Protein Structure Determination Research Articles

Discrimination of leucine and isoleucine via fragmentation by electromagnetic field.

We conduct comparative numerical studies of the effects of electric dipole field and electromagnetic radiation field on the amino acids leucine and isoleucine. Since they are structural isomers, distinguishing them by mass is a non-trivial task, while determination of protein structure can be crucial on many occasions. We emphasize the influence of the magnetic field of radiation by utilizing a modified basis sets with correction coefficients to the [Formula: see text] and [Formula: see text] orbitals following the Anisotropic Gaussian Type Orbitals method. Studying the electric potential of the isomers in dipole electric or electromagnetic fields proves that the different layout of leucine vs isoleucine is the main reason why some fragments could not be formed during chemical bond cleavage. Comparison of the chemical structure of the fragments created due to the decomposition of the isomers in the dipole electric or electromagnetic fields shows that their decomposition products are different. These findings can be used also for discrimination between the two isoleucine conformers, for which the cleavage starts at different values of the dipole electric field strength, as well as the products of the decomposition reaction are not identical. Our numerical calculations of the fragmentation outcomes, taking into account the magnetic field effects, can serve as a guidance for discrimination between the isomers/conformers. We applied the Becke's three-parameter hybrid functional approach with non-local correlation by Lee, Yang, and Parr ([Formula: see text]), together with the [Formula: see text] basis set as it is implemented in the GAUSSIAN09 quantum chemistry package in order to obtain the most stable conformers of leucine and isoleucine. We used the options provided by GAUSSIAN09 to add finite external field in order to perform the calculations of leucine and isoleucine in the electric dipole and electromagnetic fields. The Anisotropic Gaussian Type Orbitals method was used to obtain the correction coefficients which modify the original [Formula: see text] basis set in order to account for the effects of magnetic field of radiation. Results were visualized and the electrical potentials analyzed by the Molden visualization program.

LipIDens: simulation assisted interpretation of lipid densities in cryo-EM structures of membrane proteins

Cryo-electron microscopy (cryo-EM) enables the determination of membrane protein structures in native-like environments. Characterising how membrane proteins interact with the surrounding membrane lipid environment is assisted by resolution of lipid-like densities visible in cryo-EM maps. Nevertheless, establishing the molecular identity of putative lipid and/or detergent densities remains challenging. Here we present LipIDens, a pipeline for molecular dynamics (MD) simulation-assisted interpretation of lipid and lipid-like densities in cryo-EM structures. The pipeline integrates the implementation and analysis of multi-scale MD simulations for identification, ranking and refinement of lipid binding poses which superpose onto cryo-EM map densities. Thus, LipIDens enables direct integration of experimental and computational structural approaches to facilitate the interpretation of lipid-like cryo-EM densities and to reveal the molecular identities of protein-lipid interactions within a bilayer environment. We demonstrate this by application of our open-source LipIDens code to ten diverse membrane protein structures which exhibit lipid-like densities.

Rapidly determining the 3D structure of proteins by surface-enhanced Raman spectroscopy.

Despite great advances in protein structure analysis, label-free and ultrasensitive methods to obtain the natural and dynamic three-dimensional (3D) structures are still urgently needed. Surface-enhanced Raman spectroscopy (SERS) can be a good candidate, whereas the complexity originated from the interactions between the protein and the gradient surface electric field makes it extremely challenging to determine the protein structure. Here, we propose a deciphering strategy for accurate determination of 3D protein structure from experimental SERS spectra in seconds by simply summing SERS spectra of isolated amino acids in electric fields of different strength with their orientations in protein. The 3D protein structure can be reconstructed by comparing the experimental spectra obtained in a well-defined gap-mode SERS configuration with the simulated spectra. The gradient electric field endows SERS with a unique advantage to section biomolecules with atomic precision, which makes SERS a competent tool for monitoring biomolecular events under physiological conditions.

