Search Results (35)

Ubiquitin-specific protease 7 (USP7), a deubiquitinase enzyme responsible for removing ubiquitin (Ub) from target proteins, plays a crucial role in oncogenic pathways and has been implicated in various human diseases. X-ray crystallography has revealed distinct conformations of USP7, including apo (ligand-free), allosteric inhibitor-, and Ub-bound states. However, the dynamic mechanisms underlying the allosteric inhibition of USP7 remain unclear. This study investigates the effect of allosteric inhibitor binding on the dynamics of USP7 through multiple replica molecular dynamics simulations. Our results demonstrate that Ub binding stabilizes the USP7 conformation, while allosteric inhibitor binding increases flexibility and variability in the fingers and palm domains of USP7. Furthermore, our analysis of USP7 local regions reveals that allosteric inhibitor binding not only restrains the dynamics of the C-terminal Ub binding site, thereby impeding the accessibility of Ub to USP7, but also disrupts the proper alignment of the catalytic triad (Cys223-His464-Asp481) in USP7. Additionally, community network analysis indicates that intra-domain communications within the fingers domain in USP7 are significantly enhanced upon allosteric inhibitor binding. This study reveals that the binding of an allosteric inhibitor induces a dynamic shift in enzyme’s conformational equilibrium, effectively disrupting its catalytic activity through allosteric modulation. Full article

Zika virus infection is a mosquito-borne viral disease that has become a global health concern recently. Zika virus belongs to the Flavivirus genus and is primarily transmitted by Aedes mosquitoes. Prevention of Zika virus infection involves avoiding mosquito bites by using repellent, wearing protective clothing, and staying in screened areas, especially for pregnant women. Treatment focuses on managing symptoms with rest, fluids, and acetaminophen, with close monitoring for pregnant women. Currently, there is no specific antiviral treatment or vaccine for the Zika virus, highlighting the importance of prevention strategies to control its spread. Therefore, in this study, the Zika virus non-structural protein NS3 was targeted to inhibit Zika infection by identifying the novel inhibitor through an in silico approach. Here, 2864 natural compounds were screened using a machine learning-based QSAR model, and later docking was performed to select the potential target. Subsequently, Tanimoto similarity and clustering were performed to obtain the potential target. The three most potential compounds were obtained: (a) 5297, (b) 432449, and (c) 85137543. The protein–ligand complex’s stability and flexibility were then investigated by dynamic modelling. The 300 ns simulation showed that 5297 exhibited the steadiest deviation and constant creation of hydrogen bonds. Compared to the other compounds, 5297 demonstrated a superior binding free energy (ΔG = −20.81 kcal/mol) with the protein when the MM/GBSA technique was used. The study determined that 5297 showed significant therapeutic potential and justifies further experimental investigation as a possible inhibitor of the NS2B-NS3 protease target implicated in Zika virus infection. Full article

The emergence of drug-resistance-inducing mutations in Hepatitis C virus (HCV) coupled with genotypic heterogeneity has made targeting NS3/4A serine protease difficult. In this work, we investigated the mutagenic variations in the binding pocket of Genotype 3 (G3) HCV NS3/4A and evaluated ligands for efficacious inhibition. We report mutations at 14 positions within the ligand-binding residues of HCV NS3/4A, including H57R and S139P within the catalytic triad. We then modelled each mutational variant for pharmacophore-based virtual screening (PBVS) followed by covalent docking towards identifying a potential covalent inhibitor, i.e., cpd-217. The binding stability of cpd-217 was then supported by molecular dynamic simulation followed by MM/GBSA binding free energy calculation. The free energy decomposition analysis indicated that the resistant mutants alter the HCV NS3/4A–ligand interaction, resulting in unbalanced energy distribution within the binding site, leading to drug resistance. Cpd-217 was identified as interacting with all NS3/4A G3 variants with significant covalent docking scores. In conclusion, cpd-217 emerges as a potential inhibitor of HCV NS3/4A G3 variants that warrants further in vitro and in vivo studies. This study provides a theoretical foundation for drug design and development targeting HCV G3 NS3/4A. Full article

