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Accelerating optical reporting for conformation of tyrosine kinase inhibitors in solutions
  • Feng Wang,
  • Vladislav Vasilyev
Feng Wang
Swinburne University of Technology

Corresponding Author:[email protected]

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Vladislav Vasilyev
Australian National University
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Abstract

It has been a challenge in automated analysis of medical and chemical knowledge to extract represent quantitative structure–activity relationship (QSAR) using intelligent computing in drug discovery. One of many domain-specific bottlenecks in drug discovery is robust conformation search in three-dimensional (3D) space for flexible drug candidates. The process involves researchers and machines working together to achieve their own strengths for greater outcome. The present study has been developing a method for conformational sampling conformers in the class of 4-anilinoquinazoline derivatives for epidermal growth factor receptor (EGFR) tyrosine kinases inhibitors (TKIs). We use AG-1478 to demonstrate how the new intelligent computing method helps to quantum mechanically determine 22 target drug conformer clusters and their properties from conformational sampling, based on density functional theory (DFT) method, time-dependent (TD)-DFT in solvents and clustering analysis (CA). The UV-vis spectra of the preferred conformers agree well with earlier experimental measurements in which the conformer dependent UV-Vis spectral shift of AG-1478 can be as large as approximately 15 nm. We are further developing this method to study and design new 4-anilinoquinazoline derivatives of EGFR TKIs.
02 Mar 2021Submitted to International Journal of Quantum Chemistry
02 Mar 2021Submission Checks Completed
02 Mar 2021Assigned to Editor
11 Mar 2021Reviewer(s) Assigned
30 May 2021Review(s) Completed, Editorial Evaluation Pending
02 Jun 2021Editorial Decision: Revise Minor
06 Jun 20211st Revision Received
08 Jun 2021Submission Checks Completed
08 Jun 2021Assigned to Editor
08 Jun 2021Reviewer(s) Assigned
17 Jun 2021Review(s) Completed, Editorial Evaluation Pending
17 Jun 2021Editorial Decision: Accept