Exploring the Complexity of Protein Structure Determination Through X-ray Diffraction

The determination of a protein structure by using X-ray diffraction encompasses a series of sequential steps (including gene identification and cloning, protein expression and purification, crystallization, phasing model building, refinement, and validation), which need the application of several methodologies derived from molecular biology, bioinformatics, and physical sciences. This article thoroughly examines the complicated procedure of elucidating protein structures within plant biology, using X-ray diffraction as the primary methodology. Commencing with the gene identification process and progressing toward crystallography, this article explores the many obstacles and achievements in acquiring diffraction pictures and their subsequent conversion into electron density maps. The ensuing phases of model construction, refinement, and structural validation are thoroughly examined, providing insight into the inherent complexity associated with each stage. The paper also discusses the critical component of understanding the resultant model and scrutinizing its biological significance. By comprehensively examining these stages, this article presents a nuanced comprehension of the intricate procedure in ascertaining protein structures within plant biology. It offers valuable insights into the obstacles encountered and the biological importance of the acquired structural data.

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

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

Solid-state NMR structure determination of a membrane protein in E. coli cellular inner membrane.

Structure determination of membrane proteins in native cellular membranes is critical to precisely reveal their structures in physiological conditions. However, it remains challenging for solid-state nuclear magnetic resonance (ssNMR) due to the low sensitivity and high complexity of ssNMR spectra of cellular membranes. Here, we present the structure determination of aquaporin Z (AqpZ) by ssNMR in Escherichia coli inner membranes. To enhance the signal sensitivity of AqpZ, we optimized protein overexpression and removed outer membrane components. To suppress the interference of background proteins, we used a "dual-media" expression approach and antibiotic treatment. Using 1017 distance restraints obtained from two-dimensional 13C-13C spectra based on the complete chemical shift assignments, the 1.7-Å ssNMR structure of AqpZ is determined in E. coli inner membranes. This cellular ssNMR structure determination paves the way for analyzing the atomic structural details for membrane proteins in native cellular membranes.

Molecular replacement for small-molecule crystal structure determination from X-ray and electron diffraction data with reduced resolution.

The resolution of 3D electron diffraction (ED) data of small-molecule crystals is often relatively poor, due to either electron-beam radiation damage during data collection or poor crystallinity of the material. Direct methods, used as standard for crystal structure determination, are not applicable when the data resolution falls below the commonly accepted limit of 1.2 Å. Therefore an evaluation was carried out of the performance of molecular replacement (MR) procedures, regularly used for protein structure determination, for structure analysis of small-molecule crystal structures from 3D ED data. In the course of this study, two crystal structures of Bi-3812, a highly potent inhibitor of the oncogenic transcription factor BCL6, were determined: the structure of α-Bi-3812 was determined from single-crystal X-ray data, the structure of β-Bi-3812 from 3D ED data, using direct methods in both cases. These data were subsequently used for MR with different data types, varying the data resolution limit (1, 1.5 and 2 Å) and by using search models consisting of connected or disconnected fragments of BI-3812. MR was successful with 3D ED data at 2 Å resolution using a search model that represented 74% of the complete molecule.

Unrealized targets in the discovery of antibiotics for Gram-negative bacterial infections.

Advances in areas that include genomics, systems biology, protein structure determination and artificial intelligence provide new opportunities for target-based antibacterial drug discovery. The selection of a 'good' new target for direct-acting antibacterial compounds is the first decision, for which multiple criteria must be explored, integrated and re-evaluated as drug discovery programmes progress. Criteria include essentiality of the target for bacterial survival, its conservation across different strains of the same species, bacterial species and growth conditions (which determines the spectrum of activity of a potential antibiotic) and the level of homology with human genes (which influences the potential for selective inhibition). Additionally, a bacterial target should have the potential to bind to drug-like molecules, and its subcellular location will govern the need for inhibitors to penetrate one or two bacterial membranes, which is a key challenge in targeting Gram-negative bacteria. The risk of the emergence of target-based drug resistance for drugs with single targets also requires consideration. This Review describes promising but as-yet-unrealized targets for antibacterial drugs against Gram-negative bacteria and examples of cognate inhibitors, and highlights lessons learned from past drug discovery programmes.

