Identification of a New Potential SARS-COV-2 RNA-Dependent RNA Polymerase Inhibitor via Combining Fragment-Based Drug Design, Docking, Molecular Dynamics, and MM-PBSA Calculations

Mechanism of YJKL Decoction in Treating of PCOS Infertility by Integrative Approach of Network Pharmacology and Experimental Verification

Purpose

Currently, there is still no clear treatment for polycystic ovary syndrome (PCOS). YJKL has better therapeutic effects and lower toxic side effects for PCOS type infertility. This study aims to clarify the potential mechanism of YJKL Decoction in the treatment of PCOS based on network pharmacology and experiments verification.

Patients and Methods

Network pharmacology and experimental validation approach were used to investigate the bioactive ingredients, critical targets and potential mechanisms of YJKL Decoction against PCOS. Firstly, we use network pharmacology methods to collect core targets, and then validate their effects on diseases through experiments.

Results

Five core targets were screened, Threonine kinase 1 (AKT1), Cellular tumor antigen p53 (TP53), Tumor necrosis factor (TNF), Albumin (ALB) and Vascular endothelial growthfactor A (VEGFA). KEGG analysis showed that YJKL treatment for PCOS mainly include AGE-RAGE signaling pathway in diabetic complications, TNF signaling pathway and HIF-1 signaling pathway. The molecular docking results showed that compounds have higher affinity with targets. Finally, experimental results had shown that YJKL Decoction had an better therapeutic effects in the treatment of PCOS.

Conclusion

Based on a systematic network pharmacology approach and experimental verification, our results comprehensively illustrated the active ingredients, potential targets, and molecular mechanism of YJKL for application to PCOS and helps to illustrate mechanism of action on a comprehensive level.

Identification of sulphonamide-tethered N-((triazol-4-yl)methyl)isatin derivatives as inhibitors of SARS-CoV-2 main protease

SARS-CoV-2 pandemic in the end of 2019 led to profound consequences on global health and economy. Till producing successful vaccination strategies, the healthcare sectors suffered from the lack of effective therapeutic agents that could control the spread of infection. Thus, academia and the pharmaceutical sector prioritise SARS-CoV-2 antiviral drug discovery. Here, we exploited previous reports highlighting the anti-SARS-CoV-2 activities of isatin-based molecules to develop novel triazolo-isatins for inhibiting main protease (Mpro) of the virus, a crucial enzyme for its replication in the host cells. Particularly, sulphonamide 6b showed promising inhibitory activity with an IC50= 0.249 µM. Additionally, 6b inhibited viral cell proliferation with an IC50 of 4.33 µg/ml, and was non-toxic to VERO-E6 cells (CC50 = 564.74 µg/ml) displaying a selectivity index of 130.4. In silico analysis of 6b disclosed its ability to interact with key residues in the enzyme active site, supporting the obtained in vitro findings.

Exploring the disruption of SARS-CoV-2 RBD binding to hACE2

The COVID-19 pandemic was declared due to the spread of the novel coronavirus, SARS-CoV-2. Viral infection is caused by the interaction between the SARS-CoV-2 receptor binding domain (RBD) and the human ACE2 receptor (hACE2). Previous computational studies have identified repurposed small molecules that target the RBD, but very few have screened drugs in the RBD-hACE2 interface. When studies focus solely on the binding affinity between the drug and the RBD, they ignore the effect of hACE2, resulting in an incomplete analysis. We screened ACE inhibitors and previously identified SARS-CoV-2 inhibitors for binding to the RBD-hACE2 interface, and then conducted 500 ns of unrestrained molecular dynamics (MD) simulations of fosinopril, fosinoprilat, lisinopril, emodin, diquafosol, and physcion bound to the interface to assess the binding characteristics of these ligands. Based on MM-GBSA analysis, all six ligands bind favorably in the interface and inhibit the RBD-hACE2 interaction. However, when we repeat our simulation by first binding the drug to the RBD before interacting with hACE2, we find that fosinopril, fosinoprilat, and lisinopril result in a strongly interacting trimeric complex (RBD-drug-hACE2). Hydrogen bonding and pairwise decomposition analyses further suggest that fosinopril is the best RBD inhibitor. However, when lisinopril is bound, it stabilizes the trimeric complex and, therefore, is not an ideal potential drug candidate. Overall, these results reveal important atomistic interactions critical to the binding of the RBD to hACE2 and highlight the significance of including all protein partners in the evaluation of a potential drug candidate.

