Exploring the Antiviral Potential of Natural Compounds against Influenza: A Combined Computational and Experimental Approach.

The influenza A virus nonstructural protein 1 (NS1), which is crucial for viral replication and immune evasion, has been identified as a significant drug target with substantial potential to contribute to the fight against influenza. The emergence of drug-resistant influenza A virus strains highlights the urgent need for novel therapeutics. This study proposes a combined theoretical criterion for the virtual screening of molecular libraries to identify candidate NS1 inhibitors. By applying the criterion to the ZINC Natural Product database, followed by ligand-based virtual screening and molecular docking, we proposed the most promising candidate as a potential NS1 inhibitor. Subsequently, the selected natural compound was experimentally evaluated, revealing measurable virus replication inhibition activity in cell culture. This approach offers a promising avenue for developing novel anti-influenza agents targeting the NS1 protein.

Computational Modeling and Characterization of Peptides Derived from Nanobody Complementary-Determining Region 2 (CDR2) Targeting Active-State Conformation of the ß2-Adrenergic Receptor (ß2AR).

This study assessed the suitability of the complementarity-determining region 2 (CDR2) of the nanobody (Nb) as a template for the derivation of nanobody-derived peptides (NDPs) targeting active-state ß2-adrenergic receptor (ß2AR) conformation. Sequences of conformationally selective Nbs favoring the agonist-occupied ß2AR were initially analyzed by the informational spectrum method (ISM). The derived NDPs in complex with ß2AR were subjected to protein-peptide docking, molecular dynamics (MD) simulations, and metadynamics-based free-energy binding calculations. Computational analyses identified a 25-amino-acid-long CDR2-NDP of Nb71, designated P4, which exhibited the following binding free-energy for the formation of the ß2AR:P4 complex (ΔG = -6.8 ± 0.8 kcal/mol or a Ki = 16.5 µM at 310 K) and mapped the ß2AR:P4 amino acid interaction network. In vitro characterization showed that P4 (i) can cross the plasma membrane, (ii) reduces the maximum isoproterenol-induced cAMP level by approximately 40% and the isoproterenol potency by up to 20-fold at micromolar concentration, (iii) has a very low affinity to interact with unstimulated ß2AR in the cAMP assay, and (iv) cannot reduce the efficacy and potency of the isoproterenol-mediated ß2AR/ß-arrestin-2 interaction in the BRET2-based recruitment assay. In summary, the CDR2-NDP, P4, binds preferentially to agonist-activated ß2AR and disrupts Gαs-mediated signaling.

Novel Entropy-Based Phylogenetic Algorithm: A New Approach for Classifying SARS-CoV-2 Variants.

The SARS-CoV-2 virus, the causative agent of COVID-19, is known for its genetic diversity. Virus variants of concern (VOCs) as well as variants of interest (VOIs) are classified by the World Health Organization (WHO) according to their potential risk to global health. This study seeks to enhance the identification and classification of such variants by developing a novel bioinformatics criterion centered on the virus's spike protein (SP1), a key player in host cell entry, immune response, and a mutational hotspot. To achieve this, we pioneered a unique phylogenetic algorithm which calculates EIIP-entropy as a distance measure based on the distribution of the electron-ion interaction potential (EIIP) of amino acids in SP1. This method offers a comprehensive, scalable, and rapid approach to analyze large genomic data sets and predict the impact of specific mutations. This innovative approach provides a robust tool for classifying emergent SARS-CoV-2 variants into potential VOCs or VOIs. It could significantly augment surveillance efforts and understanding of variant characteristics, while also offering potential applicability to the analysis and classification of other emerging viral pathogens and enhancing global readiness against emerging and re-emerging viral pathogens.

In Silico Investigation of Selected Pesticides and Their Determination in Agricultural Products Using QuEChERS Methodology and HPLC-DAD.

In this study, we considered some pesticides as active substances within formulations for the protection of plant-based food in the Republic of Serbia in silico, because these pesticides have not often been investigated in this way previously, and in an analytical way, because there are not very many available fast, cheap, and easy methods for their determination in real agricultural samples. Seven pesticides were detected in selected agricultural products (tomatoes, cucumbers, peppers, and grapes) using the QuEChERS methodology and HPLC-DAD. Standard curves for the investigated pesticides (chlorantraniliprole, methomyl, metalaxyl, thiacloprid, acetamiprid, emamectin benzoate, and cymoxanil) show good linearity, with R2 values from 0.9785 to 0.9996. The HPLC-DAD method is fast, and these pesticides can be determined in real spiked samples in less than 15 min. We further characterized the pesticides we found in food based on physicochemical properties and molecular descriptors to predict the absorption, distribution, metabolism, elimination, and toxicity (ADMET) of the compounds. We summarized the data supporting their effects on humans using various computational tools to determine their potential adverse effects. The results of our prediction study show that all of the selected pesticides considered in this study have good oral bioavailability, and those with high toxicity, therefore, could be harmful to human health. Chlorantraniliprole was shown in a molecular docking study as a good starting point for a new Alzheimer's disease drug candidate.

