Structural biology by NMR: structure, dynamics, and interactions

Cryo-Electron Microscopy in the Study of Antiviral Innate Immunity

Cryo-electron microscopy is a powerful methodology in structural biology and has been broadly used in high-resolution structure determination for challenging samples, which are not readily available for traditional techniques. In particular, the strength of super macro-complexes and the lack of a need for crystals for cryo-EM make this technique feasible for the structural study of complexes involved in antiviral innate immunity. This chapter presents detailed information and experimental procedures of Cryo-EM for determining the structures of the complexes using STING as an example. The procedures included a sample quality check, high-resolution data acquisition, and image processing for Cryo-EM 3D structure determination.

AI-Driven Deep Learning Techniques in Protein Structure Prediction

Protein structure prediction is important for understanding their function and behavior. This review study presents a comprehensive review of the computational models used in predicting protein structure. It covers the progression from established protein modeling to state-of-the-art artificial intelligence (AI) frameworks. The paper will start with a brief introduction to protein structures, protein modeling, and AI. The section on established protein modeling will discuss homology modeling, ab initio modeling, and threading. The next section is deep learning-based models. It introduces some state-of-the-art AI models, such as AlphaFold (AlphaFold, AlphaFold2, AlphaFold3), RoseTTAFold, ProteinBERT, etc. This section also discusses how AI techniques have been integrated into established frameworks like Swiss-Model, Rosetta, and I-TASSER. The model performance is compared using the rankings of CASP14 (Critical Assessment of Structure Prediction) and CASP15. CASP16 is ongoing, and its results are not included in this review. Continuous Automated Model EvaluatiOn (CAMEO) complements the biennial CASP experiment. Template modeling score (TM-score), global distance test total score (GDT_TS), and Local Distance Difference Test (lDDT) score are discussed too. This paper then acknowledges the ongoing difficulties in predicting protein structure and emphasizes the necessity of additional searches like dynamic protein behavior, conformational changes, and protein-protein interactions. In the application section, this paper introduces some applications in various fields like drug design, industry, education, and novel protein development. In summary, this paper provides a comprehensive overview of the latest advancements in established protein modeling and deep learning-based models for protein structure predictions. It emphasizes the significant advancements achieved by AI and identifies potential areas for further investigation.

CDK2 and CDK4: Cell Cycle Functions Evolve Distinct, Catalysis-Competent Conformations, Offering Drug Targets

Cyclin-dependent kinases (CDKs), particularly CDK4 and CDK2, are crucial for cell cycle progression from the Gap 1 (G1) to the Synthesis (S) phase by phosphorylating targets such as the Retinoblastoma Protein (Rb). CDK4, paired with cyclin-D, operates in the long G1 phase, while CDK2 with cyclin-E, manages the brief G1-to-S transition, enabling DNA replication. Aberrant CDK signaling leads to uncontrolled cell proliferation, which is a hallmark of cancer. Exactly how they accomplish their catalytic phosphorylation actions with distinct efficiencies poses the fundamental, albeit overlooked question. Here we combined available experimental data and modeling of the active complexes to establish their conformational functional landscapes to explain how the two cyclin/CDK complexes differentially populate their catalytically competent states for cell cycle progression. Our premise is that CDK catalytic efficiencies could be more important for cell cycle progression than the cyclin-CDK biochemical binding specificity and that efficiency is likely the prime determinant of cell cycle progression. We observe that CDK4 is more dynamic than CDK2 in the ATP binding site, the regulatory spine, and the interaction with its cyclin partner. The N-terminus of cyclin-D acts as an allosteric regulator of the activation loop and the ATP-binding site in CDK4. Integrated with a suite of experimental data, we suggest that the CDK4 complex is less capable of remaining in the active catalytically competent conformation, and may have a lower catalytic efficiency than CDK2, befitting their cell cycle time scales, and point to critical residues and motifs that drive their differences. Our mechanistic landscape may apply broadly to kinases, and we propose two drug design strategies: (i) allosteric Inhibition by conformational stabilization for targeting allosteric CDK4 regulation by cyclin-D, and (ii) dynamic entropy-optimized targeting which leverages the dynamic, entropic aspects of CDK4 to optimize drug binding efficacy.

Advancing Natural Product Discovery: A Structure-Oriented Fractions Screening Platform for Compound Annotation and Isolation

Natural product discovery is hindered by the lack of tools that integrate untargeted nuclear magnetic resonance and mass spectrometry data on a library scale. This article describes the first application of the innovative NMR/MS-based machine learning tool, the "Structure-Oriented Fractions Screening Platform (SFSP)", enabling functional-group-guided fractionation and accelerating the discovery and characterization of undescribed natural products. The concept was applied to the extract of a marine fungus known to be a prolific producer of diverse natural products. With the assistance of SFSP, we isolated 24 flavipidin derivatives and five phenalenone analogues from Aspergillus sp. GE2-6, revealing 27 undescribed compounds. Compounds 7-22 were proposed as isomeric derivatives featuring a 5/6-ring fusion, formed by the dimerization of flavipidin E (5). Compounds 23 and 24 were envisaged as isomeric derivatives with a 6/5/6-ring fusion, generated through the degradation of two flavipidin E molecules. Furthermore, flavipidin A (1) and asperphenalenone E (28) exhibited potent anti-influenza (PR8) activities, with IC50 values of 21.9 ± 0.2 and 12.9 ± 0.1 μM, respectively. Meanwhile, asperphenalenone (26) and asperphenalenone P (27) treatments exhibited significant inhibition of HIV pseudovirus infection in 293FT cells, boasting IC50 values of 6.1 ± 0.9 and 4.6 ± 1.1 μM, respectively. Overall, SFSP streamlines natural product isolation through NMR and MS data integration, as showcased by the discovery of numerous undescribed flavipidins and phenalenones based on NMR olefinic signals and low-field hydroxy signals.

Triboelectric Nanogenerators: Low-Cost Power Supplies for Improved Electrospray Ionization

Electrospray ionization (ESI) is one of the most popular methods to generate ions for mass spectrometry (MS). When compared with other ionization techniques, it can generate ions from liquid-phase samples without additives, retaining covalent and non-covalent interactions of the molecules of interest. When hyphenated to liquid chromatography, it greatly expands the versatility of MS analysis of complex mixtures. However, despite the extensive growth in the application of ESI, the technique still suffers from some drawbacks when powered by direct current (DC) power supplies. Triboelectric nanogenerators promise to be a new power source for the generation of ions by ESI, improving on the analytical capabilities of traditional DC ESI. In this review we highlight the fundamentals of ESI driven by DC power supplies, its contrasting qualities to triboelectric nanogenerator power supplies, and its applications to three distinct fields of research: forensics, metabolomics, and protein structure analysis.

