TRIM7 ubiquitinates SARS-CoV-2 membrane protein to limit apoptosis and viral replication.

SARS-CoV-2 is a highly transmissible virus that causes COVID-19 disease. Mechanisms of viral pathogenesis include excessive inflammation and viral-induced cell death, resulting in tissue damage. Here we show that the host E3-ubiquitin ligase TRIM7 acts as an inhibitor of apoptosis and SARS-CoV-2 replication via ubiquitination of the viral membrane (M) protein.

TRIM7 ubiquitinates SARS-CoV-2 membrane protein to limit apoptosis and viral replication.

SARS-CoV-2 is a highly transmissible virus that causes COVID-19 disease. Mechanisms of viral pathogenesis include excessive inflammation and viral-induced cell death, resulting in tissue damage. We identified the host E3-ubiquitin ligase TRIM7 as an inhibitor of apoptosis and SARS-CoV-2 replication via ubiquitination of the viral membrane (M) protein.

Ebola virus VP35 interacts non-covalently with ubiquitin chains to promote viral replication.

Ebolavirus (EBOV) belongs to a family of highly pathogenic viruses that cause severe hemorrhagic fever in humans. EBOV replication requires the activity of the viral polymerase complex, which includes the cofactor and Interferon antagonist VP35. We previously showed that the covalent ubiquitination of VP35 promotes virus replication by regulating interactions with the polymerase complex.

Ebola Virus VP35 Interacts Non-Covalently with Ubiquitin Chains to Promote Viral Replication Creating New Therapeutic Opportunities.

Ebolavirus (EBOV) belongs to a family of highly pathogenic viruses that cause severe hemorrhagic fever in humans. EBOV replication requires the activity of the viral polymerase complex, which includes the co-factor and Interferon antagonist VP35. We previously showed that the covalent ubiquitination of VP35 promotes virus replication by regulating interactions with the polymerase complex.

Sequence-sensitive elastic network captures dynamical features necessary for miR-125a maturation.

The Elastic Network Contact Model (ENCoM) is a coarse-grained normal mode analysis (NMA) model unique in its all-atom sensitivity to the sequence of the studied macromolecule and thus to the effect of mutations. We adapted ENCoM to simulate the dynamics of ribonucleic acid (RNA) molecules, benchmarked its performance against other popular NMA models and used it to study the 3D structural dynamics of human microRNA miR-125a, leveraging high-throughput experimental maturation efficiency data of over 26 000 sequence variants. We also introduce a novel way of using dynamical information from NMA to train multivariate linear regression models, with the purpose of highlighting the most salient contributions of dynamics to function.

Modelling conformational state dynamics and its role on infection for SARS-CoV-2 Spike protein variants.

The SARS-CoV-2 Spike protein needs to be in an open-state conformation to interact with ACE2 to initiate viral entry. We utilise coarse-grained normal mode analysis to model the dynamics of Spike and calculate transition probabilities between states for 17081 variants including experimentally observed variants. Our results correctly model an increase in open-state occupancy for the more infectious D614G via an increase in flexibility of the closed-state and decrease of flexibility of the open-state.

Purine analogs targeting the guanine riboswitch as potential antibiotics against Clostridioides difficile.

Riboswitches recently emerged as possible targets for the development of alternative antimicrobial approaches. Guanine-sensing riboswitches in the bacterial pathogen Clostridioides difficile (formerly known as Clostridium difficile) constitute potential targets based on their involvement in the regulation of basal metabolic control of purine compounds. In this study, we deciphered the structure-activity relationship of several guanine derivatives on the guanine riboswitch and determined their antimicrobial activity.

Remodeling adipose tissue through in silico modulation of fat storage for the prevention of type 2 diabetes.

Background: Type 2 diabetes is one of the leading non-infectious diseases worldwide and closely relates to excess adipose tissue accumulation as seen in obesity. Specifically, hypertrophic expansion of adipose tissues is related to increased cardiometabolic risk leading to type 2 diabetes. Studying mechanisms underlying adipocyte hypertrophy could lead to the identification of potential targets for the treatment of these conditions.

Large-scale detection of drug off-targets: hypotheses for drug repurposing and understanding side-effects.

Background: Promiscuity in molecular interactions between small-molecules, including drugs, and proteins is widespread. Such unintended interactions can be exploited to suggest drug repurposing possibilities as well as to identify potential molecular mechanisms responsible for observed side-effects.

Methods: We perform a large-scale analysis to detect binding-site molecular interaction field similarities between the binding-sites of the primary target of 400 drugs against a dataset of 14082 cavities within 7895 different proteins representing a non-redundant dataset of all proteins with known structure.

Modulating the selectivity of matriptase-2 inhibitors with unnatural amino acids.

Matriptase-2, a type II transmembrane serine protease (TTSP), is expressed in the liver and regulates iron homeostasis via the cleavage of hemojuvelin. Matriptase-2 emerges as an attractive target for the treatment of conditions associated with iron overload, such as hemochromatosis or beta-thalassemia. Starting from the crystal structure of its closest homolog matriptase, we constructed a homology model of matriptase-2 in order to further optimize the selectivity of serine trap peptidomimetic inhibitors for matriptase-2 vs matriptase.

Evolutionary studies of ligand binding sites in proteins.

Biological processes at their most fundamental molecular aspects are defined by molecular interactions with ligand-protein interactions in particular at the core of cellular functions such as metabolism and signalling. Divergent and convergent processes shape the evolution of ligand binding sites. The competition between similar ligands and binding sites across protein families create evolutionary pressures that affect the specificity and selectivity of interactions.

NRGsuite: a PyMOL plugin to perform docking simulations in real time using FlexAID.