In silico approaches and in vitro assays identify a coumarin derivative as antiviral potential against SARS-CoV-2

COVID-19, a disease caused by SARS-CoV-2, was declared a pandemic in 2020 and created a global crisis in health systems, with more than 545 million confirmed cases and 6.33 million deaths. In this sense, this work aims to identify possible inhibitors of the SARS-CoV-2 RdRp enzyme using in silico approaches. RdRp is a crucial enzyme in the replication and assembly cycle of new viral particles and a critical pharmacological target in the treatment of COVID-19. We performed a virtual screening based on molecular docking from our in-house chemical library, which contains a diversity of 313 structures from different chemical classes. Nine compounds were selected since they showed important interactions with the active site from RdRp. Next, the ADME-Tox in silico predictions served as a filter and selected the three most promising compounds: a coumarin LMed-052, a hydantoin LMed-087, and a guanidine LMed-250. Molecular dynamics simulations revealed details such as changes in the positions of ligands and catalytic residues during the simulations compared to the complex from molecular docking studies. Binding free energy analysis was performed using the MMGBSA method, demonstrating that LMed-052 and LMed-087 have better affinities for the RdRp by energetic contributions to the stability of the complexes when compared to LMed-250. Furthermore, LMed-052 showed significant in vitro inhibition against MHV-3, decreasing 99% of viral titers. Finally, these findings are useful to guide structural modifications aiming to improve the potential of these compounds to act as inhibitors of SARS-CoV-2.Communicated by Ramaswamy H. Sarma.

Molecular docking, molecular dynamics simulation and MM-GBSA studies of the activity of glycyrrhizin relevant substructures on SARS-CoV-2 RNA-dependent-RNA polymerase

SARS-CoV-2 is the causative agent of Coronavirus Disease (COVID-19), which is a life-threatening disease. The World Health Organization has classified COVID-19 as a severe worldwide public health pandemic due to its high death rate, quick transmission, and lack of medicines. To counteract the recurrence of the severe acute respiratory syndrome, active antiviral medications are urgently required. Glycyrrhizin was documented with activity on different viral proteins, including SARS-CoV-2; in this study, the activity of glycyrrhizin and its substructures (604 molecules) were screened on SARS-CoV-2 RNA-dependent-RNA polymerase using molecular docking, molecular dynamic (MD) simulation, and MM/GBSA. Sixteen molecules exhibited docking energy higher than -7 kcal/mol; four compounds (10772603, 101088272, 154730753 and glycyrrhizin) showed the highest binding energy, and good stability during MD simulation. The glycyrrhizin compound exhibited favorable docking energy (-7.9 kcal/mol), and it was the most stable complex during MD simulation. The predicted binding free energy of the glycyrrhizin complex was -57 ± 8 kcal/mol. These findings suggest that this molecule, after more validation, could become a good candidate for developing and manufacturing an anti-SARS-CoV-2 medication.Communicated by Ramaswamy H. Sarma.

Revealing the Molecular Interactions between Human ACE2 and the Receptor Binding Domain of the SARS-CoV-2 Wild-Type, Alpha and Delta Variants

After a sudden and first spread of the pandemic caused by the novel SARS-CoV-2 (Severe Acute Respiratory Syndrome-Coronavirus 2) wild-type strain, mutants have emerged which have been associated with increased infectivity, inducing surges in the contagions. The first of the so-called variants of concerns, was firstly isolated in the United Kingdom and later renamed Alpha variant. Afterwards, in the middle of 2021, a new variant appeared called Delta. The latter is characterized by the presence of point mutations in the Spike protein of SARS-CoV-2, especially in the Receptor Binding Domain (RBD). When in its active conformation, the RBD can interact with the human receptor Angiotensin-Converting Enzyme 2 (ACE2) to allow the entry of the virions into cells. In this contribution, by using extended all-atom molecular dynamic simulations, complemented with machine learning post-processing, we analyze the changes in the molecular interaction network induced by these different strains in comparison with the wild-type. On one hand, although relevant variations are evidenced, only limited changes in the global stability indicators and in the flexibility profiles have been observed. On the other hand, key differences were obtained by tracking hydrophilic and hydrophobic molecular interactions, concerning both positioning at the ACE2/RBD interface and formation/disruption dynamic behavior.

Multi-stage structure-based virtual screening approach towards identification of potential SARS-CoV-2 NSP13 helicase inhibitors

On account of its crucial role in the virus life cycle, SARS-COV-2 NSP13 helicase enzyme was exploited as a promising target to identify a novel potential inhibitor using multi-stage structure-based drug discovery approaches. Firstly, a 3D pharmacophore was generated based on the collected data from a protein-ligand interaction fingerprint (PLIF) study using key interactions between co-crystallised fragments and the NSP13 helicase active site. The ZINC database was screened through the generated 3D-pharmacophore retrieving 13 potential hits. All the retrieved hits exceeded the benchmark score of the co-crystallised fragments at the molecular docking step and the best five-hit compounds were selected for further analysis. Finally, a combination between molecular dynamics simulations and MM-PBSA based binding free energy calculations was conducted on the best hit (compound FWM-1) bound to NSP13 helicase enzyme, which identified FWM-1 as a potential potent NSP13 helicase inhibitor with binding free energy equals -328.6 ± 9.2 kcal/mol.

