Targeting SARS-CoV-2 Main Protease: A Successful Story Guided by an In Silico Drug Repurposing Approach.

The SARS-CoV-2 main protease (Mpro) is a crucial enzyme for viral replication and has been considered an attractive drug target for the treatment of COVID-19. In this study, virtual screening techniques and in vitro assays were combined to identify novel Mpro inhibitors starting from around 8000 FDA-approved drugs. The docking analysis highlighted 17 promising best hits, biologically characterized in terms of their Mpro inhibitory activity. Among them, 7 cephalosporins and the oral anticoagulant betrixaban were able to block the enzyme activity in the micromolar range with no cytotoxic effect at the highest concentration tested. After the evaluation of the degree of conservation of Mpro residues involved in the binding with the studied ligands, the ligands' activity on SARS-CoV-2 replication was assessed. The ability of betrixaban to affect SARS-CoV-2 replication associated to its antithrombotic effect could pave the way for its possible use in the treatment of hospitalized COVID-19 patients.

Short- and Long-Term Regulation of HuD: A Molecular Switch Mediated by Folic Acid?

The RNA-binding protein HuD has been shown to play a crucial role in gene regulation in the nervous system and is involved in various neurological and psychiatric diseases. In this study, through the creation of an interaction network on HuD and its potential targets, we identified a strong association between HuD and several diseases of the nervous system. Specifically, we focused on the relationship between HuD and the brain-derived neurotrophic factor (BDNF), whose protein is implicated in several neuronal diseases and is involved in the regulation of neuronal development, survival, and function. To better investigate this relationship and given that we previously demonstrated that folic acid (FA) is able to directly bind HuD itself, we performed in vitro experiments in neuron-like human SH-SY5Y cells in the presence of FA, also known to be a pivotal environmental factor influencing the nervous system development. Our findings show that FA exposure results in a significant increase in both HuD and BDNF transcripts and proteins after 2 and 4 h of treatment, respectively. Similar data were obtained after 2 h of FA incubation followed by 2 h of washout. This increase was no longer detected upon 24 h of FA exposure, probably due to a signaling shutdown mechanism. Indeed, we observed that following 24 h of FA exposure HuD is methylated. These findings indicate that FA regulates BDNF expression via HuD and suggest that FA can behave as an epigenetic modulator of HuD in the nervous system acting via short- and long-term mechanisms. Finally, the present results also highlight the potential of BDNF as a therapeutic target for specific neurological and psychiatric diseases.

Natural Agents as Novel Potential Source of Proteasome Inhibitors with Anti-Tumor Activity: Focus on Multiple Myeloma.

Multiple myeloma (MM) is an aggressive and incurable disease for most patients, characterized by periods of treatment, remission and relapse. The introduction of new classes of drugs, such as proteasome inhibitors (PIs), has improved survival outcomes in these patient populations. The proteasome is the core of the ubiquitin-proteasome system (UPS), a complex and conserved pathway involved in the control of multiple cellular processes, including cell cycle control, transcription, DNA damage repair, protein quality control and antigen presentation. To date, PIs represent the gold standard for the treatment of MM. Bortezomib was the first PI approved by the FDA, followed by next generation of PIs, namely carfilzomib and ixazomib. Natural agents play an important role in anti-tumor drug discovery, and many of them have recently been reported to inhibit the proteasome, thus representing a new potential source of anti-MM drugs. Based on the pivotal biological role of the proteasome and on PIs' significance in the management of MM, in this review we aim to briefly summarize recent evidence on natural compounds capable of inhibiting the proteasome, thus triggering anti-MM activity.

From Nature to Synthetic Compounds: Novel 1(N),2,3 Trisubstituted-5-oxopyrrolidines Targeting Multiple Myeloma Cells.