A Review of the Current State of Magnetic Force Microscopy to Unravel the Magnetic Properties of Nanomaterials Applied in Biological Systems and Future Directions for Quantum Technologies

Magnetism plays a pivotal role in many biological systems. However, the intensity of the magnetic forces exerted between magnetic bodies is usually low, which demands the development of ultra-sensitivity tools for proper sensing. In this framework, magnetic force microscopy (MFM) offers excellent lateral resolution and the possibility of conducting single-molecule studies like other single-probe microscopy (SPM) techniques. This comprehensive review attempts to describe the paramount importance of magnetic forces for biological applications by highlighting MFM's main advantages but also intrinsic limitations. While the working principles are described in depth, the article also focuses on novel micro- and nanofabrication procedures for MFM tips, which enhance the magnetic response signal of tested biomaterials compared to commercial nanoprobes. This work also depicts some relevant examples where MFM can quantitatively assess the magnetic performance of nanomaterials involved in biological systems, including magnetotactic bacteria, cryptochrome flavoproteins, and magnetic nanoparticles that can interact with animal tissues. Additionally, the most promising perspectives in this field are highlighted to make the reader aware of upcoming challenges when aiming toward quantum technologies.

Quantitative approaches for decoding the specificity of the human T cell repertoire

T cell receptor (TCR)-peptide-major histocompatibility complex (pMHC) interactions play a vital role in initiating immune responses against pathogens, and the specificity of TCRpMHC interactions is crucial for developing optimized therapeutic strategies. The advent of high-throughput immunological and structural evaluation of TCR and pMHC has provided an abundance of data for computational approaches that aim to predict favorable TCR-pMHC interactions. Current models are constructed using information on protein sequence, structures, or a combination of both, and utilize a variety of statistical learning-based approaches for identifying the rules governing specificity. This review examines the current theoretical, computational, and deep learning approaches for identifying TCR-pMHC recognition pairs, placing emphasis on each method's mathematical approach, predictive performance, and limitations.

Improving Geometric Validation Metrics and Ensuring Consistency with Experimental Data through TrioSA: An NMR Refinement Protocol

Protein model refinement a the crucial step in improving the quality of a predicted protein model. This study presents an NMR refinement protocol called TrioSA (torsion-angle and implicit-solvation-optimized simulated annealing) that improves the accuracy of backbone/side-chain conformations and the overall structural quality of proteins. TrioSA was applied to a subset of 3752 solution NMR protein structures accompanied by experimental NMR data: distance and dihedral angle restraints. We compared the initial NMR structures with the TrioSA-refined structures and found significant improvements in structural quality. In particular, we observed a reduction in both the maximum and number of NOE (nuclear Overhauser effect) violations, indicating better agreement with experimental NMR data. TrioSA improved geometric validation metrics of NMR protein structure, including backbone accuracy and the secondary structure ratio. We evaluated the contribution of each refinement element and found that the torsional angle potential played a significant role in improving the geometric validation metrics. In addition, we investigated protein-ligand docking to determine if TrioSA can improve biological outcomes. TrioSA structures exhibited better binding prediction compared to the initial NMR structures. This study suggests that further development and research in computational refinement methods could improve biomolecular NMR structural determination.

New insight into the traditional model of the coagulation cascade and its regulation: illustrated review of a three-dimensional view

The coagulation process relies on an intricate network of three-dimensional structural interactions and subtle biological regulations. In the present review, we illustrate the state of the art of the structural biology of the coagulation cascade by surveying the Protein Data Bank and the EBI AlphaFold databases. Investigations performed in the last decade have provided structural information on essentially all players involved in the process. Indeed, the initial characterization of specific and rather canonical domains has been progressively extended to complicated multidomain proteins. Recently, the application of cryogenic electron microscopy techniques has unraveled the structural features of highly complex coagulation factors, which has led to enhanced understanding. This review initially focuses on the structure of the individual factors as a function of their involvement in intrinsic, extrinsic, and common pathways. A specific emphasis is given to what is known or unknown on the structural basis of each step of the cascade. Available data providing clues on the structural recognition of the factors involved in the functional partnerships of the pathways are illustrated. Recent structures of important complexes formed by these proteins with regulators are described, focusing on the drugs used as anticoagulants and on their reversal agents. Finally, we highlight the different roles that innovative biomolecules such as aptamers may have in the regulation of the cascade.

NMR-Chemical-Shift-Driven Protocol Reveals the Cofactor-Bound, Complete Structure of Dynamic Intermediates of the Catalytic Cycle of Oncogenic KRAS G12C Protein and the Significance of the Mg2+ Ion

In this work, catalytically significant states of the oncogenic G12C variant of KRAS, those of Mg2+-free and Mg2+-bound GDP-loaded forms, have been determined using CS-Rosetta software and NMR-data-driven molecular dynamics simulations. There are several Mg2+-bound G12C KRAS/GDP structures deposited in the Protein Data Bank (PDB), so this system was used as a reference, while the structure of the Mg2+-free but GDP-bound state of the RAS cycle has not been determined previously. Due to the high flexibility of the Switch-I and Switch-II regions, which also happen to be the catalytically most significant segments, only chemical shift information could be collected for the most important regions of both systems. CS-Rosetta was used to derive an "NMR ensemble" based on the measured chemical shifts, which, however, did not contain the nonprotein components of the complex. We developed a torsional restraint set for backbone torsions based on the CS-Rosetta ensembles for MD simulations, overriding the force-field-based parametrization in the presence of the reinserted cofactors. This protocol (csdMD) resulted in complete models for both systems that also retained the structural features and heterogeneity defined by the measured chemical shifts and allowed a detailed comparison of the Mg2+-bound and Mg2+-free states of G12C KRAS/GDP.

