DenvInD: dengue virus inhibitors database for clinical and molecular research

Allosteric inhibition of dengue virus RNA-dependent RNA polymerase by Litsea cubeba phytochemicals: a computational study

RNA-dependent RNA polymerase (RdRp) is considered a potential drug target for dengue virus (DENV) inhibition and has attracted attention in antiviral drug discovery. Here, we screened 121 natural compounds from Litsea cubeba against DENV RdRp using various approaches of computer-based drug discovery. Notably, we identified four potential compounds (Ushinsunine, Cassameridine, (+)-Epiexcelsin, (-)-Phanostenine) with good binding scores and allosteric interactions with the target protein. Moreover, molecular dynamics simulation studies were done to check the conformational stability of the complexes under given conditions. Additionally, we performed post-simulation analysis to find the stability of potential drugs in the target protein. The findings suggest Litsea cubeba-derived phytomolecules as a therapeutic solution to control DENV infection.Communicated by Ramaswamy H. Sarma.

Application of temperature-dependent and steered molecular dynamics simulation to screen anti-dengue compounds against Marburg virus

Marburg virus infections are extremely fatal with a fatality range of 23% to 90%, therefore there is an urgent requirement to design and develop efficient therapeutic molecules. Here, a comprehensive temperature-dependent molecular dynamics (MD) simulation method was implemented to identify the potential molecule from the anti-dengue compound library that can inhibit the function of the VP24 protein of Marburg. Virtual high throughput screening identified five effective binders of VP24 after screening 484 anti-dengue compounds. These compounds were treated in MD simulation at four different temperatures: 300, 340, 380, and 420 K. Higher temperatures showed dissociation of hit compounds from the protein. Further, triplicates of 100 ns MD simulation were conducted which showed that compounds ID = 118717693, and ID = 5361 showed strong stability with the protein molecule. These compounds were further validated using Δ G binding free energies and they showed: -30.38 kcal/mol, and -67.83 kcal/mol binding free energies, respectively. Later, these two compounds were used in steered MD simulation to detect its dissociation. Compound ID = 5361 showed the maximum pulling force of 199.02 kcal/mol/nm to dissociate the protein-ligand complex while ID = 118717693 had a pulling force of 101.11 kcal/mol/nm, respectively. This ligand highest number of hydrogen bonds with varying occupancies at 89.93%, 69.80%, 57.93%, 52.33%, and 50.63%. This study showed that ID = 5361 can bind with the VP24 strongly and has the potential to inhibit its function which can be validated in the in-vitro experiment.Communicated by Ramaswamy H. Sarma.

Assessing the inhibitory potential of anti-dengue compounds against Japanese encephalitis virus RNA dependent RNA polymerase: an in silico study

Japanese encephalitis (JE), a neurological infection of severe nature, is caused by the Japanese encephalitis virus (JEV) and is transmitted by the mosquito vector. The polymerase domain of Non-structural 5 (NS5), which is also referred to as RdRp (RNA-dependent RNA polymerase), is considered a potential therapeutic target for JEV. The present study employed molecular dynamics modelling and high-throughput virtual screening to evaluate the possible antiviral activity of anti-dengue drugs against JEV RdRp. Furthermore, a ranking was performed utilising the MM/GBSA analysis to identify the three most promising compounds. Compound ID 57409246 exhibited the highest binding affinity with the protein, as evidenced by its minimum binding free energy of -72.96 kcal/mole. In contrast, the other two compounds had minimum binding free energies of -67.57 and -59.19 kcal/mole, respectively. Upon conducting a 100 nanosecond molecular dynamics simulation to confirm the binding of the chemical complexes, it was observed that the three hits, namely 57409246, 70683874, and 44577154, exhibited a consistent and stable RMSD. Subsequently, the binding strength of the trajectory was confirmed through MM/GBSA analysis. The compounds 70683874 and 57409246 exhibited the lowest binding free energies, which were -97.58 kcal/mol and -96.38 kcal/mol, respectively. The binding free energy (ΔG Bind) values for the native ligand ATP and molecule 44577154 were -65.64 kcal/mol and -69.44 kcal/mol, respectively. Overall, compared to the native ligand ATP, all three compounds exhibited higher binding affinity. The study proposes three anti-dengue molecules as a potential remedy for JE, which can be confirmed through in vitro and in vivo investigations.Communicated by Ramaswamy H. Sarma.

