Robert J. Shmookler Reis
Professor
faculty
Geriatrics, College of Medicine
Research Areas
Biography and Research Information
OverviewAI-generated summary
Robert J. Shmookler Reis investigates the molecular mechanisms underlying aging and age-progressive diseases, with a dual focus on insulin-like signaling and protein aggregation. His research group has demonstrated a significant extension of lifespan in *C. elegans* nematodes through the study of PI 3-kinase and its role in longevity. Concurrently, his lab explores protein aggregation as a common feature of age-related diseases, examining how specific proteins form aggregates and how their clearance is regulated by proteasomal and autophagic pathways. This work involves using proteomics to identify proteins within aggregates associated with neurodegenerative conditions such as Alzheimer's disease.
Shmookler Reis's research integrates computational and experimental approaches. Molecular dynamics simulations are employed to predict protein-protein and protein-drug interactions based on the structures of identified aggregate proteins. These in silico predictions are then validated in vivo using a range of model systems, including *C. elegans*, cultured human cells, and mouse models of neuropathy. Molecular genetics and bioinformatics are utilized as complementary tools to further elucidate functional interactions. His work has been supported by federal grants, including funding from the NIH/National Institute on Aging, and he has a significant publication record with a high h-index and numerous citations. He actively collaborates with researchers at the University of Arkansas for Medical Sciences.
Research Overview
My research group has been focused for the last 5 years on two areas: (1.) the role of PI 3-kinase in insulin-like signaling and extreme longevity, extending to a 10-fold increase in lifespan for C. elegans nematodes carrying a null mutation; and (2.) protein aggregation as a unifying feature of many or all age-progressive diseases. We have pursued specific aggregate proteins that favor the formation of aggregates (by promoting protein coallescence) or disrupt their clearance (through interference with proteasomes and autophagosomes). We use proteomics to identify proteins in aggregates of Alzheimer's and other human neurodegenerative diseases; their known or predicted structures allow molecular-dynamic simulations of protein-protein and protein-drug interactions. Predictions from in silico studies are then tested in vivo using models of Alzheimer’s and other human neurodegenerative diseases, in the nematode C. elegans, in cultured human cells, and in mouse models of neuropathy. Molecular genetics and bioinformatics provide complementary tools to discover and understand functional interactions. Water under the bridge (previous research): From the start of my research career, I have been fascinated by the genetic regulation of longevity and age-associated diseases. My group characterized a number of mutations that have large effects on lifespan in the nematode C. elegans. We also used gene mapping combined with bioinformatics approaches to discover and characterize the natural variation in genes that modulate lifespan. We found that Rec-8 protein (a cohesin) alters lifespan in nematodes and yeast, and a colleague then showed that it also contributed to the exceptional longevity of bowhead whales. In mammalian genetics, we were the first to identify the Pirin gene on the X chromosome as a determinant of post-menopausal bone loss in women, a discovery subsequently confirmed in a Chinese population. We also pioneered studies of homologous recombination (HR) and its roles in the etiology and subsequent progression of myeloma, prostate and breast cancers. Data from our laboratory, and subsequently many others, support the hypothesis that HR generates genetic diversity from which more highly oncogenic clones emerge by cell selection. We have exploited the heavy dependence of cancer cells on HR to develop synergistic combinations of chemotherapeutic drugs.
