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Knizner KT, Kibbe RR, Garrard KP, Nuñez JR, Anderton CR, Muddiman DC. On the importance of color in mass spectrometry imaging. J Mass Spectrom 2022; 57:e4898. [PMID: 36463891 PMCID: PMC9944061 DOI: 10.1002/jms.4898] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/27/2022] [Revised: 11/07/2022] [Accepted: 11/17/2022] [Indexed: 05/12/2023]
Abstract
Mass spectrometry imaging (MSI) data visualization relies on heatmaps to show the spatial distribution and measured abundances of molecules within a sample. Nonuniform color gradients such as jet are still commonly used to visualize MSI data, increasing the probability of data misinterpretation and false conclusions. Also, the use of nonuniform color gradients and the combination of hues used in common colormaps make it challenging for people with color vision deficiencies (CVDs) to visualize and accurately interpret data. Here we present best practices for choosing a colormap to accurately display MSI data, improve readability, and accommodate all CVDs. We also provide other resources on the misuse of color in the scientific field and resources on scientifically derived colormaps presented herein.
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Affiliation(s)
- Kevan T. Knizner
- FTMS Laboratory for Human Health Research, Department of ChemistryNorth Carolina State UniversityRaleighNorth CarolinaUSA
| | - Russell R. Kibbe
- FTMS Laboratory for Human Health Research, Department of ChemistryNorth Carolina State UniversityRaleighNorth CarolinaUSA
| | - Kenneth P. Garrard
- FTMS Laboratory for Human Health Research, Department of ChemistryNorth Carolina State UniversityRaleighNorth CarolinaUSA
- Molecular Education, Technology and Research Innovation Center (METRIC)North Carolina State UniversityRaleighNorth CarolinaUSA
- Precision Engineering ConsortiumNorth Carolina State UniversityRaleighNorth CarolinaUSA
| | - Jamie R. Nuñez
- Earth and Biological Sciences DirectoratePacific Northwest National LaboratoryRichlandWashingtonUSA
| | - Christopher R. Anderton
- Earth and Biological Sciences DirectoratePacific Northwest National LaboratoryRichlandWashingtonUSA
| | - David C. Muddiman
- FTMS Laboratory for Human Health Research, Department of ChemistryNorth Carolina State UniversityRaleighNorth CarolinaUSA
- Molecular Education, Technology and Research Innovation Center (METRIC)North Carolina State UniversityRaleighNorth CarolinaUSA
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Nuñez JR, Mcgrady M, Yesiltepe Y, Renslow RS, Metz TO. Correction to " Chespa: Streamlining Expansive Chemical Space Evaluation of Molecular Sets". J Chem Inf Model 2021; 61:2509-2510. [PMID: 33871993 DOI: 10.1021/acs.jcim.1c00392] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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Schultz KJ, Colby SM, Yesiltepe Y, Nuñez JR, McGrady MY, Renslow RS. Application and assessment of deep learning for the generation of potential NMDA receptor antagonists. Phys Chem Chem Phys 2021; 23:1197-1214. [PMID: 33355332 DOI: 10.1039/d0cp03620j] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
Uncompetitive antagonists of the N-methyl d-aspartate receptor (NMDAR) have demonstrated therapeutic benefit in the treatment of neurological diseases such as Parkinson's and Alzheimer's, but some also cause dissociative effects that have led to the synthesis of illicit drugs. The ability to generate NMDAR antagonists in silico is therefore desirable for both new medication development and preempting and identifying new designer drugs. Recently, generative deep learning models have been applied to de novo drug design as a means to expand the amount of chemical space that can be explored for potential drug-like compounds. In this study, we assess the application of a generative model to the NMDAR to achieve two primary objectives: (i) the creation and release of a comprehensive library of experimentally validated NMDAR phencyclidine (PCP) site antagonists to assist the drug discovery community and (ii) an analysis of both the advantages conferred by applying such generative artificial intelligence models to drug design and the current limitations of the approach. We apply, and provide source code for, a variety of ligand- and structure-based assessment techniques used in standard drug discovery analyses to the deep learning-generated compounds. We present twelve candidate antagonists that are not available in existing chemical databases to provide an example of what this type of workflow can achieve, though synthesis and experimental validation of these compounds are still required.
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Affiliation(s)
| | - Sean M Colby
- Pacific Northwest National Laboratory, Richland, WA, USA.
| | | | - Jamie R Nuñez
- Pacific Northwest National Laboratory, Richland, WA, USA.
| | | | - Ryan S Renslow
- Pacific Northwest National Laboratory, Richland, WA, USA.
