General Quantum-Based NMR Method for the Assignment of Absolute Configuration by Single or Double Derivatization: Scope and Limitations

Study of heavy atom influence on poly-halogenated compounds using DP4/MM-DP4+/DP4+: insights and trends

Nuclear magnetic resonance (NMR) spectroscopy complemented by density functional theory (DFT) calculations is a crucial tool for structural elucidation. Nevertheless, the precision of NMR predictions is influenced by the 'heavy atom effect', wherein heavy atoms affect the shielding values of neighboring light atoms (HALA effect). Standard practice in the field involves removing the conflicting signals. However, in the case of polyhalogenated molecules, this is challenging due to the significant amount of information that ends up being lost. In this study the HALA is thoroughly investigated in the context of three leading probability methods: DP4, MM-DP4+, and DP4+. The results show that DP4+ is more sensitive to C-Cl or C-Br signals, which is a consequence of the longer bond lengths computed with DFT. Removing conflicting signals is highly effective in DP4+, but has an uncertain outcome in methods based on molecular mechanics geometries, such as DP4 and MM-DP4+. A detailed investigation of the effect of bond distance on the corresponding chemical shifts has also been conducted.

Characteristic chromanone acids from Calophyllum membranaceum: Determination of C-3 configuration and anti-inflammatory activity

One undescribed homologous furanochromanone (1) featuring a 6/6/5/3 tetracyclic skeleton and four highly oxidized pyranochromanones (2-5), along with a set of four pyranochromanone stereoisomers [(±)-6a and (±)-6b], were isolated from the leaves of Calophyllum membranaceum Gardn. Et Champ. Their structures were elucidated by using spectroscopic data, Snatzke's method, quantum-chemical calculations, and X-ray crystallographic analysis. The correlation of characteristic Cotton effects and specific chemical shifts with C-3 configuration provided a convenient approach to assign the C-3 configuration of 2,3-dimethylchromanones. The stereochemical assignments of 3-OH substituted pyranochromanones by quantum-based NMR methods following single/double MTPA derivatization were consistent with the ECD/NMR prediction, which verified the feasibility and reliability of the proposed empirical rule. The underlying mechanism was further clarified by conformational and molecular orbital analyses. Moreover, biological evaluation and binding assays demonstrated that compound 3 (KD = 0.45 μM) tightly binds to the TLR4-MD2 target, thereby inhibiting the TLR4/MyD88-dependent and -independent signal pathways. This study provides the first evidence that Calophyllum chromanones are a novel structural type of TLR4 inhibitors, exerting their anti-inflammatory effects by disrupting the binding between TLR4 and MD2.

Straightforward synthesis of chiral sulfonate-based ionic liquids from amino alcohols for chiral recognition

New sulfonate-based chiral salts were prepared from amino alcohols and sodium hydroxymethanesulfonate, vinyl sulfonate, or sultone. The synthesis started with different amino acids from the chiral pool and gave the desired products in just four steps. After cation metathesis, the salts were explored as chiral solvating agents (CSAs) in NMR studies. The new chiral ionic liquids (CILs) were successfully able to interact with different chiral guest molecules and formed diastereomeric aggregates. In some cases, baseline separation was observed. The influence of the structural differences in the CIL as well as the structural requirements of the guest molecule is discussed.

Machine learning-assisted structure annotation of natural products based on MS and NMR data

Covering: up to March 2023Machine learning (ML) has emerged as a popular tool for analyzing the structures of natural products (NPs). This review presents a summary of the recent advancements in ML-assisted mass spectrometry (MS) and nuclear magnetic resonance (NMR) data analysis to establish the chemical structures of NPs. First, ML-based MS/MS analyses that rely on library matching are discussed, which involves the utilization of ML algorithms to calculate similarity, predict the MS/MS fragments, and form molecular fingerprint. Then, ML assisted MS/MS structural annotation without library matching is reviewed. Furthermore, the cases of ML algorithms in assisting structural studies of NPs based on NMR are discussed from four perspectives: NMR prediction, functional group identification, structural categorization and quantum chemical calculation. Finally, the review concludes with a discussion of the challenges and the trends associated with the structural establishment of NPs based on ML algorithms.

