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Patent
Nymirum Inc. | Date: 2016-09-01

Described herein is technology for determining the 2-D or 3-D atomic resolution structure of a polynucleotide bound to and/or interacting with another molecule, for example a small molecule. In some aspects of the technology, NMR and isotopic labeling strategies are used. The technology described herein is useful for a plurality of applications including but not limited to drug discovery and chemical biology probe discovery.


Frank A.T.,University of California at Irvine | Frank A.T.,Nymirum Inc. | Horowitz S.,University of Michigan | Andricioaei I.,University of California at Irvine | And 2 more authors.
Journal of Physical Chemistry B | Year: 2013

The development of methods for predicting NMR chemical shifts with high accuracy and speed is increasingly allowing use of these abundant, readily accessible measurements in determining the structure and dynamics of proteins. For nucleic acids, however, despite the availability of semiempirical methods for predicting 1H chemical shifts, their use in determining the structure and dynamics has not yet been examined. Here, we show that 1H chemical shifts offer powerful restraints for RNA structure determination, allowing discrimination of native structure from non-native states to within 2-4 Å, and <3 Å when highly flexible residues are ignored. Theoretical simulations shows that although 1H chemical shifts can provide valuable information for constructing RNA dynamic ensembles, large uncertainties in the chemical shift predictions and inherent degeneracies lead to higher uncertainties as compared to residual dipolar couplings. © 2013 American Chemical Society.


Frank A.T.,Nymirum Inc. | Frank A.T.,University of Michigan | Bae S.-H.,Nymirum Inc. | Stelzer A.C.,Nymirum Inc.
Journal of Physical Chemistry B | Year: 2013

The use of NMR-derived chemical shifts in protein structure determination and prediction has received much attention, and, as such, many methods have been developed to predict protein chemical shifts from three-dimensional (3D) coordinates. In contrast, little attention has been paid to predicting chemical shifts from RNA coordinates. Using the random forest machine learning approach, we developed RAMSEY, which is capable of predicting both 1H and protonated 13C chemical shifts from RNA coordinates. In this report, we introduce RAMSEY, assess its accuracy, and demonstrate the sensitivity of RAMSEY-predicted chemical shifts to RNA 3D structure. © 2013 American Chemical Society.


Stelzer A.C.,University of Michigan | Stelzer A.C.,Nymirum Inc. | Frank A.T.,University of California at Irvine | Kratz J.D.,University of Michigan | And 6 more authors.
Nature Chemical Biology | Year: 2011

Current approaches used to identify protein-binding small molecules are not suited for identifying small molecules that can bind emerging RNA drug targets. By docking small molecules onto an RNA dynamic ensemble constructed by combining NMR spectroscopy and computational molecular dynamics, we virtually screened small molecules that target the entire structure landscape of the transactivation response element (TAR) from HIV type 1 (HIV-1). We quantitatively predict binding energies for small molecules that bind different RNA conformations and report the de novo discovery of six compounds that bind TAR with high affinity and inhibit its interaction with a Tat peptide in vitro (Ki values of 710 nM-169 μM). One compound binds HIV-1 TAR with marked selectivity and inhibits Tat-mediated activation of the HIV-1 long terminal repeat by 81% in T-cell lines and HIV replication in an HIV-1 indicator cell line (IC50 ∼1/423.1 μM). © 2011 Nature America, Inc. All rights reserved.


Grant
Agency: Department of Health and Human Services | Branch: National Institutes of Health | Program: SBIR | Phase: Phase II | Award Amount: 1.46M | Year: 2015

DESCRIPTION provided by applicant The central dogma of molecular biology has undergone a significant revision where RNAs have emerged as important regulators of cell activity Astonishingly as much as of human DNA is transcribed into RNA as recently reported by the Encyclopedia of DNA Elements ENCODE consortium New classes of RNA are being identified including many which are non protein coding ncRNA Nonetheless ncRNAs are involved in regulating cellular activity Deciphering the structure function relationship of these RNAs is of immediate importance as ncRNAs have now been implicated in a variety of diseases including myotonic dystrophy type prostate cancer spinal muscular atrophy and Huntingtonandapos s disease like Traditional approaches to determine high resolution RNA D structures have proven to be prohibitively time consuming and expensive Nymirum has developed an Automated RNA D Structure Determination System that is faster cheaper and more robust than current approaches This System will be commercialized for use by the drug industry and academic researchers in their quest to understand and treat human disease PUBLIC HEALTH RELEVANCE RNA D structure and function information is critical to understanding basic cell function delineating dysfunctional RNA contribution to human disease and finding new drugs to treat diseases caused by dysfunctional RNAs Nymirum has developed an Automated RNA D Structure Determination System that is faster cheaper and more robust than current approaches


