Docking studies towards exploring antiviral compounds against envelope protein of yellow fever virus

Computational investigation of antiviral peptide interactions with Mpox DNA polymerase

The Mpox DNA polymerase (DNA pol) plays a crucial role in the viral replication process, making it an ideal target for antiviral therapies. It facilitates the synthetic process of viral DNA, which is an integral stage in the life of a virus. The inhibition of the operation of Mpox DNA pol would interfere with the multiplication of the virus and help manage the disease. Peptides have emerged as a possible therapeutic alternative against viruses due to their distinct characteristics. Peptides have broad-spectrum antiviral activity, being effective against a variety of viruses. Using computational techniques, we attempted to explore the molecular details of the interaction between antiviral peptides and Mpox DNA pol. Two databases of antiviral peptides were screened in this study. This study used molecular docking, followed by molecular dynamics (MD) simulation and post-simulation binding energy predictions. From the 19 selected peptides with activity against DNA polymerases, two peptides-DRAVPe01393 and DRAVPe01399-were identified as particularly promising candidates. These peptides exhibited stable interactions with Mpox DNA pol and demonstrated good cell penetration potential as evident from the MD simulation studies. Notably, the peptides DRAVPe01399 and DRAVPe01393 have a better binding affinity of - 60.86 kcal/mol and - 47.92 kcal/mol respectively than the control ligand Cidofovir diphosphate (- 10.79 kcal/mol). These findings could lead to the development of innovative antiviral treatments to prevent monkeypox, helping global efforts to battle this emerging infectious disease.

Computational Exploration of Potential Pharmacological Inhibitors Targeting the Envelope Protein of the Kyasanur Forest Disease Virus

The limitations of the current vaccination strategy for the Kyasanur Forest Disease virus (KFDV) underscore the critical need for effective antiviral treatments, highlighting the crucial importance of exploring novel therapeutic approaches through in silico drug design. Kyasanur Forest Disease, caused by KFDV, is a tick-borne disease with a mortality of 3-5% and an annual incidence of 400 to 500 cases. In the early stage of infection, the envelope protein plays a crucial role by facilitating host-virus interactions. The objective of this research is to develop effective antivirals targeting the envelope protein to disrupt the virus-host interaction. In line with this, the 3D structure of the envelope protein was modeled and refined through molecular modeling techniques, and subsequently, ligands were designed via de novo design and pharmacophore screening, yielding 12 potential hits followed by ADMET analysis. The top five candidates underwent geometry optimization and molecular docking. Notably, compounds L4 (SA28) and L3 (CNP0247967) are predicted to have significant binding affinities of -8.91 and -7.58 kcal/mol, respectively, toward the envelope protein, based on computational models. Both compounds demonstrated stability during 200 ns molecular dynamics simulations, and the MM-GBSA binding free-energy values were -85.26 ± 4.63 kcal/mol and -66.60 ± 2.92 kcal/mol for the envelope protein L3 and L4 complexes, respectively. Based on the computational prediction, it is suggested that both compounds have potential as drug candidates for controlling host-virus interactions by targeting the envelope protein. Further validation through in-vitro assays would complement the findings of the present in silico investigations.

Virtual Screening, Molecular Docking, and Dynamic Simulations Revealed TGF-β1 Potential Inhibitors to Curtail Cervical Cancer Progression

