RCSB Protein Data Bank (RCSB.org): delivery of experimentally-determined PDB structures alongside one million computed structure models of proteins from artificial intelligence/machine learning.

The Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB), founding member of the Worldwide Protein Data Bank (wwPDB), is the US data center for the open-access PDB archive. As wwPDB-designated Archive Keeper, RCSB PDB is also responsible for PDB data security. Annually, RCSB PDB serves >10 000 depositors of three-dimensional (3D) biostructures working on all permanently inhabited continents. RCSB PDB delivers data from its research-focused RCSB.org web portal to many millions of PDB data consumers based in virtually every United Nations-recognized country, territory, etc. This Database Issue contribution describes upgrades to the research-focused RCSB.org web portal that created a one-stop-shop for open access to ∼200 000 experimentally-determined PDB structures of biological macromolecules alongside >1 000 000 incorporated Computed Structure Models (CSMs) predicted using artificial intelligence/machine learning methods. RCSB.org is a 'living data resource.' Every PDB structure and CSM is integrated weekly with related functional annotations from external biodata resources, providing up-to-date information for the entire corpus of 3D biostructure data freely available from RCSB.org with no usage limitations. Within RCSB.org, PDB structures and the CSMs are clearly identified as to their provenance and reliability. Both are fully searchable, and can be analyzed and visualized using the full complement of RCSB.org web portal capabilities.

RCSB Protein Data bank: Tools for visualizing and understanding biological macromolecules in 3D.

Now in its 52nd year of continuous operations, the Protein Data Bank (PDB) is the premiere open-access global archive housing three-dimensional (3D) biomolecular structure data. It is jointly managed by the Worldwide Protein Data Bank (wwPDB) partnership. The Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB) is funded by the National Science Foundation, National Institutes of Health, and US Department of Energy and serves as the US data center for the wwPDB. RCSB PDB is also responsible for the security of PDB data in its role as wwPDB-designated Archive Keeper. Every year, RCSB PDB serves tens of thousands of depositors of 3D macromolecular structure data (coming from macromolecular crystallography, nuclear magnetic resonance spectroscopy, electron microscopy, and micro-electron diffraction). The RCSB PDB research-focused web portal (RCSB.org) makes PDB data available at no charge and without usage restrictions to many millions of PDB data consumers around the world. The RCSB PDB training, outreach, and education web portal (PDB101.RCSB.org) serves nearly 700 K educators, students, and members of the public worldwide. This invited Tools Issue contribution describes how RCSB PDB (i) is organized; (ii) works with wwPDB partners to process new depositions; (iii) serves as the wwPDB-designated Archive Keeper; (iv) enables exploration and 3D visualization of PDB data via RCSB.org; and (v) supports training, outreach, and education via PDB101.RCSB.org. New tools and features at RCSB.org are presented using examples drawn from high-resolution structural studies of proteins relevant to treatment of human cancers by targeting immune checkpoints.

Python scripting for biochemistry and molecular biology in Jupyter Notebooks.

A programming workshop has been developed for biochemists and molecular biologists to introduce them to the power and flexibility of solving problems with Python. The workshop is designed to move users beyond a "plug-and-play" approach that is based on spreadsheets and web applications in their teaching and research to writing scripts to parse large collections of data and to perform dynamic calculations. The live-coding workshop is designed to introduce specific coding skills, as well as provide insight into the broader array of open-access resources and libraries that are available for scientific computation.

Evolution of the SARS-CoV-2 proteome in three dimensions (3D) during the first 6 months of the COVID-19 pandemic.

Understanding the molecular evolution of the SARS-CoV-2 virus as it continues to spread in communities around the globe is important for mitigation and future pandemic preparedness. Three-dimensional structures of SARS-CoV-2 proteins and those of other coronavirusess archived in the Protein Data Bank were used to analyze viral proteome evolution during the first 6 months of the COVID-19 pandemic. Analyses of spatial locations, chemical properties, and structural and energetic impacts of the observed amino acid changes in >48 000 viral isolates revealed how each one of 29 viral proteins have undergone amino acid changes. Catalytic residues in active sites and binding residues in protein-protein interfaces showed modest, but significant, numbers of substitutions, highlighting the mutational robustness of the viral proteome. Energetics calculations showed that the impact of substitutions on the thermodynamic stability of the proteome follows a universal bi-Gaussian distribution. Detailed results are presented for potential drug discovery targets and the four structural proteins that comprise the virion, highlighting substitutions with the potential to impact protein structure, enzyme activity, and protein-protein and protein-nucleic acid interfaces. Characterizing the evolution of the virus in three dimensions provides testable insights into viral protein function and should aid in structure-based drug discovery efforts as well as the prospective identification of amino acid substitutions with potential for drug resistance.

