Biosurfer for systematic tracking of regulatory mechanisms leading to protein isoform diversity.

Long-read RNA sequencing has shed light on transcriptomic complexity, but questions remain about the functionality of downstream protein products. We introduce Biosurfer, a computational approach for comparing protein isoforms, while systematically tracking the transcriptional, splicing, and translational variations that underlie differences in the sequences of the protein products. Using Biosurfer, we analyzed the differences in 32,799 pairs of GENCODE annotated protein isoforms, finding a majority (70%) of variable N-termini are due to the alternative transcription start sites, while only 9% arise from 5' UTR alternative splicing. Biosurfer's detailed tracking of nucleotide-to-residue relationships helped reveal an uncommonly tracked source of single amino acid residue changes arising from the codon splits at junctions. For 17% of internal sequence changes, such split codon patterns lead to single residue differences, termed "ragged codons". Of variable C-termini, 72% involve splice- or intron retention-induced reading frameshifts. We found an unusual pattern of reading frame changes, in which the first frameshift is closely followed by a distinct second frameshift that restores the original frame, which we term a "snapback" frameshift. We analyzed long read RNA-seq-predicted proteome of a human cell line and found similar trends as compared to our GENCODE analysis, with the exception of a higher proportion of isoforms predicted to undergo nonsense-mediated decay. Biosurfer's comprehensive characterization of long-read RNA-seq datasets should accelerate insights of the functional role of protein isoforms, providing mechanistic explanation of the origins of the proteomic diversity driven by the alternative splicing. Biosurfer is available as a Python package at https://github.com/sheynkman-lab/biosurfer.

The current role and evolution of X-ray crystallography in drug discovery and development.

INTRODUCTION: Macromolecular X-ray crystallography and cryo-EM are currently the primary techniques used to determine the three-dimensional structures of proteins, nucleic acids, and viruses. Structural information has been critical to drug discovery and structural bioinformatics. The integration of artificial intelligence (AI) into X-ray crystallography has shown great promise in automating and accelerating the analysis of complex structural data, further improving the efficiency and accuracy of structure determination. AREAS COVERED: This review explores the relationship between X-ray crystallography and other modern structural determination methods. It examines the integration of data acquired from diverse biochemical and biophysical techniques with those derived from structural biology. Additionally, the paper offers insights into the influence of AI on X-ray crystallography, emphasizing how integrating AI with experimental approaches can revolutionize our comprehension of biological processes and interactions. EXPERT OPINION: Investing in science is crucially emphasized due to its significant role in drug discovery and advancements in healthcare. X-ray crystallography remains an essential source of structural biology data for drug discovery. Recent advances in biochemical, spectroscopic, and bioinformatic methods, along with the integration of AI techniques, hold the potential to revolutionize drug discovery when effectively combined with robust data management practices.

Continuous Validation Across Macromolecular Structure Determination Process.

The overall quality of the experimentally determined structures contained in the PDB is exceptionally high, mainly due to the continuous improvement of model building and structural validation programs. Improving reproducibility on a large scale requires expanding the concept of validation in structural biology and all other disciplines to include a broader framework that encompasses the entire project. A successful approach to science requires diligent attention to detail and a focus on the future. An earnest commitment to data availability and reuse is essential for scientific progress, be that by human minds or artificial intelligence.

Structural and biochemical characterisation of Co2+-binding sites on serum albumins and their interplay with fatty acids.

