Preparation of Translated, Scaled, and Rotated ATS Drugs 3D Molecular Structure for the Validation of 3D Moment Invariants-based Molecular Descriptors

EasyChair Preprint 36

Abstract

The campaign against drug abuse is fought by all countries, most notably on ATS drugs. The technical limitations of the current test kits to detect new brand of ATS drugs present a challenge to law enforcement authorities and forensic laboratories. Meanwhile, new molecular microscopy imaging devices which allowed mankind to characterize the physical 3D molecular structure have been recently introduced, and it can be used to remedy the limitations of existing drug test kits. Thus, a new type of 3D molecular structure representation technique should be developed to cater the 3D molecular structure acquired physically using these molecular imaging devices. One of the applications of image processing methods to represent a 3D image is 3D moments and moment invariants. However, since there are currently no repository or database available which provide the drugs imaging results obtained using these recent imaging devices, this paper proposes to construct the simulated 3D drugs molecular structure to be used by these 3D moments and moment invariants techniques. The drugs molecular structures are obtained from pihkal.info for the ATS drugs, while non-ATS drugs are obtained randomly from ChemSpider database.

Keyphrases: ATS drugs, Computational Intelligence, Dataset preparation, Molecular descriptor, Preprocessing, Voxel grid, atomic force microscopy, ats drug identification, binary voxel grid, drugs identification and analysis, molecular similarity, molecular structure, molecular structure representation, moment invariant

@booklet{EasyChair:36,
  author    = {Satrya Fajri Pratama and Azah Kamilah Muda and Yun-Huoy Choo and Ramon Carbó-Dorca and Ajith Abraham},
  title     = {Preparation of Translated, Scaled, and Rotated ATS Drugs 3D Molecular Structure for the Validation of 3D Moment Invariants-based Molecular Descriptors},
  doi       = {10.29007/lm11},
  howpublished = {EasyChair Preprint 36},
  year      = {EasyChair, 2018}}