| Literature DB >> 22704758 |
Chandree L Beaulieu1, Mark E Samuels, Sean Ekins, Christopher R McMaster, Aled M Edwards, Adrian R Krainer, Geoffrey G Hicks, Brendan J Frey, Kym M Boycott, Alex E Mackenzie.
Abstract
With the advent of next-generation DNA sequencing, the pace of inherited orphan disease gene identification has increased dramatically, a situation that will continue for at least the next several years. At present, the numbers of such identified disease genes significantly outstrips the number of laboratories available to investigate a given disorder, an asymmetry that will only increase over time. The hope for any genetic disorder is, where possible and in addition to accurate diagnostic test formulation, the development of therapeutic approaches. To this end, we propose here the development of a strategic toolbox and preclinical research pathway for inherited orphan disease. Taking much of what has been learned from rare genetic disease research over the past two decades, we propose generalizable methods utilizing transcriptomic, system-wide chemical biology datasets combined with chemical informatics and, where possible, repurposing of FDA approved drugs for pre-clinical orphan disease therapies. It is hoped that this approach may be of utility for the broader orphan disease research community and provide funding organizations and patient advocacy groups with suggestions for the optimal path forward. In addition to enabling academic pre-clinical research, strategies such as this may also aid in seeding startup companies, as well as further engaging the pharmaceutical industry in the treatment of rare genetic disease.Entities:
Mesh:
Year: 2012 PMID: 22704758 PMCID: PMC3458970 DOI: 10.1186/1750-1172-7-39
Source DB: PubMed Journal: Orphanet J Rare Dis ISSN: 1750-1172 Impact factor: 4.123
Figure 1Normalizing the pathogenic imbalance. Protein levels and/or activity outside of the physiological normal range usually underlie a monogenic disease. Therapeutic approaches may involve normalizing this imbalance by enhancing the mRNA, protein, or protein activity in disorders caused by LOF mutations and moderating the mRNA, protein, or protein function excess observed in GOF mutations.
Figure 2Pharmacologically responsive therapeutic targets. mRNA (and thus proteins) which are both pharmacologically responsive and disease modulating represent potential therapeutic targets.
Figure 3Orphan disease translational pathway. Schematic of possible orphan disease therapeutic avenues depending on nature of mutation, disease mechanism, and information mined from existing datasets. *In silico screen possible. **Computer based drug identification/design possible.
Figure 4Therapeutic approaches based on small molecules and ASOs. Small molecules have the potential to regulate the expression of genes. Haploinsufficient or partially functioning proteins can be upregulated to compensate for the reduced activity. If a non-functional mutated gene has a homolog with overlapping function, the homolog can be upregulated to partly compensate for the non-functioning protein (termed rescuing paralog). ASOs have the potential to modify pre-mRNA splicing or expression. Cryptic splice sites caused by mutations can be blocked to correct splicing. Conversely, genes with overexpression or with gain-of-function mutations can be downregulated.
Translational toolbox: Conditions and resources that will enable effective orphan disease translational research
| Known Gene | |
| Known Inheritance (dominant or recessive) | |
| Known Mechanism (LOF or GOF) | |
| Existence of a presymptomatic window or likeliness of clinical reversibility | |
| Dysregulated pathway known | |
| Diagnostic assay associated with primary defect available | |
| Purified protein available | |
| Protein crystal structure known | |
| Antibody directed against protein available | |
| Previous screen related to disease gene exists (screen for pharmacologic modulation, ASO screening, etc) | |
| Gene under control of transcription factors responsive to drugs | |
| Scorable cell culture phenotype exists | |
| Animal or other model available | |
| Scorable biomarker reflecting disease state exists (metabolomic, transcriptomic marker, etc) | |
| Disease management protocol in use | |
Examples of computational technologies used for rare disease drug discovery
| Small Molecule Upregulation | Spinal Muscular Atrophy | Connectivity Map | Anisomycin | [ |
| Small Molecule Upregulation | Spinal Muscular Atrophy | Transcription factor binding site identification | Prolactin | [ |
| Chaperone: drug safety predictions | Gaucher disease | Leadscope | Core structures of aminoquinoline, sulfonamide, and triazine | [ |
| Chaperone: identify binding sites and compounds | Huntington disease | AutoDock, Patch Dock Server, CastP | Metoprolol, minocyclines, and 18 F fluorodeoxyglucose | [ |
| Drug similarity predictions | Neurodegenerative disorders due to protein misfolding | Mode of Action by Network Analysis, MANTRA | Fasudil | [ |
| Prediction of which mutations respond to treatment | Fabry disease | Position specific substitution matrix | 1-deoxy-galactonojirimycin | [ |