New insights into toxicity of microcystins produced by cyanobacteria using in silico ADMET prediction

Toxicon ◽  
2021 ◽  
Author(s):  
Cristiane Gonçalves da Silva ◽  
Marcelo Dutra Duque ◽  
Cristina Souza Freire Nordi ◽  
Cristina Viana-Niero
Keyword(s):  
In Silico ◽  
In Silico Admet

2,4-Dichloro-5-[(N-aryl/alkyl)sulfamoyl]benzoic Acid Derivatives: In Vitro Antidiabetic Activity, Molecular Modeling and In silico ADMET Screening

2019 ◽  
Vol 15 (2) ◽  
pp. 186-195 ◽  
Author(s):  
Samridhi Thakral ◽  
Vikramjeet Singh
Keyword(s):  
Molecular Docking ◽  
Benzoic Acid ◽  
Inhibitory Activity ◽  
In Silico ◽  
Computational Study ◽  
Antidiabetic Activity ◽  
Standard Drug ◽  
Benzoic Acid Derivatives ◽  
In Silico Admet ◽  
Inhibitory Potential

Background: Postprandial hyperglycemia can be reduced by inhibiting major carbohydrate hydrolyzing enzymes, such as α-glucosidase and α-amylase which is an effective approach in both preventing and treating diabetes. Objective: The aim of this study was to synthesize a series of 2,4-dichloro-5-[(N-aryl/alkyl)sulfamoyl] benzoic acid derivatives and evaluate α-glucosidase and α-amylase inhibitory activity along with molecular docking and in silico ADMET property analysis. Method: Chlorosulfonation of 2,4-dichloro benzoic acid followed by reaction with corresponding anilines/amines yielded 2,4-dichloro-5-[(N-aryl/alkyl)sulfamoyl]benzoic acid derivatives. For evaluating their antidiabetic potential α-glucosidase and α-amylase inhibitory assays were carried out. In silico molecular docking studies of these compounds were performed with respect to these enzymes and a computational study was also carried out to predict the drug-likeness and ADMET properties of the title compounds. Results: Compound 3c (2,4-dichloro-5-[(2-nitrophenyl)sulfamoyl]benzoic acid) was found to be highly active having 3 fold inhibitory potential against α-amylase and 5 times inhibitory activity against α-glucosidase in comparison to standard drug acarbose. Conclusion: Most of the synthesized compounds were highly potent or equipotent to standard drug acarbose for inhibitory potential against α-glucosidase and α-amylase enzyme and hence this may indicate their antidiabetic activity. The docking study revealed that these compounds interact with active site of enzyme through hydrogen bonding and different pi interactions.

Virtual Screening, Molecular docking and in-silico ADME-Tox analysis for identification of potential main protease (Mpro) enzyme inhibitors

2020 ◽  
Vol 18 ◽  
Author(s):  
Debadash Panigrahi ◽  
Ganesh Prasad Mishra
Keyword(s):  
Molecular Docking ◽  
Virtual Screening ◽  
In Silico ◽  
Data Bank ◽  
Future Research ◽  
Reference Compound ◽  
Unexpected Death ◽  
Main Protease ◽  
In Silico Admet

Objective:: Recent pandemic caused by SARS-CoV-2 described in Wuhan China in December-2019 spread widely almost all the countries of the world. Corona virus (COVID-19) is causing the unexpected death of many peoples and severe economic loss in several countries. Virtual screening based on molecular docking, drug-likeness prediction, and in silico ADMET study has become an effective tool for the identification of small molecules as novel antiviral drugs to treat diseases. Methods:: In the current study, virtual screening was performed through molecular docking for identifying potent inhibitors against Mpro enzyme from the ZINC library for the possible treatment of COVID-19 pandemic. Interestingly, some compounds are identified as possible anti-covid-19 agents for future research. 350 compounds were screened based on their similarity score with reference compound X77 from ZINC data bank and were subjected to docking with crystal structure available of Mpro enzyme. These compounds were then filtered by their in silico ADME-Tox and drug-likeness prediction values. Result:: Out of these 350 screened compounds, 10 compounds were selected based on their docking score and best docked pose in comparison to the reference compound X77. In silico ADME-Tox and drug likeliness predictions of the top compounds were performed and found to be excellent results. All the 10 screened compounds showed significant binding pose with the target enzyme main protease (Mpro) enzyme and satisfactory pharmacokinetic and toxicological properties. Conclusion:: Based on results we can suggest that the identified compounds may be considered for therapeutic development against the COVID-19 virus and can be further evaluated for in vitro activity, preclinical, clinical studies and formulated in a suitable dosage form to maximize their bioavailability.

