IDG Program Highlights
Identifying Targets for Pain Medication with Artificial Intelligence
Chronic pain, a condition where pain persists or recurs over a long period of time, is common in the US, affecting an estimated 1 in 5 adults. Experiencing chronic pain significantly impacts patients’ lives by interfering with day-to-day activities and increasing risk of depression and substance abuse. There are different causes of pain, including pain that arises from inflammation, nervous system injury, or tissue damage. The way the body senses these different types of pain varies. Despite this variety, current pain relief medications focus on relatively few drug targets (defined as molecules in the body that interact with or are modified by a drug). As a result, current medications may not be effective at treating some types of chronic pain.
A major goal of the Common Fund’s Illuminating the Druggable Genome program is to discover new targets for medications. In research supported by the Illuminating the Druggable Genome program, Dr. Avi Ma’ayan and colleagues identified new drug targets for pain treatment. The researchers used machine learning, a type of artificial intelligence where computer algorithms make predictions from data. By combining data on genes, proteins, and RNA molecules from 14 databases and publications, the computer algorithms prioritized targets for human genes associated with 17 unique types of pain. Using this approach, the researchers identified 13 potential drug targets for migraine drug development and four for rheumatoid arthritis. This work has the potential to accelerate research on the identified drug targets, paving the way for more treatment options for chronic pain.
Prioritizing Pain-Associated Targets with Machine Learning. Minji Jeon, Kathleen M. Jagodnik, Eryk Kropiwnicki, Daniel J. Stein, Avi Ma’ayan. Biochemistry. 2021 May 11; 60(18):1430-1446.
Feeling sleepy? New ways to understand how our bodies rest
While there are many factors that help animals sleep, a driving component is known as the circadian rhythm. This rhythm is a set of physical, mental, and behavioral changes that follow the daily light and dark cycle. During nighttime, a chemical called melatonin is released to help synchronize our circadian rhythm and prepare us for sleep by interacting with two proteins called MT1 and MT2. Changes to our circadian rhythm leads to insomnia or other sleep defects. Gaining insight into how the MT1 and MT2 proteins work, could allow researchers to develop new therapeutics to help treat circadian rhythm disorders.
The goal of the Illuminating the Druggable Genome (IDG) program is to identify and provide information on proteins that are currently not well studied within commonly drug-targeted protein families, including G-protein coupled receptors (GCPRs), to which MT1 and MT2 belong. Research supported by the IDG program, and published in the journal Nature, used advanced computational methods to model how over 150 million different chemicals may interact with the MT1 protein. The study identified two brand new molecules that changed how the MT1 protein functioned and shifted a mouse’s sleep cycle by up to 1.5 hours. These two molecules bound to regions of the protein unidentified before and opened a new pathway for changing MT1 activity. This study illustrates opportunities for controlling melatonin biology via specific MT1 binders. It also shows the value of screening large libraries of known chemicals for the discovery of new, active binding sites on proteins of interest. By finding new chemicals that interact with these proteins, we will be able to better understand the biology behind sleep and may be able to develop new therapies for those who suffer from sleep disorders.
Virtual discovery of melatonin receptor ligands to modulate circadian rhythms. Reed Stein, Hye Jin Kang, John McCorvy, Grant C. Glatfelter, Anthony J. Jones, Tao Che, Samuel Slocum, Xi-Ping Huang, Olena Savych, Yurii S. Moroz, Benjamin Stauch, Linda C. Johansson, Vadim Cherezov, Terry Kenakin, John J. Irwin, Brian K. Shoichet, Bryan L. Roth & Margarita L. Dubocovich. Nature, February 2020, https://doi.org/10.1038/s41586-020-2027-0
Investigators in the IDG Consortium have Mapped out the Targets of Every FDA Approved Drug
The vast majority of drugs approved by the FDA act through binding to and changing the activity of protein targets. These targets could be human proteins or proteins from pathogens that infect humans. One measure of the remaining opportunities available for new drug discovery is the number of proteins that have not yet been targeted by a drug. To this end, the Knowledge Management Center of the IDG Program compiled all the information about which proteins are targeted by all the US FDA approved drugs. Through this effort, they were able to show that 1,414 approved drugs act through targeting 667 human and 189 pathogen proteins. By examining trends in the proteins being targeted by new drugs, the authors were able to determine which types of proteins have been the most successful targets for new medications for particular classes of diseases. This data can also be used to understand which human proteins have not yet been targeted by drug development efforts, thus cataloging the unexplored space from which new drugs can be designed in the future.
A comprehensive map of molecular drug targets. Santos R1, Ursu O, Gaulton A, Bento AP, Donadi RS, Bologa CG, Karlsson A, Al-Lazikani B, Hersey A, Oprea TI, Overington JP. Nat Rev Drug Discov. 2017 Jan; 16(1):19-34.
Publications from IDG Investigators: Exploring the Druggable Genome
A recent paper published in Nature by IDG grantees Brian Shoichet and Bryan Roth, suggests combining physical and structure-based screening as a broadly useful method for ligand discovery of understudied and orphan GPCRs.
A recent article in Science Translational Medicine from IDG investigator Joel T. Dudley, demonstrates the usefulness of applying the precision medicine approach to characterize the complexity of Type 2 diabetes using high-dimensional electronic medical records and genotype data from over 11,000 patients.
An article published in Nature Structural and Molecular Biology describes PRESTO-Tango; a screening assay developed by Dr. Bryan L. Roth and colleagues at the University of North Carolina, Chapel Hill. PRESTO-Tango allows for the simultaneous investigation of every nonolfactory G protein-coupled receptor in the human genome. The methods and reagents developed are freely available to the scientific community.
Dr. Gary Johnson at the University of North Carolina, Chapel Hill published a paper in Cell Reports that used a global approach to study the effects of adaptation of the kinome (the full complement of human protein kinases) and its role in drug resistance during cancer treatment.
This page last reviewed on August 2, 2021