Computationally Assisted Analysis of NMR Chemical Shifts as a Tool in Conformational Analysis

A key to understanding the properties of functional molecules is to determine their conformation in solution. A conformational analysis procedure that relies on quantum mechanical calculations and the widely used DP4+ probability was evaluated to decipher the structural information encoded in NMR chemical shifts. The results underscore the potential utility of using NMR chemical shifts in advancing conformational analysis studies of complex molecules in solution.

Influence of Solvent Polarity on the Conformer Ratio of Bicalutamide in Saturated Solutions: Insights from NOESY NMR Analysis and Quantum-Chemical Calculations

The study presents a thorough and detailed analysis of bicalutamide's structural and conformational properties. Quantum chemical calculations were employed to explore the conformational properties of the molecule, identifying significant energy differences between conformers. Analysis revealed that hydrogen bonds stabilise the conformers, with notable variations in torsion angles. Conformers were classified into 'closed' and 'open' types based on the relative orientation of the cyclic fragments. NOE spectroscopy in different solvents (CDCl3 and DMSO-d6) was used to study the conformational preferences of the molecule. NOESY experiments provided the predominance of 'closed' conformers in non-polar solvents and a significant presence of 'open' conformers in polar solvents. The proportions of open conformers were 22.7 ± 3.7% in CDCl3 and 59.8 ± 6.2% in DMSO-d6, while closed conformers accounted for 77.3 ± 3.7% and 40.2 ± 6.2%, respectively. This comprehensive study underscores the solvent environment's impact on its structural behaviour. The findings significantly contribute to a deeper understanding of conformational dynamics, stimulating further exploration in drug development.

An optimized purification protocol for enzymatically synthesized S-adenosyl-L-methionine (SAM) for applications in solution state infrared spectroscopic studies

S-adenosyl-L-methionine (SAM) is an abundant biomolecule used by methyltransferases to regulate a wide range of essential cellular processes such as gene expression, cell signaling, protein functions, and metabolism. Despite considerable effort, there remain many specificity challenges associated with designing small molecule inhibitors for methyltransferases, most of which exhibit off-target effects. Interestingly, NMR evidence suggests that SAM undergoes conformeric exchange between several states when free in solution. Infrared spectroscopy can detect different conformers of molecules if present in appreciable populations. When SAM is noncovalently bound within enzyme active sites, the nature and the number of different conformations of the molecule are likely to be altered from when it is free in solution. If there are unique structures or different numbers of conformers between different methyltransferase active sites, solution-state information may provide promising structural leads to increase inhibitor specificity for a particular methyltransferase. Toward this goal, frequencies measured in SAM's infrared spectra must be assigned to the motions of specific atoms via isotope incorporation at discrete positions. The incorporation of isotopes into SAM's structure can be accomplished via an established enzymatic synthesis using isotopically labeled precursors. However, published protocols produced an intense and highly variable IR signal which overlapped with many of the signals from SAM rendering comparison between isotopes challenging. We observed this intense absorption to be from co-purifying salts and the SAM counterion, producing a strong, broad signal at 1100 cm-1. Here, we report a revised SAM purification protocol that mitigates the contaminating salts and present the first IR spectra of isotopically labeled CD3-SAM. These results provide a foundation for isotopic labeling experiments of SAM that will define which atoms participate in individual molecular vibrations, as a means to detect specific molecular conformations.

Conformational Preferences at the Glycosidic Linkage of Saccharides in Solution as Deduced from NMR Experiments and MD Simulations: Comparison to Crystal Structures

Glycans are central to information content and regulation in biological systems. These carbohydrate molecules are active either as oligo- or polysaccharides, often in the form of glycoconjugates. The monosaccharide entities are joined by glycosidic linkages and stereochemical arrangements are of utmost importance in determining conformation and flexibility of saccharides. The conformational preferences and population distributions at the glycosidic torsion angles φ and ψ have been investigated for O-methyl glycosides of three disaccharides where the substitution takes place at a secondary alcohol, viz., in α-l-Fucp-(1→3)-β-d-Glcp-OMe, α-l-Fucp-(1→3)-α-d-Galp-OMe and α-d-Glcp-(1→4)-α-d-Galp-OMe, corresponding to disaccharide structural elements present in bacterial polysaccharides. Stereochemical differences at or adjacent to the glycosidic linkage were explored by solution state NMR spectroscopy using one-dimensional 1 H,1 H-NOESY NMR experiments to obtain transglycosidic proton-proton distances and one- and two-dimensional heteronuclear NMR experiments to obtain 3 JCH transglycosidic coupling constants related to torsion angles φ and ψ. Computed effective proton-proton distances from molecular dynamics (MD) simulations showed excellent agreement to experimentally derived distances for the α-(1→3)-linked disaccharides and revealed that for the bimodal distribution at the ψ torsion angle for the α-(1→4)-linked disaccharide experiment and simulation were at variance with each other, calling for further force field developments. The MD simulations disclosed a highly intricate inter-residue hydrogen bonding pattern for the α-(1→4)-linked disaccharide, including a nonconventional hydrogen bond between H5' in the glucosyl residue and O3 in the galactosyl residue, supported by a large downfield 1 H NMR chemical shift displacement compared to α-d-Glcp-OMe. Comparison of population distributions of the glycosidic torsion angles φ and ψ in the disaccharide entities to those of corresponding crystal structures highlighted the potential importance of solvation on the preferred conformation.