Evolution of the SARS-CoV-2 proteome in three dimensions (3D) during the first six months of the COVID-19 pandemic.

Three-dimensional structures of SARS-CoV-2 and other coronaviral proteins archived in the Protein Data Bank were used to analyze viral proteome evolution during the first six months of the COVID-19 pandemic. Analyses of spatial locations, chemical properties, and structural and energetic impacts of the observed amino acid changes in >48,000 viral proteome sequences showed how each one of the 29 viral study proteins have undergone amino acid changes. Structural models computed for every unique sequence variant revealed that most substitutions map to protein surfaces and boundary layers with a minority affecting hydrophobic cores. Conservative changes were observed more frequently in cores versus boundary layers/surfaces. Active sites and protein-protein interfaces showed modest numbers of substitutions. Energetics calculations showed that the impact of substitutions on the thermodynamic stability of the proteome follows a universal bi-Gaussian distribution. Detailed results are presented for six drug discovery targets and four structural proteins comprising the virion, highlighting substitutions with the potential to impact protein structure, enzyme activity, and functional interfaces. Characterizing the evolution of the virus in three dimensions provides testable insights into viral protein function and should aid in structure-based drug discovery efforts as well as the prospective identification of amino acid substitutions with potential for drug resistance.

Publishing in education: A parallel session at the IUBMB/PSBMB 2019 "Harnessing Interdisciplinary Education in Biochemistry and Molecular Biology" conference.

Ensuring currency with trends, knowledge, and understanding of teaching and learning is essential for all educators. Researching learning and teaching is an enormous field which can range from examining the practical impact of new classes to research into the processes of learning. The "Publishing in Education" conference session discussed some of the approaches and outcomes of researching and publishing in education.

Laboratory classes in biochemistry and molecular biology: A parallel session at the IUBMB/PSBMB 2019 "Harnessing Interdisciplinary Education in Biochemistry and Molecular Biology" conference.

Laboratory classes are a central element of all biochemistry and molecular biology programs. These play a role in developing students' hands-on and technical skills and also offer much more. The design of laboratory classes depends on many factors including the programs the students are enrolled in, the level they are at, employment destinations, and learning outcomes. This conference session considered the design and outcomes of laboratory experiences for undergraduate students.

Publishing your educational research.

Publishing has always been a part of academic tradition and there is increasing pressure on faculty to publish, even those who carry heavy teaching loads. This article, based on a presentation at the IUBMB 2019 Education Conference session on Publishing in Education, contains suggestions on how to conduct educational research with an eye toward publishing your findings.

Something old, something new: Teaching the BMB lab.

Lab courses are a significant component of biochemistry and molecular biology (BMB) education. In teaching the labs, we combine established techniques with novel approaches. Lab formats have also moved from traditional cookbook style labs to guided inquiry to course-based undergraduate research experiences (CUREs), where faculty bring their own research interests into the course setting with a larger number of students in a much more restricted time frame. This presentation is designed to explore some of these ideas and challenge the reader to introduce research opportunities to all students, not just the smaller group of students in their research labs.

Developing and applying computational resources for biochemistry education.

Biochemistry is about structure and function, but it is also about data and this is where computers come in. From my time as a graduate student and post doc, whenever I encountered data I thought, "I can work this up by hand, but I think a computer could do a better job." Since that time, I have been working at the interface of biochemistry and computers, by attracting talented students and collaborating with colleagues with complementary skills. This has resulted in several exciting projects: a simulation of 2D electrophoresis and tandem mass spectrometry, the human visualization project, and two different programs that enable biochemists to search protein structures for enzyme active sites: ProMOL (promol.org) and Moltimate (moltimate.appspot.com). The human side of software development for education involved finding the right students and colleagues, communicating effectively across disciplines, building and managing effective teams and the importance of serendipity throughout the process.

BioVR: a platform for virtual reality assisted biological data integration and visualization.

BACKGROUND: Functional characterization of single nucleotide variants (SNVs) involves two steps, the first step is to convert DNA to protein and the second step is to visualize protein sequences with their structures. As massively parallel sequencing has emerged as a leading technology in genomics, resulting in a significant increase in data volume, direct visualization of SNVs together with associated protein sequences/structures in a new user interface (UI) would be a more effective way to assess their potential effects on protein function. RESULTS: We have developed BioVR, an easy-to-use interactive, virtual reality (VR)-assisted platform for integrated visual analysis of DNA/RNA/protein sequences and protein structures using Unity3D and the C# programming language. It utilizes the cutting-edge Oculus Rift, and Leap Motion hand detection, resulting in intuitive navigation and exploration of various types of biological data. Using Gria2 and its associated gene product as an example, we present this proof-of-concept software to integrate protein and nucleic acid data. For any amino acid or nucleotide of interest in the Gria2 sequence, it can be quickly linked to its corresponding location on Gria2 protein structure and visualized within VR. CONCLUSIONS: Using innovative 3D techniques, we provide a VR-based platform for visualization of DNA/RNA sequences and protein structures in aggregate, which can be extended to view omics data.