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Nuñez JR, Mcgrady M, Yesiltepe Y, Renslow RS, Metz TO. Chespa: Streamlining Expansive Chemical Space Evaluation of Molecular Sets. J Chem Inf Model 2020; 60:6251-6257. [PMID: 33283505 DOI: 10.1021/acs.jcim.0c00899] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Thousands of chemical properties can be calculated for small molecules, which can be used to place the molecules within the context of a broader "chemical space." These definitions vary based on compounds of interest and the goals for the given chemical space definition. Here, we introduce a customizable Python module, chespa, built to easily assess different chemical space definitions through clustering of compounds in these spaces and visualizing trends of these clusters. To demonstrate this, chespa currently streamlines prediction of various molecular descriptors (predicted chemical properties, molecular substructures, AI-based chemical space, and chemical class ontology) in order to test six different chemical space definitions. Furthermore, we investigated how these varying definitions trend with mass spectrometry (MS)-based observability, that is, the ability of a molecule to be observed with MS (e.g., as a function of the molecule ionizability), using an example data set from the U.S. EPA's nontargeted analysis collaborative trial, where blinded samples had been analyzed previously, providing 1398 data points. Improved understanding of observability would offer many advantages in small-molecule identification, such as (i) a priori selection of experimental conditions based on suspected sample composition, (ii) the ability to reduce the number of candidate structures during compound identification by removing those less likely to ionize, and, in turn, (iii) a reduced false discovery rate and increased confidence in identifications. Factors controlling observability are not fully understood, making prediction of this property nontrivial and a prime candidate for chemical space analysis. Chespa is available at github.com/pnnl/chespa.
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Affiliation(s)
- Jamie R Nuñez
- Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland, Washington 99352, United States.,The Gene and Linda Voiland School of Chemical Engineering and Bioengineering, Washington State University, Pullman, Washington 99164, United States
| | - Monee Mcgrady
- Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland, Washington 99352, United States
| | - Yasemin Yesiltepe
- Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland, Washington 99352, United States.,The Gene and Linda Voiland School of Chemical Engineering and Bioengineering, Washington State University, Pullman, Washington 99164, United States
| | - Ryan S Renslow
- Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland, Washington 99352, United States.,The Gene and Linda Voiland School of Chemical Engineering and Bioengineering, Washington State University, Pullman, Washington 99164, United States
| | - Thomas O Metz
- Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland, Washington 99352, United States
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Colby SM, Nuñez JR, Hodas NO, Corley CD, Renslow RR. Deep Learning to Generate in Silico Chemical Property Libraries and Candidate Molecules for Small Molecule Identification in Complex Samples. Anal Chem 2019; 92:1720-1729. [DOI: 10.1021/acs.analchem.9b02348] [Citation(s) in RCA: 38] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Affiliation(s)
- Sean M. Colby
- Pacific Northwest National Laboratory, Richland, Washington 99352, United States
| | - Jamie R. Nuñez
- Pacific Northwest National Laboratory, Richland, Washington 99352, United States
| | - Nathan O. Hodas
- Pacific Northwest National Laboratory, Richland, Washington 99352, United States
| | - Courtney D. Corley
- Pacific Northwest National Laboratory, Richland, Washington 99352, United States
| | - Ryan R. Renslow
- Pacific Northwest National Laboratory, Richland, Washington 99352, United States
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Bohutskyi P, McClure RS, Hill EA, Nelson WC, Chrisler WB, Nuñez JR, Renslow RS, Charania MA, Lindemann SR, Beliaev AS. Metabolic effects of vitamin B12 on physiology, stress resistance, growth rate and biomass productivity of Cyanobacterium stanieri planktonic and biofilm cultures. ALGAL RES 2019. [DOI: 10.1016/j.algal.2019.101580] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
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Nuñez JR, Colby SM, Thomas DG, Tfaily MM, Tolic N, Ulrich EM, Sobus JR, Metz TO, Teeguarden JG, Renslow RS. Evaluation of In Silico Multifeature Libraries for Providing Evidence for the Presence of Small Molecules in Synthetic Blinded Samples. J Chem Inf Model 2019; 59:4052-4060. [PMID: 31430141 DOI: 10.1021/acs.jcim.9b00444] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
The current gold standard for unambiguous molecular identification in metabolomics analysis is comparing two or more orthogonal properties from the analysis of authentic reference materials (standards) to experimental data acquired in the same laboratory with the same analytical methods. This represents a significant limitation for comprehensive chemical identification of small molecules in complex samples. The process is time consuming and costly, and the majority of molecules are not yet represented by standards. Thus, there is a need to assemble evidence for the presence of small molecules in complex samples through the use of libraries containing calculated chemical properties. To address this need, we developed a Multi-Attribute Matching Engine (MAME) and a library derived in part from our in silico chemical library engine (ISiCLE). Here, we describe an initial evaluation of these methods in a blinded analysis of synthetic chemical mixtures as part of the U.S. Environmental Protection Agency's (EPA) Non-Targeted Analysis Collaborative Trial (ENTACT, Phase 1). For molecules in all mixtures, the initial blinded false negative rate (FNR), false discovery rate (FDR), and accuracy were 57%, 77%, and 91%, respectively. For high evidence scores, the FDR was 35%. After unblinding of the sample compositions, we optimized the scoring parameters to better exploit the available evidence and increased the accuracy for molecules suspected as present. The final FNR, FDR, and accuracy were 67%, 53%, and 96%, respectively. For high evidence scores, the FDR was 10%. This study demonstrates that multiattribute matching methods in conjunction with in silico libraries may one day enable reduced reliance on experimentally derived libraries for building evidence for the presence of molecules in complex samples.