Determination of the Crystal Structure of the Cell Wall-Anchored Proteins and Pilins.

Surface proteins and pili (or pilus) anchored on the Gram-positive bacterial cell wall play a vital role in adhesion, colonization, biofilm formation, and immunomodulation. The pilus consists of building blocks called pilins or pilus subunits. The surface proteins and pilins share some common sequences and structural features. They contain an N-terminal signal sequence and the C-terminal cell wall sorting region, enabling their transportation across the membrane and covalent attachment to the bacterial cell wall, respectively. The transpeptidase enzymes called sortases facilitate the covalent links between the pilins during the pilus assembly and between surface proteins or basal subunits of pili and peptidoglycan-bridge during the cell wall anchoring. Thus, elucidating three-dimensional structures for the surface proteins and pilins at the atomic level is essential for understanding the mechanism of adhesion, pilus assembly, and host interaction. This chapter aims to provide a general protocol for crystal structure determination of surface proteins and pilins anchored on the Gram-positive bacterial cell wall and substrates for sortases. The protocol involves the production of recombinant protein, crystallization, and structure determination by X-ray crystallography technique.

Structural Determination of Glucosyltransferase C by Cryo-Electron Microscopy.

Biofilm formation is a critical factor in the development of cariogenic virulence of Streptococcus mutans. S. mutans has evolved a concerted mechanism to synthesize a biofilm matrix from dietary sugars by a family of glucosyltransferases (Gtfs). Three Gtfs, GtfB, C, and D utilize sucrose to form a sticky polymer consisting of insoluble and soluble glucans, a biofilm foundation. Each Gtf possesses two distinct domains, an N-terminal enzyme catalytic domain and a C-terminal glucan binding domain. X-ray crystallographic studies have determined a three-dimensional structure of the catalytic domain of GtfC, however, the structure of the C-terminal domain and the overall structure of Gtfs are unknown. Here, we provided a protocol that will guide us to solve Gtf structures using cryo-electron microscopy (cryo-EM). Cryo-EM and X-ray crystallography are two widely used techniques for determining protein structures, and both methods have their own advantages and limitations. Additionally, we also predicted the full-length GtfC structural using AlphaFold2. Overall, the combination of AlphaFold 2 with experimental approaches offers a powerful and synergistic strategy for protein structure determination, accelerating the pace of scientific discovery and enabling new insights into the molecular basis that govern the biosynthetic activities of Gtfs, which may inform the design of more effective treatments for cariogenic biofilms and associated diseases.

Palmitoylation of the hemagglutinin of influenza B virus by ER-localized DHHC enzymes 1, 2, 4, and 6 is required for efficient virus replication.

Influenza viruses are a public health concern since they cause seasonal outbreaks and occasionally pandemics. Our study investigates the importance of a protein modification called "palmitoylation" in the replication of influenza B virus. Palmitoylation involves attaching fatty acids to the viral protein hemagglutinin and has previously been studied for influenza A virus. We found that this modification is important for the influenza B virus to replicate, as mutating the sites where palmitate is attached prevented the virus from generating viable particles. Our experiments also showed that this modification occurs in the endoplasmic reticulum. We identified the specific enzymes responsible for this modification, which are different from those involved in palmitoylation of HA of influenza A virus. Overall, our research illuminates the similarities and differences in fatty acid attachment to HA of influenza A and B viruses and identifies the responsible enzymes, which might be promising targets for anti-viral therapy.

