Updated resources for exploring experimentally-determined PDB structures and Computed Structure Models at the RCSB Protein Data Bank.

The Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB, RCSB.org), the US Worldwide Protein Data Bank (wwPDB, wwPDB.org) data center for the global PDB archive, provides access to the PDB data via its RCSB.

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 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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

Conscript: RasMol to PyMOL script converter.

The aim of the Structural Biology Extensible Visualization Scripting Language (SBEVSL) project is to allow users who are experts in one scripting language to use that language in a second molecular visualization environment without requiring the user to learn a new scripting language. ConSCRIPT, the first SBEVSL release, is a plug-in for PyMOL that accepts RasMol scripting commands either as premade scripts or as line-by-line entries from PyMOL's own command line. The plug-in is available for download at http://sourceforge.

Efficient molecular surface rendering by linear-time pseudo-Gaussian approximation to Lee-Richards surfaces (PGALRS).

The PGALRS (pseudo-Gaussian approximation to Lee-Richards surfaces) algorithm is discussed. By modeling electron density with unphysical pseudo-Gaussian atoms, the Lee-Richards surface can be approximated by a contour level of that density in time approximately linear in the number of atoms. Having that contour level, the atoms and residues closest to that surface can be identified in average time O[n(2/3)log(n)] using a NearTree-based nearest neighbor search.

Introducing proteomics in the undergraduate curriculum: A simple 2D gel electrophoresis exercise with serum proteins.

Two-dimensional gel electrophoresis (2DGE) remains an important tool in the study of biological systems by proteomics. While the use of 2DGE is commonplace in research publications, there are few instructional laboratories that address the use of 2DGE for analyzing complex protein samples. One reason for this lack is the fact that the preparation of samples for 2DGE is a complex and difficult process that can commonly yield gels of poor quality and resolution.

EZ-Viz, a tool for simplifying molecular viewing in PyMOL.

PyMOL is a molecular modeling program that can be used in a wide range of studies within the scientific community. Its ability to produce informative, detailed, stereoscopic images makes it a very powerful tool both in the laboratory and in the classroom. However, the PyMOL user interface is difficult to use, and the PyMOL User's Manual readily admits that "development has been focused on capabilities, not on ease-of-use for new users.