Real-world evidence from over one million COVID-19 vaccinations is consistent with reactivation of the varicella-zoster virus.

BACKGROUND: Reactivation of the varicella-zoster virus (VZV), which causes herpes zoster (HZ, synonym: shingles) in humans, can be a rare adverse reaction to vaccines. Recently, reports of cases after COVID-19 vaccination have arisen. OBJECTIVES: The aim of this study was to assess whether the frequency of HZ is found to increase after COVID-19 vaccination in a large cohort, based on real-world data. As a hypothesis, the incidence of HZ was assumed to be significantly higher in subjects who received a COVID-19 vaccine (Cohort I) vs. unvaccinated individuals (Cohort II). METHODS: The initial cohorts of 1 095 086 vaccinated and 16 966 018 unvaccinated patients were retrieved from the TriNetX database and were matched on age and gender in order to mitigate confounder bias. RESULTS: After matching, each cohort accounted for 1 095 086 patients. For the vaccinated group (Cohort I), 2204 subjects developed HZ within 60 days of COVID-19 vaccination, while among Cohort II, 1223 patients were diagnosed with HZ within 60 days after having visited the clinic for any other reason (i.e. not vaccination). The risk of developing shingles was calculated as 0.20% and 0.11% for cohort I and cohort II, respectively. The difference was statistically highly significant (P < 0.0001; log-rank test). The risk ratio and odds ratio were 1.802 (95% confidence interval [CI] = 1.680; 1.932) and 1.804 (95% CI = 1.682; 1.934). CONCLUSIONS: Consistent with the hypothesis, a higher incidence of HZ was statistically detectable post-COVID-19 vaccine. Accordingly, the eruption of HZ may be a rare adverse drug reaction to COVID-19 vaccines. Even though the molecular basis of VZV reactivation remains murky, temporary compromising of VZV-specific T-cell-mediated immunity may play a mechanistic role in post-vaccination pathogenesis of HZ. Note that VZV reactivation is a well-established phenomenon both with infections and with other vaccines (i.e. this adverse event is not COVID-19-specific).

A case study of high-throughput biological data processing on parallel platforms.

MOTIVATION: Analysis of large biological data sets using a variety of parallel processor computer architectures is a common task in bioinformatics. The efficiency of the analysis can be significantly improved by properly handling redundancy present in these data combined with taking advantage of the unique features of these compute architectures. RESULTS: We describe a generalized approach to this analysis, but present specific results using the program CEPAR, an efficient implementation of the Combinatorial Extension algorithm in a massively parallel (PAR) mode for finding pairwise protein structure similarities and aligning protein structures from the Protein Data Bank. CEPAR design and implementation are described and results provided for the efficiency of the algorithm when run on a large number of processors. AVAILABILITY: Source code is available by contacting one of the authors.

The status of structural genomics defined through the analysis of current targets and structures.

Structural genomics--large-scale macromolecular 3-dimenional structure determination--is unique in that major participants report scientific progress on a weekly basis. The target database (TargetDB) maintained by the Protein Data Bank (http://targetdb.pdb.org) reports this progress through the status of each protein sequence (target) under consideration by the major structural genomics centers worldwide. Hence, TargetDB provides a unique opportunity to analyze the potential impact that this major initiative provides to scientists interested in the sequence-structure-function-disease paradigm. Here we report such an analysis with a focus on: (i) temporal characteristics--how is the project doing and what can we expect in the future? (ii) target characteristics--what are the predicted functions of the proteins targeted by structural genomics and how biased is the target set when compared to the PDB and to predictions across complete genomes? (iii) structures solved--what are the characteristics of structures solved thus far and what do they contribute? The analysis required a more extensive database of structure predictions using different methods integrated with data from other sources. This database, associated tools and related data sources are available from http://spam.sdsc.edu.

The apoptosis database.

