Combined Displacement and Angle Sensor with Ultra-High Compactness Based on Self-Imaging Effect of Optical Microgratings.

In this paper, an ultracompact combined sensor for displacement and angle-synchronous measurement is proposed based on the self-imaging effect of optical microgratings. Using a two-grating structure, linear and angular displacement can be measured by detecting the change of phase and amplitude of the optical transmission, respectively, within one single structure in the meantime. The optically transmitted properties of the two-grating structure are investigated in both theory and simulation. Simulated results indicate that optical transmission changes in a sinusoidal relationship to the input linear displacement. Meanwhile, the amplitude of the curve decreases with an input pitch angle, indicating the ability for synchronous measurement within one single compact structure. The synchronous measurement of the linear displacement and the angle is also demonstrated experimentally. The results show a resolution down to 4 nm for linear displacement measurement and a maximum sensitivity of 0.26 mV/arcsec within a range of ±1° for angle measurement. Benefiting from a simple common-path structure without using optical components, including reflectors and polarizers, the sensor shows ultra-high compactness for multiple-degrees-of-freedom measuring, indicating the great potential for this sensor in fields such as integrated mechanical positioning and semiconductor fabrication.

Prediction of folding patterns for intrinsic disordered protein.

The conformation flexibility of natural protein causes both complexity and difficulty to understand the relationship between structure and function. The prediction of intrinsically disordered protein primarily is focusing on to disclose the regions with structural flexibility involving relevant biological functions and various diseases. The order of amino acids in protein sequence determines possible conformations, folding flexibility and biological function. Although many methods provided the information of intrinsically disordered protein (IDP), but the results are mainly limited to determine the locations of regions without knowledge of possible folding conformations. Here, the developed protein folding fingerprint adopted the protein folding variation matrix (PFVM) to reveal all possible folding patterns for the intrinsically disordered protein along its sequence. The PFVM integrally exhibited the intrinsically disordered protein with disordering regions, degree of disorder as well as folding pattern. The advantage of PFVM will not only provide rich information for IDP, but also may promote the study of protein folding problem.

Impact of alternating amino acid sequences on beta-amyloid-induced neurotoxicity and neuroinflammation in Alzheimer's disease.

Alzheimer's disease (AD) is a chronic neurodegenerative disease and the common cause of dementia. The aggregation of beta-amyloid (Aß peptide) leading to excessive neuroinflammation is considered to be the neuropathological hallmark of AD, although the precise mechanisms remain unclear. Oligomerization of these peptides may be associated with their 42 amino acid residue arrangement. However, the process of amyloid plaque formation is still not well known. The protein folding-shape code (PFSC) method is a powerful tool to analyze protein confirmation which could exhibit the local structural folding features in detail. In our study, we utilized the PFSC to analyze Aß peptide in humans and mice and found that mouse Aß42 is less likely to polymerize than human's. Subsequently, we used the PFSC method to analyze the 42 amino acids of Aß, transformed some species in human Aß42 and obtained 7 mutants. We showed that it was not easy to aggregate Aß in mutants. Herein, inflammatory responses were decreased, as indicated by the expression of cytokines. We confirmed that the neurotoxicity of mutant human Aß was decreased by preventing peptide aggregation. This may represent a new therapeutic approach for treating AD.

Severe Acute Respiratory Syndrome Coronavirus 2 Epitope Mapping for Antibodies.

Epitope mapping of the interactions between severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and Abs is challenging because of complexity in protein three-dimensional structures. Protein structure fingerprint technology was applied for epitope mapping of 44 SARS-CoV-2 Abs with three-dimensional structure complexes. The results defined how the epitopes were distributed on SARS-CoV-2 and how the patterns of six CDRs from Abs participated in neutralization. Also, the residue-residue recognition revealed that certain residues had higher frequencies on the interfaces between SARS-CoV-2 and Abs, and the activity correlated with the physicochemical properties of the residues at the interface. Thus, epitope mapping provides significant lead information for development of epitope-based designs for Abs, vaccines, and diagnostic reagents. This is a bioinformatics project of structural data analysis; no animals or cells were used.