In Silico and In Vitro Inhibition of SARS-CoV-2 PLpro with Gramicidin D.

Finding an effective drug to prevent or treat COVID-19 is of utmost importance in tcurrent pandemic. Since developing a new treatment takes a significant amount of time, drug repurposing can be an effective option for achieving a rapid response. This study used a combined in silico virtual screening protocol for candidate SARS-CoV-2 PLpro inhibitors. The Drugbank database was searched first, using the Informational Spectrum Method for Small Molecules, followed by molecular docking. Gramicidin D was selected as a peptide drug, showing the best in silico interaction profile with PLpro. After the expression and purification of PLpro, gramicidin D was screened for protease inhibition in vitro and was found to be active against PLpro. The current study's findings are significant because it is critical to identify COVID-19 therapies that are efficient, affordable, and have a favorable safety profile.

Inhibition of SARS-CoV-2 Mpro with Vitamin C, L-Arginine and a Vitamin C/L-Arginine Combination.

BACKGROUND: Drug resistance is a critical problem in health care that affects therapy outcomes and requires new approaches to drug design. SARS-CoV-2 Mpro mutations are of concern as they can potentially reduce therapeutic efficacy. Viral infections are amongst the many disorders for which nutraceuticals have been employed as an adjunct therapy. The aim of this study was to examine the potential in vitro activity of L-arginine and vitamin C against SARS-CoV-2 Mpro. METHODS: The Mpro inhibition assay was developed by cloning, expression, purification, and characterization of Mpro. Selected compounds were then screened for protease inhibition. RESULTS: L-arginine was found to be active against SARS-CoV-2 Mpro, while a vitamin C/L-arginine combination had a synergistic antiviral action against Mpro. These findings confirm the results of our previous in silico repurposing study that showed L-arginine and vitamin C were potential Mpro inhibitors. Moreover, they suggest a possible molecular mechanism to explain the beneficial effect of arginine in COVID patients. CONCLUSIONS: The findings of the current study are important because they help to identify COVID-19 treatments that are efficient, inexpensive, and have a favorable safety profile. The results of this study also suggest a possible adjuvant nutritional strategy for COVID-19 that could be used in conjunction with pharmacological agents.

Patterns of human and porcine gammaherpesvirus-encoded BILF1 receptor endocytosis.

BACKGROUND: The viral G-protein-coupled receptor (vGPCR) BILF1 encoded by the Epstein-Barr virus (EBV) is an oncogene and immunoevasin and can downregulate MHC-I molecules at the surface of infected cells. MHC-I downregulation, which presumably occurs through co-internalization with EBV-BILF1, is preserved among BILF1 receptors, including the three BILF1 orthologs encoded by porcine lymphotropic herpesviruses (PLHV BILFs). This study aimed to understand the detailed mechanisms of BILF1 receptor constitutive internalization, to explore the translational potential of PLHV BILFs compared with EBV-BILF1. METHODS: A novel real-time fluorescence resonance energy transfer (FRET)-based internalization assay combined with dominant-negative variants of dynamin-1 (Dyn K44A) and the chemical clathrin inhibitor Pitstop2 in HEK-293A cells was used to study the effect of specific endocytic proteins on BILF1 internalization. Bioluminescence resonance energy transfer (BRET)-saturation analysis was used to study BILF1 receptor interaction with ß-arrestin2 and Rab7. In addition, a bioinformatics approach informational spectrum method (ISM) was used to investigate the interaction affinity of BILF1 receptors with ß-arrestin2, AP-2, and caveolin-1. RESULTS: We identified dynamin-dependent, clathrin-mediated constitutive endocytosis for all BILF1 receptors. The observed interaction affinity between BILF1 receptors and caveolin-1 and the decreased internalization in the presence of a dominant-negative variant of caveolin-1 (Cav S80E) indicated the involvement of caveolin-1 in BILF1 trafficking. Furthermore, after BILF1 internalization from the plasma membrane, both the recycling and degradation pathways are proposed for BILF1 receptors. CONCLUSIONS: The similarity in the internalization mechanisms observed for EBV-BILF1 and PLHV1-2 BILF1 provide a foundation for further studies exploring a possible translational potential for PLHVs, as proposed previously, and provides new information about receptor trafficking.