Metrics
- h-index: 44
- Publications: 173
- Citations: 5,735
Selected Publications
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Accelerating Discovery of Leukemia Inhibitors Using AI-Driven Quantitative Structure-Activity Relationship: Algorithm Development and Validation (2025)
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Altered protein homeostasis in cardiovascular diseases contributes to Alzheimer’s-like neuropathology (2025)
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Mitochondria in aging and age-associated diseases (2025)
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Strong reduction of cryoprotectant toxicity by stress response induction (2024)
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Ezetimibe Lowers Risk of Alzheimer’s and Related Dementias over Sevenfold, Reducing Aggregation in Model Systems by Inhibiting 14-3-3G::Hexokinase Interaction (2024)
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Model biological systems demonstrate the inducibility of pathways that strongly reduce cryoprotectant toxicity (2024)
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Rescue of ApoE4-related lysosomal autophagic failure in Alzheimer’s disease by targeted small molecules (2024)
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Alzheimer’s-specific brain amyloid interactome: Neural-network analysis of intra-aggregate crosslinking identifies novel drug targets (2023)
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Myocardial infarction elevates endoplasmic reticulum stress and protein aggregation in heart as well as brain (2023)
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Thiadiazolidinone (TDZD) Analogs Inhibit Aggregation-Mediated Pathology in Diverse Neurodegeneration Models, and Extend C. elegans Life- and Healthspan (2023)
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Protein homeostasis in the aged and diseased heart (2023)
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In silico analysis of TUBA4A mutations in Amyotrophic Lateral Sclerosis to define mechanisms of microtubule disintegration (2023)
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Physiological Consequences of Targeting 14-3-3 and Its Interacting Partners in Neurodegenerative Diseases (2022)
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Machine-learning analysis of intrinsically disordered proteins identifies key factors that contribute to neurodegeneration-related aggregation (2022)
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Glial Fibrillary Acidic Protein: A Biomarker and Drug Target for Alzheimer’s Disease (2022)
Federal Grants 1 $374,971 total
Inference of Common Pathways Underlying Neurodegeneration & Other Age-Progressive Diseases
Grants & Funding
- No FP attached Quantum Pharmaceuticals Ltd Principal Investigator
- Inference of Common Pathways Underlying Neurodegeneration & Other Age-Progressive Diseases NIH/Nat. Inst. on Aging Principal Investigator
- Center for Studies of Host Response to Cancer Therapy NIH Co-Investigator
- Role of glutathione transferases in life span extension of C. elegans NIH Co-Investigator
- Repurposing FDA-approved drugs to disrupt tau- and amyloid-associated protein-protein interactions in Alzheimer's disease aggregates VA (I01 Dept. of Veterans Affairs) Principal Investigator
- Roles of protein aggregation in Alzheimer’s and other neurodegenerative diseases NIH/NIA Principal Investigator
- Analysis and Therapy of Age-Dependent Proteostasis Failure in Neurodegeneration Veterans Administration Principal Investigator
- Inference of Common Pathways Underlying Neurodegeneration & Other Age-Progressive Diseases - Continuation - Continuation NIH/Nat. Inst. on Aging Principal Investigator
Collaboration Network
Top Collaborators
- Glial Fibrillary Acidic Protein: A Biomarker and Drug Target for Alzheimer’s Disease
- Intrinsically disordered proteins identified in the aggregate proteome serve as biomarkers of neurodegeneration