Conformational State of Fenamates at the Membrane Interface: A MAS NOESY Study

The present work analyzes the ¹H NOESY MAS NMR spectra of three fenamates (mefenamic, tolfenamic, and flufenamic acids) localized in the lipid-water interface of phosphatidyloleoylphosphatidylcholine (POPC) membranes. The observed cross-peaks in the two-dimensional NMR spectra characterized intramolecular proximities between the hydrogen atoms of the fenamates as well as intermolecular interactions between the fenamates and POPC molecules. The peak amplitude normalization for an improved cross-relaxation (PANIC) approach, the isolated spin-pair approximation (ISPA) model, and the two-position exchange model were used to calculate the interproton distances indicative of specific conformations of the fenamates. The results showed that the proportions of the A+C and B+D conformer groups of mefenamic and tolfenamic acids in the presence of POPC were comparable within the experimental error and amounted to 47.8%/52.2% and 47.7%/52.3%, respectively. In contrast, these proportions for the flufenamic acid conformers differed and amounted to 56.6%/43.4%. This allowed us to conclude that when they bind to the POPC model lipid membrane, fenamate molecules change their conformational equilibria.

Investigation of the Spatial Structure of Flufenamic Acid in Supercritical Carbon Dioxide Media via 2D NOESY

The search for new forms of already known drug compounds is an urgent problem of high relevance as more potent drugs with fewer side effects are needed. The trifluoromethyl group in flufenamic acid renders its chemical structure differently from other fenamates. This modification is responsible for a large number of conformational polymorphs. Therefore, flufenamic acid is a promising structural modification of well-known drug molecules. An effective approach in this field is micronization, employing "green" supercritical fluid technologies. This research raises some key questions to be answered on how to control polymorphic forms during the micronization of drug compounds. The results presented in this work demonstrate the ability of two-dimensional nuclear Overhauser effect spectroscopy to determine conformational preferences of small molecular weight drug compounds in solutions and fluids, which can be used to predict the polymorphic form during the micronization. Quantitative analysis was carried out to identify the conformational preferences of flufenamic acid molecules in dimethyl sulfoxide-d6 medium at 25 °C and 0.1 MPa, and in mixed solvent medium containing supercritical carbon dioxide at 45 °C and 9 MPa. The data presented allows predictions of the flufenamic acid conformational preferences of poorly soluble drug compounds to obtain new micronized forms.

The Role of Hidden Conformers in Determination of Conformational Preferences of Mefenamic Acid by NOESY Spectroscopy

Mefenamic acid has been used as a non-steroidal anti-inflammatory drug for a long time. However, its practical use is quite limited due to a number of side effects on the intestinal organs. Conformational polymorphism provides mefenamic acid with unique properties regarding possible modifications obtained during the micronization process, which can improve pharmacokinetics and minimize side effects. Micronization can be performed by decompression of supercritical fluids; methods such as rapid expansion of the supercritical solution have proven their efficiency. However, this group of methods is poorly applicable for compounds with low solubility, and the modification of the method using a pharmaceutically suitable co-solvent may be useful. In our case, addition of only 2 mol% dimethyl sulfoxide increased the solubility remarkably. Information on the conformational state may be critically important for carrying out micronization. In this work, structural analysis and estimate of conformational preferences of mefenamic acid in dimethyl sulfoxide-d6 (at 25 °C and 0.1 MPa) and in a mixed solvent supercritical carbon dioxide + dimethyl sulfoxide-d6 (45 °C, 9 MPa) were performed based on nuclear Overhauser effect spectroscopy. Results show changes in the conformation fractions depending on the medium used. The importance of allowing for hidden conformers in estimating the conformational state was demonstrated in the analysis. Obtained results may be useful for improving micronization parameters.

Activation of Glycyl Radical Enzymes─Multiscale Modeling Insights into Catalysis and Radical Control in a Pyruvate Formate-Lyase-Activating Enzyme

Pyruvate formate-lyase (PFL) is a glycyl radical enzyme (GRE) playing a pivotal role in the metabolism of strict and facultative anaerobes. Its activation is carried out by a PFL-activating enzyme, a member of the radical S-adenosylmethionine (rSAM) superfamily of metalloenzymes, which introduces a glycyl radical into the Gly radical domain of PFL. The activation mechanism is still not fully understood and is structurally based on a complex with a short model peptide of PFL. Here, we present extensive molecular dynamics simulations in combination with quantum mechanics/molecular mechanics (QM/MM)-based kinetic and thermodynamic reaction evaluations of a more complete activation model comprising the 49 amino acid long C-terminus region of PFL. We reveal the benefits and pitfalls of the current activation model, providing evidence that the bound peptide conformation does not resemble the bound protein-protein complex conformation with PFL, with implications for the activation process. Substitution of the central glycine with (S)- and (R)-alanine showed excellent binding of (R)-alanine over unstable binding of (S)-alanine. Radical stabilization calculations indicate that a higher radical stability of the glycyl radical might not be the sole origin of the evolutionary development of GREs. QM/MM-derived radical formation kinetics further demonstrate feasible activation barriers for both peptide and C-terminus activation, demonstrating why the crystalized model peptide system is an excellent inhibitory system for natural activation. This new evidence supports the theory that GREs converged on glycyl radical formation due to the better conformational accessibility of the glycine radical loop, rather than the highest radical stability of the formed peptide radicals.

