Selective observation of semi-rigid non-core residues in dynamically complex mutant huntingtin protein fibrils.

Many amyloid-forming proteins, which are normally intrinsically disordered, undergo a disorder-to-order transition to form fibrils with a rigid ß-sheet core flanked by disordered domains. Solid-state NMR (ssNMR) and cryogenic electron microscopy (cryoEM) excel at resolving the rigid structures within amyloid cores but studying the dynamically disordered domains remains challenging. This challenge is exemplified by mutant huntingtin exon 1 (HttEx1), which self-assembles into pathogenic neuronal inclusions in Huntington disease (HD). The mutant protein's expanded polyglutamine (polyQ) segment forms a fibril core that is rigid and sequestered from the solvent. Beyond the core, solvent-exposed surface residues mediate biological interactions and other properties of fibril polymorphs. Here we deploy magic angle spinning ssNMR experiments to probe for semi-rigid residues proximal to the fibril core and examine how solvent dynamics impact the fibrils' segmental dynamics. Dynamic spectral editing (DYSE) 2D ssNMR based on a combination of cross-polarization (CP) ssNMR with selective dipolar dephasing reveals the weak signals of solvent-mobilized glutamine residues, while suppressing the normally strong background of rigid core signals. This type of 'intermediate motion selection' (IMS) experiment based on cross-polarization (CP) ssNMR, is complementary to INEPT- and CP-based measurements that highlight highly flexible or highly rigid protein segments, respectively. Integration of the IMS-DYSE element in standard CP-based ssNMR experiments permits the observation of semi-rigid residues in a variety of contexts, including in membrane proteins and protein complexes. We discuss the relevance of semi-rigid solvent-facing residues outside the fibril core to the latter's detection with specific dyes and positron emission tomography tracers.

Putting on molecular weight: Enabling cryo-EM structure determination of sub-100-kDa proteins.

Significant advances in the past decade have enabled high-resolution structure determination of a vast variety of proteins by cryogenic electron microscopy single particle analysis. Despite improved sample preparation, next-generation imaging hardware, and advanced single particle analysis algorithms, small proteins remain elusive for reconstruction due to low signal-to-noise and lack of distinctive structural features. Multiple efforts have therefore been directed at the development of size-increase techniques for small proteins. Here we review the latest methods for increasing effective molecular weight of proteins <100 â€‹kDa through target protein binding or target protein fusion - specifically by using nanobody-based assemblies, fusion tags, and symmetric scaffolds. Finally, we summarize these state-of-the-art techniques into a decision-tree to facilitate the design of tailored future approaches, and thus for further exploration of ever-smaller proteins that make up the largest part of the human genome.

Single domain antibodies derived from ancient animals as broadly neutralizing agents for SARS-CoV-2 and other coronaviruses.

With severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) as an emergent human virus since December 2019, the world population is susceptible to coronavirus disease 2019 (COVID-19). SARS-CoV-2 has higher transmissibility than the previous coronaviruses, associated by the ribonucleic acid (RNA) virus nature with high mutation rate, caused SARS-CoV-2 variants to arise while circulating worldwide. Neutralizing antibodies are identified as immediate and direct-acting therapeutic against COVID-19. Single-domain antibodies (sdAbs), as small biomolecules with non-complex structure and intrinsic stability, can acquire antigen-binding capabilities comparable to conventional antibodies, which serve as an attractive neutralizing solution. SARS-CoV-2 spike protein attaches to human angiotensin-converting enzyme 2 (ACE2) receptor on lung epithelial cells to initiate viral infection, serves as potential therapeutic target. sdAbs have shown broad neutralization towards SARS-CoV-2 with various mutations, effectively stop and prevent infection while efficiently block mutational escape. In addition, sdAbs can be developed into multivalent antibodies or inhaled biotherapeutics against COVID-19.

Multiscale modelling of the extracellular matrix.