Discovering new potential inhibitors to SARS-CoV-2 RNA dependent RNA polymerase (RdRp) using high throughput virtual screening and molecular dynamics simulations

RNA dependent RNA polymerase (RdRp), is an essential in the RNA replication within the life cycle of the severely acute respiratory coronavirus-2 (SARS-CoV-2), causing the deadly respiratory induced sickness COVID-19. Remdesivir is a prodrug that has seen some success in inhibiting this enzyme, however there is still the pressing need for effective alternatives. In this study, we present the discovery of four non-nucleoside small molecules that bind favorably to SARS-CoV-2 RdRp over the active form of the popular drug remdesivir (RTP) and adenosine triphosphate (ATP) by utilizing high-throughput virtual screening (HTVS) against the vast ZINC compound database coupled with extensive molecular dynamics (MD) simulations. After post-trajectory analysis, we found that the simulations of complexes containing both ATP and RTP remained stable for the duration of their trajectories. Additionally, it was revealed that the phosphate tail of RTP was stabilized by both the positive amino acid pocket and magnesium ions near the entry channel of RdRp which includes residues K551, R553, R555 and K621. It was also found that residues D623, D760, and N691 further stabilized the ribose portion of RTP with U10 on the template RNA strand forming hydrogen pairs with the adenosine motif. Using these models of RdRp, we employed them to screen the ZINC database of ~ 17 million molecules. Using docking and drug properties scoring, we narrowed down our selection to fourteen candidates. These were subjected to 200 ns simulations each underwent free energy calculations. We identified four hit compounds from the ZINC database that have similar binding poses to RTP while possessing lower overall binding free energies, with ZINC097971592 having a binding free energy two times lower than RTP.

Computational approach investigation bioactive molecules from Saussurea Costus plant as SARS-CoV-2 main protease inhibitors using reverse docking, molecular dynamics simulation, and pharmacokinetic ADMET parameters

SARS-COV-2 virus causes (COVID-19) disease; it has become a global pandemic since 2019 and has negatively affected all aspects of human life. Scientists have made great efforts to find a reliable cure, vaccine, or treatment for this emerging disease. Efforts have been directed towards using medicinal plants as alternative medicines, as the active chemical compounds in them have been discovered as potential antiviral or anti-inflammatory agents. In this research, the potential of Saussurea costus (S. Costus) or QUST Al Hindi chemical consistent as potential antiviral agents was investigated by using computational methods such as Reverse Docking, ADMET, and Molecular Dynamics with different proteases COVID-19 such as PDB: 2GZ9; 6LU7; 7AOL, 6Y2E, 6Y84. The results of Reverse Docking the complex between 6LU7 proteases and Cynaropicrin compound being the best complex, as the same result, is achieved by molecular dynamics. Also, the toxicity testing result from ADMET method proved that the complex is the least toxic and the safest possible drug. In addition, 6LU7-Cynaropicrin complex obeyed Lipinski rule; it formed ≤5 H-bond donors and ≤10 H bond acceptors, MW < 500 Daltons, and octanol/water partition coefficient <5.

LC/MS analysis of Viscum cruciatum Sieber ex Boiss. extract with anti-proliferative activity against MCF-7 cell line via G0/G1 cell cycle arrest: An in-silico and in-vitro study

ETHNOPHARMACOLOGICAL RELEVANCE

Viscum cruciatum Sieb is a well-known medicinal plant in Jordan containing various secondary metabolites. It has traditionally been used to treat many ailments, most notably cancer. However, there is a significant gap between scientific research and its value in traditional medicine.

AIM OF THE WORK

To evaluate the antiproliferative activity of different V. cruciatum extracts against MCF-7 breast cancer cell lines and recognize the affected cell cycle phase. Besides, identifying the bioactive components present in the active extract using LC/MS technique. Also, to determine the possible mechanism of action by in silico and in-vitro study.

MATERIALS AND METHODS

V. cruciatum was extracted using solvents with increasing polarity. The antiproliferative effects of the extracts against MCF-7 cell lines were evaluated using SRB assay. Further, flow cytometry was used to identify the inhibited phase of the cell cycle, while LC/MS-MS technique was used to analyze the chemical composition of the most active extract. After that, the putative mechanism of action was investigated through in-silico docking, molecular dynamic simulation for compounds with the highest docking scores, and Western blot analysis of cyclin-dependent kinases (CDK2/4/6).

RESULTS

The chloroform/methanol 90/10 (ChMe) extract showed the most potent antiproliferative effect against MCF-7 cells (IC₅₀ = 23.8 μg/mL), and cell cycle arrest at the G0/G1phase. Furthermore, LC-MS/MS analysis revealed the presence of several polyphenolics belonging to the flavonoids and phenolic acids classes. Additionally, quercetin-4'-glucoside, 3, 5, 7-trihydroxy-4'-methoxy flavone, and hesperetin-7-O-neohesperidoside demonstrated the highest docking binding scores and stable complexes against CDK2 and CDK4/6. Moreover, RMSD (root-mean-square deviation), RMSF (root-mean-square fluctuation), Rg (radius of gyration), and energy analysis during molecular dynamic simulation indicated the stable binding of the studied complexes. These results were supported by Western blot analysis, which revealed the downregulation of CDK2, CDK4, and CDK6 protein expression in MCF-7 cell lines.

