Regions Of Secondary Structure Research Articles

Structural and functional insights into the interaction between the bacteriophage T4 DNA processing proteins gp32 and Dda.

Bacteriophage T4 is a classic model system for studying the mechanisms of DNA processing. A key protein in T4 DNA processing is the gp32 single-stranded DNA-binding protein. gp32 has two key functions: it binds cooperatively to single-stranded DNA (ssDNA) to protect it from nucleases and remove regions of secondary structure, and it recruits proteins to initiate DNA processes including replication and repair. Dda is a T4 helicase recruited by gp32, and we purified and crystallized a gp32-Dda-ssDNA complex. The low-resolution structure revealed how the C-terminus of gp32 engages Dda. Analytical ultracentrifugation analyses were consistent with the crystal structure. An optimal Dda binding peptide from the gp32 C-terminus was identified using surface plasmon resonance. The crystal structure of the Dda-peptide complex was consistent with the corresponding interaction in the gp32-Dda-ssDNA structure. A Dda-dependent DNA unwinding assay supported the structural conclusions and confirmed that the bound gp32 sequesters the ssDNA generated by Dda. The structure of the gp32-Dda-ssDNA complex, together with the known structure of the gp32 body, reveals the entire ssDNA binding surface of gp32. gp32-Dda-ssDNA complexes in the crystal are connected by the N-terminal region of one gp32 binding to an adjacent gp32, and this provides key insights into this interaction.

Characterization of Hibiscus Chlorotic Ringspot Virus-Derived vsiRNAs from Infected Hibiscus rosa-sinensis in China.

Lots of progress have been made about pathogen system of Hibiscus rosa-sinensis and hibiscus chlorotic ringspot virus (HCRSV), however, interactions between H. rosa-sinensis and HCRSV remain largely unknown. Hereon, firstly, HCRSV infection in H. rosa-sinensis from Zhangzhou city of China was confirmed by traditional electron microscopy, modern reverse transcription polymerase chain reaction and RNA-seq methods. Secondly, sequence feature analysis showed the full-length sequence of HCRSV-ZZ was 3,909 nucleotides (nt) in length and had a similar genomic structure with other carmovirus. It contains a 5' untranslated region (UTR), followed by seven open reading frames encoding for P28, P23, P81, P8, P9, P38, and P25, and the last a 3-terminal UTR. Thirdly, HCRSV- ZZ-derived vsiRNAs were identified and characterized for the first time from disease H. rosa-sinensis through sRNA-seq to reveal interactions between pathogen ant plant host. It was shown that the majority of HCRSV-ZZ-derived vsiRNAs were 21 nt, 22 nt, and 20 nt, with 21 nt being most abundant. The 5'-terminal nucleotide of HCRSV-ZZ vsiRNAs preferred U and C. HCRSV-ZZ vsiRNAs derived predominantly (72%) from the viral genome positive-strand RNA. The distribution of HCRSV-ZZ vsiRNAs along the viral genome is generally even, with some hot spots and cold spots forming in local regions. These hot spots and cold spots could be corresponded to the regions of stem loop secondary structures forming in HCRSV-ZZ genome by nucleotide paring. Taken together, our findings certify HCRSV infection in H. rosa-sinensis and provide an insight into interaction between HCRSV and H. rosa-sinensis and contribute to the prevention and treatment of this virus.

AlphaFold predictions of fold-switched conformations are driven by structure memorization

Recent work suggests that AlphaFold (AF)–a deep learning-based model that can accurately infer protein structure from sequence–may discern important features of folded protein energy landscapes, defined by the diversity and frequency of different conformations in the folded state. Here, we test the limits of its predictive power on fold-switching proteins, which assume two structures with regions of distinct secondary and/or tertiary structure. We find that (1) AF is a weak predictor of fold switching and (2) some of its successes result from memorization of training-set structures rather than learned protein energetics. Combining >280,000 models from several implementations of AF2 and AF3, a 35% success rate was achieved for fold switchers likely in AF’s training sets. AF2’s confidence metrics selected against models consistent with experimentally determined fold-switching structures and failed to discriminate between low and high energy conformations. Further, AF captured only one out of seven experimentally confirmed fold switchers outside of its training sets despite extensive sampling of an additional ~280,000 models. Several observations indicate that AF2 has memorized structural information during training, and AF3 misassigns coevolutionary restraints. These limitations constrain the scope of successful predictions, highlighting the need for physically based methods that readily predict multiple protein conformations.

