Literature DB >> 35781578

Exploring the fuzzy border between senolytics and senomorphics with chemoinformatics and systems pharmacology.

Kevin Samael Olascoaga-Del Angel1,2, Humberto Gutierrez3, Mina Königsberg2, Jaime Pérez-Villanueva4, Norma Edith López-Diazguerrero5.   

Abstract

Senescent cells accumulate within tissues during aging and secrete an array of pro-inflammatory molecules known as senescent-associated secretory phenotype (SASP), which contribute to the appearance and progression of various chronic degenerative diseases. Novel pharmacological approaches aimed at modulating or eliminating senescent cells´ harmful effects have recently emerged: Senolytics are molecules that selectively eliminate senescent cells, while senomorphics modulate or decrease the inflammatory response to specific SASP. So far, the physicochemical, structural, and pharmacological properties that define these two kinds of pharmacological approaches remain unclear. Therefore, the identification and correct choice of molecules, based on their physicochemical, structural, and pharmacological properties, likely to exhibit the desired senotherapeutic activity is crucial for developing effective, selective, and safe senotherapies. Here we compared the physicochemical, structural, and pharmacological properties of 84 senolytics and 79 senomorphics using a chemoinformatic and systems pharmacology approach. We found great physicochemical, structural, and pharmacological similarities between them, also reflected in their cellular responses measured through transcriptome perturbations. The identified similarities between senolytics and senomorphics might explain the dual activity of some of those molecules. These findings will help design and discover new, more effective, and highly selective senotherapeutic agents.
© 2022. The Author(s), under exclusive licence to Springer Nature B.V.

Entities:  

Keywords:  SASP; SCAPs; Senescence; Senolytics; Senomorphics; Senotherapy

Mesh:

Substances:

Year:  2022        PMID: 35781578     DOI: 10.1007/s10522-022-09974-x

Source DB:  PubMed          Journal:  Biogerontology        ISSN: 1389-5729            Impact factor:   4.284


  41 in total

1.  Quantifying the chemical beauty of drugs.

Authors:  G Richard Bickerton; Gaia V Paolini; Jérémy Besnard; Sorel Muresan; Andrew L Hopkins
Journal:  Nat Chem       Date:  2012-01-24       Impact factor: 24.427

2.  The properties of known drugs. 1. Molecular frameworks.

Authors:  G W Bemis; M A Murcko
Journal:  J Med Chem       Date:  1996-07-19       Impact factor: 7.446

3.  Azelaic acid reduced senescence-like phenotype in photo-irradiated human dermal fibroblasts: possible implication of PPARγ.

Authors:  Stefania Briganti; Enrica Flori; Arianna Mastrofrancesco; Daniela Kovacs; Emanuela Camera; Matteo Ludovici; Giorgia Cardinali; Mauro Picardo
Journal:  Exp Dermatol       Date:  2013-01       Impact factor: 3.960

4.  Clearance of p16Ink4a-positive senescent cells delays ageing-associated disorders.

Authors:  Darren J Baker; Tobias Wijshake; Tamar Tchkonia; Nathan K LeBrasseur; Bennett G Childs; Bart van de Sluis; James L Kirkland; Jan M van Deursen
Journal:  Nature       Date:  2011-11-02       Impact factor: 49.962

Review 5.  Cellular senescence in aging and age-related disease: from mechanisms to therapy.

Authors:  Bennett G Childs; Matej Durik; Darren J Baker; Jan M van Deursen
Journal:  Nat Med       Date:  2015-12       Impact factor: 53.440

Review 6.  The senescence-associated secretory phenotype: the dark side of tumor suppression.

Authors:  Jean-Philippe Coppé; Pierre-Yves Desprez; Ana Krtolica; Judith Campisi
Journal:  Annu Rev Pathol       Date:  2010       Impact factor: 23.472

7.  Why is Tanimoto index an appropriate choice for fingerprint-based similarity calculations?

Authors:  Dávid Bajusz; Anita Rácz; Károly Héberger
Journal:  J Cheminform       Date:  2015-05-20       Impact factor: 5.514

8.  Elimination of senescent cells by β-galactosidase-targeted prodrug attenuates inflammation and restores physical function in aged mice.

Authors:  Yusheng Cai; Huanhuan Zhou; Yinhua Zhu; Qi Sun; Yin Ji; Anqi Xue; Yuting Wang; Wenhan Chen; Xiaojie Yu; Longteng Wang; Han Chen; Cheng Li; Tuoping Luo; Hongkui Deng
Journal:  Cell Res       Date:  2020-04-27       Impact factor: 25.617

9.  A proteomic atlas of senescence-associated secretomes for aging biomarker development.

Authors:  Nathan Basisty; Abhijit Kale; Ok Hee Jeon; Chisaka Kuehnemann; Therese Payne; Chirag Rao; Anja Holtz; Samah Shah; Vagisha Sharma; Luigi Ferrucci; Judith Campisi; Birgit Schilling
Journal:  PLoS Biol       Date:  2020-01-16       Impact factor: 8.029

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.