Structural determinants of cardiac light chain amyloidosis

Light chain amyloidosis (AL) is an acute systemic amyloid disease in which the overexpression and misfolding of immunoglobulin light chains leads to the formation of insoluble fibrils at critical organs in the body. The typical prognosis for AL patients is extremely severe—usually less than three years of diagnosis—but in the case of cardiac involvement, this is reduced to under a year. As a result of the complex and diverse nature of the disease, our understanding of how it onsets and imparts its devastating effects remains elusive, consequently delaying progress on the identification of robust diagnostic and therapeutic strategies. To address this deficiency, we investigate the structural and dynamical properties of the fibrils involved in a severe case of cardiac AL disease, formed from the light-chain variable domain (VL) patient-derived protein, AL-09. We performed these studies through the use of solid-state nuclear magnetic resonance (SSNMR) spectroscopy, which have revealed new insights on specific features of the fibril species. First, we report our findings on the 13C and 15N chemical shift assignments and sequence involvement of AL-09 VL fibrils, followed by subsequent investigations on the predominant secondary structure and relative dynamics across the protein sequence. In addition, we present a comparison of AL-09 VL fibrils (prepared in vitro) with ex vivo amyloid deposits of another AL protein fibril (HIG) obtained from human spleen tissue using 1D 13C SSNMR analysis. Next, we describe the development and implementation of 4D 13C-detected SSNMR experiments that combine non-uniform sampling with band-selective J-decoupling pulses to enable the resolution of previously unassignable resonances while maintaining high sensitivity. Last, we introduce an improved program and strategy for the computationally-aided assignment of protein chemical shifts that incorporates peak intensity and frequency overlap information as an additional scoring function in the multi-objective search for optimal assignment solutions

Structural determinants of cardiac light chain amyloidosis

Light chain amyloidosis (AL) is an acute systemic amyloid disease in which the overexpression and misfolding of immunoglobulin light chains leads to the formation of insoluble fibrils at critical organs in the body. The typical prognosis for AL patients is extremely severe—usually less than three years of diagnosis—but in the case of cardiac involvement, this is reduced to under a year. As a result of the complex and diverse nature of the disease, our understanding of how it onsets and imparts its devastating effects remains elusive, consequently delaying progress on the identification of robust diagnostic and therapeutic strategies. To address this deficiency, we investigate the structural and dynamical properties of the fibrils involved in a severe case of cardiac AL disease, formed from the light-chain variable domain (VL) patient-derived protein, AL-09. We performed these studies through the use of solid-state nuclear magnetic resonance (SSNMR) spectroscopy, which have revealed new insights on specific features of the fibril species. First, we report our findings on the 13C and 15N chemical shift assignments and sequence involvement of AL-09 VL fibrils, followed by subsequent investigations on the predominant secondary structure and relative dynamics across the protein sequence. In addition, we present a comparison of AL-09 VL fibrils (prepared in vitro) with ex vivo amyloid deposits of another AL protein fibril (HIG) obtained from human spleen tissue using 1D 13C SSNMR analysis. Next, we describe the development and implementation of 4D 13C-detected SSNMR experiments that combine non-uniform sampling with band-selective J-decoupling pulses to enable the resolution of previously unassignable resonances while maintaining high sensitivity. Last, we introduce an improved program and strategy for the computationally-aided assignment of protein chemical shifts that incorporates peak intensity and frequency overlap information as an additional scoring function in the multi-objective search for optimal assignment solutions.LimitedAuthor requested closed access (OA after 2yrs) in Vireo ETD syste

Immunoglobulin Light Chains Form an Extensive and Highly Ordered Fibril Involving the N- and C-Termini

Light-chain (AL)-associated amyloidosis is a systemic disorder involving the formation and deposition of immunoglobulin AL fibrils in various bodily organs. One severe instance of AL disease is exhibited by the patient-derived variable domain (V_L) of the light chain AL-09, a 108 amino acid residue protein containing seven mutations relative to the corresponding germline protein, κI O18/O8 V_L. Previous work has demonstrated that the thermodynamic stability of native AL-09 V_L is greatly lowered by two of these mutations, Y87H and N34I, whereas a third mutation, K42Q, further increases the kinetics of fibril formation. However, detailed knowledge regarding the residues that are responsible for stabilizing the misfolded fibril structure is lacking. In this study, using solid-state NMR spectroscopy, we show that the majority of the AL-09 V_L sequence is immobilized in the fibrils and that the N- and C-terminal portions of the sequence are particularly well-structured. Thus, AL-09 V_L forms an extensively ordered and β-strand-rich fibril structure. Furthermore, we demonstrate that the predominant β-sheet secondary structure and rigidity observed for in vitro prepared AL-09 V_L fibrils are qualitatively similar to those observed for AL fibrils extracted from postmortem human spleen tissue, suggesting that this conformation may be representative of a common feature of AL fibrils