Investigating the Mechanism of Action of Anti-Dengue Compounds as Potential Binders of Zika Virus RNA-Dependent RNA Polymerase

The World Health Organization (WHO) has designated the Zika virus (ZIKV) as a significant risk to the general public's health. Currently, there are no vaccinations or medications available to treat or prevent infection with the Zika virus. Thus, it is urgently required to develop a highly efficient therapeutic molecule. In the presented study, a computationally intensive search was carried out to identify potent compounds that have the potential to bind and block the activity of ZIKV NS5 RNA-dependent RNA polymerase (RdRp). The anti-dengue chemical library was subjected to high-throughput virtual screening and MM/GBSA analysis in order to rate the potential candidates. The top three compounds were then chosen. According to the MM/GBSA analysis, compound 127042987 from the database had the highest binding affinity to the protein with a minimum binding free energy of -77.16 kcal/mole. Compound 127042987 had the most stable RMSD trend and the greatest number of hydrogen bond interactions when these chemical complexes were evaluated further under a 100 ns molecular dynamics simulation. Compound 127042987 displayed the best binding free energy (GBind) of -96.50 kcal/mol, surpassing the native ligand binding energy (-66.17 kcal/mole). Thereafter, an MM/GBSA binding free energy study was conducted to validate the stability of selected chemical complexes. Overall, this study illustrated that compound 127042987 showed preferred binding free energies, suggesting a possible inhibitory mechanism against ZIKV-RdRp. As per this study, it was proposed that compound 127042987 could be used as a therapeutic option to prevent Zika virus infection. These compounds need to be tested in experiments for further validation.

Ligand-based pharmacophore modeling and QSAR approach to identify potential dengue protease inhibitors

The viral disease dengue is transmitted by the Aedes mosquito and is commonly seen to occur in the tropical and subtropical regions of the world. It is a growing public health concern. To date, other than supportive treatments, there are no specific antiviral treatments to combat the infection. Therefore, finding potential compounds that have antiviral activity against the dengue virus is essential. The NS2B-NS3 dengue protease plays a vital role in the replication and viral assembly. If the functioning of this protease were to be obstructed then viral replication would be halted. As a result, this NS2B-NS3 proves to be a promising target in the process of anti-viral drug design. Through this study, we aim to provide suggestions for compounds that may serve as potent inhibitors of the dengue NS2B-NS3 protein. Here, a ligand-based pharmacophore model was generated and the ZINC database was screened through ZINCPharmer to identify molecules with similar features. 2D QSAR model was developed and validated using reported 4-Benzyloxy Phenyl Glycine derivatives and was utilized to predict the IC50 values of unknown compounds. Further, the study is extended to molecular docking to investigate interactions at the active pocket of the target protein. ZINC36596404 and ZINC22973642 showed a predicted pIC50 of 6.477 and 7.872, respectively. They also showed excellent binding with NS3 protease as is evident from their binding energy of -8.3and -8.1 kcal/mol, respectively. ADMET predictionsofcompounds have shown high drug-likeness. Finally, the molecular dynamic simulations integrated with MM-PBSA binding energy calculations confirmedboth identified ZINC compounds as potential hit moleculeswith good stability.

