Structure calculation, refinement and validation using CcpNmr Analysis

CcpNmr Analysis provides a streamlined pipeline for both NMR chemical shift assignment and structure determination of biological macromolecules. In addition, it encompasses tools to analyse the many additional experiments that make NMR such a pivotal technique for research into complex biological questions. This report describes how CcpNmr Analysis can seamlessly link together all of the tasks in the NMR structure-determination process. It details each of the stages from generating NMR restraints [distance, dihedral,hydrogen bonds and residual dipolar couplings (RDCs)],exporting these to and subsequently re-importing them from structure-calculation software (such as the programs CYANA or ARIA) and analysing and validating the results obtained from the structure calculation to, ultimately, the streamlined deposition of the completed assignments and the refined ensemble of structures into the PDBe repository. Until recently, such solution-structure determination by NMR has been quite a laborious task, requiring multiple stages and programs. However, with the new enhancements to CcpNmr Analysis described here, this process is now much more intuitive and efficient and less error-prone

A software framework for analysing solid-state MAS NMR data

Solid-state magic-angle-spinning (MAS) NMR of proteins has undergone many rapid methodological developments in recent years, enabling detailed studies of protein structure, function and dynamics. Software development, however, has not kept pace with these advances and data analysis is mostly performed using tools developed for solution NMR which do not directly address solid-state specific issues. Here we present additions to the CcpNmr Analysis software package which enable easier identification of spinning side bands, straightforward analysis of double quantum spectra, automatic consideration of non-uniform labelling schemes, as well as extension of other existing features to the needs of solid-state MAS data. To underpin this, we have updated and extended the CCPN data model and experiment descriptions to include transfer types and nomenclature appropriate for solid-state NMR experiments, as well as a set of experiment prototypes covering the experiments commonly employed by solid-sate MAS protein NMR spectroscopists. This work not only improves solid-state MAS NMR data analysis but provides a platform for anyone who uses the CCPN data model for programming, data transfer, or data archival involving solid-state MAS NMR data

SARS-CoV-2 antibody prevalence among homeless people and shelter workers in Denmark:a nationwide cross-sectional study

BACKGROUND: People experiencing homelessness (PEH) and associated shelter workers may be at higher risk of infection with “Severe acute respiratory syndrome coronavirus 2” (SARS-CoV-2). The aim of this study was to determine the prevalence of SARS-CoV-2 among PEH and shelter workers in Denmark. DESIGN AND METHODS: In November 2020, we conducted a nationwide cross-sectional seroprevalence study among PEH and shelter workers at 21 recruitment sites in Denmark. The assessment included a point-of-care test for antibodies against SARS-CoV-2, followed by a questionnaire. The seroprevalence was compared to that of geographically matched blood donors considered as a proxy for the background population, tested using a total Ig ELISA assay. RESULTS: We included 827 participants in the study, of whom 819 provided their SARS-CoV-2 antibody results. Of those, 628 were PEH (median age 50.8 (IQR 40.9–59.1) years, 35.5% female) and 191 were shelter workers (median age 46.6 (IQR 36.1–55.0) years and 74.5% female). The overall seroprevalence was 6.7% and was similar among PEH and shelter workers (6.8% vs 6.3%, p = 0.87); and 12.2% among all participants who engaged in sex work. The overall participant seroprevalence was significantly higher than that of the background population (2.9%, p < 0.001). When combining all participants who reported sex work or were recruited at designated safe havens, we found a significantly increased risk of seropositivity compared to other participants (OR 2.23, 95%CI 1.06–4.43, p = 0.02). Seropositive and seronegative participants reported a similar presence of at least one SARS-CoV-2 associated symptom (49% and 54%, respectively). INTERPRETATIONS: The prevalence of SARS-CoV-2 antibodies was more than twice as high among PEH and associated shelter workers, compared to the background population. These results could be taken into consideration when deciding in which phase PEH are eligible for a vaccine, as part of the Danish national SARS-CoV-2 vaccination program rollout. FUNDING: TrygFonden and HelseFonden. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12889-022-13642-7