Unlabelled: Ligand protein docking simulations play a fundamental role in understanding molecular recognition. Herein we introduce the NRGsuite, a PyMOL plugin that permits the detection of surface cavities in proteins, their refinements, calculation of volume and use, individually or jointly, as target binding-sites for docking simulations with FlexAID. The NRGsuite offers the users control over a large number of important parameters in docking simulations including the assignment of flexible side-chains and definition of geometric constraints.

FlexAID: Revisiting Docking on Non-Native-Complex Structures.

Small-molecule protein docking is an essential tool in drug design and to understand molecular recognition. In the present work we introduce FlexAID, a small-molecule docking algorithm that accounts for target side-chain flexibility and utilizes a soft scoring function, i.e.

ENCoM server: exploring protein conformational space and the effect of mutations on protein function and stability.

ENCoM is a coarse-grained normal mode analysis method recently introduced that unlike previous such methods is unique in that it accounts for the nature of amino acids. The inclusion of this layer of information was shown to improve conformational space sampling and apply for the first time a coarse-grained normal mode analysis method to predict the effect of single point mutations on protein dynamics and thermostability resulting from vibrational entropy changes. Here we present a web server that allows non-technical users to have access to ENCoM calculations to predict the effect of mutations on thermostability and dynamics as well as to generate geometrically realistic conformational ensembles.

Achievements and challenges in structural bioinformatics and computational biophysics.

Motivation: The field of structural bioinformatics and computational biophysics has undergone a revolution in the last 10 years. Developments that are captured annually through the 3DSIG meeting, upon which this article reflects.

Results: An increase in the accessible data, computational resources and methodology has resulted in an increase in the size and resolution of studied systems and the complexity of the questions amenable to research.

A coarse-grained elastic network atom contact model and its use in the simulation of protein dynamics and the prediction of the effect of mutations.

Normal mode analysis (NMA) methods are widely used to study dynamic aspects of protein structures. Two critical components of NMA methods are coarse-graining in the level of simplification used to represent protein structures and the choice of potential energy functional form. There is a trade-off between speed and accuracy in different choices.

Deep-sequencing of the peach latent mosaic viroid reveals new aspects of population heterogeneity.

Viroids are small circular single-stranded infectious RNAs characterized by a relatively high mutation level. Knowledge of their sequence heterogeneity remains largely elusive and previous studies, using Sanger sequencing, were based on a limited number of sequences. In an attempt to address sequence heterogeneity from a population dynamics perspective, a GF305-indicator peach tree was infected with a single variant of the Avsunviroidae family member Peach latent mosaic viroid (PLMVd).

The mode of action of recombinant Mycobacterium tuberculosis shikimate kinase: kinetics and thermodynamics analyses.

Tuberculosis remains as one of the main cause of mortality worldwide due to a single infectious agent, Mycobacterium tuberculosis. The aroK-encoded M. tuberculosis Shikimate Kinase (MtSK), shown to be essential for survival of bacilli, catalyzes the phosphoryl transfer from ATP to the carbon-3 hydroxyl group of shikimate (SKH), yielding shikimate-3-phosphate and ADP.

Structures of the first representatives of Pfam family PF06938 (DUF1285) reveal a new fold with repeated structural motifs and possible involvement in signal transduction.

The crystal structures of SPO0140 and Sbal_2486 were determined using the semiautomated high-throughput pipeline of the Joint Center for Structural Genomics (JCSG) as part of the NIGMS Protein Structure Initiative (PSI). The structures revealed a conserved core with domain duplication and a superficial similarity of the C-terminal domain to pleckstrin homology-like folds. The conservation of the domain interface indicates a potential binding site that is likely to involve a nucleotide-based ligand, with genome-context and gene-fusion analyses additionally supporting a role for this family in signal transduction, possibly during oxidative stress.

Structural analysis of metal sites in proteins: non-heme iron sites as a case study.

In metalloproteins, the protein environment modulates metal properties to achieve the required goal, which can be protein stabilization or function. The analysis of metal sites at the atomic level of detail provided by protein structures can thus be of benefit in functional and evolutionary studies of proteins. In this work, we propose a structural bioinformatics approach to the study of metalloproteins based on structural templates of metal sites that include the PDB coordinates of protein residues forming the first and the second coordination sphere of the metal.

Analysis of binding site similarity, small-molecule similarity and experimental binding profiles in the human cytosolic sulfotransferase family.

Motivation: In the present work we combine computational analysis and experimental data to explore the extent to which binding site similarities between members of the human cytosolic sulfotransferase family correlate with small-molecule binding profiles. Conversely, from a small-molecule point of view, we explore the extent to which structural similarities between small molecules correlate to protein binding profiles.

Results: The comparison of binding site structural similarities and small-molecule binding profiles shows that proteins with similar small-molecule binding profiles tend to have a higher degree of binding site similarity but the latter is not sufficient to predict small-molecule binding patterns, highlighting the difficulty of predicting small-molecule binding patterns from sequence or structure.

A method for localizing ligand binding pockets in protein structures.

The accurate identification of ligand binding sites in protein structures can be valuable in determining protein function. Once the binding site is known, it becomes easier to perform in silico and experimental procedures that may allow the ligand type and the protein function to be determined. For example, binding pocket shape analysis relies heavily on the correct localization of the ligand binding site.

Real spherical harmonic expansion coefficients as 3D shape descriptors for protein binding pocket and ligand comparisons.

Motivation: An increasing number of protein structures are being determined for which no biochemical characterization is available. The analysis of protein structure and function assignment is becoming an unexpected challenge and a major bottleneck towards the goal of well-annotated genomes. As shape plays a crucial role in biomolecular recognition and function, the examination and development of shape description and comparison techniques is likely to be of prime importance for understanding protein structure-function relationships.