Protein Structure Determination Research Articles

Advances in Peptide/Protein Structure Prediction Tools and their Relevance for Structural Biology in the Last Decade

Abstract: Peptides and proteins are involved in several biological processes at a molecular level. In this context, three-dimensional structure characterization and determination of peptides and proteins have helped researchers unravel the chemical and biological role of these macromolecules. Over 50 years, peptide and protein structures have been determined by experimental methods, including nuclear magnetic resonance (NMR), X-ray crystallography, and cryo-electron microscopy (cryo-EM). Therefore, an increasing number of atomic coordinates for peptides and proteins have been deposited in public databases, thus assisting the development of computational tools for predicting unknown 3D structures. In the last decade, a race for innovative methods has arisen in computational sciences, including more complex biological activity and structure prediction algorithms. As a result, peptide/protein theoretical models have achieved a new level of structure prediction accuracy compared with experimentally determined structures. Machine learning and deep learning approaches, for instance, incorporate fundamental aspects of peptide/protein geometry and include physical/biological knowledge about these macromolecules' experimental structures to build more precise computational models. Additionally, computational strategies have helped structural biology, including comparative, threading, and ab initio modeling and, more recently, prediction tools based on machine learning and deep learning. Bearing this in mind, here we provide a retrospective of protein and peptide structure prediction tools, highlighting their advances and obstacles and how they have assisted researchers in answering crucial biological questions.

Identification of host receptors for viral entry and beyond: a perspective from the spike of SARS-CoV-2.

Identification of the interaction between the host membrane receptor and viral receptor-binding domain (RBD) represents a crucial step for understanding viral pathophysiology and for developing drugs against pathogenic viruses. While all membrane receptors and carbohydrate chains could potentially be used as receptors for viruses, prioritized searches focus typically on membrane receptors that are known to have been used by the relatives of the pathogenic virus, e.g., ACE2 used as a receptor for SARS-CoV is a prioritized candidate receptor for SARS-CoV-2. An ideal receptor protein from a viral perspective is one that is highly expressed in epithelial cell surface of mammalian respiratory or digestive tracts, strongly conserved in evolution so many mammalian species can serve as potential hosts, and functionally important so that its expression cannot be readily downregulated by the host in response to the infection. Experimental confirmation of host receptors includes (1) infection studies with cell cultures/tissues/organs with or without candidate receptor expression, (2) experimental determination of protein structure of the complex between the putative viral RDB and the candidate host receptor, and (3) experiments with mutant candidate receptor or homologues of the candidate receptor in other species. Successful identification of the host receptor opens the door for mechanism-based development of candidate drugs and vaccines and facilitates the inference of what other animal species are vulnerable to the viral pathogen. I illustrate these approaches with research on identification of the receptor and co-factors for SARS-CoV-2.

GradPose: a very fast and memory-efficient gradient descent-based tool for superimposing millions of protein structures from computational simulations.

Computational simulations like molecular dynamics and docking are providing crucial insights into the dynamics and interaction conformations of proteins, complementing experimental methods for determining protein structures. These methods often generate millions of protein conformations, necessitating highly efficient structure comparison and clustering methods to analyze the results. In this article, we introduce GradPose, a fast and memory-efficient structural superimposition tool for models generated by these large-scale simulations. GradPose uses gradient descent to optimally superimpose structures by optimizing rotation quaternions and can handle insertions and deletions compared to the reference structure. It is capable of superimposing thousands to millions of protein structures on standard hardware and utilizes multiple CPU cores and, if available, CUDA acceleration to further decrease superimposition time. Our results indicate that GradPose generally outperforms traditional methods, with a speed improvement of 2-65 times and memory requirement reduction of 1.7-48 times, with larger protein structures benefiting the most. We observed that traditional methods outperformed GradPose only with very small proteins consisting of ∼20 residues. The prerequisite of GradPose is that residue-residue correspondence is predetermined. With GradPose, we aim to provide a computationally efficient solution to the challenge of efficiently handling the demand for structural alignment in the computational simulation field. Source code is freely available at https://github.com/X-lab-3D/GradPose; doi:10.5281/zenodo.7671922.