Analysis of Correlation Effects of Double Mutations in Enzymes: A Revised Residual-Contact Network Clique Model.

The relationship between amino acid mutations and enzyme bioactivity is a significant challenge in modern bio-industrial applications. Despite many successful designs relying on complex correlations among mutations at different enzyme sites, the underlying mechanisms of these correlations still need to be explored. In this study, we introduced a revised version of the residual-contact network clique model to investigate the additive effect of double mutations based on the mutation occurrence topology, secondary structures, and physicochemical properties. The model was applied to a set of 182 double mutations reported in three extensively studied enzymes, and it successfully identified over 90% of additive double mutations and a majority of non-additive double mutations. The calculations revealed that the mutation additivity depends intensely on the studied mutation sites' topology and physicochemical properties. For example, double mutations on irregular secondary structure regions tend to be non-additive. Our method provides valuable tools for facilitating enzyme design and optimization. The code and relevant data are available at Github.

Insertion-Deletion Events Are Depleted in Protein Regions with Predicted Secondary Structure.

A fundamental goal in evolutionary biology and population genetics is to understand how selection shapes the fate of new mutations. Here, we test the null hypothesis that insertion-deletion (indel) events in protein-coding regions occur randomly with respect to secondary structures. We identified indels across 11,444 sequence alignments in mouse, rat, human, chimp, and dog genomes and then quantified their overlap with four different types of secondary structure-alpha helices, beta strands, protein bends, and protein turns-predicted by deep-learning methods of AlphaFold2. Indels overlapped secondary structures 54% as much as expected and were especially underrepresented over beta strands, which tend to form internal, stable regions of proteins. In contrast, indels were enriched by 155% over regions without any predicted secondary structures. These skews were stronger in the rodent lineages compared to the primate lineages, consistent with population genetic theory predicting that natural selection will be more efficient in species with larger effective population sizes. Nonsynonymous substitutions were also less common in regions of protein secondary structure, although not as strongly reduced as in indels. In a complementary analysis of thousands of human genomes, we showed that indels overlapping secondary structure segregated at significantly lower frequency than indels outside of secondary structure. Taken together, our study shows that indels are selected against if they overlap secondary structure, presumably because they disrupt the tertiary structure and function of a protein.

High frequency of transition to transversion ratio in the stem region of RNA secondary structure of untranslated region of SARS-CoV-2.

The propensity of nucleotide bases to form pairs, causes folding and the formation of secondary structure in the RNA. Therefore, purine (R): pyrimidine (Y) base-pairing is vital to maintain uniform lateral dimension in RNA secondary structure. Transversions or base substitutions between R and Y bases, are more detrimental to the stability of RNA secondary structure, than transitions derived from substitutions between A and G or C and T. The study of transversion and transition base substitutions is important to understand evolutionary mechanisms of RNA secondary structure in the 5' and 3' untranslated (UTR) regions of SARS-CoV-2. In this work, we carried out comparative analysis of transition and transversion base substitutions in the stem and loop regions of RNA secondary structure of SARS-CoV-2. We have considered the experimentally determined and well documented stem and loop regions of 5' and 3' UTR regions of SARS-CoV-2 for base substitution analysis. The secondary structure comprising of stem and loop regions were visualized using the RNAfold web server. The GISAID repository was used to extract base sequence alignment of the UTR regions. Python scripts were developed for comparative analysis of transversion and transition frequencies in the stem and the loop regions. The results of base substitution analysis revealed a higher transition (ti) to transversion (tv) ratio (ti/tv) in the stem region of UTR of RNA secondary structure of SARS-CoV-2 reported during the early stage of the pandemic. The higher ti/tv ratio in the stem region suggested the influence of secondary structure in selecting the pattern of base substitutions. This differential pattern of ti/tv values between stem and loop regions was not observed among the Delta and Omicron variants that dominated the later stage of the pandemic. It is noteworthy that the ti/tv values in the stem and loop regions were similar among the later dominant Delta and Omicron variant strains which is to be investigated to understand the rapid evolution and global adaptation of SARS-CoV-2. Our findings implicate the lower frequency of transversions than the transitions in the stem regions of UTRs of SARS-CoV-2. The RNA secondary structures are associated with replication, translation, and packaging, further investigations are needed to understand these base substitutions across different variants of SARS-CoV-2.

