Newer QSAR Techniques

Roy, Kunal; Kar, Supratik; Das, Rudra Narayan

doi:10.1016/b978-0-12-801505-6.00009-0

Cited by 35 publications

(53 citation statements)

References 56 publications

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“…A complex 1, B complex 2, C complex 3, D complex 4, and E complex 5 acids with side chains (except glycine, which has no side chains) [43]. Molecular docking is used to investigate the small molecule behavior inside the binding pocket of protein and to predict the affinity that might be occurred during binding [44]. From our docking simulation, we suggested that three ligands, i.e., diposphoryl lipid A, FC-core lipid A, and Kdo2 lipid A, can be activators of the factor C protein by binding to the region of the receptor to form a ligandreceptor complex.…”

Section: Discussionmentioning

confidence: 99%

Characterization, protein modeling, and molecular docking of factor C from Indonesian horseshoe crab (Tachypleus gigas)

Mustopa

Izaki

Suharsono

et al. 2023

Journal of Genetic Engineering and Biotechnology

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Background Horseshoe crab (Tachypleus gigas) amebocytes are useful biomedical components for endotoxin detection, and their growing needs for biomedical purposes cause the horseshoe crab population to decline. Factor C synthesis via genetic engineering offers a solution to replace natural horseshoe crab’s factor C and prevent its excessive harvest from nature. In response to these concerns, this study aimed to characterize the amebocyte lysates and factor C protein modeling of T. gigas originated from Banyuasin South Sumatra Estuary. Methods and results Sampling of T. gigas was carried out in Banyuasin South Sumatra Estuary, Indonesia. The endotoxin test or TAL (Tachypleus amebocyte lysates) assay was performed using gel coagulation method. Protein characterization of protease enzyme was conducted by protease activity, SDS-PAGE, and zymogram analysis. The cDNA of mitochondrial COI gene was amplified for molecular identification followed by cDNA cloning of factor C. Protein modeling was investigated by molecular docking and molecular dynamic (MD) simulation. Endotoxin test results showed that TAL-35 had endotoxin sensitivity in a range of 0.0156–1 EU/ml, while TAL 36 had a sensitivity between 00,625 and 1 EU/ml. T. gigas amebocytes have protease activity in molecular mass sizes less than 60 kDa, with 367 U/ml for TAL 35 and 430 U/ml for TAL 36. The molecular identification revealed 98.68% identity similarity to T. gigas. The docking results suggested three ligands; i.e., diphosphoryl lipid A, core lipid A, and Kdo2 lipid A can be activators of the factor C protein by binding to the region of the receptor to form a ligand-receptor complex. Conclusions Endotoxins can be detected using horseshoe crab amebocytes. The presence of proteases is considered responsible for this ability, as evidenced by casein zymogram results. According to docking and MD analysis, we found that lipopolysaccharides (LPS) participate to the binding site of factor C.

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Section: Discussionmentioning

confidence: 99%

Characterization, protein modeling, and molecular docking of factor C from Indonesian horseshoe crab (Tachypleus gigas)

Mustopa

Izaki

Suharsono

et al. 2023

Journal of Genetic Engineering and Biotechnology

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“…In the field of in silico toxicology, quantitative structure-toxicity relationship (QSTR) is originally a statistical method for developing models to quantitatively correlate the change in the toxicity of chemicals with changes in their structural features or physicochemical properties. 251 In the early stages of QSTR, only a group of structurally similar chemicals was considered suitable for implementing this method to predict toxicity. This is mainly because traditional QSTR was analyzed assuming that similar structures exhibit the same binding modes with specific biological targets.…”

Section: In Silico Modeling Used In Toxicity Assessmentmentioning

confidence: 99%

Toxicological data bank bridges the gap between environmental risk assessment and green organic chemical design in One Health world

et al. 2023

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“…The DoA for a model’s classifications is the set of chemicals for which those classifications are likely to work well. DoA is important for the creation, validation and application of QSARs ( Roy, 2017 ). In development, DoA informs modelers on the kinds of data that should be used and the set of chemicals.…”

Section: Algorithms To Predict Toxicological Properties Of Substancmentioning

confidence: 99%

“…Nate Silver, author and founder of the blog FiveThirtyEight, wrote “ When human judgment and big data intersect there are some funny things that happen ”. Nevertheless, toxicological modeling already impacts drug development ( Cronin, 2000 ; Patlewicz, 2006 ), chemical synthesis ( Santana et al, 2006 ), hazard estimation ( Gerner et al, 2004 ; Fjodorova et al, 2008 ), and many more real-world applications ( Puzyn et al, 2010 ; Roy, 2017 ).…”

Section: Introductionmentioning

confidence: 99%

Computational approaches to chemical hazard assessment

Luechtefeld¹

2017

ALTEX

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Summary Computational prediction of toxicity has reached new heights as a result of decades of growth in the magnitude and diversity of biological data. Public packages for statistics and machine learning make model creation faster. New theory in machine learning and cheminformatics enables integration of chemical structure, toxicogenomics, simulated and physical data in the prediction of chemical health hazards, and other toxicological information. Our earlier publications have characterized a toxicological dataset of unprecedented scale resulting from the European REACH legislation (Registration Evaluation Authorisation and Restriction of Chemicals). These publications dove into potential use cases for regulatory data and some models for exploiting this data. This article analyzes the options for the identification and categorization of chemicals, moves on to the derivation of descriptive features for chemicals, discusses different kinds of targets modeled in computational toxicology, and ends with a high-level perspective of the algorithms used to create computational toxicology models.

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Newer QSAR Techniques

Cited by 35 publications

References 56 publications

Characterization, protein modeling, and molecular docking of factor C from Indonesian horseshoe crab (Tachypleus gigas)

Characterization, protein modeling, and molecular docking of factor C from Indonesian horseshoe crab (Tachypleus gigas)

Toxicological data bank bridges the gap between environmental risk assessment and green organic chemical design in One Health world

Computational approaches to chemical hazard assessment

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