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Affiliation(s)
- Jamie R Nuñez
- Earth and Biological Sciences Directorate , Pacific Northwest National Laboratory , Richland , Washington 99354 , United States
| | - Sean M Colby
- Earth and Biological Sciences Directorate , Pacific Northwest National Laboratory , Richland , Washington 99354 , United States
| | - Dennis G Thomas
- Earth and Biological Sciences Directorate , Pacific Northwest National Laboratory , Richland , Washington 99354 , United States
| | - Malak M Tfaily
- Earth and Biological Sciences Directorate , Pacific Northwest National Laboratory , Richland , Washington 99354 , United States.,Department of Environmental Science , University of Arizona , Tucson 85712 , United States
| | - Nikola Tolic
- Earth and Biological Sciences Directorate , Pacific Northwest National Laboratory , Richland , Washington 99354 , United States
| | - Elin M Ulrich
- U.S. Environmental Protection Agency, Office of Research and Development , National Exposure Research Laboratory , Research Triangle Park , North Carolina 27711 , United States
| | - Jon R Sobus
- U.S. Environmental Protection Agency, Office of Research and Development , National Exposure Research Laboratory , Research Triangle Park , North Carolina 27711 , United States
| | - Thomas O Metz
- Earth and Biological Sciences Directorate , Pacific Northwest National Laboratory , Richland , Washington 99354 , United States
| | - Justin G Teeguarden
- Earth and Biological Sciences Directorate , Pacific Northwest National Laboratory , Richland , Washington 99354 , United States.,Department of Environmental and Molecular Toxicology , Oregon State University , Corvallis , Oregon 97331 , United States
| | - Ryan S Renslow
- Earth and Biological Sciences Directorate , Pacific Northwest National Laboratory , Richland , Washington 99354 , United States
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Colby SM, Thomas DG, Nuñez JR, Baxter DJ, Glaesemann KR, Brown JM, Pirrung MA, Govind N, Teeguarden JG, Metz TO, Renslow RS. ISiCLE: A Quantum Chemistry Pipeline for Establishing in Silico Collision Cross Section Libraries. Anal Chem 2019; 91:4346-4356. [PMID: 30741529 PMCID: PMC6526953 DOI: 10.1021/acs.analchem.8b04567] [Citation(s) in RCA: 68] [Impact Index Per Article: 13.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
High-throughput, comprehensive, and confident identifications of metabolites and other chemicals in biological and environmental samples will revolutionize our understanding of the role these chemically diverse molecules play in biological systems. Despite recent technological advances, metabolomics studies still result in the detection of a disproportionate number of features that cannot be confidently assigned to a chemical structure. This inadequacy is driven by the single most significant limitation in metabolomics, the reliance on reference libraries constructed by analysis of authentic reference materials with limited commercial availability. To this end, we have developed the in silico chemical library engine (ISiCLE), a high-performance computing-friendly cheminformatics workflow for generating libraries of chemical properties. In the instantiation described here, we predict probable three-dimensional molecular conformers (i.e., conformational isomers) using chemical identifiers as input, from which collision cross sections (CCS) are derived. The approach employs first-principles simulation, distinguished by the use of molecular dynamics, quantum chemistry, and ion mobility calculations, to generate structures and chemical property libraries, all without training data. Importantly, optimization of ISiCLE included a refactoring of the popular MOBCAL code for trajectory-based mobility calculations, improving its computational efficiency by over 2 orders of magnitude. Calculated CCS values were validated against 1983 experimentally measured CCS values and compared to previously reported CCS calculation approaches. Average calculated CCS error for the validation set is 3.2% using standard parameters, outperforming other density functional theory (DFT)-based methods and machine learning methods (e.g., MetCCS). An online database is introduced for sharing both calculated and experimental CCS values ( metabolomics.pnnl.gov ), initially including a CCS library with over 1 million entries. Finally, three successful applications of molecule characterization using calculated CCS are described, including providing evidence for the presence of an environmental degradation product, the separation of molecular isomers, and an initial characterization of complex blinded mixtures of exposure chemicals. This work represents a method to address the limitations of small molecule identification and offers an alternative to generating chemical identification libraries experimentally by analyzing authentic reference materials. All code is available at github.com/pnnl .
