Automated Landmarking via Multiple Templates

Geometric morphometrics based on landmark data has been increasingly used in biomedical and biological researchers for quantifying complex phenotypes. However, manual landmarking can be laborious and subject to intra and interobserver errors. This has motivated the development of automated landmarking methods. We have recently introduced ALPACA (Automated Landmarking through Point cloud Alignment and Correspondence), a fast method to automatically annotate landmarks via use of a landmark template as part of the SlicerMorph toolkit. Yet, using a single template may not consistently perform well for large study samples, especially when the sample consists of specimen with highly variable morphology, as it is common evolutionary studies. In this study, we introduce a variation on our ALPACA pipeline that supports multiple specimen templates, which we call MALPACA. We show that MALPACA outperforms ALPACA consistently by testing on two different datasets. We also introduce a method of choosing the templates that can be used in conjunction with MALPACA, when no prior information is available. This K-means method uses an approximation of the total morphological variation in the dataset to suggest samples within the population to be used as landmark templates. While we advise investigators to pay careful attention to the template selection process in any of the template-based automated landmarking approaches, our analyses show that the introduced K-means based method of templates selection is better than randomly choosing the templates. In summary, MALPACA can accommodate larger morphological disparity commonly found in evolutionary studies with performance comparable to human observer.

Applying Waveform Correlation to Reduce Seismic Analyst Workload Due to Repeating Mining Blasts

ABSTRACT Agencies that monitor for underground nuclear tests are interested in techniques that automatically characterize mining blasts to reduce the human analyst effort required to produce high-quality event bulletins. Waveform correlation is effective in finding similar waveforms from repeating seismic events, including mining blasts. We report the results of an experiment to detect and identify mining blasts for two regions, Wyoming (U.S.A.) and Scandinavia, using waveform templates recorded by multiple International Monitoring System stations of the Preparatory Commission for the Comprehensive Nuclear-Test-Ban Treaty Organization (CTBTO PrepCom) for up to 10 yr prior to the time of interest. We discuss approaches for template selection, threshold setting, and event detection that are specialized for characterizing mining blasts using a sparse, global network. We apply the approaches to one week of data for each of the two regions to evaluate the potential for establishing a set of standards for waveform correlation processing of mining blasts that can be generally applied to operational monitoring systems with a sparse network. We compare candidate events detected with our processing methods to the Reviewed Event Bulletin of the International Data Centre to assess potential reduction in analyst workload.

Insights into Comparative Modeling of VHH Domains

In the particular case of the Camelidae family, immunoglobulin proteins have evolved into a unique and more simplified architecture with only heavy chains. The variable domains of these chains, named VHHs, have a number of Complementary Determining Regions (CDRs) reduced by half, and can function as single domains making them good candidates for molecular tools. 3D structure prediction of these domains is a beneficial and advantageous step to advance their developability as molecular tools. Nonetheless, the conformations of CDRs loops in these domains remain difficult to predict due to their higher conformational diversity. In addition to CDRs loop diversity, our earlier study has established that Framework Regions (FRs) are also not entirely conformationally conserved which establishes a need for more rigorous analyses of these regions that could assist in template selection. In the current study, VHHs models using different template selection strategies for comparative modeling using Modeller have been extensively assessed. This study analyses the conformational changes in both CDRs and FRs using an original strategy of conformational discretization based on a structural alphabet. Conformational sampling in selected cases is precisely reported. Some interesting outcomes of the structural analyses of models also draw attention towards the distinct difficulty in 3D structure prediction of VHH domains.

BIO-GATS: A Tool for Automated GPCR Template Selection Through a Biophysical Approach for Homology Modeling

G protein-coupled receptors (GPCRs) are the largest family of membrane proteins with more than 800 members. GPCRs are involved in numerous physiological functions within the human body and are the target of more than 30% of the United States Food and Drug Administration (FDA) approved drugs. At present, over 400 experimental GPCR structures are available in the Protein Data Bank (PDB) representing 76 unique receptors. The absence of an experimental structure for the majority of GPCRs demand homology models for structure-based drug discovery workflows. The generation of good homology models requires appropriate templates. The commonly used methods for template selection are based on sequence identity. However, there exists low sequence identity among the GPCRs. Sequences with similar patterns of hydrophobic residues are often structural homologs, even with low sequence identity. Extending this, we propose a biophysical approach for template selection based principally on hydrophobicity correspondence between the target and the template. Our approach takes into consideration other relevant parameters, including resolution, similarity within the orthosteric binding pocket of GPCRs, and structure completeness, for template selection. The proposed method was implemented in the form of a free tool called Bio-GATS, to provide the user with easy selection of the appropriate template for a query GPCR sequence. Bio-GATS was successfully validated with recent published benchmarking datasets. An application to an olfactory receptor to select an appropriate template has also been provided as a case study.