CONCLUSION

These findings emphasized the potential breast anticancer activity of the V. cruciatum ChMe extract by arresting the G0/G1 phase of the cell cycle, which could be related to its flavonoid content. Moreover, the results provided experimental support for the traditional anticancer activity of V. cruciatum, and its ChMe extract might be a source of chemoprotective or chemotherapeutic isolates.

Design, synthesis, in vitro biological assessment and molecular modeling insights for novel 3-(naphthalen-1-yl)-4,5-dihydropyrazoles as anticancer agents with potential EGFR inhibitory activity

Currently, the humanity is in a fierce battle against various health-related challenges especially those associated with human malignancies. This created the urge to develop potent and selective inhibitors for tumor cells through targeting specific oncogenic proteins possessing crucial roles in cancer progression and survive. In this respect, new series of pyrazole-thiazol-4-one hybrids (9a–p) were synthesized as potential anticancer agents. All the synthesized molecules exhibited potent antiproliferative actions against breast cancer (BC) T-47D and MDA-MB-231 cell lines with IC₅₀ ranges 3.14–4.92 and 0.62–58.01, respectively. Moreover, the most potent anti-proliferative counterparts 9g and 9k were assessed against EGFR. They displayed nanomolar inhibitory activity, IC₅₀ 267 ± 12 and 395 ± 17 nM, respectively. Worth noting, both compounds 9g and 9k induced apoptosis in MDA-MB-231 cells, and resulted in a cell cycle arrest at G2/M phase. Furthermore, an in silico analysis including docking and molecular dynamic simulations was performed.

A strategy to optimize the peptide-based inhibitors against different mutants of the spike protein of SARS-CoV-2

The SARS-CoV-2 virus has caused high-priority health concerns at a global level. Vaccines have stalled the proliferation of viruses to some extent. Yet, the emergence of newer, potentially more infectious, and dangerous mutants such as Delta and Omicron are among the major challenges in finding a more permanent solution for this pandemic. The effectiveness of antivirals Molnupiravir and Paxlovid, authorized for emergency use by the FDA, are yet to be assessed on a larger population. Patients with a high risk of disease progression have received treatment with antibody-cocktail. Most of the mutations leading to the new lineage of SARS-CoV-2 are found in the spike protein of this virus that plays a key role in facilitating host entry. The current study has investigated how to modify a promising peptide-based inhibitor of spike protein, LCB3, against common mutations, N501Y and K417N in the target protein so that it retains its efficacy against the spike protein. LCB3 being a prototype for protein-based inhibitors is an ideal testing system to learn about protein-based inhibitors. This study proposes the substitutions of amino acid residues of LCB3 inhibitor using a structure-based approach that considers free energy decomposition of residues, the distance between atoms, and the interaction among amino acids. The binding free energy calculations suggest a possible improvement in the binding affinity of existing inhibitor LCB3 to the mutant forms of the S-protein using simple substitutions at specific positions of the inhibitor. This approach, being general, can be used in different inhibitors and other mutations and help in fighting against SARS-CoV-2.Communicated by Ramaswamy H. Sarma.

Development of potent inhibitors by fragment-linking strategies

Fragment-based drug discovery (FBDD) is a method of identifying small molecule hits that can be elaborated rationally through fragment growing, merging, and linking, to afford high affinity ligands for biological targets. Despite the promised theoretical potential of fragment linking, examples are still surprisingly sparse and remain overshadowed by the successes of fragment growing. The aim of this review is to outline a number of key examples of fragment linking strategies and discuss their strengths and limitations. Structure-based approaches including X-ray crystallography and in silico methods fragment optimisation are discussed, as well as fragment linking guided by NMR experiments. Target-guided approaches, exploiting the biological target to assemble its own inhibitors through dynamic combinatorial chemistry (DCC) and kinetic target-guided synthesis (KTGS), are identified as alternative efficient methods for fragment linking.

