Protein Modeling with DEER Spectroscopy

Double electron-electron resonance (DEER) combined with site-directed spin labeling can provide distance distributions between selected protein residues to investigate protein structure and conformational heterogeneity. The utilization of the full quantitative information contained in DEER data requires effective protein and spin label modeling methods. Here, we review the application of DEER data to protein modeling. First, we discuss the significance of spin label modeling for accurate extraction of protein structural information and review the most popular label modeling methods. Next, we review several important aspects of protein modeling with DEER, including site selection, how DEER restraints are applied, common artifacts, and the unique potential of DEER data for modeling structural ensembles and conformational landscapes. Finally, we discuss common applications of protein modeling with DEER data and provide an outlook.

Nature-inspired innovation: Alginic-kojic acid material for sustainable antibacterial and carbon dioxide fixation

The current environmental consciousness of the world's population encourages researchers to work on new materials that are environmentally benign and able to display the appropriate features for the needed application. To develop high-performing, inexpensive eco-materials, scientists have frequently turned to nature, attempting to mimic its processes' excellent performance at a reasonable price. In this regard, we decided to focus on alginic acid (AA), a polysaccharide widely found in brown algae, and kojic acid (KA), a chelating agent fungi produces. This study proposes rapidly synthesizing a sustainable, biocompatible material (AK) based on AA and KA, employing chlorokojic acid (CKA). The material has a dual function: antibacterial activity on both Gram-positive and Gram-negative bacteria, without any cytotoxic action on human cells in vitro, and catalytic ability to convert CO2 into cyclic carbonates at atmospheric pressure, without solvents, with high yields, and without the use of metals. Furthermore, the material's insolubility in organic solvents allows it to be easily separated from the reaction product and reused for other catalytic cycles. Both applications have a key role in the medical and environmental fields, combating the outbreak of infections and providing an innovative methodology to fix the CO2 on specific substrates.

CREST-A program for the exploration of low-energy molecular chemical space

Conformer-rotamer sampling tool (CREST) is an open-source program for the efficient and automated exploration of molecular chemical space. Originally developed in Pracht et al. [Phys. Chem. Chem. Phys. 22, 7169 (2020)] as an automated driver for calculations at the extended tight-binding level (xTB), it offers a variety of molecular- and metadynamics simulations, geometry optimization, and molecular structure analysis capabilities. Implemented algorithms include automated procedures for conformational sampling, explicit solvation studies, the calculation of absolute molecular entropy, and the identification of molecular protonation and deprotonation sites. Calculations are set up to run concurrently, providing efficient single-node parallelization. CREST is designed to require minimal user input and comes with an implementation of the GFNn-xTB Hamiltonians and the GFN-FF force-field. Furthermore, interfaces to any quantum chemistry and force-field software can easily be created. In this article, we present recent developments in the CREST code and show a selection of applications for the most important features of the program. An important novelty is the refactored calculation backend, which provides significant speed-up for sampling of small or medium-sized drug molecules and allows for more sophisticated setups, for example, quantum mechanics/molecular mechanics and minimum energy crossing point calculations.

Integrating Electron Paramagnetic Resonance Spectroscopy and Computational Modeling to Measure Protein Structure and Dynamics

Electron paramagnetic resonance (EPR) has become a powerful probe of conformational heterogeneity and dynamics of biomolecules. In this Review, we discuss different computational modeling techniques that enrich the interpretation of EPR measurements of dynamics or distance restraints. A variety of spin labels are surveyed to provide a background for the discussion of modeling tools. Molecular dynamics (MD) simulations of models containing spin labels provide dynamical properties of biomolecules and their labels. These simulations can be used to predict EPR spectra, sample stable conformations and sample rotameric preferences of label sidechains. For molecular motions longer than milliseconds, enhanced sampling strategies and de novo prediction software incorporating or validated by EPR measurements are able to efficiently refine or predict protein conformations, respectively. To sample large-amplitude conformational transition, a coarse-grained or an atomistic weighted ensemble (WE) strategy can be guided with EPR insights. Looking forward, we anticipate an integrative strategy for efficient sampling of alternate conformations by de novo predictions, followed by validations by systematic EPR measurements and MD simulations. Continuous pathways between alternate states can be further sampled by WE-MD including all intermediate states.