Long Non-Coding RNA-Cardiac-Inducing RNA 6 Mediates Repair of Infarcted Hearts by Inducing Mesenchymal Stem Cell Differentiation into Cardiogenic Cells through Cyclin-Dependent Kinase 1.

This study aims to investigate the induction effect of LncRNA-CIR6 on MSC differentiation into cardiogenic cells in vitro and in vivo. In addition to pretreatment with Ro-3306 (a CDK1 inhibitor), LncRNA-CIR6 was transfected into BMSCs and hUCMSCs using jetPRIME. LncRNA-CIR6 was further transfected into the hearts of C57BL/6 mice via 100 μL of AAV9-cTnT-LncRNA-CIR6-ZsGreen intravenous injection. After three weeks of transfection followed by AMI surgery, hUCMSCs (5 × 105/100 μL) were injected intravenously one week later. Cardiac function was evaluated using VEVO 2100 and electric mapping nine days after cell injection. Immunofluorescence, Evans blue-TTC, Masson staining, FACS, and Western blotting were employed to determine relevant indicators. LncRNA-CIR6 induced a significant percentage of differentiation in BMSCs (83.00 ± 0.58)% and hUCMSCs (95.43 ± 2.13)% into cardiogenic cells, as determined by the expression of cTnT using immunofluorescence and FACS. High cTNT expression was observed in MSCs after transfection with LncRNA-CIR6 by Western blotting. Compared with the MI group, cardiac contraction and conduction function in MI hearts treated with LncRNA-CIR6 or combined with MSCs injection groups were significantly increased, and the areas of MI and fibrosis were significantly lower. The transcriptional expression region of LncRNA-CIR6 was on Chr17 from 80209290 to 80209536. The functional region of LncRNA-CIR6 was located at nucleotides 0-50/190-255 in the sequence. CDK1, a protein found to be related to the proliferation and differentiation of cardiomyocytes, was located in the functional region of the LncRNA-CIR6 secondary structure (from 0 to 17). Ro-3306 impeded the differentiation of MSCs into cardiogenic cells, while MSCs transfected with LncRNA-CIR6 showed a high expression of CDK1. LncRNA-CIR6 mediates the repair of infarcted hearts by inducing MSC differentiation into cardiogenic cells through CDK1.

The Glucocorticoid Receptor’s tau1c Activation Domain 35 Years on—Making Order out of Disorder

Almost exactly 35 years after starting to work with the human glucocorticoid receptor (hGR), it is interesting for me to re-evaluate the data and results obtained in the 1980s–1990s with the benefit of current knowledge. What was understood then and how can modern perspectives increase that understanding? The hGR’s tau1c activation domain that we delineated was an enigmatic protein domain. It was apparently devoid of secondary and tertiary protein structures but nonetheless maintained gene activation activity in the absence of other hGR domains, not only in human cells but also in yeast, which is evolutionarily very divergent from humans and which does not contain hGR or other nuclear receptors. We now know that the basic machinery of cells is much more conserved across evolution than was previously thought, so the hGR’s tau1c domain was able to utilise transcription machinery components that were conserved between humans and yeast. Further, we can now see that structure–function aspects of the tau1c domain conform to a general mechanistic framework, such as the acidic exposure model, that has been proposed for many activation domains. As for many transcription factor activation domains, it is now clear that tau1c activity requires regions of transient secondary structure. We now know that there is a tendency for positive Darwinian selection to target intrinsically disordered protein domains. It will be interesting to study the distribution and nature of the many single nucleotide variants of the hGR in this respect.

