Drug Repurposing to Identify Nilotinib as a Potential SARS-CoV-2 Main Protease Inhibitor: Insights from a Computational and In Vitro Study

Current perspectives and trend of computer-aided drug design: a review and bibliometric analysis

AIM

Computer-aided drug design (CADD) is a drug design technique for computing ligand-receptor interactions and is involved in various stages of drug development. To better grasp the frontiers and hotspots of CADD, we conducted a review analysis through bibliometrics.

METHODS

A systematic review of studies published between 2000 and 20 July 2023 was conducted following the PRISMA guidelines. Literature on CADD was selected from the Web of Science Core Collection. General information, publications, output trends, countries/regions, institutions, journals, keywords, and influential authors were visually analyzed using software such as Excel, VOSviewer, RStudio, and CiteSpace.

RESULTS

A total of 2031 publications were included. These publications primarily originated from 99 countries or regions led by the U.S. and China. Among the contributors, MacKerell AD had the highest number of articles and the greatest influence. The Journal of Medicinal Chemistry was the most cited journal, whereas the Journal of Chemical Information and Modeling had the highest number of publications.

CONCLUSIONS

Influential authors in the field were identified. Current research shows active collaboration between countries, institutions, and companies. CADD technologies such as homology modeling, pharmacophore modeling, quantitative conformational relationships, molecular docking, molecular dynamics simulation, binding free energy prediction, and high-throughput virtual screening can effectively improve the efficiency of new drug discovery. Artificial intelligence-assisted drug design and screening based on CADD represent key topics that will influence future development. Furthermore, this paper will be helpful in better understanding the frontiers and hotspots of CADD.

SARS-CoV-2 Omicron BA.5.2-infection and COVID-19 in persons with chronic myeloid leukaemia

OBJECTIVE

A SARS-CoV-2 Omicron (BA.5.2) epidemic began in China in December, 2022 following stopping the zero COVID policy.

METHODS

We studied features of the epidemic in 1,121 persons with chronic myeloid leukaemia (CML).

RESULTS

1103 (98%) were in chronic, 10 in accelerated and 8 in acute phases. 834 (74%) became infected almost all of whom met criteria for COVID-19. The most common symptoms were fever (91%), cough (90%) and fatigue (82%). 42 infected persons were asymptomatic. Most people quarantined at home and self-medicated. 22 were hospitalized for COVID-19. At admission 5 had mild, 14, moderate and 3, severe/critical disease according to World Health Organization (WHO) criteria. 5 received respiratory assistance, 3 were admitted to the intensive care unit (ICU) and 1 in accelerated phase died from COVID-19. Co-variates associated with a risk of COVID-19 in SARS-CoV-2-infected subjects include age ≥ 65 years, higher education level and imatinib therapy.

CONCLUSION

In conclusion, most SARS-CoV-2 Omicron BA.5.2 infections in persons with CML resulted in COVID-19 most of which cases are mild with only 1 death.

Repurposing Navitoclax to block SARS-CoV-2 fusion and entry by targeting heptapeptide repeat sequence 1 in S2 protein

Along with the long pandemic of COVID-19 caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has come the dilemma of emerging viral variants of concern (VOC), particularly Omicron and its subvariants, able to deftly escape immune surveillance and the otherwise protective effect of current vaccines and antibody drugs. We previously identified a peptide-based pan-CoV fusion inhibitor, termed as EK1, able to bind the HR1 region in viral spike (S) protein S2 subunit. This effectively blocked formation of the six-helix bundle (6-HB) fusion core and, thus, showed efficacy against all human coronaviruses (HCoVs). EK1 is now in phase 3 clinical trials. However, the peptide drug generally lacks oral availability. Therefore, we herein performed a structure-based virtual screening of the libraries of biologically active molecules and identified nine candidate compounds. One is Navitoclax, an orally active anticancer drug by inhibition of Bcl-2. Like EK1 peptide, it could bind HR1 and block 6-HB formation, efficiently inhibiting fusion and infection of all SARS-CoV-2 variants tested, as well as SARS-CoV and MERS-CoV, with IC50 values ranging from 0.5 to 3.7 μM. These findings suggest that Navitoclax is a promising repurposed drug candidate for development as a safe and orally available broad-spectrum antiviral drug to combat the current SARS-CoV-2 and its variants, as well as other HCoVs.