Grant
Agency: Department of Health and Human Services | Branch: | Program: SBIR | Phase: Phase I | Award Amount: 215.02K | Year: 2014

DESCRIPTION (provided by applicant): The central dogma of molecular biology has undergone a significant revision where RNAs have emerged as important regulators of cell activity. Astonishingly, as much as 80% of human DNA is transcribed into RNA as recently reported by the Encyclopedia of DNA Elements (ENCODE) consortium. New classes of RNA are being identified including many which are non-protein coding (ncRNA). Nonetheless ncRNAs are involved in regulating cellular activity. Deciphering the structure-function relationship of these RNAs is of immediate importance as ncRNAs have now been implicated in a variety of diseases including myotonic dystrophy type 1, prostate cancer, spinal muscular atrophy, and Huntington's disease-like 2. Traditional approaches todetermine high-resolution RNA 3D structures have proven to be prohibitively time consuming and expensive. Nymirum has developed an Automated RNA 3D Structure Determination System that is faster, cheaper, and more robust than current approaches. This


Grant
Agency: Department of Health and Human Services | Branch: | Program: SBIR | Phase: Phase I | Award Amount: 244.59K | Year: 2013

DESCRIPTION: Myotonic dystrophy 1 (DM1) is the leading form of adult muscular dystrophy resulting in progressive neuromuscular effects. The disease affects 1 in 6000 people. Nymirum is interested in identifying a small molecule that can be used to slow oreliminate the progression of DM1. The cause of DM1 is the expansion of a CUG RNA sequence within the DMPK gene. This repeat RNA is toxic to normal cellular function by sequestering and altering the activity of needed splicing factors for normal neuromuscular function. We are taking an approach to identify small molecules that will bind to the expanded CUG RNA repeat to prevent sequestration of splicing factors and repair the abnormal splicing phonotype in cells. To this end we have identified 2 chemicalseries of small molecules with clear structure activity relationships for CUG RNA binding and rescue of abnormal splicing in a DM1 cell model. In this proposal, we aim to optimize the structural features of the series to find more potent binders and splicing rescue molecules. To do this we will utilize our extensive knowledge and tools related to RNA structure and small molecule interactions and bring it to bear on targeted medicinal chemistry. DM1 represents a major unmet medical need and patients are inneed of new drugs to slow or eliminate the neuromuscular deterioration PUBLIC HEALTH RELEVANCE PUBLIC HEALTH RELEVANCE: Myotonic dystrophy 1 (DM1) is a progressive neuromuscular disease in adults with no known cure. Nymirum has identified molecules with biological activity to alleviate the disease and will be optimizing them for better activity and drg development purposes.


The present invention provides a method for determining the 3-dimensional or 3-D atomic resolution structure of a biomolecule using chemical shift data obtained from the biomolecule having one or more selectively isotopically labeled biomolecule monomers and interrogation of same using an NMR device. Methods also comprise use of a low-field NMR device and structure determination method to determine the 2-D and 3-D structure of the biomolecule, for example, a polynucleotide.


PubMed | Nymirum Inc.
Type: Journal Article | Journal: The journal of physical chemistry. B | Year: 2013

The use of NMR-derived chemical shifts in protein structure determination and prediction has received much attention, and, as such, many methods have been developed to predict protein chemical shifts from three-dimensional (3D) coordinates. In contrast, little attention has been paid to predicting chemical shifts from RNA coordinates. Using the random forest machine learning approach, we developed RAMSEY, which is capable of predicting both (1)H and protonated (13)C chemical shifts from RNA coordinates. In this report, we introduce RAMSEY, assess its accuracy, and demonstrate the sensitivity of RAMSEY-predicted chemical shifts to RNA 3D structure.

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