Serum albumin-Co2+ interactions are of clinical importance. They play a role in mediating the physiological effects associated with cobalt toxicity and are central to the albumin cobalt binding (ACB) assay for diagnosis of myocardial ischemia. To further understand these processes, a deeper understanding of albumin-Co2+ interactions is required. Here, we present the first crystallographic structures of human serum albumin (HSA; three structures) and equine serum albumin (ESA; one structure) in complex with Co2+. Amongst a total of sixteen sites bearing a cobalt ion across the structures, two locations were prominent, and they relate to metal-binding sites A and B. Site-directed mutagenesis and isothermal titration calorimetry (ITC) were employed to characterise sites on HSA. The results indicate that His9 and His67 contribute to the primary (putatively corresponding to site B) and secondary Co2+-binding sites (site A), respectively. The presence of additional multiple weak-affinity Co2+ binding sites on HSA was also supported by ITC studies. Furthermore, addition of 5 molar equivalents of the non-esterified fatty acid palmitate (C16:0) reduced the Co2+-binding affinity at both sites A and B. The presence of bound myristate (C14:0) in the HSA crystal structures provided insight into the fatty acid-mediated structural changes that diminish the affinity of the protein toward Co2+. Together, these data provide further support for the idea that ischemia-modified albumin corresponds to albumin with excessive fatty-acid loading. Collectively, our findings provide a comprehensive understanding of the molecular underpinnings governing Co2+ binding to serum albumin.

CMM-An enhanced platform for interactive validation of metal binding sites.

Metal ions bound to macromolecules play an integral role in many cellular processes. They can directly participate in catalytic mechanisms or be essential for the structural integrity of proteins and nucleic acids. However, their unique nature in macromolecules can make them difficult to model and refine, and a substantial portion of metal ions in the PDB are misidentified or poorly refined. CheckMyMetal (CMM) is a validation tool that has gained widespread acceptance as an essential tool for researchers working on metal-macromolecule complexes. CMM can be used during structure determination or to validate metal binding sites in structural models within the PDB. The functionalities of CMM have recently been greatly enhanced and provide researchers with additional information that can guide modeling decisions. The new version of CMM shows metals in the context of electron density maps and allows for on-the-fly refinement of metal binding sites. The improvements should increase the reproducibility of biomedical research. The web server is available at https://cmm.minorlab.org.

Optimal structure determination from sub-optimal diffraction data.

Herein we present the newest version of the HKL-3000 system that integrates data collection, data reduction, phasing, model building, refinement, and validation. The system significantly accelerates the process of structure determination and has proven its high value for the determination of very high-quality structures. The heuristic for choosing the best approach for every step of structure determination for various quality samples and diffraction data has been optimized. The latest modifications increase the likelihood of a successful structure determination with challenging data. The HKL-3000 is a successor of HKL and HKL-2000 programs. The use of the HKL family of programs has been reported for over 73,000 PDB deposits, that is, almost 50% of macromolecular structures determined with X-ray diffraction.

virusMED: an atlas of hotspots of viral proteins.

Metal binding sites, antigen epitopes and drug binding sites are the hotspots in viral proteins that control how viruses interact with their hosts. virusMED (virus Metal binding sites, Epitopes and Drug binding sites) is a rich internet application based on a database of atomic interactions around hotspots in 7041 experimentally determined viral protein structures. 25306 hotspots from 805 virus strains from 75 virus families were characterized, including influenza, HIV-1 and SARS-CoV-2 viruses. Just as Google Maps organizes and annotates points of interest, virusMED presents the positions of individual hotspots on each viral protein and creates an atlas upon which newly characterized functional sites can be placed as they are being discovered. virusMED contains an extensive set of annotation tags about the virus species and strains, viral hosts, viral proteins, metal ions, specific antibodies and FDA-approved drugs, which permits rapid screening of hotspots on viral proteins tailored to a particular research problem. The virusMED portal (https://virusmed.biocloud.top) can serve as a window to a valuable resource for many areas of virus research and play a critical role in the rational design of new preventative and therapeutic agents targeting viral infections.

Rapid response to emerging biomedical challenges and threats.

As part of the global mobilization to combat the present pandemic, almost 100 000 COVID-19-related papers have been published and nearly a thousand models of macromolecules encoded by SARS-CoV-2 have been deposited in the Protein Data Bank within less than a year. The avalanche of new structural data has given rise to multiple resources dedicated to assessing the correctness and quality of structural data and models. Here, an approach to evaluate the massive amounts of such data using the resource https://covid19.bioreproducibility.org is described, which offers a template that could be used in large-scale initiatives undertaken in response to future biomedical crises. Broader use of the described methodology could considerably curtail information noise and significantly improve the reproducibility of biomedical research.