Structure Prediction and Potential Inhibitors Docking of Enterovirus 2C Proteins

Human enterovirus infections are mostly asymptomatic and occasionally could be severe and life-threatening. The conserved non-structural 2C from enteroviruses protein is a promising target in antiviral therapies against human enteroviruses. Understanding of 2C-drug interactions is crucial for developing the potential antiviral agents. While functions of enterovirus 2C proteins have been widely studied, three-dimensional structure information of 2C is limited. In this study, the structures of 2C proteins from 20 enteroviruses were simulated and reconstructed using I-TASSER programs. Subsequent docking studies of the known 22 antiviral inhibitors for 2C proteins were performed to uncover the inhibitor-binding characteristics of 2C. Among the potential inhibitors, the compound hydantoin exhibited the highest broad-spectrum antiviral activities with binding to 2C protein. The anti-enteroviral activity of GuaHCL, compound 19b, R523062, compound 12a, compound 12b, quinoline analogs 12a, compound 19d, N⁶-benzyladenosine, dibucaine derivatives 6i, TBZE-029, fluoxetine analogs 2b, dibucaine, 2-(α-hydroxybenzyl)-benzimidazole (HBB), metrifudil, pirlindole, MRL-1237, quinoline analogs 10a, zuclopenthixol, fluoxetine, fluoxetine HCl, and quinoline analogs 12c showed a trend of gradual decrease. In addition, the free energy with 22 compounds binding to EV 2C ranged from −0.35 to −88.18 kcal/mol. Our in silico studies will provide important information for the development of pan-enterovirus antiviral agents based on 2C.

Lead generation of cysteine based mesenchymal epithelial transition (c-Met) kinase inhibitors: Using structure-based scaffold hopping, 3D-QSAR pharmacophore modeling, virtual screening, molecular docking, and molecular dynamics simulation

Cysteine-based mesenchymal-epithelial transition (c-Met) is a receptor tyrosine kinase that plays a definitive role during cancer progression and was identified as a possible target for anti-angiogenesis drugs. In the present study, different protocols of computer-based drug design were performed. Construction of predictive pharmacophore model using HypoGen algorithm resulted in a validated model of four features of positive ionizable, hydrogen bond acceptor, hydrophobic, and ring aromatic features with a correlation coefficient of 0.87, a configuration cost of 14.95, and a cost difference of 357.92. The model revealed a promising predictive power and had >90% probability of representing true correlation with the activity data. The model was established using Fisher's validation test at the 95% confidence level and test set prediction (r = 0.96), furthermore, the model was validated by mapping of set of compounds undergoing clinical trials as class Ⅱ c-met inhibitors. The generated valid pharmacophore model was then anticipated for virtual screening of three data bases. Moreover, scaffold hopping using replace fragments protocol was implemented. Hits generated were filtered according to Lipinski's rule; 510 selected hits were anatomized and subjected to molecular docking studies into the crystal structure of c-Met kinase. The good correlation between docking scores and ligand pharmacophore mapping fit values provided a reliable foundation for designing new potentially active candidates that may target c-Met kinase. Eventually, eight hits were selected as potential leads. Subsequently, seven (Hits) have displayed a higher dock score and demonstrated key residue interactions with stable molecular dynamics simulation. Therefore, these c-Met kinase inhibitors may further serve as new chemical spaces in designing new compounds.

Fenticonazole nitrate loaded trans-novasomes for effective management of tinea corporis: design characterization, in silico study, and exploratory clinical appraisal

The current investigation aimed for loading fenticonazole nitrate (FTN), an antifungal agent with low aqueous solubility, into trans-novasomes (TNs) for management of tinea corporis topically. TNs contain Brij^® as an edge activator besides the components of novasomes (cholesterol, Span 60, and oleic acid) owing to augment the topical delivery of FTN. TNs were fabricated applying ethanol injection method based on D-optimal experiment. TNs were evaluated with regard to entrapment efficiency percent (EE%), particle size (PS), polydispersity index (PDI), and zeta potential (ZP). Further explorations were conducted on the optimum formulation (F7). F7 showed spherical appearance with EE%, PS, PDI, and ZP of 100.00 ± 1.10%, 358.60 ± 10.76 nm, 0.51 ± 0.004, and −30.00 ± 0.80 mV, respectively. The in silico study revealed the ability of the FTN–cholesterol complex to maintain favorable interactions throughout the molecular dynamics simulation (MDS) study. Moreover, Trichophyton mentagrophytes growth was inhibited effectively by F7 than by FTN suspension applying 2,3-bis(2-methyloxy-4-nitro-5-sulfophenyl)-2H-tetrazolium-5-carboxanilide (XTT) reduction assay. Furthermore, a clinical appraisal on patients with tinea corporis fungal lesions confirmed the superiority of F7 compared to Miconaz^® cream in the magnitude of clinical cure of tinea corporis. Thereby, TNs could be considered as promising vesicles for enhancing the antifungal potential of FTN for the topical management of tinea corporis.

Investigative on the Molecular Mechanism of Licorice Flavonoids Anti-Melanoma by Network Pharmacology, 3D/2D-QSAR, Molecular Docking, and Molecular Dynamics Simulation

Licorice flavonoids (LCFs) are natural flavonoids isolated from Glycyrrhiza which are known to have anti-melanoma activities in vitro. However, the molecular mechanism of LCF anti-melanoma has not been fully understood. In this study, network pharmacology, 3D/2D-QSAR, molecular docking, and molecular dynamics (MD) simulation were used to explore the molecular mechanism of LCF anti-melanoma. First of all, we screened the key active components and targets of LCF anti-melanoma by network pharmacology. Then, the logIC50 values of the top 20 compounds were predicted by the 2D-QSAR pharmacophore model, and seven highly active compounds were screened successfully. An optimal 3D-QSAR pharmacophore model for predicting the activity of LCF compounds was established by the HipHop method. The effectiveness of the 3D-QSAR pharmacophore was verified by a training set of compounds with known activity, and the possible decisive therapeutic effect of the potency group was inferred. Finally, molecular docking and MD simulation were used to verify the effective pharmacophore. In conclusion, this study established the structure–activity relationship of LCF and provided theoretical guidance for the research of LCF anti-melanoma.

