Entrectinib—A SARS-CoV-2 Inhibitor in Human Lung Tissue (HLT) Cells

COVID-19; Drug repurposing; Viral cell entry assaysCOVID-19; Reutilización de medicamentos; Ensayos de entrada de células viralesCOVID-19; Reutilització de medicaments; Assajos d'entrada de cèl·lules viralsSince the start of the COVID-19 outbreak, pharmaceutical companies and research groups have focused on the development of vaccines and antiviral drugs against SARS-CoV-2. Here, we apply a drug repurposing strategy to identify drug candidates that are able to block the entrance of the virus into human cells. By combining virtual screening with in vitro pseudovirus assays and antiviral assays in Human Lung Tissue (HLT) cells, we identify entrectinib as a potential antiviral drug.This research was funded by the Spanish Ministry of Science, Innovation, and Universities (FPU16/01209 to M.T.-F.); the Health department of the Government of Catalonia (DGRIS 3_9 to A.P.G. and J.S. and DGRIS 1_5 to M.J.B. and M.G.)

Making protein dynamics FAIR : Research platforms for the collection, dissemination, and analysis of molecular dynamics simulations

Molecular dynamics (MD) simulations are a well-established technique to characterize the structural motions of biological systems at atomic resolution. However, accessing, viewing, and sharing MD trajectories is typically restricted by large file sizes and the need for specialized software, which limits the audience to which this data is available. The aim of this thesis is to extend the outreach of MD simulations by providing online resources that facilitate the dissemination, visual inspection, and analysis of this data. For that, we present GPCRmd and SCoV2-MD, two online resources focused on proteins with high biomedical interest: G protein-coupled receptors (GPCRs) and the proteome of the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), respectively. We also showcase the capabilities of GPCRmd and SCoV2-MD for exploring key aspects of protein dynamics. Overall, these platforms have the potential to promote data “Findability, Accessibility, Interoperability, and Reusability” in the MD field, supporting the FAIR principles for scientific data management.Les simulacions de dinàmica molecular (MD, per les seves sigles en anglès) són una tècnica ben establerta per caracteritzar els moviments estructurals de sistemes biològics amb una resolució atòmica. No obstant això, l'accés, la visualització i la compartició de trajectòries de MD solen estar restringits per la gran mida dels seus fitxers i la necessitat de programari especialitzat, que limita el públic al qual estan disponibles aquestes dades. L'objectiu d'aquesta tesi és ampliar la difusió de les simulacions de MD proporcionant recursos en línia que facilitin la compartició, inspecció visual i anàlisi d'aquestes dades. Per això, presentem GPCRmd i SCoV2-MD, dos recursos en línia centrats en proteïnes d'alt interès biomèdic: els receptors acoblats a proteïnes G (coneguts com a GPCRs, per les seves sigles en anglès) i el proteoma del coronavirus 2 de la síndrome respiratòria aguda greu (SARS-CoV-2), respectivament. També mostrem les capacitats de GPCRmd i SCoV2-MD per explorar aspectes clau de la dinàmica de proteïnes. En definitiva, aquestes plataformes tenen el potencial de promoure la cercabilitat, l'accessibilitat, la interoperabilitat i la reutilització de dades en l'àmbit de la MD, donant suport als principis FAIR (acrònim de l’anglès Findable, Accessible, Interoperable and Reusable) per a la gestió de dades científiques

How do molecular dynamics data complement static structural data of GPCRs

G protein-coupled receptors (GPCRs) are implicated in nearly every physiological process in the human body and therefore represent an important drug targeting class. Advances in X-ray crystallography and cryo-electron microscopy (cryo-EM) have provided multiple static structures of GPCRs in complex with various signaling partners. However, GPCR functionality is largely determined by their flexibility and ability to transition between distinct structural conformations. Due to this dynamic nature, a static snapshot does not fully explain the complexity of GPCR signal transduction. Molecular dynamics (MD) simulations offer the opportunity to simulate the structural motions of biological processes at atomic resolution. Thus, this technique can incorporate the missing information on protein flexibility into experimentally solved structures. Here, we review the contribution of MD simulations to complement static structural data and to improve our understanding of GPCR physiology and pharmacology, as well as the challenges that still need to be overcome to reach the full potential of this technique

