Eucalyptus globulus leaf-isolated isorhapontin serves as a natural insecticide via acetylcholinesterase inhibition.

Acetylcholinesterase (AChE) inhibitors cause insect death by preventing the hydrolysis of the neurotransmitter acetylcholine, which overstimulates the nervous system. In this study, isorhapontin, isolated from E. globulus leaves, was evaluated as a natural insecticide with AChE inhibition at 12.5 µM. Using kinetic analyses, we found that isorhapontin acted as a competitive inhibitor that binds to the active site of AChE. The inhibition constant (Ki) was 6.1 µM. Furthermore, isorhapontin and resveratrol, which have basic skeletons, were predicted to bind to the active site of AChE via molecular docking. A comparison of the hydrogen bonding between the two stilbenes revealed characteristic differences in their interactions with amino acids. In isorhapontin, Trp83, Gly149, Tyr162, Tyr324, and Tyr370 interacted with the sugar moiety. These results suggest that with further development, isorhapontin can be used as an insecticide alternative.

Analogues of Dihydroflavonol and Flavone as Protein Tyrosine Phosphatase 1B Inhibitors from the Leaves of Artocarpus elasticus.

Protein tyrosine phosphatase 1B (PTP1B) is one of the target enzymes whose disruption leads to obesity and diabetes. A series of PTP1B inhibitors were isolated from the leaves of Artocarpus elasticus, used in traditional medicines for diabetes. The isolated inhibitors (1-13), including two new compounds (1 and 2), consisted of dihydroflavonols and flavones. The structural requirements for the PTP1B inhibitory mode and potency were revealed in both skeletons. The two highest PTP1B inhibitory properties were dihydroflavonol 1 and flavone 6 analogs with IC50 values of 0.17 and 0.79 µM, respectively. The stereochemistry also affected inhibitory potencies: trans isomer 1 (IC50= 0.17 µM) vs cis isomer 2 (IC50= 2.24 µM). Surprisingly, the dihydroflavonol and flavone glycosides (11 and 13) displayed potent inhibition with IC50s of 2.39 and 0.22 µM, respectively. Furthermore, competitive inhibitor 1 was applied to time-dependence experiments as a simple slow-binding inhibitor with parameters of Kiapp = 0.064103 µM, k3 = 0.2262 µM-1 min-1, and k4 = 0.0145 min-1. The binding affinities by using the fluorescence quenching experiment were highly correlated with inhibitory potencies: 1 (IC50= 0.17 µM, KSV = 0.4375 × 105 L·mol-1) vs 3 (IC50= 17.79 µM, KSV = 0.0006 × 105 L·mol-1). The specific binding interactions were estimated at active and allosteric sites according to the inhibitory mode by molecular docking.

New Class of Tyrosinase Inhibitors, Rotenoids, from Amorpha fruticosa.

A series of rotenoids including a new one from the seeds of Amorpha fruticosa were found to have significant potential as tyrosinase inhibitors. All of the isolated rotenoids (1-6) displayed inhibitory activity against tyrosinase, both as a monophenolase for the oxidation of l-tyrosine and as a diphenolase for the oxidation of l-DOPA. The three most active compounds (1, 5, and 6) showed significant monophenolase inhibition with IC50 values of 2.1, 1.7, and 1.2 µM, respectively. They also inhibited diphenolase function with IC50 values in the range of 9.5-21.5 µM. The inhibition kinetics established all compounds to be competitive inhibitors of both oxidation processes. All rotenoids formed the Emet·I complex effectively around their IC50 values with long lag times. Tyrosinase inhibition of the new rotenoid 6 was additionally demonstrated using high-performance liquid chromatography (HPLC) analysis with N-acetyl-l-tyrosine. Molecular docking disclosed that the sugar moiety of 5 interacted with the bottom of the catalytic gorge.

Investigation of bacterial neuraminidase inhibition of xanthones bearing geranyl and prenyl groups from Cratoxylum cochinchinense.

