Docking-based Screening Research Articles

Exploring the Targets of Dengue Virus and Designs of Potential Inhibitors.

Dengue, a mosquito-borne viral disease spread by the dengue virus (DENV), has become one of the most alarming health issues in the global scenario in recent days. The risk of infection by DENV is mostly high in tropical and subtropical areas of the world. The mortality rate of patients affected with DENV is ever-increasing, mainly due to a lack of anti-dengue viral-specific synthetic drug components. Repurposing synthetic drugs has been an effective tool in combating several pathogens, including DENV. However, only the Dengvaxia vaccine has been developed so far to fight against the deadly disease despite the grave situation, mainly because of the limitations of understanding the actual pathogenicity of the disease. To address this particular issue and explore the actual disease pathobiology, several potential targets, like three structural proteins and seven non-structural (NS) proteins, along with their inhibitors of synthetic and natural origin, have been screened using docking simulation. Exploration of these targets, along with their inhibitors, has been extensively studied in culmination with molecular docking-based screening to potentiate the treatment. These screened inhibitors could possibly be helpful for the designing of new congeneric potential compounds to combat dengue fever and its complications.

Potential therapeutic biomolecules of hymenopteran venom against SARS-CoV-2 from Egyptian patients

The therapeutic potential of insect-derived bioactive molecules as anti-SARS-CoV-2 agents has shown promising results. Hymenopteran venoms, notably from Apis mellifera (honeybee) and Vespa orientalis (oriental wasp), were examined for the first time in an in vitro setting for their potential anti-COVID-19 activity. This assessment utilized an immunodiagnostic system to detect the SARS-CoV-2 nucleocapsid antigen titer reduction. Further analyses, including cytotoxicity assays, plaque reduction assays, and in silico docking-based screening, were performed to evaluate the efficacy of the most potent venom. Results indicated that bee and wasp venoms contain bioactive molecules with potential therapeutic effects against SARS-CoV-2.Nevertheless, the wasp venom exhibited superior efficacy compared to bee venom, achieving a 90% maximal (EC90) concentration effect of antigen depletion at 0.184 mg/mL, in contrast to 2.23 mg/mL for bee venom. The cytotoxicity of the wasp venom was assessed on Vero E6 cells 48 h post-treatment using the MTT assay. The CC 50 of the cell growth was 0.16617 mg/mL for Vero E6 cells. The plaque reduction assay of wasp venom revealed 50% inhibition (IC50) at a 0.208 mg/mL concentration. The viral count at 50% inhibition was 2.5 × 104 PFU/mL compared to the initial viral count of 5 × 104 PFU/mL. In silico data for the wasp venom revealed a strong attraction to binding sites on the ACE2 protein, indicating ideal interactions. This substantiates the potential of wasp venom as a promising viral inhibitor against SARS-CoV-2, suggesting its consideration as a prospective natural preventive and curative antiviral drug. In conclusion, hymenopteran venoms, particularly wasp venom, hold promise as a source of potential therapeutic biomolecules against SARS-CoV-2. More research and clinical trials are needed to evaluate these results and investigate their potential for translation into innovative antiviral therapies.

Molecular Docking-Based Screening of Five Heterocyclic Quinone Compounds for Antifungal Activity on Yeast Sec14p and Validation by Redocking

Discover new antifungal drugs by evaluating the efficacy of heterocyclic compounds. Investigate the potential of yeast Sec14p protein as a target for antifungal drugs. Compare the effectiveness of Auto Dock and PyRX software for docking simulations of heterocyclic compounds against Sec14p. Docking simulations were performed using Auto Dock and PyRX software to assess the binding affinity of five specific heterocyclic compounds to the yeast Sec14p protein. The reference compound for comparison was a known antifungal agent with a Picolamide scaffold (PDB ID: 6FOE). Atovaquone exhibited the strongest binding affinity (-9.4 kcal/mol) using PyRX. A known antifungal agent showed a significant discrepancy in binding energy between Auto Dock (-6.2 kcal/mol) and PyRX (-3.64 kcal/mol). This study explores a novel class of compounds (Quinones) for antifungal drug discovery. It highlights the potential of yeast Sec14p protein as a target for antifungal drugs. The findings suggest that PyRX might be more suitable for docking simulations of certain compound classes than Auto Dock. This emphasizes the importance of software selection based on the specific molecules under investigation. Keywords: Molecular docking, Quinones, Antifungal, PyRX, Auto dock

Machine learning accelerates pharmacophore-based virtual screening of MAO inhibitors