Analyzing the aromatic-aromatic interactions in proteins: A2ID 2.0

The Aromatic-Aromatic Interactions Database (A2ID) is a comprehensive repository dedicated to documenting aromatic-aromatic (π-π) networks observed in experimentally determined protein structures. The first version of A2ID was reported in 2011 [Int J Biol Macromol, 2011, 48, 540]. It has undergone a series of significant updates, leading to its current version, which focuses on the identification and analysis of 3,444,619 π-π networks from proteins. The geometrical parameters such as centroid-centroid distances (r) and interplanar angles (ϕ) were used to identify and characterize π-π networks. It was observed that among the 84,500 proteins with at least one aromatic π-π network, about 92.50 % of the instances are found to be either 2π (77.34 %) or 3π (15.23 %) networks. The analysis of interacting amino acid pairs in 2π networks indicated a dominance of PHE residues followed by TYR. The updated version of A2ID incorporates analysis of π-π networks based on SCOP2 and ECOD classifiers, in addition to the existing SCOP, CATH, and EC classifications. This expanded scope allows researchers to explore the characteristics and functional implications of π-π networks in protein structures from multiple perspectives. The current version of A2ID along with its extensive dataset and detailed geometric information is publicly accessible using https://acds.neist.res.in/a2idv2.

Analyzing the cation-aromatic interactions in proteins: Cation-aromatic database V2.0.

The cation-aromatic database (CAD) is a comprehensive repository of cation-aromatic motifs found in experimentally determined protein structures, first reported in 2007 [Proteins, 2007, 67, 1179]. The present article is an update of CAD that contains information of approximately 27.26 million cation-aromatic motifs. CAD uses three distance parameters (r, d1, and d2) to determine the position of the cation relative to the centroid of the aromatic residue and classifies the motifs as cation-π or cation-σ interactions. As of June 2023, about 193 936 protein structures were retrieved from Protein Data Bank, and this resulted in the identification of an impressive number of 27 255 817 cation-aromatic motifs. Among these motifs, spherical motifs constituted 94.09%, while cylindrical motifs made up the remaining 5.91%. When considering the interaction of metal ions with aromatic residues, 965 564 motifs are identified. Remarkably, 82.08% of these motifs involved the binding of metal ions to the amino acid HIS. Moreover, the analysis of binding preferences between cations and aromatic residues revealed that the HIS-HIS, PHE-ARG, and TRP-ARG pairs exhibited a preferential geometry. The motif pair HIS-HIS was the most prevalent, accounting for 19.87% of the total, closely followed by TYR-LYS at 10.17%. Conversely, the motif pair TRP-HIS had the lowest occurrence, representing only 4.20% of the total. The data generated help in revealing the characteristics and biological functions of cation-aromatic interactions in biological molecules. The updated version of CAD (Cation-Aromatic Database V2.0) can be accessed at https://acds.neist.res.in/cadv2.

Recent Advances and Best Practices for Cryo-EM Analysis for Protein Structure Determination.

ARTICLES DISCUSSED: de Martin Garrido, N., Ramlaul, K., Aylett, C. H. S. Preparation of sample support films in transmission electron microscopy using a support floatation block. Journal of Visualized Experiments. (170), doi:10.3791/62321 (2021). Klebl, D. P., Sobott, F., White, H. D., Muench, S. P. Fast grid preparation for time-resolved cryo-electron microscopy. Journal of Visualized Experiments. (177), doi:10.3791/62199 (2021). Budell, W. C., Allegri, L., Dandey, V., Potter, C. S., Carragher, B. Cryo-Electron microscopic grid preparation for time-resolved studies using a novel robotic system, Spotiton. Journal of Visualized Experiments. (168), doi:10.3791/62271 (2021). Nguyen, H. P. M., McGuire, K. L., Cook, B. D., Herzik, M. A., Jr. Manual blot-and-plunge freezing of biological specimens for single-particle cryogenic electron microscopy. Journal of Visualized Experiments. (180), doi:10.3791/62765 (2022). Martynowycz, M. W., Gonen, T. Microcrystal electron diffraction of small molecules. Journal of Visualized Experiments. (169), doi:10.3791/62313 (2021). Bisson, C., Hecksel, C. W., Gilchrist, J. B., Fleck, R. A. Preparing lamellae from vitreous biological samples using a dual-beam scanning electron microscope for cryo-electron tomography. Journal of Visualized Experiments. (174), doi:10.3791/62350 (2021). Wypych, D., Kierecki, D., Golebiowski, F. M., Rohou, A. gP2S, an information management system for CryoEM experiments. Journal of Visualized Experiments. (172), doi:10.3791/62377 (2021).