Comprehensive folding variations for protein folding.

The revelation of protein folding is a challenging subject in both discovery and description. Except for acquirement of accurate 3D structure in protein stable state, another big hurdle is how to discover structural flexibility for protein innate character. Even if a huge number of flexible conformations are known, difficulty is how to represent these conformations. A novel approach, protein structure fingerprint, has been developed to expose the comprehensive local folding variations, and then construct folding conformations for entire protein. The backbone of five amino acid residues was identified as a universal folden, and then a set of Protein Folding Shape Code (PFSC) was derived for completely covering folding space in alphabetic description. Sequentially, a database was created to collect all possible folding shapes of local folding variations for all permutation of five amino acids. Successively, Protein Folding Variation Matrix (PFVM) assembled all possible local folding variations along sequence for a protein, which possesses several prominent features. First, it showed the fluctuation with certain folding patterns along sequence which revealed how the protein folding was related the order of amino acids in sequence. Second, all folding variations for an entire protein can be simultaneously apprehended at a glance within PFVM. Third, all conformations can be determined by local folding variations from PFVM, so total number of conformations is no longer ambiguous for any protein. Finally, the most possible folding conformation and its 3D structure can be acquired according PFVM for protein structure prediction. Therefore, the protein structure fingerprint approach provides a significant means for investigation of protein folding problem.

High-Throughput Prediction and Design of Novel Conopeptides for Biomedical Research and Development.

Cone snail venoms have been considered a valuable treasure for international scientists and businessmen, mainly due to their pharmacological applications in development of marine drugs for treatment of various human diseases. To date, around 800 Conus species are recorded, and each of them produces over 1,000 venom peptides (termed as conopeptides or conotoxins). This reflects the high diversity and complexity of cone snails, although most of their venoms are still uncharacterized. Advanced multiomics (such as genomics, transcriptomics, and proteomics) approaches have been recently developed to mine diverse Conus venom samples, with the main aim to predict and identify potentially interesting conopeptides in an efficient way. Some bioinformatics techniques have been applied to predict and design novel conopeptide sequences, related targets, and their binding modes. This review provides an overview of current knowledge on the high diversity of conopeptides and multiomics advances in high-throughput prediction of novel conopeptide sequences, as well as molecular modeling and design of potential drugs based on the predicted or validated interactions between these toxins and their molecular targets.

Exposing structural variations in SARS-CoV-2 evolution.

The mutation of SARS-CoV-2 influences viral function as residue replacements affect both physiochemical properties and folding conformations. Although a large amount of data on SARS-CoV-2 is available, the investigation of how viral functions change in response to mutations is hampered by a lack of effective structural analysis. Here, we exploit the advances of protein structure fingerprint technology to study the folding conformational changes induced by mutations. With integration of both protein sequences and folding conformations, the structures are aligned for SARS-CoV to SARS-CoV-2, including Alpha variant (lineage B.1.1.7) and Delta variant (lineage B.1.617.2). The results showed that the virus evolution with change in mutational positions and physicochemical properties increased the affinity between spike protein and ACE2, which plays a critical role in coronavirus entry into human cells. Additionally, these structural variations impact vaccine effectiveness and drug function over the course of SARS-CoV-2 evolution. The analysis of structural variations revealed how the coronavirus has gradually evolved in both structure and function and how the SARS-CoV-2 variants have contributed to more severe acute disease worldwide.

Exposing Structural Variations in SARS-CoV-2 Evolution.