Designing Novel Compounds for the Treatment and Management of RET-Positive Non-Small Cell Lung Cancer-Fragment Based Drug Design Strategy

Rearranged during transfection (RET) is an oncogenic driver receptor that is overexpressed in several cancer types, including non-small cell lung cancer. To date, only multiple kinase inhibitors are widely used to treat RET-positive cancer patients. These inhibitors exhibit high toxicity, less efficacy, and specificity against RET. The development of drug-resistant mutations in RET protein further deteriorates this situation. Hence, in the present study, we aimed to design novel drug-like compounds using a fragment-based drug designing strategy to overcome these issues. About 18 known inhibitors from diverse chemical classes were fragmented and bred to form novel compounds against RET proteins. The inhibitory activity of the resultant 115 hybrid molecules was evaluated using molecular docking and RF-Score analysis. The binding free energy and chemical reactivity of the compounds were computed using MM-GBSA and density functional theory analysis, respectively. The results from our study revealed that the developed hybrid molecules except for LF21 and LF27 showed higher reactivity and stability than Pralsetinib. Ultimately, the process resulted in three hybrid molecules namely LF1, LF2, and LF88 having potent inhibitory activity against RET proteins. The scrutinized molecules were then subjected to molecular dynamics simulation for 200 ns and MM-PBSA analysis to eliminate a false positive design. The results from our analysis hypothesized that the designed compounds exhibited significant inhibitory activity against multiple RET variants. Thus, these could be considered as potential leads for further experimental studies.

Pharmacogenetics and Precision Medicine Approaches for the Improvement of COVID-19 Therapies

Many drugs are being administered to tackle coronavirus disease 2019 (COVID-19) pandemic situations without establishing clinical effectiveness or tailoring safety. A repurposing strategy might be more effective and successful if pharmacogenetic interventions are being considered in future clinical studies/trials. Although it is very unlikely that there are almost no pharmacogenetic data for COVID-19 drugs, however, from inferring the pharmacokinetic (PK)/pharmacodynamic(PD) properties and some pharmacogenetic evidence in other diseases/clinical conditions, it is highly likely that pharmacogenetic associations are also feasible in at least some COVID-19 drugs. We strongly mandate to undertake a pharmacogenetic assessment for at least these drug-gene pairs (atazanavir-UGT1A1, ABCB1, SLCO1B1, APOA5; efavirenz-CYP2B6; nevirapine-HLA, CYP2B6, ABCB1; lopinavir-SLCO1B3, ABCC2; ribavirin-SLC28A2; tocilizumab-FCGR3A; ivermectin-ABCB1; oseltamivir-CES1, ABCB1; clopidogrel-CYP2C19, ABCB1, warfarin-CYP2C9, VKORC1; non-steroidal anti-inflammatory drugs (NSAIDs)-CYP2C9) in COVID-19 patients for advancing precision medicine. Molecular docking and computational studies are promising to achieve new therapeutics against SARS-CoV-2 infection. The current situation in the discovery of anti-SARS-CoV-2 agents at four important targets from in silico studies has been described and summarized in this review. Although natural occurring compounds from different herbs against SARS-CoV-2 infection are favorable, however, accurate experimental investigation of these compounds is warranted to provide insightful information. Moreover, clinical considerations of drug-drug interactions (DDIs) and drug-herb interactions (DHIs) of the existing repurposed drugs along with pharmacogenetic (e.g., efavirenz and CYP2B6) and herbogenetic (e.g., andrographolide and CYP2C9) interventions, collectively called multifactorial drug-gene interactions (DGIs), may further accelerate the development of precision COVID-19 therapies in the real-world clinical settings.

Computational prediction of the potential target of SARS-CoV-2 inhibitor plitidepsin via molecular docking, dynamic simulations and MM-PBSA calculations

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) replication depends on the interaction between the viral proteins and the human translation machinery. The cytotoxic peptide plitidepsin was found to inhibit CoV-2 up to 90% at a concentration of 0.88 nM. In vitro studies suggest that this activity may be attributed to the inhibition of the eukaryotic translation elongation factor 1A (eEF1A). However, recent reports raised the potential for other cellular targets which plitidepsin may use to exert its potent antiviral activity. The lack of data about these potential targets represents a major limitation for its structural optimization. This work describes the use of a molecular modeling approach to rationalize the in vitro antiviral activity of plitidepsin and to identify potential cellular targets. The developed protocol involves an initial molecular docking step followed by molecular dynamics and binding free energy calculations. The results reveal the potential for plitidepsin to bind to the active site of the key enzyme SARS-CoV-2 RdRp. The results also highlight the importance of van der Waals interactions for proper binding with the enzyme. We believe that the results presented in this study could provide the grounds for the optimization of plitidepsin analogues as SARS-CoV-2 inhibitors.