Influence of the mRNA initial region on protein production: a case study using recombinant detoxified pneumolysin as a model.

Recombinant proteins are of great importance in modern society, mostly as biopharmaceutical products. However, challenging and complex processes with low production yield are major drawbacks. Normally, the optimization to overcome these obstacles is focused on bioreactor and purification processes, and the biomolecular aspects are neglected, seen as less important. In this work, we present how the 5' mRNA secondary structure region can be relevant for translation and, therefore, protein production. For this, Escherichia coli BL21(DE3) clones, producing recombinant detoxified pneumolysin (PdT) with and without the N-terminal His-tag, were cultivated in 10-L bioreactors. Another version of the pdt gene (version 2) with synonymous changes in the 5'-end nucleotide sequence was also obtained. Protein production, plasmid stability, carbon sources, and acetic acid were quantified during the cultures. Furthermore, in silico mRNA analyses were performed using TIsigner and RNAfold. The results showed that the His-tag presence at the N-terminus generated a minimum 1.5-fold increase in target protein synthesis, which was explained by the in silico mRNA analyses that returned an mRNA secondary structure easier to translate and, therefore, higher protein production than without the His-tag. The pdt gene version 2 showed lower 5' mRNA opening energy than version 1, allowing higher PdT production even without a tag. This work reveals that simple mRNA analyses during heterologous gene design and production steps can help reach high-recombinant protein titers in a shorter time than using only traditional bioprocess optimization strategies.

GC heterogeneity reveals sequence-structures evolution of angiosperm ITS2

BackgroundDespite GC variation constitutes a fundamental element of genome and species diversity, the precise mechanisms driving it remain unclear. The abundant sequence data available for the ITS2, a commonly employed phylogenetic marker in plants, offers an exceptional resource for exploring the GC variation across angiosperms.ResultsA comprehensive selection of 8666 species, comprising 165 genera, 63 families, and 30 orders were used for the analyses. The alignment of ITS2 sequence-structures and partitioning of secondary structures into paired and unpaired regions were performed using 4SALE. Substitution rates and frequencies among GC base-pairs in the paired regions of ITS2 were calculated using RNA-specific models in the PHASE package. The results showed that the distribution of ITS2 GC contents on the angiosperm phylogeny was heterogeneous, but their increase was generally associated with ITS2 sequence homogenization, thereby supporting the occurrence of GC-biased gene conversion (gBGC) during the concerted evolution of ITS2. Additionally, the GC content in the paired regions of the ITS2 secondary structure was significantly higher than that of the unpaired regions, indicating the selection of GC for thermodynamic stability. Furthermore, the RNA substitution models demonstrated that base-pair transformations favored both the elevation and fixation of GC in the paired regions, providing further support for gBGC.ConclusionsOur findings highlight the significance of secondary structure in GC investigation, which demonstrate that both gBGC and structure-based selection are influential factors driving angiosperm ITS2 GC content.

Babesia bovis RON2 binds to bovine erythrocytes through a highly conserved epitope

B. bovis invasion of bovine erythrocytes requires tight junction formation involving AMA-1/RON2 complex interaction. RON2 has been considered a vaccine candidate since antibodies targeting the protein can inhibit parasite invasion of target cells; however, the mechanism controlling B. bovis RON2 interaction with red blood cells is not yet fully understood. This study was thus aimed at identifying B. bovis RON2 protein regions associated with interaction with bovine erythrocytes. Natural selection analysis of the ron2 gene identified predominantly negative selection signals in the C-terminal region. Interestingly, protein-cell and competition assays highlighted the RON2-C region’s role in peptide 42918-mediated erythrocyte binding, probably to a sialoglycoprotein receptor. This peptide (1218SFIMVKPPALHCVLKPVETL1237) lies within an intrinsically disordered region of the RON2 secondary structure flanked by two helical residues. The study provides, for the first time, valuable insights into RON2’s role in interaction with its target cells. Future studies are required for studying the peptide’s potential as an anti-B. bovis vaccine component.