Nowadays, an efficient and robust virtual screening procedure is crucial in the drug discovery process, especially when performed on large and chemically diverse databases. Virtual screening methods, like molecular docking and classic QSAR models, are limited in their ability to handle vast numbers of compounds and to learn from scarce data, respectively. In this study, we introduce a universal methodology that uses a machine learning-based approach to predict docking scores without the need for time-consuming molecular docking procedures. The developed protocol yielded 1000 times faster binding energy predictions than classical docking-based screening. The proposed predictive model learns from docking results, allowing users to choose their preferred docking software without relying on insufficient and incoherent experimental activity data. The methodology described employs multiple types of molecular fingerprints and descriptors to construct an ensemble model that further reduces prediction errors and is capable of delivering highly precise docking score values for monoamine oxidase ligands, enabling faster identification of promising compounds. An extensive pharmacophore-constrained screening of the ZINC database resulted in a selection of 24 compounds that were synthesized and evaluated for their biological activity. A preliminary screen discovered weak inhibitors of MAO-A with a percentage efficiency index close to a known drug at the lowest tested concentration. The approach presented here can be successfully applied to other biological targets as target-specific knowledge is not incorporated at the screening phase.

Screening Marine Microbial Metabolites as Promising Inhibitors of Borrelia garinii: A Structural Docking Approach towards Developing Novel Lyme Disease Treatment.

Lyme disease caused by the Borrelia species is a growing health concern in many parts of the world. Current treatments for the disease may have side effects, and there is also a need for new therapies that can selectively target the bacteria. Pathogens responsible for Lyme disease include B. burgdorferi, B. afzelii, and B. garinii. In this study, we employed structural docking-based screening to identify potential lead-like inhibitors against the bacterium. We first identified the core essential genome fraction of the bacterium, using 37 strains. Later, we screened a library of lead-like marine microbial metabolites (n = 4730) against the arginine deiminase (ADI) protein of Borrelia garinii. This protein plays a crucial role in the survival of the bacteria, and inhibiting it can kill the bacterium. The prioritized lead compounds demonstrating favorable binding energies and interactions with the active site of ADI were then evaluated for their drug-like and pharmacokinetic parameters to assess their suitability for development as drugs. Results from molecular dynamics simulation (100 ns) and other scoring parameters suggest that the compound CMNPD18759 (common name: aureobasidin; IUPAC name: 2-[(4R,6R)-4,6-dihydroxydecanoyl]oxypropan-2-yl (3S,5R)-3,5-dihydroxydecanoate) holds promise as a potential drug candidate for the treatment of Lyme disease, caused by B. garinii. However, further experimental studies are needed to validate the efficacy and safety of this compound in vivo.

Taming the cytokine storm: small molecule inhibitors targeting IL-6/IL-6α receptor.

Given the increasing effectiveness of immune-based therapies, management of their associated toxicities is of utmost importance. Cytokine release syndrome (CRS), characterized by elevated levels of cytokine, poses a significant challenge following the administration of antibodies and CAR-T cell therapies. CRS also contributes to multiple organ dysfunction in severe viral infections, notably in COVID-19. Given the pivotal role of IL-6 cytokine in initiating CRS, it has been considered a most potential therapeutic target to mitigate hyperactivated immune responses. While monoclonal antibodies of IL-6 show promise in mitigating cytokine storm, concerns about immunotoxicity persist, and small molecule IL-6 antagonists remain unavailable. The present study employed sophisticated computational techniques to identify potential hit compounds as IL-6 inhibitors, with the aim of inhibiting IL-6/IL-6R protein-protein interactions. Through ligand-based pharmacophore mapping and shape similarity in combination with docking-based screening, we identified nine hit compounds with diverse chemical scaffolds as potential binders of IL-6. Further, the MD simulation of 300 ns of five virtual hits in a complex with IL-6 was employed to study the dynamic behavior. To provide a more precise prediction, binding free energy was also estimated. The identified compounds persistently interacted with the residues lining the binding site of the IL-6 protein. These compounds displayed low binding energy during MMPBSA calculations, substantiating their strong association with IL-6. This study suggests promising scaffolds as potential inhibitors of IL-6/IL-6R protein-protein interactions and provides direction for lead optimization.

Targeting the hSSB1-INTS3 Interface: A Computational Screening Driven Approach to Identify Potential Modulators.