Identification of a Putative SARS-CoV-2 Main Protease Inhibitor through In Silico Screening of Self-Designed Molecular Library

There have been outbreaks of SARS-CoV-2 around the world for over three years, and its variants continue to evolve. This has become a major global health threat. The main protease (M^pro, also called 3CL^pro) plays a key role in viral replication and proliferation, making it an attractive drug target. Here, we have identified a novel potential inhibitor of M^pro, by applying the virtual screening of hundreds of nilotinib-structure-like compounds that we designed and synthesized. The screened compounds were assessed using SP docking, XP docking, MM-GBSA analysis, IFD docking, MD simulation, ADME/T prediction, and then an enzymatic assay in vitro. We finally identified the compound V291 as a potential SARS-CoV-2 M^pro inhibitor, with a high docking affinity and enzyme inhibitory activity. Moreover, the docking results indicate that His41 is a favorable amino acid for pi-pi interactions, while Glu166 can participate in salt-bridge formation with the protonated primary or secondary amines in the screened molecules. Thus, the compounds reported here are capable of engaging the key amino acids His41 and Glu166 in ligand-receptor interactions. A pharmacophore analysis further validates this assertion.

Montelukast and Telmisartan as Inhibitors of SARS-CoV-2 Omicron Variant

Earlier studies with montelukast (M) and telmisartan (T) have revealed their potential antiviral properties against SARS-CoV-2 wild-type (WT) but have not assessed their efficacy against emerging Variants of Concern (VOCs) such as Omicron. Our research fills this gap by investigating these drugs' impact on VOCs, a topic that current scientific literature has largely overlooked. We employed computational methodologies, including molecular mechanics and machine learning tools, to identify drugs that could potentially disrupt the SARS-CoV-2 spike RBD-ACE2 protein interaction. This led to the identification of two FDA-approved small molecule drugs, M and T, conventionally used for treating asthma and hypertension, respectively. Our study presents an additional potential use for these drugs as antivirals. Our results show that both M and T can inhibit not only the WT SARS-CoV-2 but also, in the case of M, the Omicron variant, without reaching cytotoxic concentrations. This novel finding fills an existing gap in the literature and introduces the possibility of repurposing these drugs for SARS-CoV-2 VOCs, an essential step in responding to the evolving global pandemic.

Discovery of PLpro and Mpro Inhibitors for SARS-CoV-2

There are very few small-molecule antivirals for SARS-CoV-2 that are either currently approved (or emergency authorized) in the US or globally, including remdesivir, molnupiravir, and paxlovid. The increasing number of SARS-CoV-2 variants that have appeared since the outbreak began over three years ago raises the need for continual development of updated vaccines and orally available antivirals in order to fully protect or treat the population. The viral main protease (Mpro) and the papain-like protease (PLpro) are key for viral replication; therefore, they represent valuable targets for antiviral therapy. We herein describe an in vitro screen performed using the 2560 compounds from the Microsource Spectrum library against Mpro and PLpro in an attempt to identify additional small-molecule hits that could be repurposed for SARS-CoV-2. We subsequently identified 2 hits for Mpro and 8 hits for PLpro. One of these hits was the quaternary ammonium compound cetylpyridinium chloride with dual activity (IC50 = 2.72 ± 0.09 μM for PLpro and IC50 = 7.25 ± 0.15 μM for Mpro). A second inhibitor of PLpro was the selective estrogen receptor modulator raloxifene (IC50 = 3.28 ± 0.29 μM for PLpro and IC50 = 42.8 ± 6.7 μM for Mpro). We additionally tested several kinase inhibitors and identified olmutinib (IC50 = 0.54 ± 0.04 μM), bosutinib (IC50 = 4.23 ± 0.28 μM), crizotinib (IC50 = 3.81 ± 0.04 μM), and dacominitinib (IC50 = IC50 3.33 ± 0.06 μM) as PLpro inhibitors for the first time. In some cases, these molecules have also been tested by others for antiviral activity for this virus, or we have used Calu-3 cells infected with SARS-CoV-2. The results suggest that approved drugs can be identified with promising activity against these proteases, and in several cases we or others have validated their antiviral activity. The additional identification of known kinase inhibitors as molecules targeting PLpro may provide new repurposing opportunities or starting points for chemical optimization.