Differentiating between Label and Protein Conformers in Pulsed Dipolar EPR Spectroscopy with the dHis-Cu2+ (NTA) Motif

Pulsed dipolar EPR spectroscopy (PDS) in combination with site-directed spin labeling is a powerful tool in structural biology. However, the commonly used spin labels are conjugated to biomolecules via rather long and flexible linkers, which hampers the translation of distance distributions into biomolecular conformations. In contrast, the spin label copper(II)-nitrilotriacetic acid [Cu2+ (NTA)] bound to two histidines (dHis) is rigid and yields narrow distance distributions, which can be more easily translated into biomolecular conformations. Here, we use this label on the 71 kDa Yersinia outer protein O (YopO) to decipher whether a previously experimentally observed bimodal distance distribution is due to two conformations of the biomolecule or of the flexible spin labels. Two different PDS experiments, that is, pulsed electron-electron double resonance (PELDOR aka DEER) and relaxation-induced dipolar modulation enhancement (RIDME), yield unimodal distance distribution with the dHis-Cu2+ (NTA) motif; this result suggests that the α-helical backbone of YopO adopts a single conformation in frozen solution. In addition, we show that the Cu2+ (NTA) label preferentially binds to the target double histidine (dHis) sites even in the presence of 22 competing native histidine residues. Our results therefore suggest that the generation of a His-null background is not required for this spin labeling methodology. Together these results highlight the value of the dHis-Cu2+ (NTA) motif in PDS experiments.

Revealing the DNA Binding Modes of CsoR by EPR Spectroscopy

In pathogens, a unique class of metalloregulator proteins, called gene regulatory proteins, sense specific metal ions that initiate gene transcription of proteins that export metal ions from the cell, thereby preventing toxicity and cell death. CsoR is a metalloregulator protein found in various bacterial systems that "sense" Cu(I) ions with high affinity. Upon copper binding, CsoR dissociates from the DNA promoter region, resulting in initiation of gene transcription. Crystal structures of CsoR in the presence and absence of Cu(I) from various bacterial systems have been reported, suggesting either a dimeric or tetrameric structure of these helical proteins. However, structural information about the CsoR-DNA complex is missing. Here, we applied electron paramagnetic resonance (EPR) spectroscopy to follow the conformational and dynamical changes that Mycobacterium tuberculosis CsoR undergoes upon DNA binding in solution. We showed that the quaternary structure is predominantly dimeric in solution, and only minor conformational and dynamical changes occur in the DNA bound state. Also, labeling of the unresolved C- terminus revealed no significant change in dynamics upon DNA binding. These observations are unique, since for other bacterial copper metalloregulators, such as the MerR and CopY families, major conformational changes were observed upon DNA binding, indicating a different mode of action for this protein family.

Bridging the Monomer to Polymer Gap in Radical Polymer Design

Radical polymers bearing open-shell moieties at pendant sites exhibit unique redox and optoelectronic properties that are promising for many organic electronic applications. Nevertheless, gaps remain in relating the electronic properties of repeat units, which can be easily calculated, to the condensed-phase charge transport behaviors of these materials. To address this gap, we have performed the first quantum chemical study on a broad swathe of radical polymer design space that explicitly includes the coupling between polymer constraints and radical-mediated intramolecular charge transfer. For this purpose, a chemical space of 64 radical polymer chemistries was constructed based on varying backbone units, open-shell chemistries, and spacer units between the backbone and the radical groups. For each combination of backbone, radical, and spacer, comprehensive conformational sampling was used to calculate expected values of intrachain charge transport using several complementary metrics, including the end-to-end thermal Green's function, Delta-Wye transformed inverse resistance, and the Kirchhoff transport index. We observe that charge transport in radical polymers is primarily driven by the choice radical chemistry, which influences the optimal choice of backbone chemistry and spacer group that mediate radical alignment and avoid the formation of undesired trap states. Given the limited exploration of radical chemistries beyond the TEMPO radical for this class of materials, these findings suggest tremendous opportunities exist for synthetic exploration in radical polymers.

