AI-Driven De Novo Design and Molecular Modeling for Discovery of Small-Molecule Compounds as Potential Drug Candidates Targeting SARS-CoV-2 Main Protease.

Over the past three years, significant progress has been made in the development of novel promising drug candidates against COVID-19. However, SARS-CoV-2 mutations resulting in the emergence of new viral strains that can be resistant to the drugs used currently in the clinic necessitate the development of novel potent and broad therapeutic agents targeting different vulnerable spots of the viral proteins. In this study, two deep learning generative models were developed and used in combination with molecular modeling tools for de novo design of small molecule compounds that can inhibit the catalytic activity of SARS-CoV-2 main protease (Mpro), an enzyme critically important for mediating viral replication and transcription. As a result, the seven best scoring compounds that exhibited low values of binding free energy comparable with those calculated for two potent inhibitors of Mpro, via the same computational protocol, were selected as the most probable inhibitors of the enzyme catalytic site. In light of the data obtained, the identified compounds are assumed to present promising scaffolds for the development of new potent and broad-spectrum drugs inhibiting SARS-CoV-2 Mpro, an attractive therapeutic target for anti-COVID-19 agents.

Why All the Fury over Furin?

Analysis of the SARS-CoV-2 sequence revealed a multibasic furin cleavage site at the S1/S2 boundary of the spike protein distinguishing this virus from SARS-CoV. Furin, the best-characterized member of the mammalian proprotein convertases, is an ubiquitously expressed single pass type 1 transmembrane protein. Cleavage of SARS-CoV-2 spike protein by furin promotes viral entry into lung cells. While furin knockout is embryonically lethal, its knockout in differentiated somatic cells is not, thus furin provides an exciting therapeutic target for viral pathogens including SARS-CoV-2 and bacterial infections. Several peptide-based and small-molecule inhibitors of furin have been recently reported, and select cocrystal structures have been solved, paving the way for further optimization and selection of clinical candidates. This perspective highlights furin structure, substrates, recent inhibitors, and crystal structures with emphasis on furin's role in SARS-CoV-2 infection, where the current data strongly suggest its inhibition as a promising therapeutic intervention for SARS-CoV-2.

Unravelling lead antiviral phytochemicals for the inhibition of SARS-CoV-2 Mpro enzyme through in silico approach.

A new SARS coronavirus (SARS-CoV-2) belonging to the genus Betacoronavirus has caused a pandemic known as COVID-19. Among coronaviruses, the main protease (Mpro) is an essential drug target which, along with papain-like proteases catalyzes the processing of polyproteins translated from viral RNA and recognizes specific cleavage sites. There are no human proteases with similar cleavage specificity and therefore, inhibitors are highly likely to be nontoxic. Therefore, targeting the SARS-CoV-2 Mpro enzyme with small molecules can block viral replication. The present study is aimed at the identification of promising lead molecules for SARS-CoV-2 Mpro enzyme through virtual screening of antiviral compounds from plants. The binding affinity of selected small drug-like molecules to SARS-CoV-2 Mpro, SARS-CoV Mpro and MERS-CoV Mpro were studied using molecular docking. Bonducellpin D was identified as the best lead molecule which shows higher binding affinity (-9.28 kcal/mol) as compared to the control (-8.24 kcal/mol). The molecular binding was stabilized through four hydrogen bonds with Glu166 and Thr190 as well as hydrophobic interactions via eight residues. The SARS-CoV-2 Mpro shows identities of 96.08% and 50.65% to that of SARS-CoV Mpro and MERS-CoV Mpro respectively at the sequence level. At the structural level, the root mean square deviation (RMSD) between SARS-CoV-2 Mpro and SARS-CoV Mpro was found to be 0.517 Å and 0.817 Å between SARS-CoV-2 Mpro and MERS-CoV Mpro. Bonducellpin D exhibited broad-spectrum inhibition potential against SARS-CoV Mpro and MERS-CoV Mpro and therefore is a promising drug candidate, which needs further validations through in vitro and in vivo studies.

Computational pharmacology: New avenues for COVID-19 therapeutics search and better preparedness for future pandemic crises.

