Identification of natural diterpenes isolated from Azorella species targeting dispersin B using in silico approaches.

CONTEXT: A bacterial biofilm is a cluster of bacterial cells embedded in a self-produced matrix of extracellular polymeric substances such as DNA, proteins, and polysaccharides. Several diseases have been reported to cause by bacterial biofilms, and difficulties in treating these infections are of concern. This work aimed to identify the inhibitor with the highest binding affinity for the receptor protein by screening various inhibitors obtained from Azorella species for a potential target to inhibit dispersin B. This work shows that azorellolide has the highest binding affinity (- 8.2 kcal/mol) among the compounds tested, followed by dyhydroazorellolide, mulinone A, and 7-acetoxy-mulin-9,12-diene which all had a binding affinity of - 8.0 kcal/mol. To the best of our knowledge, this is the first study to evaluate and contrast several diterpene compounds as antibacterial biofilm chemicals. METHODS: Here, molecular modelling techniques tested 49 diterpene compounds of Azorella and six FDA-approved antibiotics medicines for antibiofilm activity. Since protein-like interactions are crucial in drug discovery, AutoDock Vina was initially employed to carry out structure-based virtual screening. The drug-likeness and ADMET properties of the chosen compounds were examined to assess the antibiofilm activity further. Lipinski's rule of five was then applied to determine the antibiofilm activity. Then, molecular electrostatic potential was used to determine the relative polarity of a molecule using the Gaussian 09 package and GaussView 5.08. Following three replica molecular dynamic simulations (using the Schrodinger program, Desmond 2019-4 package) that each lasted 100 ns on the promising candidates, binding free energy was estimated using MM-GBSA. Structural visualisation was used to test the binding affinity of each compound to the crystal structure of dispersin B protein (PDB: 1YHT), a well-known antibiofilm compound.

A computational predicting of possible inhibitors of the main SARS-CoV-2 protease found in Algerian herbal medicines

COVID-19 is a zoonotic viral disease caused by the SARS-CoV-2 virus. Its abrupt outbreak has caused a tremendous challenge to public health systems due to the rapid spread of the virus. In this sense, a great deal of work has been focused on finding substances from herbal plants to be used against this virus. In order to investigate the molecular interactions between natural metabolites from Algerian herbal plants and the SARS-CoV-2 protease Mpro, computational docking and molecular dynamics were used, also the drug likeness degree and in silico ADMET prediction were carried out in this study. warfarin and catalponol preferentially binds to a pocket of the SARS-Cov-2 Mpro active site that is made up of residues His 41 to Glu 166 and Leu 27 to His 163 with a relatively low binding energy of -7.1 and -6.6 kcal/mol respectively. Dynamic molecular assay further established that only warfarin managed to stay in the active site. The results suggest that warfarin may be an interesting candidate for development as a medical treatment of COVID-19 and more research is proposed, without disregarding its toxicity which deserves to be well studied.

El COVID-19 es una enfermedad zoonótica causada por el virus SARS-CoV-2. Su abrupto brote en años recientes ha supuesto un tremendo desafío para los sistemas de salud pública, como resultado de la rápida propagación del virus. En tal sentido, muchos trabajos se han centrado en encontrar sustancias de origen vegetal, para ser utilizadas contra este virus. Se realizaron estudios de acoplamiento computacional y dinámica molecular para investigar las interacciones moleculares entre los metabolitos secundarios de las plantas herbales argelinas con la Proteasa Mpro del SARS-CoV-2, también se realizaron estudios de semejanza con drogas mediante ADMET computacional. La warfarina y el catalponol se unen preferentemente al sitio activo SARS-Cov-2 Mpro que se compone de residuos His 41 a Glu 166 y Leu 27 a His 163 con una energía de enlace relativamente baja, -7,1 y -6,6 kcal/mol respectivamente. Los ensayos de dinámica molecular establecieron además que sólo la warfarina logró permanecer en el sitio activo. Estos resultados sugieren que la warfarina puede ser un candidato interesante para el desarrollo como tratamiento médico de COVID-19 e instan a realizar más investigaciones, sin dejar de lado estudios de toxicidad respectivos.