Cervical cancer is one of the main causes of cancer death in women globally, and its epidemiology is similar to that of a low-infectious venereal illness. Many sexual partners and early age at first intercourse have been demonstrated to have a significant influence on risk. TGF-β1 is a multifunctional cytokine that is required for cervical carcinoma metastasis, tumor development, progression, and invasion. The TGF-β1 signaling system plays a paradoxical function in cancer formation, suppressing early-stage tumor growth while increasing tumor progression and metastasis. Importantly, TGF-β1 and TGF-β receptor 1 (TGF-βR1), two components of the TGF-β signaling system, are substantially expressed in a range of cancers, including breast cancer, colon cancer, gastric cancer, and hepatocellular carcinoma. The current study aims to investigate possible inhibitors targeting TGF-β1 using molecular docking and dynamic simulations. To target TGF-β1, we used anti-cancer drugs and small molecules. MVD was utilized for virtual screening, and the highest scoring compound was then subjected to MD simulations using Schrodinger software package v2017-1 (Maestro v11.1) to identify the most favorable lead interactions against TGF-β1. The Nilotinib compound has shown the least XP Gscore of -2.581 kcal/mol, 30ns MD simulations revealing that the Nilotinib- TGF-β1 complex possesses the lowest energy of -77784.917 kcal/mol. Multiple parameters, including Root Mean Square Deviation, Root Mean Square Fluctuation, and Intermolecular Interactions, were used to analyze the simulation trajectory. Based on the results; we conclude that the ligand nilotinib appears to be a promising prospective TGF-β1inhibitor for reducing TGF-β1 expression ad halting cervical cancer progression.

Comprehensive structural and functional analysis of hVEGFR1: Insights into phosphorylation, molecular interactions, and potential inhibitors through docking and dynamics simulations

Vascular Endothelial Growth Factor Receptor 1 (VEGFR1), is an enzyme with tyrosine kinase activity that plays a pivotal role in angiogenesis, the process of new blood vessel formation. This receptor is of significant clinical importance as it is implicated in various cancers, particularly non-small cell lung cancer (NSCLC), where its dysregulation leads to uncontrolled cell growth through ligand-induced phosphorylation. While commercially available drugs target VEGFR1, their prolonged use often leads to drug resistance and the emergence of mutations in cancer patients. To address these challenges, researchers have identified the human tyrosine kinase (hTK) domain of VEGFR1 as a potential therapeutic marker for lung malignancies. The 3D crystal structure of the hTK domain, obtained from Protein Data Bank (PDB ID: 3HNG), has provided vital structural insights of hVEGFR1. This study has revealed variations within the hVEGFR1 tyrosine kinase domain, distinguishing between regions associated with phosphorylase kinase and transferase activities. We identified numerous potential phosphorylation sites within the TK domain, shedding light on the protein's regulation and signaling possible. Detailed molecular interaction analyses have elucidated the binding forces between lead molecules and hVEGFR1, including hydrogen bonds, electrostatic, hydrophobic, and π-sigma interactions. The stability observed during molecular dynamics simulations further underscores the biological relevance of these interactions. Furthermore, docked complexes has highlighted localized structural fluctuations, offering insight into potential allosteric effects and dynamic conformational changes induced by lead molecules. These findings not only provide a comprehensive characterization of hVEGFR1 but also pave the way for the development of targeted therapies. Eventually, this study has the potential in identifying drug to combat diseases associated with hVEGFR1 dysregulation, including cancer and angiogenesis-related disorders, contributing to effective treatment strategies.

3-deazaadenosine: A promising novel p38γ antagonist with potential as a breast cancer therapeutic agent