The apoptosis database is a public resource for researchers and students interested in the molecular biology of apoptosis. The resource provides functional annotation, literature references, diagrams/images, and alternative nomenclatures on a set of proteins having 'apoptotic domains'. These are the distinctive domains that are often, if not exclusively, found in proteins involved in apoptosis. The initial choice of proteins to be included is defined by apoptosis experts and bioinformatics tools. Users can browse through the web accessible lists of domains, proteins containing these domains and their associated homologs. The database can also be searched by sequence homology using basic local alignment search tool, text word matches of the annotation, and identifiers for specific records. The resource is available at http://www.apoptosis-db.org and is updated on a regular basis.

Design and implementation of a collaborative molecular graphics environment.

During the determination of macromolecular structures, scientists routinely use complex graphics software to display various representations of the molecule of interest. Once the structure determination is complete, coordinates are deposited in the Protein Data Bank (PDB), from where anyone with an Internet connection may download and view them or request them on CD-ROM. However, the currently available visualization software is such that causal users, whose expertise may not be in structure determination, often cannot obtain useful images of interesting molecules without expending considerable time and effort. Existing visualization software is generally very complex, requiring a high degree of familiarity to obtain the best results, or else it is too simplistic to provide users with the level of customizability needed to get the most out of the atomic coordinates. Few of the existing software packages have the capability for collaborative visualization via the Internet. These and other issuses are being addressed by the Molecular Interactive Collaborative Environment (MICE) project (http://mice.sdsc.edu/). The core of the MICE project is the MICE application, an interactive molecular structure viewer with built-in collaborative capabilities. MICE not only addresses the issues of usability and flexibility but also extends the role of traditional visualization tools by allowing multiple users to view, manipulate, and interact with a single representation of a macromolecular structure. MICE is written entirely in Java, using the Java3D extensions for rendering and manipulation of the three-dimensional scene, and the Common Object Request Broker Architecture (CORBA) communications suite to enable collaborative manipulation of that scene.

A new algorithm for the alignment of multiple protein structures using Monte Carlo optimization.

We have developed a new algorithm for the alignment of multiple protein structures based on a Monte Carlo optimization technique. The algorithm uses pair-wise structural alignments as a starting point. Four different types of moves were designed to generate random changes in the alignment. A distance-based score is calculated for each trial move and moves are accepted or rejected based on the improvement in the alignment score until the alignment is converged. Initial tests on 66 protein structural families show promising results, the score increases by 69% on average. The increase in score is accompanied by an increase (12%) in the number of residue positions incorporated into the alignment. Two specific families, protein kinases and aspartic proteinases were tested and compared against curated alignments from HOMSTRAD and manual alignments. This algorithm has improved the overall number of aligned residues while preserving key catalytic residues. Further refinement of the method and its application to generate multiple alignments for all protein families in the PDB, is currently in progress.

Conserved key amino acid positions (CKAAPs) derived from the analysis of common substructures in proteins.

An all-against-all protein structure comparison using the Combinatorial Extension (CE) algorithm applied to a representative set of PDB structures revealed a gallery of common substructures in proteins (http://cl.sdsc.edu/ce.html). These substructures represent commonly identified folds, domains, or components thereof. Most of the subsequences forming these similar substructures have no significant sequence similarity. We present a method to identify conserved amino acid positions and residue-dependent property clusters within these subsequences starting with structure alignments. Each of the subsequences is aligned to its homologues in SWALL, a nonredundant protein sequence database. The most similar sequences are purged into a common frequency matrix, and weighted homologues of each one of the subsequences are used in scoring for conserved key amino acid positions (CKAAPs). We have set the top 20% of the high-scoring positions in each substructure to be CKAAPs. It is hypothesized that CKAAPs may be responsible for the common folding patterns in either a local or global view of the protein-folding pathway. Where a significant number of structures exist, CKAAPs have also been identified in structure alignments of complete polypeptide chains from the same protein family or superfamily. Evidence to support the presence of CKAAPs comes from other computational approaches and experimental studies of mutation and protein-folding experiments, notably the Paracelsus challenge. Finally, the structural environment of CKAAPs versus non-CKAAPs is examined for solvent accessibility, hydrogen bonding, and secondary structure. The identification of CKAAPs has important implications for protein engineering, fold recognition, modeling, and structure prediction studies and is dependent on the availability of structures and an accurate structure alignment methodology. Proteins 2001;42:148-163.

