SwissADME predictions of pharmacokinetics and drug-likeness properties of small molecules present in Spirulina platensis

Riyadi, Putut Har; Romadhon, Romadhon; Sari, I D; Kurniasih, RA; Agustini, Tri Winarni; Swastawati, Fronthea; Herawati, Vivi Endar; Tanod, Wendy Alexander

doi:10.1088/1755-1315/890/1/012021

Cited by 19 publications

(6 citation statements)

References 42 publications

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“…The SwissADME will provide several parameters: general characteristics, physicochemical properties, lipophilicity, water solubility, pharmacokinetic parameters, drug-likeness rule, bioavailability score, medicinal chemistry, and BOILED-Egg. The BOILED-Egg is schematic or imaging presentation of compounds ability through pass gastrointestinal by passive absorption, penetration to the brain, and bioavailability radar for drug-likeness compounds evaluation [22].…”

Section: Resultsmentioning

confidence: 99%

The Bioavailability Prediction and Screening Phytochemicals of Sansevieria Trifasciata Leaves Extract

Oomariyah

Dijk

2022

MATEC Web Conf.

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Leaves and rhizomes of Sansevieria trifasciata are used to treat some infectious diseases and have anti-diabetes potential. Active compounds and their bioavailability are not known yet. This study aimed to identify phytochemical compounds of Sansevieria trifasciata leaves and their orally bioavailability by absorption, distribution, metabolism, and excretion (ADME) evaluation. Leaves were obtained from the Tropical Biopharmaca Research Center, IPB University. After drying in an oven (38±2°C) for seven days and pulverized, the powder leaves macerated in 5 ml 100% methanol/g. After five days, extracts were filtered and evaporated using the rotary evaporator system. A bioactive test was carried out by mixing extracts with a reagent to screen alkaloids, flavonoids, saponin, steroids, triterpenoids, tannins, and phenolic compounds. Samples were injected into GC-MS using column (HP5), fused silica tubing 30 m long (0.25 mm I.D) filled with acetonitrile. Sansevieria trifasciata bioactive was analyzed using the Swiss-ADME tool to check their bioavailability. The qualitative screening showed the presence of main plant compounds. The GC-MS analysis presented phytol, stigmasterol, linoleic acid, oleic acid, stearic acid, and palmitic acid. The SwissADME showed bioavailability phytochemicals of Sansevieria trifasciata not orally available according to Lipinski’s rules using SwissADME. It indicated that extract of Sansevieria trifasciata has promising potential as an alternative medicine compound.

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Section: Resultsmentioning

confidence: 99%

The Bioavailability Prediction and Screening Phytochemicals of Sansevieria Trifasciata Leaves Extract

Oomariyah

Dijk

2022

MATEC Web Conf.

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“…The more negative the score of skin permeability is the less the permeability. The bioavailability score 0.55 is well correlated with most market drugs ( Riyadi et al, 2021 ). The compounds have lipophilicity score near one which is the recommended score for a drug.…”

Section: Discussionmentioning

confidence: 99%

Characterization of sulfated polysaccharide activity against virulent Plasmodium falciparum PHISTb/RLP1 protein