Human p38γ protein kinase, or MAPK12, is a crucial signaling protein that is important in channelizing membrane signals to the nucleus in the MAPK cascade pathway, associated with breast and colorectal cancer, besides other forms of malignancies and atherosclerotic lesions too. P38γ has a significant contribution to the progression of breast carcinoma due to its multifaceted functions. Targeting p38γ for defining potent antagonists against p38γ can turn out to be an attractive and novel means of breast cancer therapeutics. Novel and potent lead molecules were designed utilizing computational drug design methodologies. Using high-throughput virtual screening, 1909 geometrically similar analogs of known inhibitors were generated, primarily using BIRB796, SB202190, ANP, CHEBI: 620708, and CHEBI: 524699. Chemical correctness was ensured using LigPrep for the standalone library, and Prep Wizard for p38γ using Maestro v.11.5. Using the Glide v5.5 flexible docking procedure on a standalone library of p38γ binding sites, we defined 18 potential leads and assessed their ADMET properties. Lead "1", among the proposed four p38γ antagonists with high-scoring and favorable interactions, was considered for 100 ns molecular dynamics simulations. Among the four proposed leads, Lead '1' displayed consistent and stable bonding interactions with p38γ throughout the 100 ns molecular dynamics (MD) simulations. Additionally, it formed water bridges, contributing to its strong association with the protein. Notably, Lead '1' (3-deazaadenosine) exhibited favorable root-mean-square deviation (RMSD) and root-mean-square fluctuation (RMSF) within the acceptable range of pharmacological properties. Thus, 3-deazaadenosine and its mimetic might be promising new directions for developing a novel class of antagonists for breast cancer treatment.

Identification of Potential HCV Inhibitors Based on the Interaction of Epigallocatechin-3-Gallate with Viral Envelope Proteins

Hepatitis C is affecting millions of people around the globe annually, which leads to death in very high numbers. After many years of research, hepatitis C virus (HCV) remains a serious threat to the human population and needs proper management. The in silico approach in the drug discovery process is an efficient method in identifying inhibitors for various diseases. In our study, the interaction between Epigallocatechin-3-gallate, a component of green tea, and envelope glycoprotein E2 of HCV is evaluated. Epigallocatechin-3-gallate is the most promising polyphenol approved through cell culture analysis that can inhibit the entry of HCV. Therefore, various in silico techniques have been employed to find out other potential inhibitors that can behave as EGCG. Thus, the homology modelling of E2 protein was performed. The potential lead molecules were predicted using ligand-based as well as structure-based virtual screening methods. The compounds obtained were then screened through PyRx. The drugs obtained were ranked based on their binding affinities. Furthermore, the docking of the topmost drugs was performed by AutoDock Vina, while its 2D interactions were plotted in LigPlot+. The lead compound mms02387687 (2-[[5-[(4-ethylphenoxy) methyl]-4-prop-2-enyl-1,2,4-triazol-3-yl] sulfanyl]-N-[3(trifluoromethyl) phenyl] acetamide) was ranked on top, and we believe it can serve as a drug against HCV in the future, owing to experimental validation.

Remdesivir (GS-5734) as a therapeutic option of 2019-nCOV main protease - in silico approach

2019 – Novel Coronavirus (2019-nCOV), enclosed large genome positive-sense RNA virus characterized by crown-like spikes that protrude from their surface, and have a distinctive replication strategy. The 2019-nCOV belongs to the Coronaviridae family, principally consists of virulent pathogens showing zoonotic property, has emerged as a pandemic outbreak with high mortality and high morbidity rate around the globe and no therapeutic vaccine or drugs against 2019-nCoV are discovered till now. In this study, in silico methods and algorithms were used for sequence, structure analysis and molecular docking on M^pro of 2019-nCOV. The co-crystal structure of 2019-nCOV protease, 6LU7 have ∼99% identity with SARS-CoV protease. The 6LU7 residues, Cys145 and His164 are playing a significant role in replication and are essential for the survival of 2019-nCOV. Alongside, 2019-nCOV M^pro sequence is non-homologous to human host-pathogen. Complete genome sequence analysis, structural and molecular docking results revealed that Remdesivir is having a better binding affinity with -8.2 kcal/mol than the rest of protease inhibitors, and peptide. Remdesivir is strongly forming h-bonds with crucial M^pro residues, Cys145, and His164. Further, MD simulation analysis also confirmed, that these residues are forming H-bond with Remdesivir during 100 ns simulations run and found stable (∼99%) by RMSD and RMSF. Thus, present in silico study at molecular approaches suggest that, Remdesivir is a potent therapeutic inhibitor against 2019-nCoV.