The extracellular matrix is a complex three-dimensional network of molecules that provides cells with a complex microenvironment. The major constituents of the extracellular matrix such as collagen, elastin and associated proteins form supramolecular assemblies contributing to its physicochemical properties and organization. The structure of proteins and their supramolecular assemblies such as fibrils have been studied at the atomic level (e.g., by X-ray crystallography, Nuclear Magnetic Resonance and cryo-Electron Microscopy) or at the microscopic scale. However, many protein complexes are too large to be studied at the atomic level and too small to be studied by microscopy. Most extracellular matrix components fall into this intermediate scale, so-called the mesoscopic scale, preventing their detailed characterization. Simulation and modelling are some of the few powerful and promising approaches that can deepen our understanding of mesoscale systems. We have developed a set of modelling tools to study the self-organization of the extracellular matrix and large motion of macromolecules at the mesoscale level by taking advantage of the dynamics of articulated rigid bodies as a mean to study a larger range of motions at the cost of atomic resolution.

Structure-based in silico approaches for drug discovery against Mycobacterium tuberculosis.

Mycobacterium tuberculosis is the causative agent of TB and was estimated to cause 1.4 million death in 2019, alongside 10 million new infections. Drug resistance is a growing issue, with multi-drug resistant infections representing 3.3% of all new infections, hence novel antimycobacterial drugs are urgently required to combat this growing health emergency. Alongside this, increased knowledge of gene essentiality in the pathogenic organism and larger compound databases can aid in the discovery of new drug compounds. The number of protein structures, X-ray based and modelled, is increasing and now accounts for greater than > 80% of all predicted M. tuberculosis proteins; allowing novel targets to be investigated. This review will focus on structure-based in silico approaches for drug discovery, covering a range of complexities and computational demands, with associated antimycobacterial examples. This includes molecular docking, molecular dynamic simulations, ensemble docking and free energy calculations. Applications of machine learning onto each of these approaches will be discussed. The need for experimental validation of computational hits is an essential component, which is unfortunately missing from many current studies. The future outlooks of these approaches will also be discussed.

Binding mode analysis of ABCA7 for the prediction of novel Alzheimer's disease therapeutics.

The adenosine-triphosphate-(ATP)-binding cassette (ABC) transporter ABCA7 is a genetic risk factor for Alzheimer's disease (AD). Defective ABCA7 promotes AD development and/or progression. Unfortunately, ABCA7 belongs to the group of 'under-studied' ABC transporters that cannot be addressed by small-molecules. However, such small-molecules would allow for the exploration of ABCA7 as pharmacological target for the development of new AD diagnostics and therapeutics. Pan-ABC transporter modulators inherit the potential to explore under-studied ABC transporters as novel pharmacological targets by potentially binding to the proposed 'multitarget binding site'. Using the recently reported cryogenic-electron microscopy (cryo-EM) structures of ABCA1 and ABCA4, a homology model of ABCA7 has been generated. A set of novel, diverse, and potent pan-ABC transporter inhibitors has been docked to this ABCA7 homology model for the discovery of the multitarget binding site. Subsequently, application of pharmacophore modelling identified the essential pharmacophore features of these compounds that may support the rational drug design of innovative diagnostics and therapeutics against AD.

Crystallographic and cryogenic electron microscopic structures and enzymatic characterization of sulfur oxygenase reductase from Sulfurisphaera tokodaii.

Sulfur oxygenase reductases (SORs) are present in thermophilic and mesophilic archaea and bacteria, and catalyze oxygen-dependent oxygenation and disproportionation of elemental sulfur. SOR has a hollow, spherical homo-24-mer structure and reactions take place at active sites inside the chamber. The crystal structures of SORs from Acidianus species have been reported. However, the states of the active site components (mononuclear iron and cysteines) and the entry and exit paths of the substrate and products are still in dispute. Here, we report the biochemical and structural characterizations of SORs from the thermoacidophilic archaeon Sulfurisphaera tokodaii (StSOR) and present high-resolution structures determined by X-ray crystallography and cryogenic electron microscopy (cryo-EM). The crystal structure of StSOR was determined at 1.73 Å resolution. At the catalytic center, iron is ligated to His86, His90, Glu114, and two water molecules. Three conserved cysteines in the cavity are located 9.5-13 Å from the iron and were observed as free thiol forms. A mutational analysis indicated that the iron and one of the cysteines (Cys31) were essential for both activities. The cryo-EM structure was determined at 2.24 Å resolution using an instrument operating at 200 kV. The two structures determined by different methodologies showed similar main chain traces, but the maps exhibited different features at catalytically important components. A possible role of StSOR in the sulfur metabolism of S. tokodaii (an obligate aerobe) is discussed based on this study. Given the high resolution achieved in this study, StSOR was shown to be a good benchmark sample for cryo-EM.