Lessons from my undergraduate research students.

From very early on, my personal/professional life has been shaped by teachers in many different settings. Teaching and learning form a two-way street. In the process of teaching undergraduate students, particularly in the research lab, I have learned some profound lessons about the importance of listening to them, challenging them, giving them autonomy, and allowing them to enjoy success and to risk failure. I am now working with a team of faculty members to implement these lessons in a course-based undergraduate research experience in the biochemistry teaching laboratory. Our goal is to seek answers to the question "How do students become scientists?" and to implement those answers with our future students.

A survey on faculty perspectives on the transition to a biochemistry course-based undergraduate research experience laboratory.

It will always remain a goal of an undergraduate biochemistry laboratory course to engage students hands-on in a wide range of biochemistry laboratory experiences. In 2006, our research group initiated a project for in silico prediction of enzyme function based only on the 3D coordinates of the more than 3800 proteins "of unknown function" in the Protein Data Bank, many of which resulted from the Protein Structure Initiative. Students have used the ProMOL plugin to the PyMOL molecular graphics environment along with BLAST, Pfam, and Dali to predict protein functions. As young scientists, these undergraduate research students wanted to see if their predictions were correct and so they developed an approach for in vitro testing of predicted enzyme function that included literature exploration, selection of a suitable assay and the search for commercially available substrates. Over the past two years, a team of faculty members from seven different campuses (California Polytechnic San Luis Obispo, Hope College, Oral Roberts University, Rochester Institute of Technology, St. Mary's University, Ursinus College, and Purdue University) have transferred this approach to the undergraduate biochemistry teaching laboratory as a Course-based Undergraduate Research Experience. A series of ten course modules and eight instructional videos have been created (www.promol.org/home/basil-modules-1) and the group is now expanding these resources, creating assessments and evaluating how this approach helps student to grow as scientists. The focus of this manuscript will be the logistical implications of this transition on campuses that have different cultures, expectations, schedules, and student populations. © 2017 by The International Union of Biochemistry and Molecular Biology, 45(5):426-436, 2017.

An expanded framework for biomolecular visualization in the classroom: Learning goals and competencies.

A thorough understanding of the molecular biosciences requires the ability to visualize and manipulate molecules in order to interpret results or to generate hypotheses. While many instructors in biochemistry and molecular biology use visual representations, few indicate that they explicitly teach visual literacy. One reason is the need for a list of core content and competencies to guide a more deliberate instruction in visual literacy. We offer here the second stage in the development of one such resource for biomolecular three-dimensional visual literacy. We present this work with the goal of building a community for online resource development and use. In the first stage, overarching themes were identified and submitted to the biosciences community for comment: atomic geometry; alternate renderings; construction/annotation; het group recognition; molecular dynamics; molecular interactions; monomer recognition; symmetry/asymmetry recognition; structure-function relationships; structural model skepticism; and topology and connectivity. Herein, the overarching themes have been expanded to include a 12th theme (macromolecular assemblies), 27 learning goals, and more than 200 corresponding objectives, many of which cut across multiple overarching themes. The learning goals and objectives offered here provide educators with a framework on which to map the use of molecular visualization in their classrooms. In addition, the framework may also be used by biochemistry and molecular biology educators to identify gaps in coverage and drive the creation of new activities to improve visual literacy. This work represents the first attempt, to our knowledge, to catalog a comprehensive list of explicit learning goals and objectives in visual literacy. © 2016 by The International Union of Biochemistry and Molecular Biology, 45(1):69-75, 2017.

Team Training for Dynamic Cross-Functional Teams in Aviation: Behavioral, Cognitive, and Performance Outcomes.

OBJECTIVE: This study evaluates the effectiveness of a training program designed to improve cross-functional coordination in airline operations. BACKGROUND: Teamwork across professional specializations is essential for safe and efficient airline operations, but aviation education primarily emphasizes positional knowledge and skill. Although crew resource management training is commonly used to provide some degree of teamwork training, it is generally focused on specific specializations, and little training is provided in coordination across specializations. METHOD: The current study describes and evaluates a multifaceted training program designed to enhance teamwork and team performance of cross-functional teams within a simulated airline flight operations center. The training included a variety of components: orientation training, position-specific declarative knowledge training, position-specific procedural knowledge training, a series of high-fidelity team simulations, and a series of after-action reviews. RESULTS: Following training, participants demonstrated more effective teamwork, development of transactive memory, and more effective team performance. CONCLUSION: Multifaceted team training that incorporates positional training and team interaction in complex realistic situations and followed by after-action reviews can facilitate teamwork and team performance. APPLICATION: Team training programs, such as the one described here, have potential to improve the training of aviation professionals. These techniques can be applied to other contexts where multidisciplinary teams and multiteam systems work to perform highly interdependent activities.

