The influence of model building schemes and molecular dynamics sampling on QM-cluster models: the chorismate mutase case study.

Most QM-cluster models of enzymes are constructed based on X-ray crystal structures, which limits comparison to in vivo structure and mechanism. The active site of chorismate mutase from Bacillus subtilis and the enzymatic transformation of chorismate to prephenate is used as a case study to guide construction of QM-cluster models built first from the X-ray crystal structure, then from molecular dynamics (MD) simulation snapshots. The Residue Interaction Network ResidUe Selector (RINRUS) software toolkit, developed by our group to simplify and automate the construction of QM-cluster models, is expanded to handle MD to QM-cluster model workflows. Several options, some employing novel topological clustering from residue interaction network (RIN) information, are evaluated for generating conformational clustering from MD simulation. RINRUS then generates a statistical thermodynamic framework for QM-cluster modeling of the chorismate mutase mechanism via refining 250 MD frames with density functional theory (DFT). The 250 QM-cluster models sampled provide a mean ΔG‡ of 10.3 ± 2.6 kcal mol-1 compared to the experimental value of 15.4 kcal mol-1 at 25 °C. While the difference between theory and experiment is consequential, the level of theory used is modest and therefore "chemical" accuracy is unexpected. More important are the comparisons made between QM-cluster models designed from the X-ray crystal structure versus those from MD frames. The large variations in kinetic and thermodynamic properties arise from geometric changes in the ensemble of QM-cluster models, rather from the composition of the QM-cluster models or from the active site-solvent interface. The findings open the way for further quantitative and reproducible calibration in the field of computational enzymology using the model construction framework afforded with the RINRUS software toolkit.

Correction: The solution structures and relative stability constants of lanthanide-EDTA complexes predicted from computation.

Correction for 'The solution structures and relative stability constants of lanthanide-EDTA complexes predicted from computation' by Ravi D. O'Brien et al., Phys. Chem. Chem. Phys., 2022, 24, 10263-10271, https://doi.org/10.1039/D2CP01081J.

Mutation Space of Spatially Conserved Amino Acid Sites in Proteins.

The mutation space of spatially conserved (MSSC) amino acid residues is a protein structural quantity developed and described in this work. The MSSC quantifies how many mutations and which different mutations, i.e., the mutation space, occur in each amino acid site in a protein. The MSSC calculates the mutation space of amino acids in a target protein from the spatially conserved residues in a group of multiple protein structures. Spatially conserved amino acid residues are identified based on their relative positions in the protein structure. The MSSC examines each residue in a target protein, compares it to the residues present in the same relative position in other protein structures, and uses physicochemical criteria of mutations found in each conserved spatial site to quantify the mutation space of each amino acid in the target protein. The MSSC is analogous to scoring each site in a multiple sequence alignment but in three-dimensional space considering the spatial location of residues instead of solely the order in which they appear in a protein sequence. MSSC analysis was performed on example cases, and it reproduces the well-known observation that, regardless of secondary structure, solvent-exposed residues are more likely to be mutated than internal ones. The MSSC code is available on GitHub: "https://github.com/Cantu-Research-Group/Mutation_Space".

Analysis of the First Ion Coordination Sphere: A Toolkit to Analyze the Coordination Sphere of Ions.

Rapid and accurate approaches to characterizing the coordination structure of an ion are important for designing ligands and quantifying structure-property trends. Here, we introduce AFICS (Analysis of the First Ion Coordination Sphere), a tool written in Python 3 for analyzing the structural and geometric features of the first coordination sphere of an ion over the course of molecular dynamics simulations. The principal feature of AFICS is its ability to quantify the distortion a coordination geometry undergoes compared to uniform polyhedra. This work applies the toolkit to analyze molecular dynamics simulations of the well-defined coordination structure of aqueous Cr3+ along with the more ambiguous structure of aqueous Eu3+ chelated to ethylenediaminetetraacetic acid. The tool is targeted for analyzing ions with fluxional or irregular coordination structures (e.g., solution structures of f-block elements) but is generalized such that it may be applied to other systems.

Solution Structures of Europium Terpyridyl Complexes with Nitrate and Triflate Counterions in Acetonitrile.

