scholarly journals In silico Design of Novel N-hydrosulfonylbenzamides inhibitors of dengue RNA-dependent RNA polymerase showing favorable predicted pharmacokinetic profiles

2021 ◽  
Vol 5 (2) ◽  
pp. 561-584
Author(s):  
Kouakou Kouakou Jean-Louis ◽  
◽  
Melalie Keita ◽  
Akori Elvice Esmel ◽  
Brice Dali ◽  
...  
Keyword(s):  
Gas Phase ◽  
In Silico ◽  
Pharmacophore Model ◽  
Pharmacokinetic Profile ◽  
Qsar Model ◽  
Active Conformation ◽  
Rna Dependent Rna Polymerase ◽  
In Silico Screening ◽  
Lipinski’S Rule ◽  
Adme Properties

Background: In recent years, there has been a growing interest in Denv NS5 inhibition, with several reported RdRp inhibitors such as sulfonylbenzamides, non-nucleo-side inhibitors without any 3D-QSAR pharmacophore (PH4) available. In this context, we report here, in silico design and virtual evaluation of novel sulfonylbenzamides Denv RdRp inhibitors with favorable predicted pharmacokinetic profile. Methods: By using in situ modifications of the crystal structure of 5-(5-(3-hydroxyprop-1-yn-1-yl)thiophen-2-yl)-4- methoxy-2-methyl-N-(methylsulfonyl) benzamide (EHB)-RdRp complex (PDB entry 5HMZ), 3D models of RdRp-EHBx complexes were prepared for a training set of 18 EHBs with experimentally determined inhibitory potencies (half-maximal inhibitory concentrations IC50exp). In the search for active conformation of the EHB1-18, linear QSAR model was prepared, which correlated computed gas phase enthalpies of formation ∆∆HMM of RdRp-EHBx complexes with the IC50exp. Further, considering the solvent effect and entropy changes upon ligand binding resulted in a superior QSAR model correlating computed complexation Gibbs free energies (∆∆Gcom). The successive pharmacophore model (PH4) generated from the active conformations of EHBs served as a virtual screening tool of novel analogs included in a virtual combinatorial library (VCL) of compounds with scaffolds restricted to phenyl. The VCL filtered by the Lipinski’s rule-of-five was screened by the PH4 model to identify new EHB analogs. Results: Gas phase QSAR model: -log10(IC50exp) = p IC50exp =-0.1403 x ∆∆HMM _ 7.0879, R2 = 0.73; superior aqueous phase QSAR model: p IC50exp = -0.2036 x ∆∆Gcom + 7.4974, R2 = 0.81 and PH4 pharmacophore model: p IC50exp = 1.0001 x p IC50pre -0.0017, R2 = 0.97. The VCL of more than 30 million EHBs was filtered down to 125,915 analogs Lipinski’s rule. The five-point PH4 screening retained 329 new and potent EHBs with predicted inhibitory potencies p IC50pre up to 30 times lower than that of EHB1 (IC50exp = 23nM). Predicted pharmacokinetic profile of the new analogs showed enhanced cell membrane permeability and high human oral absorption compared to the alone drug to treat dengue virus. Conclusions: Combined use of QSAR models, which considered binding of the EHBs to RdRp, pharmacophore model and ADME properties helped to recognize bound active conformation of the sulfonylbenzamide inhibitors, permitted in silico screening of VCL of compounds sharing sulfonylbenzamide scaffold and identify new analogs with predicted high inhibitory potencies and favorable pharmacokinetic profiles. Keywords: ADME properties prediction, Dengue, 3-(5-ethynylthiophen-2-yl)-N-hydrosulfonylbenzamides, in silico screening, RNA-dependent RNA polymerase.

scholarly journals Structure-Based Design and in Silico Screening of Virtual Combinatorial Library of Benzamides Inhibiting 2-trans Enoyl-Acyl Carrier Protein Reductase of Mycobacterium tuberculosis with Favorable Predicted Pharmacokinetic Profiles