Introduction: The root of Cratoxylum cochinchinense has been widely used as Chinese folk medicine to cure fevers, burns, and abdominal complications because it contains various bioactive metabolites such as xanthones, triterpenes, and flavonoids. In this study, we estimated bacterial neuraminidase inhibition with a series of xanthones from C. cochinchinense. BNA has connected to various biological functions such as pathogenic bacteria infection inflammatory process after infection and biofilm formation. Methods: The identification of xanthones (1-6) bearing geranyl and prenyl groups was established by spectroscopic data using UV, IR, NMR, and HREIMS. BNA inhibitory modes of isolated xanthones were investigated by Double-reciprocal plots. Moreover, the competitive inhibitor was evaluated the additional kinetic modes determined by kinetic parameters (k 3, k 4, and K i app). The molecular docking (MD) and molecular dynamics simulations (MDS) studies also provided the critical information regarding the role of the geranyl and prenyl groups against BNA inhibition. Results: A series of xanthones (1-6) appended prenyl and geranyl groups on the A-ring were isolated, and compounds 1-3 were shown to be new xanthones. The analogues within this series were highly inhibited with excellent affinity against bacterial neuraminidase (BNA). A subtle change in the prenyl or geranyl motif affected the inhibitory potency and behavior significantly. For example, the inhibitory potency and binding affinity resulting from the geranyl group on C4: xanthone 1 (IC50 = 0.38 µM, KA = 2.4434 × 105 L·mol-1) were 100-fold different from those of xanthone 3 (IC50 = 35.8 µM, KA = 0.0002 × 105 L·mol-1). The most potent compound 1 was identified as a competitive inhibitor which interacted with BNA under reversible slow-binding inhibition: K i app = 0.1440 µM, k 3 = 0.1410 µM-1s-1, and k 4 = 0.0203 min-1. The inhibitory potencies (IC50) were doubly confirmed by the binding affinities (KA). Discussion: This study suggests the potential of xanthones derived from C. cochinchinense as promising candidates for developing novel BNA inhibitors. Further research and exploration of these xanthones may contribute to the development of effective treatments for bacterial infections and inflammatory processes associated with BNA activity.

Identification of Activated Cdc42-Associated Kinase Inhibitors as Potential Anticancer Agents Using Pharmacoinformatic Approaches.

BACKGROUND: Activated Cdc42-associated kinase (ACK1) is essential for numerous cellular functions, such as growth, proliferation, and migration. ACK1 signaling occurs through multiple receptor tyrosine kinases; therefore, its inhibition can provide effective antiproliferative effects against multiple human cancers. A number of ACK1-specific inhibitors were designed and discovered in the previous decade, but none have reached the clinic. Potent and selective ACK1 inhibitors are urgently needed. METHODS: In the present investigation, the pharmacophore model (PM) was rationally built utilizing two distinct inhibitors coupled with ACK1 crystal structures. The generated PM was utilized to screen the drug-like database generated from the four chemical databases. The binding mode of pharmacophore-mapped compounds was predicted using a molecular docking (MD) study. The selected hit-protein complexes from MD were studied under all-atom molecular dynamics simulations (MDS) for 500 ns. The obtained trajectories were ranked using binding free energy calculations (ΔG kJ/mol) and Gibb's free energy landscape. RESULTS: Our results indicate that the three hit compounds displayed higher binding affinity toward ACK1 when compared with the known multi-kinase inhibitor dasatinib. The inter-molecular interactions of Hit1 and Hit3 reveal that compounds form desirable hydrogen bond interactions with gatekeeper T205, hinge region A208, and DFG motif D270. As a result, we anticipate that the proposed scaffolds might help in the design of promising selective ACK1 inhibitors.

Pharmacophore-Oriented Identification of Potential Leads as CCR5 Inhibitors to Block HIV Cellular Entry.

Cysteine-cysteine chemokine receptor 5 (CCR5) has been discovered as a co-receptor for cellular entry of human immunodeficiency virus (HIV). Moreover, the role of CCR5 in a variety of cancers and various inflammatory responses was also discovered. Despite the fact that several CCR5 antagonists have been investigated in clinical trials, only Maraviroc has been licensed for use in the treatment of HIV patients. This indicates that there is a need for novel CCR5 antagonists. Keeping this in mind, the present study was designed. The active CCR5 inhibitors with known IC50 value were selected from the literature and utilized to develop a ligand-based common feature pharmacophore model. The validated pharmacophore model was further used for virtual screening of drug-like databases obtained from the Asinex, Specs, InterBioScreen, and Eximed chemical libraries. Utilizing computational methods such as molecular docking studies, molecular dynamics simulations, and binding free energy calculation, the binding mechanism of selected inhibitors was established. The identified Hits not only showed better binding energy when compared to Maraviroc, but also formed stable interactions with the key residues and showed stable behavior throughout the 100 ns MD simulation. Our findings suggest that Hit1 and Hit2 may be potential candidates for CCR5 inhibition, and, therefore, can be considered for further CCR5 inhibition programs.

