Structural Biology Research Articles

CSSP-2.0: A refined Consensus method for accurate protein secondary structure prediction

Studying the relationship between sequences and their corresponding three-dimensional structure assists structural biologists in solving the protein-folding problem. Despite several experimental and in-silico approaches, still understanding or decoding the three-dimensional structures from the sequence remains a mystery. In such cases, the accuracy of the structure prediction plays an indispensable role. To address this issue, an updated web server (CSSP-2.0) has been created to improve the accuracy of our previous version of CSSP by deploying the existing algorithms. It uses input as probabilities and predicts the consensus for the secondary structure as a highly accurate three-state Q3 (helix, strand, and coil). This prediction is achieved using six recent top-performing methods: MUFOLD-SS, RaptorX, PSSpred v4, PSIPRED, JPred v4, and Porter 5.0. CSSP-2.0 validation includes datasets involving various protein classes from the PDB, CullPDB, and AlphaFold databases. Our results indicate a significant improvement in the accuracy of the consensus Q3 prediction. Using CSSP-2.0, crystallographers can sort out the stable regular secondary structures from the entire complex structure, which would aid in inferring the functional annotation of hypothetical proteins. The web server is freely available at https://bioserver3.physics.iisc.ac.in/cgi-bin/cssp-2/

The mechanism of mammalian proton-coupled peptide transporters.

Proton-coupled oligopeptide transporters (POTs) are of great pharmaceutical interest owing to their promiscuous substrate binding site that has been linked to improved oral bioavailability of several classes of drugs. Members of the POT family are conserved across all phylogenetic kingdoms and function by coupling peptide uptake to the proton electrochemical gradient. Cryo-EM structures and alphafold models have recently provided new insights into different conformational states of two mammalian POTs, SLC15A1, and SLC15A2. Nevertheless, these studies leave open important questions regarding the mechanism of proton and substrate coupling, while simultaneously providing a unique opportunity to investigate these processes using molecular dynamics (MD) simulations. Here, we employ extensive unbiased and enhanced-sampling MD to map out the full SLC15A2 conformational cycle and its thermodynamic driving forces. By computing conformational free energy landscapes in different protonation states and in the absence or presence of peptide substrate, we identify a likely sequence of intermediate protonation steps that drive inward-directed alternating access. These simulations identify key differences in the extracellular gate between mammalian and bacterial POTs, which we validate experimentally in cell-based transport assays. Our results from constant-PH MD and absolute binding free energy (ABFE) calculations also establish a mechanistic link between proton binding and peptide recognition, revealing key details underpining secondary active transport in POTs. This study provides a vital step forward in understanding proton-coupled peptide and drug transport in mammals and pave the way to integrate knowledge of solute carrier structural biology with enhanced drug design to target tissue and organ bioavailability.

Structural Biology in Drug Discovery and Development: Call for Papers

Structural Biology in Drug Discovery and Development: Call for Papers

Bicarbonate is a key regulator but not a substrate for O2 evolution in Photosystem II.

Photosystem II (PSII) uses light energy to oxidize water and to reduce plastoquinone in the photosynthetic electron transport chain. O2 is produced as a byproduct. While most members of the PSII research community agree that O2 originates from water molecules, alternative hypotheses involving bicarbonate persist in the literature. In this perspective, we provide an overview of the important roles of bicarbonate in regulating PSII activity and assembly. Further, we emphasize that biochemistry, spectroscopy, and structural biology experiments have all failed to detect bicarbonate near the active site of O2 evolution. While thermodynamic arguments for oxygen-centered bicarbonate oxidation are valid, the claim that bicarbonate is a substrate for photosynthetic O2 evolution is challenged.

The myth of high-resolution liquid phase biological electron microscopy.

Cryo-electron microscopy (cryo-EM) has transformed structural biology over the past 12 years, with it now being routine rather than exceptional to reach a near-atomic level of resolution for proteins and macromolecular complexes. Samples are immobilized by vitrification and this sample can be maintained at liquid nitrogen temperatures in the vacuum of the electron microscope with negligible sublimation. Due to the low electron doses needed to avoid radiation damage, averaging over tens of thousands to hundreds of thousands of particle images is used to achieve a high signal-to-noise ratio. An alternative approach has been proposed where samples are at room temperature in the liquid state, maintained in the vacuum of the electron microscope by thin film enclosures that are relatively transparent to electrons while preventing evaporation of the liquid. A paper has argued that using this liquid-phase approach, higher resolution (3.2 Å) can be achieved than using cryo-EM (3.4 Å) when imaging and reconstructing adeno-associated virus particles. I show here that these assertions are untrue, and that basic principles in mathematics and physics would need to be violated to achieve the stated resolution in the liquid state. Thus, high resolution liquid phase EM of macromolecules remains science fiction.

Intervertebral disc creep behaviour through viscoelastic models: an in-vitro study

The intervertebral disc (IVD) is a complex biological structure that ensures the spine strength, stability, mobility, and flexibility. This is achieved due to its biphasic nature which is attained by its solid phase (annulus fibrosus) and fluid phases (nucleus pulposus). Hence, the IVD biomechanical response to long-term loads, which is critical as it affects hydration, and nutrients-water transport influencing disc height reduction, has been further explored and mathematically modelled in this paper. An in-vitro study was performed on seven human lumbar spine specimens (L4-5), to assess if the classical rheological models and Nutting's power law can model in a simple way the intermediate characteristics between solid and fluid of the IVD. Creep tests were conducted by applying a static compression load of 500 N for 15 min. A correlation analysis was done (Pearson, p < 0.05) between the model parameters and the maximum value of Disc Height Reduction, followed by a linear regression analysis. In summary, the long-term IVD mechanical behavior was modeled in a simple way, emphasizing that yet there is no mathematical certainty about this mechanical behavior. Hence, a future aim might be to develop intervertebral disc prostheses capable of replicating only the disc mechanical response, without necessarily considering the microscopic-level biological drivers. Therefore, a future goal is to fully understand and model the disc's mechanical response toward the design of new disc prostheses that would consider only the macroscopic aspect, without considering the biological aspects.

Harnessing Biomimicry for Controlled Adhesion on Material Surfaces.

Nature serves as an abundant wellspring of inspiration for crafting innovative adhesive materials. Extensive research is conducted on various complex forms of biological attachment, such as geckos, tree frogs, octopuses, and mussels. However, significant obstacles still exist in developing adhesive materials that truly replicate the behaviors and functionalities observed in living organisms. Here, an overview of biological organs, structures, and adhesive secretions endowed with adhesion capabilities, delving into the intricate relationship between their morphology and function, and potential for biomimicry are provided. First, the design principles and mechanisms of adhesion behavior and individual organ morphology in nature are summarized from the perspective of structural and size constraints. Subsequently, the value of engineered and bioinspired adhesive materials through selective application cases in practical fields is emphasized. Then, a forward-looking gaze on the conceivable challenges and associated opportunities in harnessing biomimetic strategies and biological materials for advancing adhesive material innovation is highlighted and cast.

Strategy for modeling higher-order G-quadruplex structures recalcitrant to NMR determination

Guanine-rich nucleic acids can form intramolecularly folded four-stranded structures known as G-quadruplexes (G4s). Traditionally, G4 research has focused on short, highly modified DNA or RNA sequences that form well-defined homogeneous compact structures. However, the existence of longer sequences with multiple G4 repeats, from proto-oncogene promoters to telomeres, suggests the potential for more complex higher-order structures with multiple G4 units that might offer selective drug-targeting sites for therapeutic development. These larger structures present significant challenges for structural characterization by traditional high-resolution methods like multi-dimensional NMR and X-ray crystallography due to their molecular complexity. To address this current challenge, we have developed an integrated structural biology (ISB) platform, combining experimental and computational methods to determine self-consistent molecular models of higher-order G4s (xG4s). Here we outline our ISB method using two recent examples from our lab, an extended c-Myc promoter and long human telomere G4 repeats, that highlights the utility and generality of our approach to characterizing biologically relevant xG4s.

Enzyme-Responsive Supramolecular Self-Assembly in Small Amphiphiles.

Enzyme-responsive molecular assemblies have recently made remarkable progress, owing to their widespread applications. As a class of catalysts with high specificity and efficiency, enzymes play a critical role in producing new molecules and maintaining metabolic stability in living organisms. Therefore, the study of enzyme-responsive assembly aids in understanding the origin of life and the physiological processes occurring within living bodies, contributing to further advancements across various disciplines. In this Review, we summarize three kinds of enzyme-responsive assembly systems in amphiphiles: enzyme-triggered assembly, disassembly, and structural transformation. Furthermore, motivated by the fact that biological macromolecules and complex structures all originated with small molecules, our focus lies on the small amphiphiles (e.g., peptides, surfactants, fluorescent molecules, and drug molecules). We also provide an outlook on the potential of enzyme-responsive assembly systems for biomimetic development and hope this Review will attract more attention to this emerging research branch at the intersection of assembly chemistry and biological science.

Structural biology of HER2/ERBB2 dimerization: mechanistic insights and differential roles in healthy versus cancerous cells

Aim: Present study was done to understand the dimerization of HER2/ERBB2 in normal and cancer cells using in-silico study. Methods: Pathway analysis was done using Reactome. Structure of HER2/ERBB2 protein was obtained from PDB database, and using Schrödinger software protein structure was analysed and dimerization was done. Results: In normal cells, HER2/ERBB2 is present at low levels and forms a stable complex with HSP90 (heat shock protein 90), CDC37 (cell division cycle 37), and ERBIN (an adaptor protein of the HER2/ERBB2 receptor). HER2/ERBB2 lacks a ligand-binding site, so it cannot bind ligands to activate HER2/ERBB2 signaling directly. Instead, it heterodimerizes with other EGFR family members, using their ligand-binding sites to activate cell proliferation signaling cascades. In cancer, overexpression of HER2/ERBB2 leads to ligand-independent activation of signaling through dimerization. During this process, HER2/ERBB2 dissociates from the HSP90 complex. Normally, HSP90 helps to correct misfolded and aggregated proteins, but it fails to correct mutated HER2/ERBB2 in cancer cells. Conclusions: This discussion focuses on the structural changes that HER2/ERBB2 undergoes, particularly in the form of homodimers, under normal and cancerous conditions. This analysis highlights the mutated state of HER2/ERBB2 and the role of HSP90 in this context. Notably, a single-point mutation outside a protein’s active site can significantly alter its structure. This is a critical consideration in drug discovery, underscoring the need to evaluate the entire protein conformation during simulations.

Array tomography: trails to discovery

Abstract Tissue slicing is at the core of many approaches to studying biological structures. Among the modern volume electron microscopy (vEM) methods, array tomography (AT) is based on serial ultramicrotomy, section collection onto solid support, imaging via light and/or scanning electron microscopy, and re-assembly of the serial images into a volume for analysis. While AT largely uses standard EM equipment, it provides several advantages, including long-term preservation of the sample and compatibility with multi-scale and multi-modal imaging. Furthermore, the collection of serial ultrathin sections improves axial resolution and provides access for molecular labeling, which is beneficial for light microscopy and immunolabeling, and facilitates correlation with EM. Despite these benefits, AT techniques are underrepresented in imaging facilities and labs, due to their perceived difficulty and lack of training opportunities. Here we point towards novel developments in serial sectioning and image analysis that facilitate the AT pipeline, and solutions to overcome constraints. Because no single vEM technique can serve all needs regarding field of view and resolution, we sketch a decision tree to aid researchers in navigating the plethora of options available. Lastly, we elaborate on the unexplored potential of AT approaches to add valuable insight in diverse biological fields.

Reactions Driven by Primitive Nonbiological Polyesters.

ConspectusAll life on Earth is composed of cells, which are built from and run by biological reactions and structures. These reactions and structures are generally the result of action by cellular biomolecules, which are indispensable for the function and survival of all living organisms. Specifically, biological catalysis, namely by protein enzymes, but also by other biomolecules including nucleic acids, is an essential component of life. How the biomolecules themselves that perform biological catalysis came to exist in the first place is a major unanswered question that plagues researchers to this day, which is generally the focus of the origins of life (OoL) research field. Based on current knowledge, it is generally postulated that early Earth was full of a myriad of different chemicals, and that these chemicals reacted in specific ways that led to the emergence of biochemistry, cells, and later, life. In particular, a significant part of OoL research focuses on the synthesis, evolution, and function of biomolecules potentially present under early Earth conditions, as a way to understand their eventual transition into modern life. However, this narrative overlooks possibilities that other molecules contributed to the OoL, as while biomolecules that led to life were certainly present on early Earth, at the same time, other molecules that may not have strict, direct biological lineage were also widely and abundantly present. For example, hydroxy acids, although playing a role in metabolism or as parts of certain biological structures, are not generally considered to be as essential to modern biology as amino acids (a chemically similar monomer), and thus research in the OoL field tends to perhaps focus more on amino acids than hydroxy acids. However, their likely abundance on early Earth coupled with their ability to spontaneously condense into polymers (i.e., polyesters) make hydroxy acids, and their subsequent products, functions, and reactions, a reasonable target of investigation for prebiotic chemists. Whether "non-biological" hydroxy acids or polyesters can contribute to the emergence of life on early Earth is an inquiry that deserves attention within the OoL community, as this knowledge can also contribute to our understanding of the plausibility of extraterrestrial life that does not exactly use the biochemical set found in terrestrial organisms. While some demonstrations have been made with respect to compartment assembly, compartmentalization, and growth of primitive polyester-based systems, whether these "non-biological" polymers can contribute any catalytic function and/or drive primitive reactions is still an important step toward the development of early life. Here, we review research both from the OoL field as well as from industry and applied sciences regarding potential catalysis or reaction driven by "non-biological" polyesters in various forms: as linear polymers, as hyperbranched polyesters, and as membraneless microdroplets.

Enhancing predictions of protein stability changes induced by single mutations using MSA-based Language Models.

Protein Language Models offer a new perspective for addressing challenges in structural biology, while relying solely on sequence information. Recent studies have investigated their effectiveness in forecasting shifts in thermodynamic stability caused by single amino acid mutations, a task known for its complexity due to the sparse availability of data, constrained by experimental limitations. To tackle this problem, we introduce two key novelties: leveraging a Protein Language Model that incorporates Multiple Sequence Alignments to capture evolutionary information, and using a recently released mega-scale dataset with rigorous data pre-processing to mitigate overfitting. We ensure comprehensive comparisons by fine-tuning various pre-trained models, taking advantage of analyses such as ablation studies and baselines evaluation. Our methodology introduces a stringent policy to reduce the widespread issue of data leakage, rigorously removing sequences from the training set when they exhibit significant similarity with the test set. The MSA Transformer emerges as the most accurate among the models under investigation, given its capability to leverage co-evolution signals encoded in aligned homologous sequences. Moreover, the optimized MSA Transformer outperforms existing methods and exhibits enhanced generalization power, leading to a notable improvement in predicting changes in protein stability resulting from point mutations. Code and data at https://github.com/RitAreaSciencePark/PLM4Muts. Supplementary Information is available at Bioinformatics online.

A modular inquiry-based semester theme that integrates data science education and bioinformatics in protein structure function courses.

With an exponential growth in biological data and computing power, familiarity with bioinformatics has become a demanding and popular skill set both in academia and industry. There is a need to increase students' competencies to be able to take on bioinformatic careers, to get them familiarized with scientific professions in data science and the academic training required to pursue them, in a field where demand outweighs the supply. Here we implemented a set of bioinformatic activities into a protein structure and function course of a graduate program. Concisely, students were given hands-on opportunities to explore the bioinformatics-based analyses of biomolecular data and structural biology via a semester-long case study structured as inquiry-based bioinformatics exercises. Towards the end of the term, the students also designed and presented an assignment project that allowed them to document the unknown protein that they identified using bioinformatic knowledge during the term. The post-module survey responses and students' performances in the lab module imply that it furthered an in-depth knowledge of bioinformatics. Despite having not much prior knowledge of bioinformatics prior to taking this module students indicated positive feedback. The students got familiar with cross-indexed databases that interlink important data about proteins, enzymes as well as genes. The essential skillsets honed by this research-based bioinformatic pedagogical approach will empower students to be able to leverage this knowledge for their future endeavours in the bioinformatics field.

How can the diterpene synthase CotB2V80L alter the product profile?

Structural diversity of diterpenes is mediated by the enigmatic family of diterpene synthases. The overall enzymatic contribution hereby lies in a carefully concerted chemistry of highly reactive carbocation intermediates mainly guided by aromatic and polar amino acid side chains and the pyrophosphate cofactor. To date several studies aimed to shed light on the mechanism underlining terpene synthases chemistry. Specifically, the diterpene synthase CotB2 serves as model enzyme for detailed mutagenesis studies. Here we investigate the catalytic mechanism of CotB2 variant V80L in a holistic, biochemical, structural, and computational biology approach. We were able to identify an altered product profile compared to CotB2WT for the substrates geranylgeranyl diphosphate and farnesyl diphosphate. Moreover, we solved the crystal structure, and shed further light on terpene synthase chemistry by modelling of the substrate and intermediate binding.

Progress in Preparation and Application of Fucoxanthin from Marine Algae

This paper reviews the preparation and application of fucoxanthin from marine algae. It details the progress in various aspects, including biological origin, chemical structure, production process, structure identification, physiological functions, and applications, based on experimental data and clinical applications. The paper also highlights technical challenges and issues in fucoxanthin research, such as improving yield, purity, and structure modification. Finally, it summarizes the research findings and discusses future research directions and prospects for fucoxanthin from marine algae, offering suggestions for further studies.

FRESH-based 3D bioprinting of complex biological geometries using chitosan bioink

Traditional three-dimensional (3D) bioprinting has always been associated with the challenge of print fidelity of complex geometries due to the gel-like nature of the bioinks. Embedded 3D bioprinting has emerged as a potential solution to print complex geometries using proteins and polysaccharides-based bioinks. This study demonstrated the Freeform Reversible Embedding of Suspended Hydrogels (FRESH) 3D bioprinting method of chitosan bioink to 3D bioprint complex geometries. 4.5% chitosan was dissolved in an alkali solvent to prepare the bioink. Rheological evaluation of the bioink described its shear-thinning nature. The power law equation was fitted to the shear rate-viscosity plot. The flow index value was found to be less than 1, categorizing the material as pseudo-plastic. The chitosan bioink was extruded into another medium, a thermo-responsive 4.5% gelatin hydrogel. This hydrogel supports the growing print structures while printing. After this, the 3D bioprinted structure was crosslinked with hot water to stabilize the structure. Using this method, we have 3D bioprinted complex biological structures like the human tri-leaflet heart valve, a section of a human right coronary arterial tree, a scale-down outer structure of the human kidney, and a human ear. Additionally, we have shown the mechanical tunability and suturability of the 3D bioprinted structures. This study demonstrates the capability of the chitosan bioink and FRESH method for 3D bioprinting of complex biological models for biomedical applications.

Identification of metal tolerance proteins (MTP) and their gene expression under drought stress in potato (Solanum tuberosum L.)

Metal tolerance proteins (MTPs) are as metal efflux transporters, existing extensively at all plant sections and play significant roles in regulation of the metal levels in biological processes. In the current study, phylogenetic relationships, gene structures, conserved motifs, and StMTP domains were analyzed. Here, 12 MTP genes in S. tuberosum were detected and categorized in three major clusters namely Fe/Zn-MTP, Zn-MTP, and Mn-MTP and seven groups (1, 5, 6, 7, 8, 9, and 11) according to phylogenetic relationships. Based on in silico and qPCR analysis, all of StMTPs included a cation diffusion facilitator (CDF) domains and the putative Mn-MTP harbored the ZT-dimer. An evolutionary analysis indicated that StMTP genes had undergone gene duplication leading to gene loss and gene expansion events. Analysis of transcription factor binding sites (TFBS) and microRNA in promoter region and coding sequence of StMTP genes revealed the presence of 5312 putative TFBS and 13 StmiRNAs. The analysis of promoter regions of StMTP genes possess various frequencies of TFBS, illustrating various responses in different growth and developmental stages as well as under abiotic stress. Expression profile analysis revealed that the StMTP9 were up-regulated in leaves and stem, while, StMTP8 up-regulated in leaves. Both genes down-regulated in tubers, roots as well as under drought stress. These results will provide a better insight for functional characterization of StMTP genes and can be helpful to elucidate the biological structure of their genes in potato.

Unraveling Spatial Domain Characterization in Spatially Resolved Transcriptomics with Robust Graph Contrastive Clustering.

Spatial transcriptomics can quantify gene expression and its spatial distribution in tissues, thus revealing molecular mechanisms of cellular interactions underlying tissue heterogeneity, tissue regeneration, and spatially localized disease mechanisms. However, existing spatial clustering methods often fail to exploit the full potential of spatial information, resulting in inaccurate identification of spatial domains. In this paper, we develop a deep graph contrastive clustering framework, stDGCC, that accurately uncovers underlying spatial domains via explicitly modeling spatial information and gene expression profiles from spatial transcriptomics data. The stDGCC framework proposes a spatially informed graph node embedding model to preserve the topological information of spots and to learn the informative and discriminative characterization of spatial transcriptomics data through self-supervised contrastive learning. By simultaneously optimizing the contrastive learning loss, reconstruction loss, and Kullback-Leibler (KL) divergence loss, stDGCC achieves joint optimization of feature learning and topology structure preservation in an end-to-end manner. We validate the effectiveness of stDGCC on various spatial transcriptomics datasets acquired from different platforms, each with varying spatial resolutions. Our extensive experiments demonstrate the superiority of stDGCC over various state-of-the-art clustering methods in accurately identifying cellular-level biological structures. Code and data are available from https://github.com/TimE9527/stDGCC and https://figshare.com/projects/stDGCC/186525. Supplementary data are available at Bioinformatics online.

On-line correlative imaging of cryo-PALM and soft X-ray tomography for identification of subcellular structures

Correlative imaging of fluorescence microscopy and soft X-ray microscopy plays a crucial role in exploring the relationship between structure and function in cellular biology. However, the current correlative imaging methods are limited either to off-line or low-resolution fluorescence imaging. In this study, we developed an integrated on-line cryogenic photoactivated localization microscopy (cryo-PALM) system at a soft X-ray microscopy station. This design eliminates some critical issues such as sample damage and complex post-correlation arising from transferring samples between different cryostages. Furthermore, we successfully achieved correlative imaging of cryopreserved near-native cells, with a resolution of about 50 nm of cryo-PALM. Therefore, the developed on-line correlation imaging platform provides a powerful tool for investigating the intricate relationship between structure and function in biological and molecular interactions, as well as in other life science disciplines.