A database and tools for 3-D protein structure comparison and alignment using the Combinatorial Extension (CE) algorithm.

The database reported here is derived using the Combinatorial Extension (CE) algorithm which compares pairs of protein polypeptide chains and provides a list of structurally similar proteins along with their structure alignments. Using CE, structure-structure alignments can provide insights into biological function. When a protein of known function is shown to be structurally similar to a protein of unknown function, a relationship might be inferred; a relationship not necessarily detectable from sequence comparison alone. Establishing structure-structure relationships in this way is of great importance as we enter an era of structural genomics where there is a likelihood of an increasing number of structures with unknown functions being determined. Thus the CE database is an example of a useful tool in the annotation of protein structures of unknown function. Comparisons can be performed on the complete PDB or on a structurally representative subset of proteins. The source protein(s) can be from the PDB (updated monthly) or uploaded by the user. CE provides sequence alignments resulting from structural alignments and Cartesian coordinates for the aligned structures, which may be analyzed using the supplied Compare3D Java applet, or downloaded for further local analysis. Searches can be run from the CE web site, http://cl.sdsc.edu/ce.html, or the database and software downloaded from the site for local use.

CKAAPs DB: a conserved key amino acid positions database.

The Conserved Key Amino Acid Positions DataBase (CKAAPs DB) provides access to an analysis of structurally similar proteins with dissimilar sequences where key residues within a common fold are identified. The derivation and significance of CKAAPs starting from pairwise structure alignments is described fully in Reddy et al. [Reddy,B.V.B., Li,W.W., Shindyalov,I.N. and Bourne,P.E. (2000) PROTEINS:, in press]. The CKAAPs identified from this theoretical analysis are provided to experimentalists and theoreticians for potential use in protein engineering and modeling. It has been suggested that CKAAPs may be crucial features for protein folding, structural stability and function. Over 170 substructures, as defined by the Combinatorial Extension (CE) database, which are found in approximately 3000 representative polypeptide chains have been analyzed and are available in the CKAAPs DB. CKAAPs DB also provides CKAAPs of the representative set of proteins derived from the CE and FSSP databases. Thus the database contains over 5000 representative poly-peptide chains, covering all known structures in the PDB. A web interface to a relational database permits fast retrieval of structure-sequence alignments, CKAAPs and associated statistics. Users may query by PDB ID, protein name, function and Enzyme Classification number. Users may also submit protein alignments of their own to obtain CKAAPs. An interface to display CKAAPs on each structure from a web browser is also being implemented. CKAAPs DB is maintained by the San Diego Supercomputer Center and accessible at the URL http://ckaaps.sdsc.edu.

The Protein Data Bank and the challenge of structural genomics.

The PDB has created systems for the processing, exchange, query, and distribution of data that will enable many aspects of high throughput structural genomics.

STAR/mmCIF: an ontology for macromolecular structure.

MOTIVATION: Crystallographers were motivated 10 years ago to develop a simple and consistent data representation for the exchange and archiving of data associated with the crystallographic experiment and the final structure. As this process evolved (and the data grew at near exponential rates) came the recognition that this representation should also facilitate the automated management of the data and, with the aid of additional software for verification and validation, provide improved consistency and accuracy and hence improved scientific inquiry. This realization led to a new Dictionary Definition Language (DDL) and an extensive dictionary based on this DDL for describing macromolecular structure. In broad terms this could be considered an ontology. An important feature in the development of the ontology was the endorsement and ongoing maintenance and support of the International Union of Crystallography (IUCr). While the description of macromolecular structure and the x-ray crystallographic experiment used to derive it represent explicit data, the ontology is extensible and applicable to other less well-characterized data domains. RESULTS: Details of the DDL, the dictionaries that have been developed, and software for reading and using this ontology are presented. AVAILABILITY: Extensive documentation, software tools and the DDL and dictionaries are available from http://ndbserver.rutgers.edu/mmcif and associated mirror sites. CONTACT: Bourne: bourne@sdsc.edu and Westbrook:jwest@rcsp.rutgers.edu

Common EF-hand motifs in cholinesterases and neuroligins suggest a role for Ca2+ binding in cell surface associations.

