Literature DB >> 32456484

Advances in the study of drug metabolism - symposium report of the 12th Meeting of the International Society for the Study of Xenobiotics (ISSX).

Laura E Russell1, Mary Alexandra Schleiff2, Eric Gonzalez3,4, Aaron G Bart5, Fabio Broccatelli6, Jessica H Hartman7, W Griffith Humphreys8, Volker M Lauschke9, Iain Martin10, Chukwunonso Nwabufo11, Bhagwat Prasad12, Emily E Scott5,13, Matthew Segall14, Ryan Takahashi15, Mitchell E Taub16, Jasleen K Sodhi17.   

Abstract

The 12th International Society for the Study of Xenobiotics (ISSX) meeting, held in Portland, OR, USA from July 28 to 31, 2019, was attended by diverse members of the pharmaceutical sciences community. The ISSX New Investigators Group provides learning and professional growth opportunities for student and early career members of ISSX. To share meeting content with those who were unable to attend, the ISSX New Investigators herein elected to highlight the "Advances in the Study of Drug Metabolism" symposium, as it engaged attendees with diverse backgrounds. This session covered a wide range of current topics in drug metabolism research including predicting sites and routes of metabolism, metabolite identification, ligand docking, and medicinal and natural products chemistry, and highlighted approaches complemented by computational modeling. In silico tools have been increasingly applied in both academic and industrial settings, alongside traditional and evolving in vitro techniques, to strengthen and streamline pharmaceutical research. Approaches such as quantum mechanics simulations facilitate understanding of reaction energetics toward prediction of routes and sites of drug metabolism. Furthermore, in tandem with crystallographic and orthogonal wet lab techniques for structural validation of drug metabolizing enzymes, in silico models can aid understanding of substrate recognition by particular enzymes, identify metabolic soft spots and predict toxic metabolites for improved molecular design. Of note, integration of chemical synthesis and biosynthesis using natural products remains an important approach for identifying new chemical scaffolds in drug discovery. These subjects, compiled by the symposium organizers, presenters, and the ISSX New Investigators Group, are discussed in this review.

Entities:  

Keywords:  Biosynthetic lead diversification; CYP1A1; X-ray crystallography; cytochrome P450; drug metabolism; matched molecular pairs; molecular docking; predictive tools; site of metabolism

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Substances:

Year:  2020        PMID: 32456484      PMCID: PMC7466845          DOI: 10.1080/03602532.2020.1765793

Source DB:  PubMed          Journal:  Drug Metab Rev        ISSN: 0360-2532            Impact factor:   4.518


  36 in total

Review 1.  Discovering drugs through biological transformation: role of pharmacologically active metabolites in drug discovery.

Authors:  Aberra Fura; Yue-Zhong Shu; Mingshe Zhu; Ronald L Hanson; Vikram Roongta; W Griffith Humphreys
Journal:  J Med Chem       Date:  2004-08-26       Impact factor: 7.446

2.  Enhanced metabolite identification with MS(E) and a semi-automated software for structural elucidation.

Authors:  Britta Bonn; Carina Leandersson; Fabien Fontaine; Ismael Zamora
Journal:  Rapid Commun Mass Spectrom       Date:  2010-11-15       Impact factor: 2.419

Review 3.  In Silico Absorption, Distribution, Metabolism, Excretion, and Pharmacokinetics (ADME-PK): Utility and Best Practices. An Industry Perspective from the International Consortium for Innovation through Quality in Pharmaceutical Development.

Authors:  Franco Lombardo; Prashant V Desai; Rieko Arimoto; Kelly E Desino; Holger Fischer; Christopher E Keefer; Carl Petersson; Susanne Winiwarter; Fabio Broccatelli
Journal:  J Med Chem       Date:  2017-06-27       Impact factor: 7.446

4.  Clinical pharmacokinetics of erlotinib in patients with solid tumors and exposure-safety relationship in patients with non-small cell lung cancer.

Authors:  Jian-Feng Lu; Steve M Eppler; Julie Wolf; Marta Hamilton; Ashok Rakhit; Rene Bruno; Bert L Lum
Journal:  Clin Pharmacol Ther       Date:  2006-08       Impact factor: 6.875

5.  Identification of Ketene-Reactive Intermediate of Erlotinib Possibly Responsible for Inactivation of P450 Enzymes.

Authors:  Huimin Zhao; Siyuan Li; Zixin Yang; Ying Peng; Xiaohui Chen; Jiang Zheng
Journal:  Drug Metab Dispos       Date:  2018-01-19       Impact factor: 3.922

6.  A panel of cytochrome P450 BM3 variants to produce drug metabolites and diversify lead compounds.

Authors:  Andrew M Sawayama; Michael M Y Chen; Palaniappan Kulanthaivel; Ming-Shang Kuo; Horst Hemmerle; Frances H Arnold
Journal:  Chemistry       Date:  2009-11-02       Impact factor: 5.236

Review 7.  Computational prediction of metabolism: sites, products, SAR, P450 enzyme dynamics, and mechanisms.

Authors:  Johannes Kirchmair; Mark J Williamson; Jonathan D Tyzack; Lu Tan; Peter J Bond; Andreas Bender; Robert C Glen
Journal:  J Chem Inf Model       Date:  2012-02-17       Impact factor: 4.956

Review 8.  Selective CH bond functionalization with engineered heme proteins: new tools to generate complexity.

Authors:  Ruijie K Zhang; Xiongyi Huang; Frances H Arnold
Journal:  Curr Opin Chem Biol       Date:  2018-10-18       Impact factor: 8.822

9.  Structures of human cytochrome P450 1A1 with bergamottin and erlotinib reveal active-site modifications for binding of diverse ligands.

Authors:  Aaron G Bart; Emily E Scott
Journal:  J Biol Chem       Date:  2018-09-25       Impact factor: 5.157

Review 10.  Recent applications of deep learning and machine intelligence on in silico drug discovery: methods, tools and databases.

Authors:  Ahmet Sureyya Rifaioglu; Heval Atas; Maria Jesus Martin; Rengul Cetin-Atalay; Volkan Atalay; Tunca Doğan
Journal:  Brief Bioinform       Date:  2019-09-27       Impact factor: 11.622

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  2 in total

Review 1.  Successful and Unsuccessful Prediction of Human Hepatic Clearance for Lead Optimization.

Authors:  Jasleen K Sodhi; Leslie Z Benet
Journal:  J Med Chem       Date:  2021-03-25       Impact factor: 7.446

2.  Significance of Multiple Bioactivation Pathways for Meclofenamate as Revealed through Modeling and Reaction Kinetics.

Authors:  Mary Alexandra Schleiff; Noah R Flynn; Sasin Payakachat; Benjamin Mark Schleiff; Anna O Pinson; Dennis W Province; S Joshua Swamidass; Gunnar Boysen; Grover P Miller
Journal:  Drug Metab Dispos       Date:  2020-11-25       Impact factor: 3.922

  2 in total

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