In Silico Screening of Natural Compounds for Candidates 5HT6 Receptor Antagonists against Alzheimer's Disease.

Alzheimer's disease (AD), a devastating neurodegenerative disease, is the focus of pharmacological research. One of the targets that attract the most attention for the potential therapy of AD is the serotonin 5HT6 receptor, which is the receptor situated exclusively in CNS on glutamatergic and GABAergic neurons. The neurochemical impact of this receptor supports the hypothesis about its role in cognitive, learning, and memory systems, which are of critical importance for AD. Natural products are a promising source of novel bioactive compounds with potential therapeutic potential as a 5HT6 receptor antagonist in the treatment of AD dementia. The ZINC-natural product database was in silico screened in order to find the candidate antagonists of 5-HT6 receptor against AD. A virtual screening protocol that includes both short-and long-range interactions between interacting molecules was employed. First, the EIIP/AQVN filter was applied for in silico screening of the ZINC database followed by 3D QSAR and molecular docking. Ten best candidate compounds were selected from the ZINC Natural Product database as potential 5HT6 Receptor antagonists and were proposed for further evaluation. The best candidate was evaluated by molecular dynamics simulations and free energy calculations.

Simple Theoretical Criterion for Selection of Natural Compounds with Anti-COVID-19 Activity.

BACKGROUND: A novel human coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has become the leading threat to global health. An effective antiviral could not only help those still vulnerable to the virus but could be a critical treatment if a virus emerges toward evading coronavirus disease 2019 (COVID-19) vaccines. Despite the significant efforts to test already-approved drugs for their potential to kill the virus, researchers found very few actually worked. METHODS: The present report uses the electronic molecular descriptors, the quasi-valence number (AQVN), and the electron-ion interaction potential (EIIP), for the analysis of natural compounds with proven therapeutic activity against the COVID-19. RESULTS: Based on the analysis of the electronic properties of natural compounds which are effective against SARS-CoV-2 virus the simple theoretical criterion for the selection of candidate compounds for the treatment of COVID-19 is proposed. CONCLUSIONS: The proposed theoretical criterion can be used for the identification and optimization of new lead compounds for the treatment of the COVID-19 disease and for the selection of the food and food supplements which could have a beneficial effect on COVID-19 patients.

Identification of SARS-CoV-2 Papain-like Protease (PLpro) Inhibitors Using Combined Computational Approach.

In the current pandemic, finding an effective drug to prevent or treat the infection is the highest priority. A rapid and safe approach to counteract COVID-19 is in silico drug repurposing. The SARS-CoV-2 PLpro promotes viral replication and modulates the host immune system, resulting in inhibition of the host antiviral innate immune response, and therefore is an attractive drug target. In this study, we used a combined in silico virtual screening for candidates for SARS-CoV-2 PLpro protease inhibitors. We used the Informational spectrum method applied for Small Molecules for searching the Drugbank database followed by molecular docking. After in silico screening of drug space, we identified 44 drugs as potential SARS-CoV-2 PLpro inhibitors that we propose for further experimental testing.

Critical Impact of Different Conserved Endoplasmic Retention Motifs and Dopamine Receptor Interacting Proteins (DRIPs) on Intracellular Localization and Trafficking of the D2 Dopamine Receptor (D2-R) Isoforms.

The type 2 dopamine receptor D2 (D2-R), member of the G protein-coupled receptor (GPCR) superfamily, exists in two isoforms, short (D2S-R) and long (D2L-R). They differ by an additional 29 amino acids (AA) in the third cytoplasmic loop (ICL3) of the D2L-R. These isoforms differ in their intracellular localization and trafficking functionality, as D2L-R possesses a larger intracellular pool, mostly in the endoplasmic reticulum (ER). This review focuses on the evolutionarily conserved motifs in the ICL3 of the D2-R and proteins interacting with the ICL3 of both isoforms, specifically with the 29 AA insert. These motifs might be involved in D2-R exit from the ER and have an impact on cell-surface and intracellular localization and, therefore, also play a role in the function of dopamine receptor signaling, ligand binding and possible homo/heterodimerization. Our recent bioinformatic data on potential new interaction partners for the ICL3 of D2-Rs are also presented. Both are highly relevant, and have clinical impacts on the pathophysiology of several diseases such as Parkinson's disease, schizophrenia, Tourette's syndrome, Huntington's disease, manic depression, and others, as they are connected to a variety of essential motifs and differences in communication with interaction partners.