Revisiting structural organization of proteins at high temperature from a network perspective

Interactions between distantly placed amino acids in the primary chain (long-range) play a very crucial role in the formation and stabilization of the tertiary structure of a protein, while interactions between closely placed amino acids in the primary chain (short-range) mostly stabilize the secondary structures. Every protein needs to maintain marginal stability in order to perform its physiological functions in its native environment. The requirements for this stability in mesophilic and thermophilic proteins are different. Thermophilic proteins need to form more interactions as well as more stable interactions to survive in the extreme environment, they live in. Here, we aim to find out how the interacting amino acids in three-dimensional space are positioned in the primary chains in thermophilic and mesophilic. How does this arrangement help thermophiles to maintain their structural integrity at high temperatures? Working on a dataset of 1560 orthologous pairs we perceive that thermophiles are not only enriched with long-range interactions, they feature bigger connected clusters and higher network densities compared to their mesophilic orthologs, at higher interaction strengths between the amino acids. Moreover, we have observed the enrichment of different types of interactions at different secondary structural regions.

Multiplexed long-read plasmid validation and analysis using OnRamp.

Recombinant plasmid vectors are versatile tools that have facilitated discoveries in molecular biology, genetics, proteomics, and many other fields. As the enzymatic and bacterial processes used to create recombinant DNA can introduce errors, sequence validation is an essential step in plasmid assembly. Sanger sequencing is the current standard for plasmid validation; however, this method is limited by an inability to sequence through complex secondary structure and lacks scalability when applied to full-plasmid sequencing of multiple plasmids owing to read-length limits. Although high-throughput sequencing does provide full-plasmid sequencing at scale, it is impractical and costly when used outside of library-scale validation. Here, we present Oxford nanopore-based rapid analysis of multiplexed plasmids (OnRamp), an alternative method for routine plasmid validation that combines the advantages of high-throughput sequencing's full-plasmid coverage and scalability with Sanger's affordability and accessibility by leveraging nanopore's long-read sequencing technology. We include customized wet-laboratory protocols for plasmid preparation along with a pipeline designed for analysis of read data obtained using these protocols. This analysis pipeline is deployed on the OnRamp web app, which generates alignments between actual and predicted plasmid sequences, quality scores, and read-level views. OnRamp is designed to be broadly accessible regardless of programming experience to facilitate more widespread adoption of long-read sequencing for routine plasmid validation. Here we describe the OnRamp protocols and pipeline and show our ability to obtain full sequences from pooled plasmids while detecting sequence variation even in regions of high secondary structure at less than half the cost of equivalent Sanger sequencing.

Description of Neochlorella semenenkoi gen. et. sp. nov. (Chlorophyta, Trebouxiophyceae), a Novel Chlorella-like Alga with High Biotechnological Potential

Despite many publications about Chlorella-like algae, their reliable and accurate identification is still difficult due to their simplicity and high phenotypic plasticity. The molecular approach has revolutionized our understanding of the diversity of ’small green balls’, and a natural classification of this group is currently being developed. This work is aimed at providing a detailed study of the phylogenetic position, morphology, ultrastructure, and physiology of the biotechnologically remarkable Chlorella-like strain IPPAS C-1210. Based on the SSU–ITS1–5.8S–ITS2 phylogeny, genetic distances, and the presence of compensatory base changes (CBCs) in ITS1 and conserved regions of ITS2 secondary structures, we describe a new genus, Neochlorella, with IPPAS C-1210 as the authentic strain of the type species, N. semenenkoi gen. and sp. nov. In addition, we justify the reassignment of the strain C. thermophila ITBB HTA 1–65 into N. thermophila comb. nov. The distinctive ultrastructural and physiological traits of the new species are discussed.

Periodontal disease in chronic kidney disease patients: salivomics by Fourier-transform infrared spectroscopy.