Recent Developments in Free Energy Calculations for Drug Discovery

The grand challenge in structure-based drug design is achieving accurate prediction of binding free energies. Molecular dynamics (MD) simulations enable modeling of conformational changes critical to the binding process, leading to calculation of thermodynamic quantities involved in estimation of binding affinities. With recent advancements in computing capability and predictive accuracy, MD based virtual screening has progressed from the domain of theoretical attempts to real application in drug development. Approaches including the Molecular Mechanics Poisson Boltzmann Surface Area (MM-PBSA), Linear Interaction Energy (LIE), and alchemical methods have been broadly applied to model molecular recognition for drug discovery and lead optimization. Here we review the varied methodology of these approaches, developments enhancing simulation efficiency and reliability, remaining challenges hindering predictive performance, and applications to problems in the fields of medicine and biochemistry.

Toward the Identification of Potential α-Ketoamide Covalent Inhibitors for SARS-CoV-2 Main Protease: Fragment-Based Drug Design and MM-PBSA Calculations

Since December 2019, the world has been facing the outbreak of the SARS-CoV-2 pandemic that has infected more than 149 million and killed 3.1 million people by 27 April 2021, according to WHO statistics. Safety measures and precautions taken by many countries seem insufficient, especially with no specific approved drugs against the virus. This has created an urgent need to fast track the development of new medication against the virus in order to alleviate the problem and meet public expectations. The SARS-CoV-2 3CL main protease (Mpro) is one of the most attractive targets in the virus life cycle, which is responsible for the processing of the viral polyprotein and is a key for the ribosomal translation of the SARS-CoV-2 genome. In this work, we targeted this enzyme through a structure-based drug design (SBDD) protocol, which aimed at the design of a new potential inhibitor for Mpro. The protocol involves three major steps: fragment-based drug design (FBDD), covalent docking and molecular dynamics (MD) simulation with the calculation of the designed molecule binding free energy at a high level of theory. The FBDD step identified five molecular fragments, which were linked via a suitable carbon linker, to construct our designed compound RMH148. The mode of binding and initial interactions between RMH148 and the enzyme active site was established in the second step of our protocol via covalent docking. The final step involved the use of MD simulations to test for the stability of the docked RMH148 into the Mpro active site and included precise calculations for potential interactions with active site residues and binding free energies. The results introduced RMH148 as a potential inhibitor for the SARS-CoV-2 Mpro enzyme, which was able to achieve various interactions with the enzyme and forms a highly stable complex at the active site even better than the co-crystalized reference.

Salmon sperm DNA binding study to cabozantinib, a tyrosine kinase inhibitor: Multi-spectroscopic and molecular docking approaches

In the current work, the binding interaction of cabozantinib with salmon sperm DNA (SS-DNA) was studied under simulated physiological conditions (pH 7.4) using fluorescence emission spectroscopy, UV-Vis absorption spectroscopy, viscosity measurement, ionic strength measurement, FT-IR spectroscopy, and molecular modeling methods. The obtained experimental data demonstrated an apparent binding interaction of cabozantinib with SS-DNA. The binding constant (K_b) of cabozantinib with SS-DNA evaluated from the Benesi-Hildebrand plot was equal to 5.79 × 10⁵ at 298 K. The entropy and enthalpy changes (∆S⁰ and ∆H⁰) in the binding interaction of SS-DNA with cabozantinib were 44.13 J mol^-1 K^-1 and -19.72 KJ mol^-1, respectively, demonstrating that the basic binding interaction forces are hydrophobic and hydrogen bonding interactions. Results from UV-Vis absorption spectroscopy, competitive binding interaction with rhodamine B or ethidium bromide, and viscosity measurements revealed that cabozantinib binds to SS-DNA via minor groove binding. The molecular docking results revealed that cabozantinib fits into the AT-rich region of the B-DNA minor groove and the binding site of cabozantinib was 4 base pairs long. Moreover, cabozantinib has eight active torsions, implying a high degree of flexibility in its structure, which played a significant role in the formation of a stable cabozantinib-DNA complex.