2019 ◽  
Vol 20 (19) ◽  
pp. 4730
Author(s):  
Koffi Charles Kouman ◽  
Melalie Keita ◽  
Raymond Kre N’Guessan ◽  
Luc Calvin Owono Owono ◽  
Eugene Megnassan ◽  
...  
Keyword(s):  
Gas Phase ◽  
In Silico ◽  
Combinatorial Library ◽  
Acyl Carrier Protein ◽  
Pharmacophore Model ◽  
Qsar Model ◽  
Active Conformation ◽  
In Silico Screening ◽  
Lipinski’S Rule ◽  
Pharmacokinetic Profiles

Background: During the previous decade a new class of benzamide-based inhibitors of 2-trans enoyl-acyl carrier protein reductase (InhA) of Mycobacterium tuberculosis (Mt) with unusual binding mode have emerged. Here we report in silico design and evaluation of novel benzamide InhA-Mt inhibitors with favorable predicted pharmacokinetic profiles. Methods: By using in situ modifications of the crystal structure of N-benzyl-4-((heteroaryl)methyl) benzamide (BHMB)-InhA complex (PDB entry 4QXM), 3D models of InhA-BHMBx complexes were prepared for a training set of 19 BHMBs with experimentally determined inhibitory potencies (half-maximal inhibitory concentrations IC50exp). In the search for active conformation of the BHMB1-19, linear QSAR model was prepared, which correlated computed gas phase enthalpies of formation (∆∆HMM) of InhA-BHMBx complexes with the IC50exp. Further, taking into account the solvent effect and entropy changes upon ligand, binding resulted in a superior QSAR model correlating computed complexation Gibbs free energies (∆∆Gcom). The successive pharmacophore model (PH4) generated from the active conformations of BHMBs served as a virtual screening tool of novel analogs included in a virtual combinatorial library (VCL) of compounds containing benzamide scaffolds. The VCL filtered by Lipinski’s rule-of-five was screened by the PH4 model to identify new BHMB analogs. Results: Gas phase QSAR model: −log10(IC50exp) = pIC50exp = −0.2465 × ∆∆HMM + 7.95503, R2 = 0.94; superior aqueous phase QSAR model: pIC50exp = −0.2370 × ∆∆Gcom + 7.8783, R2 = 0.97 and PH4 pharmacophore model: p IC 50 exp = 1.0013 × p IC 50 exp − 0.0085, R2 = 0.95. The VCL of more than 114 thousand BHMBs was filtered down to 73,565 analogs Lipinski’s rule. The five-point PH4 screening retained 90 new and potent BHMBs with predicted inhibitory potencies IC50pre up to 65 times lower than that of BHMB1 (IC50exp = 20 nM). Predicted pharmacokinetic profile of the new analogs showed enhanced cell membrane permeability and high human oral absorption compared to current anti-tuberculotics. Conclusions: Combined use of QSAR models that considered binding of the BHMBs to InhA, pharmacophore model, and ADME properties helped to recognize bound active conformation of the benzamide inhibitors, permitted in silico screening of VCL of compounds sharing benzamide scaffold and identification of new analogs with predicted high inhibitory potencies and favorable pharmacokinetic profiles.

A QSAR Model for in Silico Screening of MAO-A Inhibitors. Prediction, Synthesis, and Biological Assay of Novel Coumarins†

2006 ◽  
Vol 49 (3) ◽  
pp. 1149-1156 ◽  
Author(s):  
Lourdes Santana ◽  
Eugenio Uriarte ◽  
Humberto González-Díaz ◽  
Giuseppe Zagotto ◽  
Ramón Soto-Otero ◽  
...  
Keyword(s):  
In Silico ◽  
Qsar Model ◽  
Biological Assay ◽  
In Silico Screening ◽  
Mao A

scholarly journals In Silico Ligand-Based Methods Targeting Porcupine Receptor Inhibitors with Potential Anticancer Effect

Proceedings ◽  
2018 ◽  
Vol 9 (1) ◽  
pp. 19
Author(s):  
Ana Borota ◽  
Luminita Crisan
Keyword(s):  
Wnt Signaling ◽  
In Silico ◽  
Pharmacophore Model ◽  
Correlation Coefficients ◽  
3D Qsar ◽  
Qsar Model ◽  
Hydrogen Bond Donor ◽  
Screening Process ◽  
Wnt Proteins ◽  
In Silico Study

