Literature DB >> 15093284

Application of proteomic technologies in the drug development process.

Jennie L Walgren1, David C Thompson.   

Abstract

Proteins are the principal targets of drug discovery. Most large pharmaceutical companies now have a proteomics-oriented biotech or academic partner or have started their own proteomics division. Common applications of proteomics in the drug industry include target identification and validation, identification of efficacy and toxicity biomarkers from readily accessible biological fluids, and investigations into mechanisms of drug action or toxicity. Target identification and validation involves identifying proteins whose expression levels or activities change in disease states. These proteins may serve as potential therapeutic targets or may be used to classify patients for clinical trials. Proteomics technologies may also help identify protein-protein interactions that influence either the disease state or the proposed therapy. Efficacy biomarkers are used to assess whether target modulation has occurred. They are used for the characterization of disease models and to assess the effects and mechanism of action of lead candidates in animal models. Toxicity (safety) biomarkers are used to screen compounds in pre-clinical studies for target organ toxicities as well as later on in development during clinical trials. Complementary approaches such as metabolomics and genomics can be used in conjunction with proteomics throughout the drug development process to create more of a unified, systems biology approach.

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Year:  2004        PMID: 15093284     DOI: 10.1016/j.toxlet.2003.12.047

Source DB:  PubMed          Journal:  Toxicol Lett        ISSN: 0378-4274            Impact factor:   4.372


  9 in total

Review 1.  Proteomic identification of multitasking proteins in unexpected locations complicates drug targeting.

Authors:  Georgina S Butler; Christopher M Overall
Journal:  Nat Rev Drug Discov       Date:  2009-12       Impact factor: 84.694

2.  Omics-based molecular target and biomarker identification.

Authors:  Zhang-Zhi Hu; Hongzhan Huang; Cathy H Wu; Mira Jung; Anatoly Dritschilo; Anna T Riegel; Anton Wellstein
Journal:  Methods Mol Biol       Date:  2011

3.  Tailoring subtractive cell biopanning to identify diffuse gastric adenocarcinoma-associated antigens via human scFv antibodies.

Authors:  Tayebeh Mehdipour; Mohammad R Tohidkia; Amir Ata Saei; Amir Kazemi; Shirin Khajeh; Ali A Rahim Rahimi; Sepideh Nikfarjam; Mehrdad Farhadi; Monireh Halimi; Ramin Soleimani; Roman A Zubarev; Mohammad Nouri
Journal:  Immunology       Date:  2019-11-08       Impact factor: 7.397

Review 4.  'Unknown' proteins and 'orphan' enzymes: the missing half of the engineering parts list--and how to find it.

Authors:  Andrew D Hanson; Anne Pribat; Jeffrey C Waller; Valérie de Crécy-Lagard
Journal:  Biochem J       Date:  2009-12-14       Impact factor: 3.857

5.  Protein expression profiling in the African clawed frog Xenopus laevis tadpoles exposed to the polychlorinated biphenyl mixture aroclor 1254.

Authors:  Virginie Gillardin; Frédéric Silvestre; Marc Dieu; Edouard Delaive; Martine Raes; Jean-Pierre Thomé; Patrick Kestemont
Journal:  Mol Cell Proteomics       Date:  2008-11-16       Impact factor: 5.911

Review 6.  Drug target inference through pathway analysis of genomics data.

Authors:  Haisu Ma; Hongyu Zhao
Journal:  Adv Drug Deliv Rev       Date:  2013-01-28       Impact factor: 15.470

7.  Quantitative proteomics reveals that Hsp90 inhibition preferentially targets kinases and the DNA damage response.

Authors:  Kirti Sharma; R Martin Vabulas; Boris Macek; Stefan Pinkert; Jürgen Cox; Matthias Mann; F Ulrich Hartl
Journal:  Mol Cell Proteomics       Date:  2011-12-13       Impact factor: 5.911

8.  Proteomic profiling of Serratia marcescens by high-resolution mass spectrometry.

Authors:  Bhavya Somalapura Gangadharappa; Sharath Rajashekarappa; Gajanan Sathe
Journal:  Bioimpacts       Date:  2020-03-26

9.  Applicability of Artificial Vascularized Liver Tissue to Proteomic Analysis.

Authors:  Nobuhito Mori; Yasuyuki S Kida
Journal:  Micromachines (Basel)       Date:  2021-04-11       Impact factor: 2.891

  9 in total

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