Automated protein motif generation in the structure-based protein function prediction tool ProMOL.

ProMOL, a plugin for the PyMOL molecular graphics system, is a structure-based protein function prediction tool. ProMOL includes a set of routines for building motif templates that are used for screening query structures for enzyme active sites. Previously, each motif template was generated manually and required supervision in the optimization of parameters for sensitivity and selectivity. We developed an algorithm and workflow for the automation of motif building and testing routines in ProMOL. The algorithm uses a set of empirically derived parameters for optimization and requires little user intervention. The automated motif generation algorithm was first tested in a performance comparison with a set of manually generated motifs based on identical active sites from the same 112 PDB entries. The two sets of motifs were equally effective in identifying alignments with homologs and in rejecting alignments with unrelated structures. A second set of 296 active site motifs were generated automatically, based on Catalytic Site Atlas entries with literature citations, as an expansion of the library of existing manually generated motif templates. The new motif templates exhibited comparable performance to the existing ones in terms of hit rates against native structures, homologs with the same EC and Pfam designations, and randomly selected unrelated structures with a different EC designation at the first EC digit, as well as in terms of RMSD values obtained from local structural alignments of motifs and query structures. This research is supported by NIH grant GM078077.

Annotation of proteins of unknown function: initial enzyme results.

Working with a combination of ProMOL (a plugin for PyMOL that searches a library of enzymatic motifs for local structural homologs), BLAST and Pfam (servers that identify global sequence homologs), and Dali (a server that identifies global structural homologs), we have begun the process of assigning functional annotations to the approximately 3,500 structures in the Protein Data Bank that are currently classified as having "unknown function". Using a limited template library of 388 motifs, over 500 promising in silico matches have been identified by ProMOL, among which 65 exceptionally good matches have been identified. The characteristics of the exceptionally good matches are discussed.

Estimation of protein function using template-based alignment of enzyme active sites.

BACKGROUND: The accumulation of protein structural data occurs more rapidly than it can be characterized by traditional laboratory means. This has motivated widespread efforts to predict enzyme function computationally. The most useful/accurate strategies employed to date are based on the detection of motifs in novel structures that correspond to a specific function. Functional residues are critical components of predictively useful motifs. We have implemented a novel method, to complement current approaches, which detects motifs solely on the basis of distance restraints between catalytic residues. RESULTS: ProMOL is a plugin for the PyMOL molecular graphics environment that can be used to create active site motifs for enzymes. A library of 181 active site motifs has been created with ProMOL, based on definitions published in the Catalytic Site Atlas (CSA). Searches with ProMOL produce better than 50% useful Enzyme Commission (EC) class suggestions for level 1 searches in EC classes 1, 4 and 5, and produce some useful results for other classes. 261 additional motifs automatically translated from Jonathan Barker's JESS motif set [Bioinformatics 19:1644-1649, 2003] and a set of NMR motifs is under development. Alignments are evaluated by visual superposition, Levenshtein distance and root-mean-square deviation (RMSD) and are reasonably consistent with related search methods. CONCLUSION: The ProMOL plugin for PyMOL provides ready access to template-based local alignments. Recent improvements to ProMOL, including the expanded motif library, RMSD calculations and output selection formatting, have greatly increased the program's usability and speed, and have improved the way that the results are presented.

A survey of educational uses of molecular visualization freeware.

As biochemists, one of our most captivating teaching tools is the use of molecular visualization. It is a compelling medium that can be used to communicate structural information much more effectively with interactive animations than with static figures. We have conducted a survey to begin a systematic evaluation of the current classroom usage of molecular visualization. Participants (n = 116) were asked to complete 11 multiple choice and 3 open ended questions. To provide more depth to these results, interviews were conducted with 12 of the participants. Many common themes arose in the survey and the interviews: a shared passion for the use of molecular visualization in teaching, broad diversity in software preference, the lack of uniform standards for assessment, a desire for more quality resources, and the challenge of enabling students to incorporate visualization in their learning. The majority of respondents had used molecular visualization for more than 5 years and mentioned 32 different visualization tools used, with Jmol and PyMOL clearly standing out as the most frequently used programs at the present time. The most common uses of molecular visualization in teaching were lecture and lab illustrations, followed by exam questions, in-class or in-laboratory exercises, and student projects, which frequently included presentations. While a minority of instructors used a grading rubric/scoring matrix for assessment of student learning with molecular visualization, many expressed a desire for common use assessment tools.