Improving protein crystal quality using deep eutectic solvents

Protein crystallization is an essentially important process for its valuable applications in molecular structure determination of proteins, the study of biomolecular interaction mechanism, research and development of special functional crystal materials, theoretical study of crystallization mechanism, industrial production of proteins, and so on. Improving the quality of protein crystals is desirable research because it can provide high-quality samples or products for these studies and applications. Here we report that the utilization of DESs as additives in protein crystallization can significantly affect the crystallization process and effectively improve the crystal quality. We synthesized 9 types of DESs, studied their physicochemical properties, and selected 3 DESs suitable as additives for protein crystallization. Using three model proteins (lysozyme, thaumatin, and proteinase K), we confirmed that DESs can significantly affect the protein crystallization process. Crystals obtained at appropriate concentrations of DESs have higher quality, higher diffraction resolution, and better diffraction data collection. A comparison of the 3D structure of protein molecules showed that the addition of DESs did not affect the molecular structure of the proteins. These results proved that the presence of DESs during protein crystallization can help to improve crystal quality without affecting the structure of proteins, showing that DESs can be employed as a novel class of additives for protein crystallization.

Identification and characterization of RNA polymerase II (RNAP) C-Terminal domain phosphatase-like 3 (SlCPL3) in tomato under biotic stress.

Bacterial diseases are a huge threat to the production of tomatoes. During infection intervals, pathogens affect biochemical, oxidant and molecular properties of tomato. Therefore, it is necessary to study the antioxidant enzymes, oxidation state and genes involved during bacterial infection in tomato. Different bioinformatic analyses were performed to conduct homology, gene promoter analysis and determined protein structure. Antioxidant, MDA and H2O2 response was measured in Falcon, Rio grande and Sazlica tomato cultivars. In this study, RNA Polymerase II (RNAP) C-Terminal Domain Phosphatase-like 3 (SlCPL-3) gene was identified and characterized. It contained 11 exons, and encoded for two protein domains i.e., CPDCs and BRCT. SOPMA and Phyre2, online bioinformatic tools were used to predict secondary structure. For the identification of protein pockets CASTp web-based tool was used. Netphos and Pondr was used for prediction of phosphorylation sites and protein disordered regions. Promoter analysis revealed that the SlCPL-3 is involved in defense-related mechanisms. We further amplified two different regions of SlCPL-3 and sequenced them. It showed homology respective to the reference tomato genome. Our results showed that SlCPL-3 gene was triggered during bacterial stress. SlCPL-3 expression was upregulated in response to bacterial stress during different time intervals. Rio grande showed a high level of SICPL-3 gene expression after 72 hpi. Biochemical and gene expression analysis showed that under biotic stress Rio grande cultivar is more sensitive to Pst DC 3000 bacteria. This study lays a solid foundation for the functional characterization of SlCPL-3 gene in tomato cultivars. All these findings would be beneficial for further analysis of SlCPL-3 gene and may be helpful for the development of resilient tomato cultivars.

Lipid nanodiscs as a template for high-resolution cryo-EM structures of peripheral membrane proteins

Peripheral membrane proteins are ubiquitous throughout cell biology and are required for a variety of cellular processes such as signal transduction, membrane trafficking, and autophagy. Transient binding to the membrane has a profound impact on protein function, serving to induce conformational changes and alter biochemical and biophysical parameters by increasing the local concentration of factors and restricting diffusion to two dimensions. Despite the centrality of the membrane in serving as a template for cell biology, there are few reported high-resolution structures of peripheral membrane proteins bound to the membrane. We analyzed the utility of lipid nanodiscs to serve as a template for cryo-EM analysis of peripheral membrane proteins. We tested a variety of nanodiscs and we report a 3.3 Å structure of the AP2 clathrin adaptor complex bound to a 17-nm nanodisc, with sufficient resolution to visualize a bound lipid head group. Our data demonstrate that lipid nanodiscs are amenable to high-resolution structure determination of peripheral membrane proteins and provide a framework for extending this analysis to other systems.

Identification of a covert evolutionary pathway between two protein folds

Although homologous protein sequences are expected to adopt similar structures, some amino acid substitutions can interconvert α-helices and β-sheets. Such fold switching may have occurred over evolutionary history, but supporting evidence has been limited by the: (1) abundance and diversity of sequenced genes, (2) quantity of experimentally determined protein structures, and (3) assumptions underlying the statistical methods used to infer homology. Here, we overcome these barriers by applying multiple statistical methods to a family of ~600,000 bacterial response regulator proteins. We find that their homologous DNA-binding subunits assume divergent structures: helix-turn-helix versus α-helix + β-sheet (winged helix). Phylogenetic analyses, ancestral sequence reconstruction, and AlphaFold2 models indicate that amino acid substitutions facilitated a switch from helix-turn-helix into winged helix. This structural transformation likely expanded DNA-binding specificity. Our approach uncovers an evolutionary pathway between two protein folds and provides a methodology to identify secondary structure switching in other protein families.

True Origin of Amide I Shifts Observed in Protein Spectra Obtained with Sum Frequency Generation Spectroscopy.

