Identification and preclinical development of an anti-proteolytic uPA antibody for rheumatoid arthritis.

Blocking the proteolytic capacity of urokinase-type plasminogen activator (uPA) with a monoclonal antibody (mAb) reduces arthritis progression in the collagen-induced mouse arthritis model to an extent that is on par with the effect of blocking tumor necrosis factor-alpha by etanercept. Seeking to develop a novel therapy for rheumatoid arthritis, a humanized mAb, NNC0266-0043, was selected for its dual inhibition of both the zymogen activation and the proteolytic capacity of human uPA. The antibody revealed nonlinear elimination kinetics in cynomolgus monkeys consistent with binding to and turnover of endogenous uPA. At a dose level of 20.6 mg kg-1, the antibody had a plasma half-life of 210 h. Plasma uPA activity, a pharmacodynamic marker of anti-uPA therapy, was reduced to below the detection limit during treatment, indicating that an efficacious plasma concentration was reached. Pharmacokinetic modeling predicted that sufficient antibody levels can be sustained in arthritis patients dosed subcutaneously once weekly. The anti-uPA mAb was also well tolerated in cynomolgus monkeys at weekly doses up to 200 mg kg-1 over 4 weeks. The data from cynomolgus monkeys and from human material presented here indicates that anti-uPA mAb NNC0266-0043 is suitable for clinical testing as a novel therapeutic for rheumatic diseases. KEY MESSAGES: Background: Anti-uPA therapy is on par with etanercept in a mouse arthritis model. A new humanized antibody blocks activation and proteolytic activity of human uPA. The antibody represents a radically novel mode-of-action in anti-rheumatic therapy. The antibody has PK/PD properties in primates consistent with QW clinical dosing.

GFRAL is the receptor for GDF15 and is required for the anti-obesity effects of the ligand.

Growth differentiation factor 15 (GDF15; also known as MIC-1) is a divergent member of the TGF-ß superfamily and is associated with body-weight regulation in humans and rodents. However, the cognate receptor of GDF15 is unknown. Here we show that GDF15 binds specifically to GDNF family receptor α-like (GFRAL) with high affinity, and that GFRAL requires association with the coreceptor RET to elicit intracellular signaling in response to GDF15 stimulation. We also found that GDF15-mediated reductions in food intake and body weight of mice with obesity were abolished in GFRAL-knockout mice. We further found that GFRAL expression was limited to hindbrain neurons and not present in peripheral tissues, which suggests that GDF15-GFRAL-mediated regulation of food intake is by a central mechanism. Lastly, given that GDF15 did not increase energy expenditure in treated mice with obesity, the anti-obesity actions of the cytokine are likely driven primarily by a reduction in food intake.

Building a BioChemformatics database.

The structural registration of chemically modified macromolecules is vital for the development of biopharmaceuticals. However, registration and search of such complex molecules has so far posed formidable challenges performance-wise, since today's chemistry-oriented databases do not scale well to macromolecules. As a practical consequence, macromolecules tend to be stored in protein databases with a focus on protein sequence only, and salient chemistry details are therefore lost. This article describes protein format extensions and the use of pseudoatoms for representing natural amino acids in chemical structures to allow high-performance registration and retrieval of large macromolecules. The representations include exact chemical modifications and enable lossless conversion between chemistry and sequence formats. Registration is done in parallel in both sequence and chemistry formats, and users can register and retrieve molecules in either format as they choose, resulting in what we call a BioChemformatics database. Having both sequence and chemistry formats available on-demand allows for the construction of protein SAR tables with mixed sequence and chemistry information. Likewise, searching may combine sequence and chemistry terms and be performed in standard vendor applications like MDL's ISIS/Base or in-house applications using standard SQL queries.

In silico prediction of cytochrome P450 2D6 and 3A4 inhibition using Gaussian kernel weighted k-nearest neighbor and extended connectivity fingerprints, including structural fragment analysis of inhibitors versus noninhibitors.

Inhibition of cytochrome P450 (CYP) enzymes is unwanted because of the risk of severe side effects due to drug-drug interactions. We present two in silico Gaussian kernel weighted k-nearest neighbor models based on extended connectivity fingerprints that classify CYP2D6 and CYP3A4 inhibition. Data used for modeling consisted of diverse sets of 1153 and 1382 drug candidates tested for CYP2D6 and CYP3A4 inhibition in human liver microsomes. For CYP2D6, 82% of the classified test set compounds were predicted to the correct class. For CYP3A4, 88% of the classified compounds were correctly classified. CYP2D6 and CYP3A4 inhibition were additionally classified for an external test set on 14 drugs, and multidimensional scaling plots showed that the drugs in the external test set were in the periphery of the training sets. Furthermore, fragment analyses were performed and structural fragments frequent in CYP2D6 and CYP3A4 inhibitors and noninhibitors are presented.

Human C5aR knock-in mice facilitate the production and assessment of anti-inflammatory monoclonal antibodies.

Complement component C5a binds C5a receptor (C5aR) and facilitates leukocyte chemotaxis and release of inflammatory mediators. We used neutrophils from human C5aR knock-in mice, in which the mouse C5aR coding region was replaced with that of human C5aR, to immunize wild-type mice and to generate high-affinity antagonist monoclonal antibodies (mAbs) to human C5aR. These mAbs blocked neutrophil migration to C5a in vitro and, at low doses, both prevented and reversed inflammatory arthritis in the murine K/BxN model. Of approximately 40 mAbs generated to C5aR, all potent inhibitors recognized a small region of the second extracellular loop that seems to be critical for regulation of receptor activity. Human C5aR knock-in mice not only facilitated production of high-affinity mAbs against an important human therapeutic target but were also useful in preclinical validation of the potency of these antagonists. This strategy should be applicable to other important mAb therapeutics.

In silico prediction of membrane permeability from calculated molecular parameters.

A data set consisting of 712 compounds was used for classification into two classes with respect to membrane permeation in a cell-based assay: (0) apparent permeability (P(app)) below 4 x 10(-6) cm/s and (1) P(app) on 4 x 10(-6) cm/s or higher. Nine molecular descriptors were calculated for each compound and Nearest-Neighbor classification was applied using five neighbors as optimized by full cross-validation. A model based on five descriptors, number of flex bonds, number of hydrogen bond acceptors and donors, and molecular and polar surface area, was selected by variable selection. In an external test set of 112 compounds, 104 compounds were classified and 8 compounds were judged as "unknown". Among the 104 compounds, 16 were misclassified corresponding to a misclassification rate of 15% and no compounds were falsely predicted in the nonpermeable class.