A COVID-19 é uma doença zoonótica causada pelo vírus SARS-CoV-2, cujo surto abrupto nos últimos anos representou um tremendo desafio para os sistemas de saúde pública devido à rápida disseminação do vírus. Nesse sentido, muitos trabalhos têm se concentrado em encontrar substâncias de origem vegetal, para serem utilizadas contra esse vírus. Estudos de ancoragem computacional e dinâmica molecular foram conduzidos para investigar as interações moleculares entre metabólitos secundários de ervas argelinas com o SARS-CoV-2 Protease Mpro, estudos de similaridade de drogas também foram conduzidos usando ADMET in silico. A varfarina e o catalponol ligam-se preferencialmente ao sítio ativo SARS-Cov-2 Mpro que é composto pelos resíduos His 41 a Glu 166 e Leu 27 a His 163 com uma energia de ligação relativamente baixa, -7,1 e -6,6 kcal/mol, respectivamente. Ensaios de dinâmica molecular estabeleceram ainda que apenas a varfarina conseguiu permanecer no sítio ativo. Esses resultados sugerem que a varfarina pode ser um candidato interessante para desenvolvimento como tratamento médico para COVID-19 e exigem mais pesquisas, incluindo os respectivos estudos de toxicidade.

Unsymmetrical aromatic disulfides as SARS-CoV-2 Mpro inhibitors: Molecular docking, molecular dynamics, and ADME scoring investigations.

COVID-19 pandemic caused by very severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) agent is an ongoing major global health concern. The disease has caused more than 452 million affected cases and more than 6 million death worldwide. Hence, there is an urgency to search for possible medications and drug treatments. There are no approved drugs available to treat COVID-19 yet, although several vaccine candidates are already available and some of them are listed for emergency use by the world health organization (WHO). Identifying a potential drug candidate may make a significant contribution to control the expansion of COVID-19. The in vitro biological activity of asymmetric disulfides against coronavirus through the inhibition of SARS-CoV-2 main protease (Mpro) protein was reported. Due to the lack of convincing evidence those asymmetric disulfides have favorable pharmacological properties for the clinical treatment of Coronavirus, in silico evaluation should be performed to assess the potential of these compounds to inhibit the SARS-CoV-2 Mpro. In this context, we report herein the molecular docking for a series of 40 unsymmetrical aromatic disulfides as SARS-CoV-2 Mpro inhibitor. The optimal binding features of disulfides within the binding pocket of SARS-CoV-2 endoribonuclease protein (Protein Data Bank [PDB]: 6LU7) was described. Studied compounds were ranked for potential effectiveness, and those have shown high molecular docking scores were proposed as novel drug candidates against SARS-CoV-2. Moreover, the outcomes of drug similarity and ADME (Absorption, Distribution, Metabolism, and Excretion) analyses have may have the effectiveness of acting as medicines, and would be of interest as promising starting point for designing compounds against SARS-CoV-2. Finally, the stability of these three compounds in the complex with Mpro was validated through molecular dynamics (MD) simulation, in which they displayed stable trajectory and molecular properties with a consistent interaction profile.

QSAR, ADMET In Silico Pharmacokinetics, Molecular Docking and Molecular Dynamics Studies of Novel Bicyclo (Aryl Methyl) Benzamides as Potent GlyT1 Inhibitors for the Treatment of Schizophrenia.

Forty-four bicyclo ((aryl) methyl) benzamides, acting as glycine transporter type 1 (GlyT1) inhibitors, are developed using molecular modeling techniques. QSAR models generated by multiple linear and non-linear regressions affirm that the biological inhibitory activity against the schizophrenia disease is strongly and significantly correlated with physicochemical, geometrical and topological descriptors, in particular: Hydrogen bond donor, polarizability, surface tension, stretch and torsion energies and topological diameter. According to in silico ADMET properties, the most active ligands (L6, L9, L30, L31 and L37) are the molecules having the highest probability of penetrating the central nervous system (CNS), but the molecule 32 has the highest probability of being absorbed by the gastrointestinal tract. Molecular docking results indicate that Tyr124, Phe43, Phe325, Asp46, Phe319 and Val120 amino acids are the active sites of the dopamine transporter (DAT) membrane protein, in which the most active ligands can inhibit the glycine transporter type 1 (GlyT1). The results of molecular dynamics (MD) simulation revealed that all five inhibitors remained stable in the active sites of the DAT protein during 100 ns, demonstrating their promising role as candidate drugs for the treatment of schizophrenia.

