Search Results (24)

AAA+ ATPases are ring-shaped hexameric protein complexes that operate as elaborate macromolecular motors, driving a variety of ATP-dependent cellular processes. AAA+ ATPases undergo large-scale conformational changes that lead to the conversion of chemical energy from ATP into mechanical work to perform a wide range of functions, such as unfolding and translocation of the protein substrate inside a proteolysis chamber of an AAA+-associated protease. Despite extensive biochemical studies on these macromolecular assemblies, the mechanism of substrate unfolding and degradation has long remained elusive. Indeed, until recently, structural characterization of AAA+ protease complexes remained hampered by the size and complexity of the machinery, harboring multiple protein subunits acting together to process proteins to be degraded. Additionally, the major structural rearrangements involved in the mechanism of this complex represent a crucial challenge for structural biology. Here, we report the main advances in deciphering molecular details of the proteolytic reaction performed by AAA+ proteases, based on the remarkable progress in structural biology techniques. Particular emphasis is placed on the latest findings from high-resolution structural analysis of the ClpXP proteolytic complex, using crystallographic and cryo-EM investigations. In addition, this review presents some additional dynamic information obtained using solution-state NMR. This information provides molecular details that help to explain the protein degradation process by such molecular machines. Full article

B30.2 domains, sometimes referred to as PRY/SPRY domains, were originally identified by sequence profiling methods at the gene level. The B30.2 domain comprises a concanavalin A-like fold consisting of two twisted seven-stranded anti-parallel β-sheets. B30.2 domains are present in about 150 human and 700 eukaryotic proteins, usually fused to other domains. The B30.2 domain represents a scaffold, which, through six variable loops, binds different unrelated peptides or endogenous low-molecular-weight compounds. At the cellular level, B30.2 proteins engage in supramolecular assemblies with important signaling functions. In humans, B30.2 domains are often found in E3-ligases, such as tripartite motif (Trim) proteins, SPRY domain-containing SOCS box proteins, Ran binding protein 9 and −10, Ret-finger protein-like, and Ring-finger proteins. The B30.2 protein recognizes the target and recruits the E2-conjugase by means of the fused domains, often involving specific adaptor proteins. Further well-studied B30.2 proteins are the methyltransferase adaptor protein Ash2L, some butyrophilins, and Ryanodine Receptors. Although the affinity of an isolated B30.2 domain to its ligand might be weak, it can increase strongly due to avidity effects upon recognition of oligomeric targets or in the context of macromolecular machines. Full article

Background/Objectives: Pathway annotations of non-macromolecular (relatively small) biomolecules facilitate biological and biomedical interpretation of metabolomics datasets. However, low pathway annotation levels of detected biomolecules hinder this type of interpretation. Thus, predicting the pathway involvement of detected but unannotated biomolecules has a high potential to improve metabolomics data analysis and omics integration. Past publications have only made use of the Kyoto Encyclopedia of Genes and Genomes-derived datasets to develop machine learning models to predict pathway involvement. However, to our knowledge, the Reactome knowledgebase has not been utilized to develop these types of predictive models. Methods: We created a dataset ready for machine learning using chemical representations of all pathway-annotated compounds available from the Reactome knowledgebase. Next, we trained and evaluated a multilayer perceptron binary classifier using combined metabolite-pathway paired feature vectors engineered from this new dataset. Results: While models trained on a prior corresponding KEGG dataset with 502 pathways scored a mean Matthew’s correlation coefficient (MCC) of 0.847 and a 0.0098 standard deviation, the models trained on the Reactome dataset with 3985 pathways demonstrated improved performance with a mean MCC of 0.916, but with a higher standard deviation of 0.0149. Conclusions: These results indicate that the pathways in Reactome can also be effectively predicted, greatly increasing the number of human-defined pathways available for prediction. Full article