Accurate determination of protein structure at interfaces is critical for understanding protein interactions, which is directly relevant to a molecular-level understanding of interfacial proteins in biology and medicine. Vibrational sum frequency generation (VSFG) spectroscopy is often used for probing the protein amide I mode, which reports protein structures at interfaces. Observed peak shifts are attributed to conformational changes and often form the foundation of hypotheses explaining protein working mechanisms. Here, we investigate structurally diverse proteins using conventional and heterodyne-detected VSFG (HD-VSFG) spectroscopy as a function of solution pH. We reveal that blue-shifts of the amide I peak observed in conventional VSFG spectra upon lowering the pH are governed by the drastic change of the nonresonant contribution. Our results highlight that connecting changes in conventional VSFG spectra to conformational changes of interfacial proteins can be arbitrary, and that HD-VSFG measurements are required to draw unambiguous conclusions about structural changes in biomolecules.

Fast and accurate protein intrinsic disorder prediction by using a pretrained language model.

Determining intrinsically disordered regions of proteins is essential for elucidating protein biological functions and the mechanisms of their associated diseases. As the gap between the number of experimentally determined protein structures and the number of protein sequences continues to grow exponentially, there is a need for developing an accurate and computationally efficient disorder predictor. However, current single-sequence-based methods are of low accuracy, while evolutionary profile-based methods are computationally intensive. Here, we proposed a fast and accurate protein disorder predictor LMDisorder that employed embedding generated by unsupervised pretrained language models as features. We showed that LMDisorder performs best in all single-sequence-based methods and is comparable or better than another language-model-based technique in four independent test sets, respectively. Furthermore, LMDisorder showed equivalent or even better performance than the state-of-the-art profile-based technique SPOT-Disorder2. In addition, the high computation efficiency of LMDisorder enabled proteome-scale analysis of human, showing that proteins with high predicted disorder content were associated with specific biological functions. The datasets, the source codes, and the trained model are available at https://github.com/biomed-AI/LMDisorder.

Insulin purification-Innovation continuum via synthesis of fundamentals, technology, and modeling.

Advancement in all disciplines (art, science, education, and engineering) requires a careful balance of disruption and advancement of classical techniques. Often technologies are created with a limited understanding of fundamental principles and are prematurely abandoned. Over time, knowledge improves, new opportunities are identified, and technology is reassessed in a different light leading to a renaissance. Recovery of biological products is currently experiencing such a renaissance. Crystallization is one example of an elegant and ancient technology that has been applied in many fields and was employed to purify insulins from naturally occurring sources. Crystallization can also be utilized to determine protein structures. However, a multitude of parameters can impact protein crystallization and the "hit rate" for identifying protein crystals is relatively low, so much so that the development of a crystallization process is often viewed as a combination of art and science even today. Supplying the worldwide requirement for insulin (and associated variants) requires significant advances in process intensification to support scale of production and to minimize the overall cost to enable broader access. Expanding beyond insulin, the increasing complexity and diversity of biologics agents challenge the current purification methodologies. To harness the full potential of biologics, there is a need to fully explore a broader range of purification technologies, including nonchromatographic approaches. This impetus requires one to challenge and revisit the classical techniques including crystallization, chromatography, and filtration from a different vantage point and with a new set of tools, including molecular modeling. Fortunately, computational biophysics tools now exist to provide insights into mechanisms of protein/ligand interactions and molecular assembly processes (including crystallization) that can be used to support de novo process development. For example, specific regions or motifs of insulins and ligands can be identified and used as targets to support crystallization or purification development. Although the modeling tools have been developed and validated for insulin systems, the same tools can be applied to more complex modalities and to other areas including formulation, where the issue of aggregation and concentration-dependent oligomerization could be mechanistically modeled. This paper will illustrate a case study juxtaposing historical approaches to insulin downstream processes to a recent production process highlighting the application and evolution of technologies. Insulin production from Escherichia coli via inclusion bodies is an elegant example since it incorporates virtually all the unit operations associated with protein production-recovery of cells, lysis, solubilization, refolding, purification, and crystallization. The case study will include an example of an innovative application of existing membrane technology to combine three-unit operations into one, significantly reducing solids handling and buffer consumption. Ironically, a new separations technology was developed over the course of the case study that could further simplify and intensify the downstream process, emphasizing and highlighting the ever-accelerating pace of innovation in downstream processing. Molecular biophysics modeling was also employed to enhance the mechanistic understanding of the crystallization and purification processes.