Exploration of Potent Antiviral Phytomedicines from Lauraceae Family Plants against SARS-CoV-2 Main Protease

A new Coronaviridae strain, Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2), emerged from Wuhan city of China and caused one of the substantial global health calamities in December 2019. Even though several vaccines and drugs have been developed worldwide since COVID-19, a cost-effective drug with the least side effects is still unavailable. Currently, plant-derived compounds are mostly preferred to develop antiviral therapeutics due to its less toxicity, easy access, and cost-effective characteristics. Therefore, in this study, 124 phytochemical compounds from plants of Lauraceae family with medicinal properties were virtually screened against SARS-CoV-2 M^pro. Identification of four phytomolecules, i.e., cassameridine, laetanine, litseferine and cassythicine, with docking scores -9.3, -8.8, -8.6, and -8.6 kcal/mol, respectively, were undertaken by virtual screening, and molecular docking. Furthermore, the molecular dynamic simulation and essential dynamics analysis have contributed in understanding the stability and inhibitory effect of these selected compounds. These phytomolecules can be considered for further in vitro and in vivo experimental study to develop anti-SARS-CoV-2 therapeutics targeting the main protease (M^pro).

Repositioning of anti-dengue compounds against SARS-CoV-2 as viral polyprotein processing inhibitor

A therapy for COVID-19 (Coronavirus Disease 19) caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) remains elusive due to the lack of an effective antiviral therapeutic molecule. The SARS-CoV-2 main protease (Mpro), which plays a vital role in the viral life cycle, is one of the most studied and validated drug targets. In Several prior studies, numerous possible chemical entities were proposed as potential Mpro inhibitors; however, most failed at various stages of drug discovery. Repositioning of existing antiviral compounds accelerates the discovery and development of potent therapeutic molecules. Hence, this study examines the applicability of anti-dengue compounds against the substrate binding site of Mpro for disrupting its polyprotein processing mechanism. An in-silico structure-based virtual screening approach is applied to screen 330 experimentally validated anti-dengue compounds to determine their affinity to the substrate binding site of Mpro. This study identified the top five compounds (CHEMBL1940602, CHEMBL2036486, CHEMBL3628485, CHEMBL200972, CHEMBL2036488) that showed a high affinity to Mpro with a docking score > -10.0 kcal/mol. The best-docked pose of these compounds with Mpro was subjected to 100 ns molecular dynamic (MD) simulation followed by MM/GBSA binding energy. This showed the maximum stability and comparable ΔG binding energy against the reference compound (X77 inhibitor). Overall, we repurposed the reported anti-dengue compounds against SARS-CoV-2-Mpro to impede its polyprotein processing for inhibiting SARS-CoV-2 infection.

Pharmacophore-Model-Based Drug Repurposing for the Identification of the Potential Inhibitors Targeting the Allosteric Site in Dengue Virus NS5 RNA-Dependent RNA Polymerase

Dengue virus (DENV) is the causative agent of DENV infection. To tackle DENV infection, the development of therapeutic molecules as direct-acting antivirals (DAAs) has been demonstrated as a truly effective approach. Among various DENV drug targets, non-structural protein 5 (NS5)-a highly conserved protein among the family Flaviviridae-carries the RNA-dependent RNA polymerase (DENV^RdRp) domain at the C-terminal, and its "N-pocket" allosteric site is widely considered for anti-DENV drug development. Therefore, in this study, we developed a pharmacophore model by utilising 41 known inhibitors of the DENV^RdRp domain, and performed model screening against the FDA's approved drug database for drug repurposing against DENV^RdRp. Herein, drugs complying with the pharmacophore hypothesis were further processed through standard-precision (SP) and extra-precision (XP) docking scores (DSs) and binding pose refinement based on MM/GBSA binding energy (BE) calculations. This resulted in the identification of four potential potent drugs: (i) desmopressin (DS: -10.52, BE: -69.77 kcal/mol), (ii) rutin (DS: -13.43, BE: -67.06 kcal/mol), (iii) lypressin (DS: -9.84, BE: -67.65 kcal/mol), and (iv) lanreotide (DS: -8.72, BE: -64.7 kcal/mol). The selected drugs exhibited relevant interactions with the allosteric N-pocket of DENV^RdRp, including priming-loop and entry-point residues (i.e., R729, R737, K800, and E802). Furthermore, 100 ns explicit-solvent molecular dynamics simulations and end-point binding free energy assessments support the considerable stability and free energy of the selected drugs in the targeted allosteric pocket of DENV^RdRp. Hence, these four drugs, repurposed as potent inhibitors of the allosteric site of DENV^RdRp, are recommended for further validation using experimental assays.