3D-QSAR, molecular docking and in silico ADMET studies of propiophenone derivatives with anti-HIV-1 protease activity

2021 ◽  
Author(s):  
Milan Jovanović ◽  
Nemanja Turković ◽  
Branka Ivković ◽  
Zorica Vujić ◽  
Katarina Nikolić ◽  
...  
Keyword(s):  
Molecular Docking ◽  
In Silico ◽  
Protease Activity ◽  
3D Qsar ◽  
In Silico Admet ◽  
Anti Hiv ◽  
Hiv 1

Design, synthesis, molecular docking, in silico ADMET profile and anticancer evaluations of sulfonamide endowed with hydrazone-coupled derivatives as VEGFR-2 inhibitors

2021 ◽  
Vol 108 ◽  
pp. 104669
Author(s):  
Asmaa M Sayed ◽  
Fatma A. Taher ◽  
Mohammad R.K. Abdel-Samad ◽  
Mohamed S.A. El-Gaby ◽  
Khaled El‐Adl ◽  
...  
Keyword(s):  
Molecular Docking ◽  
In Silico ◽  
Design Synthesis ◽  
In Silico Admet

Molecular Modeling Studies on 2,4-Disubstituted Imidazopyridines as Anti-Malarials: Atom-Based 3D-QSAR, Molecular Docking, Virtual Screening, In-Silico ADMET and Theoretical Analysis

2021 ◽  
pp. 2150012
Author(s):  
Suraj N. Mali ◽  
Anima Pandey
Keyword(s):  
Molecular Docking ◽  
Molecular Modeling ◽  
Virtual Screening ◽  
In Silico ◽  
Energy Gap ◽  
3D Qsar ◽  
Modeling Studies ◽  
In Vitro Investigation ◽  
In Silico Admet ◽  
Molecular Modeling Studies

Malarial parasites have been reported for moderate-high resistance towards classical antimalarial agents and henceforth development of newer novel chemical entities targeting multiple targets rather than targeting single target will be a highly promising strategy in antimalarial drug discovery. Herein, we carried out molecular modeling studies on 2,4-disubstituted imidazopyridines as anti-hemozoin formation inhibitors by using Schrödinger’s molecular modeling package (2020_4). We have developed statistically robust atom-based 3D-QSAR model (training set, [Formula: see text]; test set, [Formula: see text]; [Formula: see text] [Formula: see text]; root-mean-square error, [Formula: see text]; standard deviation, [Formula: see text]). Our molecular docking, in-silico ADMET analysis showed that dataset molecule 37, has highly promising results. Our ligand-based virtual screening resulted in top five ZINC hits, among them ZINC73737443 hit was observed with lesser energy gap, i.e. 7.85[Formula: see text]eV, higher softness value (0.127[Formula: see text]eV), and comparatively good docking score of [Formula: see text]10.2[Formula: see text]kcal/mol. Our in-silico analysis for a proposed hit, ZINC73737443 showed that this molecule has good ADMET, in-silico nonames toxic as well as noncarcinogenic profile. We believe that further experimental as well as the in-vitro investigation will throw more lights on the identification of ZINC73737443 as a potential antimalarial agent.

scholarly journals In silico chemical profiling and identification of neuromodulators from Curcuma amada targeting Acetylcholinesterase

2020 ◽  
Author(s):  
Md. Chayan Ali ◽  
Yeasmin Akter Munni ◽  
Raju Das ◽  
Marium sultana ◽  
Nasrin Akter ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Molecular Docking ◽  
Molecular Dynamics Simulations ◽  
In Silico ◽  
Network Pharmacology ◽  
Chemical Profiling ◽  
Ache Inhibitors ◽  
Curcuma Amada ◽  
In Silico Admet ◽  
Dynamics Simulations