Web Server-based structure prediction as a supplementary tool for basic and acidic FGF secondary structure analysis using FTIR spectroscopy and a case study comparing curve-fit with the model-based structure inspection of the FTIR data

Aim: Fourier Transform Infrared (FTIR) spectroscopy can provide relative proportion of secondary structure elements in a protein. However, extracting this information from the Amide I band area of an FTIR spectrum is difficult. In addition to experimental methods, several protein secondary structure prediction algorithms serving on the Web can be used as supplementary tools requiring only protein amino acid sequences as inputs. WeIn addition, web-server based docking tools can provide structure information when proteins are mixed and potentially interacting. Accordingly, we aimed to utilize web-server based structure predictors in fibroblast growth factor (FGF) protein structure determination through the FTIR data. Materials and methods: Seven such predictors arewere selected and tested on basic FGF (bFGF) protein, to predict FGF secondary structure. Results arewere compared to available structure-files deposited in the Protein Data Bank (PDB). Then, FTIR spectra of bFGF and the acidic form of the protein with 50 folds more bovine serum albumin as carrier protein (1FGFA/50BSA) arewere collected. Optimized Amide I curve-fit parameters of bFGF with low (

Structures of antibody/MHC-I complexes reveal deficiencies in structure prediction programs

Abstract The remarkable success of structural prediction programs such as AlphaFold2 and RosettaFold have revolutionized the contemporary approach to protein structure determination. However, intrinsically disordered proteins (IDPs) and protein/protein complexes provide a greater challenge to such algorithms. In particular, there has been limited success in the structural prediction of antibody/protein antigen complexes and TCR/MHC complexes, in part because the database of such structures is limited. Here, we present several high-resolution X-ray structures of anti-MHC/MHC-I complexes consistent with previous exon-shuffling and epitope mapping data that contradict computational predictions. Specifically, two mAb previously mapped to the alpha3 domain of H2-D(d) or H2-L(d)/D(b) respectively are shown to bind in distinct orientations, either of which may sterically block CD8 binding. In addition, a peptide dependent, but peptide non-specific anti-H2-D(d) mAb binds to loops of the alpha2 domain. These results substantiate the need to determine experimental structures of antibody/protein complexes as we proceed to develop avenues for the de novo design of specific antibodies. Supported by the Intramural Research Program of the NIAID, NIH Supported by the Intramural Research Program of the NIAID, NIH

Membrane protein isolation and structure determination in cell-derived membrane vesicles

Integral membrane protein structure determination traditionally requires extraction from cell membranes using detergents or polymers. Here, we describe the isolation and structure determination of proteins in membrane vesicles derived directly from cells. Structures of the ion channel Slo1 from total cell membranes and from cell plasma membranes were determined at 3.8Å and 2.7Å resolution, respectively. The plasma membrane environment stabilizes Slo1, revealing an alteration of global helical packing, polar lipid, and cholesterol interactions that stabilize previously unresolved regions of the channel and an additional ion binding site in the Ca2+ regulatory domain. The two methods presented enable structural analysis of both internal and plasma membrane proteins without disrupting weakly interacting proteins, lipids, and cofactors that are essential to biological function.

Halobacterium salinarum: Life with more than a grain of salt.

Halobacterium salinarum is a halophilic (salt-loving) archaeon that grows in salt concentrations near or at saturation. Although isolated from salted fish a century ago, it was the 1971 discovery of bacteriorhodopsin, the light-driven proton pump, that raised interest in Hbt. salinarum across a range of disciplines, including biophysics, chemistry, molecular evolution and biotechnology. Hbt. salinarum have since contributed to numerous discoveries, such as advances in membrane protein structure determination and the first example of a non-eukaryal glycoprotein. Work on Hbt. salinarum, one of the species used to define Archaea, has also elucidated molecular workings in the third domain. Finally, Hbt. salinarum presents creative solutions to the challenges of life in high salt.

Determining protein structures in cellular lamella at pseudo-atomic resolution by GisSPA

Cryo-electron tomography is a major tool used to study the structure of protein complexes in situ. However, the throughput of tilt-series image data collection is still quite low. Here, we show that GisSPA, a GPU accelerated program, can translationally and rotationally localize the target protein complex in cellular lamellae, as prepared with a focused ion beam, using single cryo-electron microscopy images without tilt-series, and reconstruct the protein complex at near-atomic resolution. GisSPA allows high-throughput data collection without the acquisition of tilt-series images and reconstruction of the tomogram, which is essential for high-resolution reconstruction of asymmetric or low-symmetry protein complexes. We demonstrate the power of GisSPA with 3.4-Å and 3.9-Å resolutions of resolving phycobilisome and tetrameric photosystem II complex structures in cellular lamellae, respectively. In this work, we present GisSPA as a practical tool that facilitates high-resolution in situ protein structure determination.

