iSARST: an integrated SARST web server for rapid protein structural similarity searches

Essential amino acids in the Plant-Conserved and Class-Specific Regions of cellulose synthases

The Plant-Conserved Region (P-CR) and the Class-Specific Region (CSR) are two plant-unique sequences in the catalytic core of cellulose synthases (CESAs) for which specific functions have not been established. Here, we used site-directed mutagenesis to replace amino acids and motifs within these sequences predicted to be essential for assembly and function of CESAs. We developed an in vivo method to determine the ability of mutated CesA1 transgenes to complement an Arabidopsis (Arabidopsis thaliana) temperature-sensitive root-swelling1 (rsw1) mutant. Replacement of a Cys residue in the CSR, which blocks dimerization in vitro, rendered the AtCesA1 transgene unable to complement the rsw1 mutation. Examination of the CSR sequences from 33 diverse angiosperm species showed domains of high-sequence conservation in a class-specific manner but with variation in the degrees of disorder, indicating a nonredundant role of the CSR structures in different CESA isoform classes. The Cys residue essential for dimerization was not always located in domains of intrinsic disorder. Expression of AtCesA1 transgene constructs, in which Pro417 and Arg453 were substituted for Ala or Lys in the coiled-coil of the P-CR, were also unable to complement the rsw1 mutation. Despite an expected role for Arg457 in trimerization of CESA proteins, AtCesA1 transgenes with Arg457Ala mutations were able to fully restore the wild-type phenotype in rsw1. Our data support that Cys662 within the CSR and Pro417 and Arg453 within the P-CR of Arabidopsis CESA1 are essential residues for functional synthase complex formation, but our data do not support a specific role for Arg457 in trimerization in native CESA complexes.

Discovering the Ultimate Limits of Protein Secondary Structure Prediction

Secondary structure prediction (SSP) of proteins is an important structural biology technique with many applications. There have been ~300 algorithms published in the past seven decades with fierce competition in accuracy. In the first 60 years, the accuracy of three-state SSP rose from ~56% to 81%; after that, it has long stayed at 81–86%. In the 1990s, the theoretical limit of three-state SSP accuracy had been estimated to be 88%. Thus, SSP is now generally considered not challenging or too challenging to improve. However, we found that the limit of three-state SSP might be underestimated. Besides, there is still much room for improving segment-based and eight-state SSPs, but the limits of these emerging topics have not been determined. This work performs large-scale sequence and structural analyses to estimate SSP accuracy limits and assess state-of-the-art SSP methods. The limit of three-state SSP is re-estimated to be ~92%, 4–5% higher than previously expected, indicating that SSP is still challenging. The estimated limit of eight-state SSP is 84–87%. Several proposals for improving future SSP algorithms are made based on our results. We hope that these findings will help move forward the development of SSP and all its applications.

CirPred, the first structure modeling and linker design system for circularly permuted proteins

Background

This work aims to help develop new protein engineering techniques based on a structural rearrangement phenomenon called circular permutation (CP), equivalent to connecting the native termini of a protein followed by creating new termini at another site. Although CP has been applied in many fields, its implementation is still costly because of inevitable trials and errors.

Results

Here we present CirPred, a structure modeling and termini linker design method for circularly permuted proteins. Compared with state-of-the-art protein structure modeling methods, CirPred is the only one fully capable of both circularly-permuted modeling and traditional co-linear modeling. CirPred performs well when the permutant shares low sequence identity with the native protein and even when the permutant adopts a different conformation from the native protein because of three-dimensional (3D) domain swapping. Linker redesign experiments demonstrated that the linker design algorithm of CirPred achieved subangstrom accuracy.

Conclusions

The CirPred system is capable of (1) predicting the structure of circular permutants, (2) designing termini linkers, (3) performing traditional co-linear protein structure modeling, and (4) identifying the CP-induced occurrence of 3D domain swapping. This method is supposed helpful for broadening the application of CP, and its web server is available at http://10.life.nctu.edu.tw/CirPred/ and http://lo.life.nctu.edu.tw/CirPred/.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-021-04403-1.