Eriocheir sinensis is an economically important aquatic animal. Its regulatory mechanisms underlying many biological processes are still vague due to the lack of systematic analysis tools. The protein–protein interaction network (PIN) is an important tool for the systematic analysis of regulatory mechanisms. In this work, a novel machine learning method, DGO-SVM, was applied to predict the protein–protein interaction (PPI) in E. sinensis, and its PIN was reconstructed. With the domain, biological process, molecular functions and subcellular locations of proteins as the features, DGO-SVM showed excellent performance in Bombyx mori, humans and five aquatic crustaceans, with 92–96% accuracy. With DGO-SVM, the PIN of E. sinensis was reconstructed, containing 14,703 proteins and 7,243,597 interactions, in which 35,604 interactions were associated with 566 novel proteins mainly involved in the response to exogenous stimuli, cellular macromolecular metabolism and regulation. The DGO-SVM demonstrated that the biological process, molecular functions and subcellular locations of proteins are significant factors for the precise prediction of PPIs. We reconstructed the largest PIN for E. sinensis, which provides a systematic tool for the regulatory mechanism analysis. Furthermore, the novel-protein-related PPIs in the PIN may provide important clues for the mechanism analysis of the underlying specific physiological processes in E. sinensis. Full article

Accurate energy data from noncovalent interactions are essential for constructing force fields for molecular dynamics simulations of bio-macromolecular systems. There are two important practical issues in the construction of a reliable force field with the hope of balancing the desired chemical accuracy and working efficiency. One is to determine a suitable quantum chemistry level of theory for calculating interaction energies. The other is to use a suitable continuous energy function to model the quantum chemical energy data. For the first issue, we have recently calculated the intermolecular interaction energies using the SAPT0 level of theory, and we have systematically organized these energies into the ab initio SOFG-31 (homodimer) and SOFG-31-heterodimer datasets. In this work, we re-calculate these interaction energies by using the more advanced SAPT2 level of theory with a wider series of basis sets. Our purpose is to determine the SAPT level of theory proper for interaction energies with respect to the CCSD(T)/CBS benchmark chemical accuracy. Next, to utilize these energy datasets, we employ one of the well-developed machine learning techniques, called the CLIFF scheme, to construct a general-purpose force field for biomolecular dynamics simulations. Here we use the SOFG-31 dataset and the SOFG-31-heterodimer dataset as the training and test sets, respectively. Our results demonstrate that using the CLIFF scheme can reproduce a diverse range of dimeric interaction energy patterns with only a small training set. The overall errors for each SAPT energy component, as well as the SAPT total energy, are all well below the desired chemical accuracy of ~1 kcal/mol. Full article

Bacteria have existed on Earth for billions of years, exhibiting ubiquity and involvement in various biological activities. To ensure survival, bacteria usually release and secrete effector proteins to acquire nutrients and compete with other microorganisms for living space during long-term evolution. Consequently, bacteria have developed a range of secretion systems, which are complex macromolecular transport machines responsible for transporting proteins across the bacterial cell membranes. Among them, one particular secretion system that stands out from the rest is the type V secretion system (T5SS), known as the “autotransporter”. Bacterial activities mediated by T5SS include adherence to host cells or the extracellular matrix, invasion of host cells, immune evasion and serum resistance, contact-dependent growth inhibition, cytotoxicity, intracellular flow, protease activity, autoaggregation, and biofilm formation. In a bacterial body, it is not enough to rely on T5SS alone; in most cases, T5SS cooperates with other secretion systems to carry out bacterial life activities, but regardless of how good the relationship is, there is friction between the secretion systems. T5SS and T1SS/T2SS/T3SS/T6SS all play a synergistic role in the pathogenic processes of bacteria, such as nutrient acquisition, pathogenicity enhancement, and immune modulation, but T5SS indirectly inhibits the function of T4SS. This could be considered a love–hate relationship between secretion systems. This paper uses the systematic literature review methodology to review 117 journal articles published within the period from 1995 to 2024, which are all available from the PubMed, Web of Science, and Scopus databases and aim to elucidate the link between T5SS and other secretion systems, providing clues for future prevention and control of bacterial diseases. Full article