Porcupine is a protein belonging to the O-acyltransferase family, involved in the catalyzing of palmitoylation of wingless-related integration (WNT) proteins. WNT signaling has significant roles in many physiological functions, e.g., hematopoiesis, homeostasis, neurogenesis, and apoptosis. Anomalous WNT signaling has been observed to be related to tumor generation, and metabolic and neurodegenerative disorders. Therefore, compounds that inhibit this pathway are of great interest for the development of therapeutic approaches. For a better understanding of the common traits of such compounds, we have undertaken an in silico study in order to develop a valid ligand-based pharmacophore model based on a series of porcupine inhibitors. The best pharmacophore hypothesis found after the 3D QSAR validation process is represented by the following features: one hydrogen bond donor (D), three rings (R) and one hydrophobic centroid (H). The 3D-QSAR model obtained using the DRRRH hypothesis shows statistically significant parameters: correlation coefficients for the training set: R2 of 0.90, and a predictive correlation coefficient for the test set, Q2 of 0.86. The assessment of the pharmacophore model was also done and provided very reliable metrics values (Receiver Operating Characteristic—ROC of 1; Robust Initial Enhancement—RIE of 17.97). Thereby, we obtained valuable results which can be further used in the virtual screening process for the discovery of new active compounds with potential anticancer activity.

scholarly journals In Silico ADME/T Properties of Quinine Derivatives using SwissADME and pkCSM Webservers

2021 ◽  
pp. 1-12
Author(s):  
Jean Gonfi M. Mvondo ◽  
Aristote Matondo ◽  
Dani T. Mawete ◽  
Sylvie-Mireille N. Bambi ◽  
Blaise M. Mbala ◽  
...  
Keyword(s):  
Physicochemical Properties ◽  
In Silico ◽  
Pharmacokinetic Profile ◽  
Drug Formulation ◽  
New Drugs ◽  
Oral Drug ◽  
Free Access ◽  
Lipinski’S Rule ◽  
Development Of Resistance ◽  
Lipinski’S Rule Of Five

Aim: Malaria is among the most devastating and widespread tropical parasitic diseases. To overcome antimalarial drug resistance, new drugs need to be developed. This study is designed to establish the pharmacokinetic profile and toxicity of nine quinine derivatives as potential antimalarial drugs using in silico approaches by SwissADME and pkCSM. Methodology: The structures of investigated compounds were translated into canonical SMILES format and then submitted to SwissADME web tool that gives free access to physicochemical properties, pharmacokinetics, drug-likeness and medicinal chemistry friendliness of compounds, and pkCSM webserver for predicting and optimizing pharmacokinetic and toxicity properties. Results: SwissADME mainly used to predict the physicochemical properties of compounds and their drug-likeness revealed that all quinine derivatives have good bioavailability and satisfied the Lipinski’s rule of five. The pkCSM results on the absorption, distribution, metabolism, excretion and toxicity show  that all investigated compounds have a good pharmacokinetic profile and they are safe since they belong to class 4 of the Globally Harmonized System (300 < Category 4 ≤ 2000 mg/kg/day). Conclusion: Drug-likeness and ADME/T predictions of nine investigated quinine derivatives revealed that they are good candidates to oral drug formulation and thus they can be used in a broader context of overcoming the development of resistance by Plasmodium protozoans against most of the drugs currently used to treat malaria. As future prospects, further studies on bioevaluation of compounds are needed to elucidate their potential pharmacological activities.

scholarly journals In silico Screening of Food Bioactive Compounds to Predict Potential Inhibitors of COVID-19 Main protease (Mpro) and RNA-dependent RNA polymerase (RdRp)

2020 ◽  
Author(s):  
Brahmaiah Pendyala ◽  
Ankit Patras
Keyword(s):  
Rna Polymerase ◽  
Bioactive Compounds ◽  
In Silico ◽  
World Health ◽  
Rna Dependent Rna Polymerase ◽  
In Silico Screening ◽  
Main Protease ◽  
Health Organization