The mutation of SARS-CoV-2 influences viral function as residue replacements affect both physiochemical properties and folding conformations. Although a large amount of data on SARS-CoV-2 is available, the investigation of how viral functions change in response to mutations is hampered by a lack of effective structural analysis. Here, we exploit advances in protein structure fingerprint technology to study the folding conformational changes induced by mutations. With the integration of both protein sequences and folding conformations and alignments of SARS-CoV to SARS-CoV-2, the UK variant and India variant, we found that structural variations in the spike protein at the binding interface interacting with ACE2 play a critical role in coronavirus entry into human cells. Additionally, the structural variations impact vaccine effectiveness and drug function over the course of SARS-CoV-2 evolution. The analysis of structural variations revealed how the coronavirus has gradually evolved in both structure and function and how the SARS-CoV-2 variants have contributed to more severe acute disease worldwide.

The first Conus genome assembly reveals a primary genetic central dogma of conopeptides in C. betulinus.

Although there are various Conus species with publicly available transcriptome and proteome data, no genome assembly has been reported yet. Here, using Chinese tubular cone snail (C. betulinus) as a representative, we sequenced and assembled the first Conus genome with original identification of 133 genome-widely distributed conopeptide genes. After integration of our genomics, transcriptomics, and peptidomics data in the same species, we established a primary genetic central dogma of diverse conopeptides, assuming a rough number ratio of ~1:1:1:10s for the total genes: transcripts: proteins: post-translationally modified peptides. This ratio may be special for this worm-hunting Conus species, due to the high diversity of various Conus genomes and the big number ranges of conopeptide genes, transcripts, and peptides in previous reports of diverse Conus species. Only a fraction (45.9%) of the identified conotopeptide genes from our achieved genome assembly are transcribed with transcriptomic evidence, and few genes individually correspond to multiple transcripts possibly due to intraspecies or mutation-based variances. Variable peptide processing at the proteomic level, generating a big diversity of venom conopeptides with alternative cleavage sites, post-translational modifications, and N-/C-terminal truncations, may explain how the 133 genes and ~123 transcripts can generate thousands of conopeptides in the venom of individual C. betulinus. We also predicted many conopeptides with high stereostructural similarities to the putative analgesic ω-MVIIA, addiction therapy AuIB and insecticide ImI, suggesting that our current genome assembly for C. betulinus is a valuable genetic resource for high-throughput prediction and development of potential pharmaceuticals.

Characterization and validation of somatic mutation spectrum to reveal heterogeneity in gastric cancer by single cell sequencing.

Gastric cancer (GC) is a highly heterogeneous disease with multiple cellular types and poor prognosis. However, the cellular evolution and molecular basis of GC at the individual intra-tumor level has not been well demonstrated. We performed single-cell whole exome sequencing to detect somatic single-nucleotide variants (SNVs) and significantly mutated genes (SMGs) among 34 tumor cells and 9 normal cells from a patient with GC. The Complete Prediction for Protein Conformation (CPPC) approach directly predicting the folding conformation of the protein 3D structure with Protein Folding Shape Code, combined with functional experiments were used to confirm the characterization of mutated SMGs in GC cells. We identified 201 somatic SNVs, including 117 non-synonymous mutations in GC cells. Further analysis identified 24 significant mutated genes (SMGs) in single cells, for which a single amino acid change might affect protein conformation. Among them, two genes (CDC27 and FLG) that were mutated only in single cells but not in the corresponding tumor tissue, were recurrently present in another GC tissue cohort, and may play a potential role to promote carcinogenesis, as confirmed by functional characterization. Our findings showed a mutational landscape of GC at intra-tumor level for the first time and provided opportunities for understanding the heterogeneity and individualized target therapy for this disease.

Cone Snails: A Big Store of Conotoxins for Novel Drug Discovery.

