Elsevier

Progress in Neurobiology

Volume 99, Issue 3, December 2012, Pages 262-280
Progress in Neurobiology

Therapeutic approaches to preventing cell death in Huntington disease

https://doi.org/10.1016/j.pneurobio.2012.08.004Get rights and content

Abstract

Neurodegenerative diseases affect the lives of millions of patients and their families. Due to the complexity of these diseases and our limited understanding of their pathogenesis, the design of therapeutic agents that can effectively treat these diseases has been challenging. Huntington disease (HD) is one of several neurological disorders with few therapeutic options. HD, like numerous other neurodegenerative diseases, involves extensive neuronal cell loss. One potential strategy to combat HD and other neurodegenerative disorders is to intervene in the execution of neuronal cell death. Inhibiting neuronal cell death pathways may slow the development of neurodegeneration. However, discovering small molecule inhibitors of neuronal cell death remains a significant challenge. Here, we review candidate therapeutic targets controlling cell death mechanisms that have been the focus of research in HD, as well as an emerging strategy that has been applied to developing small molecule inhibitors—fragment-based drug discovery (FBDD). FBDD has been successfully used in both industry and academia to identify selective and potent small molecule inhibitors, with a focus on challenging proteins that are not amenable to traditional high-throughput screening approaches. FBDD has been used to generate potent leads, pre-clinical candidates, and has led to the development of an FDA approved drug. This approach can be valuable for identifying modulators of cell-death-regulating proteins; such compounds may prove to be the key to halting the progression of HD and other neurodegenerative disorders.

Highlights

Huntington disease is one of numerous neurodegenerative disorders. ► Inhibiting neuronal cell death is one strategy to combat Huntington disease. ► Inhibiting cell-death proteins or activating autophagy leads to neuroprotection. ► Numerous proteins are not amenable to classical methods of drug discovery. ► Fragment-based drug discovery is an alternative method to identify potent drugs.

Introduction

Neurodegenerative diseases encompass a large class of disorders that affect millions of individuals around the world. Broadly, such diseases can be defined as those that selectively and progressively induce neuronal death or dysfunction, especially in midlife. Currently, there are few effective therapies for such disorders. The number of patients affected by neurodegenerative diseases, such as Alzheimer's disease (AD), Parkinson's disease (PD), multiple sclerosis (MS), amyotrophic lateral sclerosis (ALS), and HD, is estimated to increase over time due, to the growing size of the elderly population (Hebert et al., 2001, Thrall, 2005). The cost of care in the US for AD patients alone surpasses $100 billion (Alzheimer's Association, 2010). Delaying the onset or slowing the development of neurodegeneration would have a significant benefit: it would decrease the economic burden and improve the quality of life of affected individuals and their families (Alzheimer's Association, 2010, Thrall, 2005).

Here, we focus on one neurological disorder, HD, and emerging drug discovery approaches involving fragment-based and computational drug design that can be applied to developing small molecule inhibitors of proteins that induce cell-death. We begin by reviewing what is known about HD (Section 2) and then examine the pro-cell-death targets that may be of therapeutic benefit to HD (Section 3). In the final section, we describe FBDD and how it may be used in drug discovery efforts for HD and other neurodegenerative diseases (Section 4).

Section snippets

Huntington disease

There have been several extensive reviews published on HD (Imarisio et al., 2008, Ross and Tabrizi, 2011, Walker, 2007, Zuccato et al., 2010). Here, we provide only a brief overview of the disease.

Regulated cell death pathways and HD targets

Classical programmed cell death was initially used to describe apoptosis, a tightly regulated, active, self-terminating process that Kerr morphologically characterized in 1972 to contrast with accidental cell death (Kerr et al., 1972). Today, there are numerous cell death pathways that have been identified. In addition to the well-established regulated cell death pathway of apoptosis, novel pathways and processes involving cell death are being identified, such as ferroptosis (Dixon et al., 2012

Drug design

Identifying potential therapeutic targets in HD is only the first stage of creating new therapies. The next challenge is designing inhibitors for those targets. Since the first introduction of Pfizer's “high-throughput screen” in 1948 (Janzen, 2002), the high-throughput screening (HTS) approach for lead elicitation has become ubiquitous within the pharmaceutical industry (Fischer and Hubbard, 2009, Janzen, 2002) and academia. However, limitations of this method have started to emerge and a

Conclusions

Developing pharmaceutical agents to counteract neurodegenerative diseases has always posed a grand challenge. Primarily, our understanding of the molecular pathways involved in these diseases is still limited. Furthermore, the proteins that are known to be involved in neurodegenerative disorders are not easy targets to modulate with traditional approaches. To overcome the first problem, research has focused on the most downstream effectors of neurodegeneration—cell death pathways. There is an

Acknowledgments

We would like to thank R.R. Letso and B.E. Kaplan for their thorough review of the manuscript. We apologize to investigators whose work we did not include in this review due to time and space restrictions. BRS is an Early Career Scientist of the Howard Hughes Medical Institute, and is supported by additional funding from the Arnold and Mabel Beckman Foundation, NYSTAR and the National Institutes of Health (R01CA097061, R01GM085081 and R01CA161061). AK is supported by the Training Program in

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