Lanthanide-ligand complexes are key components of technological applications, and their properties depend on their structures in the solution phase, which are challenging to resolve experimentally or computationally. The coordination structure of the Eu3+ ion in different coordination environments in acetonitrile is examined using ab initio molecular dynamics (AIMD) simulations and extended X-ray absorption fine structure (EXAFS) spectroscopy. AIMD simulations are conducted for the solvated Eu3+ ion in acetonitrile, both with or without a terpyridyl ligand, and in the presence of either triflate or nitrate counterions. EXAFS spectra are calculated directly from AIMD simulations and then compared to experimentally measured EXAFS spectra. In acetonitrile solution, both nitrate and triflate anions are shown to coordinate directly to the Eu3+ ion forming either ten- or eight-coordinate solvent complexes where the counterions are binding as bidentate or monodentate structures, respectively. Coordination of a terpyridyl ligand to the Eu3+ ion limits the available binding sites for the solvent and anions. In certain cases, the terpyridyl ligand excludes any solvent binding and limits the number of coordinated anions. The solution structure of the Eu-terpyridyl complex with nitrate counterions is shown to have a similar arrangement of Eu3+ coordinating molecules as the crystal structure. This study illustrates how a combination of AIMD and EXAFS can be used to determine how ligands, solvent, and counterions coordinate with the lanthanide ions in solution.

Evaluating the active site-substrate interplay between x-ray crystal structure and molecular dynamics in chorismate mutase.

Designing realistic quantum mechanical (QM) models of enzymes is dependent on reliably discerning and modeling residues, solvents, and cofactors important in crafting the active site microenvironment. Interatomic van der Waals contacts have previously demonstrated usefulness toward designing QM-models, but their measured values (and subsequent residue importance rankings) are expected to be influenceable by subtle changes in protein structure. Using chorismate mutase as a case study, this work examines the differences in ligand-residue interatomic contacts between an x-ray crystal structure and structures from a molecular dynamics simulation. Select structures are further analyzed using symmetry adapted perturbation theory to compute ab initio ligand-residue interaction energies. The findings of this study show that ligand-residue interatomic contacts measured for an x-ray crystal structure are not predictive of active site contacts from a sampling of molecular dynamics frames. In addition, the variability in interatomic contacts among structures is not correlated with variability in interaction energies. However, the results spotlight using interaction energies to characterize and rank residue importance in future computational enzymology workflows.

Quality-of-life outcomes and risk prediction for patients randomized to nivolumab plus ipilimumab vs nivolumab on LungMAP-S1400I.

BACKGROUND: An important issue for patients with cancer treated with novel therapeutics is how they weigh the effects of treatment on survival and quality of life (QOL). We compared QOL in patients enrolled to SWOG S1400I, a substudy of the LungMAP biomarker-driven master protocol. METHODS: SWOG S1400I was a randomized phase III trial comparing nivolumab plus ipilimumab vs nivolumab for treatment of immunotherapy-naïve disease in advanced squamous cell lung cancer. The primary endpoint was the MD Anderson Symptom Inventory-Lung Cancer severity score at week 7 and week 13 with a target difference of 1.0 points, assessed using multivariable linear regression. A composite risk model for progression-free and overall survival was derived using best-subset selection. RESULTS: Among 158 evaluable patients, median age was 67.6 years and most were male (66.5%). The adjusted MD Anderson Symptom Inventory-Lung Cancer severity score was 0.04 points (95% confidence interval [CI] = -0.44 to 0.51 points; P = .89) at week 7 and 0.12 points (95% CI = -0.41 to 0.65; P = .66) at week 13. A composite risk model showed that patients with high levels of appetite loss and shortness of breath had a threefold increased risk of progression or death (hazard ratio [HR] = 3.06, 95% CI = 1.88 to 4.98; P < .001) and that those with high levels of both appetite loss and work limitations had a fivefold increased risk of death (HR = 5.60, 95% CI = 3.27 to 9.57; P < .001)-compared with those with neither risk category. CONCLUSIONS: We found no evidence of a benefit of ipilimumab added to nivolumab compared with nivolumab alone for QOL in S1400I. A risk model identified patients at high risk of poor survival, demonstrating the prognostic relevance of baseline patient-reported outcomes even in those with previously treated advanced cancer.

The solution structures and relative stability constants of lanthanide-EDTA complexes predicted from computation.

