Drug discovery in the age of systems biology: the rise of computational approaches for data integration

2012 ◽  
Vol 23 (4) ◽  
pp. 609-616 ◽  
Author(s):  
Murat Iskar ◽  
Georg Zeller ◽  
Xing-Ming Zhao ◽  
Vera van Noort ◽  
Peer Bork
Keyword(s):  
Systems Biology ◽  
Drug Discovery ◽  
Data Integration ◽  
Computational Approaches

scholarly journals An integrated dataset for in silico drug discovery

2010 ◽  
Vol 7 (3) ◽  
Author(s):  
Simon J Cockell ◽  
Jochen Weile ◽  
Phillip Lord ◽  
Claire Wipat ◽  
Dmytro Andriychenko ◽  
...  
Keyword(s):  
Systems Biology ◽  
Drug Discovery ◽  
Drug Development ◽  
Data Integration ◽  
In Silico ◽  
Drug Repositioning ◽  
Integrated Systems ◽  
Integration Platform ◽  
Treatment Indications ◽  
New Treatment

SummaryDrug development is expensive and prone to failure. It is potentially much less risky and expensive to reuse a drug developed for one condition for treating a second disease, than it is to develop an entirely new compound. Systematic approaches to drug repositioning are needed to increase throughput and find candidates more reliably. Here we address this need with an integrated systems biology dataset, developed using the Ondex data integration platform, for the in silico discovery of new drug repositioning candidates. We demonstrate that the information in this dataset allows known repositioning examples to be discovered. We also propose a means of automating the search for new treatment indications of existing compounds.

Experimental and Computational Approaches to Improve Binding Affinity in Chemical Biology and Drug Discovery

2020 ◽  
Vol 20 (19) ◽  
pp. 1651-1660
Author(s):  
Anuraj Nayarisseri
Keyword(s):  
Drug Discovery ◽  
Drug Design ◽  
Binding Affinity ◽  
Chemical Biology ◽  
De Novo ◽  
Structure Based Drug Design ◽  
Computational Approaches ◽  
Drug Designing ◽  
Traditional Drug ◽  
Computer Based

Drug discovery is one of the most complicated processes and establishment of a single drug may require multidisciplinary attempts to design efficient and commercially viable drugs. The main purpose of drug design is to identify a chemical compound or inhibitor that can bind to an active site of a specific cavity on a target protein. The traditional drug design methods involved various experimental based approaches including random screening of chemicals found in nature or can be synthesized directly in chemical laboratories. Except for the long cycle design and time, high cost is also the major issue of concern. Modernized computer-based algorithm including structure-based drug design has accelerated the drug design and discovery process adequately. Surprisingly from the past decade remarkable progress has been made concerned with all area of drug design and discovery. CADD (Computer Aided Drug Designing) based tools shorten the conventional cycle size and also generate chemically more stable and worthy compounds and hence reduce the drug discovery cost. This special edition of editorial comprises the combination of seven research and review articles set emphasis especially on the computational approaches along with the experimental approaches using a chemical synthesizing for the binding affinity in chemical biology and discovery as a salient used in de-novo drug designing. This set of articles exfoliates the role that systems biology and the evaluation of ligand affinity in drug design and discovery for the future.

scholarly journals A data integration methodology for systems biology

2005 ◽  
Vol 102 (48) ◽  
pp. 17296-17301 ◽  
Author(s):  
D. Hwang ◽  
A. G. Rust ◽  
S. Ramsey ◽  
J. J. Smith ◽  
D. M. Leslie ◽  
...  
Keyword(s):  
Systems Biology ◽  
Data Integration

Systems Biology in Drug Discovery

2010 ◽  
pp. 399-414 ◽  
Author(s):  
Greg Tucker-Kellogg ◽  
Amit Aggarwal ◽  
Kerry Blanchard ◽  
Richard Gaynor
Keyword(s):  
Systems Biology ◽  
Drug Discovery

scholarly journals Advancing Drug Discovery and Development from Active Constituents of Yinchenhao Tang, a Famous Traditional Chinese Medicine Formula

2013 ◽  
Vol 2013 ◽  
pp. 1-6 ◽  
Author(s):  
Aihua Zhang ◽  
Hui Sun ◽  
Shi Qiu ◽  
Xijun Wang
Keyword(s):  
Systems Biology ◽  
Drug Discovery ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Molecular Mechanisms ◽  
Synergistic Effects ◽  
Molecular Networks ◽  
Agile Development ◽  
Therapeutic Effects ◽  
Systematic Analysis

Traditional Chinese medicine (TCM) formula has been playing a very important role in health protection and disease control for thousands of years. Guided by TCM syndrome theories, formula are designed to contain a combination of various kinds of crude drugs that, when combined, will achieve synergistic efficacy. However, the precise mechanism of synergistic action remains poorly understood. One example is a famous TCM formula Yinchenhao Tang (YCHT), whose efficacy in treating hepatic injury (HI) and Jaundice syndrome, has recently been well established as a case study. We also conducted a systematic analysis of synergistic effects of the principal compound using biochemistry, pharmacokinetics and systems biology, to explore the key molecular mechanisms. We had found that the three component (6,7-dimethylesculetin (D), geniposide (G), and rhein (R)) combination exerts a more robust synergistic effect than any one or two of the three individual compounds by hitting multiple targets. They can regulate molecular networks through activating both intrinsic and extrinsic pathways to synergistically cause intensified therapeutic effects. This paper provides an overview of the recent and potential developments of chemical fingerprinting coupled with systems biology advancing drug discovery towards more agile development of targeted combination therapies for the YCHT.

Sign in / Sign up

Export Citation Format

Share Document