Evolution of Sequence and Structure of SARS-CoV-2 Spike Protein: A Dynamic Perspective

Novel coronavirus (SARS-CoV-2) enters its host cell through a surface spike protein. The viral spike protein has undergone several modifications/mutations at the genomic level, through which it modulated its structure-function and passed through several variants of concern. Recent advances in high-resolution structure determination and multiscale imaging techniques, cost-effective next-generation sequencing, and development of new computational methods (including information theory, statistical methods, machine learning, and many other artificial intelligence-based techniques) have hugely contributed to the characterization of sequence, structure, function of spike proteins, and its different variants to understand viral pathogenesis, evolutions, and transmission. Laying on the foundation of the sequence-structure-function paradigm, this review summarizes not only the important findings on structure/function but also the structural dynamics of different spike components, highlighting the effects of mutations on them. As dynamic fluctuations of three-dimensional spike structure often provide important clues for functional modulation, quantifying time-dependent fluctuations of mutational events over spike structure and its genetic/amino acidic sequence helps identify alarming functional transitions having implications for enhanced fusogenicity and pathogenicity of the virus. Although these dynamic events are more difficult to capture than quantifying a static, average property, this review encompasses those challenging aspects of characterizing the evolutionary dynamics of spike sequence and structure and their implications for functions.

Lessons Learnt from COVID-19: Computational Strategies for Facing Present and Future Pandemics

Since its outbreak in December 2019, the COVID-19 pandemic has caused the death of more than 6.5 million people around the world. The high transmissibility of its causative agent, the SARS-CoV-2 virus, coupled with its potentially lethal outcome, provoked a profound global economic and social crisis. The urgency of finding suitable pharmacological tools to tame the pandemic shed light on the ever-increasing importance of computer simulations in rationalizing and speeding up the design of new drugs, further stressing the need for developing quick and reliable methods to identify novel active molecules and characterize their mechanism of action. In the present work, we aim at providing the reader with a general overview of the COVID-19 pandemic, discussing the hallmarks in its management, from the initial attempts at drug repurposing to the commercialization of Paxlovid, the first orally available COVID-19 drug. Furthermore, we analyze and discuss the role of computer-aided drug discovery (CADD) techniques, especially those that fall in the structure-based drug design (SBDD) category, in facing present and future pandemics, by showcasing several successful examples of drug discovery campaigns where commonly used methods such as docking and molecular dynamics have been employed in the rational design of effective therapeutic entities against COVID-19.

Efficient protein conformation dynamics characterization enabled by mobility-mass spectrometry

Protein structure dynamics in solution and from solution to gas phase are important but challenging topics. Great efforts and advances have been made especially since the wide application of ion mobility mass spectrometry (IM-MS), by which protein collision cross section (CCS) in gas phase could be measured. Due to the lack of efficient experimental methods, protein structures in protein databank are typically referred as their structures in solution. Although conventional structural biology techniques provide high-resolution protein structures, complicated and stringent processes also limit their applicability under different solvent conditions, thus preventing the capture of protein dynamics in solution. Enabled by the combination of mobility capillary electrophoresis (MCE) and IM-MS, an efficient experimental protocol was developed to characterize protein conformation dynamics in solution and from solution to gas phase. As a first attempt, key factors that affecting protein conformations were distinguished and evaluated separately, including pH, temperature, softness of ionization process, presence and specific location of disulfide bonds. Although similar extent of unfolding could be observed for different proteins, in-depth analysis reveals that pH decrease from 7.0 to 3.0 dominates the unfolding of proteins without disulfide bonds in conventional ESI-MS experiments; while harshness of the ionization process dominates the unfolding of proteins with disulfide bonds. Second, disulfide bonds show capability of preserving protein conformations in acidic solution environments. However, by monitoring protein conformation dynamics and comparing results from different proteins, it is also found that their capability is position dependent. Surprisingly, disulfide bonds did not show the capability of preserving protein conformations during ionization processes.

A scoring function for the prediction of protein complex interfaces based on the neighborhood preferences of amino acids

Proteins often assemble into functional complexes, the structures of which are more difficult to obtain than those of the individual protein molecules. Given the structures of the subunits, it is possible to predict plausible complex models via computational methods such as molecular docking. Assessing the quality of the predicted models is crucial to obtain correct complex structures. Here, an energy-scoring function was developed based on the interfacial residues of structures in the Protein Data Bank. The statistically derived energy function (Nepre) imitates the neighborhood preferences of amino acids, including the types and relative positions of neighboring residues. Based on the preference statistics, a program iNepre was implemented and its performance was evaluated with several benchmarking decoy data sets. The results show that iNepre scores are powerful in model ranking to select the best protein complex structures.

DNA G-quadruplex-stabilizing metal complexes as anticancer drugs

Guanine quadruplexes (G4s) are important targets for cancer treatments as their stabilization has been associated with a reduction of telomere ends or a lower oncogene expression. Although less abundant than purely organic ligands, metal complexes have shown remarkable abilities to stabilize G4s, and a wide variety of techniques have been used to characterize the interaction between ligands and G4s. However, improper alignment between the large variety of experimental techniques and biological activities can lead to improper identification of top candidates, which hampers progress of this important class of G4 stabilizers. To address this, we first review the different techniques for their strengths and weaknesses to determine the interaction of the complexes with G4s, and provide a checklist to guide future developments towards comparable data. Then, we surveyed 74 metal-based ligands for G4s that have been characterized to the in vitro level. Of these complexes, we assessed which methods were used to characterize their G4-stabilizing capacity, their selectivity for G4s over double-stranded DNA (dsDNA), and how this correlated to bioactivity data. For the biological activity data, we compared activities of the G4-stabilizing metal complexes with that of cisplatin. Lastly, we formulated guidelines for future studies on G4-stabilizing metal complexes to further enable maturation of this field.

Solvent paramagnetic relaxation enhancement as a versatile method for studying structure and dynamics of biomolecular systems

Solvent paramagnetic relaxation enhancement (sPRE) is a versatile nuclear magnetic resonance (NMR)-based method that allows characterization of the structure and dynamics of biomolecular systems through providing quantitative experimental information on solvent accessibility of NMR-active nuclei. Addition of soluble paramagnetic probes to the solution of a biomolecule leads to paramagnetic relaxation enhancement in a concentration-dependent manner. Here we review recent progress in the sPRE-based characterization of structural and dynamic properties of biomolecules and their complexes, and aim to deliver a comprehensive illustration of a growing number of applications of the method to various biological systems. We discuss the physical principles of sPRE measurements and provide an overview of available co-solute paramagnetic probes. We then explore how sPRE, in combination with complementary biophysical techniques, can further advance biomolecular structure determination, identification of interaction surfaces within protein complexes, and probing of conformational changes and low-population transient states, as well as deliver insights into weak, nonspecific, and transient interactions between proteins and co-solutes. In addition, we present examples of how the incorporation of solvent paramagnetic probes can improve the sensitivity of NMR experiments and discuss the prospects of applying sPRE to NMR metabolomics, drug discovery, and the study of intrinsically disordered proteins.