Brown seaweeds of the Fucus genus represent a rich source of natural antiviral products. In this study, a Fucus ceranoides hydroalcoholic extract (FCHE) was found to inhibit 74.2 ± 1.3% of the proteolytic activity of the free SARS-CoV-2 3CL protease (3CLpro), an enzyme that plays a pivotal role in polyprotein processing during coronavirus replication and has been identified as a relevant drug discovery target for SARS- and MERS-CoVs infections. To purify and identify 3CLpro ligands with potential inhibitory activity using a one-step approach, we immobilized the enzyme onto magnetic microbeads (3CLpro-MPs), checked that the enzymatic activity was maintained after grafting, and used this bait for a ligand-fishing strategy followed by a high-resolution mass spectrometry analysis of the fished-out molecules. Proof of concept for the ligand-fishing capacity of the 3CLpro-MPs was demonstrated by doping the FCHE extract with the substrate peptide TSAVLQ-pNA, resulting in the preferential capture of this high-affinity peptide within the macroalgal complex matrix. Ligand fishing in the FCHE alone led to the purification and identification via high-resolution mass spectrometry (HRMS) of seven hepta-, octa-, and decapeptides in an eluate mix that significantly inhibited the free 3CLpro more than the starting FCHE (82.7 ± 2.2% inhibition). Molecular docking simulations of the interaction between each of the seven peptides and the 3CLpro demonstrated a high affinity for the enzyme’s proteolytic active site surpassing that of the most affine peptide ligand identified so far (a co-crystallographic peptide). Testing of the corresponding synthetic peptides demonstrated that four out of seven significantly inhibited the free 3CLpro (from 46.9 ± 6.4 to 76.8 ± 3.6% inhibition at 10 µM). This study is the first report identifying peptides from Fucus ceranoides with high inhibitory activity against the SARS-CoV-2 3CLprotease which bind with high affinity to the protease’s active site. It also confirms the effectiveness of the ligand-fishing strategy for the single-step purification of enzyme inhibitors from complex seaweed matrices. Full article

Cancer is a serious threat to human life and social development and the use of scientific methods for cancer prevention and control is necessary. In this study, HQSAR, CoMFA, CoMSIA and TopomerCoMFA methods are used to establish models of 65 imidazo[4,5-b]pyridine derivatives to explore the quantitative structure-activity relationship between their anticancer activities and molecular conformations. The results show that the cross-validation coefficients q² of HQSAR, CoMFA, CoMSIA and TopomerCoMFA are 0.892, 0.866, 0.877 and 0.905, respectively. The non-cross-validation coefficients r² are 0.948, 0.983, 0.995 and 0.971, respectively. The externally validated complex correlation coefficients r²_pred of external validation are 0.814, 0.829, 0.758 and 0.855, respectively. The PLS analysis verifies that the QSAR models have the highest prediction ability and stability. Based on these statistics, virtual screening based on R group is performed using the ZINC database by the Topomer search technology. Finally, 10 new compounds with higher activity are designed with the screened new fragments. In order to explore the binding modes and targets between ligands and protein receptors, these newly designed compounds are conjugated with macromolecular protein (PDB ID: 1MQ4) by molecular docking technology. Furthermore, to study the nature of the newly designed compound in dynamic states and the stability of the protein-ligand complex, molecular dynamics simulation is carried out for N3, N4, N5 and N7 docked with 1MQ4 protease structure for 50 ns. A free energy landscape is computed to search for the most stable conformation. These results prove the efficient and stability of the newly designed compounds. Finally, ADMET is used to predict the pharmacology and toxicity of the 10 designed drug molecules. Full article

Although the COVID-19 pandemic caused by SARS-CoV-2 viruses is officially over, the search for new effective agents with activity against a wide range of coronaviruses is still an important task for medical chemists and virologists. We synthesized a series of thiazolo-thiophenes based on (+)- and (−)-usnic acid and studied their ability to inhibit the main protease of SARS-CoV-2. Substances containing unsubstituted thiophene groups or methyl- or bromo-substituted thiophene moieties showed moderate activity. Derivatives containing nitro substituents in the thiophene heterocycle—just as pure (+)- and (−)-usnic acids—showed no anti-3CL^pro activity. Kinetic parameters of the most active compound, (+)-3e, were investigated, and molecular modeling of the possible interaction of the new thiazolo-thiophenes with the active site of the main protease was carried out. We evaluated the binding energies of the ligand and protein in a ligand–protein complex. Active compound (+)-3e was found to bind with minimum free energy; the binding of inactive compound (+)-3g is characterized by higher values of minimum free energy; the positioning of pure (+)-usnic acid proved to be unstable and is accompanied by the formation of intermolecular contacts with many amino acids of the catalytic binding site. Thus, the molecular dynamics results were consistent with the experimental data. In an in vitro antiviral assay against six strains (Wuhan, Delta, and four Omicron sublineages) of SARS-CoV-2, (+)-3e demonstrated pronounced antiviral activity against all the strains. Full article