The insurgence of drug resistance in treating Multiple Myeloma (MM) still represents a major hamper in finding effective treatments, although over the past decades new classes of drugs, such as proteasome inhibitors and immunomodulatory drugs, have been discovered. Recently, our research team, within a Nature-Aided Drug Discovery project, isolated from Hibiscus Sabdariffa L. calyces the secondary metabolite called Hib-ester which possesses antiproliferative properties against human multiple myeloma RPMI 8226 cells, reduces migration and cell invasion and inhibits proteasome without neurotoxic effects. In the present study, we explored the chemical spaces of the hit compound Hib-ester. We explored the structure-activity relationships (SAR), and we optimized the scaffold through sequentially modifying Hib-ester subunits. Compound screening was performed based on cytotoxicity against the RPMI 8226 cells to assess the potential efficacy toward human MM. The ability of the most effective molecules to inhibit the proteasome was evaluated and the binding mode of the most promising compounds in the proteasome chymotrypsin binding pocket was deciphered through molecular modeling simulations. Compounds 13 and 14 are more potent than Hib-ester, demonstrating that our strategy was suitable for the identification of a novel chemotype for developing possible drug candidates and hopefully widening the drug armamentarium against MM.

Targeting SARS-CoV-2 nsp13 Helicase and Assessment of Druggability Pockets: Identification of Two Potent Inhibitors by a Multi-Site In Silico Drug Repurposing Approach.

The SARS-CoV-2 non-structural protein 13 (nsp13) helicase is an essential enzyme for viral replication and has been identified as an attractive target for the development of new antiviral drugs. In detail, the helicase catalyzes the unwinding of double-stranded DNA or RNA in a 5' to 3' direction and acts in concert with the replication-transcription complex (nsp7/nsp8/nsp12). In this work, bioinformatics and computational tools allowed us to perform a detailed conservation analysis of the SARS-CoV-2 helicase genome and to further predict the druggable enzyme's binding pockets. Thus, a structure-based virtual screening was used to identify valuable compounds that are capable of recognizing multiple nsp13 pockets. Starting from a database of around 4000 drugs already approved by the Food and Drug Administration (FDA), we chose 14 shared compounds capable of recognizing three out of four sites. Finally, by means of visual inspection analysis and based on their commercial availability, five promising compounds were submitted to in vitro assays. Among them, PF-03715455 was able to block both the unwinding and NTPase activities of nsp13 in a micromolar range.

Key genetic elements, single and in clusters, underlying geographically dependent SARS-CoV-2 genetic adaptation and their impact on binding affinity for drugs and immune control.

OBJECTIVES: To define key genetic elements, single or in clusters, underlying SARS-CoV-2 (severe acute respiratory syndrome coronavirus-2) evolutionary diversification across continents, and their impact on drug-binding affinity and viral antigenicity. METHODS: A total of 12 150 SARS-CoV-2 sequences (publicly available) from 69 countries were analysed. Mutational clusters were assessed by hierarchical clustering. Structure-based virtual screening (SBVS) was used to select the best inhibitors of 3-chymotrypsin-like protease (3CL-Pr) and RNA-dependent RNA polymerase (RdRp) among the FDA-approved drugs and to evaluate the impact of mutations on binding affinity of these drugs. The impact of mutations on epitope recognition was predicted following Grifoni et al. (Cell Host Microbe 2020. 27: 671-80.). RESULTS: Thirty-five key mutations were identified (prevalence: ≥0.5%), residing in different viral proteins. Sixteen out of 35 formed tight clusters involving multiple SARS-CoV-2 proteins, highlighting intergenic co-evolution. Some clusters (including D614GSpike + P323LRdRp + R203KN + G204RN) occurred in all continents, while others showed a geographically restricted circulation (T1198KPL-Pr + P13LN + A97VRdRp in Asia, L84SORF-8 + S197LN in Europe, Y541CHel + H504CHel + L84SORF-8 in America and Oceania). SBVS identified 20 best RdRp inhibitors and 21 best 3CL-Pr inhibitors belonging to different drug classes. Notably, mutations in RdRp or 3CL-Pr modulate, positively or negatively, the binding affinity of these drugs. Among them, P323LRdRp (prevalence: 61.9%) reduced the binding affinity of specific compounds including remdesivir while it increased the binding affinity of the purine analogues penciclovir and tenofovir, suggesting potential hypersusceptibility. Finally, specific mutations (including Y541CHel + H504CHel) strongly hampered recognition of Class I/II epitopes, while D614GSpike profoundly altered the structural stability of a recently identified B cell epitope target of neutralizing antibodies (amino acids 592-620). CONCLUSIONS: Key genetic elements reflect geographically dependent SARS-CoV-2 genetic adaptation, and may play a potential role in modulating drug susceptibility and hampering viral antigenicity. Thus, a close monitoring of SARS-CoV-2 mutational patterns is crucial to ensure the effectiveness of treatments and vaccines worldwide.

Current status of antivirals and druggable targets of SARS CoV-2 and other human pathogenic coronaviruses.

Coronaviridae is a peculiar viral family, with a very large RNA genome and characteristic appearance, endowed with remarkable tendency to transfer from animals to humans. Since the beginning of the 21st century, three highly transmissible and pathogenic coronaviruses have crossed the species barrier and caused deadly pneumonia, inflicting severe outbreaks and causing human health emergencies of inconceivable magnitude. Indeed, in the past two decades, two human coronaviruses emerged causing serious respiratory illness: severe acute respiratory syndrome coronavirus (SARS-CoV-1) and Middle Eastern respiratory syndrome coronavirus (MERS-CoV), causing more than 10,000 cumulative cases, with mortality rates of 10 % for SARS-CoV-1 and 34.4 % for MERS-CoV. More recently, the severe acute respiratory syndrome coronavirus virus 2 (SARS-CoV-2) has emerged in China and has been identified as the etiological agent of the recent COVID-19 pandemic outbreak. It has rapidly spread throughout the world, causing nearly 22 million cases and ∼ 770,000 deaths worldwide, with an estimated mortality rate of ∼3.6 %, hence posing serious challenges for adequate and effective prevention and treatment. Currently, with the exception of the nucleotide analogue prodrug remdesivir, and despite several efforts, there is no known specific, proven, pharmacological treatment capable of efficiently and rapidly inducing viral containment and clearance of SARS-CoV-2 infection as well as no broad-spectrum drug for other human pathogenic coronaviruses. Another confounding factor is the paucity of molecular information regarding the tendency of coronaviruses to acquire drug resistance, a gap that should be filled in order to optimize the efficacy of antiviral drugs. In this light, the present review provides a systematic update on the current knowledge of the marked global efforts towards the development of antiviral strategies aimed at coping with the infection sustained by SARS-CoV-2 and other human pathogenic coronaviruses, displaying drug resistance profiles. The attention has been focused on antiviral drugs mainly targeting viral protease, RNA polymerase and spike glycoprotein, that have been tested in vitro and/or in clinical trials as well as on promising compounds proven to be active against coronaviruses by an in silico drug repurposing approach. In this respect, novel insights on compounds, identified by structure-based virtual screening on the DrugBank database endowed by multi-targeting profile, are also reported. We specifically identified 14 promising compounds characterized by a good in silico binding affinity towards, at least, two of the four studied targets (viral and host proteins). Among which, ceftolozane and NADH showed the best multi-targeting profile, thus potentially reducing the emergence of resistant virus strains. We also focused on potentially novel pharmacological targets for the development of compounds with anti-pan coronavirus activity. Through the analysis of a large set of viral genomic sequences, the current review provides a comprehensive and specific map of conserved regions across human coronavirus proteins which are essential for virus replication and thus with no or very limited tendency to mutate. Hence, these represent key druggable targets for novel compounds against this virus family. In this respect, the identification of highly effective and innovative pharmacological strategies is of paramount importance for the treatment and/or prophylaxis of the current pandemic but potentially also for future and unavoidable outbreaks of human pathogenic coronaviruses.

Anti-Multiple Myeloma Potential of Secondary Metabolites from Hibiscus sabdariffa-Part 2.

Multiple Myeloma (MM) is an aggressive tumor causing millions of deaths every year and currently available therapies are often unsuccessful or correlated with severe side effects. In our previous work we demonstrated that the Hibiscus sabdariffa hydroalcoholic extract inhibits the growth of the MM cell line and we isolated two metabolites responsible for the activity: Hib-ester and Hib-carbaldehyde. Herein we report their interaction with proteasome, one of the main targets in the fight against MM. The molecular modelling study outlined a good interaction of both compounds with the target and these results prompted us to investigate their potential to inhibit proteasome. Metabolites were then isolated from the calyces and an extract with a high content of Hib-ester and Hib-carbaldehyde was prepared. An anticancer profile was drawn, evaluating apoptosis, autophagy and proteasome inhibition, with the anticancer properties being mainly attributed to the Hib-ester and Hib-carbaldehyde, while the proteasome inhibition of the extract could also be ascribed to the presence of anthocyanins, a class of secondary metabolites already known for their proteasome inhibitory activity.

AutoDock Bias: improving binding mode prediction and virtual screening using known protein-ligand interactions.

SUMMARY: The performance of docking calculations can be improved by tuning parameters for the system of interest, e.g. biasing the results towards the formation of relevant protein-ligand interactions, such as known ligand pharmacophore or interaction sites derived from cosolvent molecular dynamics. AutoDock Bias is a straightforward and easy to use script-based method that allows the introduction of different types of user-defined biases for fine-tuning AutoDock4 docking calculations. AVAILABILITY AND IMPLEMENTATION: AutoDock Bias is distributed with MGLTools (since version 1.5.7), and freely available on the web at http://ccsb.scripps.edu/mgltools/ or http://autodockbias.wordpress.com. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

D3R Grand Challenge 4: prospective pose prediction of BACE1 ligands with AutoDock-GPU.

In this paper we describe our approaches to predict the binding mode of twenty BACE1 ligands as part of Grand Challenge 4 (GC4), organized by the Drug Design Data Resource. Calculations for all submissions (except for one, which used AutoDock4.2) were performed using AutoDock-GPU, the new GPU-accelerated version of AutoDock4 implemented in OpenCL, which features a gradient-based local search. The pose prediction challenge was organized in two stages. In Stage 1a, the protein conformations associated with each of the ligands were undisclosed, so we docked each ligand to a set of eleven receptor conformations, chosen to maximize the diversity of binding pocket topography. Protein conformations were made available in Stage 1b, making it a re-docking task. For all calculations, macrocyclic conformations were sampled on the fly during docking, taking the target structure into account. To leverage information from existing structures containing BACE1 bound to ligands available in the PDB, we tested biased docking and pose filter protocols to facilitate poses resembling those experimentally determined. Both pose filters and biased docking resulted in more accurate docked poses, enabling us to predict for both Stages 1a and 1b ligand poses within 2 Å RMSD from the crystallographic pose. Nevertheless, many of the ligands could be correctly docked without using existing structural information, demonstrating the usefulness of physics-based scoring functions, such as the one used in AutoDock4, for structure based drug design.

Comparison of affinity ranking using AutoDock-GPU and MM-GBSA scores for BACE-1 inhibitors in the D3R Grand Challenge 4.

Molecular docking has been successfully used in computer-aided molecular design projects for the identification of ligand poses within protein binding sites. However, relying on docking scores to rank different ligands with respect to their experimental affinities might not be sufficient. It is believed that the binding scores calculated using molecular mechanics combined with the Poisson-Boltzman surface area (MM-PBSA) or generalized Born surface area (MM-GBSA) can predict binding affinities more accurately. In this perspective, we decided to take part in Stage 2 of the Drug Design Data Resource (D3R) Grand Challenge 4 (GC4) to compare the performance of a quick scoring function, AutoDock4, to that of MM-GBSA in predicting the binding affinities of a set of [Formula: see text]-Amyloid Cleaving Enzyme 1 (BACE-1) ligands. Our results show that re-scoring docking poses using MM-GBSA did not improve the correlation with experimental affinities. We further did a retrospective analysis of the results and found that our MM-GBSA protocol is sensitive to details in the protein-ligand system: (i) neutral ligands are more adapted to MM-GBSA calculations than charged ligands, (ii) predicted binding affinities depend on the initial conformation of the BACE-1 receptor, (iii) protonating the aspartyl dyad of BACE-1 correctly results in more accurate binding affinity predictions.

Neurodegeneration: can metabolites from Eremurus persicus help?

The number of patients affected by neurodegenerative diseases is increasing worldwide, and no effective treatments have been developed yet. Although precision medicine could represent a powerful tool, it remains a challenge due to the high variability among patients. To identify molecules acting with innovative mechanisms of action, we performed a computational investigation using SAFAN technology, focusing specifically on HuD. This target belongs to the human embryonic lethal abnormal visual-like (ELAV) proteins and plays a key role in neuronal plasticity and differentiation. The results highlighted that the molecule able to bind the selected target was (R)-aloesaponol-III-8-methyl ether [(R)-ASME], a metabolite extracted from Eremurus persicus. Notably, this molecule is a TNF-α inhibitor, a cytokine involved in neuroinflammation. To obtain a suitable amount of (R)-ASME to confirm its activity on HuD, we optimized the extraction procedure. Together with ASME, another related metabolite, germichrysone, was isolated. Both ASME and germichrysone underwent biological investigation, but only ASME confirmed its ability to bind HuD. Given the multifactorial nature of neurodegenerative diseases, we decided to investigate ASME as a proteasome activator, being molecules endowed with this kind of activity potentially able to counteract aggregations of dysregulated proteins. ASME was able to activate the considered target both in enzymatic and cellular assays. Therefore, ASME may be considered a promising hit in the fight against neurodegenerative diseases.

New Insights for Polyphenolic Compounds as Naturally Inspired Proteasome Inhibitors.

Polyphenols, an important class of natural products, are widely distributed in plant-based foods. These compounds are endowed with several biological activities and exert protective effects in various physiopathological contexts, including cancer. We herein investigated novel potential mechanisms of action of polyphenols, focusing on the proteasome, which has emerged as an attractive therapeutic target in cancers such as multiple myeloma. We carried out a structure-based virtual screening study using the DrugBank database as a repository of FDA-approved polyphenolic molecules. Starting from 86 polyphenolic compounds, based on the theoretical binding affinity and the interactions established with key residues of the chymotrypsin binding site, we selected 2 promising candidates, namely Hesperidin and Diosmin. The further assessment of the biologic activity highlighted, for the first time, the capability of these two molecules to inhibit the ß5-proteasome activity and to exert anti-tumor activity against proteasome inhibitor-sensitive or resistant multiple myeloma cell lines.

Molecular and Structural Aspects of Clinically Relevant Mutations of SARS-CoV-2 RNA-Dependent RNA Polymerase in Remdesivir-Treated Patients.

(1) Background: SARS-CoV-2 RNA-dependent RNA polymerase (RdRp) is a promising therapeutic target to fight COVID-19, and many RdRp inhibitors nucleotide/nucleoside analogs, such as remdesivir, have been identified or are in clinical studies. However, the appearance of resistant mutations could reduce their efficacy. In the present work, we structurally evaluated the impact of RdRp mutations found at baseline in 39 patients treated with remdesivir and associated with a different degree of antiviral response in vivo. (2) Methods: A refined bioinformatics approach was applied to assign SARS-CoV-2 clade and lineage, and to define RdRp mutational profiles. In line with such a method, the same mutations were built and analyzed by combining docking and thermodynamics evaluations with both molecular dynamics and representative pharmacophore models. (3) Results: Clinical studies revealed that patients bearing the most prevalent triple mutant P323L+671S+M899I, which was present in 41% of patients, or the more complex mutational profile P323L+G671S+L838I+D738Y+K91E, which was found with a prevalence of 2.6%, showed a delayed reduced response to remdesivir, as confirmed by the increase in SARS-CoV-2 viral load and by a reduced theoretical binding affinity versus RdRp (ΔGbindWT = -122.70 kcal/mol; ΔGbindP323L+671S+M899I = -84.78 kcal/mol; ΔGbindP323L+G671S+L838I+D738Y+K91E = -96.74 kcal/mol). Combined computational approaches helped to rationalize such clinical observations, offering a mechanistic understanding of the allosteric effects of mutants on the global motions of the viral RNA synthesis machine and in the changes of the interactions patterns of remdesivir during its binding.

Synthesis, Computational Insights, and Evaluation of Novel Sigma Receptors Ligands.

The development of diazabicyclo[4.3.0]nonane and 2,7-diazaspiro[3.5]nonane derivatives as sigma receptors (SRs) ligands is reported. The compounds were evaluated in S1R and S2R binding assays, and modeling studies were carried out to analyze the binding mode. The most notable compounds, 4b (AD186, KiS1R = 2.7 nM, KiS2R = 27 nM), 5b (AB21, KiS1R = 13 nM, KiS2R = 102 nM), and 8f (AB10, KiS1R = 10 nM, KiS2R = 165 nM), have been screened for analgesic effects in vivo, and their functional profile was determined through in vivo and in vitro models. Compounds 5b and 8f reached the maximum antiallodynic effect at 20 mg/kg. The selective S1R agonist PRE-084 completely reversed their action, indicating that the effects are entirely dependent on the S1R antagonism. Conversely, compound 4b sharing the 2,7-diazaspiro[3.5]nonane core as 5b was completely devoid of antiallodynic effect. Interestingly, compound 4b fully reversed the antiallodynic effect of BD-1063, indicating that 4b induces an S1R agonistic in vivo effect. The functional profiles were confirmed by the phenytoin assay. Our study might establish the importance of 2,7-diazaspiro[3.5]nonane core for the development of S1R compounds with specific agonist or antagonist profile and the role of the diazabicyclo[4.3.0]nonane in the development of novel SR ligands.

Identification of HuR-RNA Interfering Compounds by Dynamic Combinatorial Chemistry and Fluorescence Polarization.

The RNA binding protein HuR regulates the post-transcriptional process of different oncogenes and tumor suppressor genes, and its dysregulation is linked with cancer. Thus, modulating the complex HuR-RNA represents a promising anticancer strategy. To search for novel HuR ligands able to interfere with the HuR-RNA complex, the protein-templated dynamic combinatorial chemistry (pt-DCC) method was utilized. The recombinant RRM1+2 protein construct, which contains essential domains for ligand-HuR binding and exhibits enhanced solubility and stability compared to the native protein, was used for pt-DCC. Seven acylhydrazones with over 80% amplification were identified. The binding of the fragments to HuR extracted from DCC was validated using STD-NMR, and molecular modeling studies revealed the ability of the compounds to bind HuR at the mRNA binding pocket. Notably, three compounds effectively interfered with HuR-RNA binding in fluorescence polarization studies, suggesting their potential as foundational compounds for developing anticancer HuR-RNA interfering agents.

Discovery of AD258 as a Sigma Receptor Ligand with Potent Antiallodynic Activity.

The design and synthesis of a series of 2,7-diazaspiro[4.4]nonane derivatives as potent sigma receptor (SR) ligands, associated with analgesic activity, are the focus of this work. In this study, affinities at S1R and S2R were measured, and molecular modeling studies were performed to investigate the binding pose characteristics. The most promising compounds were subjected to in vitro toxicity testing and subsequently screened for in vivo analgesic properties. Compound 9d (AD258) exhibited negligible in vitro cellular toxicity and a high binding affinity to both SRs (KiS1R = 3.5 nM, KiS2R = 2.6 nM), but not for other pain-related targets, and exerted high potency in a model of capsaicin-induced allodynia, reaching the maximum antiallodynic effect at very low doses (0.6-1.25 mg/kg). Functional activity experiments showed that S1R antagonism is needed for the effects of 9d and that it did not induce motor impairment. In addition, 9d exhibited a favorable pharmacokinetic profile.

In Silico-Guided Rational Drug Design and Synthesis of Novel 4-(Thiophen-2-yl)butanamides as Potent and Selective TRPV1 Agonists.

We describe an in silico-guided rational drug design and the synthesis of the suggested ligands, aimed at improving the TRPV1-ligand binding properties and the potency of N-(4-hydroxy-3-methoxybenzyl)-4-(thiophen-2-yl) butanamide I, a previously identified TRPV1 agonist. The docking experiments followed by molecular dynamics simulations and thermodynamic analysis led the drug design toward both the introduction of a lipophilic iodine and a flat pyridine/benzene at position 5 of the thiophene nucleus. Most of the synthesized compounds showed high TRPV1 efficacy and potency as well as selectivity. The molecular modeling analysis highlighted crucial hydrophobic interactions between Leu547 and the iodo-thiophene nucleus, as in amide 2a, or between Phe543 and the pyridinyl moiety, as in 3a. In the biological evaluation, both compounds showed protective properties against oxidative stress-induced ROS formation in human keratinocytes. Additionally, while 2a showed neuroprotective effects in both neurons and rat brain slices, 3a exhibited potent antinociceptive effect in vivo..

Update on SARS-CoV-2 Omicron Variant of Concern and Its Peculiar Mutational Profile.

The process of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genetic diversification is still ongoing and has very recently led to the emergence of a new variant of concern (VOC), defined as Omicron or B.1.1.529. Omicron VOC is the most divergent variant identified so far and has generated immediate concern for its potential capability to increase SARS-CoV-2 transmissibility and, more worryingly, to escape therapeutic and vaccine-induced antibodies. Nevertheless, a clear definition of the Omicron VOC mutational spectrum is still missing. Herein, we provide a comprehensive definition and functional characterization (in terms of infectivity and/or antigenicity) of mutations characterizing the Omicron VOC. In particular, 887,475 SARS-CoV-2 Omicron VOC whole-genome sequences were retrieved from the GISAID database and used to precisely define its specific patterns of mutations across the different viral proteins. In addition, the functional characterization of Omicron VOC spike mutations was finely discussed according to published manuscripts. Lastly, residues characterizing the Omicron VOC and the previous four VOCs (Alpha, Beta, Gamma, and Delta) were mapped on the three-dimensional structure of the SARS-CoV-2 spike protein to assess their localization in the different spike domains. Overall, our study will assist with deciphering the Omicron VOC mutational profile and will shed more light on its clinical implications. This is critical considering that Omicron VOC is currently the predominant variant worldwide. IMPORTANCE The Omicron variant of concern (VOC) has a peculiar spectrum of mutations characterized by the acquisition of mutations or deletions rarely detected in previously identified variants, particularly in the spike glycoprotein. Such mutations, mostly residing in the receptor-binding domain, could play a pivotal role in enhancing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infectivity (by increasing binding affinity for ACE2), jeopardizing spike recognition by therapeutic and vaccine-induced antibodies and causing diagnostic assay failure. To our knowledge, this is one of the first exhaustive descriptions of newly emerged mutations underlying the Omicron VOC and its biological and clinical implications.

SARS-CoV-2 Variants and Their Relevant Mutational Profiles: Update Summer 2021.

Since the beginning of the coronavirus disease 2019 (COVID-19) pandemic caused by it, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been undergoing a genetic diversification leading to the emergence of new variants. Nevertheless, a clear definition of the genetic signatures underlying the circulating variants is still missing. Here, we provide a comprehensive insight into mutational profiles characterizing each SARS-CoV-2 variant, focusing on spike mutations known to modulate viral infectivity and/or antigenicity. We focused on variants and on specific relevant mutations reported by GISAID, Nextstrain, Outbreak.info, Pango, and Stanford database websites that were associated with any clinical/diagnostic impact, according to published manuscripts. Furthermore, 1,223,338 full-length high-quality SARS-CoV-2 genome sequences were retrieved from GISAID and used to accurately define the specific mutational patterns in each variant. Finally, mutations were mapped on the three-dimensional structure of the SARS-CoV-2 spike protein to assess their localization in the different spike domains. Overall, this review sheds light and assists in defining the genetic signatures characterizing the currently circulating variants and their clinical relevance. IMPORTANCE Since the emergence of SARS-CoV-2, several recurrent mutations, particularly in the spike protein, arose during human-to-human transmission or spillover events between humans and animals, generating distinct worrisome variants of concern (VOCs) or of interest (VOIs), designated as such due to their clinical and diagnostic impacts. Characterizing these variants and their related mutations is important in tracking SAR-CoV-2 evolution and understanding the efficacy of vaccines and therapeutics based on monoclonal antibodies, convalescent-phase sera, and direct antivirals. Our study provides a comprehensive survey of the mutational profiles characterizing the important SARS-CoV-2 variants, focusing on spike mutations and highlighting other protein mutations.