A novel approach to modeling side chain ensembles of the bifunctional spin label RX

We introduce a novel approach to modeling side chain ensembles of bifunctional spin labels. This approach utilizes rotamer libraries to generate side chain conformational ensembles. Because the bifunctional label is constrained by two attachment sites, the label is split into two monofunctional rotamers which are first attached to their respective sites, then rejoined by a local optimization in dihedral space. We validate this method against a set of previously published experimental data using the bifunctional spin label, RX. This method is relatively fast and can readily be used for both experimental analysis and protein modeling, providing significant advantages over modeling bifunctional labels with molecular dynamics simulations. Use of bifunctional labels for site directed spin labeling (SDSL) electron paramagnetic resonance (EPR) spectroscopy dramatically reduces label mobility, which can significantly improve resolution of small changes in protein backbone structure and dynamics. Coupling the use of bifunctional labels with side chain modeling methods allows for improved quantitative application of experimental SDSL EPR data to protein modeling.

chiLife: An open-source Python package for in silico spin labeling and integrative protein modeling

Here we introduce chiLife, a Python package for site-directed spin label (SDSL) modeling for electron paramagnetic resonance (EPR) spectroscopy, in particular double electron-electron resonance (DEER). It is based on in silico attachment of rotamer ensemble representations of spin labels to protein structures. chiLife enables the development of custom protein analysis and modeling pipelines using SDSL EPR experimental data. It allows the user to add custom spin labels, scoring functions and spin label modeling methods. chiLife is designed with integration into third-party software in mind, to take advantage of the diverse and rapidly expanding set of molecular modeling tools available with a Python interface. This article describes the main design principles of chiLife and presents a series of examples.

Reconciling membrane protein simulations with experimental DEER spectroscopy data

Spectroscopy experiments are crucial to study membrane proteins for which traditional structure determination methods still prove challenging. Double electron-electron resonance (DEER) spectroscopy experiments provide protein residue-pair distance distributions that are indicative of their conformational heterogeneity. Atomistic molecular dynamics (MD) simulations are another tool that have been proven to be vital to study the structural dynamics of membrane proteins such as to identify inward-open, occluded, and outward-open conformations of transporter membrane proteins, among other partially open or closed states of the protein. Yet, studies have reported that there is no direct consensus between the distributional data from DEER experiments and MD simulations, which has challenged validation of structures obtained from long-timescale simulations and using simulations to design experiments. Current coping strategies for comparisons rely on heuristics, such as mapping the nearest matching peaks between two ensembles or biased simulations. Here we examine the differences in residue-pair distance distributions arising due to the choice of membranes around the protein and covalent modification of a pair of residues to nitroxide spin labels in DEER experiments. Through comparing MD simulations of two proteins, PepT_So and LeuT-both of which have been characterized using DEER experiments previously-we show that the proteins' dynamics are similar despite the choice of the detergent micelle as a membrane mimetic in DEER experiments. On the other hand, covalently modified residues show slight local differences in their dynamics and a huge divergence when the oxygen atom pair distances between spin labeled residues are measured rather than protein backbone distances. Given the computational expense associated with pairwise MTSSL labeled MD simulations, we examine the use of biased simulations to explore the conformational dynamics of the spin labels only to reveal that such simulations alter the underlying protein dynamics. Our study identifies the main cause for the mismatch between DEER experiments and MD simulations and will accelerate the development of potential mitigation strategies to improve the match.