SARS-CoV-2 proteins structural studies using synchrotron radiation.

In the process of the development of structural biology, both the size and the complexity of the determined macromolecular structures have grown significantly. As a result, the range of application areas for the results of structural studies of biological macromolecules has expanded. Significant progress in the development of structural biology methods has been largely achieved through the use of synchrotron radiation. Modern sources of synchrotron radiation allow to conduct high-performance structural studies with high temporal and spatial resolution. Thus, modern techniques make it possible to obtain not only static structures, but also to study dynamic processes, which play a key role in understanding biological mechanisms. One of the key directions in the development of structural research is the drug design based on the structures of biomolecules. Synchrotron radiation offers insights into the three-dimensional time-resolved structure of individual viral proteins and their complexes at atomic resolution. The rapid and accurate determination of protein structures is crucial for understanding viral pathogenicity and designing targeted therapeutics. Through the application of experimental techniques, including X-ray crystallography and small-angle X-ray scattering (SAXS), it is possible to elucidate the structural details of SARS-CoV-2 virion containing 4 structural, 16 nonstructural proteins (nsp), and several accessory proteins. The most studied potential targets for vaccines and drugs are the structural spike (S) protein, which is responsible for entering the host cell, as well as nonstructural proteins essential for replication and transcription, such as main protease (Mpro), papain-like protease (PLpro), and RNA-dependent RNA polymerase (RdRp). This article provides a brief overview of structural analysis techniques, with focus on synchrotron radiation-based methods applied to the analysis of SARS-CoV-2 proteins.

Se-MAG Is a Convenient Additive for Experimental Phasing and Structure Determination of Membrane Proteins Crystallised by the Lipid Cubic Phase (In Meso) Method

Both intensity and phase information are needed for structure determination by macromolecular X-ray crystallography. The diffraction experiment provides intensities. Phases must be accessed indirectly by molecular replacement, or by experimental phasing. A popular method for crystallising membrane proteins employs a lipid cubic mesophase (the in meso method). Monoolein is the most popular lipid for in meso crystallisation. Invariably, the lipid co-crystallises with the protein recapitulating the biomembrane from whence it came. We reasoned that such a lipid bearing a heavy atom could be used for experimental phasing. In this study, we replaced half the monoolein in the mesophase with a seleno-labelled analogue (Se-MAG), which has a selenium atom in the fatty acyl chain of the lipid. The lipid mixture formed the cubic mesophase and grew crystals by the in meso method of the alginate transporter, AlgE, and the lipoprotein N-acyltransferase, Lnt. Se-MAGs co-crystallised with both proteins and were used to obtain phases for high-resolution structure determination by the selenium single-wavelength anomalous diffraction method. The use of such a mixed lipid system may prove to be a general strategy for the experimental phasing part of crystallographic structure determination of membrane proteins that crystallise via the in meso method.

Starting at Go: Protein structure prediction succumbs to machine learning

This year’s Albert Lasker Basic Medical Research Award recognizes the invention of AlphaFold, a revolutionary advance in the history of protein research which for the first time offers the practical ability to accurately predict the three-dimensional arrangement of amino acids in the vast majority of proteins on a genomic scale on the basis of sequence alone [J. Jumper et al., Nature 596, 583–589 (2021) and K. Tunyasuvunakool et al., Nature 596, 590–596 (2021)]. This extraordinary achievement by Demis Hassabis and John Jumper and their coworkers at Google’s DeepMind and other collaborators was built on decades of experimental protein structure determination (structural biology) as well as the gradual development of multiple strategies incorporating biologically inspired statistical approaches. But when Jumper and Hassabis added a brew of innovative neural network-based machine learning approaches to the mix, the results were explosive. Realizing the half-century-old dream of predicting protein structure has already accelerated the pace and creativity of many areas of Chemistry, Biology, and Medicine.

