Structure and function of engineered stromal cell-derived factor-1α

To design biologically active, collagen-based scaffolds for bone tissue engineering, we have synthesized chimeric proteins consisting of stromal cell-derived factor-1α (SDF) and the von Willebrand factor A3 collagen-binding domain (CBD). The chimeric proteins were used to evaluate the effect of domain linkage and its order on the structure and function of the SDF and CBD. The structure of the chimeric proteins was analyzed by circular dichroism spectroscopy, while functional analysis was performed by a cell migration assay for the SDF domain and a collagen-binding assay for the CBD domain. Furthermore, computational structural prediction was conducted for the chimeric proteins to examine the consistency with the results of structural and functional analyses. Our structural and functional analyses as well as structural prediction revealed that linking two domains can affect their functions. However, their order had minor effects on the three-dimensional structure of CBD and SDF in the chimeric proteins.

Molecular basis of Climp63-mediated ER lumen spacing

The width of cisternal structures in the endoplasmic reticulum (ER) is maintained by ER-resident protein Climp63. Self-association of the Climp63 luminal domain (LD), even though moderate, plays a key role in shaping ER sheets. However, the molecular basis of luminal spacing remains elusive. Here, we analyze the homotypic interactions of the Climp63 LD using AI-predicted structures. The LD is highly alpha-helical, with a flexible leading helix followed by a five-helix bundle (5HB). Charge-based trans associations are formed between the tip of the 5HB and the C-terminus of the LD, consistent with generating a width of ∼50 nm for ER sheets. The leading helix of the LD is dispensable for homotypic interactions, but packing of the 5HB regulates self-association. The density of Climp63, likely reflecting the strength of cis interactions, influences the ER width, which is maintained by trans interactions. These results indicate that a general principle in maintaining membrane tethering is multi-modular self-association.

Identification of SEC14 like lipid binding 2(SEC14L2) sequence and expression profiles in the Chinese tree shrew (Tupaia belangeri chinensis)

BACKGROUND

The product of the SEC14L2 (SEC14 Like Lipid Binding 2) gene belongs to a family of lipid-binding proteins including Sec14p, alpha-tocopherol transfer protein, and cellular retinol-binding protein. SEC14L2 expression enables replication of clinical hepatitis C virus (HCV) isolates in several hepatoma cell lines, and mutations in SEC14L2 may enhance HCV replication in vitro. The Chinese tree shrew (Tupaia belangeri chinensis) is a potential animal model for studying HCV replication, however, the cDNA sequence, protein structure, and expression of the Chinese tree shrew SEC14L2 gene have yet to be characterized.

METHODS AND RESULTS

In the present study, we cloned the full-length cDNA sequence of the SEC14L2 in the Chinese tree shrew by using rapid amplification of cDNA ends technology. This led us to determine that, this is 2539 base pairs (bp) in length, the open reading frame sequence is 1212 bp, and encodes 403 amino acids. Following this, we constructed a phylogenetic tree based on SEC14L2 molecules from various species and compared SEC14L2 amino acid sequence with other species. This analysis indicated that the Chinese tree shrew SEC14L2 protein (tsSEC14L2) has 96.28% amino acid similarity to the human protein, and is more closely related to the human protein than either mouse or rat protein. The Chinese tree shrew SEC14L2 mRNA was detected in all tissues, and showed highest expression levels in the pancreas, small intestine and trachea, however the tsSEC14L2 protein abundance was highest in the liver and small intestine.

CONCLUSION

The Chinese tree shrew SEC14L2 gene was closer in evolutionary relation to humans and non-human primates and expression of the tsSEC14L2 protein was highest in the liver and small intestine. These results may provide useful information for tsSEC14L2 function in HCV infection.

In depth analysis of Cyprus-specific mutations of SARS-CoV-2 strains using computational approaches

BACKGROUND

This study aims to characterize SARS-CoV-2 mutations which are primarily prevalent in the Cypriot population. Moreover, using computational approaches, we assess whether these mutations are associated with changes in viral virulence.