Comparative evaluation of spin-label modeling methods for protein structural studies

Site-directed spin-labeling electron paramagnetic resonance spectroscopy is a powerful technique for the investigation of protein structure and dynamics. Accurate spin-label modeling methods are essential to make full quantitative use of site-directed spin-labeling electron paramagnetic resonance data for protein modeling and model validation. Using a set of double electron-electron resonance data from seven different site pairs on maltodextrin/maltose-binding protein under two different conditions using five different spin labels, we compare the ability of two widely used spin-label modeling methods, based on accessible volume sampling and rotamer libraries, to predict experimental distance distributions. We present a spin-label modeling approach inspired by canonical side-chain modeling methods and compare modeling accuracy with the established methods.

A Computational Protocol for Vibrational Circular Dichroism Spectra of Cyclic Oligopeptides

Cyclic peptides are a promising class of compounds for next-generation antibiotics as they may provide new ways of limiting antibiotic resistance development. Although their cyclic structure will introduce some rigidity, their conformational space is large and they usually have multiple chiral centers that give rise to a wide range of possible stereoisomers. Chiroptical spectroscopies such as vibrational circular dichroism (VCD) are used to assign stereochemistry and discriminate enantiomers of chiral molecules, often in combination with electronic structure methods. The reliable determination of the absolute configuration of cyclic peptides will require robust computational methods than can identify all significant conformers and their relative population and reliably assign their stereochemistry from their chiroptical spectra by comparison with ab initio calculated spectra. We here present a computational protocol for the accurate calculation of the VCD spectra of a series of flexible cyclic oligopeptides. The protocol builds on the Conformer-Rotamer Ensemble Sampling Tool (CREST) developed by Grimme and co-workers ( Phys. Chem. Chem. Phys. 2020, 22, 7169-7192 and J. Chem. Theory. Comput. 2019, 15, 2847-2862) in combination with postoptimizations using B3LYP and moderately sized basis sets. Our recommended computational protocol for the computation of VCD spectra of cyclic oligopeptides consists of three steps: (1) conformational sampling with CREST and tight-binding density functional theory (xTB); (2) energy ranking based on single-point energy calculations as well as geometry optimization and VCD calculations of conformers that are within 2.5 kcal/mol of the most stable conformer using B3LYP/6-31+G*/CPCM; and (3) VCD spectra generation based on Boltzmann weighting with Gibbs free energies. Our protocol provides a feasible basis for generating VCD spectra also for larger cyclic peptides of biological/pharmaceutical interest and can thus be used to investigate promising compounds for next-generation antibiotics.

Cross-validation of distance measurements in proteins by PELDOR/DEER and single-molecule FRET

Pulsed electron-electron double resonance spectroscopy (PELDOR/DEER) and single-molecule Förster resonance energy transfer spectroscopy (smFRET) are frequently used to determine conformational changes, structural heterogeneity, and inter probe distances in biological macromolecules. They provide qualitative information that facilitates mechanistic understanding of biochemical processes and quantitative data for structural modelling. To provide a comprehensive comparison of the accuracy of PELDOR/DEER and smFRET, we use a library of double cysteine variants of four proteins that undergo large-scale conformational changes upon ligand binding. With either method, we use established standard experimental protocols and data analysis routines to determine inter-probe distances in the presence and absence of ligands. The results are compared to distance predictions from structural models. Despite an overall satisfying and similar distance accuracy, some inconsistencies are identified, which we attribute to the use of cryoprotectants for PELDOR/DEER and label-protein interactions for smFRET. This large-scale cross-validation of PELDOR/DEER and smFRET highlights the strengths, weaknesses, and synergies of these two important and complementary tools in integrative structural biology.

