Chemical diversity in angiosperms - monoterpene synthases control complex reactions that provide the precursors for ecologically and commercially important monoterpenoids.

Monoterpene synthases (MTSs) catalyze the first committed step in the biosynthesis of monoterpenoids, a class of specialized metabolites with particularly high chemical diversity in angiosperms. In addition to accomplishing a rate enhancement, these enzymes manage the formation and turnover of highly reactive carbocation intermediates formed from a prenyl diphosphate substrate. At each step along the reaction path, a cationic intermediate can be subject to cyclization, migration of a proton, hydride, or alkyl group, or quenching to terminate the sequence. However, enzymatic control of ligand folding, stabilization of specific intermediates, and defined quenching chemistry can maintain the specificity for forming a signature product. This review article will discuss our current understanding of how angiosperm MTSs control the reaction environment. Such knowledge allows inferences about the origin and regulation of chemical diversity, which is pertinent for appreciating the role of monoterpenoids in plant ecology but also for aiding commercial efforts that harness the accumulation of these specialized metabolites for the food, cosmetic, and pharmaceutical industries.

X-ray absorption spectroscopy and theoretical investigations of the effect of extended ligands in potassium organic matter interaction.

Potassium (K) is an essential nutrient for plant growth, and despite its abundance in soil, most of the K is structurally bound in minerals, limiting its bioavailability and making this soil K reservoir largely inaccessible to plants. Microbial biochemical weathering has been shown to be a promising pathway to sustainably increase plant available K. However, the mechanisms underpinning microbial K uptake, transformation, storage, and sharing are poorly resolved. To better understand the controls on microbial K transformations, we performed K K-edge x-ray absorption near-edge structure (XANES) spectroscopy on K-organic salts, including acetate, citrate, nitrate, oxalate, and tartrate, which are frequently observed as low molecular weight organic acids secreted by soil microbes, as well as humic acid, which acts as a proxy for higher molecular weight organic acids. The organic salts display feature-rich K XANES spectra, each demonstrating numerous unique features spanning ∼13 eV range across the absorption edge. In contrast, the spectra for humic acid have one broad, wide feature across the same energy range. We used a combination of time-dependent density functional theory and the Bethe-Salpeter equation based approach within the OCEAN code to simulate the experimental spectra for K-nitrate (KNO3) and K-citrate [K3(C6H5O7)·H2O] to identify the electronic transitions that give rise to some of the outlying and unique spectral features in the organic salts. KNO3 has both the lowest and highest lying energy features, and K3(C6H5O7)·H2O is produced by several soil microbes and is effective at mineral weathering. Our results analyze the K-organic salt bonding in detail to elucidate why the spectral shapes differ and indicate that the K K-edge XANES spectra are associated with the entire ligand despite similar first-shell bonding environments around the K center. The improved understanding of K bonding environments with organic ligands and their use for interpretation of the K-XANES spectra provides an important toolkit to understand how K is transformed by microbial processes and made bioavailable for plant uptake.

Atomistic simulations for investigation of substrate and salt effects on lipid in-source fragmentation in secondary ion mass spectrometry: A follow-up study.

In-source fragmentation (ISF) poses a significant challenge in secondary ion mass spectrometry (SIMS). These fragment ions increase the spectral complexity and can lead to incorrect annotation of fragments as intact species. The presence of salt that is ubiquitous in biological samples can influence the fragmentation and ionization of analytes in a significant manner, but their influences on SIMS have not been well characterized. To elucidate the effect of substrates and salt on ISF in SIMS, we have employed experimental SIMS in combination with atomistic simulations of a sphingolipid on a gold surface with various NaCl concentrations as a model system. Our results revealed that a combination of bond dissociation energy and binding energy between N-palmitoyl-sphingomyelin and a gold surface is a good predictor of fragment ion intensities in the absence of salt. However, ion-fragment interactions play a significant role in determining fragment yields in the presence of salt. Additionally, the charge distribution on fragment species may be a major contributor to the varying effects of salt on fragmentation. This study demonstrates that atomistic modeling can help predict ionization potential when salts are present, providing insights for more accurate interpretations of complex biological spectra.

