Drug repositioning is an important area in drug development, providing new therapeutic opportunities for existing drugs that are already approved for their original indications. This circumvents some of the most expensive aspects of the drug discovery process, thanks to previously established safety and pharmacokinetic profiles. Recent developments in multiomic strategies with proteomics at their centre are greatly expanding our understanding of disease biology, our ability to diagnose patients and predict outcomes, and are providing actionable insights into therapeutic responses and drug modes of action.
Can proteomics help redefine how we understand disease?
Genomics has provided a wealth of data to better understand the underlying biology and facilitate more effective drug development for some types of diseases (e.g. in oncology). It is becoming clear, however, that more comprehensive investigations may be required to provide mechanistic insights into unclassified and complex diseases, and that complementary approaches such as proteomics are needed to understanding the complex interplay between environment and phenotype. Thorough molecular characterization of human disease will not only help guide development of new therapies but may also provide an invaluable resource for repurposing existing drugs.
Taking disease beyond polygenic risk scores – Dr. Kari Stefansson (deCODE)
Dr. Kari Stefansson, the CEO of deCODE Genetics of Iceland, shared a lunchtime presentation at the recent European Society for Human Genetics held in Vienna Austria, “The Proteome as a net with which to catch environmental influences on phenotype“. He stressed the importance of using proteomics to go beyond polygenic risk scores to better understand the biology of human disease and the impact of environment on disease and health.
Watch the full presentation
Dr. Kari Stefansson at 2022 ESHG lunchtime workshop, “The Proteome as a net with which to catch environmental influences on phenotype”.
Reclassifying disease through biomarkers – Dr. Timothy Radstake (Abbvie)
In a pharmaceutical roundtable discussion hosted by SelectScience, three pharmaceutical research scientists discussed the opportunities and challenges in using biomarker data in drug discovery and development. Dr. Timothy Radstake, MD, Ph.D. (Executive Director Immunology Discovery, Head of Transformational and Translational Immunology Discovery, AbbVie) emphasized how drug discovery based upon a diagnostic approach is wrong. Biomarker research shows that in fact, different diseases exhibit shared disease drivers and biological pathways. This will lead to a reclassification of medicine, where new types of clinical trials may be conducted based on biomarkers and protein profiles, rather than by disease. This will also likely provide robust new opportunities for repurposing of current drugs, based on these comprehensive disease profiles. Listen to a snippet of Dr. Radstake’s perspective on this in the webinar snippet, or watch the on-demand webinar recording of the full roundtable discussion using the links below.
Leveraging proteomics for drug repurposing opportunities
The following are examples of peer-reviewed publications citing the use of Olink protein biomarker panels that highlight the potential of using plasma proteomics to help repurpose drugs for new indications.
Identifying proteins with causal links to neurological diseases
Png G, Barysenka A, Repetto L, et al. Mapping the serum proteome to neurological diseases using whole genome sequencing. (2021) Nature Communications, DOI: 10.1038/s41467-021-27387-1
This protein quantitative trait locus (pQTL) analysis analyzed 184 neurologically-relevant proteins using whole genome sequencing data from two isolated population-based cohorts (N = 2893). In total, 214 independently-associated variants were detected for 107 proteins, the majority of which (76%) were cis-acting, including 114 previously unknown variants. Two-sample Mendelian randomisation identified causal associations between serum CD33 and Alzheimer’s disease, GPNMB and Parkinson’s disease, and MSR1 and schizophrenia, describing their clinical potential and highlighting repurposing opportunities for existing drugs targeting these proteins.
“In addition to exploring the genetic architecture of these proteins, we show that pQTL analysis has the potential to identify disease-relevant serum biomarkers for debilitating neurological conditions. We identify opportunities for the repurposing of therapeutic targets, and deliver deeper insight into disease pathways”
Png et al. (2021) Nature Communications
Candidate drugs based on plasma proteomics of patients with severe COVID-19
Al-Nesf MAY, Abdesselem HB, Bensmail I, et al. Prognostic tools and candidate drugs based on plasma proteomics of patients with severe COVID-19 complications. (2022) Nature Communications, DOI: 10.1038/s41467-022-28639-4
This study used plasma proteomics to identify 375 proteins that are differentially expressed in patients with severe COVID-19 compared to those with mild or moderate disease. This was used to derive a 12-protein “COVID-19 molecular severity score” with extremely high predictive value for the severe form of the disease (100% specificity and 98% sensitivity, AUC= 0.999). Additionally, they used the protein data to train another high-performance risk score based on clinical measurements and both were then validated in an independent data set. The authors also identified a list of FDA-approved drugs that target proteins identified in their severity score, which they suggested could be further investigated in the context of repurposing for severe COVID-19 therapy.
“Our drug–protein interaction analyses shortlisted several FDA-approved drugs that can target the upregulated proteins in severe COVID-19 cases.”
Al-Nesf et al. (2021) Nature Communications
In silico selection and MOA analysis of candidate drugs for ischemic stroke
Simats A, Ramiro L, Valls R, et al. Ceruletide and Alpha-1 Antitrypsin as a Novel Combination Therapy for Ischemic Stroke. (2022) Neurotherapeutics, DOI: 10.1007/s13311-022-01203-0
This study took a novel approach to repurpose existing drugs for improved treatment of ischemic stroke. While tPA is used successfully as a thrombolytic therapy for stroke, attempts to develop neuroprotective drugs to limit the impact of the stoke have all failed so far. The study authors used an in silico, systems biology strategy based on artificial intelligence and pattern recognition tools to integrate available biological, pharmacological, and medical knowledge into mathematical models to simulate in silico complexity of the stroke. Combinational treatments were acquired by screening these models with more than 5 million two-by-two combinations of drugs on the DRUGBANK database. This identified a combination of ceruletide alpha-1 antitrypsin (referred to as CA) as having a high probability to confer neuroprotection in stroke cases.
Experimental verification of CA treatment in a mouse model of stroke indicated a significant neuroprotective effect, reducing brain tissue death by >30%, but only when the two drugs were used in combination. Proteomic analysis of affected and unaffected brain hemisphere tissue from CA-treated mice suffering stroke provided important information regarding the MOA of the drug combination. Enrichment analysis of proteins differentially expressed in CA vs placebo animals were involved in pro-inflammatory cytokine signaling, necrotic and apoptotic processes, as well as promotion of endothelial cell proliferation and angiogenesis, suggesting important mechanistic aspects of the drug combination treatment.
“This in silico representation allowed us to identify a drug combination formed by ceruletide and alpha-1 antitrypsin which showed synergic neuroprotective effects after ischemia in vivo. Overall, our findings shed light on a new powerful strategy for developing future therapies for ischemic stroke.”
Simats et al. (2021) Neurotherapeutics
Proteomics at the heart of multiomics strategies
Systems biology approaches addressing multiple molecular and cellular components are adding vital insights into the dynamic biology underlying human health and disease.