Current limitations of solid-state NMR in carbohydrate and cell wall research

High-resolution investigation of cell wall materials has emerged as an important application of biomolecular solid-state NMR (ssNMR). Multidimensional correlation experiments have become a standard method for obtaining sufficient spectral resolution to determine the polymorphic structure of carbohydrates and address biochemical questions regarding the supramolecular organization of cell walls. Using plant cellulose and matrix polysaccharides as examples, we will review how the multifaceted complexity of polysaccharide structure is impeding the resonance assignment process and assess the available biochemical and spectroscopic approaches that could circumvent this barrier. We will emphasize the ineffectiveness of the current methods in reconciling the ever-growing dataset and deriving structural information. We will evaluate the protocols for achieving efficient and homogeneous hyperpolarization across the cell wall material using magic-angle spinning dynamic nuclear polarization (MAS-DNP). Critical questions regarding the line-broadening effects of cell wall molecules at cryogenic temperature and by paramagnetic biradicals will be considered. Finally, the MAS-DNP method will be placed into a broader context with other structural characterization techniques, such as cryo-electron microscopy, to advance ssNMR research in carbohydrate and cell wall biomaterials.

Insights into Phosphorylation-Induced Protein Allostery and Conformational Dynamics of Glycogen Phosphorylase via Integrative Structural Mass Spectrometry and In Silico Modeling

Allosteric regulation plays a fundamental role in innumerable biological processes. Understanding its dynamic mechanism and impact at the molecular level is of great importance in disease diagnosis and drug discovery. Glycogen phosphorylase (GP) is a phosphoprotein responding to allosteric regulation and has significant biological importance to glycogen metabolism. Although the atomic structures of GP have been previously solved, the conformational dynamics of GP related to allostery regulation remain largely elusive due to its macromolecular size (∼196 kDa). Here, we integrated native top-down mass spectrometry (nTD-MS), hydrogen-deuterium exchange MS (HDX-MS), protection factor (PF) analysis, molecular dynamics (MD) simulations, and allostery signaling analysis to examine the structural basis and dynamics for the allosteric regulation of GP by phosphorylation. nTD-MS reveals differences in structural stability as well as oligomeric state between the unphosphorylated (GPb) and phosphorylated (GPa) forms. HDX-MS, PF analysis, and MD simulations further pinpoint the structural differences between GPb and GPa involving the binding interfaces (the N-terminal and tower-tower helices), catalytic site, and PLP-binding region. More importantly, it also allowed us to complete the missing link of the long-range communication process from the N-terminal tail to the catalytic site caused by phosphorylation. This integrative MS and in silico-based platform is highly complementary to biophysical approaches and yields valuable insights into protein structures and dynamic regulation.

The detoxification activities and mechanisms of microcystinase towards MC-LR

Microcystins (MCs) are the most common and toxic cyanotoxins that are hazardous to human health and ecosystems. Microcystinase is the enzyme in charge of the initial step in the biodegradation of MCs. The characterization, application conditions, and detoxification mechanisms of microcystinase from an indigenous bacterium Sphingopyxis sp. YF1 towards MC-LR were investigated in the current study. The microcystinase gene of strain YF1 was most similar to Sphingomonas sp. USTB-05 and contained a CAAX-family conversed abortive Infection (ABI) domain. The microcystinase was successful obtained and purified by overexpression in Escherichia coli. The highest degradation rate of MC-LR was 1.0 μg/mL/min under the optimal condition of 30 ℃, pH 7, 20 μg/mL MC-LR, and 400 μg/mL microcystinase. The MC-degrading product was identified as linearized MC-LR, which possessed a much lower inhibitory activity against protein phosphatase 2A than MC-LR. Microcystinase interacted with MC-LR via amino acid residues involved in through the formation of conventional Hydrogen Bond, Pi-Pi T-shapes, Van der Waals force, and so on. The optimal MC-degrading condition of pure microcystinase and its detoxification mechanisms against MC-LR were revealed. The toxicity of purified linearized MC-LR was explored for the first time. These findings suggest that pure microcystinase may efficiently detoxify MCs and it is promising in the bioremediation of MC-polluted environments.

Molecular Architecture of the Antiophidic Protein DM64 and its Binding Specificity to Myotoxin II From Bothrops asper Venom

DM64 is a toxin-neutralizing serum glycoprotein isolated from Didelphis aurita, an ophiophagous marsupial naturally resistant to snake envenomation. This 64 kDa antitoxin targets myotoxic phospholipases A2, which account for most local tissue damage of viperid snakebites. We investigated the noncovalent complex formed between native DM64 and myotoxin II, a myotoxic phospholipase-like protein from Bothrops asper venom. Analytical ultracentrifugation (AUC) and size exclusion chromatography indicated that DM64 is monomeric in solution and binds equimolar amounts of the toxin. Attempts to crystallize native DM64 for X-ray diffraction were unsuccessful. Obtaining recombinant protein to pursue structural studies was also challenging. Classical molecular modeling techniques were impaired by the lack of templates with more than 25% sequence identity with DM64. An integrative structural biology approach was then applied to generate a three-dimensional model of the inhibitor bound to myotoxin II. I-TASSER individually modeled the five immunoglobulin-like domains of DM64. Distance constraints generated by cross-linking mass spectrometry of the complex guided the docking of DM64 domains to the crystal structure of myotoxin II, using Rosetta. AUC, small-angle X-ray scattering (SAXS), molecular modeling, and molecular dynamics simulations indicated that the DM64-myotoxin II complex is structured, shows flexibility, and has an anisotropic shape. Inter-protein cross-links and limited hydrolysis analyses shed light on the inhibitor's regions involved with toxin interaction, revealing the critical participation of the first, third, and fifth domains of DM64. Our data showed that the fifth domain of DM64 binds to myotoxin II amino-terminal and beta-wing regions. The third domain of the inhibitor acts in a complementary way to the fifth domain. Their binding to these toxin regions presumably precludes dimerization, thus interfering with toxicity, which is related to the quaternary structure of the toxin. The first domain of DM64 interacts with the functional site of the toxin putatively associated with membrane anchorage. We propose that both mechanisms concur to inhibit myotoxin II toxicity by DM64 binding. The present topological characterization of this toxin-antitoxin complex constitutes an essential step toward the rational design of novel peptide-based antivenom therapies targeting snake venom myotoxins.