Synchrotron Radiation as a Tool for Macromolecular X-Ray Crystallography: a XXI Century Perspective.

Intense X-rays available at powerful synchrotron beamlines provide macromolecular crystallographers with an incomparable tool for investigating biological phenomena on an atomic scale. The resulting insights into the mechanism's underlying biological processes have played an essential role and shaped biomedical sciences during the last 30 years, considered the "golden age" of structural biology. In this review, we analyze selected aspects of the impact of synchrotron radiation on structural biology. Synchrotron beamlines have been used to determine over 70% of all macromolecular structures deposited into the Protein Data Bank (PDB). These structures were deposited by over 13,000 different research groups. Interestingly, despite the impressive advances in synchrotron technologies, the median resolution of macromolecular structures determined using synchrotrons has remained constant throughout the last 30 years, at about 2 Å. Similarly, the median times from the data collection to the deposition and release have not changed significantly. We describe challenges to reproducibility related to recording all relevant data and metadata during the synchrotron experiments, including diffraction images. Finally, we discuss some of the recent opinions suggesting a diminishing importance of X-ray crystallography due to impressive advances in Cryo-EM and theoretical modeling. We believe that synchrotrons of the future will increasingly evolve towards a life science center model, where X-ray crystallography, Cryo-EM, and other experimental and computational resources and knowledge are encompassed within a versatile research facility. The recent response of crystallographers to the COVID-19 pandemic suggests that X-ray crystallography conducted at synchrotron beamlines will continue to play an essential role in structural biology and drug discovery for years to come.

Covid-19.bioreproducibility.org: A web resource for SARS-CoV-2-related structural models.

The COVID-19 pandemic has triggered numerous scientific activities aimed at understanding the SARS-CoV-2 virus and ultimately developing treatments. Structural biologists have already determined hundreds of experimental X-ray, cryo-EM, and NMR structures of proteins and nucleic acids related to this coronavirus, and this number is still growing. To help biomedical researchers, who may not necessarily be experts in structural biology, navigate through the flood of structural models, we have created an online resource, covid19.bioreproducibility.org, that aggregates expert-verified information about SARS-CoV-2-related macromolecular models. In this article, we describe this web resource along with the suite of tools and methodologies used for assessing the structures presented therein.

State-of-the-Art Data Management: Improving the Reproducibility, Consistency, and Traceability of Structural Biology and in Vitro Biochemical Experiments.

Efficient and comprehensive data management is an indispensable component of modern scientific research and requires effective tools for all but the most trivial experiments. The LabDB system developed and used in our laboratory was originally designed to track the progress of a structure determination pipeline in several large National Institutes of Health (NIH) projects. While initially designed for structural biology experiments, its modular nature makes it easily applied in laboratories of various sizes in many experimental fields. Over many years, LabDB has transformed into a sophisticated system integrating a range of biochemical, biophysical, and crystallographic experimental data, which harvests data both directly from laboratory instruments and through human input via a web interface. The core module of the system handles many types of universal laboratory management data, such as laboratory personnel, chemical inventories, storage locations, and custom stock solutions. LabDB also tracks various biochemical experiments, including spectrophotometric and fluorescent assays, thermal shift assays, isothermal titration calorimetry experiments, and more. LabDB has been used to manage data for experiments that resulted in over 1200 deposits to the Protein Data Bank (PDB); the system is currently used by the Center for Structural Genomics of Infectious Diseases (CSGID) and several large laboratories. This chapter also provides examples of data mining analyses and warnings about incomplete and inconsistent experimental data. These features, together with its capabilities for detailed tracking, analysis, and auditing of experimental data, make the described system uniquely suited to inspect potential sources of irreproducibility in life sciences research.

Molecular determinants of vascular transport of dexamethasone in COVID-19 therapy.