ML-J-DP4: An Integrated Quantum Mechanics-Machine Learning Approach for Ultrafast NMR Structural Elucidation

A new tool, ML-J-DP4, provides an efficient and accurate method for determining the most likely structure of complex molecules within minutes using standard computational resources. The workflow involves combining fast Karplus-type J calculations with NMR chemical shifts predictions at the cheapest HF/STO-3G level enhanced using machine learning (ML), all embedded in the J-DP4 formalism. Our ML provides accurate predictions, which compare favorably alongside with other ML methods.

Minimizing the risk of deducing wrong natural product structures from NMR data

There continues to be a disturbing number of natural products reported in the literature whose structures are incorrect. At least in part, this reflects the fact that many natural product chemists have limited formal nuclear magnetic resonance training. Gaps in training and lack of awareness regarding the challenges and ambiguities associated with two-dimensional nuclear magnetic resonance data interpretation can easily lead to errors in structure elucidation. The purpose of this tutorial is to point out some of these issues, highlight the kinds of errors that have been made and provide specific advice on how to avoid these missteps such that the risk of reporting a wrong structure is minimized.

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.

Restriction of S-adenosylmethionine conformational freedom by knotted protein binding sites

S-adenosylmethionine (SAM) is one of the most important enzyme substrates. It is vital for the function of various proteins, including large group of methyltransferases (MTs). Intriguingly, some bacterial and eukaryotic MTs, while catalysing the same reaction, possess significantly different topologies, with the former being a knotted one. Here, we conducted a comprehensive analysis of SAM conformational space and factors that affect its vastness. We investigated SAM in two forms: free in water (via NMR studies and explicit solvent simulations) and bound to proteins (based on all data available in the PDB and on all-atom molecular dynamics simulations in water). We identified structural descriptors—angles which show the major differences in SAM conformation between unknotted and knotted methyltransferases. Moreover, we report that this is caused mainly by a characteristic for knotted MTs compact binding site formed by the knot and the presence of adenine-binding loop. Additionally, we elucidate conformational restrictions imposed on SAM molecules by other protein groups in comparison to conformational space in water.

The topology of a folded polypeptide chain has great impact on the resulting protein function and its interaction with ligands. Interestingly, topological constraints appear to affect binding of one of the most ubiquitous substrates in the cell, S-adenosylmethionine (SAM), to its target proteins. Here, we demonstrate how binding sites of specific proteins restrict SAM conformational freedom in comparison to its unbound state, with a special interest in proteins with non-trivial topology, including an exciting group of knotted methyltransferases. Using a vast array of computational methods combined with NMR experiments, we identify key structural features of knotted methyltransferases that impose unorthodox SAM conformations. We compare them with the characteristics of standard, unknotted SAM binding proteins. These results are significant for understanding differences between analogous, yet topologically different enzymes, as well as for future rational drug design.

Radical Stabilization Energies for Enzyme Engineering: Tackling the Substrate Scope of the Radical Enzyme QueE

Experimental assessment of catalytic reaction mechanisms and profiles of radical enzymes can be severely challenging due to the reactive nature of the intermediates and sensitivity of cofactors such as iron-sulfur clusters. Here, we present an enzyme-directed computational methodology for the assessment of thermodynamic reaction profiles and screening for radical stabilization energies (RSEs) for the assessment of catalytic turnovers in radical enzymes. We have applied this new screening method to the radical S-adenosylmethione enzyme 7-carboxy-7-deazaguanine synthase (QueE), following a detailed molecular dynamics (MD) analysis that clarifies the role of both specific enzyme residues and bound Mg²⁺, Ca²⁺, or Na⁺. The MD simulations provided the basis for a statistical approach to sample different conformational outcomes. RSE calculation at the M06-2X/6-31+G* level of theory provided the most computationally cost-effective assessment of enzyme-based energies, facilitated by an initial triage using semiempirical methods. The impact of intermolecular interactions on RSE was clearly established, and application to the assessment of potential alternative substrates (focusing on radical clock type rearrangements) proposes a selection of carbon-substituted analogues that would react to afford cyclopropylcarbinyl radical intermediates as candidates for catalytic turnover by QueE.

The role of computer-assisted structure elucidation (CASE) programs in the structure elucidation of complex natural products

Computer-assisted structure elucidation can help to determine the structures of complex natural products while minimizing the risk of structure errors.