- “Protein aggregates” contain RNA and DNA, entrapped by misfolded proteins but largely rescued by slowing translational elongation
- Novel hydroxybenzylamine-deoxyvasicinone hybrids as anticholinesterase therapeutics for Alzheimer’s disease
- Rescue of ApoE4-related lysosomal autophagic failure in Alzheimer’s disease by targeted small molecules
Showing 5 of 28 shared publications
- Glial Fibrillary Acidic Protein: A Biomarker and Drug Target for Alzheimer’s Disease
- Intrinsically disordered proteins identified in the aggregate proteome serve as biomarkers of neurodegeneration
- “Protein aggregates” contain RNA and DNA, entrapped by misfolded proteins but largely rescued by slowing translational elongation
- Novel hydroxybenzylamine-deoxyvasicinone hybrids as anticholinesterase therapeutics for Alzheimer’s disease
- Rescue of ApoE4-related lysosomal autophagic failure in Alzheimer’s disease by targeted small molecules
Showing 5 of 15 shared publications
- Glial Fibrillary Acidic Protein: A Biomarker and Drug Target for Alzheimer’s Disease
- Intrinsically disordered proteins identified in the aggregate proteome serve as biomarkers of neurodegeneration
- “Protein aggregates” contain RNA and DNA, entrapped by misfolded proteins but largely rescued by slowing translational elongation
- Rescue of ApoE4-related lysosomal autophagic failure in Alzheimer’s disease by targeted small molecules
- In silico analysis of TUBA4A mutations in Amyotrophic Lateral Sclerosis to define mechanisms of microtubule disintegration
Showing 5 of 12 shared publications
- Mitochondria in aging and age-associated diseases
- Myocardial infarction elevates endoplasmic reticulum stress and protein aggregation in heart as well as brain
- Thiadiazolidinone (TDZD) Analogs Inhibit Aggregation-Mediated Pathology in Diverse Neurodegeneration Models, and Extend C. elegans Life- and Healthspan
- Physiological Consequences of Targeting 14-3-3 and Its Interacting Partners in Neurodegenerative Diseases
- Ezetimibe Lowers Risk of Alzheimer’s and Related Dementias over Sevenfold, Reducing Aggregation in Model Systems by Inhibiting 14-3-3G::Hexokinase Interaction
Showing 5 of 10 shared publications
- Advances in understanding the molecular basis of clonal hematopoiesis
- Supplementary Figure 3: Dinaciclib reduces the mRNA transcripts of Rad51, its paralogs and Brca1 in vivo from A Cyclin-Dependent Kinase Inhibitor, Dinaciclib, Impairs Homologous Recombination and Sensitizes Multiple Myeloma Cells to PARP Inhibition
- Supplementary Figure 1: Dinaciclib potentiates cytotoxic effects of doxorubicin from A Cyclin-Dependent Kinase Inhibitor, Dinaciclib, Impairs Homologous Recombination and Sensitizes Multiple Myeloma Cells to PARP Inhibition
- Supplementary Figure 2: Dinaciclib induces S-phase accumulation and reduces G2/M-phase accumulation from A Cyclin-Dependent Kinase Inhibitor, Dinaciclib, Impairs Homologous Recombination and Sensitizes Multiple Myeloma Cells to PARP Inhibition
- Supplementary Figure 2: Dinaciclib induces S-phase accumulation and reduces G2/M-phase accumulation from A Cyclin-Dependent Kinase Inhibitor, Dinaciclib, Impairs Homologous Recombination and Sensitizes Multiple Myeloma Cells to PARP Inhibition
Showing 5 of 9 shared publications
- Supplementary Figure 3: Dinaciclib reduces the mRNA transcripts of Rad51, its paralogs and Brca1 in vivo from A Cyclin-Dependent Kinase Inhibitor, Dinaciclib, Impairs Homologous Recombination and Sensitizes Multiple Myeloma Cells to PARP Inhibition
- Supplementary Figure 1: Dinaciclib potentiates cytotoxic effects of doxorubicin from A Cyclin-Dependent Kinase Inhibitor, Dinaciclib, Impairs Homologous Recombination and Sensitizes Multiple Myeloma Cells to PARP Inhibition
- Supplementary Figure 2: Dinaciclib induces S-phase accumulation and reduces G2/M-phase accumulation from A Cyclin-Dependent Kinase Inhibitor, Dinaciclib, Impairs Homologous Recombination and Sensitizes Multiple Myeloma Cells to PARP Inhibition
