Machine Learning augmented docking studies of aminothioureas at the SARS-CoV-2—ACE2 interface

The current pandemic outbreak clearly indicated the urgent need for tools allowing fast predictions of bioactivity of a large number of compounds, either available or at least synthesizable. In the computational chemistry toolbox, several such tools are available, with the main ones being docking and structure-activity relationship modeling either by classical linear QSAR or Machine Learning techniques. In this contribution, we focus on the comparison of the results obtained using different docking protocols on the example of the search for bioactivity of compounds containing N-N-C(S)-N scaffold at the S-protein of SARS-CoV-2 virus with ACE2 human receptor interface. Based on over 1800 structures in the training set we have predicted binding properties of the complete set of nearly 600000 structures from the same class using the Machine Learning Random Forest Regressor approach.

Structures of mouse and human GITR–GITRL complexes reveal unique TNF superfamily interactions

Glucocorticoid-induced tumor necrosis factor receptor-related protein (GITR) and GITR ligand (GITRL) are members of the tumor necrosis superfamily that play a role in immune cell signaling, activation, and survival. GITR is a therapeutic target for directly activating effector CD4 and CD8 T cells, or depleting GITR-expressing regulatory T cells (Tregs), thereby promoting anti-tumor immune responses. GITR activation through its native ligand is important for understanding immune signaling, but GITR structure has not been reported. Here we present structures of human and mouse GITR receptors bound to their cognate ligands. Both species share a receptor–ligand interface and receptor–receptor interface; the unique C-terminal receptor–receptor enables higher order structures on the membrane. Human GITR–GITRL has potential to form a hexameric network of membrane complexes, while murine GITR–GITRL complex forms a linear chain due to dimeric interactions. Mutations at the receptor–receptor interface in human GITR reduce cell signaling with in vitro ligand binding assays and minimize higher order membrane structures when bound by fluorescently labeled ligand in cell imaging experiments.

First-in-class humanized FSH blocking antibody targets bone and fat

Blocking the action of FSH genetically or pharmacologically in mice reduces body fat, lowers serum cholesterol, and increases bone mass, making an anti-FSH agent a potential therapeutic for three global epidemics: obesity, osteoporosis, and hypercholesterolemia. Here, we report the generation, structure, and function of a first-in-class, fully humanized, epitope-specific FSH blocking antibody with aKDof 7 nM. Protein thermal shift, molecular dynamics, and fine mapping of the FSH–FSH receptor interface confirm stable binding of the Fab domain to two of five receptor-interacting residues of the FSHβ subunit, which is sufficient to block its interaction with the FSH receptor. In doing so, the humanized antibody profoundly inhibited FSH action in cell-based assays, a prelude to further preclinical and clinical testing.

Docking and QSAR of Aminothioureas at the SARS-CoV-2 S-Protein–Human ACE2 Receptor Interface

Docking of over 160 aminothiourea derivatives at the SARS-CoV-2 S-protein–human ACE2 receptor interface, whose structure became available recently, has been evaluated for its complex stabilizing potency and subsequently subjected to quantitative structure–activity relationship (QSAR) analysis. The structural variety of the studied compounds, that include 3 different forms of the N–N–C(S)–N skeleton and combinations of 13 different substituents alongside the extensive length of the interface, resulted in the failure of the QSAR analysis, since different molecules were binding to different parts of the interface. Subsequently, absorption, distribution, metabolism, and excretion (ADME) analysis on all studied compounds, followed by a toxicity analysis using statistical models for selected compounds, was carried out to evaluate their potential use as lead compounds for drug design. Combined, these studies highlighted two molecules among the studied compounds, i.e., 5-(pyrrol-2-yl)-2-(2-methoxyphenylamino)-1,3,4-thiadiazole and 1-(cyclopentanoyl)-4-(3-iodophenyl)-thiosemicarbazide, as the best candidates for the development of future drugs.

COVID-19 Repurposed Therapeutics Targeting the Viral Protease and Spike-protein:ACE2 Interface using MD-based Pharmacophore and Consensus Virtual Screening

<p>Molecular dynamics (MD) and enhanced sampling MD was performed for 100 ns on the biological assembly of the COVID-19 protease (<a href="https://www.rcsb.org/structure/6lu7">6LU7</a>), and a template of the COVID-19 S-protein:ACE2 receptor interface (99.88% coverage of 6M0J; model03, <a href="https://swissmodel.expasy.org/interactive/HLkhkP/models/">swissmodel</a>). Apo-site pharmacophores of the resulting structural clusters were used to mine the FDA database (8700 compounds), and a multi-target library was developed from MD-based hits in high affinity sites across 100 ns. Consensus hits from high throughput docking in crystal structures 5R82, 6LU7 and 6Y2F (protease), and 6VW1 (S-protein:ACE2) were also added, and the resulting libraries were re-docked into MD sites to collect potential COVID-19 re-purposed therapeutics by estimated binding energies. </p>

COVID-19 Repurposed Therapeutics Targeting the Viral Protease and Spike-protein:ACE2 Interface using MD-based Pharmacophore and Consensus Virtual Screening

<p>Molecular dynamics (MD) and enhanced sampling MD was performed for 100 ns on the biological assembly of the COVID-19 protease (<a href="https://www.rcsb.org/structure/6lu7">6LU7</a>), and a template of the COVID-19 S-protein:ACE2 receptor interface (99.88% coverage of 6M0J; model03, <a href="https://swissmodel.expasy.org/interactive/HLkhkP/models/">swissmodel</a>). Apo-site pharmacophores of the resulting structural clusters were used to mine the FDA database (8700 compounds), and a multi-target library was developed from MD-based hits in high affinity sites across 100 ns. Consensus hits from high throughput docking in crystal structures 5R82, 6LU7 and 6Y2F (protease), and 6VW1 (S-protein:ACE2) were also added, and the resulting libraries were re-docked into MD sites to collect potential COVID-19 re-purposed therapeutics by estimated binding energies. </p>

Transferrin receptor binds virus capsid with dynamic motion

Canine parvovirus (CPV) is an important pathogen causing severe diseases in dogs, including acute hemorrhagic enteritis, myocarditis, and cerebellar disease. Cross-species transmission of CPV occurs as a result of mutations on the viral capsid surface that alter the species-specific binding to the host receptor, transferrin receptor type-1 (TfR). The interaction between CPV and TfR has been extensively studied, and previous analyses have suggested that the CPV–TfR complex is asymmetric. To enhance the understanding of the underlying molecular mechanisms, we determined the CPV–TfR interaction using cryo-electron microscopy to solve the icosahedral (3.0-Å resolution) and asymmetric (5.0-Å resolution) complex structures. Structural analyses revealed conformational variations of the TfR molecules relative to the binding site, which translated into dynamic molecular interactions between CPV and TfR. The precise footprint of the receptor on the virus capsid was identified, along with the identity of the amino acid residues in the virus–receptor interface. Our “rock-and-roll” model provides an explanation for previous findings and gives insights into species jumping and the variation in host ranges associated with new pandemics in dogs.