative splicing with molecular masses of 17.3, 18.5, 20.2, and 21.5 kDa. The 18.5-kDa variant, composed of 180 amino acids including 19 Arg and 12 Lys basic residues, is most abundant in mature myelin (19). One of the major functions of MBP is to hold together the cytoplasmic leaflets of myelin membranes to maintain proper compaction of the myelin sheath through the electrostatic interaction between the positive Arg and Lys residues of MBP and the negatively charged phosphate groups of the membrane lipid (20). MBP plays an important role in the pathology of multiple sclerosis, which is an autoimmune disease characterized by demyelination within white matter (21). Recently, it was reported that purified MBP exhibits autocleavage activity, generating distinct peptide fragments (22). In this study, serine 151 was reported as the active site serine residue involved in autocatalysis.In the early stages of AD, appreciable and diffuse myelin breakdown in the white matter is observed (23). Also, in white matter regions there are much fewer fibrillar amyloid deposits than are commonly found in gray matter regions. Recently, our laboratory has shown that MBP strongly interacts with Aβ peptides and prevents their assembly into mature amyloid fibrils (24, 25). Through the course of these studies we observed that upon longer incubations the levels of Aβ peptides were reduced upon treatment with MBP. In light of this observation, coupled with the report that MBP possesses proteolytic activity, we hypothesized that MBP may degrade Aβ peptides. In the present study, we show that purified human brain MBP and recombinantly expressed human MBP can degrade soluble Aβ40 and Aβ42 peptides in vitro. Purified MBP also degraded fibrillar Aβ in vitro. Mass spectrometry analysis identified distinct degradation products generated from soluble and fibrillar Aβ digestion by MBP. Furthermore, purified MBP degraded parenchymal and vascular fibrillar amyloid deposits in situ in the brain tissue of APP transgenic mice. Together, these findings indicate that purified MBP possesses Aβ degrading activity in vitro.