Induction of heme oxygenase I (HMOX1) by HPP-4382: a novel modulator of Bach1 activity.

Oxidative stress is generated by reactive oxygen species (ROS) produced in response to metabolic activity and environmental factors. Increased oxidative stress is associated with the pathophysiology of a broad spectrum of inflammatory diseases. Cellular response to excess ROS involves the induction of antioxidant response element (ARE) genes under control of the transcriptional activator Nrf2 and the transcriptional repressor Bach1. The development of synthetic small molecules that activate the protective anti-oxidant response network is of major therapeutic interest. Traditional small molecules targeting ARE-regulated gene activation (e.g., bardoxolone, dimethyl fumarate) function by alkylating numerous proteins including Keap1, the controlling protein of Nrf2. An alternative is to target the repressor Bach1. Bach1 has an endogenous ligand, heme, that inhibits Bach1 binding to ARE, thus allowing Nrf2-mediated gene expression including that of heme-oxygenase-1 (HMOX1), a well described target of Bach1 repression. In this report, normal human lung fibroblasts were used to screen a collection of synthetic small molecules for their ability to induce HMOX1. A class of HMOX1-inducing compounds, represented by HPP-4382, was discovered. These compounds are not reactive electrophiles, are not suppressed by N-acetyl cysteine, and do not perturb either ROS or cellular glutathione. Using RNAi, we further demonstrate that HPP-4382 induces HMOX1 in an Nrf2-dependent manner. Chromatin immunoprecipitation verified that HPP-4382 treatment of NHLF cells reciprocally coordinated a decrease in binding of Bach1 and an increase of Nrf2 binding to the HMOX1 E2 enhancer. Finally we show that HPP-4382 can inhibit Bach1 activity in a reporter assay that measures transcription driven by the human HMOX1 E2 enhancer. Our results suggest that HPP-4382 is a novel activator of the antioxidant response through the modulation of Bach1 binding to the ARE binding site of target genes.

Effect of TTP488 in patients with mild to moderate Alzheimer's disease.

BACKGROUND: TTP488, an antagonist at the Receptor for Advanced Glycation End products, was evaluated as a potential treatment for patients with mild-to-moderate Alzheimer's disease (AD). A previous report describes decreased decline in ADAS-cog (delta = 3.1, p = 0.008 at 18 months, ANCOVA with multiple imputation), relative to placebo, following a 5 mg/day dose of TTP488. Acute, reversible cognitive worsening was seen with a 20 mg/day dose. The present study further evaluates the efficacy of TTP488 by subgroup analyses based on disease severity and concentration effect analysis. METHODS: 399 patients were randomized to one of two oral TTP488 doses (60 mg for 6 days followed by 20 mg/day; 15 mg for 6 days followed by 5 mg/day) or placebo for 18 months. Pre-specified primary analysis, using an ITT population, was on the ADAS-cog11. Secondary analyses included as a key secondary variable the Clinical Dementia Rating-Sum of Boxes (CDR-SB), and another secondary variable of the ADCS-ADL. RESULTS: On-treatment analysis demonstrated numerical differences favoring 5 mg/day over placebo, with nominal significance at Month 18 (delta = 2.7, p = 0.03). Patients with mild AD, whether defined by MMSE or ADAS-cog, demonstrated significant differences favoring 5 mg/day on ADAS-cog and trends on CDR-sb and ADCS-ADL at Month 18. TTP488 plasma concentrations of 7.6-16.8 ng/mL were associated with a decreased decline in ADAS-cog over time compared to placebo. Worsening on the ADAS-cog relative to placebo was evident at 46.8-167.0 ng/mL. CONCLUSIONS: Results of these analyses support further investigation of 5 mg/day in future Phase 3 trials in patients with mild AD.

Integrated approaches to perform in silico drug discovery.

Computer assisted, or in silico, drug discovery approaches play an important role in the search for small molecule hits and leads. These include structure- and ligand-based methods, as well as data mining and QSAR. They are used to analyze and predict ligand-receptor binding, as well as pharmacokinentic profiles of compounds with therapeutic potential. A diversity of offerings is publically/commercially available for performing these tasks. Each offering comprises select combinations of in silico methods. Efficient in silico drug discovery requires effective use of combinations of these tools. Unfortunately, no single vendor offering integrates all in silico capabilities. Typically, different vendors offer different "flavors" of the same method and specific "flavors" have associated strengths and weaknesses. Furthermore, significant inter-vendor format incompatibilities exist. Consequently, extensive scripting as well as manual intervention is required in order to overcome disparate data formats. In this article, we introduce the architecture and implementation of a highly efficient, and automated in silico drug discovery engine that integrates multi-vendor software. A single graphical user interface enables the user to 'Click & Configure' modeling tools and permits 'Mix & Matching' components from various vendors. It deploys a 'Divide & Conquer' strategy to marshal the resources of a multi-node compute cluster for compute-intensive tasks. This basic framework in performing in silico modeling activities (work-flow automation) envisions the integration of structure-based, ligand-based, and other modes of in silico drug discovery.