Communicated by Ramaswamy H. Sarma

What Does the Future Hold for Yellow Fever Virus? (II)

As revealed by the recent resurgence of yellow fever virus (YFV) activity in the tropical regions of Africa and South America, YFV control measures need urgent rethinking. Over the last decade, most reported outbreaks occurred in, or eventually reached, areas with low vaccination coverage but that are suitable for virus transmission, with an unprecedented risk of expansion to densely populated territories in Africa, South America and Asia. As reflected in the World Health Organization's initiative launched in 2017, it is high time to strengthen epidemiological surveillance to monitor accurately viral dissemination, and redefine vaccination recommendation areas. Vector-control and immunisation measures need to be adapted and vaccine manufacturing must be reconciled with an increasing demand. We will have to face more yellow fever (YF) cases in the upcoming years. Hence, improving disease management through the development of efficient treatments will prove most beneficial. Undoubtedly, these developments will require in-depth descriptions of YFV biology at molecular, physiological and ecological levels. This second section of a two-part review describes the current state of knowledge and gaps regarding the molecular biology of YFV, along with an overview of the tools that can be used to manage the disease at the individual, local and global levels.

Construction and characterization of a recombinant yellow fever virus stably expressing Gaussia luciferase

Yellow fever is an arthropod-borne viral disease that still poses high public health concerns, despite the availability of an effective vaccine. The development of recombinant viruses is of utmost importance for several types of studies, such as those aimed to dissect virus-host interactions and to search for novel antiviral strategies. Moreover, recombinant viruses expressing reporter genes may greatly facilitate these studies. Here, we report the construction of a recombinant yellow fever virus (YFV) expressing Gaussia luciferase (GLuc) (YFV-GLuc). We show, through RT-PCR, sequencing and measurement of GLuc activity, that stability of the heterologous gene was maintained after six passages. Furthermore, a direct association between GLuc expression and viral replication was observed (r2=0.9967), indicating that measurement of GLuc activity may be used to assess viral replication in different applications. In addition, we evaluated the use of the recombinant virus in an antiviral assay with recombinant human alfa-2b interferon. A 60% inhibition of GLuc expression was observed in cells infected with YFV-GLuc and incubated with IFN alfa-2b. Previously tested on YFV inhibition by plaque assays indicated a similar fold-decrease in viral replication. These results are valuable as they show the stability of YFV-GLuc and one of several possible applications of this construct.

Frog skin cultures secrete anti-yellow fever compounds

There is an urgent need to develop novel antimicrobial substances. Antimicrobial peptides (AMPs) are considered as promising candidates for future therapeutic use. Because of the re-emergence of the Flavivirus infection, and particularly the yellow fever virus (YFV), we have compared the antiviral activities from skin secretions of seven different frog species against YFV (strain 17D). Secretions from Sphaenorhynchus lacteus, Cryptobatrachus boulongeri and Leptodactylus fuscus displayed the more powerful activities. S. lacteus was found to inhibit viral lysis of Vero E6 cells even at the highest viral concentration evaluated of 10 LD₅₀. We also report the identification of a novel frenatin-related peptide from S. lacteus and found that this peptide-on its own-can lead to 35% protection against YVF, while displaying no cytotoxicity against somatic cells even at fivefold higher concentrations. These results are attractive and support the need for continued exploration of new sources of AMPs from frog skin secretions such as those described here in the development of new compounds for the treatment of infectious diseases in general and specific viral infections in particular.

