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Tool Specialty Company rdkit implementation
Rdkit Implementation, supplied by Tool Specialty Company, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/rdkit/implementation+rdkit/pm42047671-520-17-5
Average 86 stars, based on 1 article reviews
rdkit implementation - by Bioz Stars, 2026-09
86/100 stars

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Article Title: Development of homology model, docking protocol and Machine-Learning based scoring functions for identification of Equus caballus 's butyrylcholinesterase inhibitors.
Article Snippet: Machine learning (ML), an emerging field in drug design, has the potential to predict in silico toxicity, shape-based analysis of inhibitors, scoring function (SF) etc.. In the present study, a homology model, docking protocol, and a dedicated SF have been developed to identify the inhibitors of horse butyrylcholinesterase (BChE) enzyme.. Horse BChE enzyme has homology with human BChE and is a substitute for the screening of in vitro inhibitors.

Article Title: Relationships between the Photodegradation Reaction Rate and Structural Properties of Polymer Systems.
Article Snippet: The development of reusable polymeric materials inspires an attempt to combine renewable biomass with upcycling to form a biorenewable closed system.. It has been reported that 2,5-furandicarboxylic acid (FDCA) can be recovered for recycling when incorporated as monomers into photodegradable polymeric systems.. Here, we develop a procedure to better understand the photodegradation reactions combining density functional theory (DFT) based time-dependent excited-state molecular dynamics (TDESMD) studies with machine learning-based quantitative structure−activity relationships (QSAR) methodology.

Article Title: ModiFinder: Tandem Mass Spectral Alignment Enables Structural Modification Site Localization.
Article Snippet: 2020, 34 (10), No. e8725. (37) Landrum, G.; Tosco, P.. Rdkit/Rdkit. https://github.com/ rdkit/rdkit. (38) Stincone, P.; Pakkir Shah, A. K.; Schmid, R.; Graves, L. G.; Lambidis, S. P.; Torres, R. R.; Xia, S.-N.; Minda, V.; Aron, A. T.; https://doi.org/10.1021/jasms.4c00061 J.

Article Title: Imidazolone as an Amide Bioisostere in the Development of β-1,3- N -Acetylglucosaminyltransferase 2 (B3GNT2) Inhibitors.
Article Snippet: B3GNT2 is responsible for elongation of cell surface longchain polylactosamine, which influences the regulation of the immune response, making it an attractive target for immunomodulation.. In the development of amide containing B3GNT2 inhibitors guided by structure-based drug design, imidazolones were found to successfully serve as amide bioisosteres.. This novel imidazolone isosteric strategy alleviated torsional strain of the amide bond on binding to B3GNT2 and improved potency, isoform selectivity, as well as certain physicochemical and pharmacokinetic properties.

Biomarker Discovery:

Article Title: DASH: Dynamic Attention-Based Substructure Hierarchy for Partial Charge Assignment.
Article Snippet: .. Zenodo 2023, 7671152, 1. (43) Tosco, P.; Stiefl, N.; Landrum, G. Bringing the MMFF Force Field to the RDKit: Implementation and Validation. ..

Article Title: Boosting Graph Neural Networks with Molecular Mechanics: A Case Study of Sigma Profile Prediction.
Article Snippet: Sigma profiles are quantum-chemistry-derived molecular descriptors that encode the polarity of molecules.. They have shown great performance when used as a feature in machine learning applications.. To accelerate the development of these models and the construction of large sigma profile databases, this work proposes a graph convolutional network (GCN) architecture to predict sigma profiles from molecule structures.

Article Title: 3DReact: Geometric Deep Learning for Chemical Reactions.
Article Snippet: .. Model. 2015, 55, 2562−2574. (139) Tosco, P.; Stiefl, N.; Landrum, G. Bringing the MMFF force field to the RDKit: implementation and validation. ..

Article Title: Machine Learning for Bridging the Gap between Density Functional Theory and Coupled Cluster Energies.
Article Snippet: Accurate electronic energies and properties are crucial for successful reaction design and mechanistic investigations.. Computing energies and properties of molecular structures has proven extremely useful, and, with increasing computational power, the limits of high-level approaches (such as coupled cluster theory) are expanding to ever larger systems.. However, because scaling is highly unfavorable, these methods are still not universally applicable to larger systems.



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