Tetrel bonds involving a CF3 group participate in protein-drug recognition: a combined crystallographic and computational study

In this study, the ability of CF₃ groups to bind to the electron-rich side chains and backbone groups of proteins has been investigated by combining a Protein Data Bank (PDB) survey and ab initio quantum mechanics calculations. More precisely, an inspection of the PDB involving organic ligands containing a CF₃ group and electron-rich atoms (A = N, O and S) in the vicinity revealed 419 X-ray structures exhibiting CF₃⋯A tetrel bonds (TtBs). In a posterior stage, those hits that exhibited the most relevant features in terms of directionality and intermolecular distance were selected for theoretical calculations at the RI-MP2/def2-TZVPD level of theory. Also, Hammett's regression plots of several TtB complexes involving meta- and para-substituted benzene derivatives were computed to shed light on the substituent effects. Moreover, the TtBs were characterized through several state-of-the-art computational techniques, such as the Quantum Theory of Atoms in Molecules (QTAIM) and Noncovalent Interactions plot (NCIplot) methodologies. We believe that the results gathered from our study will be useful for rational drug design and biological communities as well as for further expanding the role of this interaction to biomedical applications.

Molecular Modeling of Viral Type I Fusion Proteins: Inhibitors of Influenza Virus Hemagglutinin and the Spike Protein of Coronavirus

The fusion of viral and cell membranes is one of the basic processes in the life cycles of viruses. A number of enveloped viruses confer fusion of the viral envelope and the cell membrane using surface viral fusion proteins. Their conformational rearrangements lead to the unification of lipid bilayers of cell membranes and viral envelopes and the formation of fusion pores through which the viral genome enters the cytoplasm of the cell. A deep understanding of all the stages of conformational transitions preceding the fusion of viral and cell membranes is necessary for the development of specific inhibitors of viral reproduction. This review systematizes knowledge about the results of molecular modeling aimed at finding and explaining the mechanisms of antiviral activity of entry inhibitors. The first section of this review describes types of viral fusion proteins and is followed by a comparison of the structural features of class I fusion proteins, namely influenza virus hemagglutinin and the S-protein of the human coronavirus.

Bioinformatics-based investigation on the genetic influence between SARS-CoV-2 infections and idiopathic pulmonary fibrosis (IPF) diseases, and drug repurposing

