Biology subjects

Musiani, F.

Publications and source records attributed to Musiani, F..

5 recordsLinked to original sources

bioRxiv2025

Computational screening and automatic filtering for the discovery of novel inhibitors of TMPRSS2, a type II transmembrane serine protease

Transmembrane Serine Protease 2 (TMPRSS2) is a membrane protein of the type II serine protease family of enzymes implied in epithelial homeostasis. It is involved in several diseases, notably prostate cancer and SARS-CoV-2 infections. Over the years, only a few tested TMPRSS2 inhibitors showed consistent results. This prompted us to select it as target of structure-based virtual screening, to search for novel inhibitors among a library of 475,770 small molecules. Two sets of TMPRSS2 structures were selected, one taken from molecular dynamics simulations, the other from recently solved X-ray crystallographic structures. We designed a workflow to filter docking results in a reproducible way, allowing for a faster and more reliable selection. The program uses four metrics: the pose consistency of the ligand, docking score, number of interactions with key protein residues, and cluster analysis. This led to the selection and visual inspection of two sets of 500 compounds, which yielded 10 reasonable hit candidates.

bioinformatics↗

bioRxiv2023

A computational study to assess the pathogenicity of single or combinations of missense variants on respiratory Complex I

Variants found in the respiratory complex I (CI) subunit genes encoded by mitochondrial DNA can cause severe genetic diseases. However, it is difficult to establish a priori whether a single or a combination of CI variants may impact oxidative phosphorylation. Here we propose a computational approach based on coarse-grained molecular dynamics simulations. One of the primary CI variants (m.14484T>C/MT-ND6) associated with the Leber hereditary optic neuropathy was used as a test case. This variant was investigated alone or in combination with two additional rare CI variants whose role remains uncertain. We found that the primary variant stiffens CI dynamics in the crucial E-channel region and that one of the other variants, located in the vicinity of the primary one, further worsens the stiffening. This approach may be extended to other variants candidate to exert a pathogenic impact on CI function, or to investigate the interaction of multiple variants. TeaserMolecular dynamics is able to predict the functional impact of variants hitting respiratory complex I mitochondrial genes.

biophysics↗

bioRxiv2022

Modelling eNvironment for Isoforms (MoNvIso): A general platform to predict structural determinants of protein isoforms in genetic diseases

The seamless integration of human disease-related mutation data into protein structures is an essential component of any attempt to correctly assess the impact of the mutation. The key step preliminary to any structural modelling is the identification of the correct isoform onto which mutations should be mapped because there are several functionally different protein isoforms from the same gene. To handle large sets of data coming from omics techniques, this challenging task should be automatized. Here we present our code MoNvIso (Modelling eNvironment for Isoforms), which pinpoints the correct isoform associated with the mutation of interest and builds a structural model of both the wild type isoform and the related variants starting from the name of the gene and the list of mutations of interest.

bioinformatics↗

bioRxiv2020

Identification of inhibitors of SARS-CoV-2 3CL-Pro enzymatic activity using a small molecule in-vitro repurposing screen

Compound repurposing is an important strategy for the identification of effective treatment options against SARS-CoV-2 infection and COVID-19 disease. In this regard, SARS-CoV-2 main protease (3CL-Pro), also termed M-Pro, is an attractive drug target as it plays a central role in viral replication by processing the viral polyproteins pp1a and pp1ab at multiple distinct cleavage sites. We here report the results of a repurposing program involving 8.7 K compounds containing marketed drugs, clinical and preclinical candidates, and small molecules regarded as safe in humans. We confirmed previously reported inhibitors of 3CL-Pro, and have identified 62 additional compounds with IC50 values below 1 M and profiled their selectivity towards Chymotrypsin and 3CL-Pro from the MERS virus. A subset of 8 inhibitors showed anti-cytopathic effect in a Vero-E6 cell line and the compounds thioguanosine and MG-132 were analysed for their predicted binding characteristics to SARS-CoV-2 3CL-Pro. The X-ray crystal structure of the complex of myricetin and SARS-Cov-2 3CL-Pro was solved at a resolution of 1.77 [A], showing that myricetin is covalently bound to the catalytic Cys145 and therefore inhibiting its enzymatic activity. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=154 SRC="FIGDIR/small/422677v1_ufig1.gif" ALT="Figure 1"> View larger version (41K): org.highwire.dtl.DTLVardef@17ca2aeorg.highwire.dtl.DTLVardef@19c5159org.highwire.dtl.DTLVardef@1a0adf6org.highwire.dtl.DTLVardef@1fd05cd_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOAbstract Figure.C_FLOATNO Workflow for identification and profiling of inhibitors of SARS-CoV-2 3CL-Pro using a large scale repurposing and bioactive compound collection (rhs). Primary assay principle based on quenched FRET peptide substrate of SARS-CoV-2 3CL-Pro (lhs). Inhibiting compounds reduce fluorescence signal relative to DMSO controls. Hit profiling using X-ray. C_FIG

molecular biology↗

bioRxiv2020

A blueprint for high affinity SARS-CoV-2 Mpro inhibitors from activity-based compound library screening guided by analysis of protein dynamics

The SARS-CoV-2 coronavirus outbreak continues to spread at a rapid rate worldwide. The main protease (Mpro) is an attractive target for anti-COVID-19 agents. Unfortunately, unexpected difficulties have been encountered in the design of specific inhibitors. Here, by analyzing an ensemble of ~30,000 SARS-CoV-2 Mpro conformations from crystallographic studies and molecular simulations, we show that small structural variations in the binding site dramatically impact ligand binding properties. Hence, traditional druggability indices fail to adequately discriminate between highly and poorly druggable conformations of the binding site. By performing ~200 virtual screenings of compound libraries on selected protein structures, we redefine the proteins druggability as the consensus chemical space arising from the multiple conformations of the binding site formed upon ligand binding. This procedure revealed a unique SARS-CoV-2 Mpro blueprint that led to a definition of a specific structure-based pharmacophore. The latter explains the poor transferability of potent SARS-CoV Mpro inhibitors to SARS-CoV-2 Mpro, despite the identical sequences of the active sites. Importantly, application of the pharmacophore predicted novel high affinity inhibitors of SARS-CoV-2 Mpro, that were validated by in vitro assays performed here and by a newly solved X-ray crystal structure. These results provide a strong basis for effective rational drug design campaigns against SARS-CoV-2 Mpro and a new computational approach to screen protein targets with malleable binding sites.

biophysics↗