- Supplementary Figure 2: Dinaciclib induces S-phase accumulation and reduces G2/M-phase accumulation from A Cyclin-Dependent Kinase Inhibitor, Dinaciclib, Impairs Homologous Recombination and Sensitizes Multiple Myeloma Cells to PARP Inhibition
- Supplementary Figure 1: Dinaciclib potentiates cytotoxic effects of doxorubicin from A Cyclin-Dependent Kinase Inhibitor, Dinaciclib, Impairs Homologous Recombination and Sensitizes Multiple Myeloma Cells to PARP Inhibition
Showing 5 of 8 shared publications
- Thiadiazolidinone (TDZD) Analogs Inhibit Aggregation-Mediated Pathology in Diverse Neurodegeneration Models, and Extend C. elegans Life- and Healthspan
- DNA Polymerase Inhibitor Discovery Using Machine Learning-Enhanced QSAR Modeling
- Accelerating Discovery of Leukemia Inhibitors Using AI-Driven Quantitative Structure-Activity Relationship: Algorithm Development and Validation
- Machine Learning–Enhanced Quantitative Structure-Activity Relationship Modeling for DNA Polymerase Inhibitor Discovery: Algorithm Development and Validation
- Advanced QSAR Modeling with Machine Learning for Drug Discovery: Targeting DNA Polymerase Inhibitors. (Preprint)
Showing 5 of 6 shared publications
- “Protein aggregates” contain RNA and DNA, entrapped by misfolded proteins but largely rescued by slowing translational elongation
- Rescue of ApoE4-related lysosomal autophagic failure in Alzheimer’s disease by targeted small molecules
- Thiadiazolidinone (TDZD) Analogs Inhibit Aggregation-Mediated Pathology in Diverse Neurodegeneration Models, and Extend C. elegans Life- and Healthspan
- Ezetimibe Lowers Risk of Alzheimer’s and Related Dementias over Sevenfold, Reducing Aggregation in Model Systems by Inhibiting 14-3-3G::Hexokinase Interaction
- Mitochondria in aging and age-associated diseases
- Ezetimibe Lowers Risk of Alzheimer’s and Related Dementias over Sevenfold, Reducing Aggregation in Model Systems by Inhibiting 14-3-3G::Hexokinase Interaction
- Alzheimer’s-specific brain amyloid interactome: Neural-network analysis of intra-aggregate crosslinking identifies novel drug targets
- Altered protein homeostasis in cardiovascular diseases contributes to Alzheimer’s-like neuropathology
- Rescue of ApoE4-related lysosomal autophagic failure in Alzheimer’s disease by targeted small molecules
- In silico analysis of TUBA4A mutations in Amyotrophic Lateral Sclerosis to define mechanisms of microtubule disintegration
- In Silico Analysis of TUBA4A Mutations in Amyotrophic Lateral Sclerosis to Define Mechanisms of Microtubule Disintegration
- DNA Polymerase Inhibitor Discovery Using Machine Learning-Enhanced QSAR Modeling
- Machine Learning–Enhanced Quantitative Structure-Activity Relationship Modeling for DNA Polymerase Inhibitor Discovery: Algorithm Development and Validation
- Advanced QSAR Modeling with Machine Learning for Drug Discovery: Targeting DNA Polymerase Inhibitors. (Preprint)
- DNA Polymerase Inhibitor Discovery Using Machine Learning-Enhanced QSAR Modeling
- Machine Learning–Enhanced Quantitative Structure-Activity Relationship Modeling for DNA Polymerase Inhibitor Discovery: Algorithm Development and Validation
- Advanced QSAR Modeling with Machine Learning for Drug Discovery: Targeting DNA Polymerase Inhibitors. (Preprint)
- Novel hydroxybenzylamine-deoxyvasicinone hybrids as anticholinesterase therapeutics for Alzheimer’s disease
- Thiadiazolidinone (TDZD) Analogs Inhibit Aggregation-Mediated Pathology in Diverse Neurodegeneration Models, and Extend C. elegans Life- and Healthspan
- Novel hydroxybenzylamine-deoxyvasicinone hybrids as anticholinesterase therapeutics for Alzheimer’s disease
- Thiadiazolidinone (TDZD) Analogs Inhibit Aggregation-Mediated Pathology in Diverse Neurodegeneration Models, and Extend C. elegans Life- and Healthspan
- In silico analysis of TUBA4A mutations in Amyotrophic Lateral Sclerosis to define mechanisms of microtubule disintegration
- In Silico Analysis of TUBA4A Mutations in Amyotrophic Lateral Sclerosis to Define Mechanisms of Microtubule Disintegration
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