Inhibitor design against JNK1 through e-pharmacophore modeling docking and molecular dynamics simulations

c-Jun-NH2 terminal kinases (JNKs) come under a class of serine/threonine protein kinases and are encoded by three genes, namely JNK1, JNK2 and JNK3. Human JNK1 is a cytosolic kinase belonging to mitogen-activated protein kinase (MAPK) family, which plays a major role in intracrinal signal transduction cascade mechanism. Overexpressed human JNK1, a key kinase interacts with other kinases involved in the etiology of many cancers, such as skin cancer, liver cancer, breast cancer, brain tumors, leukemia, multiple myeloma and lymphoma. Thus, to unveil a novel human JNK1 antagonist, receptor-based pharmacophore modeling was performed with the available eighteen cocrystal structures of JNK1 in the protein data bank. Eighteen e-pharmacophores were generated from the 18 cocrystal structures. Four common e-pharmacophores were developed from the 18 e-pharmacophores, which were used as three-dimensional (3D) query for shape-based similarity screening against more than one million small molecules to generate a JNK1 ligand library. Rigid receptor docking (RRD) performed using GLIDE v6.3 for the 1683 compounds from in-house library and 18 cocrystal ligands with human JNK1 from lower stringency to higher stringency revealed 17 leads. Further to derive the best leads, dock complexes obtained from RRD were studied further with quantum-polarized ligand docking (QPLD), induced fit docking (IFD) and molecular mechanics/generalized Born surface area (MM-GBSA). Four leads have showed lesser binding free energy and better binding affinity towards JNK1 compared to 18 cocrystal ligands. Additionally, JNK1-lead1 complex interaction stability was reasserted using 50 ns MD simulations run and also compared with the best resolute cocrystal structure using Desmond v3.8. Thus, the results obtained from RRD, QPLD, IFD and MD simulations indicated that lead1 might be used as a potent antagonist toward human JNK1 in cancer therapeutics.

E-pharmacophore-based virtual screening to identify GSK-3β inhibitors

Glycogen synthase kinase-3β (GSK-3β) is a serine/threonine kinase which has attracted significant attention during recent years in drug design studies. The deregulation of GSK-3β increased the loss of hippocampal neurons by triggering apoptosis-mediating production of neurofibrillary tangles and alleviates memory deficits in Alzheimer's disease (AD). Given its role in the formation of neurofibrillary tangles leading to AD, it has been a major therapeutic target for intervention in AD, hence was targeted in the present study. Twenty crystal structures were refined to generate pharmacophore models based on energy involvement in binding co-crystal ligands. Four common e-pharmacophore models were optimized from the 20 pharmacophore models. Shape-based screening of four e-pharmacophore models against nine established small molecule databases using Phase v3.9 had resulted in 1800 compounds having similar pharmacophore features. Rigid receptor docking (RRD) was performed for 1800 compounds and 20 co-crystal ligands with GSK-3β to generate dock complexes. Interactions of the best scoring lead obtained through RRD were further studied with quantum polarized ligand docking (QPLD), induced fit docking (IFD) and molecular mechanics/generalized Born surface area. Comparing the obtained leads to 20 co-crystal ligands resulted in 18 leads among them, lead1 had the lowest docking score, lower binding free energy and better binding orientation toward GSK-3β. The 50 ns MD simulations run confirmed the stable nature of GSK-3β-lead1 docking complex. The results from RRD, QPLD, IFD and MD simulations confirmed that lead1 might be used as a potent antagonist for GSK-3β.

Integrating sampling techniques and inverse virtual screening: toward the discovery of artificial peptide-based receptors for ligands

A novel heuristic using an iterative select-and-purge strategy is proposed. It combines statistical techniques for sampling and classification by rigid molecular docking through an inverse virtual screening scheme. This approach aims to the de novo discovery of short peptides that may act as docking receptors for small target molecules when there are no data available about known association complexes between them. The algorithm performs an unbiased stochastic exploration of the sample space, acting as a binary classifier when analyzing the entire peptides population. It uses a novel and effective criterion for weighting the likelihood of a given peptide to form an association complex with a particular ligand molecule based on amino acid sequences. The exploratory analysis relies on chemical information of peptides composition, sequence patterns, and association free energies (docking scores) in order to converge to those peptides forming the association complexes with higher affinities. Statistical estimations support these results providing an association probability by improving predictions accuracy even in cases where only a fraction of all possible combinations are sampled. False positives/false negatives ratio was also improved with this method. A simple rigid-body docking approach together with the proper information about amino acid sequences was used. The methodology was applied in a retrospective docking study to all 8000 possible tripeptide combinations using the 20 natural amino acids, screened against a training set of 77 different ligands with diverse functional groups. Afterward, all tripeptides were screened against a test set of 82 ligands, also containing different functional groups. Results show that our integrated methodology is capable of finding a representative group of the top-scoring tripeptides. The associated probability of identifying the best receptor or a group of the top-ranked receptors is more than double and about 10 times higher, respectively, when compared to classical random sampling methods.