DP4+App: Finding the Best Balance between Computational Cost and Predictive Capacity in the Structure Elucidation Process by DP4+. Factors Analysis and Automation

DP4+ is one of the most popular methods for the structure elucidation of natural products using NMR calculations. While the method is simple and easy to implement, it requires a series of procedures that can be tedious, coupled with the fact that its computational demand can be high in certain cases. In this work, we made a substantial improvement to these limitations. First, we deeply explored the effect of molecular mechanics architecture on the DP4+ formalism (MM-DP4+). In addition, a Python applet (DP4+App) was developed to automate the entire process, requiring only the Gaussian NMR output files and a spreadsheet containing the experimental NMR data and labels. The script is designed to use the statistical parameters from the original 24 levels of theory (employing B3LYP/6-31G* geometries) and the new 36 levels explored in this work (over MMFF geometries). Furthermore, it enables the development of customizable methods using any desired level of theory, allowing for a free choice of test molecules.

E/Z configurational determination of oximes and related derivatives through quantum mechanics NMR calculations: scope and limitations of the leading probabilistic methods

Oximes and related derivatives featuring a CN double bond are important in many areas of chemistry. Different methods for the determination of the E/Z configuration have been developed, each with its own scope and limitations. While some cannot be used when only one isomer is available, others require special NMR experiments. Here, three popular computational methodologies (DP4, DP4+, and ML-J-DP4) have been thoroughly studied using a challenging test set. Although DP4+ provides the best confidence, its computational cost might be high. On the other hand, ML-J-DP4 shows excellent performance in most cases in a fraction of CPU time. A detailed analysis of the structural factors affecting the NMR prediction and sense of the assignment is also provided.

Anti-inflammatory abietanes diterpenes and triterpenoids isolated from Clinopodium polycephalum

Two previously undescribed diterpenes (1 and 2), as well as one curious triterpenoid were isolated from Clinopodium polycephalum, a medicinal plant distributed in southwestern and eastern China. Their structures were elucidated using MS analyses, UV spectrum, and extensive 2D-homo and heteronuclear NMR data interpretations. Among them, 1 had an unusual skeletal characteristic produced by a rare methyl migration pathway. All monomer compounds exhibited inhibitory effects on NO production in LPS-induced RAW 264.7 cells without affecting cell viabilities, which were comparable to that of positive control.

Novel Triterpenoid Alkaloids With Their Potential Cytotoxic Activity From the Roots of Siraitia grosvenorii

Four novel triterpenoid alkaloids, siragrosvenins A–D (1–4), and two new cucurbitane-type triterpenoids, siragrosvenins E–F (5, 6), together with eight known analogs (7−14), were isolated from the roots of Siraitia grosvenorii. Compounds 1−4 possessed a rare cucurbitane-type triterpenoid scaffold, featuring an extra pyrazine unit via the Strecker reaction in the cucurbitane framework. Compound 5 displayed a 6/6/6/5/6/5-fused polycyclic ring system, with an uncommon fused furan and pyran ring in the side chain. All the structures were characterized by extensive spectroscopic analysis, including HRESIMS, NMR, and X-ray crystallographic data. It is worth noting that the DP4⁺ analysis method was applied for the first time to determine the absolute configurations of the trihydroxybutyl moiety in the side chain of compounds 1–4. In vitro cytotoxicity screening found that compounds 4, 8, 9, 13, and 14 exhibited remarkable cytotoxic activities against three cell lines with IC₅₀ values ranging from 1.44 to 9.99 μM. Siragrosvenin D shows remarkable cytotoxic activity on MCF-7 cells. As a result, it inhibited the proliferation of MCF-7 cells and reduced their viability via the induction of G2/M phase arrest and significantly induced apoptosis in MCF-7 cells.

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

Covering: 2015 up to the end of 2020Even 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.

The Future of Retrosynthesis and Synthetic Planning: Algorithmic, Humanistic or the Interplay?

The practice of deploying and teaching retrosynthesis is on the cusp of considerable change, which in turn forces practitioners and educators to contemplate whether this impending change will advance or erode the efficiency and elegance of organic synthesis in the future. A short treatise is presented herein that covers the concept of retrosynthesis, along with exemplified methods and theories, and an attempt to comprehend the impact of artificial intelligence in an era when freely and commercially available retrosynthetic and forward synthesis planning programs are increasingly prevalent. Will the computer ever compete with human retrosynthetic design and the art of organic synthesis?