Dexamethasone, a widely used corticosteroid, has recently been reported as the first drug to increase the survival chances of patients with severe COVID-19. Therapeutic agents, including dexamethasone, are mostly transported through the body by binding to serum albumin. Here, the first structure of serum albumin in complex with dexamethasone is reported. Dexamethasone binds to drug site 7, which is also the binding site for commonly used nonsteroidal anti-inflammatory drugs and testosterone, suggesting potentially problematic binding competition. This study bridges structural findings with an analysis of publicly available clinical data from Wuhan and suggests that an adjustment of the dexamethasone regimen should be further investigated as a strategy for patients affected by two major COVID-19 risk factors: low albumin levels and diabetes.

Molecular determinants of vascular transport of dexamethasone in COVID-19 therapy.

Dexamethasone, a widely used corticosteroid, has recently been reported as the first drug to increase the survival chances of patients with severe COVID-19. Therapeutic agents, including dexamethasone, are mostly transported through the body by binding to serum albumin. Herein, we report the first structure of serum albumin in complex with dexamethasone. We show that it binds to Drug Site 7, which is also the binding site for commonly used nonsteroidal anti-inflammatory drugs and testosterone, suggesting potentially problematic binding competition. This study bridges structural findings with our analysis of publicly available clinical data from Wuhan and suggests that an adjustment of dexamethasone regimen should be considered for patients affected by two major COVID-19 risk-factors: low albumin levels and diabetes.

Albumin-Based Transport of Nonsteroidal Anti-Inflammatory Drugs in Mammalian Blood Plasma.

Every day, hundreds of millions of people worldwide take nonsteroidal anti-inflammatory drugs (NSAIDs), often in conjunction with multiple other medications. In the bloodstream, NSAIDs are mostly bound to serum albumin (SA). We report the crystal structures of equine serum albumin complexed with four NSAIDs (ibuprofen, ketoprofen, etodolac, and nabumetone) and the active metabolite of nabumetone (6-methoxy-2-naphthylacetic acid, 6-MNA). These compounds bind to seven drug-binding sites on SA. These sites are generally well-conserved between equine and human SAs, but ibuprofen binds to both SAs in two drug-binding sites, only one of which is common. We also compare the binding of ketoprofen by equine SA to binding of it by bovine and leporine SAs. Our comparative analysis of known SA complexes with FDA-approved drugs clearly shows that multiple medications compete for the same binding sites, indicating possibilities for undesirable physiological effects caused by drug-drug displacement or competition with common metabolites. We discuss the consequences of NSAID binding to SA in a broader scientific and medical context, particularly regarding achieving desired therapeutic effects based on an individual's drug regimen.

Structure-based design approach to rational site-directed mutagenesis of ß-lactoglobulin.

Recombinant proteins play an important role in medicine and have diverse applications in industrial biotechnology. Lactoglobulin has shown great potential for use in targeted drug delivery and body fluid detoxification because of its ability to bind a variety of molecules. In order to modify the biophysical properties of ß-lactoglobulin, a series of single-site mutations were designed using a structure-based approach. A 3-dimensional structure alignment of homologous molecules led to the design of nine ß-lactoglobulin variants with mutations introduced in the binding pocket region. Seven stable and correctly folded variants (L39Y, I56F, L58F, V92F, V92Y, F105L, M107L) were thoroughly characterized by fluorescence, circular dichroism, isothermal titration calorimetry, size-exclusion chromatography, and X-ray structural investigations. The effects of the amino acid substitutions were observed as slight rearrangements of the binding pocket geometry, but they also significantly influenced the global properties of the protein. Most of the mutations increased the thermal/chemical stability without altering the dimerization constant or pH-dependent conformational behavior. The crystal structures reveal that the I56F and F105L mutations reduced the depth of the binding pocket, which is advantageous since it can reduce the affinity to endogenous fatty acids. The F105L mutant created a unique binding mode for a fatty acid, supporting the idea that lactoglobulin can be altered to bind unique molecules. Selected variants possessing a unique combination of their individual properties can be used for further, more advanced mutagenesis, and the presented results support further research using ß-lactoglobulin as a therapeutic delivery agent or a blood detoxifying molecule.