Automated Molecular Cluster Growing for Explicit Solvation by Efficient Force Field and Tight Binding Methods

An automated and broadly applicable workflow for the description of solvation effects in an explicit manner is introduced. This method, termed quantum cluster growth (QCG), is based on the semiempirical GFN2-xTB/GFN-FF methods, enabling efficient geometry optimizations and MD simulations. Fast structure generation is provided using the intermolecular force field xTB-IFF. Additionally, the approach uses an efficient implicit solvation model for the electrostatic embedding of the growing clusters. The novel QCG procedure presents a robust cluster generation tool for subsequent application of higher-level (e.g., DFT) methods to study solvation effects on molecular geometries explicitly or to average spectroscopic properties over cluster ensembles. Furthermore, the computation of the solvation free energy with a supermolecular approach can be carried out with QCG. The underlying growing process is physically motivated by computing the leading-order solute-solvent interactions first and can account for conformational and chemical changes due to solvation for low-energy barrier processes. The conformational space is explored with the NCI-MTD algorithm as implemented in the CREST program, using a combination of metadynamics and MD simulations. QCG with GFN2-xTB yields realistic solution geometries and reasonable solvation free energies for various systems without introducing many empirical parameters. Computed IR spectra of some solutes with QCG show a better match to the experimental data compared to well-established implicit solvation models.

Dynamical interplay between the human high-affinity copper transporter hCtr1 and its cognate metal ion

Abnormal cellular copper levels have been clearly implicated in genetic diseases, cancer, and neurodegeneration. Ctr1, a high-affinity copper transporter, is a homotrimeric integral membrane protein that provides the main route for cellular copper uptake. Together with a sophisticated copper transport system, Ctr1 regulates Cu(I) metabolism in eukaryotes. Despite its pivotal role in normal cell function, the molecular mechanism of copper uptake and transport via Ctr1 remains elusive. In this study, electron paramagnetic resonance (EPR), UV-visible spectroscopy, and all-atom simulations were employed to explore Cu(I) binding to full-length human Ctr1 (hCtr1), thereby elucidating how metal binding at multiple distinct sites affects the hCtr1 conformational dynamics. We demonstrate that each hCtr1 monomer binds up to five Cu(I) ions and that progressive Cu(I) binding triggers a marked structural rearrangement in the hCtr1 C-terminal region. The observed Cu(I)-induced conformational remodeling suggests that the C-terminal region may play a dual role, serving both as a channel gate and as a shuttle mediating the delivery of copper ions from the extracellular hCtr1 selectivity filter to intracellular metallochaperones. Our findings thus contribute to a more complete understanding of the mechanism of hCtr1-mediated Cu(I) uptake and provide a conceptual basis for developing mechanism-based therapeutics for treating pathological conditions linked to de-regulated copper metabolism.

PELDOR Measurements on Nitroxide-Labeled Oligonucleotides

In the past decades, pulsed dipolar electron paramagnetic resonance spectroscopy (PDS) has emerged as a powerful tool in biophysical chemistry to study the structure, dynamics, and function of biomolecules like oligonucleotides and proteins. Structural information is obtained from PDS methods in form of a distribution of distances between spin centers. Such spin centers can either be intrinsically present paramagnetic metal ions and organic radicals or may be attached to the biomolecule by means of site-directed spin labeling. The most common PDS experiment for probing interspin distances in the nanometer range is pulsed electron-electron double resonance (PELDOR or DEER). In the protocol presented here, we provide a step-by-step workflow on how to set up a PELDOR experiment on a commercially available pulsed EPR spectrometer, outline the data analysis, and highlight potential pitfalls. We suggest PELDOR measurements on nitroxide-labeled oligonucleotides to study the structure of either RNA-cleaving DNAzymes in complex with their RNA targets or modified DNAzymes with different functions and targets, in which deoxynucleotides are substituted by nitroxide-labeled nucleotides.

A Comparison of Cysteine-Conjugated Nitroxide Spin Labels for Pulse Dipolar EPR Spectroscopy