Characterization of backbone dynamics using solution NMR spectroscopy to discern the functional plasticity of structurally analogous proteins

The comprehensive delineation of inherent dynamic motions embedded in proteins, which can be crucial for their functional repertoire, is often essential yet remains poorly understood in the majority of cases. In this protocol, we outline detailed descriptions of the necessary steps for employing solution NMR spectroscopy for the in-depth amino acid level understanding of backbone dynamics of proteins. We describe the application of the protocol on the structurally analogous Tudor domains with disparate functionalities as a model system. For complete details on the use and execution of this protocol, please refer to Kawale and Burmann (2021).

Implementing Digital-Waveform Technology for Extended m/z Range Operation on a Native Dual-Quadrupole FT-IM-Orbitrap Mass Spectrometer

Here, we describe a digital-waveform dual-quadrupole mass spectrometer that enhances the performance of our drift tube FT-IMS high-resolution Orbitrap mass spectrometer (MS). The dual-quadrupole analyzer enhances the instrument capabilities for studies of large protein and protein complexes. The first quadrupole (q) provides a means for performing low-energy collisional activation of ions to reduce or eliminate noncovalent adducts, viz., salts, buffers, detergents, and/or endogenous ligands. The second quadrupole (Q) is used to mass-select ions of interest for further interrogation by ion mobility spectrometry and/or collision-induced dissociation (CID). Q is operated using digital-waveform technology (DWT) to improve the mass selection compared to that achieved using traditional sinusoidal waveforms at floated DC potentials (>500 V DC). DWT allows for increased precision of the waveform for a fraction of the cost of conventional RF drivers and with readily programmable operation and precision (Hoffman, N. M. . A comparison-based digital-waveform generator for high-resolution duty cycle. Review of Scientific Instruments 2018, 89, 084101).

Biophysical applications in structural and molecular biology

The main objective of structural biology is to model proteins and other biological macromolecules and link the structural information to function and dynamics. The biological functions of protein molecules and nucleic acids are inherently dependent on their conformational dynamics. Imaging of individual molecules and their dynamic characteristics is an ample source of knowledge that brings new insights about mechanisms of action. The atomic-resolution structural information on most of the biomolecules has been solved by biophysical techniques; either by X-ray diffraction in single crystals or by nuclear magnetic resonance (NMR) spectroscopy in solution. Cryo-electron microscopy (cryo-EM) is emerging as a new tool for analysis of a larger macromolecule that couldn't be solved by X-ray crystallography or NMR. Now a day's low-resolution Cryo-EM is used in combination with either X-ray crystallography or NMR. The present review intends to provide updated information on applications like X-ray crystallography, cryo-EM and NMR which can be used independently and/or together in solving structures of biological macromolecules for our full comprehension of their biological mechanisms.

Molecular insights on CALX-CBD12 interdomain dynamics from MD simulations, RDCs, and SAXS

Na⁺/Ca²⁺ exchangers (NCXs) are secondary active transporters that couple the translocation of Na⁺ with the transport of Ca²⁺ in the opposite direction. The exchanger is an essential Ca²⁺ extrusion mechanism in excitable cells. It consists of a transmembrane domain and a large intracellular loop that contains two Ca²⁺-binding domains, CBD1 and CBD2. The two CBDs are adjacent to each other and form a two-domain Ca²⁺ sensor called CBD12. Binding of intracellular Ca²⁺ to CBD12 activates the NCX but inhibits the NCX of Drosophila, CALX. NMR spectroscopy and SAXS studies showed that CALX and NCX CBD12 constructs display significant interdomain flexibility in the apo state but assume rigid interdomain arrangements in the Ca²⁺-bound state. However, detailed structure information on CBD12 in the apo state is missing. Structural characterization of proteins formed by two or more domains connected by flexible linkers is notoriously challenging and requires the combination of orthogonal information from multiple sources. As an attempt to characterize the conformational ensemble of CALX-CBD12 in the apo state, we applied molecular dynamics (MD) simulations, NMR (¹H-¹⁵N residual dipolar couplings), and small-angle x-ray scattering (SAXS) data in a combined strategy to select an ensemble of conformations in agreement with the experimental data. This joint approach demonstrated that CALX-CBD12 preferentially samples closed conformations, whereas the wide-open interdomain arrangement characteristic of the Ca²⁺-bound state is less frequently sampled. These results are consistent with the view that Ca²⁺ binding shifts the CBD12 conformational ensemble toward extended conformers, which could be a key step in the NCXs' allosteric regulation mechanism. This strategy, combining MD with NMR and SAXS, provides a powerful approach to select ensembles of conformations that could be applied to other flexible multidomain systems.

Conformational changes and binding property of the periplasmic binding protein BtuF during vitamin B12 transport revealed by collision-induced unfolding, hydrogen-deuterium exchange mass spectrometry and molecular dynamic simulation

The periplasmic binding protein (PBP) BtuF plays a key role in transporting vitamin B₁₂ from periplasm to the ATP-binding cassette (ABC) transporter BtuCD. Conformational changes of BtuF during transport can hardly be captured by traditional biophysical methods and the exact mechanism regarding B₁₂ and BtuF recognition is still under debate. In the present work, conformational changes of BtuF upon B₁₂ binding and release were investigated using hybrid approaches including collision-induced unfolding (CIU), hydrogen deuterium exchange mass spectrometry (HDX-MS) and molecular dynamics (MD) simulation. It was found that B₁₂ binding increased the stability of BtuF. In addition, fast exchange regions of BtuF were localized. Most importantly, midpoint of hinge helix in BtuF was found highly flexible, and binding of B₁₂ proceed in a manner similar to the Venus flytrap mechanism. Our study therefore delineates a clear view of BtuF delivering B₁₂, and demonstrated a hybrid approach encompassing MS and computer based methods that holds great potential to the probing of conformational dynamics of proteins in action.