Atomistic simulations for investigation of substrate effects on lipid in-source fragmentation in secondary ion mass spectrometry.

In beam-based ionization methods, the substrate plays an important role on the desorption mechanism of molecules from surfaces. Both the specific orientation that a molecule adopts at a surface and the strength of the molecule-surface interaction can greatly influence desorption processes, which in turn will affect the ion yield and the degree of in-source fragmentation of a molecule. In the beam-based method of secondary ion mass spectrometry (SIMS), in-source fragmentation can be significant and molecule specific due to the hard ionization method of using a primary ion beam for molecule desorption. To investigate the role of the substrate on orientation and in-source fragmentation, we have used atomistic simulations-molecular dynamics in combination with density functional theory calculations-to explore the desorption of a sphingolipid (palmitoylsphingomyelin) from a model surface (gold). We then compare SIMS data from this model system to our modeling findings. Using this approach, we found that the combined adsorption and binding energy of certain bonds associated with the headgroup fragments (C3H8N+, C5H12N+, C5H14NO+, and C5H15PNO4 +) was a good predictor for fragment intensities (as indicated by relative ion yields). This is the first example where atomistic simulations have been applied in beam-based ionization of lipids, and it presents a new approach to study biointerfacial lipid ordering effects on SIMS imaging.

PTM-Psi: A python package to facilitate the computational investigation of post-translational modification on protein structures and their impacts on dynamics and functions.

Post-translational modification (PTM) of a protein occurs after it has been synthesized from its genetic template, and involves chemical modifications of the protein's specific amino acid residues. Despite of the central role played by PTM in regulating molecular interactions, particularly those driven by reversible redox reactions, it remains challenging to interpret PTMs in terms of protein dynamics and function because there are numerous combinatorially enormous means for modifying amino acids in response to changes in the protein environment. In this study, we provide a workflow that allows users to interpret how perturbations caused by PTMs affect a protein's properties, dynamics, and interactions with its binding partners based on inferred or experimentally determined protein structure. This Python-based workflow, called PTM-Psi, integrates several established open-source software packages, thereby enabling the user to infer protein structure from sequence, develop force fields for non-standard amino acids using quantum mechanics, calculate free energy perturbations through molecular dynamics simulations, and score the bound complexes via docking algorithms. Using the S-nitrosylation of several cysteines on the GAP2 protein as an example, we demonstrated the utility of PTM-Psi for interpreting sequence-structure-function relationships derived from thiol redox proteomics data. We demonstrate that the S-nitrosylated cysteine that is exposed to the solvent indirectly affects the catalytic reaction of another buried cysteine over a distance in GAP2 protein through the movement of the two ligands. Our workflow tracks the PTMs on residues that are responsive to changes in the redox environment and lays the foundation for the automation of molecular and systems biology modeling.

Mechanistic investigation of SARS-CoV-2 main protease to accelerate design of covalent inhibitors.

Targeted covalent inhibition represents one possible strategy to block the function of SARS-CoV-2 Main Protease (MPRO), an enzyme that plays a critical role in the replication of the novel SARS-CoV-2. Toward the design of covalent inhibitors, we built a covalent inhibitor dataset using deep learning models followed by high throughput virtual screening of these candidates against MPRO. Two top-ranking inhibitors were selected for mechanistic investigations-one with an activated ester warhead that has a piperazine core and the other with an acrylamide warhead. Specifically, we performed a detailed analysis of the free energetics of covalent inhibition by hybrid quantum mechanics/molecular mechanics simulations. Cleavage of a fragment of the non-structured protein (NSP) from the SARS-CoV-2 genome was also simulated for reference. Simulations show that both candidates form more stable enzyme-inhibitor (E-I) complexes than the chosen NSP. It was found that both the NSP fragment and the activated ester inhibitor react with CYS145 of MPRO in a concerted manner, whereas the acrylamide inhibitor follows a stepwise mechanism. Most importantly, the reversible reaction and the subsequent hydrolysis reaction from E-I complexes are less probable when compared to the reactions with an NSP fragment, showing promise for these candidates to be the base for efficient MPRO inhibitors.