Marine drugs have developed rapidly in recent decades. Cone snails, a group of more than 700 species, have always been one of the focuses for new drug discovery. These venomous snails capture prey using a diverse array of unique bioactive neurotoxins, usually named as conotoxins or conopeptides. These conotoxins have proven to be valuable pharmacological probes and potential drugs due to their high specificity and affinity to ion channels, receptors, and transporters in the nervous systems of target prey and humans. Several research groups, including ours, have examined the venom gland of cone snails using a combination of transcriptomic and proteomic sequencing, and revealed the existence of hundreds of conotoxin transcripts and thousands of conopeptides in each Conus species. Over 2000 nucleotide and 8000 peptide sequences of conotoxins have been published, and the number is still increasing quickly. However, more than 98% of these sequences still lack 3D structural and functional information. With the rapid development of genomics and bioinformatics in recent years, functional predictions and investigations on conotoxins are making great progress in promoting the discovery of novel drugs. For example, ω-MVIIA was approved by the U.S. Food and Drug Administration in 2004 to treat chronic pain, and nine more conotoxins are at various stages of preclinical or clinical evaluation. In short, the genus Conus, the big family of cone snails, has become an important genetic resource for conotoxin identification and drug development.

High-throughput identification of novel conotoxins from the Chinese tubular cone snail (Conus betulinus) by multi-transcriptome sequencing.

BACKGROUND: The venom of predatory marine cone snails mainly contains a diverse array of unique bioactive peptides commonly referred to as conopeptides or conotoxins. These peptides have proven to be valuable pharmacological probes and potential drugs because of their high specificity and affinity to important ion channels, receptors and transporters of the nervous system. Most previous studies have focused specifically on the conopeptides from piscivorous and molluscivorous cone snails, but little attention has been devoted to the dominant vermivorous species. RESULTS: The vermivorous Chinese tubular cone snail, Conus betulinus, is the dominant Conus species inhabiting the South China Sea. The transcriptomes of venom ducts and venom bulbs from a variety of specimens of this species were sequenced using both next-generation sequencing and traditional Sanger sequencing technologies, resulting in the identification of a total of 215 distinct conopeptides. Among these, 183 were novel conopeptides, including nine new superfamilies. It appeared that most of the identified conopeptides were synthesized in the venom duct, while a handful of conopeptides were identified only in the venom bulb and at very low levels. CONCLUSIONS: We identified 215 unique putative conopeptide transcripts from the combination of five transcriptomes and one EST sequencing dataset. Variation in conopeptides from different specimens of C. betulinus was observed, which suggested the presence of intraspecific variability in toxin production at the genetic level. These novel conopeptides provide a potentially fertile resource for the development of new pharmaceuticals, and a pathway for the discovery of new conotoxins.

Comprehensive description of protein structures using protein folding shape code.

Understanding and describing three-dimensional (3D) protein structures have dominated biological and biochemistry research for many years. A comprehensive description of protein folding structure is essential for the advancement of protein research. In this study, a novel description method is developed to generate a set of folding patterns with specific shape features, as well as vector characteristics in space. To accomplish the goal, this method embeds features from geometry, morphology and topology together into an algorithmic approach to achieve a full description for proteins. A set of 27 vectors is derived mathematically from an enclosed space, and each vector represents a 3D folding shape of five successive C(alpha) atoms in the protein backbone. The 27 vectors are represented by 27 symbols, which are called as the protein folding shape code (PFSC). The PFSC method offers a digital description of folding shapes along a protein backbone, which facilitates protein structure analysis. The PFSC method provides a tool to study the similarity and dissimilarity for protein or protein conformers. The PFSC results show overall agreement with structural assignments from the protein data bank, as well as results from other methods. All results show that the PFSC method is a reliable tool with explicit meaning for protein folding shape description.

Effective descriptions of molecular structures and the quantitative structure-activity relationship studies.

In this research, we found CoMFA alone could not obtain sufficiently a strong equation to allow confident prediction for aminobenzenes. When some other parameter, such as heat of molecular formation of the compounds, was introduced into the CoMFA model, the results were improved greatly. It gives us a hint that a better description for molecular structures will yield a better prediction model, and this hint challenged us to look for another method--the projection areas of molecules in 3D space for 3D-QSAR. It is surprising that much better results than that obtained by using CoMFA were achieved. Besides the CoMFA analysis, multiregression analysis and neural network methods for building the models were used in this paper.