In Silico Identification of Natural Food Compounds as Potential Quorum-Sensing Inhibitors Targeting the LasR Receptor of Pseudomonas aeruginosa.

Pseudomonas aeruginosa is a major cause of nosocomial infections and is often associated with biofilm-mediated antibiotic resistance. The LasR protein is a key component of the quorum system in P. aeruginosa, allowing it to regulate its biofilm-induced pathogenicity. When the bacterial population reaches a sufficient density, the accumulation of N-(3-oxododecanoyl) acyl homoserine lactone (3O-C12-HSL) leads to the activation of the LasR receptor, which then acts as a transcriptional activator of target genes involved in biofilm formation and virulence, thereby increasing the bacteria's antibiotic resistance and enhancing its virulence. In this study, we performed a structure-based virtual screening of a natural food database of 10 997 compounds against the crystal structure of the ligand-binding domain of the LasR receptor (PDB ID: 3IX4). This allowed us to identify four molecules, namely ZINC000001580795, ZINC000014819517, ZINC000014708292, and ZINC000004098719, that exhibited a favorable binding mode and docking scores greater than -13 kcal/mol. Furthermore, the molecular dynamics simulation showed that these four molecules formed stable complexes with LasR during the 150-ns molecular dynamics (MD) simulation, indicating their potential for use as inhibitors of the LasR receptor in P. aeruginosa. However, further experimental validation is needed to confirm their activity.

In Silico Analyses of All STAT3 Missense Variants Leading to Explore Divergent AD-HIES Clinical Phenotypes.

Autosomal dominant hyper-IgE syndrome (AD-HIES) is linked to dominant negative mutations of the STAT3 protein whose molecular basis for dysfunction is unclear and presenting with a variety of clinical manifestations with only supportive treatment. To establish the relationship between the impact of STAT3 mutations in different domains and the severity of the clinical manifestations, 105 STAT3 mutations were analyzed for their impact on protein stability, flexibility, function, and binding affinity using in Silico approaches. Our results showed that 73% of the studied mutations have an impact on the physicochemical properties of the protein, altering the stability, flexibility and function to varying degrees. In particular, mutations affecting the DNA binding domain (DBD) and the Src Homology 2 (SH2) have a significant impact on the protein structure and disrupt its interaction either with DNA or other STAT3 to form a heterodomain complex, leading to severe clinical phenotypes. Collectively, this study suggests that there is a close relationship between the domain involving the mutation, the degree of variation in the properties of the protein and the degree of loss of function ranging from partial loss to complete loss, explaining the variability of clinical manifestations between mild and severe.

Genomic analysis of Paenibacillus sp. MDMC362 from the Merzouga desert leads to the identification of a potentially thermostable catalase.

Microorganisms in hot deserts face heat and other environmental conditions, such as desiccation, UV radiation, or low nutrient availability. Therefore, this hostile environment harbour microorganisms with acquired characteristics related to survival in their habitat, which can be exploited in biotechnology. In this work, the genome of Paenibacillus sp. MDMC362 isolated from the Merzouga desert in Morocco was sequenced to understand its survival strategy's genetic basis; and to evaluate the thermostability of a catalase extracted from genomic annotation files using molecular dynamics. Paenibacillus sp. MDMC362 genome was rich in genetic elements involved in the fight against different stresses, notably temperature stress, UV radiations, osmotic stress, carbon starvation, and oxidative stress. Indeed, we could identify genes of the operons groES-groEL and hrcA-grpE-dnaK and those involved in the different stages of sporulation, which can help the bacteria to survive the high temperatures imposed by a desertic environment. We also observed the genetic components of the UvrABC system and additional mechanisms involved in DNA repair, which help overcome UV radiation damage. Other genes have been identified in the genome, like those coding for ectoine and proline, that aids fight osmotic stress and desiccation. Catalase thermostability investigation using molecular dynamics showed that the protein reached stability and conserved its compactness at temperatures up to 373.15 K. These results suggest a potential thermostability of the enzyme. Since the studied protein is a core protein, thermostability could be conserved among Paenibacillus sp. MDMC362 closely related strains; however, bacteria from harsh environments may have a slight advantage regarding protein stability.

Computational modeling and druggability assessment of Aggregatibacter actinomycetemcomitans leukotoxin.

The leukotoxin (LtxA) of Aggregatibacter actinomycetemcomitans (A. actinomycetemcomitans) is a protein exotoxin belonging to the repeat-in-toxin family (RTX). Numerous studies have demonstrated that LtxA may play a critical role in the pathogenicity of A. actinomycetemcomitans since hyper-leukotoxic strains have been associated with severe disease. Accordingly, considerable effort has been made to elucidate the mechanisms by which LtxA interacts with host cells and induce their death. However, these attempts have been hampered by the unavailability of a tertiary structure of the toxin, which limits the understanding of its molecular properties and mechanisms. In this paper, we used homology and template free modeling algorithms to build the complete tertiary model of LtxA at atomic level in its calcium-bound Holo-state. The resulting model was refined by energy minimization, validated by Molprobity and ProSA tools, and subsequently subjected to a cumulative 600ns of all-atom classical molecular dynamics simulation to evaluate its structural aspects. The druggability of the proposed model was assessed using Fpocket and FTMap tools, resulting in the identification of four putative cavities and fifteen binding hotspots that could be targeted by rational drug design tools to find new ligands to inhibit LtxA activity.

In silico exploration of small-molecule α-helix mimetics as inhibitors of SARS-COV-2 attachment to ACE2.

The novel coronavirus, SARS-CoV-2, has infected more than 10 million people and caused more than 502,539 deaths worldwide as of June 2020. The explosive spread of the virus and the rapid increase in the number of cases require the immediate development of effective therapies and vaccines as well as accurate diagnosis tools. The pathogenesis of the disease is triggered by the entry of SARS-CoV-2 via its spike protein into ACE2-bearing host cells, particularly pneumocytes, resulting in overactivation of the immune system, which attacks the infected cells and damages the lung tissue. The interaction of the SARS-CoV-2 receptor binding domain (RBD) with host cells is primarily mediated by the N-terminal helix of ACE2; thus, inhibition of the spike-ACE2 interaction may be a promising therapeutic strategy for blocking the virus entry into host cells. In this paper, we used an in-silico approach to explore small-molecule α-helix mimetics as inhibitors that may disrupt the attachment of SARS-CoV-2 to ACE2. First, the RBD-ACE2 interface in the 6M0J structure was studied by the MM-GBSA decomposition module of the HawkDock server, which led to the identification of two critical target regions in the RBD. Next, two virtual screening experiments of 7236 α-helix mimetics from ASINEX were conducted on the above regions using the iDock tool, which resulted in 10 candidates with favorable binding affinities. Finally, the stability of RBD complexes with the top-two ranked compounds was further validated by 100 ns of molecular dynamics simulations.Communicated by Ramaswamy H. Sarma.

In-silico identification of potential inhibitors targeting the DNA binding domain of estrogen receptor α for the treatment of hormone therapy-resistant breast cancer.

Estrogen receptor α (ERα) plays a critical role in breast cancer (BC) development. The standard therapeutic strategies for ERα- positive (ERα+) BC consist of impairing ERα signalling pathway by either estrogen competitors blocking its interaction with the ligand binding domain (LBD) or agents inhibiting the production of estrogen. These strategies are limited by many factors that lead to constitutive activation of ERα and consequently, resistance to treatment. Targeting the DNA binding domain (DBD) of ERα instead of its LBD with small-molecule inhibitors could be an alternative to impair ERα's signalling pathway. For this purpose, we conducted a structure based virtual screening of DrugBank against the crystal structure of ERα-DBD (PDB ID: 1HCQ) using the Glide module in standard precision (SP) and extra precision (XP) mode of docking. Molecules with XP Gscore less than -8 kcal/mol were selected and visually inspected to keep only the reasonable docking poses. Subsequently, these molecules were clustered using structural interaction fingerprints analysis and the complexes of the top ranked molecules of each cluster based on XP Gscore were subjected to 200 ns molecular dynamics simulations followed by MM-GBSA binding free energy calculation for the last 100 ns of each complex. In this study, we identified three molecules from DrugBank namely DB03450, DB02593 and DB08001 showing significant stability and strong interaction with the key amino acids during MD simulation suggesting a potential inhibition of the target. These molecules could be used as promising lead compounds to impair the ERα signalisation in hormone therapy-resistant breast cancer.Communicated by Ramaswamy H. Sarma.

IDbSV: An Open-Access Repository for Monitoring SARS-CoV-2 Variations and Evolution.

Ending COVID-19 pandemic requires a collaborative understanding of SARS-CoV-2 and COVID-19 mechanisms. Yet, the evolving nature of coronaviruses results in a continuous emergence of new variants of the virus. Central to this is the need for a continuous monitoring system able to detect potentially harmful variants of the virus in real-time. In this manuscript, we present the International Database of SARS-CoV-2 Variations (IDbSV), the result of ongoing efforts in curating, analyzing, and sharing comprehensive interpretation of SARS-CoV-2's genetic variations and variants. Through user-friendly interactive data visualizations, we aim to provide a novel surveillance tool to the scientific and public health communities. The database is regularly updated with new records through a 4-step workflow (1-Quality control of curated sequences, 2-Call of variations, 3-Functional annotation, and 4-Metadata association). To the best of our knowledge, IDbSV provides access to the largest repository of SARS-CoV-2 variations and the largest analysis of SARS-CoV-2 genomes with over 60 thousand annotated variations curated from the 1,808,613 genomes alongside their functional annotations, first known appearance, and associated genetic lineages, enabling a robust interpretation tool for SARS-CoV-2 variations to help understanding SARS-CoV-2 dynamics across the world.

Identifying epitopes for cluster of differentiation and design of new peptides inhibitors against human SARS-CoV-2 spike RBD by an in-silico approach.

The coronavirus disease 19 (COVID-19) is a highly contagious and rapidly spreading infection caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In some cases, the disease can be fatal which resulted in more than one million deaths worldwide according the WHO. Currently, there is no effective vaccine or treatment for COVID-19, however many small-molecule inhibitors have shown potent antiviral activity against SARS-CoV-2 and some of them are now under clinical trials. Despite their promising activities, the development of these small molecules for the clinical use can be limited by many factors like the off-target effect, the poor stability, and the low bioavailability. The clusters of differentiation CD147, CD209, CD299 have been identified as essential entry co-receptors for SARS-CoV-2 species specificity to humans, although the underlying mechanisms are yet to be fully elucidated. In this paper, protein-protein docking was utilized for identifying the critical epitopes in CD147, CD209 and CD299 which are involved in the binding with SARS-CoV-2 Spike receptor binding domain (RBD). The results of binding free energies showed a high affinity of SARS-CoV-2 RBD to CD299 receptor which was used as a reference to derive hypothetical peptide sequences with specific binding activities to SARS-CoV-2 RBD. Molecular docking and molecular dynamics simulations of the newly designed peptides showed favorable binding features and stability with SARS-CoV-2 RBD and therefore can be further considered as potential candidates in future anti-SARS CoV-2 drug discovery studies.

Large scale genomic analysis of 3067 SARS-CoV-2 genomes reveals a clonal geo-distribution and a rich genetic variations of hotspots mutations.

In late December 2019, an emerging viral infection COVID-19 was identified in Wuhan, China, and became a global pandemic. Characterization of the genetic variants of SARS-CoV-2 is crucial in following and evaluating it spread across countries. In this study, we collected and analyzed 3,067 SARS-CoV-2 genomes isolated from 55 countries during the first three months after the onset of this virus. Using comparative genomics analysis, we traced the profiles of the whole-genome mutations and compared the frequency of each mutation in the studied population. The accumulation of mutations during the epidemic period with their geographic locations was also monitored. The results showed 782 variants sites, of which 512 (65.47%) had a non-synonymous effect. Frequencies of mutated alleles revealed the presence of 68 recurrent mutations, including ten hotspot non-synonymous mutations with a prevalence higher than 0.10 in this population and distributed in six SARS-CoV-2 genes. The distribution of these recurrent mutations on the world map revealed that certain genotypes are specific to geographic locations. We also identified co-occurring mutations resulting in the presence of several haplotypes. Moreover, evolution over time has shown a mechanism of mutation co-accumulation which might affect the severity and spread of the SARS-CoV-2. The phylogentic analysis identified two major Clades C1 and C2 harboring mutations L3606F and G614D, respectively and both emerging for the first time in China. On the other hand, analysis of the selective pressure revealed the presence of negatively selected residues that could be taken into considerations as therapeutic targets. We have also created an inclusive unified database (http://covid-19.medbiotech.ma) that lists all of the genetic variants of the SARS-CoV-2 genomes found in this study with phylogeographic analysis around the world.

In silico analysis of ACE2 orthologues to predict animal host range with high susceptibility to SARS-CoV-2.

SARS-CoV-2, which causes severe pneumonia epidemics, probably originated from Chinese horseshoe bats, but the intermediate and host range is still unknown. ACE2 is the entry receptor for SARS-CoV-2. The binding capacity of SARS-CoV-2 spike protein to ACE2 is the critical determinant of viral host range and cross-species infection. Here, we used an in silico approach to predict the potential animals range with high susceptibility to SARS-CoV-2 by modelling and studying the Spike-ACE2 interaction of 22 domestic and wild animals. Our results showed that all studied animals are potentially susceptible to SARS-CoV-2 infection with a slight difference in the binding affinity and stability of their ACE2-RBD complexes. Furthermore, we identified a specific substitution of tyrosine to histidine at position 41 in ACE2 that likely reduces the affinity to SARS-CoV-2 in horses and greater horseshoe bats. These results may help to provide important insights into SARS-CoV-2 host range which will make it possible to control the spread of the virus and identify animal models that could be used for screening antiviral drugs or vaccine candidates against SARS-CoV-2.

Genomic Diversity and Hotspot Mutations in 30,983 SARS-CoV-2 Genomes: Moving Toward a Universal Vaccine for the "Confined Virus"?

The COVID-19 pandemic has been ongoing since its onset in late November 2019 in Wuhan, China. Understanding and monitoring the genetic evolution of the virus, its geographical characteristics, and its stability are particularly important for controlling the spread of the disease and especially for the development of a universal vaccine covering all circulating strains. From this perspective, we analyzed 30,983 complete SARS-CoV-2 genomes from 79 countries located in the six continents and collected from 24 December 2019, to 13 May 2020, according to the GISAID database. Our analysis revealed the presence of 3206 variant sites, with a uniform distribution of mutation types in different geographic areas. Remarkably, a low frequency of recurrent mutations has been observed; only 169 mutations (5.27%) had a prevalence greater than 1% of genomes. Nevertheless, fourteen non-synonymous hotspot mutations (>10%) have been identified at different locations along the viral genome; eight in ORF1ab polyprotein (in nsp2, nsp3, transmembrane domain, RdRp, helicase, exonuclease, and endoribonuclease), three in nucleocapsid protein, and one in each of three proteins: Spike, ORF3a, and ORF8. Moreover, 36 non-synonymous mutations were identified in the receptor-binding domain (RBD) of the spike protein with a low prevalence (<1%) across all genomes, of which only four could potentially enhance the binding of the SARS-CoV-2 spike protein to the human ACE2 receptor. These results along with intra-genomic divergence of SARS-CoV-2 could indicate that unlike the influenza virus or HIV viruses, SARS-CoV-2 has a low mutation rate which makes the development of an effective global vaccine very likely.

Repurposing of known anti-virals as potential inhibitors for SARS-CoV-2 main protease using molecular docking analysis.

The new SARS-CoV-2 coronavirus is the causative agent of the COVID-19 pandemic outbreak that affected more than 190 countries worldwide with more than 292,000 confirmed cases and over 12,700 deaths. There is at the moment no vaccine or effective treatment for this disease which constitutes a serious global health problem. It is of interest to use a structure based virtual screening approach for the identification of potential inhibitors of the main protease of SARS-CoV-2 (Mpro) from antiviral drugs used to treat other viral disease such as human immunodeficiency virus (HIV) and hepatitis C virus (HCV) infections. The crystallographic structure with PDB ID: 6LU7 of Mpro in complex with the inhibitor N3 was used as a model in the virtual screening of 33 protease inhibitors collected from the ChEMBL chemical database. Molecular docking analysis was performed using the standard AutoDock vina protocol followed by ranking and selection of compounds based on their binding affinity. We report 10 candidates with optimal binding features to the active site of the protease for further consideration as potential drugs to treat patients infected with the emerging COVID-19 disease.