In Silico Approach to Support that p-Nitrophenol Monooxygenase from Arthrobacter sp. Strain JS443 Catalyzes the Initial Two Sequential Monooxygenations

p-Nitrophenol (PNP), used primarily for manufacturing pesticides and dyes, has been recognized as a priority environmental pollutant. It is therefore important to reduce the input of this toxicant into the environment and to establish approaches for its removal from the contaminated sites. PNP monooxygenase, a novel enzyme from Gram-positive bacteria like Arthrobacter sp. and Bacillus sp., that comprises two components, a flavoprotein reductase and an oxygenase, catalyzes the initial two sequential monooxygenations to convert PNP to trihydroxybenzene. Accurate and reliable prediction of this enzyme-substrate interactions and binding affinity are of vital importance in understanding these catalytic mechanisms of the two sequential reactions. As crystal structure of the enzyme has not yet been published, we built a homology model for PNP monooxygenase using crystallized chlorophenol 4-monooxygenase from Burkholderia cepacia AC1100 (3HWC) as the template. The model was assessed for its reliability using PROCHECK, ERRAT and ProSA. Molecular docking of the physiological substrates, PNP and 4-nitrocatechol (4-NC), was carried out using Glide v5.7 implemented in Maestro v9.2, and the binding energies were calculated to substantiate the prediction. Docking complexes formed by molecular level interactions of PNP monooxygenase-PNP/4-NC without or with the cofactors, FAD and NADH, showed good correlation with the established experimental evidence that the two-component PNP monooxygenase catalyzes both the hydroxylation of PNP and the oxidative release of nitrite from 4-NC in B. sphaericus JS905. Furthermore, molecular dynamics simulations performed for docking complexes using Desmond v3.0 showed stable nature of the interactions as well.

Experimental therapies for yellow fever

A number of viruses in the family Flaviviridae are the focus of efforts to develop effective antiviral therapies. Success has been achieved with inhibitors for the treatment of hepatitis C, and there is interest in clinical trials of drugs against dengue fever. Antiviral therapies have also been evaluated in patients with Japanese encephalitis and West Nile encephalitis. However, no treatment has been developed against the prototype flavivirus, yellow fever virus (YFV). Despite the availability of the live, attenuated 17D vaccine, thousands of cases of YF continue to occur each year in Africa and South America, with a significant mortality rate. In addition, a small number of vaccinees develop severe systemic infections with the 17D virus. This paper reviews current efforts to develop antiviral therapies, either directly targeting the virus or blocking detrimental host responses to infection.

In silico virtual screening approaches for anti-viral drug discovery

Despite the considerable advances in medical and pharmaceutical research during the past years, diseases caused by viruses have remained a major burden to public health. Virtual in silico screening has repeatedly proven to be useful to meet the special challenges of antiviral drug discovery. Large virtual compound libraries are filtered by different computational screening methods such as docking, ligand-based similarity searches or pharmacophore-based screening, reducing the number of candidate molecules to a smaller set of promising candidates that are then tested biologically. This rational approach makes the drug discovery process more goal-oriented and saves resources in terms of time and money. In this review we discuss how different virtual screening techniques can be applied to antiviral drug discovery, present recent success stories in this field and finally address the main differences between the methods.: