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PTS: a pharmaceutical target seeker.

Peng Ding1, Xin Yan1, Zhihong Liu1

  • 1Research Center for Drug Discovery, School of Pharmaceutical Sciences, Sun Yat-Sen University, Guangzhou 510006, China.

Database : the Journal of Biological Databases and Curation
|November 15, 2019
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Summary
This summary is machine-generated.

A new tool, Pharmaceutical Target Seeker (PTS), identifies drug targets by comparing compound structures with known ligands. It utilizes 3D shape and static properties for accurate drug discovery, enhancing target identification efficiency.

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Area of Science:

  • Medicinal Chemistry
  • Computational Drug Discovery
  • Pharmacology

Background:

  • Identifying protein targets is crucial for drug discovery.
  • Molecular similarity is a common method for predicting drug targets, assuming similar compounds interact with the same targets.
  • Existing similarity metrics (topological, steric, static) have limitations in accurately representing a compound's properties.

Purpose of the Study:

  • To introduce the Pharmaceutical Target Seeker (PTS), a novel computational tool for identifying protein targets of bioactive compounds.
  • To leverage 3D steric and static shape comparisons against experimental ligand structures for improved target prediction.
  • To provide a user-friendly platform with a comprehensive database and visualization tools for drug target identification.

Main Methods:

  • Developed the Pharmaceutical Target Seeker (PTS) tool for protein target identification.
  • Employed static and steric shape comparison between query compound structures and experimental ligand structures.
  • Utilized crystal structures of active compounds for similarity calculations and filtered predictions using multi-activity thresholds.
  • Integrated a pharmaceutical target database with approximately 250,000 ligands and 2,300 protein targets.

Main Results:

  • The PTS tool enables efficient searching of protein targets based on detailed molecular shape and property comparisons.
  • Incorporation of experimental crystal structures enhances the reliability of similarity assessments.
  • The system allows for filtering potential targets based on multiple activity thresholds, refining drug discovery efforts.
  • A comprehensive database and visualization tools facilitate user interaction and result examination.

Conclusions:

  • The Pharmaceutical Target Seeker (PTS) offers a robust and reliable method for identifying potential drug targets.
  • Its approach, focusing on 3D steric and static properties using experimental data, overcomes limitations of traditional methods.
  • PTS provides a valuable resource for accelerating the drug discovery pipeline through enhanced target identification and validation.