Ligand selectivity to specific lanthanide (Ln) ions is key to the separation of rare earth elements from each other. Ligand selectivity can be quantified with relative stability constants (measured experimentally) or relative binding energies (calculated computationally). The relative stability constants of EDTA (ethylenediaminetetraacetic acid) with La3+, Eu3+, Gd3+, and Lu3+ were predicted from relative binding energies, which were quantified using electronic structure calculations with relativistic effects and based on the molecular structures of Ln-EDTA complexes in solution from density functional theory molecular dynamics simulations. The protonation state of an EDTA amine group was varied to study pH ∼7 and ∼11 conditions. Further, simulations at 25 °C and 90 °C were performed to elucidate how structures of Ln-EDTA complexes varying with temperature are related to complex stabilities at different pH conditions. Relative stability trends are predicted from computation for varying Ln3+ ions (La, Eu, Gd, Lu) with a single ligand (EDTA at pH ∼11), as well as for a single Ln3+ ion (La) with varying ligands (EDTA at pH ∼7 and ∼11). Changing the protonation state of an EDTA amine site significantly changes the solution structure of the Ln-EDTA complex resulting in a reduction of the complex stability. Increased Ln-ligand complex stability is correlated to reduced structural variations in solution upon an increase in temperature.

Cheminformatic quantum mechanical enzyme model design: A catechol-O-methyltransferase case study.

To accurately simulate the inner workings of an enzyme active site with quantum mechanics (QM), not only must the reactive species be included in the model but also important surrounding residues, solvent, or coenzymes involved in crafting the microenvironment. Our lab has been developing the Residue Interaction Network Residue Selector (RINRUS) toolkit to utilize interatomic contact network information for automated, rational residue selection and QM-cluster model generation. Starting from an x-ray crystal structure of catechol-O-methyltransferase, RINRUS was used to construct a series of QM-cluster models. The reactant, product, and transition state of the methyl transfer reaction were computed for a total of 550 models, and the resulting free energies of activation and reaction were used to evaluate model convergence. RINRUS-designed models with only 200-300 atoms are shown to converge. RINRUS will serve as a cornerstone for improved and automated cheminformatics-based enzyme model design.

Quantifying Inter-Residue Contacts through Interaction Energies.

The validity and accuracy of protein modeling is dependent on constructing models that account for the inter-residue interactions crucial for protein structure and function. Residue interaction networks derived from interatomic van der Waals contacts have previously demonstrated usefulness toward designing protein models, but there has not yet been evidence of a connection between network-predicted interaction strength and quantitative interaction energies. This work evaluates the intraprotein contact networks of five proteins against ab initio interaction energies computed using symmetry-adapted perturbation theory. To more appropriately capture the local chemistry of the protein, we deviate from traditional protein network analysis to redefine the interacting nodes in terms of main chain and side chain functional groups rather than complete amino acids. While there is no simple correspondence between the features of the contact network and actual interaction strength, random forest models constructed from minimal structural, network, and chemical descriptors are capable of accurately predicting interaction energy. The results of this work serve as a foundation for the development and improvement of functional group-based contact networks.

A transition state "trapped"? QM-cluster models of engineered threonyl-tRNA synthetase.

In a recent study [Science, 2015, 347, 6224], protein engineering was used to design a core within the enzyme threonyl-tRNA synthetase (ThrRS) capable of stabilizing the coplanar transition state conformation of an inserted noncanonical p-biphenylalanine (BiPhe) residue. Using the X-ray crystal structures of the preliminary (Protein Data Bank entries 4S02, 4S0J, 4S0L, 4S0I, and 4S0K) and final (PDB entry 4S03) ThrRS proteins, fully quantum mechanical (QM) cluster models were constructed and analyzed. Density functional theory and molecular dynamics computations were performed to investigate the energetic profiles of BiPhe dihedral rotation within the ThrRS models. For the 4S03 model, results indicate that steric and hydrophobic forces of the residues surrounding BiPhe eliminate the coplanar transition state entirely. Molecular dynamics simulations were carried out that confirmed the extent of BiPhe rotational flexibility, and provided additional information on barrier heights of full BiPhe rotation. Transition states of near-coplanar biphenyl rings of BiPhe were found for the 4S0I and 4S0K models, but are not likely persistent on any observable timescale. The dihedral angle of the biphenyl moiety is thermally allowed to fluctuate within the ThrRS protein core models by a range of 17°-26°. BiPhe-residue interaction counts (RICs) were used to compare the interaction differences among the different ThrRS cores. The RICs demonstrate how BiPhe is compacted within the 4S03 core, resulting in the experimentally observed "trapped" coplanar transition state analogue. This work presents a unique application of QM-cluster models towards studying the inner workings of proteins, and suggests avenues that computational chemistry can be used to further guide bioengineering.