Predicted structural mimicry of spike receptor-binding motifs from highly pathogenic human coronaviruses

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Potential coronavirus spike protein mimicry revealed by structural comparison.

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Human and non-human protein potential interactions with virus identified.

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Predicted structural mimicry corroborated by protein–protein docking.

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Epitope-based alignments may help guide vaccine efforts.

Viruses often encode proteins that mimic host proteins in order to facilitate infection. Little work has been done to understand the potential mimicry of the SARS-CoV-2, SARS-CoV, and MERS-CoV spike proteins, particularly the receptor-binding motifs, which could be important in determining tropism and druggability of the virus. Peptide and epitope motifs have been detected on coronavirus spike proteins using sequence homology approaches; however, comparing the three-dimensional shape of the protein has been shown as more informative in predicting mimicry than sequence-based comparisons. Here, we use structural bioinformatics software to characterize potential mimicry of the three coronavirus spike protein receptor-binding motifs. We utilize sequence-independent alignment tools to compare structurally known protein models with the receptor-binding motifs and verify potential mimicked interactions with protein docking simulations. Both human and non-human proteins were returned for all three receptor-binding motifs. For example, all three were similar to several proteins containing EGF-like domains: some of which are endogenous to humans, such as thrombomodulin, and others exogenous, such as Plasmodium falciparum MSP-1. Similarity to human proteins may reveal which pathways the spike protein is co-opting, while analogous non-human proteins may indicate shared host interaction partners and overlapping antibody cross-reactivity. These findings can help guide experimental efforts to further understand potential interactions between human and coronavirus proteins.

A simple strategy to enhance the speed of protein secondary structure prediction without sacrificing accuracy

The secondary structure prediction of proteins is a classic topic of computational structural biology with a variety of applications. During the past decade, the accuracy of prediction achieved by state-of-the-art algorithms has been >80%; meanwhile, the time cost of prediction increased rapidly because of the exponential growth of fundamental protein sequence data. Based on literature studies and preliminary observations on the relationships between the size/homology of the fundamental protein dataset and the speed/accuracy of predictions, we raised two hypotheses that might be helpful to determine the main influence factors of the efficiency of secondary structure prediction. Experimental results of size and homology reductions of the fundamental protein dataset supported those hypotheses. They revealed that shrinking the size of the dataset could substantially cut down the time cost of prediction with a slight decrease of accuracy, which could be increased on the contrary by homology reduction of the dataset. Moreover, the Shannon information entropy could be applied to explain how accuracy was influenced by the size and homology of the dataset. Based on these findings, we proposed that a proper combination of size and homology reductions of the protein dataset could speed up the secondary structure prediction while preserving the high accuracy of state-of-the-art algorithms. Testing the proposed strategy with the fundamental protein dataset of the year 2018 provided by the Universal Protein Resource, the speed of prediction was enhanced over 20 folds while all accuracy measures remained equivalently high. These findings are supposed helpful for improving the efficiency of researches and applications depending on the secondary structure prediction of proteins. To make future implementations of the proposed strategy easy, we have established a database of size and homology reduced protein datasets at http://10.life.nctu.edu.tw/UniRefNR.

Streptococcus pneumoniae Genome-wide Identification and Characterization of BOX Element-binding Domains

