Ruben Abagyan

About

Ruben Abagyan, PhD, is a professor at the Skaggs School of Pharmacy and Pharmaceutical Sciences. His research focuses on the development of novel technologies for structure-based drug discovery and optimization, structural systems biology for target finding, and protein modeling. His laboratory screens specific biomedical targets to discover new drug leads and validate them experimentally, with applications spanning cancer, neurodegeneration, parasitic, viral, and endocrine diseases. He models alternative functional states and allosteric pockets of kinases, GPCRs, and Nuclear Receptors, and has derived comprehensive sets of ligand pockets, known as the Pocketome, for target identification and multi-target pharmacology profiling. His work includes docking drugs, leads, and environmental chemicals to models predicting endocrine disruption and adverse effects, as well as identifying new uses for existing drugs based on multi-target pharmacology. Dr. Abagyan has made significant contributions to the fields of internal coordinate mechanics for structure sampling, dynamics, molecular docking, and structure-based lead discovery, establishing himself as a leading figure in computational drug discovery.

Research topics

• Biology
• Botany
• Biochemistry

Selected publications

• A receptor-like protein mediates plant immune responses to herbivore-associated molecular patterns

  Proceedings of the National Academy of Sciences · 2020 · 153 citations

  ) in tobacco. Our results support the role of plant immune receptors in the perception of chewing herbivores and defense.

  PublisherOA PDFDOI

• De novo generation of multi-target compounds using deep generative chemistry

  Nature Communications · 2024-05-06 · 74 citations

  articleOpen access

  Polypharmacology drugs-compounds that inhibit multiple proteins-have many applications but are difficult to design. To address this challenge we have developed POLYGON, an approach to polypharmacology based on generative reinforcement learning. POLYGON embeds chemical space and iteratively samples it to generate new molecular structures; these are rewarded by the predicted ability to inhibit each of two protein targets and by drug-likeness and ease-of-synthesis. In binding data for >100,000 comp…

  PublisherOA PDFDOI

• Systems Biology Analysis Reveals Eight SLC22 Transporter Subgroups, Including OATs, OCTs, and OCTNs

  International Journal of Molecular Sciences · 2020-03-05 · 71 citations

  articleOpen access

  The SLC22 family of OATs, OCTs, and OCTNs is emerging as a central hub of endogenous physiology. Despite often being referred to as "drug" transporters, they facilitate the movement of metabolites and key signaling molecules. An in-depth reanalysis supports a reassignment of these proteins into eight functional subgroups, with four new subgroups arising from the previously defined OAT subclade: OATS1 (SLC22A6, SLC22A8, and SLC22A20), OATS2 (SLC22A7), OATS3 (SLC22A11, SLC22A12, and Slc22a22), and…

  PublisherOA PDFDOI

• Unique metabolite preferences of the drug transporters OAT1 and OAT3 analyzed by machine learning

  Journal of Biological Chemistry · 2020-01-03 · 55 citations

  articleOpen accessCorresponding

  The multispecific organic anion transporters, OAT1 (SLC22A6) and OAT3 (SLC22A8), the main kidney elimination pathways for many common drugs, are often considered to have largelyredundant roles. However, whereas examination of metabolomics data from Oat-knockout mice (Oat1 and Oat3KO) revealed considerable overlap, over a hundred metabolites were increased in the plasma of one or the other of these knockout mice. Many of these relatively unique metabolites are components of distinct biochemical a…

  PublisherOA PDFDOI

• Thyroid Hyperplasia and Neoplasm Adverse Events Associated With Glucagon-Like Peptide-1 Receptor Agonists in the Food and Drug Administration Adverse Event Reporting System: Retrospective Analysis

  JMIRx Med · 2024-03-19 · 10 citations

  articleOpen accessSenior author

  Background: Glucagon-like peptide-1 (GLP-1) receptor agonists (RAs) are one of the most commonly used drugs for type 2 diabetes mellitus. Clinical guidelines recommend GLP-1 RAs as an adjunct to diabetes therapy in patients with chronic kidney disease, presence or risk of atherosclerotic cardiovascular disease, and obesity. The weight loss observed in clinical trials has been explored further in healthy individuals, putting GLP-1 RAs on track to be the next weight loss treatment. Objective: Alth…

  PublisherDOI

Recent grants

• NIH Grant U01GM094612

  NIH · $9.1M · 2015

• Addressing biomedical challenges with computational mechanics and big data

  NIH · $1.9M · 2019–2024

• NIH Grant R01GM071872

  NIH · $4.2M · 2020

Frequent coauthors

• Irina Kufareva

  University of Montana

  155 shared

• Andrew Orry

  Molsoft (United States)

  154 shared

• Polo C.‐H. Lam

  Molsoft (United States)

  141 shared

• Laurence J. Miller

  Mayo Clinic in Arizona

  127 shared

• Patrick M. Sexton

  Australian Research Council

  120 shared

• Maxim Totrov

  Molsoft (United States)

  119 shared

• Vsevolod Katritch

  University of Southern California

  86 shared

• Arthur Christopoulos

  Monash University

  86 shared

Awards & honors

• Two CapCure awards for excellence in prostate cancer researc…
• Princess Diana award and medal, Sydney (2003)
• UCSD Faculty and Staff Excellence Award (2007)
• AACP’s 2016 Teacher of the Year Award
• SSPPS Student-voted Faculty of the Year Award (2018)

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