MEMOPS: Data modelling and automatic code generation

In recent years the amount of biological data has exploded to the point where much useful information can only be extracted by complex computational analyses. Such analyses are greatly facilitated by metadata standards, both in terms of the ability to compare data originating from different sources, and in terms of exchanging data in standard forms, e.g. when running processes on a distributed computing infrastructure. However, standards thrive on stability whereas science tends to constantly move, with new methods being developed and old ones modified. Therefore maintaining both metadata standards, and all the code that is required to make them useful, is a non-trivial problem. Memops is a framework that uses an abstract definition of the metadata (described in UML) to generate internal data structures and subroutine libraries for data access (application programming interfaces - APIs - currently in Python, C and Java) and data storage (in XML files or databases). For the individual project these libraries obviate the need for writing code for input parsing, validity checking or output. Memops also ensures that the code is always internally consistent, massively reducing the need for code reorganisation. Across a scientific domain a Memops-supported data model makes it easier to support complex standards that can capture all the data produced in a scientific area, share them among all programs in a complex software pipeline, and carry them forward to deposition in an archive. The principles behind the Memops generation code will be presented, along with example applications in Nuclear Magnetic Resonance (NMR) spectroscopy and structural biology

CcpNmr AnalysisAssign: a flexible platform for integrated NMR analysis.

NMR spectroscopy is an indispensably powerful technique for the analysis of biomolecules under ambient conditions, both for structural- and functional studies. However, in practice the complexity of the technique has often frustrated its application by non-specialists. In this paper, we present CcpNmr version-3, the latest software release from the Collaborative Computational Project for NMR, for all aspects of NMR data analysis, including liquid- and solid-state NMR data. This software has been designed to be simple, functional and flexible, and aims to ensure that routine tasks can be performed in a straightforward manner. We have designed the software according to modern software engineering principles and leveraged the capabilities of modern graphics libraries to simplify a variety of data analysis tasks. We describe the process of backbone assignment as an example of the flexibility and simplicity of implementing workflows, as well as the toolkit used to create the necessary graphics for this workflow. The package can be downloaded from www.ccpn.ac.uk/v3-software/downloads and is freely available to all non-profit organisations

CcpNmr AnalysisAssign: a flexible platform for integrated NMR analysis.

NMR spectroscopy is an indispensably powerful technique for the analysis of biomolecules under ambient conditions, both for structural- and functional studies. However, in practice the complexity of the technique has often frustrated its application by non-specialists. In this paper, we present CcpNmr version-3, the latest software release from the Collaborative Computational Project for NMR, for all aspects of NMR data analysis, including liquid- and solid-state NMR data. This software has been designed to be simple, functional and flexible, and aims to ensure that routine tasks can be performed in a straightforward manner. We have designed the software according to modern software engineering principles and leveraged the capabilities of modern graphics libraries to simplify a variety of data analysis tasks. We describe the process of backbone assignment as an example of the flexibility and simplicity of implementing workflows, as well as the toolkit used to create the necessary graphics for this workflow. The package can be downloaded from www.ccpn.ac.uk/v3-software/downloads and is freely available to all non-profit organisations

Analysis of the Structural Quality of the CASD-NMR 2013 Entries

We performed a comprehensive structure validation of both automated and manually generated structures of the 10 targets of the CASD-NMR-2013 effort. We established that automated structure determination protocols are capable of reliably producing structures of comparable accuracy and quality to those generated by a skilled researcher, at least for small, single domain proteins such as the ten targets tested. The most robust results appear to be obtained when NOESY peak lists are used either as the primary input data or to augment Chemical Shift (CS) data without the need to manually filter such lists. A detailed analysis of the long-range NOE restraints generated by the different programs from the same data showed a surprisingly low degree of overlap. Additionally, we found that there was no significant correlation between the extent of the NOE restraint overlap and the accuracy of the structure. This result was surprising given the importance of NOE data in producing good quality structures. We suggest that this could be explained by the information redundancy present in NOEs between atoms contained within a fixed covalent network