METHODS

We utilize genetic data from 144 sequences of SARS-CoV-2 strains from the Cypriot population obtained between March 2020 and January 2021, as well as all data available from GISAID. We combine this with countries' regional information, such as deaths and cases per million, as well as COVID-19-related public health austerity measure response times. Initial indications of selective advantage of Cyprus-specific mutations are obtained by mutation tracking analysis. This entails calculating specific mutation frequencies within the Cypriot population and comparing these with their prevalence world-wide throughout the course of the pandemic. We further make use of linear regression models to extrapolate additional information that may be missed through standard statistical analysis.

RESULTS

We report a single mutation found in the ORF1ab gene (nucleotide position 18,440) that appears to be significantly enriched within the Cypriot population. The amino acid change is denoted as S6059F, which maps to the SARS-CoV-2 NSP14 protein. We further analyse this mutation using regression models to investigate possible associations with increased deaths and cases per million. Moreover, protein structure prediction tools show that the mutation infers a conformational change to the protein that significantly alters its structure when compared to the reference protein.

CONCLUSIONS

Investigating Cyprus-specific mutations for SARS-CoV-2 can lead to a better understanding of viral pathogenicity. Researching these mutations can generate potential links between viral-specific mutations and the unique genomics of the Cypriot population. This can not only lead to important findings from which to battle the pandemic on a national level, but also provide insights into viral virulence worldwide.

De novo post-SELEX optimization of a G-quadruplex DNA aptamer binding to marine toxin gonyautoxin 1/4

Ligand-binding aptamers obtained by SELEX (Systematic Evolution of Ligands by EXponential enrichment) often have low affinity or/and specificity, and post-SELEX optimization is usually needed. Due to experimental difficulty in determining three-dimensional (3D) structures of aptamer-ligand complexes, there are few structure-guided methods for rational post-SELEX optimization. Here, we employed a de novo optimization approach to engineer high-affinity variants for a G-quadruplex (GQ) aptamer (GO18-T-d) that specifically binds to marine toxin gonyautoxin 1/4 (GTX1/4). First, temperature-dependent modeling was carried out to predict the atomic structure of GO18-T-d. Then, to identify key bases for the optimization, spontaneous binding simulations were performed to reveal the complex structure of GO18-T-d with GTX1/4. Finally, binding energy analysis was conducted to evaluate the designed variants for high affinity. We predicted that GO18-T-d has the typical parallel GQ topology, consistent with circular dichroism (CD) measurements. Our simulations showed that the 5′-end of GO18-T-d hinders the GTX1/4 movement toward the binding pocket, leading to a designed variant that removes the first 5 nucleotides at the 5′-end. Microscale thermophoresis (MST) experiments verified that the binding affinity of the engineered aptamer increases by ~20 folds. Thus, this study not only provides a high-affinity variant of GO18-T-d, but also suggests that our computational approach is useful for the structure-guided optimization of GQ aptamers.

In silico characterization of class II plant defensins from Arabidopsis thaliana

Defensins comprise a polyphyletic group of multifunctional defense peptides. Cis-defensins, also known as cysteine stabilized αβ (CSαβ) defensins, are one of the most ancient defense peptide families. In plants, these peptides have been divided into two classes, according to their precursor organization. Class I defensins are composed of the signal peptide and the mature sequence, while class II defensins have an additional C-terminal prodomain, which is proteolytically cleaved. Class II defensins have been described in Solanaceae and Poaceae species, indicating this class could be spread among all flowering plants. Here, a search by regular expression (RegEx) was applied to the Arabidopsis thaliana proteome, a model plant with more than 300 predicted defensin genes. Two sequences were identified, A7REG2 and A7REG4, which have a typical plant defensin structure and an additional C-terminal prodomain. TraVA database indicated they are expressed in flower, ovules and seeds, and being duplicated genes, this indicates they could be a result of a subfunctionalization process. The presence of class II defensin sequences in Brassicaceae and Solanaceae and evolutionary distance between them suggest class II defensins may be present in other eudicots. Discovery of class II defensins in other plants could shed some light on flower, ovules and seed physiology, as this class is expressed in these locations.