Inherent backbone dynamics fine-tune the functional plasticity of Tudor domains

Tudor domains are crucial for mediating a diversity of protein-protein or protein-DNA interactions involved in nucleic acid metabolism. Using solution NMR spectroscopy, we assess the comprehensive understanding of the dynamical properties of the respective Tudor domains from four different bacterial (Escherichia coli) proteins UvrD, Mfd, RfaH, and NusG involved in different aspects of bacterial transcription regulation and associated processes. These proteins are benchmarked to the canonical Tudor domain fold from the human SMN protein. The detailed analysis of protein backbone dynamics and subsequent analysis by the Lipari-Szabo model-free approach revealed subtle differences in motions of the amide-bond vector on both pico- to nanosecond and micro- to millisecond timescales. On these timescales, our comparative approach reveals the usefulness of discrete amplitudes of dynamics to discern the different functionalities for Tudor domains exhibiting promiscuous binding, including the metamorphic Tudor domain included in the study.

Synthesis of 13C/19F/2H labeled indoles for use as tryptophan precursors for protein NMR spectroscopy

Synthesis of indoles labeled with 13C-1H and 13C-19F spin pairs is described. All syntheses utilize inexpensive carbon-13C dioxide as the 13C isotope source. Ruthenium-mediated ring-closing metathesis is the key step in construction of the 13C containing indole carbocycle. Fluorine is introduced via electrophilic fluorination at the 7-position and via palladium-mediated cross-coupling at the 4-position. Indole and fluoroindoles are viable tryptophan precursors for in vivo protein expression. We show that they are viable also in in vitro protein synthesis using standard E. coli S30 extracts. Incorporation of the synthesized 13C-1H and 13C-19F spin pair labeled tryptophans into proteins enables high-resolution and high-sensitivity nuclear magnetic resonance (NMR) spectroscopy.

CH Mode Mixing Determines the Band Shape of the Carboxylate Symmetric Stretch in Apo-EDTA, Ca2+-EDTA, and Mg2+-EDTA

The infrared spectra of EDTA complexed with Ca²⁺ and Mg²⁺ contain, to date, unidentified vibrational bands. This study assigns the peaks in the linear and two-dimensional infrared spectra of EDTA, with and without either Ca²⁺ or Mg²⁺ ions. Two-dimensional infrared spectroscopy and DFT calculations reveal that, in both the presence and absence of ions, the carboxylate symmetric stretch and the terminal CH bending vibrations mix. We introduce a method to calculate participation coefficients that quantify the contribution of the carboxylate symmetric stretch, CH wag, CH twist, and CH scissor in the 1400-1550 cm^-1 region. With the help of participation coefficients, we assign the 1400-1430 cm^-1 region to the carboxylate symmetric stretch, which can mix with CH modes. We assign the 1000-1380 cm^-1 region to CH twist modes, the 1380-1430 cm^-1 region to wag modes, and the 1420-1650 cm^-1 region to scissor modes. The difference in binding geometry between the carboxylate-Ca²⁺ and carboxylate-Mg²⁺ complex manifests as new diagonal and cross-peaks between the mixed modes in the two complexes. The small Mg²⁺ ion binds EDTA tighter than the Ca²⁺ ion, which causes a redshift of the COO symmetric stretches of the sagittal carboxylates. Energy decomposition analysis further characterizes the importance of electrostatics and deformation energy in the bound complexes.

Computational IR Spectroscopy of Insulin Dimer Structure and Conformational Heterogeneity

We have investigated the structure and conformational dynamics of insulin dimer using a Markov state model (MSM) built from extensive unbiased atomistic molecular dynamics simulations and performed infrared spectral simulations of the insulin MSM to describe how structural variation within the dimer can be experimentally resolved. Our model reveals two significant conformations to the dimer: a dominant native state consistent with other experimental structures of the dimer and a twisted state with a structure that appears to reflect a ∼55° clockwise rotation of the native dimer interface. The twisted state primarily influences the contacts involving the C-terminus of insulin's B chain, shifting the registry of its intermolecular hydrogen bonds and reorganizing its side-chain packing. The MSM kinetics predict that these configurations exchange on a 14 μs time scale, largely passing through two Markov states with a solvated dimer interface. Computational amide I spectroscopy of site-specifically ¹³C¹⁸O labeled amides indicates that the native and twisted conformation can be distinguished through a series of single and dual labels involving the B24F, B25F, and B26Y residues. Additional structural heterogeneity and disorder is observed within the native and twisted states, and amide I spectroscopy can also be used to gain insight into this variation. This study will provide important interpretive tools for IR spectroscopic investigations of insulin structure and transient IR kinetics experiments studying the conformational dynamics of insulin dimer.

How to assess the structural dynamics of transcription factors by integrating sparse NMR and EPR constraints with molecular dynamics simulations

We review recent advances in modeling structural ensembles of transcription factors from nuclear magnetic resonance (NMR) and electron paramagnetic resonance (EPR) spectroscopic data, integrated with molecular dynamics (MD) simulations. We focus on approaches that confirm computed conformational ensembles by sparse constraints obtained from magnetic resonance. This combination enables the deduction of functional and structural protein models even if nuclear Overhauser effects (NOEs) are too scarce for conventional structure determination. We highlight recent insights into the folding-upon-DNA binding transitions of intrinsically disordered transcription factors that could be assessed using such integrative approaches.

Microfluidic platform for serial mixing experiments with in operando nuclear magnetic resonance spectroscopy

We present a microfluidic platform that allows in operando nuclear magnetic resonance (NMR) observation of serial mixing experiments. Gradually adding one reagent to another is a fundamental experimental modality, widely used to quantify equilibrium constants, for titrations, and in chemical kinetics studies. NMR provides a non-invasive means to quantify concentrations and to follow structural changes at the molecular level as a function of exchanged volume. Using active pneumatic valving on the microfluidic device directly inside an NMR spectrometer equipped with a transmission-line NMR microprobe, the system allows injection of aliquots and in situ mixing in a sample volume of less than 10 μL.