The BOX elements are short repetitive DNA sequences that distribute randomly in intergenic regions of the Streptococcus pneumoniae genome. The function and origin of such elements are still unknown, but they were found to modulate expression of neighboring genes. Evidences suggested that the modulation's mechanism can be fulfilled by sequence-specific interaction of BOX elements with transcription factor family proteins. However, the type and function of these BOX-binding proteins still remain largely unexplored to date. In the current study we described a synthetic protocol to investigate the recognition and interaction between a highly conserved site of BOX elements and the DNA-binding domains of a variety of putative transcription factors in the pneumococcal genome. With the protocol we were able to predict those high-affinity domain binders of the conserved BOX DNA site (BOX DNA) in a high-throughput manner, and analyzed sequence-specific interaction in the domainDNA recognition at molecular level. Consequently, a number of putative transcription factor domains with both high affinity and specificity for the BOX DNA were identified, from which the helix-turn-helix (HTH) motif of a small heat shock factor was selected as a case study and tested for its binding capability toward the double-stranded BOX DNA using fluorescence anisotropy analysis. As might be expected, a relatively high affinity was detected for the interaction of HTH motif with BOX DNA with dissociation constant at nanomolar level. Molecular dynamics simulation, atomic structure examination and binding energy analysis revealed a complicated network of intensive nonbonded interactions across the complex interface, which confers both stability and specificity for the complex architecture.

Production of bulk chemicals via novel metabolic pathways in microorganisms

Metabolic engineering has been playing important roles in developing high performance microorganisms capable of producing various chemicals and materials from renewable biomass in a sustainable manner. Synthetic and systems biology are also contributing significantly to the creation of novel pathways and the whole cell-wide optimization of metabolic performance, respectively. In order to expand the spectrum of chemicals that can be produced biotechnologically, it is necessary to broaden the metabolic capacities of microorganisms. Expanding the metabolic pathways for biosynthesizing the target chemicals requires not only the enumeration of a series of known enzymes, but also the identification of biochemical gaps whose corresponding enzymes might not actually exist in nature; this issue is the focus of this paper. First, pathway prediction tools, effectively combining reactions that lead to the production of a target chemical, are analyzed in terms of logics representing chemical information, and designing and ranking the proposed metabolic pathways. Then, several approaches for potentially filling in the gaps of the novel metabolic pathway are suggested along with relevant examples, including the use of promiscuous enzymes that flexibly utilize different substrates, design of novel enzymes for non-natural reactions, and exploration of hypothetical proteins. Finally, strain optimization by systems metabolic engineering in the context of novel metabolic pathways constructed is briefly described. It is hoped that this review paper will provide logical ways of efficiently utilizing 'big' biological data to design and develop novel metabolic pathways for the production of various bulk chemicals that are currently produced from fossil resources.

Crystal structure of circular permuted RoCBM21 (CP90): dimerisation and proximity of binding sites

Glucoamylases, containing starch-binding domains (SBD), have a wide range of scientific and industrial applications. Random mutagenesis and DNA shuffling of the gene encoding a starch-binding domain have resulted in only minor improvements in the affinities of the corresponding protein to their ligands, whereas circular permutation of the RoCBM21 substantially improved its binding affinity and selectivity towards longer-chain carbohydrates. For the study reported herein, we used a standard soluble ligand (amylose EX-I) to characterize the functional and structural aspects of circularly permuted RoCBM21 (CP90). Site-directed mutagenesis and the analysis of crystal structure reveal the dimerisation and an altered binding path, which may be responsible for improved affinity and altered selectivity of this newly created starch-binding domain. The functional and structural characterization of CP90 suggests that it has significant potential in industrial applications.

Crystal structure of the dopamine N-acetyltransferase-acetyl-CoA complex provides insights into the catalytic mechanism

The daily cycle of melatonin biosynthesis in mammals is regulated by AANAT (arylalkylamine N-acetyltransferase; EC 2.3.1.87), making it an attractive target for therapeutic control of abnormal melatonin production in mood and sleep disorders. Drosophila melanogaster Dat (dopamine N-acetyltransferase) is an AANAT. Until the present study, no insect Dat structure had been solved, and, consequently, the structural basis for its acetyl-transfer activity was not well understood. We report in the present paper the high-resolution crystal structure for a D. melanogaster Dat-AcCoA (acetyl-CoA) complex obtained using one-edge (selenium) single-wavelength anomalous diffraction. A binding study using isothermal titration calorimetry suggested that the cofactor bound to Dat first before substrate. Examination of the complex structure and a substrate-docked model indicated that Dat contains a novel AANAT catalytic triad. Site-directed mutagenesis, kinetic studies and pH-rate profiles confirmed that Glu(47), Ser(182) and Ser(186) were critical for catalysis. Collectively, the results of the present study suggest that Dat possesses a specialized active site structure dedicated to a catalytic mechanism.