REDD1 promotes obesity-induced metabolic dysfunction via atypical NF-κB activation.

Regulated in development and DNA damage response 1 (REDD1) expression is upregulated in response to metabolic imbalance and obesity. However, its role in obesity-associated complications is unclear. Here, we demonstrate that the REDD1-NF-κB axis is crucial for metabolic inflammation and dysregulation. Mice lacking Redd1 in the whole body or adipocytes exhibited restrained diet-induced obesity, inflammation, insulin resistance, and hepatic steatosis. Myeloid Redd1-deficient mice showed similar results, without restrained obesity and hepatic steatosis. Redd1-deficient adipose-derived stem cells lost their potential to differentiate into adipocytes; however, REDD1 overexpression stimulated preadipocyte differentiation and proinflammatory cytokine expression through atypical IKK-independent NF-κB activation by sequestering IκBα from the NF-κB/IκBα complex. REDD1 with mutated Lys219/220Ala, key amino acid residues for IκBα binding, could not stimulate NF-κB activation, adipogenesis, and inflammation in vitro and prevented obesity-related phenotypes in knock-in mice. The REDD1-atypical NF-κB activation axis is a therapeutic target for obesity, meta-inflammation, and metabolic complications.

3D-QSAR-Based Pharmacophore Modeling, Virtual Screening, and Molecular Dynamics Simulations for the Identification of Spleen Tyrosine Kinase Inhibitors.

Spleen tyrosine kinase (SYK) is an essential mediator of immune cell signaling and has been anticipated as a therapeutic target for autoimmune diseases, notably rheumatoid arthritis, allergic rhinitis, asthma, and cancers. Significant attempts have been undertaken in recent years to develop SYK inhibitors; however, limited success has been achieved due to poor pharmacokinetics and adverse effects of inhibitors. The primary goal of this research was to identify potential inhibitors having high affinity, selectivity based on key molecular interactions, and good drug-like properties than the available inhibitor, fostamatinib. In this study, a 3D-QSAR model was built for SYK based on known inhibitor IC50 values. The best pharmacophore model was then used as a 3D query to screen a drug-like database to retrieve hits with novel chemical scaffolds. The obtained compounds were subjected to binding affinity prediction using the molecular docking approach, and the results were subsequently validated using molecular dynamics (MD) simulations. The simulated compounds were ranked according to binding free energy (ΔG), and the binding affinity was compared with fostamatinib. The binding mode analysis of selected compounds revealed that the hit compounds form hydrogen bond interactions with hinge region residue Ala451, glycine-rich loop residue Lys375, Ser379, and DFG motif Asp512. Identified hits were also observed to form a desirable interaction with Pro455 and Asn457, the rare feature observed in SYK inhibitors. Therefore, we argue that identified hit compounds ZINC98363745, ZINC98365358, ZINC98364133, and ZINC08789982 may help in drug design against SYK.

Soybean phytochemicals responsible for bacterial neuraminidase inhibition and their characterization by UPLC-ESI-TOF/MS.

Ethanol extract of soybean (Glycine max (L.) Merr.) showed good inhibitory activity against bacterial neuraminidase (BNA), which plays a pivotal role in the pathogenesis of a number of microbial diseases. The saponin portion fractionated through preparative HPLC (IC50 = 2.25 µg mL-1) was found to be responsible for the observed BNA inhibition. Estimation of the inhibitory effects by individual compounds showed that the soyasaponins of group B (Ba, Bb, Bb', Bc, and Bd) exhibited extremely high inhibitions (IC50 = 0.25-0.48 µM), whereas group A (Aa, Ab, and Ac) was almost inactive. Kinetic studies determined that group B soyasaponins were noncompetitive inhibitors. Furthermore, molecular docking experiments confirmed that soyasaponin Ba (group B) could undergo binding interactions with various residues in the binding pocket. In contrast, soyasaponin Aa (group A) failed to enter the binding pocket due to its extra scaffold structure of oligosaccharides bonded to the 22-hydroxyl position. The metabolites in the soybean extract were fully characterized using UPLC-ESI-TOF/MS.