NMR Calculations with Quantum Methods: Development of New Tools for Structural Elucidation and Beyond

Structural elucidation is an important and challenging stage in the discovery of new organic molecules. Single-crystal X-ray analysis provides the most unquestionable results, though in practice the availability of suitable crystals limits its broad use. On the other hand, NMR spectroscopy has become the leading and universal technique to accomplish the task. Despite continuous advances in the field, the misinterpretation of NMR data is commonplace, evidenced by the large number of erroneous structures being published in top journals. Quantum calculations of NMR chemical shifts and scalar coupling constants emerged as ideal complements to facilitate the elucidation process when experimental NMR data is inconclusive. Since seminal reports demonstrated that affordable DFT methods provide NMR predictions accurate enough to differentiate among closely related isomers, the discipline has experienced substantial growth. The impact has been felt in different areas, and nowadays the results of such calculations are routinely seen in high impact literature.This Account describes our investigations in the field of quantum NMR calculations, focusing on the development of tools for structural elucidation and practical applications. We pioneered the use of artificial intelligence methods in the development of novel strategies of structural validation. Our first generation of trained artificial neural networks (ANNs) showed excellent ability to identify mistakes at the atom connectivity level, whereas the use of multidimensional pattern recognition pushed the performance to the stereochemical limit. In a conceptually different approach, we developed DP4+, an updated version of the DP4 probability used to determine the most likely structure among two or more candidates when one set of experimental data is available. Increasing the level of theory in NMR calculations and including unscaled data in the formalism improved the performance of the method, further validated to settle the configuration of challenging motifs such as spiroepoxides or Mosher's derivatives. One of the limitations of DP4+ is related to the relatively large computational cost involved in obtaining DFT-optimized geometries, which led to the development of a fast variant including the valuable information provided by coupling constants (J-DP4 method).These tools were explored to suggest the most probable structure of controversial natural or unnatural products originally misassigned, with some predictions further validated by synthesis (as in the case of pseudorubriflordilactone B). The possibility of predicting the structure of a natural product without requiring authentic sample was investigated in collaboration with Prof. Pilli (UNICAMP, Brazil) in the computer-guided total synthesis and stereochemical revisions of several natural products. Despite these advances, there remain considerable challenges, such as the case of configurational assessment of polar systems featuring multiple intramolecular hydrogen bonding interactions because of the poor energy predictions provided by most DFT methods. In our latest work, we tackle this problem by averaging the results provided by randomly generated ensembles, paving the way for a new paradigm in quantum NMR-assisted structural elucidation.

Unlocking the potential of late-stage functionalisation: an accurate and fully automated method for the rapid characterisation of multiple regioisomeric products

An automated pipeline for structure determination is outlined that will help unlock the potential of late-stage functionalisation (LSF).

The 125Te Chemical Shift of Diphenyl Ditelluride: Chasing Conformers over a Flat Energy Surface

The interest in diphenyl ditelluride (Ph₂Te₂) is related to its strict analogy to diphenyl diselenide (Ph₂Se₂), whose capacity to reduce organic peroxides is largely exploited in catalysis and green chemistry. Since the latter is also a promising candidate as an antioxidant drug and mimic of the ubiquitous enzyme glutathione peroxidase (GPx), the use of organotellurides in medicinal chemistry is gaining importance, despite the fact that tellurium has no recognized biological role and its toxicity must be cautiously pondered. Both Ph₂Se₂ and Ph₂Te₂ exhibit significant conformational freedom due to the softness of the inter-chalcogen and carbon–chalcogen bonds, preventing the existence of a unique structure in solution. Therefore, the accurate calculation of the NMR chemical shifts of these flexible molecules is not trivial. In this study, a detailed structural analysis of Ph₂Te₂ is carried out using a computational approach combining classical molecular dynamics and relativistic density functional theory methods. The goal is to establish how structural changes affect the electronic structure of diphenyl ditelluride, particularly the ¹²⁵Te chemical shift.

An Unusual Benzoisoquinoline-9-one Derivative and Other Related Compounds with Antiproliferative Activity from Hawaiian Endophytic Fungus Peyronellaea sp. FT431

A new polyketide containing the benzoisoquinoline-9-one moiety, peyronetide A (1), and three other new derivatives peyronetides B–D (2–4), as well as one known compound (5) were purified from the cultured broth of the endophytic fungus Peyronellaea sp. FT431, which was isolated from the Hawaiian indigenous plant, Verbena sp. The structures of the new compounds were determined through the analysis of HRMS and NMR spectroscopic data. Compounds 1, 2, and 5 showed cytotoxic activities against TK-10 (human kidney adenocarcinoma cells), cisplatin sensitive A2780S (human ovarian carcinoma cells), and cisplatin resistant A2780CisR cell lines, with IC₅₀ values between 6.7 to 29.2 μM.