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Affiliation(s)
- Sean M. Colby
- Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland, Washington 99352, United States
| | - Dennis G. Thomas
- Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland, Washington 99352, United States
| | - Jamie R. Nuñez
- Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland, Washington 99352, United States
| | - Douglas J. Baxter
- Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland, Washington 99352, United States
| | - Kurt R. Glaesemann
- Communications and Information Technology Directorate, Pacific Northwest National Laboratory, Richland, Washington 99352, United States
| | - Joseph M. Brown
- Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland, Washington 99352, United States
| | - Meg A. Pirrung
- National Security Directorate, Pacific Northwest National Laboratory, Richland, Washington 99352, United States
| | - Niranjan Govind
- Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland, Washington 99352, United States
| | - Justin G. Teeguarden
- Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland, Washington 99352, United States
- Department of Environmental and Molecular Toxicology, Oregon State University, Corvallis, Oregon 97331, United States
| | - Thomas O. Metz
- Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland, Washington 99352, United States
| | - Ryan S. Renslow
- Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland, Washington 99352, United States
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Nuñez JR, Anderton CR, Renslow RS. Optimizing colormaps with consideration for color vision deficiency to enable accurate interpretation of scientific data. PLoS One 2018; 13:e0199239. [PMID: 30067751 PMCID: PMC6070163 DOI: 10.1371/journal.pone.0199239] [Citation(s) in RCA: 65] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2017] [Accepted: 06/04/2018] [Indexed: 11/24/2022] Open
Abstract
Color vision deficiency (CVD) affects more than 4% of the population and leads to a different visual perception of colors. Though this has been known for decades, colormaps with many colors across the visual spectra are often used to represent data, leading to the potential for misinterpretation or difficulty with interpretation by someone with this deficiency. Until the creation of the module presented here, there were no colormaps mathematically optimized for CVD using modern color appearance models. While there have been some attempts to make aesthetically pleasing or subjectively tolerable colormaps for those with CVD, our goal was to make optimized colormaps for the most accurate perception of scientific data by as many viewers as possible. We developed a Python module, cmaputil, to create CVD-optimized colormaps, which imports colormaps and modifies them to be perceptually uniform in CVD-safe colorspace while linearizing and maximizing the brightness range. The module is made available to the science community to enable others to easily create their own CVD-optimized colormaps. Here, we present an example CVD-optimized colormap created with this module that is optimized for viewing by those without a CVD as well as those with red-green colorblindness. This colormap, cividis, enables nearly-identical visual-data interpretation to both groups, is perceptually uniform in hue and brightness, and increases in brightness linearly.
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Affiliation(s)
- Jamie R. Nuñez
- Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland, Washington, United States of America
| | - Christopher R. Anderton
- Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland, Washington, United States of America
| | - Ryan S. Renslow
- Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland, Washington, United States of America
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Abstract
A specific program was adopted to obtain organs, for transplant purposes from people who die at home or in the street from sudden or unexpected death (type I non-heart-beating donors [NHBD] according to the Maastricht classification). The objective of our program was to increase the donor pool by obtaining organs from well-selected potential donors who die at home, work, or in the street and are maintained on advanced life support (ALS) until hospital arrival. The great number of people who die in a previously healthy situation constitute an excellent source of organs for transplant purposes. Our program includes pre- and in-hospital attendance. Prehospital attendance is based on application of cardiopulmonary resuscitation in situ and ALS until arrival at hospital. In hospital, specific preservation maneuvers must be performed and family assessment and judge permission obtained. In the last 15 years, we developed a kidney transplant program with better results than transplants performed with organs obtained from encephalic death donors (EDD). A specific NHBD subprogram for lung transplant was developed with excellent results as well. We are now improving the liver transplant program. NHBD are an important source of human tissues, including pancreas islets. It is clear that NHBD are a great source of organs and tissues for transplant, and that this kind of program must be established in all countries in which legal regulations allow it.
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Affiliation(s)
- J R Nuñez
- Hospital Clinico San Carlos, Madrid, Spain.
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Martinez-Ramos C, Sanz MG, Pardo P, Nuñez JR, Soriano E, Escobar ST. Denervation of the greater curvature in proximal gastric vagotomy. World J Surg 1983; 7:604-9. [PMID: 6636804 DOI: 10.1007/bf01655336] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
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Ramos CM, Pelayo A, de Vega DS, Jerez L, Cazenave E, Pardo P, Nuñez JR, Tamames S. Localization of the antral-corpus boundary in proximal gastric vagotomy: an experimental comparative study. World J Surg 1983; 7:260-5. [PMID: 6868638 DOI: 10.1007/bf01656157] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.0] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
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