New dihydrobenzoxanthone derivatives with bacterial neuraminidase inhibitory activity isolated from Artocarpus elasticus.

Artocarpus elasticus is a popular fruit tree in the tropical regions. Primary screenings of methanol extracts of the root bark confirmed its potent inhibition of bacterial neuraminidase (BNA), which plays an essential role in the pathogenesis of many microbial diseases. Assessments of the responsible phytochemicals were conducted by isolating eight compounds (1-8) and two of them (6 and 8) were identified as new compounds. Among the isolates, the dihydrobenzoxanthones attained the highest BNA inhibition with IC50 values of 0.5 âˆ¼ 3.9 µM. Further investigation of the inhibitory mechanism by Lineweaver-Burk plots revealed the phytochemicals to function as reversible noncompetitive inhibitors. Fluorescence quenching showed their binding affinities were highly correlated with their inhibitory potential dose-dependently. Molecular docking experiments suggested the dihydrobenzoxanthones (4 and 6) as noncompetitive inhibitors of BNA with unique interaction with Tyr435 of BNA in comparison with the mother flavonoid (7).

Identification of New KRAS G12D Inhibitors through Computer-Aided Drug Discovery Methods.

Owing to several mutations, the oncogene Kirsten rat sarcoma 2 viral oncogene homolog (KRAS) is activated in the majority of cancers, and targeting it has been pharmacologically challenging. In this study, using an in silico approach comprised of pharmacophore modeling, molecular docking, and molecular dynamics simulations, potential KRAS G12D inhibitors were investigated. A ligand-based common feature pharmacophore model was generated to identify the framework necessary for effective KRAS inhibition. The chemical features in the selected pharmacophore model comprised two hydrogen bond donors, one hydrogen bond acceptor, two aromatic rings and one hydrophobic feature. This model was used for screening in excess of 214,000 compounds from InterBioScreen (IBS) and ZINC databases. Eighteen compounds from the IBS and ten from the ZINC database mapped onto the pharmacophore model and were subjected to molecular docking. Molecular docking results highlighted a higher affinity of four hit compounds towards KRAS G12D in comparison to the reference inhibitor, BI-2852. Sequential molecular dynamics (MD) simulation studies revealed all four hit compounds them possess higher KRAS G12D binding free energy and demonstrate stable polar interaction with key residues. Further, Principal Component Analysis (PCA) analysis of the hit compounds in complex with KRAS G12D also indicated stability. Overall, the research undertaken provides strong support for further in vitro testing of these newly identified KRAS G12D inhibitors, particularly Hit1 and Hit2.

Molecular Docking and Molecular Dynamics Simulations Discover Curcumin Analogue as a Plausible Dual Inhibitor for SARS-CoV-2.

Recently, the world has been witnessing a global pandemic with no effective therapeutics yet, while cancer continues to be a major disease claiming many lives. The natural compound curcumin is bestowed with multiple medicinal applications in addition to demonstrating antiviral and anticancer activities. In order to elucidate the impact of curcumin on COVID-19 and cancer, the current investigation has adapted several computational techniques to unfold its possible inhibitory activity. Accordingly, curcumin and similar compounds and analogues were retrieved and assessed for their binding affinities at the binding pocket of SARS-CoV-2 main protease and DDX3. The best binding pose was escalated to molecular dynamics simulation (MDS) studies to assess the time dependent stability. Our findings have rendered one compound that has demonstrated good molecular dock score complemented by key residue interactions and have shown stable MDS results inferred by root mean square deviation (RMSD), radius of gyration (Rg), binding mode, hydrogen bond interactions, and interaction energy. Essential dynamics results have shown that the systemadapts minimum energy conformation to attain a stable state. The discovered compound (curA) could act as plausible inhibitor against SARS-CoV-2 and DDX3. Furthermore, curA could serve as a chemical scaffold for designing and developing new compounds.

Computational Simulations Highlight the IL2Rα Binding Potential of Polyphenol Stilbenes from Fenugreek.