The COVID-19 pandemic created an unprecedented global healthcare emergency prompting the exploration of new therapeutic avenues, including drug repurposing. A large number of ongoing studies revealed pervasive issues in clinical research, such as the lack of accessible and organised data. Moreover, current shortcomings in clinical studies highlighted the need for a multi-faceted approach to tackle this health crisis. Thus, we set out to explore and develop new strategies for drug repositioning by employing computational pharmacology, data mining, systems biology, and computational chemistry to advance shared efforts in identifying key targets, affected networks, and potential pharmaceutical intervention options. Our study revealed that formulating pharmacological strategies should rely on both therapeutic targets and their networks. We showed how data mining can reveal regulatory patterns, capture novel targets, alert about side-effects, and help identify new therapeutic avenues. We also highlighted the importance of the miRNA regulatory layer and how this information could be used to monitor disease progression or devise treatment strategies. Importantly, our work bridged the interactome with the chemical compound space to better understand the complex landscape of COVID-19 drugs. Machine and deep learning allowed us to showcase limitations in current chemical libraries for COVID-19 suggesting that both in silico and experimental analyses should be combined to retrieve therapeutically valuable compounds. Based on the gathered data, we strongly advocate for taking this opportunity to establish robust practices for treating today's and future infectious diseases by preparing solid analytical frameworks.

Emerging therapeutic opportunities for integrin inhibitors.

Integrins are cell adhesion and signalling proteins crucial to a wide range of biological functions. Effective marketed treatments have successfully targeted integrins αIIbß3, α4ß7/α4ß1 and αLß2 for cardiovascular diseases, inflammatory bowel disease/multiple sclerosis and dry eye disease, respectively. Yet, clinical development of others, notably within the RGD-binding subfamily of αv integrins, including αvß3, have faced significant challenges in the fields of cancer, ophthalmology and osteoporosis. New inhibitors of the related integrins αvß6 and αvß1 have recently come to the fore and are being investigated clinically for the treatment of fibrotic diseases, including idiopathic pulmonary fibrosis and nonalcoholic steatohepatitis. The design of integrin drugs may now be at a turning point, with opportunities to learn from previous clinical trials, to explore new modalities and to incorporate new findings in pharmacological and structural biology. This Review intertwines research from biological, clinical and medicinal chemistry disciplines to discuss historical and current RGD-binding integrin drug discovery, with an emphasis on small-molecule inhibitors of the αv integrins.

Virtual Combinatorial Chemistry and Pharmacological Screening: A Short Guide to Drug Design.

Traditionally, drug development involved the individual synthesis and biological evaluation of hundreds to thousands of compounds with the intention of highlighting their biological activity, selectivity, and bioavailability, as well as their low toxicity. On average, this process of new drug development involved, in addition to high economic costs, a period of several years before hopefully finding a drug with suitable characteristics to drive its commercialization. Therefore, the chemical synthesis of new compounds became the limiting step in the process of searching for or optimizing leads for new drug development. This need for large chemical libraries led to the birth of high-throughput synthesis methods and combinatorial chemistry. Virtual combinatorial chemistry is based on the same principle as real chemistry-many different compounds can be generated from a few building blocks at once. The difference lies in its speed, as millions of compounds can be produced in a few seconds. On the other hand, many virtual screening methods, such as QSAR (Quantitative Sturcture-Activity Relationship), pharmacophore models, and molecular docking, have been developed to study these libraries. These models allow for the selection of molecules to be synthesized and tested with a high probability of success. The virtual combinatorial chemistry-virtual screening tandem has become a fundamental tool in the process of searching for and developing a drug, as it allows the process to be accelerated with extraordinary economic savings.

Antiviral Efficacy of Selected Natural Phytochemicals against SARS-CoV-2 Spike Glycoprotein Using Structure-Based Drug Designing.