In silico detection of potential inhibitors from vitamins and their derivatives compounds against SARS-CoV-2 main protease by using molecular docking, molecular dynamic simulation and ADMET profiling.

COVID-19 is a new infectious disease caused by SARS-COV-2 virus of the coronavirus Family. The identification of drugs against this serious infection is a significant requirement due to the rapid rise in the positive cases and deaths around the world. With this concept, a molecular docking analysis for vitamins and their derivatives (28 molecules) with the active site of SARS-CoV-2 main protease was carried out. The results of molecular docking indicate that the structures with best binding energy in the binding site of the studied enzyme (lowest energy level) are observed for the compounds; Folacin, Riboflavin, and Phylloquinone oxide (Vitamin K1 oxide). A Molecular Dynamic simulation was carried out to study the binding stability for the selected vitamins with the active site of SARS-CoV-2 main protease enzyme. Molecular Dynamic shows that Phylloquinone oxide and Folacin are quite unstable in binding to SARS-CoV-2 main protease, while the Riboflavin is comparatively rigid. The higher fluctuations in Phylloquinone oxide and Folacin indicate that they may not fit very well into the binding site. As expected, the Phylloquinone oxide exhibits small number of H-bonds with protein and Folacin does not form a good interaction with protein. Riboflavin exhibits the highest number of Hydrogen bonds and forms consistent interactions with protein. Additionally, this molecule respect the conditions mentioned in Lipinski's rule and have acceptable ADMET proprieties which indicates that Riboflavin (Vitamin B2) could be interesting for the antiviral treatment of COVID-19.

Camphor, Artemisinin and Sumac Phytochemicals as inhibitors against COVID-19: Computational approach.

Covid-19 is an emerging infectious disease caused by coronavirus SARS-CoV-2. Due to the rapid rise in deaths resulted from this infection all around the world, the identification of drugs against this new coronavirus is an important requirement. Among the drugs that can fight this type of infection; natural products are substances that serve as sources of beneficial chemical molecules for the development of effective therapies. In this study, Camphor, Artemisinin and 14 Sumac phytochemicals were docked in the active site of SARS-CoV-2 main protease (PDB code: 6LU7). We have also performed molecular dynamic simulation at 100 ns with MM-GBSA/PBSA analysis for the structures with the best affinity in the binding site of the studied enzyme (Hinokiflavone and Myricetin) after docking calculations to consider parameters like RMSD, covariance, PCA, radius of gyration, potential energy, temperature and pressure. The result indicates that Hinokiflavone and Myricetin are the structures with best affinity and stability in the binding site of the studied enzyme and they respect the conditions mentioned in Lipinski's rule and have acceptable ADMET proprieties; so, these compounds have important pharmacokinetic properties and bioavailability, and they could have more potent antiviral treatment of COVID-19 than the other studied compounds.

QSAR study of unsymmetrical aromatic disulfides as potent avian SARS-CoV main protease inhibitors using quantum chemical descriptors and statistical methods.

In silico research was executed on forty unsymmetrical aromatic disulfide derivatives as inhibitors of the SARS Coronavirus (SARS-CoV-1). Density functional theory (DFT) calculation with B3LYP functional employing 6-311 â€‹+ â€‹G(d,p) basis set was used to calculate quantum chemical descriptors. Topological, physicochemical and thermodynamic parameters were calculated using ChemOffice software. The dataset was divided randomly into training and test sets consisting of 32 and 8 compounds, respectively. In attempt to explore the structural requirements for bioactives molecules with significant anti-SARS-CoV activity, we have built valid and robust statistics models using QSAR approach. Hundred linear pentavariate and quadrivariate models were established by changing training set compounds and further applied in test set to calculate predicted IC50 values of compounds. Both built models were individually validated internally as well as externally along with Y-Randomization according to the OECD principles for the validation of QSAR model and the model acceptance criteria of Golbraikh and Tropsha's. Model 34 is chosen with higher values of R2, R2 test and Q2cv (R2 â€‹= â€‹0.838, R2 test â€‹= â€‹0.735, Q2 cv â€‹= â€‹0.757). It is very important to notice that anti-SARS-CoV main protease of these compounds appear to be mainly governed by five descriptors, i.e. highest occupied molecular orbital energy (EHOMO), energy of molecular orbital below HOMO energy (EHOMO-1), Balaban index (BI), bond length between the two sulfur atoms (S1S2) and bond length between sulfur atom and benzene ring (S2Bnz). Here the possible action mechanism of these compounds was analyzed and discussed, in particular, important structural requirements for great SARS-CoV main protease inhibitor will be by substituting disulfides with smaller size electron withdrawing groups. Based on the best proposed QSAR model, some new compounds with higher SARS-CoV inhibitors activities have been designed. Further, in silico prediction studies on ADMET pharmacokinetics properties were conducted.

