Cancer-driving mutations are enriched in genic regions intolerant to germline variation

Large reference datasets of protein-coding variation in human populations have allowed us to determine which genes and genic sub-regions are intolerant to germline genetic variation. There is also a growing number of genes implicated in severe Mendelian diseases that overlap with genes implicated in cancer. Here, we hypothesized that mitotically mutable genic sub-regions that are intolerant to germline variation are enriched for cancer-driving mutations. We introduce a new metric, OncMTR, which uses 125,748 exomes in the gnomAD database to identify genic sub-regions intolerant to germline variation but enriched for hematologic somatic variants. We demonstrate that OncMTR can significantly predict driver mutations implicated in hematologic malignancies. Divergent OncMTR regions were enriched for cancer-relevant protein domains, and overlaying OncMTR scores on protein structures identified functionally important protein residues. Finally, we performed a rare variant, gene-based collapsing analysis on an independent set of 394,694 exomes from the UK Biobank and find that OncMTR dramatically improves genetic signals for hematologic malignancies. Our web app enables easy visualization of OncMTR scores for each protein-coding gene (https://astrazeneca-cgr-publications.github.io/OncMTR-Viewer/).

Computational Studies of Au(I) and Au(III) Anticancer MetalLodrugs: A Survey

Owing to the growing hardware capabilities and the enhancing efficacy of computational methodologies, computational chemistry approaches have constantly become more important in the development of novel anticancer metallodrugs. Besides traditional Pt-based drugs, inorganic and organometallic complexes of other transition metals are showing increasing potential in the treatment of cancer. Among them, Au(I)- and Au(III)-based compounds are promising candidates due to the strong affinity of Au(I) cations to cysteine and selenocysteine side chains of the protein residues and to Au(III) complexes being more labile and prone to the reduction to either Au(I) or Au(0) in the physiological milieu. A correct prediction of metal complexes’ properties and of their bonding interactions with potential ligands requires QM computations, usually at the ab initio or DFT level. However, MM, MD, and docking approaches can also give useful information on their binding site on large biomolecular targets, such as proteins or DNA, provided a careful parametrization of the metal force field is employed. In this review, we provide an overview of the recent computational studies of Au(I) and Au(III) antitumor compounds and of their interactions with biomolecular targets, such as sulfur- and selenium-containing enzymes, like glutathione reductases, glutathione peroxidase, glutathione-S-transferase, cysteine protease, thioredoxin reductase and poly (ADP-ribose) polymerase 1.

Residue-resolved monitoring of protein hyperpolarization at sub-second time resolution

Signal-enhancement techniques for NMR spectroscopy are important to amplify the weak resonances provided by nuclear spins. Recently, ‘hyperpolarization’ techniques have been intensively investigated. These provide nuclear spin states far from equilibrium yielding strong signal boosts up to four orders of magnitude. Here we propose a method for real-time NMR of ‘hyperpolarized’ proteins at residue resolution. The approach is based on dissolution dynamic nuclear polarization (d-DNP), which enables the use of hyperpolarized buffers that selectively boost NMR signals of solvent-exposed protein residues. The resulting spectral sparseness and signal enhancements enable recording of residue-resolved spectra at a 2 Hz sampling rate. Thus, we monitor the hyperpolarization level of different protein residues simultaneously under near-physiological conditions. We aim to address two points: 1) NMR experiments are often performed under conditions that increase sensitivity but are physiologically irrelevant; 2) long signal accumulation impedes fast real-time monitoring. Both limitations are of fundamental relevance to ascertain pharmacological relevance and study protein kinetics.