Protein Data Bank: A Comprehensive Review of 3D Structure Holdings and Worldwide Utilization by Researchers, Educators, and Students

The Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB), funded by the United States National Science Foundation, National Institutes of Health, and Department of Energy, supports structural biologists and Protein Data Bank (PDB) data users around the world. The RCSB PDB, a founding member of the Worldwide Protein Data Bank (wwPDB) partnership, serves as the US data center for the global PDB archive housing experimentally-determined three-dimensional (3D) structure data for biological macromolecules. As the wwPDB-designated Archive Keeper, RCSB PDB is also responsible for the security of PDB data and weekly update of the archive. RCSB PDB serves tens of thousands of data depositors (using macromolecular crystallography, nuclear magnetic resonance spectroscopy, electron microscopy, and micro-electron diffraction) annually working on all permanently inhabited continents. RCSB PDB makes PDB data available from its research-focused web portal at no charge and without usage restrictions to many millions of PDB data consumers around the globe. It also provides educators, students, and the general public with an introduction to the PDB and related training materials through its outreach and education-focused web portal. This review article describes growth of the PDB, examines evolution of experimental methods for structure determination viewed through the lens of the PDB archive, and provides a detailed accounting of PDB archival holdings and their utilization by researchers, educators, and students worldwide

ModelCIF: An extension of PDBx/mmCIF data representation for computed structure models

ModelCIF (github.com/ihmwg/ModelCIF) is a data information framework developed for and by computational structural biologists to enable delivery of Findable, Accessible, Interoperable, and Reusable (FAIR) data to users worldwide. ModelCIF describes the specific set of attributes and metadata associated with macromolecular structures modeled by solely computational methods and provides an extensible data representation for deposition, archiving, and public dissemination of predicted three-dimensional (3D) models of macromolecules. It is an extension of the Protein Data Bank Exchange / macromolecular Crystallographic Information Framework (PDBx/mmCIF), which is the global data standard for representing experimentally-determined 3D structures of macromolecules and associated metadata. The PDBx/mmCIF framework and its extensions (e.g., ModelCIF) are managed by the Worldwide Protein Data Bank partnership (wwPDB, wwpdb.org) in collaboration with relevant community stakeholders such as the wwPDB ModelCIF Working Group (wwpdb.org/task/modelcif). This semantically rich and extensible data framework for representing computed structure models (CSMs) accelerates the pace of scientific discovery. Herein, we describe the architecture, contents, and governance of ModelCIF, and tools and processes for maintaining and extending the data standard. Community tools and software libraries that support ModelCIF are also described

ModelCIF: An Extension of PDBx/mmCIF Data Representation for Computed Structure Models

ModelCIF (github.com/ihmwg/ModelCIF) is a data information framework developed for and by computational structural biologists to enable delivery of Findable, Accessible, Interoperable, and Reusable (FAIR) data to users worldwide. ModelCIF describes the specific set of attributes and metadata associated with macromolecular structures modeled by solely computational methods and provides an extensible data representation for deposition, archiving, and public dissemination of predicted three-dimensional (3D) models of macromolecules. It is an extension of the Protein Data Bank Exchange / macromolecular Crystallographic Information Framework (PDBx/mmCIF), which is the global data standard for representing experimentally-determined 3D structures of macromolecules and associated metadata. The PDBx/mmCIF framework and its extensions (e.g., ModelCIF) are managed by the Worldwide Protein Data Bank partnership (wwPDB, wwpdb.org) in collaboration with relevant community stakeholders such as the wwPDB ModelCIF Working Group (wwpdb.org/task/modelcif). This semantically rich and extensible data framework for representing computed structure models (CSMs) accelerates the pace of scientific discovery. Herein, we describe the architecture, contents, and governance of ModelCIF, and tools and processes for maintaining and extending the data standard. Community tools and software libraries that support ModelCIF are also described

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