Histone acetylation and deacetylation – Mechanistic insights from structural biology

Histones are subject to a diverse array of post-translational modifications. Among them, lysine acetylation is not only the most pervasive and dynamic modification but also highly consequential for regulating gene transcription. Although enzymes responsible for the addition and removal of acetyl groups were discovered almost 30 years ago, high-resolution structures of the enzymes in the context of their native complexes are only now beginning to become available, thanks to revolutionary technologies in protein structure determination and prediction. Here, we will review our current understanding of the molecular mechanisms of acetylation and deacetylation engendered by chromatin-modifying complexes, compare and contrast shared features, and discuss some of the pressing questions for future studies.

`Cryo-EM': electron cryomicroscopy, cryo electron microscopy or something else?

Structural biology continues to benefit from an expanding toolkit, which is helping to gain unprecedented insight into the assembly and organization of multi-protein machineries, enzyme mechanisms and ligand/inhibitor binding. During the last ten years, cryoEM has become widely available and has provided a major boost to structure determination of membrane proteins and large multi-protein complexes. Many of the structures have now been made available at resolutions around 2 Å, where fundamental questions regarding enzyme mechanisms can be addressed. Over the years, the abbreviation cryoEM has been understood to stand for different things. We wish the wider community to engage and clarify the definition of cryoEM so that the expanding literature involving cryoEM is unified.

Characterization of two tripartite motif-containing genes from Asian Seabass Lates calcarifer and their expression in response to virus infection and microbial molecular motifs.

We identified two tripartite motif (TRIM) genes, LcTRIM21 and LcTRIM39, from the Asian Seabass Lates calcarifer, and examined their responses to experimental betanodavirus infection and stimulation with microbial pathogen-associated molecular patterns. Genes encoding LcTRIM21 and LcTRIM39 were identified, cloned, and sequenced from the Asian Seabass. We analyzed the sequence using a variety of bioinformatics tools to determine protein structure, localization, and establish a phylogenetic tree. By using quantitative real-time PCR, we analyzed expression profiles of the LcTRIM21 and LcTRIM39 genes in response to betanodavirus challenge as well as molecular pathogen-associated molecular patterns like poly(I:C) and Zymosan A. The tissue distribution pattern of these genes was also examined in healthy animals. Asian Seabass homologues of the TRIM gene, LcTRIM21 and LcTRIM39, were cloned, both encoding proteins with 547 amino acids. LcTRIM21 is predicted to have an isoelectric point of 6.32 and a molecular mass of 62.11 kilodaltons, while LcTRIM39 has an isoelectric point of 5.57 and a molecular mass of 62.11 kilodaltons. LcTRIM21 and LcTRIM39 homologues were predicted to be localized in cytoplasm by in silico protein localization. Structurally, both proteins contain an N-terminal really interesting new gene (RING) zinc-finger domain, B-box domain, coiled-coil domain and C-terminal PRY/SPRY domain. Most tissues and organs examined showed constitutive expression of LcTRIM21 and LcTRIM39. Upon poly(I:C) challenge or red-spotted grouper nervous necrosis virus infection, LcTRIM21 and LcTRIM39 mRNA expression was significantly upregulated, suggesting that they may play a critical antiviral role against fish viruses. LcTRIM21 and LcTRIM39 expression were also upregulated by administration of the glucan Zymosan A. The TRIM-containing gene is an E3 ubiquitin ligase that exhibits antiviral activity by targeting viral proteins via proteasome-mediated ubiquitination. TRIM proteins can be explored for the discovery of antivirals and strategies to combat diseases like viral nervous necrosis, that threaten seabass aquaculture.