Some recent studies showed that severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections and idiopathic pulmonary fibrosis (IPF) disease might stimulate each other through the shared genes. Therefore, in this study, an attempt was made to explore common genomic biomarkers for SARS-CoV-2 infections and IPF disease highlighting their functions, pathways, regulators and associated drug molecules. At first, we identified 32 statistically significant common differentially expressed genes (cDEGs) between disease (SARS-CoV-2 and IPF) and control samples of RNA-Seq profiles by using a statistical r-package (edgeR). Then we detected 10 cDEGs (CXCR4, TNFAIP3, VCAM1, NLRP3, TNFAIP6, SELE, MX2, IRF4, UBD and CH25H) out of 32 as the common hub genes (cHubGs) by the protein-protein interaction (PPI) network analysis. The cHubGs regulatory network analysis detected few key TFs-proteins and miRNAs as the transcriptional and post-transcriptional regulators of cHubGs. The cDEGs-set enrichment analysis identified some crucial SARS-CoV-2 and IPF causing common molecular mechanisms including biological processes, molecular functions, cellular components and signaling pathways. Then, we suggested the cHubGs-guided top-ranked 10 candidate drug molecules (Tegobuvir, Nilotinib, Digoxin, Proscillaridin, Simeprevir, Sorafenib, Torin 2, Rapamycin, Vancomycin and Hesperidin) for the treatment against SARS-CoV-2 infections with IFP diseases as comorbidity. Finally, we investigated the resistance performance of our proposed drug molecules compare to the already published molecules, against the state-of-the-art alternatives publicly available top-ranked independent receptors by molecular docking analysis. Molecular docking results suggested that our proposed drug molecules would be more effective compare to the already published drug molecules. Thus, the findings of this study might be played a vital role for diagnosis and therapies of SARS-CoV-2 infections with IPF disease as comorbidity risk.

Identification of host genomic biomarkers from multiple transcriptomics datasets for diagnosis and therapies of SARS-CoV-2 infections

The pandemic of COVID-19 is a severe threat to human life and the global economy. Despite the success of vaccination efforts in reducing the spread of the virus, the situation remains largely uncontrolled due to the random mutation in the RNA sequence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which demands different variants of effective drugs. Disease-causing gene-mediated proteins are usually used as receptors to explore effective drug molecules. In this study, we analyzed two different RNA-Seq and one microarray gene expression profile datasets by integrating EdgeR, LIMMA, weighted gene co-expression network and robust rank aggregation approaches, which revealed SARS-CoV-2 infection causing eight hub-genes (HubGs) including HubGs; REL, AURKA, AURKB, FBXL3, OAS1, STAT4, MMP2 and IL6 as the host genomic biomarkers. Gene Ontology and pathway enrichment analyses of HubGs significantly enriched some crucial biological processes, molecular functions, cellular components and signaling pathways that are associated with the mechanisms of SARS-CoV-2 infections. Regulatory network analysis identified top-ranked 5 TFs (SRF, PBX1, MEIS1, ESR1 and MYC) and 5 miRNAs (hsa-miR-106b-5p, hsa-miR-20b-5p, hsa-miR-93-5p, hsa-miR-106a-5p and hsa-miR-20a-5p) as the key transcriptional and post-transcriptional regulators of HubGs. Then, we conducted a molecular docking analysis to determine potential drug candidates that could interact with HubGs-mediated receptors. This analysis resulted in the identification of top-ranked ten drug agents, including Nilotinib, Tegobuvir, Digoxin, Proscillaridin, Olysio, Simeprevir, Hesperidin, Oleanolic Acid, Naltrindole and Danoprevir. Finally, we investigated the binding stability of the top-ranked three drug molecules Nilotinib, Tegobuvir and Proscillaridin with the three top-ranked proposed receptors (AURKA, AURKB, OAS1) by using 100 ns MD-based MM-PBSA simulations and observed their stable performance. Therefore, the findings of this study might be useful resources for diagnosis and therapies of SARS-CoV-2 infections.

Gas6/TAM Axis Involvement in Modulating Inflammation and Fibrosis in COVID-19 Patients