It has been reported that 58% of individuals with chronic kidney disease (CKD) have moderate to advanced periodontitis due to alterations of pH and biochemical composition in the saliva. In fact, the composition of this important biofluid may be modulated by systemic disorders. Here we investigate the micro-reflectance Fourier-transform infrared spectroscopy (FTIR) spectra of saliva that CKD patients submitted to periodontal treatment, aiming to identify spectral biomarkers of kidney disease evolution and the effectiveness of periodontal treatment, proposing possible biomarkers of disease evolution. Saliva from 24 CKD patients-stage-5 men, 29 to 64years old-was evaluated in (i)patients starting periodontal treatment; (ii)patients 30days after periodontal treatment; and (iii)patients 90days after periodontal treatment. Our findings indicated that there are statistically relevant changes among the groups after 30 and 90days of periodontal treatment, when considering the overall spectra in the fingerprint region (800-1800cm-1). The key bands presenting good prediction power (area under the receiver operating characteristic curve >0.70) were related to poly (ADP-ribose) polymerase (PARP) conjugated to DNA at 883, 1031, and 1060cm-1 (carbohydrates at 1043 and 1049cm-1) and triglycerides (1461cm-1). Interestingly when analyzing the derivative spectra in the secondary structure region (1590-1700cm-1), we detected over-expression of the β-sheet class of secondary structures in 90days of periodontal treatment, possibly related to over-expression of human B-defensins. Conformational changes in ribose sugar in this region corroborate the interpretation concerning PARP detection. To our knowledge, PARP was detected for the first time in saliva samples of stage-5 CKD patients by FTIR. All observed changes were correctly interpreted in terms of intensive apoptosis and dyslipidemia due to kidney disease progression. Biomarkers due to CKD predominate in saliva, and the relative improvement in the periodontal state did not cause remarkable changes in the spectra of saliva.

Cellular APOBEC3A deaminase drives mutations in the SARS-CoV-2 genome.

The number of genetic variations in the SARS-CoV-2 genome has been increasing primarily due to continuous viral mutations. Here, we report that the human APOBEC3A (A3A) cytidine deaminase plays a critical role in the induction of C-to-U substitutions in the SARS-CoV-2 genome. Bioinformatic analysis of the chronological genetic changes in a sequence database indicated that the largest UC-to-UU mutation signature, consistent with APOBEC-recognized nucleotide motifs, was predominant in single-stranded RNA regions of the viral genome. In SARS-CoV-2-infected cells, exogenous expression of A3A but not expression of other APOBEC proteins induced UC-to-UU mutations in viral RNA (vRNA). Additionally, the mutated C bases were often located at the tips in bulge or loop regions in the vRNA secondary structure. Interestingly, A3A mRNA expression was drastically increased by interferons (IFNs) and tumour necrosis factor-α (TNF-α) in epithelial cells derived from the respiratory system, a site of efficient SARS-CoV-2 replication. Moreover, the UC-to-UU mutation rate was increased in SARS-CoV-2 produced from lung epithelial cells treated with IFN-ß and TNF-α, but not from CRISPR/Cas9-based A3A knockout cells. Collectively, these findings demonstrate that A3A is a primary host factor that drives mutations in the SARS-CoV-2 RNA genome via RNA editing.

Improved NMR-data-compliant protein structure modeling captures context-dependent variations and expands the scope of functional inference.