et al. 2022

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Background: The emergence of artemisinin resistance in South East Asia calls for urgent discovery of new drug compounds that have antiplasmodial activity. Unlike the classical compound screening drug discovery methods, the rational approach involving targeted drug discovery is less cumbersome and therefore key for innovation of new antiplasmodial compounds. Plasmodium falciparum (Pf) utilizes the process of host erythrocyte remodeling using Plasmodium-helical interspersed sub-telomeric domain (PHIST) containing proteins, which are amenable drug targets. The aim of this study is to identify inhibitors of PHIST from sulfated polysaccharides as new antimalarials. Methods: 251 samples from an ongoing study of epidemiology of malaria and drug resistance sensitivity patterns in Kenya were sequenced for PHISTb/RLP1 gene using Sanger sequencing. The sequenced reads were mapped to the reference Pf3D7 protein sequence of PHISTb/RLP1 using CLC Main Workbench. Homology modeling of both reference and mutant protein structures was achieved using the LOMETs tool. The models were refined using ModRefiner for energy minimization. Ramachandran plot was generated by ProCheck to assess the conformation of amino acids in the protein model. Protein binding sites predictions were assessed using FT SITE software. We searched for prospective antimalarials from PubChem. Docking experiments were achieved using AutoDock Vina and analysis results visualized in PyMOL. Results: Sanger sequencing generated 86 complete sequences. Upon mapping of the sequences to the reference, 12 non-synonymous single nucleotide polymorphisms were considered for mutant protein structure analysis. Eleven drug compounds with antiplasmodial activity were identified. Both modeled PHISTb/RLP1 reference and mutant structures had a Ramachandran score of >90% of the amino acids in the favored region. Ten of the drug compounds interacted with amino acid residues in PHISTb and RESA domains, showing potential activity against these proteins. Conclusion: This research identifies inhibitors of exported proteins that can be used in in vitro tests against the Plasmodium parasite.

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“…Following the virtual screening, the retrieved compounds underwent additional refinement by assessing their drug-likeness utilizing the SwissADME web server [31], which offers Lipinski filter, Veber filter, Ghose filter, Egan filter, and so on. These filters helped ensure that the selected compounds met specific criteria associated with drug-likeness [32].…”

Section: Drug Likeness Analysismentioning

confidence: 99%

Deep learning based predictive modeling to screen natural compounds against TNF-alpha for the potential management of Rheumatoid Arthritis: Virtual screening to comprehensive in silico investigation

Nabi,

Riyed,

Ornob

2024

Preprint

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Rheumatoid arthritis (RA) affects an estimated 0.1% to 2.0% of the world's population, leading to a substantial impact on global health. The adverse effects and toxicity associated with conventional RA treatment pathways underscore the critical need to seek potential new therapeutic candidates, particularly those of natural sources that can treat the condition with minimal side effects. To address this challenge, this study employed a deep-learning (DL) based approach to conduct a virtual assessment of natural compounds against the Tumor Necrosis Factor-alpha (TNF-alpha) protein. TNF-alpha stands out as the primary pro-inflammatory cytokine, crucial in the development of RA. Our predictive model demonstrated appreciable performance, achieving MSE of 0.6, MAPE of 10%, and MAE of 0.5. The model was then deployed to screen a comprehensive set of 2563 natural compounds obtained from the Selleckchem database. Utilizing their predicted bioactivity (pIC50), the top 128 compounds were identified. Among them, 68 compounds were taken for further analysis based on drug-likeness analysis. Subsequently, selected compounds underwent additional evaluation using molecular docking (< -8.7 kcal/mol) and ADMET resulting in four compounds posing nominal toxicity, which were finally subjected to MD simulation for 200 ns. Later on, the stability of complexes was assessed via analysis encompassing RMSD, RMSF, Rg, H-Bonds, SASA, and Essential Dynamics. Ultimately, based on the total binding free energy estimated using the MM/GBSA method, Imperialine, Veratramine, and Gelsemine are proven to be potential natural inhibitors of TNF-alpha.

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SwissADME predictions of pharmacokinetics and drug-likeness properties of small molecules present in Spirulina platensis

Cited by 19 publications

References 42 publications

The Bioavailability Prediction and Screening Phytochemicals of Sansevieria Trifasciata Leaves Extract

The Bioavailability Prediction and Screening Phytochemicals of Sansevieria Trifasciata Leaves Extract

Characterization of sulfated polysaccharide activity against virulent Plasmodium falciparum PHISTb/RLP1 protein

Deep learning based predictive modeling to screen natural compounds against TNF-alpha for the potential management of Rheumatoid Arthritis: Virtual screening to comprehensive in silico investigation

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