New dehydroabietic acid (DHA) derivatives with anticancer activity against HepG2 cancer cell lines as a potential drug targeting EGFR kinase domain. CoMFA study and virtual ligand-based screening.

Liver cancer has become the third type of cancer that causes death; this is why the design of new chemotherapeutic drugs against this disease is a major need. With this idea, a series of Dehydroabietic Acid-Based Acylhydrazones have been used to generate a CoMFA model to design new anticancer agents. In this study, we employed a Comparative Molecular Field Analysis studies, we performed those methods on Dehydroabietic Acid-Based Acylhydrazones against HepG2 human cancer cell line. The statistical results are encouraging with Q2 equal to 0.527 and R2 equal to 0.962. The predictive ability of this model was determined using a test set of Dehydroabietic Acid-Based Acylhydrazones that gave an acceptable predictive correlation (R2test) value of 0.614. The developed model guides to design five new molecules with enhanced activity as potential drugs. On the other hand to determine a potential target to these ligands we have established a virtual screening using reverse docking with the most active molecule and 42 antiproliferative targets. Based on the affinity of complex ligand-Target, the intracellular domain of EGFR shows high stability. This suggests that our designed molecules can inhibit the target EGFR which is an important target on targeted therapy of many types of cancer.Communicated by Ramaswamy H. Sarma.

Discovery of Potent SARS-CoV-2 Inhibitors from Approved Antiviral Drugs via Docking and Virtual Screening.

BACKGROUND: Coronavirus Disease 2019 (COVID-19) pandemic continues to threaten patients, societies and healthcare systems around the world. There is an urgent need to search for possible medications. OBJECTIVE: This article intends to use virtual screening and molecular docking methods to find potential inhibitors from existing drugs that can respond to COVID-19. METHODS: To take part in the current research investigation and to define a potential target drug that may protect the world from the pandemic of corona disease, a virtual screening study of 129 approved drugs was carried out which showed that their metabolic characteristics, dosages used, potential efficacy and side effects are clear as they have been approved for treating existing infections. Especially 12 drugs against chronic hepatitis B virus, 37 against chronic hepatitis C virus, 37 against human immunodeficiency virus, 14 anti-herpesvirus, 11 anti-influenza, and 18 other drugs currently on the market were considered for this study. These drugs were then evaluated using virtual screening and molecular docking studies on the active site of the (SARS-CoV-2) main protease (6lu7). Once the efficacy of the drug is determined, it can be approved for its in vitro and in vivo activity against the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), which can be beneficial for the rapid clinical treatment of patients. These drugs were considered potentially effective against SARS-CoV-2 and those with high molecular docking scores were proposed as novel candidates for repurposing. The N3 inhibitor cocrystallized with protease (6lu7) and the anti-HIV protease inhibitor Lopinavir were used as standards for comparison. RESULTS: The results suggest the effectiveness of Beclabuvir, Nilotinib, Tirilazad, Trametinib and Glecaprevir as potent drugs against SARS-CoV-2 since they tightly bind to its main protease. CONCLUSION: These promising drugs can inhibit the replication of the virus; hence, the repurposing of these compounds is suggested for the treatment of COVID-19. No toxicity measurements are required for these drugs since they were previously tested prior to their approval by the FDA. However, the assessment of these potential inhibitors as clinical drugs requires further in vivo tests of these drugs.

Assessment of effective imidazole derivatives against SARS-CoV-2 main protease through computational approach.