Deep Learning in Protein Structural Modeling and Design

Deep learning is catalyzing a scientific revolution fueled by big data, accessible toolkits, and powerful computational resources, impacting many fields, including protein structural modeling. Protein structural modeling, such as predicting structure from amino acid sequence and evolutionary information, designing proteins toward desirable functionality, or predicting properties or behavior of a protein, is critical to understand and engineer biological systems at the molecular level. In this review, we summarize the recent advances in applying deep learning techniques to tackle problems in protein structural modeling and design. We dissect the emerging approaches using deep learning techniques for protein structural modeling and discuss advances and challenges that must be addressed. We argue for the central importance of structure, following the "sequence → structure → function" paradigm. This review is directed to help both computational biologists to gain familiarity with the deep learning methods applied in protein modeling, and computer scientists to gain perspective on the biologically meaningful problems that may benefit from deep learning techniques.

Dynamically encoded reactivity of Ras enzymes: opening new frontiers for drug discovery

Decoding molecular flexibility in order to understand and predict biological processes-applying the principles of dynamic-structure-activity relationships (DSAR)-becomes a necessity when attempting to design selective and specific inhibitors of a protein that has overlapping interaction surfaces with its upstream and downstream partners along its signaling cascade. Ras proteins are molecular switches that meet this definition perfectly. The close-lying P-loop and the highly flexible switch I and switch II regions are the site of nucleotide-, assisting-, and effector-protein binding. Oncogenic mutations that also appear in this region do not cause easily characterized overall structural changes, due partly to the inherent conformational heterogeneity and pliability of these segments. In this review, we present an overview of the results obtained using approaches targeting Ras dynamics, such as nuclear magnetic resonance (NMR) measurements and experiment-based modeling calculations (mostly molecular dynamics (MD) simulations). These methodologies were successfully used to decipher the mutant- and isoform-specific nature of certain transient states, far-lying allosteric sites, and the internal interaction networks, as well as the interconnectivity of the catalytic and membrane-binding regions. This opens new therapeutic potential: the discovered interaction hotspots present hitherto not targeted, selective sites for drug design efforts in diverse locations of the protein matrix.

ARIAweb: a server for automated NMR structure calculation

Nuclear magnetic resonance (NMR) spectroscopy is a method of choice to study the dynamics and determine the atomic structure of macromolecules in solution. The standalone program ARIA (Ambiguous Restraints for Iterative Assignment) for automated assignment of nuclear Overhauser enhancement (NOE) data and structure calculation is well established in the NMR community. To ultimately provide a perfectly transparent and easy to use service, we designed an online user interface to ARIA with additional functionalities. Data conversion, structure calculation setup and execution, followed by interactive visualization of the generated 3D structures are all integrated in ARIAweb and freely accessible at https://ariaweb.pasteur.fr.

First-Principles Collision Cross Section Measurements of Large Proteins and Protein Complexes

Rotationally averaged collision cross section (CCS) values for a series of proteins and protein complexes ranging in size from 8.6 to 810 kDa are reported. The CCSs were obtained using a native electrospray ionization drift tube ion mobility-Orbitrap mass spectrometer specifically designed to enhance sensitivity while having high-resolution ion mobility and mass capabilities. Periodic focusing (PF)-drift tube (DT)-ion mobility (IM) provides first-principles determination of the CCS of large biomolecules that can then be used as CCS calibrants. The experimental, first-principles CCS values are compared to previously reported experimentally determined and computationally calculated CCS using projected superposition approximation (PSA), the Ion Mobility Projection Approximation Calculation Tool (IMPACT), and Collidoscope. Experimental CCS values are generally in agreement with previously reported CCSs, with values falling within ∼5.5%. In addition, an ion mobility resolution (CCS centroid divided by CCS fwhm) of ∼60 is obtained for pyruvate kinase (MW ∼ 233 kDa); however, ion mobility resolution for bovine serum albumin (MW ∼ 68 kDa) is less than ∼20, which arises from sample impurities and underscores the importance of sample quality. The high resolution afforded by the ion mobility-Orbitrap mass analyzer provides new opportunities to understand the intricate details of protein complexes such as the impact of post-translational modifications (PTMs), stoichiometry, and conformational changes induced by ligand binding.

Solvation and the secondary structure of a proline-containing dipeptide: insights from VCD spectroscopy

In this study we investigate the IR and VCD spectra of the diastereomeric dipeptide Boc-Pro-Phe-(n-propyl) 1 in chloroform-d₁ (CDCl₃) and the strongly hydrogen bonding solvent dimethylsulfoxide-d₆ (DMSO-d₆). From comparison of the experimental spectra, the amide II spectral region is identified as marker signature for the stereochemistry of the dipeptide: the homochiral LL-1 features a (+/-)-pattern in the amide II region of the VCD spectrum, while the amide II signature of the diastereomer LD-1 is inverted. Computational analysis of the IR and VCD spectra of LL-1 reveals that the experimentally observed amide II signature is characteristic for a β_I-turn structure of the peptide. Likewise, the inverted pattern found for LD-1 arises from a β_II-turn structure of the dipeptide. Following a micro-solvation approach, the experimental spectra recorded in DMSO-d₆ are computationally well reproduced by considering only a single solvent molecule in a hydrogen bond with N-H groups. Considering a second solvent molecule, which would lead to a cleavage of intramolecular hydrogen bonds in 1, is found to give a significantly worse match with the experiment. Hence, the detailed computational analysis of the spectra of LL- and LD-1 recorded in DMSO-d₆ confirms that the intramolecular hydrogen bonding pattern, that stabilizes the β-turns and other conformations of LL- and LD-1 in apolar solvents, remains intact. Our findings also show that it is essential to consider solvation explicitly in the analysis of the IR and VCD spectra of dipeptides in strongly hydrogen bonding solvents. As the solute-solvent interactions affect both conformational preferences and spectral signatures, it is also demonstrated that this inclusion of solvent molecules cannot be circumvented by applying fitting procedures to non-solvated structures.