Severe acute respiratory syndrome Coronavirus 2 (SARS-CoV-2) virus syndrome caused the recent outbreak of COVID-19 disease, the most significant challenge to public health for decades. Despite the successful development of vaccines and promising therapies, the development of novel drugs is still in the interests of scientific society. SARS-CoV-2 main protease M^pro is one of the key proteins for the lifecycle of the virus and is considered an intriguing target. We used a structure-based drug design approach as a part of the search of new inhibitors for SARS-CoV-2 M^pro and hence new potential drugs for treating COVID-19. Four structures of potential inhibitors of (4S)-2-(2-(1H-imidazol-5-yl)ethyl)-4-amino-2-(1,3-dihydroxypropyl)-3-hydroxy-5-(1H-imidazol-5-yl)pentanal (L¹), (2R,4S)-2-((1H-imidazol-4-yl)methyl)-4-chloro-8-hydroxy-7-(hydroxymethyl)octanoic acid (L²), 1,9-dihydroxy-6-(hydroxymethyl)-6-(((1S)-1,7,7-trimethylbicyclo [2.2.1]heptan-2-yl)amino)nonan-4-one (L³), and 2,4,6-tris((4H-1,2,4-triazol-3-yl)amino)benzonitrile (L⁴) were modeled. Three-dimensional structures of ligand–protein complexes were modeled and their potential binding efficiency proved. Docking and molecular dynamic simulations were performed for these compounds. Detailed trajectory analysis of the ligands’ binding conformation was carried out. Binding free energies were estimated by the MM/PBSA approach. Results suggest a high potential efficiency of the studied inhibitors. Full article

The “Long-COVID syndrome” has posed significant challenges due to a lack of validated therapeutic options. We developed a novel multi-step virtual screening strategy to reliably identify inhibitors against 3-chymotrypsin-like protease of SARS-CoV-2 from abundant flavonoids, which represents a promising source of antiviral and immune-boosting nutrients. We identified 57 interacting residues as contributors to the protein-ligand binding pocket. Their energy interaction profiles constituted the input features for Machine Learning (ML) models. The consensus of 25 classifiers trained using various ML algorithms attained 93.9% accuracy and a 6.4% false-positive-rate. The consensus of 10 regression models for binding energy prediction also achieved a low root-mean-square error of 1.18 kcal/mol. We screened out 120 flavonoid hits first and retained 50 drug-like hits after predefined ADMET filtering to ensure bioavailability and safety profiles. Furthermore, molecular dynamics simulations prioritized nine bioactive flavonoids as promising anti-SARS-CoV-2 agents exhibiting both high structural stability (root-mean-square deviation < 5 Å for 218 ns) and low MM/PBSA binding free energy (<−6 kcal/mol). Among them, KB-2 (PubChem-CID, 14630497) and 9-O-Methylglyceofuran (PubChem-CID, 44257401) displayed excellent binding affinity and desirable pharmacokinetic capabilities. These compounds have great potential to serve as oral nutraceuticals with therapeutic and prophylactic properties as care strategies for patients with long-COVID syndrome. Full article

Norovirus is the leading cause of viral gastroenteritis worldwide, and there are no approved vaccines or therapeutic treatments for chronic or severe norovirus infections. The structural characterisation of the norovirus protease and drug development has predominantly focused upon GI.1 noroviruses, despite most global outbreaks being caused by GII.4 noroviruses. Here, we determined the crystal structures of the GII.4 Sydney 2012 ligand-free norovirus protease at 2.79 Å and at 1.83 Å with a covalently bound high-affinity (IC₅₀ = 0.37 µM) protease inhibitor (NV-004). We show that the active sites of the ligand-free protease structure are present in both open and closed conformations, as determined by their Arg112 side chain orientation. A comparative analysis of the ligand-free and ligand-bound protease structures reveals significant structural differences in the active site cleft and substrate-binding pockets when an inhibitor is covalently bound. We also report a second molecule of NV-004 non-covalently bound within the S4 substrate binding pocket via hydrophobic contacts and a water-mediated hydrogen bond. These new insights can guide structure-aided drug design against the GII.4 genogroup of noroviruses. Full article