Human single-stranded DNA binding protein 1 (hSSB1) forms a heterotrimeric complex, known as a sensor of single-stranded DNA binding protein 1 (SOSS1), in conjunction with integrator complex subunit 3 (INTS3) and C9ORF80. This sensory protein plays an important role in homologous recombination repair of double-strand breaks in DNA to efficiently recruit other repair proteins at the damaged sites. Previous studies have identified elevated hSSB1-mediated DNA repair activities in various cancers, highlighting its potential as an anticancer target. While prior efforts have focused on inhibiting hSSB1 by targeting its DNA binding domain, this study seeks to explore the inhibition of the hSSB1 function by disrupting its interaction with the key partner protein INTS3 in the SOSS1 complex. The investigative strategy entails a molecular docking-based screening of a specific compound library against the three-dimensional structure of INTS3 at the hSSB1 binding interface. Subsequent assessments involve in vitro analyses of protein-protein interaction (PPI) disruption and cellular effects through co-immunoprecipitation and immunofluorescence assays, respectively. Moreover, the study includes an evaluation of the structural stability of ligands at the INTS3 hot-spot site using molecular dynamics simulations. The results indicate a potential in vitro disruption of the INTS3-hSSB1 interaction by three of the tested compounds obtained from the virtual screening with one impacting the recruitment of hSSB1 and INTS3 to chromatin following DNA damage. To our knowledge, our results identify the first set of drug-like compounds that functionally target INTS3-hSSB1 interaction, and this provides the basis for further biophysical investigations that should help to speed up PPI inhibitor discovery.

Molecular docking-based screening of methicillin-resistant Staphylococcus aureus FEM proteins with FDA-approved drugs.

Antibiotic resistance stands as one of the most significant public health challenges in recent decades. FEM proteins are responsible for the synthesis of pentaglycine cross-bridge, a primary constituent of bacterial peptidoglycan polymer crosslinking during cell wall biosynthesis. Since they are necessary for bacterial survival and antibiotic resistance, they were considered as significant antibacterial targets. We report herein, the virtual screening and selection of FDA-approved drugs and their potent similar molecules as FEM protein inhibitors and analyzed for inhibiting affinity and their ADMET pharmacokinetic properties. This data provide a foundation for the development and optimization of structurally innovative antimicrobial drugs.

Empirical and molecular docking-based screening of heterocyclic compounds to identify potential acetylcholinesterase inhibitors to treat Alzheimer’s disease and its histology

Empirical and molecular docking-based screening of heterocyclic compounds to identify potential acetylcholinesterase inhibitors to treat Alzheimer’s disease and its histology

Molecular modeling study combined with deep learning approach for the identification of potent β-catenin inhibitors

β-catenin is a propitious target for various cancer drugs for inhibiting tumour cell proliferation and differentiation. Even though several inhibitors have been discovered for β-catenin but its selectivity towards β-catenin and TCF-4 interactions is a major challenge. Hence, the expedition for identifying a selective drug for β-catenin inhibition against cancer will have immense potential and favour. The present study aims to scrutinise compounds that can impede β-catenin overexpression in cancer using an integrated pharmacophore and in silico docking-based screening of 28,007 molecules from the ZINC repository. The analysis yielded the top two compounds, namely ZINC000016051423 and ZINC000028564770, with better docking scores of -4.007 kcal/mol and -6.547 kcal/mol at the β-catenin binding pocket. Moreover, their free energy scores were -40.882 and -53.989 kcal/mol with favourable drug-likeness characteristics. Eventually, both hits exhibited better inhibitory activity against 66 colorectal cell lines using the PaccMann algorithm. In conclusion, our findings suggest that the lead compounds may serve as a possible β-catenin inhibitor during the treatment of cancer, though further experimental study is needed to evaluate the compound’s efficacy.

AI-driven Discovery of Celecoxib and Dexamethasone for Exploring their Mode of Action as Human Interleukin (IL-6) Inhibitors to Treat COVID-19-induced Cytokine Storm in Humans.

In the case of COVID-19 patients, it has been observed that the immune system of the infected person exhibits an extreme inflammatory response known as cytokine release syndrome (CRS) where the inflammatory cytokines are swiftly produced in quite large amounts in response to infective stimuli. Numerous case studies of COVID-19 patients with severe symptoms have documented the presence of higher plasma concentrations of human interleukin-6 (IL-6), which suggests that IL-6 is a crucial factor in the pathophysiology of the disease. In order to prevent CRS in COVID-19 patients, the drugs that can exhibit binding interactions with IL-6 and block the signaling pathways to decrease the IL-6 activity may be repurposed. This research work focused on molecular docking-based screening of the drugs celecoxib (CXB) and dexamethasone (DME) to explore their potential to interact with the binding sites of IL-6 protein and reduce the hyper-activation of IL-6 in the infected personnel. Both of the drugs were observed to bind with the IL-6 (IL-6 receptor alpha chain) and IL-6Rα receptor with the respective affinities of -7.3 kcal/mol and -6.3 kcal/mol, respectively, for CXB and DME. Moreover, various types of binding interactions of the drugs with the target proteins were also observed in the docking studies. The dynamic behaviors of IL-6/IL-6Rα in complex with the drugs were also explored through molecular dynamics simulation analysis. The results indicated significant stabilities of the acquired drug-protein complexes up to 100 ns. The findings of this study have suggested the potential of the drugs studied to be utilized as antagonists for countering CRS in COVID-19 ailment. This study presents the studied drugs as promising candidates both for the clinical and pre-clinical treatment of COVID-19.

Molecular Docking-based Screening of Natural Heterocyclic Compounds as a Potential Drug for COVID-19

Introduction: The coronavirus pandemic poses significant challenges for the pharmaceutical industry. Methods: Coronavirus enters host cells via the angiotensin-converting enzyme 2 receptors (ACE2). The SARS-CoV-2 spike glycoprotein is a potential target for medicinal chemists in the development of specific drugs. The current study investigates molecular modeling studies to identify potential drug candidates. Molecular docking simulations were run on 11 natural heterocyclic compounds/flavonoids. Results: When tested against the viral spike protein receptor, isoquercetin had a docking binding energy of -6.74kcal/mol (PDBID:6LU7). Conclusion: A docking study revealed the interaction of the receptor-binding domain with various flavonoid compounds.

In Silico Identification of Natural Product-Based Inhibitors Targeting IL-1β/IL-1R Protein–Protein Interface

IL-1β mediates inflammation and regulates immune responses, cell proliferation, and differentiation. Dysregulation of IL-1β is linked to inflammatory and autoimmune diseases. Elevated IL-1β levels are found in patients with severe COVID-19, indicating its excessive production may worsen the disease. Also, dry eye disease patients show high IL-1β levels in tears and conjunctival epithelium. Therefore, IL-1β signaling is a potential therapeutic targeting for COVID-19 and aforementioned diseases. No small-molecule IL-1β inhibitor is clinically approved despite efforts. Developing such inhibitors is highly desirable. Herein, a docking-based strategy was used to screen the TCM (Traditional Chinese Medicine) database to identify possible IL-1β inhibitors with desirable pharmacological characteristics by targeting the IL-1β/IL-1R interface. Primarily, the docking-based screening was performed by selecting the crucial residues of IL-1β interface to retrieve the potential compounds. Afterwards, the compounds were shortlisted on the basis of binding scores and significant interactions with the crucial residues of IL-1β. Further, to gain insights into the dynamic behavior of the protein–ligand interactions, MD simulations were performed. The analysis suggests that four selected compounds were stabilized in an IL-1β pocket, possibly blocking the formation of an IL-1β/IL-1R complex. This indicates their potential to interfere with the immune response, making them potential therapeutic agents to investigate further.

Novel hits for autosomal dominated polycystic kidney disease (ADPKD) targeting derived by in silico screening on ZINC-15 natural product database

Autosomal dominant polycystic kidney disease (ADPKD) is the most common genetic kidney disorder that leads to growth cysts in the kidney, ultimately resulting in loss of function. Currently, no effective drug therapy can be safely used in the clinic. So, looking for effective therapeutic drugs is urgent for treating ADPKD. Our natural product library was prepared based on the ZINC-15 database. Lipinski’s rule of five, drug-likeness, and toxicity screening of the designed library were evaluated. Swiss model online server was used for modeling of GANAB target. Finally, docking-based screening against ADPKD targets was done by MOE 2019 software. The top 14 favorable druglike and non-toxic hits were selected for docking studies. Our results showed that compound-10 (ZINC 6073947) as a sesquiterpene coumarin had more negative binding interaction into the active site of PPARG, OXSR1, GANAB, AVPR2, and PC2 with docking scores of −8.22, −7.52, −6.98, −6.61 and −6.05 kcal/mol, respectively, in comparison to Curcumin, as a natural product that is now in phase 4 clinical trial in ADPKD disease, with an affinity of −8.03, −6.42, −6.82, −5.84 and −5.10 kcal/mol, respectively. Furthermore, seven sesquiterpene coumarins similar to compound 10 were generated and docked. Farnesiferol B (16), compared to compound-10, showed binding affinity of −8.16, −6.4, −7.46, −6.92, and −6.11 kcal/mol against the above targets, respectively. Molecular dynamics, which was done on the compound-10 and 16 (Farnesiferol B) in complex with PPARG, GANAB, and AVPR2, showed more negative binding free-energy than Pioglitazone, Miglitol, and Tolvaptan as FDA-approved drugs for each target, respectively. Communicated by Ramaswamy H. Sarma

Combining pharmacophore models derived from DNA-encoded chemical libraries with structure-based exploration to predict Tankyrase 1 inhibitors

DNA-encoded chemical libraries (DECLs) interrogate the interactions of a target of interest with vast numbers of molecules. DECLs hence provide abundant information about the chemical ligand space for therapeutic targets, and there is considerable interest in methods for exploiting DECL screening data to predict novel ligands. Here we introduce one such approach and demonstrate its feasibility using the cancer-related poly-(ADP-ribose)transferase tankyrase 1 (TNKS1) as a model target. First, DECL affinity selections resulted in structurally diverse TNKS1 inhibitors with high potency including compound 2 with an IC50 value of 0.8 nM. Additionally, TNKS1 hits from four DECLs were translated into pharmacophore models, which were exploited in combination with docking-based screening to identify TNKS1 ligand candidates in databases of commercially available compounds. This computational strategy afforded TNKS1 inhibitors that are outside the chemical space covered by the DECLs and yielded the drug-like lead compound 12 with an IC50 value of 22 nM. The study further provided insights in the reliability of screening data and the effect of library design on hit compounds. In particular, the study revealed that while in general DECL screening data are in good agreement with off-DNA ligand binding, unpredictable interactions of the DNA-attachment linker with the target protein contribute to the noise in the affinity selection data.

In-silico analysis reveals Quinic acid as a multitargeted inhibitor against Cervical Cancer

The cervix is the lowermost part of the uterus that connects to the vagina, and cervical cancer is a malignant cervix tumour. One of this cancer’s most important risk factors is HPV infection. In the approach to finding an effective treatment for this disease, various works have been done around genomics and drug discovery. Finding the major altered genes was one of the most significant studies completed in the field of cervical cancer by TCGA (The Cancer Genome Atlas), and these genes are TGFBR2, MED1, ERBB3, CASP8, and HLA-A. The greatest genomic alterations were found in the PI3K/MAPK and TGF-Beta signalling pathways, suggesting that numerous therapeutic targets may come from these pathways in the future. We, therefore, conducted a combined enrichment analysis of genes gathered from various works of literature for this study. The final six key genes from the list were obtained after enrichment analysis using GO, KEGG, and Reactome methods. The six proteins against the identified genes were then subjected to a docking-based screening against a library of 6,87,843 prepared natural compounds from the ZINC15 database. The most stable compound was subsequently discovered through virtual screening to be the natural substance Quinic acid, which also had the highest binding affinity for all six proteins and a better docking score. To examine their stability, the study was extended to MM/GBSA and MD simulations on the six docked proteins, and comparative docking-based calculations led us to identify the Quinic Acid as a multitargeted compound. The overall deviation of the compound was less than 2 Å for all the complexes considered best for the biological molecules, and the simulation interaction analysis reveals a huge web of interaction during the simulation. Communicated by Ramaswamy H. Sarma

Exploring the Targets of Novel Corona Virus and Docking-based Screening of Potential Natural Inhibitors to Combat COVID-19.

There is a need to explore natural compounds against COVID-19 due to their multitargeted actions against various targets of nCoV. They act on multiple sites rather than single targets against several diseases. Thus, there is a possibility that natural resources can be repurposed to combat COVID-19. However, the biochemical mechanisms of these inhibitors were not known. To reveal the mode of anti-nCoV action, structure-based docking plays a major role. The present study is an attempt to explore various potential targets of SARS-CoV-2 and the structure-based screening of various potential natural inhibitors to combat the novel coronavirus.

Comparative Study of Developed Formulation and Market Formulation for Antidiabetic Potential in Alloxan-Induced Diabetic Wistar Rats

Published on: October 2022Journal of Young Pharmacists, 2022; 14(4):387-393Original Article | doi:10.5530/jyp.2022.14.78 Authors:Vinod Kumar Gauttam1,*, Kavita Munjal2, Somdutt Mujwar3, Jyotiram Sawale1, Meenakashi Rohilla4, Sumeet Gupta51Department of Pharmacognosy, IES Institute of Pharmacy, IES University, Bhopal, Madhya Pradesh, INDIA.2Department of Pharmacognosy, MM College of Pharmacy, MM University (Deemed to be University), Mullana, Ambala, Haryana, INDIA.3Department of Pharmaceutical Chemistry, Chitkara College of Pharmacy, Chitkara University, Rajpura, Punjab, INDIA.4Department of Pharmacognosy, ISF College of Pharmacy, Moga, Punjab, INDIA.5Department of Pharmacology, MM College of Pharmacy, MM University (Deemed to be University), Mullana, Ambala, Haryana, INDIA. Abstract:Background: The present study was designed with the aim of minimizing the incorporation of the drugs in a polyherbal antidiabetic formulation so the load of the drugs to the patient can be avoided and also helps in standardization. Materials and Methods: Molecular docking-based screening of potential herbal leads of M. charantia, (Drug A), G. sylvestre, (Drug B) and W. somnifera, (Drug C) were performed with intent to prioritize the ratio of herbal extracts. Lyophilised hydro-alcohol (50%) extracts of above three drugs were combined in different ratios as HA: Hydroalcoholic extracts combination A, HB: Hydroalcoholic extracts combination B and HC: Hydroalcoholic extracts combination C. The study of 21 days, carried out on alloxan-induced diabetic Wistar rats to compare its anti-diabetic effect with the marketed herbal formulation (MHF). The biochemical parameters studied were serum glucose level, lipid profile and liver glycogen content along with the body weight measurement. Results: The proposed Hydroalcoholic extracts combination B (HB, 1000 mg/kg per oral) possess antihyperglycemic effect with improvement in the abnormal lipid profile as observed in the diabetic experimental animals. Moreover, the formulation also reported check on the loss of body weight when compared with untreated diabetic rats. The observations were found to be at par with standard drug, metformin (500 mg/kg). Conclusion: Our findings suggest the proposed formulation have antihyperglycemic and anti-hyperlipidimic potentials. Furthermore, its effect on chronic diabetes and its complications is needed to be explored. Based on the docking results it has been clearly indicated that the antidiabetic effect of the used herbal extract is because of the presence of Withanolide-A and Charantin.Keywords: Diabetes, Polyherbal formulation, Metformin, Docking, Charantin, Withanolide.

Dual-targeting cyclic peptides of receptor-binding domain (RBD) and main protease (Mpro) as potential drug leads for the treatment of SARS-CoV-2 infection.

The receptor-binding domain (RBD) and the main protease (Mpro) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) play a crucial role in the entry and replication of viral particles, and co-targeting both of them could be an attractive approach for the treatment of SARS-CoV-2 infection by setting up a "double lock" in the viral lifecycle. However, few dual RBD/Mpro-targeting agents have been reported. Here, four novel RBD/Mpro dual-targeting peptides, termed as MRs 1-4, were discovered by an integrated virtual screening scheme combining molecular docking-based screening and molecular dynamics simulation. All of them possessed nanomolar binding affinities to both RBD and Mpro ranging from 14.4 to 39.2nM and 22.5-40.4nM, respectively. Further pseudovirus infection assay revealed that the four selected peptides showed >50% inhibition against SARS-CoV-2 pseudovirus at a concentration of 5µM without significant cytotoxicity to host cells. This study leads to the identification of a class of dual RBD/Mpro-targeting agents, which may be developed as potential and effective SARS-CoV-2 therapeutics.

Novel Hits for N-Myristoyltransferase Inhibition Discovered by Docking-Based Screening.

N-myristoyltransferase (NMT) inhibitors that were initially developed for treatment of parasitic protozoan infections, including sleeping sickness, malaria, and leismaniasis, have also shown great promise as treatment for oncological diseases. The successful transition of NMT inhibitors, which are currently at preclinical to early clinical stages, toward clinical approval and utilization may depend on the development and design of a diverse set of drug molecules with particular selectivity or pharmacological properties. In our study, we report that a common feature in the inhibitory mechanism of NMT is the formation of a salt bridge between a positively charged chemical group of the small molecule and the negatively charged C-terminus of an enzyme. Based on this observation, we designed a virtual screening protocol to identify novel ligands that mimic this mode of interaction. By screening over 1.1 million structures downloaded from the ZINC database, several hits were identified that displayed NMT inhibitory activity. The stability of the inhibitor-NMT complexes was evaluated by molecular dynamics simulations. The ligands from the stable complexes were tested in vitro and some of them appear to be promising leads for further optimization.