A Practical Perspective on the Roles of Solution NMR Spectroscopy in Drug Discovery

Solution nuclear magnetic resonance (NMR) spectroscopy is a powerful tool to study structures and dynamics of biomolecules under physiological conditions. As there are numerous NMR-derived methods applicable to probe protein–ligand interactions, NMR has been widely utilized in drug discovery, especially in such steps as hit identification and lead optimization. NMR is frequently used to locate ligand-binding sites on a target protein and to determine ligand binding modes. NMR spectroscopy is also a unique tool in fragment-based drug design (FBDD), as it is able to investigate target-ligand interactions with diverse binding affinities. NMR spectroscopy is able to identify fragments that bind weakly to a target, making it valuable for identifying hits targeting undruggable sites. In this review, we summarize the roles of solution NMR spectroscopy in drug discovery. We describe some methods that are used in identifying fragments, understanding the mechanism of action for a ligand, and monitoring the conformational changes of a target induced by ligand binding. A number of studies have proven that ¹⁹F-NMR is very powerful in screening fragments and detecting protein conformational changes. In-cell NMR will also play important roles in drug discovery by elucidating protein-ligand interactions in living cells.

Mesophilic Pyrophosphatase Function at High Temperature: A Molecular Dynamics Simulation Study

The mesophilic inorganic pyrophosphatase from Escherichia coli (EcPPase) retains function at 353 K, the physiological temperature of hyperthermophilic Thermococcus thioreducens, whereas the homolog protein (TtPPase) from this hyperthermophilic organism cannot function at room temperature. To explain this asymmetric behavior, we examined structural and dynamical properties of the two proteins using molecular dynamics simulations. The global flexibility of TtPPase is significantly higher than its mesophilic homolog at all tested temperature/pressure conditions. However, at 353 K, EcPPase reduces its solvent-exposed surface area and increases subunit compaction while maintaining flexibility in its catalytic pocket. In contrast, TtPPase lacks this adaptability and has increased rigidity and reduced protein/water interactions in its catalytic pocket at room temperature, providing a plausible explanation for its inactivity near room temperature.

The Photocatalyzed Thiol-ene reaction: A New Tag to Yield Fast, Selective and reversible Paramagnetic Tagging of Proteins

Paramagnetic restraints have been used in biomolecular NMR for the last three decades to elucidate and refine biomolecular structures, but also to characterize protein-ligand interactions. A common technique to generate such restraints in proteins, which do not naturally contain a (paramagnetic) metal, consists in the attachment to the protein of a lanthanide-binding-tag (LBT). In order to design such LBTs, it is important to consider the efficiency and stability of the conjugation, the geometry of the complex (conformational exchanges and coordination) and the chemical inertness of the ligand. Here we describe a photo-catalyzed thiol-ene reaction for the cysteine-selective paramagnetic tagging of proteins. As a model, we designed an LBT with a vinyl-pyridine moiety which was used to attach our tag to the protein GB1 in fast and irreversible fashion. Our tag T1 yields magnetic susceptibility tensors of significant size with different lanthanides and has been characterized using NMR and relaxometry measurements.

Neighborhood Preference of Amino Acids in Protein Structures and its Applications in Protein Structure Assessment

Amino acids form protein 3D structures in unique manners such that the folded structure is stable and functional under physiological conditions. Non-specific and non-covalent interactions between amino acids exhibit neighborhood preferences. Based on structural information from the protein data bank, a statistical energy function was derived to quantify amino acid neighborhood preferences. The neighborhood of one amino acid is defined by its contacting residues, and the energy function is determined by the neighboring residue types and relative positions. The neighborhood preference of amino acids was exploited to facilitate structural quality assessment, which was implemented in the neighborhood preference program NEPRE. The source codes are available via https://github.com/LiuLab-CSRC/NePre.

Studying biomolecular folding and binding using temperature-jump mass spectrometry

Characterizing folding and complex formation of biomolecules provides a view into their thermodynamics, kinetics and folding pathways. Deciphering kinetic intermediates is particularly important because they can often be targeted by drugs. The key advantage of native mass spectrometry over conventional methods that monitor a single observable is its ability to identify and quantify coexisting species. Here, we show the design of a temperature-jump electrospray source for mass spectrometry that allows one to perform fast kinetics experiments (0.16-32 s) at different temperatures (10-90 °C). The setup allows recording of both folding and unfolding kinetics by using temperature jumps from high to low, and low to high, temperatures. Six biological systems, ranging from peptides to proteins to DNA complexes, exemplify the use of this device. Using temperature-dependent experiments, the folding and unfolding of a DNA triplex are studied, providing detailed information on its thermodynamics and kinetics.

Non-Additive Effects of Binding Site Mutations in Calmodulin

Despite decades of research on ion-sensing proteins, gaps persist in the understanding of ion binding affinity and selectivity even in well-studied proteins such as calmodulin. Site-directed mutagenesis is a powerful and popular tool for addressing outstanding questions about biological ion binding and is employed to selectively deactivate binding sites and insert chromophores at advantageous positions within ion binding structures. However, even apparently nonperturbative mutations can distort the binding dynamics they are employed to measure. We use Fourier transform infrared (FTIR) and ultrafast two-dimensional infrared (2D IR) spectroscopy of the carboxylate asymmetric stretching mode in calmodulin as a mutation- and label-independent probe of the conformational perturbations induced in calmodulin's binding sites by two classes of mutation, tryptophan insertion and carboxylate side-chain deletion, commonly used to study ion binding in proteins. Our results show that these mutations not only affect ion binding but also induce changes in calmodulin's conformational landscape along coordinates not probed by vibrational spectroscopy, remaining invisible without additional perturbation of binding site structure. Comparison of FTIR line shapes with 2D IR diagonal slices provides a clear example of how nonlinear spectroscopy produces well-resolved line shapes, refining otherwise featureless spectral envelopes into more informative vibrational spectra of proteins.

Experimental and theoretical tools to elucidate the binding mechanisms of solid-binding peptides

The interactions between biomolecules and solid surfaces play an important role in designing new materials and applications which mimic nature. Recently, solid-binding peptides (SBPs) have emerged as potential molecular building blocks in nanobiotechnology. SBPs exhibit high selectivity and binding affinity towards a wide range of inorganic and organic materials. Although these peptides have been widely used in various applications, there is a need to understand the interaction mechanism between the peptide and its material substrate, which is challenging both experimentally and theoretically. This review describes the main characterisation techniques currently available to study SBP-surface interactions and their contribution to gain a better insight for designing new peptides for tailored binding.

Focusing on “the important” through targeted NMR experiments: an example of selective13C–12C bond detection in complex mixtures

Here, a targeted NMR experiment is introduced which selectively detects the formation of¹³C–¹²C bonds in mixtures.