Literature DB >> 23713773

Network-based strategies can help mono- and poly-pharmacology drug discovery: a systems biology view.

H Billur Engin, Attila Gursoy, Ruth Nussinov, Ozlem Keskin1.   

Abstract

The cellular network and its environment govern cell and organism behavior and are fundamental to the comprehension of function, misfunction and drug discovery. Over the last few years, drugs were observed to often bind to more than one target; thus, polypharmacology approaches can be advantageous, complementing the "one drug--one target" strategy. Targeting drug discovery from the systems biology standpoint can help in studies of network effects of mono- and poly-pharmacology. In this mini-review, we provide an overview of the usefulness of network description and tools for mono- and poly-pharmacology, and the ways through which protein interactions can help single- and multi-target drug discovery efforts. We further describe how, when combined with experimental data, modeled structural networks which can predict which proteins interact and provide the structures of their interfaces, can model the cellular pathways, and suggest which specific pathways are likely to be affected. Such structural networks may facilitate structure-based drug design; forecast side effects of drugs; and suggest how the effects of drug binding can propagate in multi-molecular complexes and pathways.

Mesh:

Substances:

Year:  2014        PMID: 23713773     DOI: 10.2174/13816128113199990066

Source DB:  PubMed          Journal:  Curr Pharm Des        ISSN: 1381-6128            Impact factor:   3.116


  14 in total

Review 1.  Dynamic multiprotein assemblies shape the spatial structure of cell signaling.

Authors:  Ruth Nussinov; Hyunbum Jang
Journal:  Prog Biophys Mol Biol       Date:  2014-07-18       Impact factor: 3.667

2.  Integrating structure to protein-protein interaction networks that drive metastasis to brain and lung in breast cancer.

Authors:  H Billur Engin; Emre Guney; Ozlem Keskin; Baldo Oliva; Attila Gursoy
Journal:  PLoS One       Date:  2013-11-22       Impact factor: 3.240

3.  A Network-Based Data Integration Approach to Support Drug Repurposing and Multi-Target Therapies in Triple Negative Breast Cancer.

Authors:  Francesca Vitali; Laurie D Cohen; Andrea Demartini; Angela Amato; Vincenzo Eterno; Alberto Zambelli; Riccardo Bellazzi
Journal:  PLoS One       Date:  2016-09-15       Impact factor: 3.240

4.  Discovery of a New Class of Cathepsin K Inhibitors in Rhizoma Drynariae as Potential Candidates for the Treatment of Osteoporosis.

Authors:  Zuo-Cheng Qiu; Xiao-Li Dong; Yi Dai; Gao-Keng Xiao; Xin-Luan Wang; Ka-Chun Wong; Man-Sau Wong; Xin-Sheng Yao
Journal:  Int J Mol Sci       Date:  2016-12-16       Impact factor: 5.923

5.  Editorial: Computational and Experimental Approaches in Multi-target Pharmacology.

Authors:  Thomas J Anastasio
Journal:  Front Pharmacol       Date:  2017-06-30       Impact factor: 5.810

6.  Quo vadis computational analysis of PPI data or why the future isn't here yet.

Authors:  Konstantinos A Theofilatos; Spiros Likothanassis; Seferina Mavroudi
Journal:  Front Genet       Date:  2015-09-15       Impact factor: 4.599

Review 7.  Computational approaches in target identification and drug discovery.

Authors:  Theodora Katsila; Georgios A Spyroulias; George P Patrinos; Minos-Timotheos Matsoukas
Journal:  Comput Struct Biotechnol J       Date:  2016-05-07       Impact factor: 7.271

Review 8.  Integration of phytochemicals and phytotherapy into cancer precision medicine.

Authors:  Thomas Efferth; Mohamed E M Saeed; Elhaj Mirghani; Awadh Alim; Zahir Yassin; Elfatih Saeed; Hassan E Khalid; Salah Daak
Journal:  Oncotarget       Date:  2017-07-25

9.  Network-principled deep generative models for designing drug combinations as graph sets.

Authors:  Mostafa Karimi; Arman Hasanzadeh; Yang Shen
Journal:  Bioinformatics       Date:  2020-07-01       Impact factor: 6.937

10.  An integrated strategy for identifying new targets and inferring the mechanism of action: taking rhein as an example.

Authors:  Hao Sun; Yiting Shen; Guangwen Luo; Yuepiao Cai; Zheng Xiang
Journal:  BMC Bioinformatics       Date:  2018-09-06       Impact factor: 3.169

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.