Widely used in global households, fenugreek is well known for its culinary and medicinal uses. The various reported medicinal properties of fenugreek are by virtue of the different natural phytochemicals present in it. Regarded as a promising target, interleukin 2 receptor subunit alpha (IL2Rα) has been shown to influence immune responses. In the present research, using in silico techniques, we have demonstrated the potential IL2Rα binding properties of three polyphenol stilbenes (desoxyrhaponticin, rhaponticin, rhapontigenin) from fenugreek. As the first step, molecular docking was performed to assess the binding potential of the fenugreek phytochemicals with IL2Rα. All three phytochemicals demonstrated interactions with active site residues. To confirm the reliability of our molecular docking results, 100 ns molecular dynamics simulations studies were undertaken. As discerned by the RMSD and RMSF analyses, IL2Rα in complex with the desoxyrhaponticin, rhaponticin, and rhapontigenin indicated stability. The RMSD analysis of the phytochemicals alone also demonstrated no significant structural changes. Based on the stable molecular interactions and comparatively slightly better MM/PBSA binding free energy, rhaponticin seems promising. Additionally, ADMET analysis performed for the stilbenes indicated that all of them obey the ADMET rules. Our computational study thus supports further in vitro IL2Rα binding studies on these stilbenes, especially rhaponticin.

Identification of CDK7 Inhibitors from Natural Sources Using Pharmacoinformatics and Molecular Dynamics Simulations.

The cyclin-dependent kinase 7 (CDK7) plays a crucial role in regulating the cell cycle and RNA polymerase-based transcription. Overexpression of this kinase is linked with various cancers in humans due to its dual involvement in cell development. Furthermore, emerging evidence has revealed that inhibiting CDK7 has anti-cancer effects, driving the development of novel and more cost-effective inhibitors with enhanced selectivity for CDK7 over other CDKs. In the present investigation, a pharmacophore-based approach was utilized to identify potential hit compounds against CDK7. The generated pharmacophore models were validated and used as 3D queries to screen 55,578 natural drug-like compounds. The obtained compounds were then subjected to molecular docking and molecular dynamics simulations to predict their binding mode with CDK7. The molecular dynamics simulation trajectories were subsequently used to calculate binding affinity, revealing four hits-ZINC20392430, SN00112175, SN00004718, and SN00262261-having a better binding affinity towards CDK7 than the reference inhibitors (CT7001 and THZ1). The binding mode analysis displayed hydrogen bond interactions with the hinge region residues Met94 and Glu95, DFG motif residue Asp155, ATP-binding site residues Thr96, Asp97, and Gln141, and quintessential residue outside the kinase domain, Cys312 of CDK7. The in silico selectivity of the hits was further checked by docking with CDK2, the close homolog structure of CDK7. Additionally, the detailed pharmacokinetic properties were predicted, revealing that our hits have better properties than established CDK7 inhibitors CT7001 and THZ1. Hence, we argue that proposed hits may be crucial against CDK7-related malignancies.

Novel Butein Derivatives Repress DDX3 Expression by Inhibiting PI3K/AKT Signaling Pathway in MCF-7 and MDA-MB-231 Cell Lines.

BACKGROUND: Breast cancer is one of the major causes of mortalities noticed in women globally. DDX3 has emerged as a potent target for several cancers, including breast cancer to which currently there are no reported or approved drugs. METHODS: To find effective cancer therapeutics, three compounds were computationally designed tweaking the structure of natural compound butein. These compounds were synthesized and evaluated for their anticancer property in MCF-7 and MDA-MB-231 cell lines targeting DDX3. The in silico molecular docking studies have shown that the compounds have occupied the binding site of the human DDX3 target. Furthermore, to investigate the cell viability effect of 3a, 3b, and 3c on MCF-7 and MDA-MB-231 cell lines, the cell lines were treated with different concentrations of compounds for 24 and 48 h and measured using MTT assay. RESULTS: The cell viability results showed that the have induced dose dependent suppression of DDX3 expression. Additionally, 3b and 3c have reduced the expression of DDX3 in MCF-7 and MDA-MD-231 cell lines. 3b or 3c treated cell lines increased apoptotic protein expression. Both the compounds have induced the apoptotic cell death by elevated levels of cleaved PARP and cleaved caspase 3 and repression of the anti-apoptosis protein BCL-xL. Additionally, they have demonstrated the G2/M phase cell cycle arrest in both the cell lines. Additionally, 3c decreased PI3K and AKT levels. CONCLUSIONS: Our results shed light on the anticancer ability of the designed compounds. These compounds can be employed as chemical spaces to design new prospective drug candidates. Additionally, our computational method can be adapted to design new chemical scaffolds as plausible inhibitors.