Comparisons of protein sequence via cyclic training of Hidden Markov Models (HMMs) in conjunction with alignments of three-dimensional structure, using the Combinatorial Extension (CE) algorithm, reveal two putative EF-hand metal binding domains in acetylcholinesterase. Based on sequence similarity, putative EF-hands are also predicted for the neuroligin family of cell surface proteins. These predictions are supported by experimental evidence. In the acetylcholinesterase crystal structure from Torpedo californica, the first putative EF-hand region binds the Zn2+ found in the heavy metal replacement structure. Further, the interaction of neuroligin 1 with its cognate receptor neurexin depends on Ca2+. Thus, members of the alpha,beta hydrolase fold family of proteins contain potential Ca2+ binding sites, which in some family members may be critical for heterologous cell associations.

An alternative view of protein fold space.

Comparing and subsequently classifying protein structures information has received significant attention concurrent with the increase in the number of experimentally derived 3-dimensional structures. Classification schemes have focused on biological function found within protein domains and on structure classification based on topology. Here an alternative view is presented that groups substructures. Substructures are long (50-150 residue) highly repetitive near-contiguous pieces of polypeptide chain that occur frequently in a set of proteins from the PDB defined as structurally non-redundant over the complete polypeptide chain. The substructure classification is based on a previously reported Combinatorial Extension (CE) algorithm that provides a significantly different set of structure alignments than those previously described, having, for example, only a 40% overlap with FSSP. Qualitatively the algorithm provides longer contiguous aligned segments at the price of a slightly higher root-mean-square deviation (rmsd). Clustering these alignments gives a discreet and highly repetitive set of substructures not detectable by sequence similarity alone. In some cases different substructures represent all or different parts of well known folds indicative of the Russian doll effect--the continuity of protein fold space. In other cases they fall into different structure and functional classifications. It is too early to determine whether these newly classified substructures represent new insights into the evolution of a structural framework important to many proteins. What is apparent from on-going work is that these substructures have the potential to be useful probes in finding remote sequence homology and in structure prediction studies. The characteristics of the complete all-by-all comparison of the polypeptide chains present in the PDB and details of the filtering procedure by pair-wise structure alignment that led to the emergent substructure gallery are discussed. Substructure classification, alignments, and tools to analyze them are available at http://cl.sdsc.edu/ce.html.

The Protein Data Bank.

The Protein Data Bank (PDB; http://www.rcsb.org/pdb/ ) is the single worldwide archive of structural data of biological macromolecules. This paper describes the goals of the PDB, the systems in place for data deposition and access, how to obtain further information, and near-term plans for the future development of the resource.

Developing protein documentaries and other multimedia presentations for molecular biology.

Computer-based multimedia technology for distance learning and research has come of age--the price point is acceptable, domain experts using off-the-shelf software can prepare compelling materials, and the material can be efficiently delivered via the Internet to a large audience. While not presenting any new scientific results, this paper outlines experiences with a variety of commercial and free software tools and the associated protocols we have used to prepare protein documentaries and other multimedia presentations relevant to molecular biology. A protein documentary is defined here as a description of the relationship between structure and function in a single protein or in a related family of proteins. A description using text and images which is further enhanced by the use of sound and interactive graphics. Examples of documentaries prepared to describe cAMP dependent protein kinase, the founding structural member of the protein kinase family for which there is now over 40 structures can be found at http://franklin.burnham-inst.org/rcsb. A variety of other prototype multimedia presentations for molecular biology described in this paper can be found at http://fraklin.burnham-inst.org.