Structural classification of proteins and structural genomics: new insights into protein folding and evolution

This review article surveys the protein structures determined by Joint Center for Structural Genomics and published in this special issue of Acta Crystallographica Section F

ATTITUDES TOWARD DEATH AND THE RELIGIOUS CONSCIOUSNESS OF YOUTH

Purpose of the study: this study aimed to analyze the modern representation of death by studying the attitude of religious people, mainly Christians, towards death. Methodology: On the basis of the Siberian Federal University, the authors conducted research on the attitude of student youth towards death. The questionnaire in a standardized fashion was used. Likert scale judgments were analyzed. The methodological concepts of the attitude towards the death of such authors as Philippe Ariès and Gilbert Durand, as well as the Russian cosmists, served as the prerequisite for the formation of the research hypothesis. The group of the respondent demonstrated the religious beliefs and their faith in God. The answers of the group were interpreted on the subject of their attitude towards death, the ideas of death, and the types of protection against the fear of death. Main Findings: In the course of this work, the authors determined that the majority of student youth formed a negative representation of death that does not correspond with the religious ideology. Several concepts that reflect the attitude of youth towards death and their method of fighting the fear of death are described. The authors draw a conclusion on the state of the religious consciousness of student youth that is a result of unfamiliarity with religious norms or the fusion of the traditions of various religions. Applications of this study: The study would serve as an antecedent to further investigation on people’s attitude towards death. The research results can also be applied in social anthropology, social philosophy, and sociology. Novelty/Originality of this study: The study shows the important attitude of student youth towards death and can help to form the main problems of the religious consciousness of student youth

Disease-Associated Mutations in CEP120 Destabilize the Protein and Impair Ciliogenesis.

Ciliopathies are a group of genetic disorders caused by a failure to form functional cilia. Due to a lack of structural information, it is currently poorly understood how ciliopathic mutations affect protein functionality to give rise to the underlying disease. Using X-ray crystallography, we show that the ciliopathy-associated centriolar protein CEP120 contains three C2 domains. The point mutations V194A and A199P, which cause Joubert syndrome (JS) and Jeune asphyxiating thoracic dystrophy (JATD), respectively, both reduce the thermostability of the second C2 domain by targeting residues that point toward its hydrophobic core. Genome-engineered cells homozygous for these mutations have largely normal centriole numbers but show reduced CEP120 levels, compromised recruitment of distal centriole markers, and deficient cilia formation. Our results provide insight into the disease mechanism of two ciliopathic mutations in CEP120, identify putative binding partners of CEP120 C2B, and suggest a complex genotype-phenotype relation of the CEP120 ciliopathy alleles

SISYPHUS—structural alignments for proteins with non-trivial relationships

With the increasing amount of structural data, the number of homologous protein structures bearing topological irregularities is steadily growing. These include proteins with circular permutations, segment-swapping, context-dependent folding or chameleon sequences that can adopt alternative secondary structures. Their non-trivial structural relationships are readily identified during expert analysis but their automatic identification using the existing computational tools still remains difficult or impossible. Such non-trivial cases of protein relationships are known to pose a problem to multiple alignment algorithms and to impede comparative modeling studies. They support a new emerging concept of evolutionary changeable protein fold, which creates practical difficulties for the hierarchical classifications of protein structures.To facilitate the understanding of, and to provide a comprehensive annotation of proteins with such non-trivial structural relationships we have created SISYPHUS ([Σισυϕος]—in Greek crafty), a compendium to the SCOP database. The SISYPHUS database contains a collection of manually curated structural alignments and their inter-relationships. The multiple alignments are constructed for protein structural regions that range from oligomeric biological units, or individual domains to fragments of different size. The SISYPHUS multiple alignments are displayed with SPICE, a browser that provides an integrated view of protein sequences, structures and their annotations. The database is available from

What is hidden in the darkness? Deep-learning assisted large-scale protein family curation uncovers novel protein families and folds

Driven by the development and upscaling of fast genome sequencing and assembly pipelines, the number of protein-coding sequences deposited in public protein sequence databases is increasing exponentially. Recently, the dramatic success of deep learning-based approaches applied to protein structure prediction has done the same for protein structures. We are now entering a new era in protein sequence and structure annotation, with hundreds of millions of predicted protein structures made available through the AlphaFold database. These models cover most of the catalogued natural proteins, including those difficult to annotate for function or putative biological role based on standard, homology-based approaches. In this work, we quantified how much of such "dark matter" of the natural protein universe was structurally illuminated by AlphaFold2 and modelled this diversity as an interactive sequence similarity network that can be navigated at https://uniprot3d.org/atlas/AFDB90v4 . In the process, we discovered multiple novel protein families by searching for novelties from sequence, structure, and semantic perspectives. We added a number of them to Pfam, and experimentally demonstrate that one of these belongs to a novel superfamily of toxin-antitoxin systems, TumE-TumA. This work highlights the role of large-scale, evolution-driven protein comparison efforts in combination with structural similarities, genomic context conservation, and deep-learning based function prediction tools for the identification of novel protein families, aiding not only annotation and classification efforts but also the curation and prioritisation of target proteins for experimental characterisation