Development of Machine Learning Models for Accurately Predicting and Ranking the Activity of Lead Molecules to Inhibit PRC2 Dependent Cancer.

Disruption of epigenetic processes to eradicate tumor cells is among the most promising interventions for cancer control. EZH2 (Enhancer of zeste homolog 2), a catalytic component of polycomb repressive complex 2 (PRC2), methylates lysine 27 of histone H3 to promote transcriptional silencing and is an important drug target for controlling cancer via epigenetic processes. In the present study, we have developed various predictive models for modeling the inhibitory activity of EZH2. Binary and multiclass models were built using SVM, random forest and XGBoost methods. Rigorous validation approaches including predictiveness curve, Y-randomization and applicability domain (AD) were employed for evaluation of the developed models. Eighteen descriptors selected from Boruta methods have been used for modeling. For binary classification, random forest and XGBoost achieved an accuracy of 0.80 and 0.82, respectively, on external test set. Contrastingly, for multiclass models, random forest and XGBoost achieved an accuracy of 0.73 and 0.75, respectively. 500 Y-randomization runs demonstrate that the models were robust and the correlations were not by chance. Evaluation metrics from predictiveness curve show that the selected eighteen descriptors predict active compounds with total gain (TG) of 0.79 and 0.59 for XGBoost and random forest, respectively. Validated models were further used for virtual screening and molecular docking in search of potential hits. A total of 221 compounds were commonly predicted as active with above the set probability threshold and also under the AD of training set. Molecular docking revealed that three compounds have reasonable binding energy and favorable interactions with critical residues in the active site of EZH2. In conclusion, we highlighted the potential of rigorously validated models for accurately predicting and ranking the activities of lead molecules against cancer epigenetic targets. The models presented in this study represent the platform for development of EZH2 inhibitors.

Unravelling the therapeutic potential of marine drugs as SARS-CoV-2 inhibitors: An insight from essential dynamics and free energy landscape.

Coronavirus disease 2019 (COVID-19) is an ongoing pandemic. The virus that causes the disease, severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), predominantly infects the respiratory tract, which may lead to pneumonia and death in severe cases. Many marine compounds have been found to have immense medicinal value and have gained approval from the Food and Drug Administration (FDA), and some are being tested in clinical trials. In the current investigation, we redirected a number of marine compounds toward SARS-CoV-2 by targeting the main protease (Mpro, PDB ID: 6Y2F), subjecting them to several advanced computational techniques using co-crystallised ligand as the reference compound. The results of the binding affinity studies showed that two compounds, eribulin mesylate (eri) and soblidotin (sob), displayed higher docking scores than did the reference compound. When these compounds were assessed using molecular dynamics simulation, it was evident that they demonstrated stable binding at the binding pocket of the target protein. The systems demonstrated stable root mean square deviation and radius of gyration values, while occupying the binding pocket during the simulation run. Furthermore, the essential dynamics and free energy landscape exploration revealed that the protein had navigated through a minimal energy basin and demonstrated favourable conformation while binding to the proposed inhibitors. Collectively, our findings suggest that two marine compounds, namely eri and sob, show potential as SARS-CoV-2 main protease inhibitors.

Exploring the Binding Interaction of Raf Kinase Inhibitory Protein With the N-Terminal of C-Raf Through Molecular Docking and Molecular Dynamics Simulation.