SCoV2-MD: a database for the dynamics of the SARS-CoV-2 proteome and variant impact predictions

SCoV2-MD (www.scov2-md.org) is a new online resource that systematically organizes atomistic simulations of the SARS-CoV-2 proteome. The database includes simulations produced by leading groups using molecular dynamics (MD) methods to investigate the structure-dynamics-function relationships of viral proteins. SCoV2-MD cross-references the molecular data with the pandemic evolution by tracking all available variants sequenced during the pandemic and deposited in the GISAID resource. SCoV2-MD enables the interactive analysis of the deposited trajectories through a web interface, which enables users to search by viral protein, isolate, phylogenetic attributes, or specific point mutation. Each mutation can then be analyzed interactively combining static (e.g. a variety of amino acid substitution penalties) and dynamic (time-dependent data derived from the dynamics of the local geometry) scores. Dynamic scores can be computed on the basis of nine non-covalent interaction types, including steric properties, solvent accessibility, hydrogen bonding, and other types of chemical interactions. Where available, experimental data such as antibody escape and change in binding affinities from deep mutational scanning experiments are also made available. All metrics can be combined to build predefined or custom scores to interrogate the impact of evolving variants on protein structure and function

Mechanistic insights into dopaminergic and serotonergic neurotransmission - concerted interactions with helices 5 and 6 drive the functional outcome

Brain functions rely on neurotransmitters that mediate communication between billions of neurons. Disruption of this communication can result in a plethora of psychiatric and neurological disorders. In this work, we combine molecular dynamics simulations, live-cell biosensor and electrophysiological assays to investigate the action of the neurotransmitter dopamine at the dopaminergic D2 receptor (D2R). The study of dopamine and closely related chemical probes reveals how neurotransmitter binding translates into the activation of distinct subsets of D2R effectors (i.e.: Gi2, GoB, Gz and β-arrestin 2). Ligand interactions with key residues in TM5 (S5.42) and TM6 (H6.55) in the D2R binding pocket yield a dopamine-like coupling signature, whereas exclusive TM5 interaction is typically linked to preferential G protein coupling (in particular GoB) over β-arrestin. Further experiments for serotonin receptors indicate that the reported molecular mechanism is shared by other monoaminergic neurotransmitter receptors. Ultimately, our study highlights how sequence variation in position 6.55 is used by nature to fine-tune β-arrestin recruitment and in turn receptor signaling and internalization of neurotransmitter receptors

In silico study of allosteric communication networks in GPCR signaling bias

Signaling bias is a promising characteristic of G protein-coupled receptors (GPCRs) as it provides the opportunity to develop more efficacious and safer drugs. This is because biased ligands can avoid the activation of pathways linked to side effects whilst still producing the desired therapeutic effect. In this respect, a deeper understanding of receptor dynamics and implicated allosteric communication networks in signaling bias can accelerate the research on novel biased drug candidates. In this review, we aim to provide an overview of computational methods and techniques for studying allosteric communication and signaling bias in GPCRs. This includes (i) the detection of allosteric communication networks and (ii) the application of network theory for extracting relevant information pipelines and highly communicated sites in GPCRs. We focus on the most recent research and highlight structural insights obtained based on the framework of allosteric communication networks and network theory for GPCR signaling bias

Entrectinib-A SARS-CoV-2 inhibitor in Human Lung Tissue (HLT) cells

Since the start of the COVID-19 outbreak, pharmaceutical companies and research groups have focused on the development of vaccines and antiviral drugs against SARS-CoV-2. Here, we apply a drug repurposing strategy to identify drug candidates that are able to block the entrance of the virus into human cells. By combining virtual screening with in vitro pseudovirus assays and antiviral assays in Human Lung Tissue (HLT) cells, we identify entrectinib as a potential antiviral drug