Drug Repurposing for Candidate SARS-CoV-2 Main Protease Inhibitors by a Novel In Silico Method.

The SARS-CoV-2 outbreak caused an unprecedented global public health threat, having a high transmission rate with currently no drugs or vaccines approved. An alternative powerful additional approach to counteract COVID-19 is in silico drug repurposing. The SARS-CoV-2 main protease is essential for viral replication and an attractive drug target. In this study, we used the virtual screening protocol with both long-range and short-range interactions to select candidate SARS-CoV-2 main protease inhibitors. First, the Informational spectrum method applied for small molecules was used for searching the Drugbank database and further followed by molecular docking. After in silico screening of drug space, we identified 57 drugs as potential SARS-CoV-2 main protease inhibitors that we propose for further experimental testing.

Biological Rationale for the Repurposing of BCG Vaccine against SARS-CoV-2.

The Bacillus Calmette-Guerin vaccine is still widely used in the developing world. The vaccination prevents infant death not only from tuberculosis but also from unrelated infectious agents, especially respiratory tract infections and neonatal sepsis. It is proposed that these off-target protective effects of the BCG vaccine are mediated by the general long-term boosting of innate immune mechanisms, also termed "trained innate immunity". Recent studies indicate that both COVID-19 incidence and total deaths are strongly associated with the presence or absence of national mandatory BCG vaccination programs and encourage the initiation of several clinical studies with the expectation that revaccination with BCG could reduce the incidence and severity of COVID-19. Here, presented results from the bioinformatics analysis of the Mycobacterium bovis (strain BCG/Pasteur 1173P2) proteome suggests four immunodominant antigens that could induce an immune response against SARS-CoV-2.

Computational design and characterization of nanobody-derived peptides that stabilize the active conformation of the ß2-adrenergic receptor (ß2-AR).

This study aimed to design and functionally characterize peptide mimetics of the nanobody (Nb) related to the ß2-adrenergic receptor (ß2-AR) (nanobody-derived peptide, NDP). We postulated that the computationally derived and optimized complementarity-determining region 3 (CDR3) of Nb is sufficient for its interaction with receptor. Sequence-related Nb-families preferring the agonist-bound active conformation of ß2-AR were analysed using the informational spectrum method (ISM) and ß2-AR:NDP complexes studied using protein-peptide docking and molecular dynamics (MD) simulations in conjunction with metadynamics calculations of free energy binding. The selected NDP of Nb71, designated P3, was 17 amino acids long and included CDR3. Metadynamics calculations yielded a binding free energy for the ß2-AR:P3 complex of ΔG = (-7.23 ± 0.04) kcal/mol, or a Kd of (7.9 ± 0.5) µM, for T = 310 K. In vitro circular dichroism (CD) spectropolarimetry and microscale thermophoresis (MST) data provided additional evidence for P3 interaction with agonist-activated ß2-AR, which displayed ~10-fold higher affinity for P3 than the unstimulated receptor (MST-derived EC50 of 3.57 µM vs. 58.22 µM), while its ability to inhibit the agonist-induced interaction of ß2-AR with ß-arrestin 2 was less evident. In summary, theoretical and experimental evidence indicated that P3 preferentially binds agonist-activated ß2-AR.

Novel electrophilic amides amenable by the Ugi reaction perturb thioredoxin system via thioredoxin reductase 1 (TrxR1) inhibition: Identification of DVD-445 as a new lead compound for anticancer therapy.

A series of peptidomimetic compounds incorporating an electrophilic moiety was synthesized using the Ugi reaction. These compounds (termed the Ugi Michael acceptors or UMAs) were designed to target the selenocysteine catalytic residue of thioredoxin reductase 1 (TrxR1), a promising cancer target. The compounds were assessed for their potential to inhibit TrxR1 using human neuroblastoma (SH-SY5Y) cell lysate. Based on this initial screening, six compounds were selected for testing against recombinant rat TrxR1 and in the insulin assay to reveal low-micromolar to submicromolar potency of these inhibitors. The same frontrunner compounds were evaluated for their ability to exert antiproliferative activity and induce cell death and this activity was compared to the UMA effects on the levels of reactive oxygen and nitrogen species (RONS). Collectively, the UMA compounds class presented itself as a rich source of leads for TrxR1 inhibitor discovery for anticancer application. Compound 7 (DVD-445) was nominated a lead for further optimization.