In this work, the biological potency of nitazoxanide (NTZ) was enhanced through coordination with transition metal ions Cu(II), Ni(II), and Zn(II). Initially, complexes with a ligand-metal stoichiometry of 2:1 were successfully synthesized and characterized by spectroscopic techniques and thermogravimetric methods. Measurement of the infrared spectrum revealed the bidentate nature of the ligand and excluded the possibility of the metal ion—amide group interaction. Nuclear magnetic resonance spectra showed a reduction in the NH- intensity signal and integration, indicating the possibility of enolization and the formation of keto-enol tautomers. To interpret these results, density functional theory was utilized under B3LYP/6-311G** for the free ligand and B3LYP/LANL2DZ for the metal complexes. We used UV-Vis and fluorescence spectroscopy to understand the biological properties of the complexes. This showed stronger interactions of NTZ-Cu(II) and NTZ-Ni(II) with DNA molecules than the NTZ-Zn(II) compound, with a binding constant (K_b) for the copper complex of 7.00 × 10⁵ M⁻¹. Both Cu(II)- and Ni(II)-NTZ had functional binding to the SARS-CoV-2 (6LU7) protease. Moreover, all metal complexes showed better antioxidation properties than the free ligand, with NTZ-Ni(II) having the best IC₅₀ value of 53.45 μg/mL. NTZ-Ni(II) was an effective antibacterial, with a mean inhibitory concentration of 6 μM, which is close to that of ampicillin (a reference drug). The metal complexes had moderated anticancer potencies, with NTZ-Cu(II) having IC₅₀ values of 24.5 and 21.5 against human breast cancer cells (MCF-7) and cancerous cervical tumor cells (HeLa), respectively. All obtained complexes exhibited high selectivity. Finally, the metal ions showed a practical role in improving the biological effectiveness of NTZ molecules. Full article

Identification of novel drugs for anti-African swine fever (ASF) applications is of utmost urgency, as it negatively affects pig farming and no effective vaccine or treatment is currently available. African swine fever virus (ASFV) encoded pS273R is a cysteine protease that plays an important role in virus replication. E64, acting as an inhibitor of cysteine protease, has been established as exerting an inhibitory effect on pS273R. In order to obtain a better understanding of the interaction between E64 and pS273R, common docking, restriction docking, and covalent docking were employed to analyze the optimal bonding position between pS273R−E64 and its bonding strength. Additionally, three sets of 100 ns molecular dynamics simulations were conducted to examine the conformational dynamics of pS273R and the dynamic interaction of pS273R−E64, based on a variety of analytical methods including root mean square deviation (RMSD), root mean square fluctuation (RMSF), free energy of ligand (FEL), principal component analysis (PCA), and molecular mechanics/Poisson–Boltzmann surface area (MM/PBSA) analysis. The results show that E64 and pS273R exhibited close binding degrees at the activity center of ASFV pS273R protease. The data of these simulations indicate that binding of E64 to pS273R results in a reduction in flexibility, particularly in the ARM region, and a change in the conformational space of pS273R. Additionally, the ability of E64 to interact with polar amino acids such as ASN158, SER192, and GLN229, as well as charged amino acids such as LYS167 and HIS168, seems to be an important factor in its inhibitory effect. Finally, Octet biostratigraphy confirmed the binding of E64 and pS273R with a KD value of 903 uM. Overall, these findings could potentially be utilized in the development of novel inhibitors of pS273R to address the challenges posed by ASFV. Full article

