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9. Computational methods for NMR and MS for structure elucidation III: More advanced approaches

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Volume 1 Fundamental Concepts
This chapter is in the book Volume 1 Fundamental Concepts

Abstract

The structural assignment of natural products, even with the very sophisticated one-dimensional and two-dimensional (1D and 2D) spectroscopic methods available today, is still a tedious and time-consuming task. Mass spectrometry (MS) is generally used for molecular mass determination, molecular formula generation and MS/MSn fragmentation patterns of molecules. In the meantime, nuclear magnetic resonance (NMR) spectroscopy provides spectra (e. g. 1 H, 13C and correlation spectra) whose interpretation allows the structure determination of known or unknown compounds. With the advance of high throughput studies, like metabolomics, the fast and automated identification or annotation of natural products became highly demanded. Some growing tools to meet this demand apply computational methods for structure elucidation. These methods act on characteristic parameters in the structural determination of small molecules. We have numbered and herein present existing and reputed computational methods for peak picking analysis, resonance assignment, nuclear Overhauser effect (NOE) assignment, combinatorial fragmentation and structure calculation and prediction. Fully automated programs in structure determination are also mentioned, together with their integrated algorithms used to elucidate the structure of a metabolite. The use of these automated tools has helped to significantly reduce errors introduced by manual processing and, hence, accelerated the structure identification or annotation of compounds.

Abstract

The structural assignment of natural products, even with the very sophisticated one-dimensional and two-dimensional (1D and 2D) spectroscopic methods available today, is still a tedious and time-consuming task. Mass spectrometry (MS) is generally used for molecular mass determination, molecular formula generation and MS/MSn fragmentation patterns of molecules. In the meantime, nuclear magnetic resonance (NMR) spectroscopy provides spectra (e. g. 1 H, 13C and correlation spectra) whose interpretation allows the structure determination of known or unknown compounds. With the advance of high throughput studies, like metabolomics, the fast and automated identification or annotation of natural products became highly demanded. Some growing tools to meet this demand apply computational methods for structure elucidation. These methods act on characteristic parameters in the structural determination of small molecules. We have numbered and herein present existing and reputed computational methods for peak picking analysis, resonance assignment, nuclear Overhauser effect (NOE) assignment, combinatorial fragmentation and structure calculation and prediction. Fully automated programs in structure determination are also mentioned, together with their integrated algorithms used to elucidate the structure of a metabolite. The use of these automated tools has helped to significantly reduce errors introduced by manual processing and, hence, accelerated the structure identification or annotation of compounds.

Chapters in this book

  1. Frontmatter I
  2. About the Editor VII
  3. Contents IX
  4. List of contributing authors XIX
  5. Editorial: Chemoinformatics at the service of natural product discovery 1
  6. Part I: Foundational Chemoinformatics Concepts for Natural Product-based Drug Discovery
  7. 1. Secondary metabolites, their structural diversity, bioactivity, and ecological functions: An overview 7
  8. 2. Fundamental physical and chemical concepts behind “drug-likeness” and “natural product-likeness” 55
  9. 3. “Drug-likeness” properties of natural compounds 81
  10. 4. Chemical space of naturally occurring compounds 103
  11. 5. From natural products to drugs 125
  12. Part II: Chemoinformatics Tools and Methods for Natural Product Structure Elucidation
  13. 6. An overview of tools, software, and methods for natural product fragment and mass spectral analysis 157
  14. 7. Computational methods for NMR and MS for structure elucidation I: software for basic NMR 177
  15. 8. Computational methods for NMR and MS for structure elucidation II: database resources and advanced methods 205
  16. 9. Computational methods for NMR and MS for structure elucidation III: More advanced approaches 229
  17. Part III: Chemoinformatics Tools and Methods for Lead Compound Discovery and Development
  18. 10. A primer on natural product-based virtual screening 251
  19. 11. Drug target prediction using chem- and bioinformatics 291
  20. 12. Computer-based techniques for lead identification and optimization I: Basics 311
  21. 13. Computer-based techniques for lead identification and optimization II: Advanced search methods 333
  22. 14. Prediction of toxicity of secondary metabolites 361
  23. Part IV: Case Studies
  24. 15. Cheminformatics techniques in antimalarial drug discovery and development from natural products 1: basic concepts 381
  25. 16. Cheminformatics techniques in antimalarial drug discovery and development from natural products 2: Molecular scaffold and machine learning approaches 397
  26. Glossary of terms used in chemoinformatics of natural products: fundamental principles 417
  27. Index 443
https://doi.org/10.1515/9783110579352-010

Chapters in this book

  1. Frontmatter I
  2. About the Editor VII
  3. Contents IX
  4. List of contributing authors XIX
  5. Editorial: Chemoinformatics at the service of natural product discovery 1
  6. Part I: Foundational Chemoinformatics Concepts for Natural Product-based Drug Discovery
  7. 1. Secondary metabolites, their structural diversity, bioactivity, and ecological functions: An overview 7
  8. 2. Fundamental physical and chemical concepts behind “drug-likeness” and “natural product-likeness” 55
  9. 3. “Drug-likeness” properties of natural compounds 81
  10. 4. Chemical space of naturally occurring compounds 103
  11. 5. From natural products to drugs 125
  12. Part II: Chemoinformatics Tools and Methods for Natural Product Structure Elucidation
  13. 6. An overview of tools, software, and methods for natural product fragment and mass spectral analysis 157
  14. 7. Computational methods for NMR and MS for structure elucidation I: software for basic NMR 177
  15. 8. Computational methods for NMR and MS for structure elucidation II: database resources and advanced methods 205
  16. 9. Computational methods for NMR and MS for structure elucidation III: More advanced approaches 229
  17. Part III: Chemoinformatics Tools and Methods for Lead Compound Discovery and Development
  18. 10. A primer on natural product-based virtual screening 251
  19. 11. Drug target prediction using chem- and bioinformatics 291
  20. 12. Computer-based techniques for lead identification and optimization I: Basics 311
  21. 13. Computer-based techniques for lead identification and optimization II: Advanced search methods 333
  22. 14. Prediction of toxicity of secondary metabolites 361
  23. Part IV: Case Studies
  24. 15. Cheminformatics techniques in antimalarial drug discovery and development from natural products 1: basic concepts 381
  25. 16. Cheminformatics techniques in antimalarial drug discovery and development from natural products 2: Molecular scaffold and machine learning approaches 397
  26. Glossary of terms used in chemoinformatics of natural products: fundamental principles 417
  27. Index 443
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