Structural and biochemical analysis of Bacillus anthracis prephenate dehydrogenase reveals an unusual mode of inhibition by tyrosine via the ACT domain.

Tyrosine biosynthesis via the shikimate pathway is absent in humans and other animals, making it an attractive target for next-generation antibiotics, which is increasingly important due to the looming proliferation of multidrug-resistant pathogens. Tyrosine biosynthesis is also of commercial importance for the environmentally friendly production of numerous compounds, such as pharmaceuticals, opioids, aromatic polymers, and petrochemical aromatics. Prephenate dehydrogenase (PDH) catalyzes the penultimate step of tyrosine biosynthesis in bacteria: the oxidative decarboxylation of prephenate to 4-hydroxyphenylpyruvate. The majority of PDHs are competitively inhibited by tyrosine and consist of a nucleotide-binding domain and a dimerization domain. Certain PDHs, including several from pathogens on the World Health Organization priority list of antibiotic-resistant bacteria, possess an additional ACT domain. However, biochemical and structural knowledge was lacking for these enzymes. In this study, we successfully established a recombinant protein expression system for PDH from Bacillus anthracis (BaPDH), the causative agent of anthrax, and determined the structure of a BaPDH ternary complex with NAD+ and tyrosine, a binary complex with tyrosine, and a structure of an isolated ACT domain dimer. We also conducted detailed kinetic and biophysical analyses of the enzyme. We show that BaPDH is allosterically regulated by tyrosine binding to the ACT domains, resulting in an asymmetric conformation of the BaDPH dimer that sterically prevents prephenate binding to either active site. The presented mode of allosteric inhibition is unique compared to both the competitive inhibition established for other PDHs and to the allosteric mechanisms for other ACT-containing enzymes. This study provides new structural and mechanistic insights that advance our understanding of tyrosine biosynthesis in bacteria. ENZYMES: Prephenate dehydrogenase from Bacillus anthracis (PDH): EC database ID: 1.3.1.12. DATABASES: Coordinates and structure factors have been deposited in the Protein Data Bank (PDB) with accession numbers PDB ID: 6U60 (BaPDH complex with NAD+ and tyrosine), PDB ID: 5UYY (BaPDH complex with tyrosine), and PDB ID: 5V0S (BaPDH isolated ACT domain dimer). The diffraction images are available at http://proteindiffraction.org with DOIs: https://doi.org/10.18430/M35USC, https://doi.org/10.18430/M35UYY, and https://doi.org/10.18430/M35V0S.

The Integrated Resource for Reproducibility in Macromolecular Crystallography: Experiences of the first four years.

It has been increasingly recognized that preservation and public accessibility of primary experimental data are cornerstones necessary for the reproducibility of empirical sciences. In the field of molecular crystallography, many journals now recommend that authors of manuscripts presenting a new crystal structure should deposit their primary experimental data (X-ray diffraction images) to one of the dedicated resources created in recent years. Here, we describe our experiences developing the Integrated Resource for Reproducibility in Molecular Crystallography (IRRMC) and describe several examples of a crucial role that diffraction data can play in improving previously determined protein structures. In its first four years, several hundred crystallographers have deposited data from over 5200 diffraction experiments performed at over 60 different synchrotron beamlines or home sources all over the world. In addition to improving the resource and curating submitted data, we have been building a pipeline for extraction or, in some cases, reconstruction of the metadata necessary for seamless automated processing. Preliminary analysis indicates that about 95% of the archived data can be automatically reprocessed. A high rate of reprocessing success shows the feasibility of using the automated metadata extraction and automated processing as a validation step for the deposition of raw diffraction images. The IRRMC is guided by the Findable, Accessible, Interoperable, and Reusable data management principles.