In silico identification of novel SARS-COV-2 2'-O-methyltransferase (nsp16) inhibitors: structure-based virtual screening, molecular dynamics simulation and MM-PBSA approaches

The novel coronavirus disease COVID-19, caused by the virus SARS CoV-2, has exerted a significant unprecedented economic and medical crisis, in addition to its impact on the daily life and health care systems all over the world. Regrettably, no vaccines or drugs are currently available for this new critical emerging human disease. Joining the global fight against COVID-19, in this study we aim at identifying a potential novel inhibitor for SARS COV-2 2'-O-methyltransferase (nsp16) which is one of the most attractive targets in the virus life cycle, responsible for the viral RNA protection via a cap formation process. Firstly, nsp16 enzyme bound to Sinefungin was retrieved from the protein data bank (PDB ID: 6WKQ), then, a 3D pharmacophore model was constructed to be applied to screen 48 Million drug-like compounds of the Zinc database. This resulted in only 24 compounds which were subsequently docked into the enzyme. The best four score-ordered hits from the docking outcome exhibited better scores compared to Sinefungin. Finally, three molecular dynamics (MD) simulation experiments for 150 ns were carried out as a refinement step for our proposed approach. The MD and MM-PBSA outputs revealed compound 11 as the best potential nsp16 inhibitor herein identified, as it displayed a better stability and average binding free energy for the ligand-enzyme complex compared to Sinefungin.

In-Silico Drug Designing of Spike Receptor with Its ACE2 Receptor and Nsp10/Nsp16 MTase Complex Against SARS-CoV-2

The realm Riboviria constitutes Coronaviruses, which led to the emergence of the pandemic COVID 19 in the twenty-first century affected millions of lives. At present, the management of COVID 19 largely depends on antiviral therapeutics along with the anti-inflammatory drug. The vaccine is under the final clinical phase, and emergency use is available. We aim at ACE2 and Nsp10/Nsp16 MTase as potential drug candidate in COVID 19 management in the present work. For drug designing, various computational simulation strategies have been employed like Swiss-Model, Hawk Dock, HDOCK, py Dock, and PockDrug for homology modeling, binding energies of the molecule with a target, simulate the conformation and binding poses, statistics of protein lock with target key and drug ability, respectively. The current in-silico screening depicts that the spike protein receptor is complementary to the target when bound to each other and forms a stable complex. The MMGBSA free energy binding property of receptor and ligand is critical. The intermolecular Statistics with the target Nsp10/Nsp16 MTase complex are plausible. We have also observed a high-affinity pocket binding site with the target. Therefore, the favorable intermolecular interactions and Physico-chemical properties emanate as a drug candidate treating COVID-19. This study has approached computational tools to analyze the conformation, binding affinity, and drug ability of receptor-ligand. Thus, the spike receptor with its ACE2 receptor with Nsp10/Nsp16 MTase complex would be a potent drug against SARS CoV-2 and can cure the infection as per consensus scoring.

In silico identification of potential SARS COV-2 2′-O-methyltransferase inhibitor: fragment-based screening approach and MM-PBSA calculations

In the present era, there are many efforts trying to face the emerging and successive waves of the COVID-19 pandemic. This has led to considering new and unusual targets for SARS CoV-2. 2′-O-Methyltransferase (nsp16) is a key and attractive target in the SARS CoV-2 life cycle since it is responsible for the viral RNA protection via a cap formation process. In this study, we propose a new potential inhibitor for SARS COV-2 2′-O-methyltransferase (nsp16). A fragment library was screened against the co-crystal structure of the SARS COV-2 2′-O-methyltransferase complexed with Sinefungin (nsp16 – PDB ID: 6WKQ), and consequently the best proposed fragments were linked via a de novo approach to build molecule AP-20. Molecule AP-20 displayed a superior docking score to Sinefungin and reproduced the key interactions in the binding site of 2′-O-methyltransferase. Three molecular dynamic simulations of the 2′-O-methyltransferase apo structure and its complexed forms with AP-20 and Sinefungin were performed for 150 nano-seconds to provide insights on the dynamic nature of such setups and to assess the stability of the proposed AP-20/enzyme complex. AP-20/enzyme complex demonstrated better stability for the ligand–enzyme complex compared to Sinefungin in a respective setup. Furthermore, MM-PBSA binding free energy calculations showed a better profile for AP-20/enzyme complex compared to Sinefungin/enzyme complex emphasizing the potential inhibitory effect of AP-20 on SARS COV-2 2′-O-methyltransferase. We endorse our designed molecule AP-20 to be further explored via experimental evaluations to confront the spread of the emerging COVID-19. Also, in silico ADME profiling has ascribed to AP-20 an excellent safety and metabolic stability profile.

The identification of AP-20 as a potential SARS COV-2 2′-O-methyltransferase inhibitor: fragment-based screening approach and MM-PBSA calculations.

Immune response and possible therapeutics in COVID-19

COVID-19 has emerged as a pandemic affecting about 213 countries in all the continents of the globe, resulting in more than 37.8 million individuals getting infected and over 1.08 million deaths worldwide, jeopardizing global human health and the economy. This presents an urgent need to develop therapies that target the SARS-CoV2 virus specifically. This review aims at presenting the available information on the coronavirus disease 2019 along with various drugs that are having widespread use until a vaccine candidate is available to aid in the development of therapeutic strategies against COVID-19.