Gas6 (growth arrest-specific gene 6) is a widely expressed vitamin K-dependent protein that is involved in many biological processes such as homeostatic regulation, inflammation and repair/fibrotic processes. It is known that it is the main ligand of TAMs, a tyrosine kinase receptor family of three members, namely MerTK, Tyro-3 and Axl, for which it displays the highest affinity. Gas6/TAM axis activation is known to be involved in modulating inflammatory responses as well as fibrotic evolution in many different pathological conditions. Due to the rapidly evolving COVID-19 pandemic, this review will focus on Gas6/TAM axis activation in SARS-CoV-2 infection, where de-regulated inflammatory responses and fibrosis represent a relevant feature of severe disease manifestation. Furthermore, this review will highlight the most recent scientific evidence supporting an unsuspected role of Axl as a SARS-CoV-2 infection driver, and the potential therapeutic advantages of the use of existing Axl inhibitors in COVID-19 management. From a physiological point of view, the Gas6/TAM axis plays a dual role, fostering the tissue repair processes or leading to organ damage and loss of function, depending on the prevalence of its anti-inflammatory or profibrotic properties. This review makes a strong case for further research focusing on the Gas6/TAM axis as a pharmacological target to manage different disease conditions, such as chronic fibrosis or COVID-19.

Optimization of potential non-covalent inhibitors for the SARS-CoV-2 main protease inspected by a descriptor of the subpocket occupancy

The main protease is regarded as an essential drug target for treating Coronavirus Disease 2019. In the present study, 13 marketed drugs were investigated to explore the possible binding mechanism, utilizing molecular docking, molecular dynamics simulation, and MM-PB(GB)SA binding energy calculations. Our results suggest that fusidic acid, polydatin, SEN-1269, AZD6482, and UNC-2327 have high binding affinities of more than 23 kcal mol^-1. A descriptor was defined for the energetic occupancy of the subpocket, and it was found that S4 had a low occupancy of less than 10% on average. The molecular optimization of ADZ6482 via reinforcement learning algorithms was carried out to screen out three lead compounds, in which slight structural changes give more considerable binding energies and an occupancy of the S4 subpocket of up to 43%. The energetic occupancy could be a useful descriptor for evaluating the local binding affinity for drug design.

Small molecules in the treatment of COVID-19

The outbreak of COVID-19 has become a global crisis, and brought severe disruptions to societies and economies. Until now, effective therapeutics against COVID-19 are in high demand. Along with our improved understanding of the structure, function, and pathogenic process of SARS-CoV-2, many small molecules with potential anti-COVID-19 effects have been developed. So far, several antiviral strategies were explored. Besides directly inhibition of viral proteins such as RdRp and M^pro, interference of host enzymes including ACE2 and proteases, and blocking relevant immunoregulatory pathways represented by JAK/STAT, BTK, NF-κB, and NLRP3 pathways, are regarded feasible in drug development. The development of small molecules to treat COVID-19 has been achieved by several strategies, including computer-aided lead compound design and screening, natural product discovery, drug repurposing, and combination therapy. Several small molecules representative by remdesivir and paxlovid have been proved or authorized emergency use in many countries. And many candidates have entered clinical-trial stage. Nevertheless, due to the epidemiological features and variability issues of SARS-CoV-2, it is necessary to continue exploring novel strategies against COVID-19. This review discusses the current findings in the development of small molecules for COVID-19 treatment. Moreover, their detailed mechanism of action, chemical structures, and preclinical and clinical efficacies are discussed.

Optimization of the Prodrug Moiety of Remdesivir to Improve Lung Exposure/Selectivity and Enhance Anti-SARS-CoV-2 Activity

COVID-19 patients with severe symptoms still lack antiviral treatment options. Although remdesivir is the only FDA-approved drug for those patients, its efficacy is limited by premature hydrolysis to nucleoside (NUC), low accumulation in the disease-targeted tissue (lungs), and low antiviral potency. In this study, we synthesized a new series of remdesivir analogues by modifying the ProTide moiety. In comparison with remdesivir, the lead compound MMT5-14 showed 2- to 7-fold higher antiviral activity in four variants of SARS-CoV-2. By reducing premature hydrolysis in hamsters, MMT5-14 increased the prodrug concentration by 200- to 300-fold in the plasma and lungs but also enhanced lung accumulation of the active metabolite triphosphate nucleosides (NTP) by 5-fold. Compared to remdesivir, MMT5-14 also increased the intracellular uptake and activation in lung epithelial cells by 4- to 25-fold. These data suggest that MMT5-14 could be a potential antiviral drug to treat COVID-19 patients with severe symptoms.