Recruitment of trimeric eIF2 by phosphatase non-catalytic subunit PPP1R15B

Regulated protein phosphorylation controls most cellular processes. The protein phosphatase PP1 is the catalytic subunit of many holoenzymes that dephosphorylate serine/threonine residues. How these enzymes recruit their substrates is largely unknown. Here, we integrated diverse approaches to elucidate how the PP1 non-catalytic subunit PPP1R15B (R15B) captures its full trimeric eIF2 substrate. We found that the substrate-recruitment module of R15B is largely disordered with three short helical elements, H1, H2, and H3. H1 and H2 form a clamp that grasps the substrate in a region remote from the phosphorylated residue. A homozygous N423D variant, adjacent to H1, reducing substrate binding and dephosphorylation was discovered in a rare syndrome with microcephaly, developmental delay, and intellectual disability. These findings explain how R15B captures its 125 kDa substrate by binding the far end of the complex relative to the phosphosite to present it for dephosphorylation by PP1, a paradigm of broad relevance.</p

Genome3D: integrating a collaborative data pipeline to expand the depth and breadth of consensus protein structure annotation.

Genome3D (https://www.genome3d.eu) is a freely available resource that provides consensus structural annotations for representative protein sequences taken from a selection of model organisms. Since the last NAR update in 2015, the method of data submission has been overhauled, with annotations now being 'pushed' to the database via an API. As a result, contributing groups are now able to manage their own structural annotations, making the resource more flexible and maintainable. The new submission protocol brings a number of additional benefits including: providing instant validation of data and avoiding the requirement to synchronise releases between resources. It also makes it possible to implement the submission of these structural annotations as an automated part of existing internal workflows. In turn, these improvements facilitate Genome3D being opened up to new prediction algorithms and groups. For the latest release of Genome3D (v2.1), the underlying dataset of sequences used as prediction targets has been updated using the latest reference proteomes available in UniProtKB. A number of new reference proteomes have also been added of particular interest to the wider scientific community: cow, pig, wheat and mycobacterium tuberculosis. These additions, along with improvements to the underlying predictions from contributing resources, has ensured that the number of annotations in Genome3D has nearly doubled since the last NAR update article. The new API has also been used to facilitate the dissemination of Genome3D data into InterPro, thereby widening the visibility of both the annotation data and annotation algorithms

Genome3D: exploiting structure to help users understand their sequences.

Genome3D (http://www.genome3d.eu) is a collaborative resource that provides predicted domain annotations and structural models for key sequences. Since introducing Genome3D in a previous NAR paper, we have substantially extended and improved the resource. We have annotated representatives from Pfam families to improve coverage of diverse sequences and added a fast sequence search to the website to allow users to find Genome3D-annotated sequences similar to their own. We have improved and extended the Genome3D data, enlarging the source data set from three model organisms to 10, and adding VIVACE, a resource new to Genome3D. We have analysed and updated Genome3D's SCOP/CATH mapping. Finally, we have improved the superposition tools, which now give users a more powerful interface for investigating similarities and differences between structural models

Data growth and its impact on the SCOP database: new developments

The Structural Classification of Proteins (SCOP) database is a comprehensive ordering of all proteins of known structure, according to their evolutionary and structural relationships. The SCOP hierarchy comprises the following levels: Species, Protein, Family, Superfamily, Fold and Class. While keeping the original classification scheme intact, we have changed the production of SCOP in order to cope with a rapid growth of new structural data and to facilitate the discovery of new protein relationships. We describe ongoing developments and new features implemented in SCOP. A new update protocol supports batch classification of new protein structures by their detected relationships at Family and Superfamily levels in contrast to our previous sequential handling of new structural data by release date. We introduce pre-SCOP, a preview of the SCOP developmental version that enables earlier access to the information on new relationships. We also discuss the impact of worldwide Structural Genomics initiatives, which are producing new protein structures at an increasing rate, on the rates of discovery and growth of protein families and superfamilies. SCOP can be accessed at http://scop.mrc-lmb.cam.ac.uk/scop