Benchmarking applicability of medium-resolution cryo-EM protein structures for structure-based drug design.

Cryo-electron microscopy (cryo-EM) is gaining large attention for high-resolution protein structure determination in solutions. However, a very high percentage of cryo-EM structures correspond to resolutions of 3-5Å, making the structures difficult to be used in in silico drug design. In this study, we analyze how useful cryo-EM protein structures are for in silico drug design by evaluating ligand docking accuracy. From realistic cross-docking scenarios using medium resolution (3-5Å) cryo-EM structures and a popular docking tool Autodock-Vina, only 20% of docking succeeded, when the success rate doubles in the same kind of cross-docking but using high-resolution (<2Å) crystal structures instead. We decipher the reason for failures by decomposing the contribution from resolution-dependent and independent factors. The heterogeneity in the protein side-chain and backbone conformations is identified as the major resolution-dependent factor causing docking difficulty from our analysis, while intrinsic receptor flexibility mainly comprises the resolution-independent factor. We demonstrate the flexibility implementation in current ligand docking tools is able to rescue only a portion of failures (10%), and the limited performance was majorly due to potential structural errors than conformational changes. Our work suggests the strong necessity of more robust method developments on ligand docking and EM modeling techniques in order to fully utilize cryo-EM structures for in silico drug design.

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).

Maize protein structure resources at the maize genetics and genomics database.

Protein structures play an important role in bioinformatics, such as in predicting gene function or validating gene model annotation. However, determining protein structure was, until now, costly and time-consuming, which resulted in a structural biology bottleneck. With the release of such programs AlphaFold and ESMFold, this bottleneck has been reduced by several orders of magnitude, permitting protein structural comparisons of entire genomes within reasonable timeframes. MaizeGDB has leveraged this technological breakthrough by offering several new tools to accelerate protein structural comparisons between maize and other plants as well as human and yeast outgroups. MaizeGDB also offers bulk downloads of these comparative protein structure data, along with predicted functional annotation information. In this way, MaizeGDB is poised to assist maize researchers in assessing functional homology, gene model annotation quality, and other information unavailable to maize scientists even a few years ago.

NMRtist: an online platform for automated biomolecular NMR spectra analysis.

We present NMRtist, an online platform that combines deep learning, large-scale optimization and cloud computing to automate protein NMR spectra analysis. Our website provides virtual storage for NMR spectra deposition together with a set of applications designed for automated peak picking, chemical shift assignment and protein structure determination. The system can be used by non-experts and allows protein assignments and structures to be determined within hours after the measurements, strictly without any human intervention. NMRtist is freely available to non-commercial users at https://nmrtist.org. Supplementary data are available at Bioinformatics online.

A search for the resting conformation of the bacterial mechanosensitive channel MSCs.

Structure determination for membrane proteins remains not only technically challenging but is further complicated by potentially non-native conformations resulting from removal of stabilizing lipids. This is especially true for mechanosensitive channels, which are designed to undergo gating transitions under membrane tension that negates part of the bilayer's lateral pressure. At tensions near its activation threshold (5-7 mN/m), the MscS channel slowly transitions from the resting to the inactivated state, which is tension insensitive. This interconversion between the two non-conductive states is accompanied by an 8 nm2 lateral expansion, revealing that the resting state must be more compact. We attempt to relate these two functional states with existing MscS structures experimentally and computationally. Molecular dynamics simulations used to verify experimental conductance and in-plane area expansion revealed that the many MscS structures are non-conductive or semi-conductive. These non-conductive structures share a splayed conformation of lipid-facing TM1-TM2 helical pairs, deep crevices between TM2 and TM3, and a de-coupling of the TM3a gate from the TM1-TM2 tension-transmitting domains. Yet, functional studies demonstrate the necessity of close hydrophobic TM2-TM3 contact for the resting to open transition; hydrophilic mutations lead to immediate inactivation instead of opening. This prompted the modeling of a “compact” resting state characterized by “upright” rather than splayed TM1-TM2 pairs and tighter TM2-TM3 contact that would reconnect the gate to TM1-TM2 helices. Simulated transitions from structures with splayed TM1-TM2 pairs to this compact state revealed two conserved stabilizing salt bridges: R59-D67 and D62-R131. Charge-inverting and neutralizing mutations at these residues had drastic effects on opening and closing rates, inactivation, and especially recovery from inactivation. Disulfide pairs introduced at these salt bridge positions support their proximity as predicted by the model. A cryo-EM characterization of the disulfide cross-linked channel is in progress.