Individually double minimum-distance definition of protein-RNA binding residues and application to structure-based prediction

Identifying protein-RNA binding residues is essential for understanding the mechanism of protein-RNA interactions. So far, rigid distance thresholds are commonly used to define protein-RNA binding residues. However, after investigating 182 non-redundant protein-RNA complexes, we find that it would be unsuitable for a certain amount of complexes since the distances between proteins and RNAs vary widely. In this work, a novel definition method was proposed based on a flexible distance cutoff. This method can fully consider the individual differences among complexes by setting a variable tolerance limit of protein-RNA interactions, i.e. the double minimum-distance by which different distance thresholds are achieved for different complexes. In order to validate our method, a comprehensive comparison between our flexible method and traditional rigid methods was implemented in terms of interface structure, amino acid composition, interface area and interaction force, etc. The results indicate that this method is more reasonable because it incorporates the specificity of different complexes by extracting the important residues lost by rigid distance methods and discarding some redundant residues. Finally, to further test our double minimum-distance definition strategy, we developed a classifier to predict those binding sites derived from our new method by using structural features and a random forest machine learning algorithm. The model achieved a satisfactory prediction performance and the accuracy on independent data sets reaches to 85.0%. To the best of our knowledge, it is the first prediction model to define positive and negative samples using a flexible cutoff. So the comparison analysis and modeling results have demonstrated that our method would be a very promising strategy for more precisely defining protein-RNA binding sites.

Structural insights and characterization of human Npas4 protein

Npas4 is an activity dependent transcription factor which is responsible for gearing the expression of target genes involved in neuro-transmission. Despite the importance of Npas4 in many neuronal diseases, the tertiary structure of Npas4 protein along with its physico-chemical properties is limited. In the current study, first we perfomed the phylogenetic analysis of Npas4 and determined the content of hydrophobic, flexible and order-disorder promoting amino acids. The protein binding regions, post-translational modifications and crystallization propensity of Npas4 were predicted through different in-silico methods. The three dimensional model of Npas4 was predicted through LOMET, SPARSKS-X, I-Tasser, RaptorX, MUSTER and Pyhre and the best model was selected on the basis of Ramachandran plot, PROSA, and Qmean scores. The best model was then subjected to further refinement though MODREFINER. Finally the interacting partners of Npas4 were identified through STRING database. The phylogenetic analysis showed the human Npas4 gene to be closely related to other primates such as chimpanzees, monkey, gibbon. The physiochemical properties of Npas4 showed that it is an intrinsically disordered protein with N-terminal ordered region. The post-translational modification analyses indicated absence of acetylation and mannosylation sites. Three potential phosphorylation sites (S108, T130 and T136) were found in PAS A domain whilst a single phosphorylation site (S273) was present in PAS B domain. The predicted tertiary structure of Npas4 showed that bHLH domain and PAS domain possess tertiary structures while the rest of the protein exhibited disorder property. Protein-protein interaction analysis revealed NPas4 interaction with various proteins which are mainly involved in nuclear trafficking of proteins to cytoplasm, activity regulated gene transcription and neurodevelopmental disorders. Moreover the analysis also highlighted the direct relation to proteins involved in promoting neuronal survival, plasticity and cAMP responsive element binding protein proteins. The current study helps in understanding the physicochemical properties and reveals the neuro-modulatory role of Npas4 in crucial pathways involved in neuronal survival and neural signalling hemostasis.

Novel PSEN1 G209A mutation in early-onset Alzheimer dementia supported by structural prediction

Background

Three main genes are described as causative genes for early-onset Alzheimer dementia (EOAD): APP, PSEN1 and PSEN2. We describe a woman with EOAD had a novel PSEN1 mutation.

Case report

A 54-year-old right-handed woman presented 12-year history of progressive memory decline. She was clinically diagnosed as familial Alzheimer's disease due to a PSEN1 mutation.

One of two daughters also has the same mutation, G209A in the TM-IV of PS1 protein. Her mother had unspecified dementia that began at the age of 40s. PolyPhen2 and SIFT prediction suggested that G209A might be a damaging variant with high scores. 3D modeling revealed that G209A exchange could result significant changes in the PS1 protein.

Conclusion

We report a case of EOAD having probable novel PSEN1 (G209A) mutation verified with structural prediction.