Targeted BRCA1/2 population screening among Ashkenazi Jewish individuals using a web-enabled medical model: An observational cohort study.

PURPOSE: This study aimed to evaluate uptake and follow-up using internet-assisted population genetic testing (GT) for BRCA1/2 Ashkenazi Jewish founder pathogenic variants (AJPVs). METHODS: Across 4 cities in the United States, from December 2017 to March 2020, individuals aged ≥25 years with ≥1 Ashkenazi Jewish grandparent were offered enrollment. Participants consented and enrolled online with chatbot and video education, underwent BRCA1/2 AJPV GT, and chose to receive results from their primary care provider (PCP) or study staff. Surveys were conducted at baseline, at 12 weeks, and annually for 5 years. RESULTS: A total of 5193 participants enrolled and 4109 (79.1%) were tested (median age = 54, female = 77.1%). Upon enrollment, 35.1% of participants selected a PCP to disclose results, and 40.5% of PCPs agreed. Of those tested, 138 (3.4%) were AJPV heterozygotes of whom 21 (15.2%) had no significant family history of cancer, whereas 86 (62.3%) had a known familial pathogenic variant. At 12 weeks, 85.5% of participants with AJPVs planned increased cancer screening; only 3.7% with negative results and a significant family history reported further testing. CONCLUSION: Although continued follow-up is needed, internet-enabled outreach can expand access to targeted GT using a medical model. Observed challenges for population genetic screening efforts include recruitment barriers, improving PCP engagement, and increasing uptake of additional testing when indicated.

The other 90% of the protein: assessment beyond the Calphas for CASP8 template-based and high-accuracy models.

For template-based modeling in the CASP8 Critical Assessment of Techniques for Protein Structure Prediction, this work develops and applies six new full-model metrics. They are designed to complement and add value to the traditional template-based assessment by the global distance test (GDT) and related scores (based on multiple superpositions of Calpha atoms between target structure and predictions labeled "Model 1"). The new metrics evaluate each predictor group on each target, using all atoms of their best model with above-average GDT. Two metrics evaluate how "protein-like" the predicted model is: the MolProbity score used for validating experimental structures, and a mainchain reality score using all-atom steric clashes, bond length and angle outliers, and backbone dihedrals. Four other new metrics evaluate match of model to target for mainchain and sidechain hydrogen bonds, sidechain end positioning, and sidechain rotamers. Group-average Z-score across the six full-model measures is averaged with group-average GDT Z-score to produce the overall ranking for full-model, high-accuracy performance. Separate assessments are reported for specific aspects of predictor-group performance, such as robustness of approximately correct template or fold identification, and self-scoring ability at identifying the best of their models. Fold identification is distinct from but correlated with group-average GDT Z-score if target difficulty is taken into account, whereas self-scoring is done best by servers and is uncorrelated with GDT performance. Outstanding individual models on specific targets are identified and discussed. Predictor groups excelled at different aspects, highlighting the diversity of current methodologies. However, good full-model scores correlate robustly with high Calpha accuracy.

KinImmerse: Macromolecular VR for NMR ensembles.

BACKGROUND: In molecular applications, virtual reality (VR) and immersive virtual environments have generally been used and valued for the visual and interactive experience - to enhance intuition and communicate excitement - rather than as part of the actual research process. In contrast, this work develops a software infrastructure for research use and illustrates such use on a specific case. METHODS: The Syzygy open-source toolkit for VR software was used to write the KinImmerse program, which translates the molecular capabilities of the kinemage graphics format into software for display and manipulation in the DiVE (Duke immersive Virtual Environment) or other VR system. KinImmerse is supported by the flexible display construction and editing features in the KiNG kinemage viewer and it implements new forms of user interaction in the DiVE. RESULTS: In addition to molecular visualizations and navigation, KinImmerse provides a set of research tools for manipulation, identification, co-centering of multiple models, free-form 3D annotation, and output of results. The molecular research test case analyzes the local neighborhood around an individual atom within an ensemble of nuclear magnetic resonance (NMR) models, enabling immersive visual comparison of the local conformation with the local NMR experimental data, including target curves for residual dipolar couplings (RDCs). CONCLUSION: The promise of KinImmerse for production-level molecular research in the DiVE is shown by the locally co-centered RDC visualization developed there, which gave new insights now being pursued in wider data analysis.

MolProbity: all-atom contacts and structure validation for proteins and nucleic acids.

MolProbity is a general-purpose web server offering quality validation for 3D structures of proteins, nucleic acids and complexes. It provides detailed all-atom contact analysis of any steric problems within the molecules as well as updated dihedral-angle diagnostics, and it can calculate and display the H-bond and van der Waals contacts in the interfaces between components. An integral step in the process is the addition and full optimization of all hydrogen atoms, both polar and nonpolar. New analysis functions have been added for RNA, for interfaces, and for NMR ensembles. Additionally, both the web site and major component programs have been rewritten to improve speed, convenience, clarity and integration with other resources. MolProbity results are reported in multiple forms: as overall numeric scores, as lists or charts of local problems, as downloadable PDB and graphics files, and most notably as informative, manipulable 3D kinemage graphics shown online in the KiNG viewer. This service is available free to all users at http://molprobity.biochem.duke.edu.