Matthew P. Greving is Chief Scientific Officer at Nextval Inc., a company founded in early 2010 that has developed a discovery platform called MassInsight™.. He received his PhD in Biochemistry from Arizona State University, and prior to that he spent nearly 7 years working as a software engineer. This experience in solving complex computational problems fueled his interest in developing technologies and algorithms related to acquisition and analysis of high-dimensional biochemical data. To address the existing problems associated with label-based microarray readouts, he beganwork on a technique for label-free mass spectrometry (MS) microarray readout compatible with both matrix-assisted laser/desorption ionization (MALDI) and matrix-free nanostructure initiator mass spectrometry (NIMS). This is the core of Nextval’s MassInsight technology, which utilizes picoliter noncontact deposition of high-density arrays on mass-readout substrates along with computational algorithms for high-dimensional data processingand reduction.
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Acoustic deposition with NIMS as a high-throughput enzyme activity assay.
Anal Bioanal Chem
May 2012
Nextval, 4186 Sorrento Valley Blvd, Suite G, San Diego, CA 92121, USA.
Mass spectrometry (MS)-based enzyme assay has been shown to be a useful tool for screening enzymatic activities from environmental samples. Recently, reported approaches for high-specificity multiplexed characterization of enzymatic activities allow for providing detailed information on the range of enzymatic products and monitoring multiple enzymatic reactions. However, the throughput has been limited by the slow liquid-liquid handling and manual analysis.
View Article and Find Full Text PDFAn Interview with Matthew P. Greving, PhD. Interview by Vicki Glaser.
Assay Drug Dev Technol
October 2011
Matthew P. Greving is Chief Scientific Officer at Nextval Inc., a company founded in early 2010 that has developed a discovery platform called MassInsight™.
View Article and Find Full Text PDFThermodynamic additivity of sequence variations: an algorithm for creating high affinity peptides without large libraries or structural information.
PLoS One
November 2010
Center for BioOptical Nanotechnology and Center for Innovations in Medicine, The Biodesign Institute, Arizona State University, Tempe, Arizona, United States of America.
Background: There is a significant need for affinity reagents with high target affinity/specificity that can be developed rapidly and inexpensively. Existing affinity reagent development approaches, including protein mutagenesis, directed evolution, and fragment-based design utilize large libraries and/or require structural information thereby adding time and expense. Until now, no systematic approach to affinity reagent development existed that could produce nanomolar affinity from small chemically synthesized peptide libraries without the aid of structural information.
View Article and Find Full Text PDFNanostructure-initiator mass spectrometry metabolite analysis and imaging.
Anal Chem
January 2011
Center for Metabolomics and Mass Spectrometry, Department of Chemistry, The Scripps Research Institute.
Nanostructure-Initiator Mass Spectrometry (NIMS) is a matrix-free desorption/ionization approach that is particularly well-suited for unbiased (untargeted) metabolomics. An overview of the NIMS technology and its application in the detection of biofluid and tissue metabolites are presented. (To listen to a podcast about this feature, please go to the Analytical Chemistry multimedia page at pubs.
View Article and Find Full Text PDFDiscovery of high-affinity protein binding ligands--backwards.
PLoS One
May 2010
Center for Innovations in Medicine, Arizona State University, Tempe, Arizona, United States of America.
Background: There is a pressing need for high-affinity protein binding ligands for all proteins in the human and other proteomes. Numerous groups are working to develop protein binding ligands but most approaches develop ligands using the same strategy in which a large library of structured ligands is screened against a protein target to identify a high-affinity ligand for the target. While this methodology generates high-affinity ligands for the target, it is generally an iterative process that can be difficult to adapt for the generation of ligands for large numbers of proteins.
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