Synthesis, In Silico, and In Vitro Evaluation of Anti-Leishmanial Activity of Oxadiazoles and Indolizine Containing Compounds Flagged against Anti-Targets.

Due to the lack of approved vaccines against human leishmaniasis and the limitations of the current chemotherapy inducing side effects and drug resistance, development of new, effective chemotherapeutic agents is essential. This study describes the synthesis of a series of novel oxadiazoles and indolizine-containing compounds. The compounds were screened in silico using an EIIP/AQVN filter followed by ligand-based virtual screening and molecular docking to parasite arginase. Top hits were further screened versus human arginase and finally against an anti-target battery to tag their possible interactions with proteins essential for the metabolism and clearance of many substances. Eight candidate compounds were selected for further experimental testing. The results show measurable in vitro anti-leishmanial activity for three compounds. One compound with an IC50 value of 2.18 µM on Leishmania donovani intramacrophage amastigotes is clearly better positioned than the others as an interesting molecular template for further development of new anti-leishmanial agents.

Virtual Screen for Repurposing of Drugs for Candidate Influenza a M2 Ion-Channel Inhibitors.

Influenza A virus (IAV) matrix protein 2 (M2), an ion channel, is crucial for virus infection, and therefore, an important anti-influenza drug target. Adamantanes, also known as M2 channel blockers, are one of the two classes of Food and Drug Administration-approved anti-influenza drugs, although their use was discontinued due to prevalent drug resistance. Fast emergence of resistance to current anti-influenza drugs have raised an urgent need for developing new anti-influenza drugs against resistant forms of circulating viruses. Here we propose a simple theoretical criterion for fast virtual screening of molecular libraries for candidate anti-influenza ion channel inhibitors both for wild type and adamantane-resistant influenza A viruses. After in silico screening of drug space using the EIIP/AQVN filter and further filtering of drugs by ligand based virtual screening and molecular docking we propose the best candidate drugs as potential dual inhibitors of wild type and adamantane-resistant influenza A viruses. Finally, guanethidine, the best ranked drug selected from ligand-based virtual screening, was experimentally tested. The experimental results show measurable anti-influenza activity of guanethidine in cell culture.

Functional characterization of ß2-adrenergic and insulin receptor heteromers.

This study aimed to functionally characterize ß2-adrenergic (ß2AR) and insulin receptor (IR) heteromers in regard to ß-arrestin 2 (ßarr2) recruitment and cAMP signaling and to examine the involvement of the cytoplasmic portion of the IR ß chain in heteromerization with ß2AR. Evidence for ß2AR:IR:ßarr2 complex formation and the specificity of the IR:ßarr2 interaction was first provided by bioinfomatics analysis. Receptor-heteromer investigation technology (HIT) then provided functional evidence of ß2AR:IR heterodimerization by showing isoproterenol-induced but not insulin-induced GFP2-ßarr2 recruitment to the ß2AR:IR complex; the IR:ßarr2 interaction was found to only be constitutive. The constitutive IR:ßarr2 BRET signal (BRETconst) was significantly smaller in cells coexpressing IR-RLuc8 and a GFP2-ßarr2 1-185 mutant lacking the proposed IR binding domain. ß2AR:IR heteromerization also influenced the pharmacological phenotype of ß2AR, i.e., its efficacy in recruiting ßarr2 and activating cAMP signaling. Evidence suggesting involvement of the cytoplasmic portion of the IR ß chain in the interaction with ß2AR was provided by BRET2 saturation and HIT assays using an IR 1-1271 stop mutant lacking the IR C-terminal tail region. For the complex consisting of IR 1-1271-RLuc8:ß2AR-GFP2, saturation was not reached, most likely reflecting random collisions between IR 1-1271 and ß2AR. Furthermore, in the HIT assay, no substantial agonist-induced increase in the BRET2 signal was detected that would be indicative of ßarr2 recruitment to the IR 1-1271:ß2AR heteromer. Complementary 3D visualization of ß2AR:IR provided supporting evidence for stability of the heterotetramer complex and identified amino acid residues involved in ß2AR:IR heteromerization. This article is part of the Special Issue entitled 'Receptor heteromers and their allosteric receptor-receptor interactions'.