The structure-function and materials paradigms drive research on the understanding of structures and structural heterogeneity of molecules and solids from materials science to structural biology. Functional insights into complex architectures are often gained from a suite of complementary physicochemical methods. In the context of biomacromolecular structures, the use of pulse dipolar electron paramagnetic resonance spectroscopy (PDS) has become increasingly popular. The main interest in PDS is providing long-range nanometre distance distributions that allow for identifying macromolecular topologies, validating structural models and conformational transitions as well as docking of quaternary complexes. Most commonly, cysteines are introduced into protein structures by site-directed mutagenesis and modified site-specifically to a spin-labelled side-chain such as a stable nitroxide radical. In this contribution, we investigate labelling by four different commercial labelling agents that react through different sulfur-specific reactions. Further, the distance distributions obtained are between spin-bearing moieties and need to be related to the protein structure via modelling approaches. Here, we compare two different approaches to modelling these distributions for all four side-chains. The results indicate that there are significant differences in the optimum labelling procedure. All four spin-labels show differences in the ease of labelling and purification. Further challenges arise from the different tether lengths and rotamers of spin-labelled side-chains; both influence the modelling and translation into structures. Our comparison indicates that the spin-label with the shortest tether in the spin-labelled side-group, (bis-(2,2,5,5-Tetramethyl-3-imidazoline-1-oxyl-4-yl) disulfide, may be underappreciated and could increase the resolution of structural studies by PDS if labelling conditions are optimised accordingly.

Nanoscale π-conjugated ladders

It is challenging to increase the rigidity of a macromolecule while maintaining solubility. Established strategies rely on templating by dendrons, or by encapsulation in macrocycles, and exploit supramolecular arrangements with limited robustness. Covalently bonded structures have entailed intramolecular coupling of units to resemble the structure of an alternating tread ladder with rungs composed of a covalent bond. We introduce a versatile concept of rigidification in which two rigid-rod polymer chains are repeatedly covalently associated along their contour by stiff molecular connectors. This approach yields almost perfect ladder structures with two well-defined π-conjugated rails and discretely spaced nanoscale rungs, easily visualized by scanning tunnelling microscopy. The enhancement of molecular rigidity is confirmed by the fluorescence depolarization dynamics and complemented by molecular-dynamics simulations. The covalent templating of the rods leads to self-rigidification that gives rise to intramolecular electronic coupling, enhancing excitonic coherence. The molecules are characterized by unprecedented excitonic mobility, giving rise to excitonic interactions on length scales exceeding 100 nm. Such interactions lead to deterministic single-photon emission from these giant rigid macromolecules, with potential implications for energy conversion in optoelectronic devices.

Surface tension of liquids and binary mixtures from molecular dynamics simulations

In this work we assess and extend strategies for calculating surface tension of complex liquids from molecular dynamics simulations: the mechanical route and the instantaneous liquid interface (ILI) approach. The former employs the connection between stress tensor and surface tension, whereas the latter involves computation of instantaneous density field. Whereas the mechanical route is general, the ILI method involves system-dependent parameters restricting its original application to liquid water only. Here we generalize the approach to complex molecular liquids using atomic van der Waals radii. The performance of the approaches is evaluated on two liquid systems: acetonitrile and water-methanol mixture. In addition, we compare the effect of the computational models for interaction potentials based on semi-empirical electronic structure theory and classical force fields on the estimate of the surface tension within both stress tensor and ILI approaches.

Automated Quantum Chemistry-Based Calculation of Optical Rotation for Large Flexible Molecules

The calculation of optical rotation (OR, [α]_D) for nonrigid molecules was limited to small systems due to the challenging problem of generating reliable conformer ensembles, calculating accurate Boltzmann populations and the extreme sensitivity of the OR to the molecules' three-dimensional structure. Herein, we describe and release the crenso workflow for the automated computation of conformer ensembles in solution and corresponding [α]_D values for flexible molecules. A comprehensive set of 28 organic drug molecules (28-144 atoms) with experimentally determined values is used in our assessment. In all cases, the correct OR sign is obtained with an overall mean relative deviation of 72% (mean absolute deviation of 82 °[dm(g/cm³)]^-1 for experimental values in the range -160 to 287 °[dm(g/cm³)]^-1). We show that routine [α]_D computations for very flexible, biologically active molecules are both feasible and reproducible in about a day of computation time on a standard workstation computer. Furthermore, we observed that the effect of energetically higher-lying structures in the ensemble on the OR is often averaged out and that in 23 out of 28 cases, the correct OR sign is obtained by just considering only the lowest free energy conformer. In four example cases, we show that the approach can also describe the OR of pairs of flexible diastereomers properly. In summary, even very sensitive, multifactorial physicochemical properties appear reliably predictable with minimal user input from efficiently automated quantum chemical methods.

Benchmark Test and Guidelines for DEER/PELDOR Experiments on Nitroxide-Labeled Biomolecules

Distance distribution information obtained by pulsed dipolar EPR spectroscopy provides an important contribution to many studies in structural biology. Increasingly, such information is used in integrative structural modeling, where it delivers unique restraints on the width of conformational ensembles. In order to ensure reliability of the structural models and of biological conclusions, we herein define quality standards for sample preparation and characterization, for measurements of distributed dipole-dipole couplings between paramagnetic labels, for conversion of the primary time-domain data into distance distributions, for interpreting these distributions, and for reporting results. These guidelines are substantiated by a multi-laboratory benchmark study and by analysis of data sets with known distance distribution ground truth. The study and the guidelines focus on proteins labeled with nitroxides and on double electron-electron resonance (DEER aka PELDOR) measurements and provide suggestions on how to proceed analogously in other cases.

Electron paramagnetic resonance spectroscopy on G-protein-coupled receptors: Adopting strategies from related model systems

Membrane proteins, including ion channels, transporters and G-protein-coupled receptors (GPCRs), play a significant role in various physiological processes. Many of these proteins are difficult to express in large quantities, imposing crucial experimental restrictions. Nevertheless, there is now a wide variety of studies available utilizing electron paramagnetic resonance (EPR) spectroscopic techniques that expand experimental accessibility by using relatively small quantities of protein. Here, we give an overview starting from basic strategies in EPR on membrane proteins with a focus on GPCRs, while emphasizing several applications from recent years. We highlight how the arsenal of EPR-based techniques may provide significant further contributions to understanding the complex molecular machinery and energetic phenomena responsible for seamless workflow in essential biological processes.

Methodology for rigorous modeling of protein conformational changes by Rosetta using DEER distance restraints

We describe an approach for integrating distance restraints from Double Electron-Electron Resonance (DEER) spectroscopy into Rosetta with the purpose of modeling alternative protein conformations from an initial experimental structure. Fundamental to this approach is a multilateration algorithm that harnesses sets of interconnected spin label pairs to identify optimal rotamer ensembles at each residue that fit the DEER decay in the time domain. Benchmarked relative to data analysis packages, the algorithm yields comparable distance distributions with the advantage that fitting the DEER decay and rotamer ensemble optimization are coupled. We demonstrate this approach by modeling the protonation-dependent transition of the multidrug transporter PfMATE to an inward facing conformation with a deviation to the experimental structure of less than 2Å Cα RMSD. By decreasing spin label rotamer entropy, this approach engenders more accurate Rosetta models that are also more closely clustered, thus setting the stage for more robust modeling of protein conformational changes.

Benchmarking London dispersion corrected density functional theory for noncovalent ion-π interactions

The strongly attractive noncovalent interactions of charged atoms or molecules with π-systems are important binding motifs in many chemical and biological systems. These so-called ion-π interactions play a major role in enzymes, molecular recognition, and for the structure of proteins. In this work, a molecular test set termed IONPI19 is compiled for inter- and intramolecular ion-π interactions, which is well balanced between anionic and cationic systems. The IONPI19 set includes interaction energies of significantly larger molecules (up to 133 atoms) than in other ion-π test sets and covers a broad range of binding motifs. Accurate (local) coupled cluster values are provided as reference. Overall, 19 density functional approximations, including seven (meta-)GGAs, eight hybrid functionals, and four double-hybrid functionals combined with three different London dispersion corrections, are benchmarked for interaction energies. DFT results are further compared to wave function based methods such as MP2 and dispersion corrected Hartree-Fock. Also, the performance of semiempirical QM methods such as the GFNn-xTB and PMx family of methods is tested. It is shown that dispersion-uncorrected DFT underestimates ion-π interactions significantly, even though electrostatic interactions dominate the overall binding. Accordingly, the new charge dependent D4 dispersion model is found to be consistently better than the standard D3 correction. Furthermore, the functional performance trend along Jacob's ladder is generally obeyed and the reduction of the self-interaction error leads to an improvement of (double) hybrid functionals over (meta-)GGAs, even though the effect of the SIE is smaller than expected. Overall, the double-hybrids PWPB95-D4/QZ and revDSD-PBEP86-D4/QZ turned out to be the most reliable among all assessed methods for the description of ion-π interactions, which opens up new perspectives for systems where coupled cluster calculations are no longer computationally feasible.

Spin Labeling of RNA Using "Click" Chemistry for Coarse-grained Structure Determination via Pulsed Electron-electron Double Resonance Spectroscopy

Understanding the function of oligonucleotides on a molecular level requires methods for studying their structure, conformational changes, and internal dynamics. Various biophysical methods exist to achieve this, including the whole toolbox of Electron Paramagnetic Resonance (EPR or ESR) spectroscopy. An EPR method widely used in this regard is Pulsed Electron-Electron Double Resonance (PELDOR or DEER), which provides distances in the nanometer range between electron spins in biomolecules with Angstrom precision, without restriction to the size of the biomolecule, and in solution. Since oligonucleotides inherently do not contain unpaired electrons, these have to be introduced in the form of so-called spin labels. Firstly, this protocol describes how nitroxide spin labels can be site-specifically attached to oligonucleotides using "Click" chemistry. The reaction provides little byproducts, high yields, and is conveniently performed in aqueous solution. Secondly, the protocol details how to run the PELDOR experiment, analyze the data, and derive a coarse-grained structure. Here, emphasis is placed on the pitfalls, requirements for a good dataset, and limits of interpretation; thus, the protocol gives the user a guideline for the whole experiment i.e., from spin labeling, via the PELDOR measurement and data analysis, to the final coarse-grained structure. Graphical abstract: Schematic overview of the workflow described in this protocol: First, the spin-labeling of RNA is described, which is performed as a "Click"-reaction between the alkyne-functionalized RNA strand and the azide group of the spin label. Next, step-by-step instructions are given for setting up PELDOR/DEER distance measurements on the labeled RNA, and for data analysis. Finally, guidelines are provided for building a structural model from the previously analyzed data.

Efficient Quantum Chemical Calculation of Structure Ensembles and Free Energies for Nonrigid Molecules

The application of quantum chemical, automatic multilevel modeling workflows for the determination of thermodynamic (e.g., conformation equilibria, partition coefficients, pK_a values) and spectroscopic properties of relatively large, nonrigid molecules in solution is described. Key points are the computation of rather complete structure (conformer) ensembles with extremely fast but still reasonable GFN2-xTB or GFN-FF semiempirical methods in the CREST searching approach and subsequent refinement at a recently developed, accurate r²SCAN-3c DFT composite level. Solvation effects are included in all steps by accurate continuum solvation models (ALPB, (D)COSMO-RS). Consistent inclusion of thermostatistical contributions in the framework of the modified rigid-rotor-harmonic-oscillator approximation (mRRHO) based on xTB/FF computed PES is also recommended.

Localization of metal ions in biomolecules by means of pulsed dipolar EPR spectroscopy

Metal ions are important for the folding, structure, and function of biomolecules. Thus, knowing where their binding sites are located in proteins or oligonucleotides is a critical objective. X-ray crystallography and nuclear magnetic resonance are powerful methods in this respect, but both have their limitations. Here, a complementary method is highlighted in which paramagnetic metal ions are localized by means of trilateration using a combination of site-directed spin labeling and pulsed dipolar electron paramagnetic resonance spectroscopy. The working principle, the requirements, and the limitations of the method are critically discussed. Several applications of the method are outlined and compared with each other.