Protein-protein interactions are indispensable physiological processes regulating several biological functions. Despite the availability of structural information on protein-protein complexes, deciphering their complex topology remains an outstanding challenge. Raf kinase inhibitory protein (RKIP) has gained substantial attention as a favorable molecular target for numerous pathologies including cancer and Alzheimer's disease. RKIP interferes with the RAF/MEK/ERK signaling cascade by endogenously binding with C-Raf (Raf-1 kinase) and preventing its activation. In the current investigation, the binding of RKIP with C-Raf was explored by knowledge-based protein-protein docking web-servers including HADDOCK and ZDOCK and a consensus binding mode of C-Raf/RKIP structural complex was obtained. Molecular dynamics (MD) simulations were further performed in an explicit solvent to sample the conformations for when RKIP binds to C-Raf. Some of the conserved interface residues were mutated to alanine, phenylalanine and leucine and the impact of mutations was estimated by additional MD simulations and MM/PBSA analysis for the wild-type (WT) and constructed mutant complexes. Substantial decrease in binding free energy was observed for the mutant complexes as compared to the binding free energy of WT C-Raf/RKIP structural complex. Furthermore, a considerable increase in average backbone root mean square deviation and fluctuation was perceived for the mutant complexes. Moreover, per-residue energy contribution analysis of the equilibrated simulation trajectory by HawkDock and ANCHOR web-servers was conducted to characterize the key residues for the complex formation. One residue each from C-Raf (Arg398) and RKIP (Lys80) were identified as the druggable "hot spots" constituting the core of the binding interface and corroborated by additional long-time scale (300 ns) MD simulation of Arg398Ala mutant complex. A notable conformational change in Arg398Ala mutant occurred near the mutation site as compared to the equilibrated C-Raf/RKIP native state conformation and an essential hydrogen bonding interaction was lost. The thirteen binding sites assimilated from the overall analysis were mapped onto the complex as surface and divided into active and allosteric binding sites, depending on their location at the interface. The acquired information on the predicted 3D structural complex and the detected sites aid as promising targets in designing novel inhibitors to block the C-Raf/RKIP interaction.

Computational Simulations Identified Marine-Derived Natural Bioactive Compounds as Replication Inhibitors of SARS-CoV-2.

The rapid spread of COVID-19, caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is a worldwide health emergency. Unfortunately, to date, a very small number of remedies have been to be found effective against SARS-CoV-2 infection. Therefore, further research is required to achieve a lasting solution against this deadly disease. Repurposing available drugs and evaluating natural product inhibitors against target proteins of SARS-CoV-2 could be an effective approach to accelerate drug discovery and development. With this strategy in mind, we derived Marine Natural Products (MNP)-based drug-like small molecules and evaluated them against three major target proteins of the SARS-CoV-2 virus replication cycle. A drug-like database from MNP library was generated using Lipinski's rule of five and ADMET descriptors. A total of 2,033 compounds were obtained and were subsequently subjected to molecular docking with 3CLpro, PLpro, and RdRp. The docking analyses revealed that a total of 14 compounds displayed better docking scores than the reference compounds and have significant molecular interactions with the active site residues of SARS-CoV-2 virus targeted proteins. Furthermore, the stability of docking-derived complexes was analyzed using molecular dynamics simulations and binding free energy calculations. The analyses revealed two hit compounds against each targeted protein displaying stable behavior, binding affinity, and molecular interactions. Our investigation identified two hit compounds against each targeted proteins displaying stable behavior, higher binding affinity and key residual molecular interactions, with good in silico pharmacokinetic properties, therefore can be considered for further in vitro studies.

Computational Approaches to Discover Novel Natural Compounds for SARS-CoV-2 Therapeutics.

Scientists all over the world are facing a challenging task of finding effective therapeutics for the coronavirus disease (COVID-19). One of the fastest ways of finding putative drug candidates is the use of computational drug discovery approaches. The purpose of the current study is to retrieve natural compounds that have obeyed to drug-like properties as potential inhibitors. Computational molecular modelling techniques were employed to discover compounds with potential SARS-CoV-2 inhibition properties. Accordingly, the InterBioScreen (IBS) database was obtained and was prepared by minimizing the compounds. To the resultant compounds, the absorption, distribution, metabolism, excretion and toxicity (ADMET) and Lipinski's Rule of Five was applied to yield drug-like compounds. The obtained compounds were subjected to molecular dynamics simulation studies to evaluate their stabilities. In the current article, we have employed the docking based virtual screening method using InterBioScreen (IBS) natural compound database yielding two compounds has potential hits. These compounds have demonstrated higher binding affinity scores than the reference compound together with good pharmacokinetic properties. Additionally, the identified hits have displayed stable interaction results inferred by molecular dynamics simulation results. Taken together, we advocate the use of two natural compounds, STOCK1N-71493 and STOCK1N-45683 as SARS-CoV-2 treatment regime.