Ribosomes, in general, are viewed as constitutive macromolecular machines where protein synthesis takes place; however, this view has been recently challenged, supporting the hypothesis of ribosome specialization and opening a completely new field of research. Recent studies have demonstrated that ribosomes are heterogenous in their nature and can provide another layer of gene expression control by regulating translation. Heterogeneities in ribosomal RNA and ribosomal proteins that compose them favor the selective translation of different sub-pools of mRNAs and functional specialization. In recent years, the heterogeneity and specialization of ribosomes have been widely reported in different eukaryotic study models; however, few reports on this topic have been made on protozoa and even less on protozoa parasites of medical importance. This review analyzes heterogeneities of ribosomes in protozoa parasites highlighting the specialization in their functions and their importance in parasitism, in the transition between stages in their life cycle, in the change of host and in response to environmental conditions. Full article

Following breakthrough achievements in molecular neurosciences, the current decade witnesses a trend toward interdisciplinary and multimodal development. Supplementation of neurosciences with tools from computer science solidifies previous knowledge and sets the ground for new research on “big data” and new hypothesis-free experimental models. In this Special Issue, we set the focus on informatics-supported interdisciplinary neuroscience accomplishments symmetrically combining wet-lab and clinical routines. Video-tracking and automated mitosis detection in vitro, the macromolecular modeling of kinesin motion, and the unsupervised classification of the brain’s macrophage activation status share a common denominator: they are energized by machine and deep learning. Essential clinical neuroscience questions such as the estimated risk of brain aneurysm rupture and the surgical outcome of facial nerve transplantation are addressed in this issue as well. Precise and rapid evaluation of complex clinical data by deep learning and data mining dives deep to reveal symmetrical and asymmetrical features beyond the abilities of human perception or the limits of linear algebraic modeling. This editorial opts to motivate researchers from the wet lab, computer science, and clinical environments to join forces in reshaping scientific platforms, share and converge high-quality data on public platforms, and use informatics to facilitate interdisciplinary information exchange. Full article

Macromolecular self-assembly has great potential for application in the field of the design of molecular machines, in molecular regulation, for biological tissue, and in biomedicine for the optical, electrical, and biological characteristics that the assembly unit does not possess. In this paper, the progress in macromolecular self-assembly is systematically reviewed, including its conception, processes and mechanisms, with a focus on macromolecular self-assembly by stimuli. According to the difference in stimuli, macromolecular self-assembly can be classified into temperature-responsive self-assembly, light-responsive self-assembly, pH-responsive self-assembly, redox-responsive self-assembly, and multi-responsive self-assembly. A preliminary study on constructing dynamic macromolecular self-assembly based on a chemical self-oscillating reaction is described. Furthermore, the problems of macromolecular self-assembly research, such as the extremely simple structure of artificial self-assembly and the low degree of overlap between macromolecular self-assembly and life sciences, are analyzed. The future development of stimuli-responsive macromolecular self-assembly should imitate the complex structures, processes and functions in nature and incorporate the chemical-oscillation reaction to realize dynamic self-assembly. Full article

RND family efflux pumps are complex macromolecular machines involved in multidrug resistance by extruding antibiotics from the cell. While structural studies and molecular dynamics simulations have provided insights into the architecture and conformational states of the pumps, the path followed by conformational changes from the inner membrane protein (IMP) to the periplasmic membrane fusion protein (MFP) and to the outer membrane protein (OMP) in tripartite efflux assemblies is not fully understood. Here, we investigated AcrAB-TolC efflux pump’s allostery by comparing resting and transport states using difference distance matrices supplemented with evolutionary couplings data and buried surface area measurements. Our analysis indicated that substrate binding by the IMP triggers quaternary level conformational changes in the MFP, which induce OMP to switch from the closed state to the open state, accompanied by a considerable increase in the interface area between the MFP subunits and between the OMPs and MFPs. This suggests that the pump’s transport-ready state is at a more favourable energy level than the resting state, but raises the puzzle of how the pump does not become stably trapped in a transport-intermediate state. We propose a model for pump allostery that includes a downhill energetic transition process from a proposed ‘activated’ transport state back to the resting pump. Full article