The transmission and infectivity of COVID-19 have caused a pandemic that has lasted for several years. This is due to the constantly changing variants and subvariants that have evolved rapidly from SARS-CoV-2. To discover drugs with therapeutic potential for COVID-19, we focused on the 3CL protease (3CL^pro) of SARS-CoV-2, which has been proven to be an important target for COVID-19 infection. Computational prediction techniques are quick and accurate enough to facilitate the discovery of drugs against the 3CL^pro of SARS-CoV-2. In this paper, we used both ligand-based virtual screening and structure-based virtual screening to screen the traditional Chinese medicine small molecules that have the potential to target the 3CL^pro of SARS-CoV-2. MD simulations were used to confirm these results for future in vitro testing. MCCS was then used to calculate the normalized free energy of each ligand and the residue energy contribution. As a result, we found ZINC15676170, ZINC09033700, and ZINC12530139 to be the most promising antiviral therapies against the 3CL^pro of SARS-CoV-2. Full article

Rosemary represents an important medicinal plant that has been attributed with various health-promoting properties, especially antioxidative, anti-inflammatory, and anticarcinogenic activities. Carnosic acid, carnosol, and rosmanol, as well as the phenolic acid ester rosmarinic acid, are the main compounds responsible for these actions. In our earlier research, we carried out an inverse molecular docking at the proteome scale to determine possible protein targets of the mentioned compounds. Here, we subjected the previously identified ligand–protein complexes with HIV-1 protease, K-RAS, and factor X to molecular dynamics simulations coupled with free-energy calculations. We observed that carnosic acid and rosmanol act as viable binders of the HIV-1 protease. In addition, carnosol represents a potential binder of the oncogene protein K-RAS. On the other hand, rosmarinic acid was characterized as a weak binder of factor X. We also emphasized the importance of water-mediated hydrogen-bond networks in stabilizing the binding conformation of the studied polyphenols, as well as in mechanistically explaining their promiscuous nature. Full article

At the end of the last century, it was revealed that quinones with one, two, and three aromatic rings could inhibit HIV-1 protease, an enzyme crucial for HIV (Human Immunodeficiency Virus) replication. Since HIV-1 protease acts as key target for AIDS (Acquired Immunodeficiency Syndrome) medications, the development of efficient inhibitor of this protein would lead to an increase in medical treatment and a decrease in the drug resistance. Later research revealed that hydroxyquinones can block HIV-1 protease at the micromolar level, which enabled a direction for the creation of HIV medications. Anthrarufin (1,5-dihydroxy-9,10-anthraquinone) is an anthraquinone that possesses a moderate antioxidative capacity and antimalaric activity. In this study, molecular docking simulations were used to examine the molecular interactions between anthrarufin, its monoanion and dianion as ligands, and HIV-1 reverse transcriptase (HIV-1 RT) as a target protein. Using AGFR software, the binding site of the HIV-1 RT was identified. The three-dimensional crystal structure of HIV-1 RT was downloaded from the Protein Data Bank (PDB ID: 2ZD1). Dolutegravir, nevirapine, anthrarufin, anthrarufin-anion and anthrarufin-dianion are used as ligands in the molecular docking simulations together with rilpivirine (TMC278), a non-nucleoside inhibitor of estimated protein. The AutoDock 4.0 program is used for molecular docking simulations. Anthrarufin, its monoanion and dianion can be considered as a potential HIV-1 RT inhibitors because they have similar inhibitory potency to other ligands under consideration, according to the results of the free energy of binding (∆G_bind) and inhibition constant (K_i) values. Full article

The rapid emergence and spread of new variants of coronavirus type 2, as well as the emergence of zoonotic viruses, highlights the need for methodologies that contribute to the search for new pharmacological treatments. In the present work, we searched for new SARS-CoV-2 papain-like protease inhibitors in the PubChem database, which has more than 100 million compounds. Based on the ligand efficacy index obtained by molecular docking, 500 compounds with higher affinity than another experimentally tested inhibitor were selected. Finally, the seven compounds with ADME parameters within the acceptable range for such a drug were selected. Next, molecular dynamics simulation studies at 200 ns, ΔG calculations using molecular mechanics with generalized Born and surface solvation, and quantum mechanical calculations were performed with the selected compounds. Using this in silico protocol, seven papain-like protease inhibitors are proposed: three compounds with similar free energy (D28, D04, and D59) and three compounds with higher binding free energy (D60, D99, and D06) than the experimentally tested inhibitor, plus one compound (D24) that could bind to the ubiquitin-binding region and reduce the effect on the host immune system. The proposed compounds could be used in in vitro assays, and the described protocol could be used for smart drug design. Full article