Designing Dual Inhibitors of Autotaxin-LPAR GPCR Axis

The ATX-LPA-LPAR1 signaling pathway plays a universal role in stimulating diverse cellular responses, including cell proliferation, migration, survival, and invasion in almost every cell type. The ATX-LPAR1 axis is linked to several metabolic and inflammatory diseases including cancer, fibrosis, and rheumatoid arthritis. Numerous selective ATX or LPAR1 inhibitors have been developed and so far, their clinical efficacy has only been evaluated in idiopathic pulmonary fibrosis. None of the ATX and LPAR1 inhibitors have advanced to clinical trials for cancer and rheumatoid arthritis. Nonetheless, several research groups, including ours, have shown considerable benefit of simultaneous ATX and LPAR1 inhibition through combination therapy. Recent research suggests that dual-targeting therapies are superior to combination therapies that use two selective inhibitors. However, limited reports are available on ATX-LPAR1 dual inhibitors, potentially due to co-expression of multiple different LPARs with close structural similarities at the same target. In this review, we discuss rational design and future directions of dual ATX-LPAR1 inhibitors.

A Review of In Silico Research, SARS-CoV-2, and Neurodegeneration: Focus on Papain-Like Protease

Since the appearance of SARS-CoV-2 and the COVID-19 pandemic, the search for new approaches to treat this disease took place in the scientific community. The in silico approach has gained importance at this moment, once the methodologies used in this kind of study allow for the identification of specific protein–ligand interactions, which may serve as a filter step for molecules that can act as specific inhibitors. In addition, it is a low-cost and high-speed technology. Molecular docking has been widely used to find potential viral protein inhibitors for structural and non-structural proteins of the SARS-CoV-2, aiming to block the infection and the virus multiplication. The papain-like protease (PLpro) participates in the proteolytic processing of SARS-CoV-2 and composes one of the main targets studied for pharmacological intervention by in silico methodologies. Based on that, we performed a systematic review about PLpro inhibitors from the perspective of in silico research, including possible therapeutic molecules in relation to this viral protein. The neurological problems triggered by COVID-19 were also briefly discussed, especially relative to the similarities of neuroinflammation present in Alzheimer’s disease. In this context, we focused on two molecules, curcumin and glycyrrhizinic acid, given their PLpro inhibitory actions and neuroprotective properties and potential therapeutic effects on COVID-19.

In silico exploration of disulfide derivatives of Ferula foetida oleo-gum (Covexir®) as promising therapeutics against SARS-CoV-2

Although vaccines have been significantly successful against coronavirus, due to the high rate of the Omicron variant spread many researchers are trying to find efficient drugs against COVID-19. Herein, we conducted a computational study to investigate the binding mechanism of four potential inhibitors (including disulfide derivatives isolated from Ferula foetida) to SARS-CoV-2 main protease. Our findings revealed that the disulfides mainly interacted with HIS41, MET49, CYS145, HIS64, MET165, and GLN189 residues of SARS-CoV-2 main protease. The binding free energy decomposition results also showed that the van der Waals (vdW) energy plays the main role in the interaction of HIS41, MET49, CYS145, HIS64, MET165, and GLN189 residues with the inhibitors. Furthermore, it is found that the Z-isomer derivatives have a stronger interaction with SARS-CoV-2, and the strongest interaction belongs to the (Z)-1-(1-(methylthio)propyl)-2-(prop-1-enyl)disulfane (ΔG = -18.672 kcal/mol). The quantum mechanical calculations demonstrated that the second-order perturbation stabilization energy and the electron density values for MET49-ligand interactions are higher than the other residue-ligand complexes. This finding confirms the stronger interaction of this residue with the ligands.