Genome-scale metabolic models (GEMs) enable the mathematical simulation of the metabolism of archaea, bacteria, and eukaryotic organisms. GEMs quantitatively define a relationship between genotype and phenotype by contextualizing different types of Big Data (e.g., genomics, metabolomics, and transcriptomics). In this review, we analyze the available Big Data useful for metabolic modeling and compile the available GEM reconstruction tools that integrate Big Data. We also discuss recent applications in industry and research that include predicting phenotypes, elucidating metabolic pathways, producing industry-relevant chemicals, identifying drug targets, and generating knowledge to better understand host-associated diseases. In addition to the up-to-date review of GEMs currently available, we assessed a plethora of tools for developing new GEMs that include macromolecular expression and dynamic resolution. Finally, we provide a perspective in emerging areas, such as annotation, data managing, and machine learning, in which GEMs will play a key role in the further utilization of Big Data. Full article

A model of the polymerization process during the formation of a pair of polymer brushes was designed and investigated. The obtained system consisted of two impenetrable parallel surfaces with the same number of chains grafted on both surfaces. Coarse-grained chains embedded in nodes of a face-centered cubic lattice with excluded volume interactions were obtained by a ‘grafted from’ procedure. The structure of synthesized macromolecular systems was also studied. Monte Carlo simulations using the dynamic lattice liquid model were employed using dedicated parallel machine ARUZ in a large size and time scale. The parameters of the polymerization process were found to be crucial for the proper structure of the brush. It was found that for high grafting densities, chains were increasingly compressed, and there is surprisingly little interpenetration of chains from opposite surfaces. It was predicted and confirmed that in a polydisperse sample, the longer chains have unique configurations consisting of a stretched stem and a coiled crown. Full article

A complex interplay between several biological macromolecules maintains cellular homeostasis. Generally, the demanding chemical reactions which sustain life are not performed by individual macromolecules, but rather by several proteins that together form a macromolecular complex. Understanding the functional interactions amongst subunits of these macromolecular machines is fundamental to elucidate mechanisms by which they maintain homeostasis. As the faithful function of macromolecular complexes is essential for cell survival, their mis-function leads to the development of human diseases. Furthermore, detailed mechanistic interrogation of the function of macromolecular machines can be exploited to develop and optimize biotechnological processes. The purification of intact macromolecular complexes is an essential prerequisite for this; however, chromatographic purification schemes can induce the dissociation of subunits or the disintegration of the whole complex. Here, we discuss the development and application of chromatography-free purification strategies based on fractionated PEG precipitation and orthogonal density gradient centrifugation that overcomes existing limitations of established chromatographic purification protocols. The presented case studies illustrate the capabilities of these procedures for the purification of macromolecular complexes. Full article

Second-generation type III-B rotaxane dendrons, equipped with succinimide and acetylene functional groups, were synthesized successfully and characterized by NMR spectroscopy and mass spectrometry. A cell viability study of a dendron with a normal cell line of L929 fibroblast cells revealed no obvious cytotoxicity at a range of 5 to 100 μM. The nontoxic properties of the sophisticated rotaxane dendron building blocks provided a choice of bio-compatible macromolecular machines that could be potentially developed into polymeric materials. Full article

The BAM is a macromolecular machine responsible for the folding and the insertion of integral proteins into the outer membrane of diderm Gram-negative bacteria. In Escherichia coli, it consists of a transmembrane β-barrel subunit, BamA, and four outer membrane lipoproteins (BamB-E). Using BAM-specific antibodies, in E. coli cells, the complex is shown to localize in the lateral wall in foci. The machinery was shown to be enriched at midcell with specific cell cycle timing. The inhibition of septation by aztreonam did not alter the BAM midcell localization substantially. Furthermore, the absence of late cell division proteins at midcell did not impact BAM timing or localization. These results imply that the BAM enrichment at the site of constriction does not require an active cell division machinery. Expression of the Tre1 toxin, which impairs the FtsZ filamentation and therefore midcell localization, resulted in the complete loss of BAM midcell enrichment. A similar effect was observed for YidC, which is involved in the membrane insertion of cell division proteins in the inner membrane. The presence of the Z-ring is needed for preseptal peptidoglycan (PG) synthesis. As BAM was shown to be embedded in the PG layer, it is possible that BAM is inserted preferentially simultaneously with de novo PG synthesis to facilitate the insertion of OMPs in the newly synthesized outer membrane. Full article