Structural and Functional Aspects of Ebola Virus Proteins

Ebola virus (EBOV), member of genus Ebolavirus, family Filoviridae, have a non-segmented, single-stranded RNA that contains seven genes: (a) nucleoprotein (NP), (b) viral protein 35 (VP35), (c) VP40, (d) glycoprotein (GP), (e) VP30, (f) VP24, and (g) RNA polymerase (L). All genes encode for one protein each except GP, producing three pre-proteins due to the transcriptional editing. These pre-proteins are translated into four products, namely: (a) soluble secreted glycoprotein (sGP), (b) Δ-peptide, (c) full-length transmembrane spike glycoprotein (GP), and (d) soluble small secreted glycoprotein (ssGP). Further, shed GP is released from infected cells due to cleavage of GP by tumor necrosis factor α-converting enzyme (TACE). This review presents a detailed discussion on various functional aspects of all EBOV proteins and their residues. An introduction to ebolaviruses and their life cycle is also provided for clarity of the available analysis. We believe that this review will help understand the roles played by different EBOV proteins in the pathogenesis of the disease. It will help in targeting significant protein residues for therapeutic and multi-protein/peptide vaccine development.

Myofilament Phosphorylation in Stem Cell Treated Diastolic Heart Failure

Rationale: Phosphorylation of sarcomeric proteins has been implicated in heart failure with preserved ejection fraction (HFpEF); such changes may contribute to diastolic dysfunction by altering contractility, cardiac stiffness, Ca 2+ -sensitivity and mechanosensing. Treatment with cardiosphere-derived cells (CDCs) restores normal diastolic function, attenuates fibrosis and inflammation, and improves survival in a rat HFpEF model. Objective: Phosphorylation changes that underlie HFpEF and those reversed by CDC therapy, with a focus on the sarcomeric subproteome were analyzed. Methods and Results: Dahl salt-sensitive rats fed a high-salt diet, with echocardiographically-verified diastolic dysfunction, were randomly assigned to either intracoronary CDCs or placebo. Dahl salt-sensitive rats receiving low salt diet served as controls. Protein, and phosphorylated Ser, Thr and Tyr residues from left ventricular tissue, were quantified by mass spectrometry. HFpEF hearts exhibited extensive hyperphosphorylation with 98% of the 529 significantly changed phospho-sites increased compared to control. Of those 39% were located within the sarcomeric subproteome, with a large group of proteins located or associated with the Z-disk. CDC treatment partially reverted the hyperphosphorylation, with 85% of the significantly altered 76 residues hypophosphorylated. Bioinformatic upstream analysis of the differentially phosphorylated protein residues revealed PKC as the dominant putative regulatory kinase. PKC isoform analysis indicated increases in PKC α, β and δ concentration, whereas CDC treatment led to a reversion of PKCβ. Use of PKC isoform specific inhibition and overexpression of various PKC isoforms strongly suggests PKCβ is the dominant kinase involved in hyperphosphorylation in HFpEF and is altered with CDC treatment. Conclusions: Increased protein phosphorylation at the Z-disk is associated with diastolic dysfunction, with PKC isoforms driving most quantified phosphorylation changes. Because CDCs reverse the key abnormalities in HFpEF and selectively reverse PKCβ upregulation, PKCβ merits being classified as a potential therapeutic target in HFpEF, a disease notoriously refractory to medical intervention,

The importance of residue-level filtering, and the Top2018 best-parts dataset of high-quality protein residues

We have curated a high-quality, “best parts” reference dataset of about 3 million protein residues in about 15,000 PDB-format coordinate files, each containing only residues with good electron density support for a physically acceptable model conformation. The resulting pre-filtered data typically contains the entire core of each chain, in quite long continuous fragments. Each reference file is a single protein chain, and the total set of files were selected for low redundancy, high resolution, good MolProbity score, and other chain-level criteria. Then each residue was critically tested for adequate local map quality to firmly support its conformation, which must also be free of serious clashes or covalent-geometry outliers. The resulting Top2018 pre-filtered datasets have been released on the Zenodo online web service and is freely available for all uses under a Creative Commons license. Currently, one dataset is residue-filtered on mainchain plus Cβ atoms, and a second dataset is full-residue filtered; each is available at 4 different sequence-identity levels. Here, we illustrate both statistics and examples that show the beneficial consequences of residue-level filtering. That process is necessary because even the best of structures contain a few highly disordered local regions with poor density and low-confidence conformations that should not be included in reference data. Therefore the open distribution of these very large, pre-filtered reference datasets constitutes a notable advance for structural bioinformatics and the fields that depend upon it.The Top2018 dataset provides the first representative sample of 3D protein structure for which excellence of experimental data constrains the detailed local conformation to be correct for essentially all 3 million residues included. Earlier generations of residue-filtered datasets were central in developing MolProbity validation used worldwide, and now Zenodo has enabled anyone to use out latest version as a sound basis for structural bioinformatics, protein design, prediction, improving biomedically important structures, or other applications.