Antiviral drug discovery by targeting the SARS-CoV-2 polyprotein processing by inhibition of the main protease

The spread of SARS-CoV-2, the causative agent for COVID-19, has led to a global and deadly pandemic. To date, few drugs have been approved for treating SARS-CoV-2 infections. In this study, a structure-based approach was adopted using the SARS-CoV-2 main protease (M^pro) and a carefully selected dataset of 37,060 compounds comprising M^pro and antiviral protein-specific libraries. The compounds passed two-step docking filtration, starting with standard precision (SP) followed by extra precision (XP) runs. Fourteen compounds with the highest XP docking scores were examined by 20 ns molecular dynamics simulations (MDs). Based on backbone route mean square deviations (RMSD) and molecular mechanics/generalized Born surface area (MM/GBSA) binding energy, four drugs were selected for comprehensive MDs analysis at 100 ns. Results indicated that birinapant, atazanavir, and ritonavir potently bound and stabilized SARS-CoV-2 M^pro structure. Binding energies higher than -102 kcal/mol, RMSD values <0.22 nm, formation of several hydrogen bonds with M^pro, favourable electrostatic contributions, and low radii of gyration were among the estimated factors contributing to the strength of the binding of these three compounds with M^pro. The top two compounds, atazanavir and birinapant, were tested for their ability to prevent SARS-CoV-2 plaque formation. At 10 µM of birinapant concentration, antiviral tests against SARS-CoV-2 demonstrated a 37% reduction of virus multiplication. Antiviral assays demonstrated that birinapant has high anti-SARS-CoV-2 activity in the low micromolar range, with an IC50 value of 18 ± 3.6 µM. Therefore, birinapant is a candidate for further investigation to determine whether it is a feasible therapy option.

A Computer-Aided Approach for the Discovery of D-Peptides as Inhibitors of SARS-CoV-2 Main Protease

The SARS-CoV-2 main protease, also known as 3-chymotrypsin-like protease (3CLpro), is a cysteine protease responsible for the cleavage of viral polyproteins pp1a and pp1ab, at least, at eleven conserved sites, which leads to the formation of mature nonstructural proteins essential for the replication of the virus. Due to its essential role, numerous studies have been conducted so far, which have confirmed 3CLpro as an attractive drug target to combat Covid-19 and have reported a vast number of inhibitors and their co-crystal structures. Despite all the ongoing efforts, D-peptides, which possess key advantages over L-peptides as therapeutic agents, have not been explored as potential drug candidates against 3CLpro. The current work fills this gap by reporting an in silico approach for the discovery of D-peptides capable of inhibiting 3CLpro that involves structure-based virtual screening (SBVS) of an in-house library of D-tripeptides and D-tetrapeptides into the protease active site and subsequent rescoring steps, including Molecular Mechanics Generalized-Born Surface Area (MM-GBSA) free energy calculations and molecular dynamics (MD) simulations. In vitro enzymatic assays conducted for the four top-scoring D-tetrapeptides at 20 μM showed that all of them caused 55–85% inhibition of 3CLpro activity, thus highlighting the suitability of the devised approach. Overall, our results present a promising computational strategy to identify D-peptides capable of inhibiting 3CLpro, with broader application in problems involving protein inhibition.

Learning through a Pandemic: The Current State of Knowledge on COVID-19 and Cancer

The ongoing COVID-19 pandemic has left patients with current or past history of cancer facing disparate consequences at every stage of the cancer trajectory. This comprehensive review offers a landscape analysis of the current state of the literature on COVID-19 and cancer including the immune response to COVID-19, risk factors for severe disease, and impact of anticancer therapies. We also review the latest data on treatment of COVID-19 and vaccination safety and efficacy in patients with cancer, as well as impact of the pandemic on cancer care, including the urgent need for rapid evidence generation and real-world study designs.