Nuclear magnetic resonance (NMR) spectroscopy can reveal conformational states of a protein in physiological conditions. However, sparsely available NMR data for a protein with large degrees of freedom can introduce structural artifacts in the built models. Currently used state-of-the-art methods deriving protein structure and conformation from NMR deploy molecular dynamics (MD) coupled with simulated annealing for building models. We provide an alternate graph-based modeling approach, where we first build substructures from NMR-derived distance-geometry constraints combined in one shot to form the core structure. The remaining molecule with inadequate data is modeled using a hybrid approach respecting the observed distance-geometry constraints. One-shot structure building is rarely undertaken for large and sparse data systems, but our data-driven bottom-up approach makes this uniquely feasible by suitable partitioning of the problem. A detailed comparison of select models with state-of-art methods reveals differences in the secondary structure regions wherein the correctness of our models is confirmed by NMR data. Benchmarking of 106 protein-folds covering 38-282 length structures shows minimal experimental-constraint violations while conforming to other structure quality parameters such as the proper folding, steric clash, and torsion angle violation based on Ramachandran plot criteria. Comparative MD studies using select protein models from a state-of-art method and ours under identical experimental parameters reveal distinct conformational dynamics that could be attributed to protein structure-function. Our work is thus useful in building enhanced NMR-evidence-based models that encapsulate the contextual secondary and tertiary structure variations present during the experimentation and expand the scope of functional inference.

Conformational ensemble of amyloid-forming semenogelin 1 peptide SEM1(68–107) by NMR spectroscopy and MD simulations

SEM1(68–107) is a peptide corresponding to the region of semenogelin 1 protein from 68 to 107 amino acid position. SEM1(68–107) is an abundant component of semen, which participates in HIV infection enhanced by amyloid fibrils forming. To understand the causes influencing amyloid fibril formation, it is necessary to determine the spatial structure of SEM1(68–107). It was shown that the determination of SEM1(68–107) structure is complicated by the non-informative NMR spectra due to the high intramolecular mobility of peptides. The complementary approach based on the geometric restrictions of individual peptide fragments and molecular modeling was used for the determination of the spatial structure of SEM1(68–107). The N- (SEM1(68–85)) and C-terminuses (SEM1(86–107)) of SEM1(68–107) were chosen as two individual peptide fragments. SEM1(68–85) and SEM1(86–107) structures were established with NMR and circular dichroism CD spectroscopies. These regions were used as geometric restraints for the SEM1(68–107) structure modeling. Even though most of the SEM1(68–107) peptide is unstructured, our detailed analysis revealed the following structured elements: N-terminus (70His-84Gln) forms an α-helix, (86Asp-94Thr) and (101Gly-103Ser) regions fold into 310-helixes. The absence of a SEM1(68–107) rigid conformation leads to instability of these secondary structure regions. The calculated SEM1(68–107) structure is in good agreement with experimental values of hydrodynamic radius and dihedral angles obtained by NMR spectroscopy. This testifies the adequacy of a combined approach based on the use of peptide fragment structures for the molecular modeling formation of full-size peptide spatial structure.

MrParse: finding homologues in the PDB and the EBI AlphaFold database for molecular replacement and more.

Crystallographers have an array of search-model options for structure solution by molecular replacement (MR). The well established options of homologous experimental structures and regular secondary-structure elements or motifs are increasingly supplemented by computational modelling. Such modelling may becarried out locally or may use pre-calculated predictions retrieved from databases such as the EBI AlphaFold database. MrParse is a new pipeline to help to streamline the decision process in MR by consolidating bioinformatic predictions in one place. When reflection data are provided, MrParse can rank any experimental homologues found using eLLG, which indicates the likelihood that a given search model will work in MR. Inbuilt displays of predicted secondary structure, coiled-coil and transmembrane regions further inform the choice of MR protocol. MrParse can also identify and rank homologues in the EBI AlphaFold database, a function that will also interest other structural biologists and bioinformaticians.

Variable and Conserved Regions of Secondary Structure in the β-Trefoil Fold: Structure Versus Function

β-trefoil proteins exhibit an approximate C3 rotational symmetry. An analysis of the secondary structure for members of this diverse superfamily of proteins indicates that it is comprised of remarkably conserved β-strands and highly-divergent turn regions. A fundamental “minimal” architecture can be identified that is devoid of heterogenous and extended turn regions, and is conserved among all family members. Conversely, the different functional families of β-trefoils can potentially be identified by their unique turn patterns (or turn “signature”). Such analyses provide clues as to the evolution of the β-trefoil family, suggesting a folding/stability role for the β-strands and a functional role for turn regions. This viewpoint can also guide de novo protein design of β-trefoil proteins having novel functionality.