Because of the fast increase in deaths due to Corona Viral Infection in majority region in the world, the detection of drugs potent of this infection is a major need. With this idea, docking study was executed on eighteen imidazole derivatives based on 7-chloro-4-aminoquinoline against novel Coronavirus (SARS-CoV-2). In this study, we carried out a docking study of these molecules in the active site of SARS-CoV-2 main protease. The result indicate that Molecules N° 3, 7 and 14 have more binding energy with SARS-CoV-2 main protease recently crystallized (pdb code 6LU7) in comparison with the other imidazole derivatives and the two drug; Chloroquine and hydroxychloroquine. Because of the best energy of interaction, these three molecules could have the most potential antiviral treatment of COVID-19 than the other studied compounds. The structures with best affinity in the binding site of the protease have more than 3 cycles and electronegative atoms in the structure. This may increase the binding affinity of these molecules because of formation of π-bonds, halogen interactions and/or Hydrogen bond interactions between compounds and the enzyme. So, compounds with more cycles and electronegative atoms could have a potent inhibition of SARS-CoV-2 main protease.

Molecular docking analysis of N-substituted Oseltamivir derivatives with the SARS-CoV-2 main protease.

The identification of chemotherapeutic drugs against Novel Coronavirus (2019-nCoV) is a significant requirement due to the rapid rise in deaths due to Corona Viral Infection all around the world. Therefore, it is of interest to document the molecular docking analysis data of 32 N-substituted Oseltamivir derivatives inhibitors of influenza virus H5N1 with the Novel Coronavirus main protease (2019-nCoV). We describe the optimal binding features of Oseltamivir derivatives with the SARS-Cov-2 main protease (Code PDB: 6LU7) for further consideration.

Study of novel triazolo-benzodiazepine analogues as antidepressants targeting by molecular docking and ADMET properties prediction.

In this study, we have selected a series of a new family of molecules bearing Triazolo-benzodiazepines, an eleven membered heterocyclic ring has been studied for antidepression activity. Docking studies suggested that all the eleven ligands interacted well within active site of Drosophila melanogaster dopamine transporter (dDAT) (PDB ID: 4M48). Most ligands formed H-bond with amino acid Phe43, Asp46, Asp475, Tyr123, Ser421 and/or Gln316 and also exhibited Pi and Pi-Pi interactions with amino acid residues Tyr124, Phe319, Phe43, Phe325, Ala479 and Val120. In silico ADME evaluations of compounds showed more than 96% intestinal absorption for all compounds. During in vitro Toxicity properties prediction, the Triazolo-benzodiazepines derivatives: M1, M2, M3 and M11 showed less toxicity than the other studied molecules against algae, for daphnia the molecules M1, M2, M3, M8, M10 and M11 showed less toxicity than the reference molecule (Nortriptyline).

QSAR study of anti-Human African Trypanosomiasis activity for 2-phenylimidazopyridines derivatives using DFT and Lipinski's descriptors.

The quantitative structure-activity relationship (QSAR) of sixty 2-phenylimidazopyridines derivatives with anti-Human African Trypanosomiasis (anti-HAT) activity has been studied by using the density functional theory (DFT) and statistical methods. Becke's three-parameter hybrid method and the Lee-Yang-Parr B3LYP functional employing 6-31G(d) basis set are used to calculate quantum chemical descriptors using Gaussian 03W software, and the five Lipinski's parameters were calculated using ChemOffice software. In order to obtain robust and reliable QSAR model, the original dataset was randomly divided into training and prediction sets comprising 48 and 12 compounds, respectively. An optimal model for the training set with significant statistical quality was established. The same model was further applied to predict pEC50 values of the 12 compounds in the test set, further showing that this QSAR model has high predictive ability. It is very interesting to find that the anti-HAT of these compounds appear to be mainly governed by four factors, i.e., the number of H-bond donors, the lowest unoccupied molecular orbital energy, the molecular weight and the octanol/water partition coefficient. Here the possible action mechanism of these compounds was analysed and discussed, in particular, important structural requirements for great anti-HAT activity will be by increasing molecular size and substitute the 2-phenylimidazopyridines derivatives with polar, ionic, stronger accepting electron ability group and heteroatoms attached to one or more hydrogen atoms. Based on this proposed QSAR model, some new compounds with higher anti-HAT activities have been theoretically designed. Such results can offer useful theoretical references for future experimental works.