Protein structural features predict responsiveness to pharmacological chaperone treatment for three lysosomal storage disorders

Three-dimensional structures of proteins can provide important clues into the efficacy of personalized treatment. We perform a structural analysis of variants within three inherited lysosomal storage disorders, comparing variants responsive to pharmacological chaperone treatment to those unresponsive to such treatment. We find that predicted ΔΔG of mutation is higher on average for variants unresponsive to treatment, in the case of datasets for both Fabry disease and Pompe disease, in line with previous findings. Using both a single decision tree and an advanced machine learning approach based on the larger Fabry dataset, we correctly predict responsiveness of three Gaucher disease variants, and we provide predictions for untested variants. Many variants are predicted to be responsive to treatment, suggesting that drug-based treatments may be effective for a number of variants in Gaucher disease. In our analysis, we observe dependence on a topological feature reporting on contact arrangements which is likely connected to the order of folding of protein residues, and we provide a potential justification for this observation based on steady-state cellular kinetics.

The homogenous alternative to biomineralization: Zn- and Mn-rich materials enable sharp organismal “tools” that reduce force requirements

We measured hardness, modulus of elasticity, and, for the first time, loss tangent, energy of fracture, abrasion resistance, and impact resistance of zinc- and manganese-enriched materials from fangs, stings and other “tools” of an ant, spider, scorpion and nereid worm. The mechanical properties of the Zn- and Mn-materials tended to cluster together between plain and biomineralized “tool” materials, with the hardness reaching, and most abrasion resistance values exceeding, those of calcified salmon teeth and crab claws. Atom probe tomography indicated that Zn was distributed homogeneously on a nanometer scale and likely bound as individual atoms to more than ¼ of the protein residues in ant mandibular teeth. This homogeneity appears to enable sharper, more precisely sculpted “tools” than materials with biomineral inclusions do, and also eliminates interfaces with the inclusions that could be susceptible to fracture. Based on contact mechanics and simplified models, we hypothesize that, relative to plain materials, the higher elastic modulus, hardness and abrasion resistance minimize temporary or permanent tool blunting, resulting in a roughly 2/3 reduction in the force, energy, and muscle mass required to initiate puncture of stiff materials, and even greater force reductions when the cumulative effects of abrasion are considered. We suggest that the sharpness-related force reductions lead to significant energy savings, and can also enable organisms, especially smaller ones, to puncture, cut, and grasp objects that would not be accessible with plain or biomineralized “tools”.

Residue-resolved monitoring of protein hyperpolarization at sub-second time resolution

We propose a method for real-time nuclear magnetic resonance (NMR) spectroscopy of hyperpolarized proteins at residue resolution. The approach is based on dissolution dynamic nuclear polarization (d-DNP), which enables the use of hyperpolarized buffers that selectively boost NMR signals of backbone amides that incur magnetization fast from their surroundings. Capitalizing on the resulting spectral sparseness and simultaneous signal enhancement, we obtained residue-resolved NMR spectra at a sampling rate of 2 Hz. We could thus track the evolution of hyperpolarization at different protein residues simultaneously with time. This was achieved under near-physiological conditions, i.e., in aqueous solution at physiological salt concentration and at 37° C. With this development, two often encountered limitations of conventional solution-state NMR can be addressed: 1) NMR experiments are typically performed under conditions that increase sensitivity but are physiologically not relevant (low pH, low temperature) and; 2) signal accumulation over long periods impedes the determination of fast (on the order of seconds) real-time monitoring. Both limitations are of equal fundamental relevance: interaction studies under non-native conditions are of limited pharmacological relevance, and the key to the function of proteins often resides in their interaction kinetics. The proposed technique possibly opens new routes towards residue and temporally resolved spectroscopy at the atomistic level by overcoming the need for signal averaging in residue-resolved protein biomolecular NMR.