SARS-CoV-2 is a highly virulent coronavirus that first surfaced in late 2019 and has since created a pandemic of the acute respiratory sickness known as "coronavirus disease 2019" (COVID-19), posing a threat to human health and public safety. S-RBD is a coronaviral protein that is essential for a coronavirus (CoV) to bind and penetrate into host cells. As a result, it has become a popular pharmacological target. The goal of this study was to find potential candidates for anti-coronavirus disease 2019 (COVID-19) drugs by targeting severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) S-RBD with novel bioactive compounds and molecular interaction studies of 15,000 phytochemicals belonging to different flavonoid subgroups. A spike protein crystal structure attached to the ACE2 structure was obtained from the PDB database. A library of 15,000 phytochemicals was made by collecting compounds from different databases, such as the Zinc-database, PubChem-database, and MPD3-database. This library was docked against a receptor binding domain of a spike glycoprotein through the Molecular Operating Environment (MOE). The top drug candidates Phylloflavan, Milk thistle, Ilexin B and Isosilybin B, after virtual screening, were selected on the basis of the least binding score. Phylloflavan ranked as the top compound because of its least binding affinity score of -14.09 kcal/mol. In silico studies showed that all those compounds showed good activity and could be used as an immunological response with no bioavailability issues. Absorption, distribution, metabolism, excretion and a toxicological analysis were conducted through SwissADME. Stability and effectiveness of the docked complexes were elucidated by performing the 100 ns molecular dynamic simulation through the Desmond package.

Artificial Intelligence Technologies for COVID-19 De Novo Drug Design.

The recent covid crisis has provided important lessons for academia and industry regarding digital reorganization. Among the fascinating lessons from these times is the huge potential of data analytics and artificial intelligence. The crisis exponentially accelerated the adoption of analytics and artificial intelligence, and this momentum is predicted to continue into the 2020s and beyond. Drug development is a costly and time-consuming business, and only a minority of approved drugs generate returns exceeding the research and development costs. As a result, there is a huge drive to make drug discovery cheaper and faster. With modern algorithms and hardware, it is not too surprising that the new technologies of artificial intelligence and other computational simulation tools can help drug developers. In only two years of covid research, many novel molecules have been designed/identified using artificial intelligence methods with astonishing results in terms of time and effectiveness. This paper reviews the most significant research on artificial intelligence in de novo drug design for COVID-19 pharmaceutical research.

Ultralarge Virtual Screening Identifies SARS-CoV-2 Main Protease Inhibitors with Broad-Spectrum Activity against Coronaviruses.

Drugs targeting SARS-CoV-2 could have saved millions of lives during the COVID-19 pandemic, and it is now crucial to develop inhibitors of coronavirus replication in preparation for future outbreaks. We explored two virtual screening strategies to find inhibitors of the SARS-CoV-2 main protease in ultralarge chemical libraries. First, structure-based docking was used to screen a diverse library of 235 million virtual compounds against the active site. One hundred top-ranked compounds were tested in binding and enzymatic assays. Second, a fragment discovered by crystallographic screening was optimized guided by docking of millions of elaborated molecules and experimental testing of 93 compounds. Three inhibitors were identified in the first library screen, and five of the selected fragment elaborations showed inhibitory effects. Crystal structures of target-inhibitor complexes confirmed docking predictions and guided hit-to-lead optimization, resulting in a noncovalent main protease inhibitor with nanomolar affinity, a promising in vitro pharmacokinetic profile, and broad-spectrum antiviral effect in infected cells.

Screening of Botanical Drugs against SARS-CoV-2 Entry Reveals Novel Therapeutic Agents to Treat COVID-19.

An escalating pandemic caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has severely impacted global health. There is a severe lack of specific treatment options for diseases caused by SARS-CoV-2. In this study, we used a pseudotype virus (pv) containing the SARS-CoV-2 S glycoprotein to screen a botanical drug library containing 1037 botanical drugs to identify agents that prevent SARS-CoV-2 entry into the cell. Our study identified four hits, including angeloylgomisin O, schisandrin B, procyanidin, and oleanonic acid, as effective SARS-CoV-2 S pv entry inhibitors in the micromolar range. A mechanistic study revealed that these four agents inhibited SARS-CoV-2 S pv entry by blocking spike (S) protein-mediated membrane fusion. Furthermore, angeloylgomisin O and schisandrin B inhibited authentic SARS-CoV-2 with a high selective index (SI; 50% cytotoxic concentration/50% inhibition concentration). Our drug combination studies performed in cellular antiviral assays revealed that angeloylgomisin O has synergistic effects in combination with remdesivir, a drug widely used to treat SARS-CoV-2-mediated infections. We also showed that two hits could inhibit the newly emerged alpha (B.1.1.7) and beta (B.1.351) variants. Our findings collectively indicate that angeloylgomisin O and schisandrin B could inhibit SARS-CoV-2 efficiently, thereby making them potential therapeutic agents to treat the coronavirus disease of 2019.