LNA: fast protein structural comparison using a Laplacian characterization of tertiary structure

Abstract—In the last two decades, a lot of protein 3D shapes have been discovered, characterized, and made available thanks to the Protein Data Bank (PDB), that is nevertheless growing very quickly. New scalable methods are thus urgently required to search through the PDB efficiently. This paper presents an approach entitled LNA (Laplacian Norm Alignment) that performs a structural comparison of two proteins with dynamic programming algorithms. This is achieved by characterizing each residue in the protein with scalar features. The feature values are calculated using a Laplacian operator applied on the graph corresponding to the adjacency matrix of the residues. The weighted Laplacian operator we use estimates, at various scales, local deformations of the topology where each residue is located. On some benchmarks, which are widely shared by the community, we obtain qualitatively similar results compared to other competing approaches, but with an algorithm one or two order of magnitudes faster. 180,000 protein comparisons can be done within 1 second with a single recent Graphical Processing Unit (GPU), which makes our algorithm very scalable and suitable for real-time database querying across the web.

Insulin-like growth factor binding protein 7, a member of insulin-like growth factor signal pathway, involved in immune response of small abalone Haliotis diversicolor

Insulin-like growth factor binding protein 7 (IGFBP7), the only member of the IGFBP superfamily that binds strongly to insulin, may have different functions from other IGFBPs. Unlike other IGFBPs, there is no knowledge available on aquatic invertebrate IGFBP7. In this study, a molluscan IGFBP7 gene, saIGFBP7, was cloned for the first time from the small abalone Haliotis diversicolor. Its full-length cDNA sequence is 1812 bp, with a 720 bp open reading frame encoding a protein of 239 aa. The molecular mass of the deduced protein is approximately 25.37 kDa with an estimated pI of 5.00, and it shares highest 41% identity to IGFBP7 of Amblyomma americanum. Analysis of conserved domains revealed the presence of an IGFBP N-terminal domain (IB), a kazal-type serine proteinase inhibitor domain (KI), and an immunoglobulin-like C2 domain (IgC2) in saIGFBP7. Furthermore, the 12 cysteine residues and the signature amino acid motif 'xCGCCxxC' which are characterized by the amino terminus region of the IGFBP superfamily are all presented in saIGFBP7. Quantitative real-time PCR and western blot were employed to investigate the tissue distribution of saIGFBP7, and its expression under bacterial challenge. The saIGFBP7 mRNA and protein could be detected in all examined tissues, with the highest expression level in hemocytes, higher expression level in gills, and was up-regulated in hemocytes and gills after bacterial injection. In addition, saIGFBP7 mRNA transcripts were observed in a subset of the branchial epithelium and the nucleus of hemocytes using the in situ hybridization method. Interestingly, saIGFBP7 was detected mainly in the goblet-like cell of the branchial epithelium by immunohistochemistry. These results suggested that saIGFBP7 was likely to be involved in a function associated with pathogenic infection and may play an important role in the adult abalone immune system.

Alternaria alternata allergen Alt a 1: a unique β-barrel protein dimer found exclusively in fungi

BACKGROUND

Alternaria species is one of the most common molds associated with allergic diseases, and 80% of Alternaria species-sensitive patients produce IgE antibodies to a major protein allergen, Alt a 1. The structure and function of Alt a 1 is unknown.

OBJECTIVE

We sought to obtain a high-resolution structure of Alt a 1 using x-ray crystallography and to investigate structural relationships between Alt a 1 and other allergens and proteins reported in the Protein Data Bank.