<p>As novel corona virus (COVID-19) infections has spread throughout the world, world health organization (WHO) has announced COVID-19 as a pandemic infection. Henceforth investigators are conducting extensive research to find possible therapeutic agents against COVID-19. Main protease (Mpro) that plays an essential role in processing the polyproteins that are translated from the 2019-nCOV RNA and RNA-dependent RNA polymerase (RdRp) that catalyzes the replication of RNA from RNA template becomes as a potential targets for in silico screening of effective therapeutic compounds to COVID-19. In this study we used COVID-19 Docking Server to predict potential food bioactive compounds to inhibit Mpro and RdRp. The results showed that Phycocyanobilin, Riboflavin, Cyanidin, Daidzein, Genistein are potent inhibitor bioactive compounds to Mpro and RdRp in comparison to antiviral drugs. Though, further in vitro and/or in vivo research is required to validate the docking results. <br></p>

scholarly journals Identification of LASSBio-1945 as an inhibitor of SARS-CoV-2 main protease (MPRO) through in silico screening supported by molecular docking and a fragment-based pharmacophore model

2020 ◽  
Author(s):  
Lucas S. Franco ◽  
Rodolfo C. Maia ◽  
Eliezer J. Barreiro
Keyword(s):  
Molecular Docking ◽  
Virtual Screening ◽  
In Silico ◽  
Pharmacophore Model ◽  
In Silico Screening ◽  
Main Protease ◽  
Screening Strategies

A SARS-CoV-2 main protease (MPRO) inhibitor was discovered employing molecular docking and a fragment-based pharmacophore model as virtual screening strategies.

scholarly journals In silico Screening of Food Bioactive Compounds to Predict Potential Inhibitors of COVID-19 Main protease (Mpro) and RNA-dependent RNA polymerase (RdRp)

2020 ◽  
Author(s):  
Brahmaiah Pendyala ◽  
Ankit Patras
Keyword(s):  
Rna Polymerase ◽  
Bioactive Compounds ◽  
In Silico ◽  
World Health ◽  
Rna Dependent Rna Polymerase ◽  
In Silico Screening ◽  
Main Protease ◽  
Health Organization

<p>As novel corona virus (COVID-19) infections has spread throughout the world, world health organization (WHO) has announced COVID-19 as a pandemic infection. Henceforth investigators are conducting extensive research to find possible therapeutic agents against COVID-19. Main protease (Mpro) that plays an essential role in processing the polyproteins that are translated from the 2019-nCOV RNA and RNA-dependent RNA polymerase (RdRp) that catalyzes the replication of RNA from RNA template becomes as a potential targets for in silico screening of effective therapeutic compounds to COVID-19. In this study we used COVID-19 Docking Server to predict potential food bioactive compounds to inhibit Mpro and RdRp. The results showed that Phycocyanobilin, Riboflavin, Cyanidin, Daidzein, Genistein are potent inhibitor bioactive compounds to Mpro and RdRp in comparison to antiviral drugs. Though, further in vitro and/or in vivo research is required to validate the docking results. <br></p>

scholarly journals In silico Screening of Food Bioactive Compounds to Predict Potential Inhibitors of COVID-19 Main protease (Mpro) and RNA-dependent RNA polymerase (RdRp)

2020 ◽  
Author(s):  
Brahmaiah Pendyala ◽  
Ankit Patras
Keyword(s):  
Rna Polymerase ◽  
Bioactive Compounds ◽  
In Silico ◽  
World Health ◽  
Rna Dependent Rna Polymerase ◽  
In Silico Screening ◽  
Main Protease ◽  
Health Organization

<p>As novel corona virus (COVID-19) infections has spread throughout the world, world health organization (WHO) has announced COVID-19 as a pandemic infection. Henceforth investigators are conducting extensive research to find possible therapeutic agents against COVID-19. Main protease (Mpro) that plays an essential role in processing the polyproteins that are translated from the COVID-19 RNA becomes and RNA-dependent RNA polymerase (RdRp) that catalyzes the replication of RNA from RNA template as a potential targets for in silico screening of effective therapeutic compounds to COVID-19. In this study we used COVID-19 Docking Server to predict potential food bioactive compounds to inhibit Mpro and RdRp. The results showed that Phycocyanobilin, Riboflavin, Cyanidin, Daidzein, Genistein are potent inhibitor bioactive compounds to Mpro and RdRp in comparison to antiviral drugs. Though, further in vitro and/or in vivo research is required to validate the docking results. <br></p>

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