Pyrimidine biosynthesis in pathogens - Structures and analysis of dihydroorotases from Yersinia pestis and Vibrio cholerae.

The de novo pyrimidine biosynthesis pathway is essential for the proliferation of many pathogens. One of the pathway enzymes, dihydroorotase (DHO), catalyzes the reversible interconversion of N-carbamoyl-l-aspartate to 4,5-dihydroorotate. The substantial difference between bacterial and mammalian DHOs makes it a promising drug target for disrupting bacterial growth and thus an important candidate to evaluate as a response to antimicrobial resistance on a molecular level. Here, we present two novel three-dimensional structures of DHOs from Yersinia pestis (YpDHO), the plague-causing pathogen, and Vibrio cholerae (VcDHO), the causative agent of cholera. The evaluations of these two structures led to an analysis of all available DHO structures and their classification into known DHO types. Comparison of all the DHO active sites containing ligands that are listed in DrugBank was facilitated by a new interactive, structure-comparison and presentation platform. In addition, we examined the genetic context of characterized DHOs, which revealed characteristic patterns for different types of DHOs. We also generated a homology model for DHO from Plasmodium falciparum.

Differences in substrate specificity of V. cholerae FabH enzymes suggest new approaches for the development of novel antibiotics and biofuels.

Vibrio cholerae, the causative pathogen of the life-threatening infection cholera, encodes two copies of ß-ketoacyl-acyl carrier protein synthase III (vcFabH1 and vcFabH2). vcFabH1 and vcFabH2 are pathogenic proteins associated with fatty acid synthesis, lipid metabolism, and potential applications in biofuel production. Our biochemical assays characterize vcFabH1 as exhibiting specificity for acetyl-CoA and CoA thioesters with short acyl chains, similar to that observed for FabH homologs found in most gram-negative bacteria. vcFabH2 prefers medium chain-length acyl-CoA thioesters, particularly octanoyl-CoA, which is a pattern of specificity rarely seen in bacteria. Structural characterization of one vcFabH1 and six vcFabH2 structures determined in either apo form or in complex with acetyl-CoA/octanoyl-CoA indicate that the substrate-binding pockets of vcFabH1 and vcFabH2 are of different sizes, accounting for variations in substrate chain-length specificity. An unusual and unique feature of vcFabH2 is its C-terminal fragment that interacts with both the substrate-entrance loop and the dimer interface of the enzyme. Our discovery of the pattern of substrate specificity of both vcFabH1 and vcFabH2 can potentially aid the development of novel antibacterial agents against V. cholerae. Additionally, the distinctive substrate preference of FabH2 in V. cholerae and related facultative anaerobes conceivably make it an attractive component of genetically engineered bacteria used for commercial biofuel production.

Molstack-Interactive visualization tool for presentation, interpretation, and validation of macromolecules and electron density maps.

Our understanding of the world of biomolecular structures is based upon the interpretation of macromolecular models, of which ∼90% are an interpretation of electron density maps. This structural information guides scientific progress and exploration in many biomedical disciplines. The Protein Data Bank's web portals have made these structures available for mass scientific consumption and greatly broaden the scope of information presented in scientific publications. The portals provide numerous quality metrics; however, the portion of the structure that is most vital for interpretation of the function may have the most difficult to interpret electron density and this ambiguity is not reflected by any single metric. The possible consequences of basing research on suboptimal models make it imperative to inspect the agreement of a model with its experimental evidence. Molstack, a web-based interactive publishing platform for structural data, allows users to present density maps and structural models by displaying a collection of maps and models, including different interpretation of one's own data, re-refinements, and corrections of existing structures. Molstack organizes the sharing and dissemination of these structural models along with their experimental evidence as an interactive session. Molstack was designed with three groups of users in mind; researchers can present the evidence of their interpretation, reviewers and readers can independently judge the experimental evidence of the authors' conclusions, and other researchers can present or even publish their new hypotheses in the context of prior results. The server is available at http://molstack.bioreproducibility.org.