Issue 1, 2022

A critical review on the use of DP4+ in the structural elucidation of natural products: the good, the bad and the ugly. A practical guide

Abstract

Covering: 2015 up to the end of 2020

Even in the golden age of NMR, the number of natural products being incorrectly assigned is becoming larger every day. The use of quantum NMR calculations coupled with sophisticated data analysis provides ideal complementary tools to facilitate the elucidation process in challenging cases. Among the current computational methodologies to perform this task, the DP4+ probability is a popular and widely used method. This updated version of Goodman's DP4 synergistically combines NMR calculations at higher levels of theory with the Bayesian analysis of both scaled and unscaled data. Since its publication in late 2015, the use of DP4+ to solve controversial natural products has substantially grown, with several predictions being confirmed by total synthesis. To date, the structures of more than 200 natural products were determined with the aid of DP4+. However, all that glitters is not gold. Besides its intrinsic limitations, on many occasions it has been improperly used with potentially important consequences on the quality of the assignment. Herein we present a critical revision on how the scientific community has been using DP4+, exploring the strengths of the method and how to obtain optimal results from it. We also analyze the weaknesses of DP4+, and the paths to by-pass them to maximize the confidence in the structural elucidation.

Graphical abstract: A critical review on the use of DP4+ in the structural elucidation of natural products: the good, the bad and the ugly. A practical guide

Article information

Article type
Review Article
Submitted
05 May 2021
First published
02 Jul 2021

Nat. Prod. Rep., 2022,39, 58-76

A critical review on the use of DP4+ in the structural elucidation of natural products: the good, the bad and the ugly. A practical guide

M. O. Marcarino, S. Cicetti, M. M. Zanardi and A. M. Sarotti, Nat. Prod. Rep., 2022, 39, 58 DOI: 10.1039/D1NP00030F

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