AbstractCurcuma amada or Mango ginger, a member of the Zingiberaceae family, has been revealed as a beneficiary medicinal plant having diverse pharmacological activities against a wide range of diseases. Due to having neuromodulation properties of this plant, the present study characterized the secondary metabolites of Curcuma amada for their drug-likeness properties, identified potent hits by targeting Acetylcholinesterase (AChE) and revealed neuromodulatory potentiality by network pharmacology approaches. Here in silico ADMET analysis was performed for chemical profiling, and molecular docking and molecular dynamics simulations were used to hit selection and binding characterizations. Accordingly, ADMET prediction showed that around 87.59% of compounds processed drug-likeness activity, where four compounds have been screened out by molecular docking. Guided from induced-fit docking, molecular dynamics simulations revealed phytosterol and curcumin derivatives as the most favorable AChE inhibitors with the highest binding energy, as resulted from MM-PBSA analysis. Furthermore, all of the four hits were appeared to modulate several signaling molecules and intrinsic cellular pathways in network pharmacology analysis, which are associated with neuronal growth survival, inflammation, and immune response, supporting their capacity to revert the condition of neuro-pathobiology. Together, the present in silico based characterization and system pharmacology based findings demonstrate Curcuma amada, as a great source of neuromodulating compounds, which brings about new development for complementary and alternative medicine for the prevention and treatment of neurodegenerative disorders.

Anti-Proliferative Activity of Piper trioicum Leaf Essential Oil Based on Phytoconstituent Analysis, Molecular Docking and In Silico ADMET Approaches

2021 ◽  
Vol 25 ◽  
Author(s):  
Sudipta Jena ◽  
Asit Ray ◽  
Ambika Sahoo ◽  
Prabhat Kumar Das ◽  
Pradeep Kumar Kamila ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Chemical Composition ◽  
Essential Oil ◽  
Essential Oils ◽  
Cell Lines ◽  
In Silico ◽  
Proliferative Activity ◽  
In Silico Admet ◽  
Leaf Essential Oil ◽  
Ht 29

Background: The essential oils isolated from several medicinal plants are reported to have anticancer activities. Both the essential oil and extracts of many Piper species (Piperaceae) possess potential cytotoxic effect against cancer cell lines and are being used in traditional system of medicine for the treatment of cancer. There is a need to evaluate and validate the anticancer properties of essential oils extracted from other wild species of Piper. Objective: The current research was undertaken to determine the chemical composition and investigate the anti-proliferative activity of wild growing Piper trioicum leaf essential oil. The selected five major constituents were subjected to molecular docking to identify possible modes of binding against serine/threonine-protein kinase (MST3) protein Methods: The essential oil of leaf of P. trioicum was extracted by hydro distillation method and its chemical composition was carried out by GC-FID and GC-MS. The anti-proliferative activity of the essential oil was evaluated by MTT assay against normal (3T3-L1) and various cancer (HCT 116, HT-29, PC-3 and HepG2) cell lines. Molecular docking analysis was performed using AutoDock 4.2 software. The pharmacokinetic and pharmacodynamic properties of the major constituents were determined using absorption, distribution, metabolization, excretion and toxicity (ADMET) analysis. Results: The GC-MS analysis revealed the identification of 45 constituents with δ-cadinene (19.57%), germacrene-D (8.54%), β-caryophyllene (6.84%), 1-epi-cubenol (4.83%) and α-pinene (4.52%) were found to be predominant constituents in the leaf essential oil of P. trioicum. The highest cytotoxicity of essential oil was observed against HT-29 cells (IC50 value of 33.14 µg/ml). 1-epi-cubenol and δ-Cadinene exhibited low binding energy values of -6.25 and -5.92 kcal/mol, respectively. For prediction of in silico pharmacokinetic and druglike properties of the major compounds, ADMET prediction tool was also used, the results of which came within the ideal range. Conclusion: The present findings demonstrated that P. trioicum essential oil possesses significant anti-proliferative activity and could be effective against cancer treatment.

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