METHODS

X-ray crystallography was used to determine the structure of Alt a 1 by using a custom-designed set of crystallization conditions. An initial Alt a 1 model was determined by the application of a Ta(6)Br(12)(2+) cluster and single-wavelength anomalous diffraction. Bioinformatic analyses were used to compare the Alt a 1 sequence and structure with that of other proteins.

RESULTS

Alt a 1 is a unique β-barrel comprising 11 β-strands and forms a "butterfly-like" dimer linked by a single disulfide bond with a large (1345 Å(2)) dimer interface. Intramolecular disulfide bonds are conserved among Alt a 1 homologs. Currently, the Alt a 1 structure has no equivalent in the Protein Data Bank. Bioinformatics analyses suggest that the structure is found exclusively in fungi. Four previously reported putative IgE-binding peptides have been located on the Alt a 1 structure.

CONCLUSIONS

Alt a 1 has a unique, dimeric β-barrel structure that appears to define a new protein family with unknown function found exclusively in fungi. The location of IgE antibody-binding epitopes is in agreement with the structural analysis of Alt a 1. The Alt a 1 structure will allow mechanistic structure/function studies and immunologic studies directed toward new forms of immunotherapy for Alternaria species-sensitive allergic patients.

Molecular cloning and expression of interleukin-1 receptor-associated kinase 4, an important mediator of Toll-like receptor signal pathway, from small abalone Haliotis diversicolor

Mammal interleukin-1 receptor-associated kinases (IRAKs) have been demonstrated to play important functions in TLRs (Toll-like receptor) signal pathway and T cell proliferation, but there is less knowledge available on mollusc IRAKs. In this study, a molluscan IRAK-4 gene, saIRAK-4, was cloned for the first time from the small abalone (Haliotis diversicolor). Its full-length cDNA sequence was 2062 bp, with a 1548 bp open reading frame encoding a protein of 516 aa. The molecular mass of the deduced protein was approximately 57.8 kDa with an estimated pI of 5.23, and showed highest identity (47%) to acorn worm Saccoglossus kowalevskii. Amino acid sequence analysis revealed saIRAK-4 shares conserved signature motifs with other IRAK-4 proteins, including the death domain (DD), serine/threonine/tyrosine protein kinase domain (STYKc), protein kinases ATP-binding region signature, serine/threonine protein kinases active-site signature and prokaryotic membrane lipoprotein lipid attachment site. Quantitative real-time PCR was employed to investigate the tissue distribution of saIRAK-4 mRNA, and its expression in abalone under bacteria challenge and larvae at different developmental stages. The saIRAK-4 mRNA could be detected in all examined tissues, with the highest expression level in gills, and was up-regulated in hemocytes and gills after bacteria injection. Additionally, saIRAK-4 was constitutively expressed at all examined developmental stages. These results indicate that saIRAK-4 could respond to pathogenic infection and may play an important role in the adult abalone immune system and early innate immunity in the process of abalone larval development.

Detection and alignment of 3D domain swapping proteins using angle-distance image-based secondary structural matching techniques

This work presents a novel detection method for three-dimensional domain swapping (DS), a mechanism for forming protein quaternary structures that can be visualized as if monomers had “opened” their “closed” structures and exchanged the opened portion to form intertwined oligomers. Since the first report of DS in the mid 1990s, an increasing number of identified cases has led to the postulation that DS might occur in a protein with an unconstrained terminus under appropriate conditions. DS may play important roles in the molecular evolution and functional regulation of proteins and the formation of depositions in Alzheimer's and prion diseases. Moreover, it is promising for designing auto-assembling biomaterials. Despite the increasing interest in DS, related bioinformatics methods are rarely available. Owing to a dramatic conformational difference between the monomeric/closed and oligomeric/open forms, conventional structural comparison methods are inadequate for detecting DS. Hence, there is also a lack of comprehensive datasets for studying DS. Based on angle-distance (A-D) image transformations of secondary structural elements (SSEs), specific patterns within A-D images can be recognized and classified for structural similarities. In this work, a matching algorithm to extract corresponding SSE pairs from A-D images and a novel DS score have been designed and demonstrated to be applicable to the detection of DS relationships. The Matthews correlation coefficient (MCC) and sensitivity of the proposed DS-detecting method were higher than 0.81 even when the sequence identities of the proteins examined were lower than 10%. On average, the alignment percentage and root-mean-square distance (RMSD) computed by the proposed method were 90% and 1.8Å for a set of 1,211 DS-related pairs of proteins. The performances of structural alignments remain high and stable for DS-related homologs with less than 10% sequence identities. In addition, the quality of its hinge loop determination is comparable to that of manual inspection. This method has been implemented as a web-based tool, which requires two protein structures as the input and then the type and/or existence of DS relationships between the input structures are determined according to the A-D image-based structural alignments and the DS score. The proposed method is expected to trigger large-scale studies of this interesting structural phenomenon and facilitate related applications.

ProteinDBS v2.0: a web server for global and local protein structure search

ProteinDBS v2.0 is a web server designed for efficient and accurate comparisons and searches of structurally similar proteins from a large-scale database. It provides two comparison methods, global-to-global and local-to-local, to facilitate the searches of protein structures or substructures. ProteinDBS v2.0 applies advanced feature extraction algorithms and scalable indexing techniques to achieve a high-running speed while preserving reasonably high precision of structural comparison. The experimental results show that our system is able to return results of global comparisons in seconds from a complete Protein Data Bank (PDB) database of 152,959 protein chains and that it takes much less time to complete local comparisons from a non-redundant database of 3276 proteins than other accurate comparison methods. ProteinDBS v2.0 supports query by PDB protein ID and by new structures uploaded by users. To our knowledge, this is the only search engine that can simultaneously support global and local comparisons. ProteinDBS v2.0 is a useful tool to investigate functional or evolutional relationships among proteins. Moreover, the common substructures identified by local comparison can be potentially used to assist the human curation process in discovering new domains or folds from the ever-growing protein structure databases. The system is hosted at http://ProteinDBS.rnet.missouri.edu.

deconSTRUCT: general purpose protein database search on the substructure level

deconSTRUCT webserver offers an interface to a protein database search engine, usable for a general purpose detection of similar protein (sub)structures. Initially, it deconstructs the query structure into its secondary structure elements (SSEs) and reassembles the match to the target by requiring a (tunable) degree of similarity in the direction and sequential order of SSEs. Hierarchical organization and judicious use of the information about protein structure enables deconSTRUCT to achieve the sensitivity and specificity of the established search engines at orders of magnitude increased speed, without tying up irretrievably the substructure information in the form of a hash. In a post-processing step, a match on the level of the backbone atoms is constructed. The results presented to the user consist of the list of the matched SSEs, the transformation matrix for rigid superposition of the structures and several ways of visualization, both downloadable and implemented as a web-browser plug-in. The server is available at http://epsf.bmad.bii.a-star.edu.sg/struct_server.html.

A fast indexing approach for protein structure comparison

BACKGROUND

Protein structure comparison is a fundamental task in structural biology. While the number of known protein structures has grown rapidly over the last decade, searching a large database of protein structures is still relatively slow using existing methods. There is a need for new techniques which can rapidly compare protein structures, whilst maintaining high matching accuracy.

RESULTS

We have developed IR Tableau, a fast protein comparison algorithm, which leverages the tableau representation to compare protein tertiary structures. IR tableau compares tableaux using information retrieval style feature indexing techniques. Experimental analysis on the ASTRAL SCOP protein structural domain database demonstrates that IR Tableau achieves two orders of magnitude speedup over the search times of existing methods, while producing search results of comparable accuracy.

CONCLUSION

We show that it is possible to obtain very significant speedups for the protein structure comparison problem, by employing an information retrieval style approach for indexing proteins. The comparison accuracy achieved is also strong, thus opening the way for large scale processing of very large protein structure databases.