Dengue virus NS4B protein as a target for developing antivirals

Dengue virus is an important pathogen affecting global population while no specific treatment is available against this virus. Effort has been made to develop inhibitors through targeting viral nonstructural proteins such as NS3 and NS5 with enzymatic activities. No potent inhibitors entering clinical studies have been developed so far due to many challenges. The genome of dengue virus encodes four membrane-bound nonstructural proteins which do not possess any enzymatic activities. Studies have shown that the membrane protein-NS4B is a validated target for drug discovery and several NS4B inhibitors exhibited antiviral activities in various assays and entered preclinical studies.. Here, we summarize the recent studies on dengue NS4B protein. The structure and membrane topology of dengue NS4B derived from biochemical and biophysical studies are described. Function of NS4B through protein-protein interactions and some available NS4B inhibitors are summarized. Accumulated studies demonstrated that cell-based assays play important roles in developing NS4B inhibitors. Although the atomic structure of NS4B is not obtained, target-based drug discovery approach become feasible to develop NS4B inhibitors as recombinant NS4B protein is available.

Exploration of natural compounds with anti-SARS-CoV-2 activity via inhibition of SARS-CoV-2 Mpro

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is a dreaded pandemic in lack of specific therapeutic agent. SARS-CoV-2 Mpro, an essential factor in viral pathogenesis, is recognized as a prospective therapeutic target in drug discovery against SARS-CoV-2. To tackle this pandemic, Food and Drug Administration-approved drugs are being screened against SARS-CoV-2 Mpro via in silico and in vitro methods to detect the best conceivable drug candidates. However, identification of natural compounds with anti-SARS-CoV-2 Mpro potential have been recommended as rapid and effective alternative for anti-SARS-CoV-2 therapeutic development. Thereof, a total of 653 natural compounds were identified against SARS-CoV-2 Mpro from NP-lib database at MTi-OpenScreen webserver using virtual screening approach. Subsequently, top four potential compounds, i.e. 2,3-Dihydroamentoflavone (ZINC000043552589), Podocarpusflavon-B (ZINC000003594862), Rutin (ZINC000003947429) and Quercimeritrin 6"-O-L-arabinopyranoside (ZINC000070691536), and co-crystallized N3 inhibitor as reference ligand were considered for stringent molecular docking after geometry optimization by DFT method. Each compound exhibited substantial docking energy >-12 kcal/mol and molecular contacts with essential residues, including catalytic dyad (His41 and Cys145) and substrate binding residues, in the active pocket of SARS-CoV-2 Mpro against N3 inhibitor. The screened compounds were further scrutinized via absorption, distribution, metabolism, and excretion - toxicity (ADMET), quantum chemical calculations, combinatorial molecular simulations and hybrid QM/MM approaches. Convincingly, collected results support the potent compounds for druglikeness and strong binding affinity with the catalytic pocket of SARS-CoV-2 Mpro. Hence, selected compounds are advocated as potential inhibitors of SARS-CoV-2 Mpro and can be utilized in drug development against SARS-CoV-2 infection.

Anticancer peptides prediction with deep representation learning features

Anticancer peptides constitute one of the most promising therapeutic agents for combating common human cancers. Using wet experiments to verify whether a peptide displays anticancer characteristics is time-consuming and costly. Hence, in this study, we proposed a computational method named identify anticancer peptides via deep representation learning features (iACP-DRLF) using light gradient boosting machine algorithm and deep representation learning features. Two kinds of sequence embedding technologies were used, namely soft symmetric alignment embedding and unified representation (UniRep) embedding, both of which involved deep neural network models based on long short-term memory networks and their derived networks. The results showed that the use of deep representation learning features greatly improved the capability of the models to discriminate anticancer peptides from other peptides. Also, UMAP (uniform manifold approximation and projection for dimension reduction) and SHAP (shapley additive explanations) analysis proved that UniRep have an advantage over other features for anticancer peptide identification. The python script and pretrained models could be downloaded from https://github.com/zhibinlv/iACP-DRLF or from http://public.aibiochem.net/iACP-DRLF/.