Discovery of Potential Antiviral Compounds against Hendra Virus by Targeting Its Receptor-Binding Protein (G) Using Computational Approaches.

Hendra virus (HeV) belongs to the paramyxoviridae family of viruses which is associated with the respiratory distress, neurological illness, and potential fatality of the affected individuals. So far, no competitive approved therapeutic substance is available for HeV. For that reason, the current research work was conducted to propose some novel compounds, by adopting a Computer Aided Drug Discovery approach, which could be used to combat HeV. The G attachment Glycoprotein (Ggp) of HeV was selected to achieve the primary objective of this study, as this protein makes the entry of HeV possible in the host cells. Briefly, a library of 6000 antiviral compounds was screened for potential drug-like properties, followed by the molecular docking of short-listed compounds with the Protein Data Bank (PDB) structure of Ggp. Docked complexes of top two hits, having maximum binding affinities with the active sites of Ggp, were further considered for molecular dynamic simulations of 200 ns to elucidate the results of molecular docking analysis. MD simulations and Molecular Mechanics Energies combined with the Generalized Born and Surface Area (MMGBSA) or Poisson-Boltzmann and Surface Area (MMPBSA) revealed that both docked complexes are stable in nature. Furthermore, the same methodology was used between lead compounds and HeV Ggp in complex with its functional receptor in human, Ephrin-B2. Surprisingly, no major differences were found in the results, which demonstrates that our identified compounds can also perform their action even when the Ggp is attached to the Ephrin-B2 ligand. Therefore, in light of all of these results, we strongly suggest that compounds (S)-5-(benzylcarbamoyl)-1-(2-(4-methyl-2-phenylpiperazin-1-yl)-2-oxoethyl)-6-oxo-3,6-dihydropyridin-1-ium-3-ide and 5-(cyclohexylcarbamoyl)-1-(2-((2-(3-fluorophenyl)-2-methylpropyl)amino)-2-oxoethyl)-6-oxo-3,6-dihydropyridin-1-ium-3-ide could be considered as potential therapeutic agents against HeV; however, further in vitro and in vivo experiments are required to validate this study.

Computational Design of Miniproteins as SARS-CoV-2 Therapeutic Inhibitors.

A rational therapeutic strategy is urgently needed for combating SARS-CoV-2 infection. Viral infection initiates when the SARS-CoV-2 receptor-binding domain (RBD) binds to the ACE2 receptor, and thus, inhibiting RBD is a promising therapeutic for blocking viral entry. In this study, the structure of lead antiviral candidate binder (LCB1), which has three alpha-helices (H1, H2, and H3), is used as a template to design and simulate several miniprotein RBD inhibitors. LCB1 undergoes two modifications: structural modification by truncation of the H3 to reduce its size, followed by single and double amino acid substitutions to enhance its binding with RBD. We use molecular dynamics (MD) simulations supported by ab initio density functional theory (DFT) calculations. Complete binding profiles of all miniproteins with RBD have been determined. The MD investigations reveal that the H3 truncation results in a small inhibitor with a -1.5 kcal/mol tighter binding to RBD than original LCB1, while the best miniprotein with higher binding affinity involves D17R or E11V + D17R mutation. DFT calculations provide atomic-scale details on the role of hydrogen bonding and partial charge distribution in stabilizing the minibinder:RBD complex. This study provides insights into general principles for designing potential therapeutics for SARS-CoV-2.

Commercial SARS-CoV-2 Targeted, Protease Inhibitor Focused and Protein-Protein Interaction Inhibitor Focused Molecular Libraries for Virtual Screening and Drug Design.

Since December 2019, the new SARS-CoV-2-related COVID-19 disease has caused a global pandemic and shut down the public life worldwide. Several proteins have emerged as potential therapeutic targets for drug development, and we sought out to review the commercially available and marketed SARS-CoV-2-targeted libraries ready for high-throughput virtual screening (HTVS). We evaluated the SARS-CoV-2-targeted, protease-inhibitor-focused and protein-protein-interaction-inhibitor-focused libraries to gain a better understanding of how these libraries were designed. The most common were ligand- and structure-based approaches, along with various filtering steps, using molecular descriptors. Often, these methods were combined to obtain the final library. We recognized the abundance of targeted libraries offered and complimented by the inclusion of analytical data; however, serious concerns had to be raised. Namely, vendors lack the information on the library design and the references to the primary literature. Few references to active compounds were also provided when using the ligand-based design and usually only protein classes or a general panel of targets were listed, along with a general reference to the methods, such as molecular docking for the structure-based design. No receptor data, docking protocols or even references to the applied molecular docking software (or other HTVS software), and no pharmacophore or filter design details were given. No detailed functional group or chemical space analyses were reported, and no specific orientation of the libraries toward the design of covalent or noncovalent inhibitors could be observed. All libraries contained pan-assay interference compounds (PAINS), rapid elimination of swill compounds (REOS) and aggregators, as well as focused on the drug-like model, with the majority of compounds possessing their molecular mass around 500 g/mol. These facts do not bode well for the use of the reviewed libraries in drug design and lend themselves to commercial drug companies to focus on and improve.

Discovery of Highly Potent Fusion Inhibitors with Potential Pan-Coronavirus Activity That Effectively Inhibit Major COVID-19 Variants of Concern (VOCs) in Pseudovirus-Based Assays.

We report the discovery of several highly potent small molecules with low-nM potency against severe acute respiratory syndrome coronavirus (SARS-CoV; lowest half-maximal inhibitory concentration (IC50: 13 nM), SARS-CoV-2 (IC50: 23 nM), and Middle East respiratory syndrome coronavirus (MERS-CoV; IC50: 76 nM) in pseudovirus-based assays with excellent selectivity index (SI) values (>5000), demonstrating potential pan-coronavirus inhibitory activities. Some compounds showed 100% inhibition against the cytopathic effects (CPE; IC100) of an authentic SARS-CoV-2 (US_WA-1/2020) variant at 1.25 µM. The most active inhibitors also potently inhibited variants of concern (VOCs), including the UK (B.1.1.7) and South African (B.1.351) variants and the Delta variant (B.1.617.2) originally identified in India in pseudovirus-based assay. Surface plasmon resonance (SPR) analysis with one potent inhibitor confirmed that it binds to the prefusion SARS-CoV-2 spike protein trimer. These small-molecule inhibitors prevented virus-mediated cell-cell fusion. The absorption, distribution, metabolism, and excretion (ADME) data for one of the most active inhibitors, NBCoV1, demonstrated drug-like properties. An in vivo pharmacokinetics (PK) study of NBCoV1 in rats demonstrated an excellent half-life (t1/2) of 11.3 h, a mean resident time (MRT) of 14.2 h, and oral bioavailability. We expect these lead inhibitors to facilitate the further development of preclinical and clinical candidates.

Inhibitors of bacterial H2S biogenesis targeting antibiotic resistance and tolerance.

Emergent resistance to all clinical antibiotics calls for the next generation of therapeutics. Here we report an effective antimicrobial strategy targeting the bacterial hydrogen sulfide (H2S)-mediated defense system. We identified cystathionine γ-lyase (CSE) as the primary generator of H2S in two major human pathogens, Staphylococcus aureus and Pseudomonas aeruginosa, and discovered small molecules that inhibit bacterial CSE. These inhibitors potentiate bactericidal antibiotics against both pathogens in vitro and in mouse models of infection. CSE inhibitors also suppress bacterial tolerance, disrupting biofilm formation and substantially reducing the number of persister bacteria that survive antibiotic treatment. Our results establish bacterial H2S as a multifunctional defense factor and CSE as a drug target for versatile antibiotic enhancers.

Screening of Severe Acute Respiratory Syndrome Coronavirus 2 RNA-Dependent RNA Polymerase Inhibitors Using Computational Approach.

The detrimental effect of coronavirus disease 2019 (COVID-19) pandemic has manifested itself as a global crisis. Currently, no specific treatment options are available for COVID-19, so therapeutic interventions to tackle the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection must be urgently established. Therefore, cohesive and multidimensional efforts are required to identify new therapies or investigate the efficacy of small molecules and existing drugs against SARS-CoV-2. Since the RNA-dependent RNA Polymerase (RdRP) of SARS-CoV-2 is a promising therapeutic target, this study addresses the identification of antiviral molecules that can specifically target SARS-CoV-2 RdRP. The computational approach of drug development was used to screen the antiviral molecules from two antiviral libraries (Life Chemicals [LC] and ASINEX) against RdRP. Here, we report six antiviral molecules (F3407-4105, F6523-2250, F6559-0746 from LC and BDG 33693278, BDG 33693315, LAS 34156196 from ASINEX), which show substantial interactions with key amino acid residues of the active site of SARS-CoV-2 RdRP and exhibit higher binding affinity (>7.5 kcalmol-1) than Galidesivir, an Food and Drug Administration-approved inhibitor of the same. Further, molecular dynamics simulation and Molecular Mechanics Poisson-Boltzmann Surface Area results confirmed that identified molecules with RdRP formed higher stable RdRP-inhibitor(s) complex than RdRP-Galidesvir complex. Our findings suggest that these molecules could be potential inhibitors of SARS-CoV-2 RdRP. However, further in vitro and preclinical experiments would be required to validate these potential inhibitors of SARS-CoV-2 protein.

In Silico Exploration of Potential Natural Inhibitors against SARS-Cov-2 nsp10.

In continuation of our previous effort, different in silico selection methods were applied to 310 naturally isolated metabolites that exhibited antiviral potentialities before. The applied selection methods aimed to pick the most relevant inhibitor of SARS-CoV-2 nsp10. At first, a structural similarity study against the co-crystallized ligand, S-Adenosyl Methionine (SAM), of SARS-CoV-2 nonstructural protein (nsp10) (PDB ID: 6W4H) was carried out. The similarity analysis culled 30 candidates. Secondly, a fingerprint study against SAM preferred compounds 44, 48, 85, 102, 105, 182, 220, 221, 282, 284, 285, 301, and 302. The docking studies picked 48, 182, 220, 221, and 284. While the ADMET analysis expected the likeness of the five candidates to be drugs, the toxicity study preferred compounds 48 and 182. Finally, a density-functional theory (DFT) study suggested vidarabine (182) to be the most relevant SARS-Cov-2 nsp10 inhibitor.

Dasabuvir Inhibits Human Norovirus Infection in Human Intestinal Enteroids.

Human noroviruses (HuNoVs) are acute viral gastroenteritis pathogens that affect all age groups, yet no approved vaccines and drugs to treat HuNoV infection are available. In this study, we screened an antiviral compound library to identify compound(s) showing anti-HuNoV activity using a human intestinal enteroid (HIE) culture system in which HuNoVs are able to replicate reproducibly. Dasabuvir (DSB), which has been developed as an anti-hepatitis C virus agent, was found to inhibit HuNoV infection in HIEs at micromolar concentrations. Dasabuvir also inhibited severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and human rotavirus A (RVA) infection in HIEs. To our knowledge, this is the first study to screen an antiviral compound library for HuNoV using HIEs, and we successfully identified dasabuvir as a novel anti-HuNoV inhibitor that warrants further investigation. IMPORTANCE Although there is an urgent need to develop effective antiviral therapy directed against HuNoV infection, compound screening to identify anti-HuNoV drug candidates has not been reported so far. Using a human HIE culture system, our compound screening successfully identified dasabuvir as a novel anti-HuNoV inhibitor. Dasabuvir's inhibitory effect was also demonstrated in the cases of SARS-CoV-2 and RVA infection, highlighting the usefulness of the HIE platform for screening antiviral agents against various viruses that target the intestines.