Improving the efficacy-safety balance of polypharmacology in multi-target drug discovery

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Pysyväisosoite

http://hdl.handle.net/10138/322247

Lähdeviite

Ravikumar , B & Aittokallio , T 2018 , ' Improving the efficacy-safety balance of polypharmacology in multi-target drug discovery ' , Expert opinion on drug discovery , vol. 13 , no. 2 , pp. 179-192 . https://doi.org/10.1080/17460441.2018.1413089

Julkaisun nimi: Improving the efficacy-safety balance of polypharmacology in multi-target drug discovery
Tekijä: Ravikumar, Balaguru; Aittokallio, Tero
Tekijän organisaatio: Institute for Molecular Medicine Finland
University of Helsinki
Tero Aittokallio / Principal Investigator
Bioinformatics
Computational Systems Medicine
Päiväys: 2018
Kieli: eng
Sivumäärä: 14
Kuuluu julkaisusarjaan: Expert opinion on drug discovery
ISSN: 1746-0441
DOI-tunniste: https://doi.org/10.1080/17460441.2018.1413089
URI: http://hdl.handle.net/10138/322247
Tiivistelmä: Introduction: Polypharmacology has emerged as an essential paradigm for modern drug discovery process. Multiple lines of evidence suggest that agents capable of modulating multiple targets in a selective manner may offer also improved balance between therapeutic efficacy and safety compared to single-targeted agents. Areas covered: Herein, the authors review the recent progress made in experimental and computational strategies for addressing the critical challenges with rational discovery of selective multi-targeted agents within the context of polypharmacological modelling. Specific focus is placed on multi-targeted mono-therapies, although examples of combinatorial polytherapies are also covered as an important part of the polypharmacology paradigm. The authors focus mainly on anti-cancer treatment applications, where polypharmacology is playing a key role in determining the efficacy-toxicity trade-off of multi-targeting strategies. Expert opinion: Even though it is widely appreciated that complex polypharmacological interactions can contribute both to therapeutic and adverse side-effects, systematic approaches for improving this balance by means of integrated experimental-computational strategies are still lacking. Future developments will be needed for comprehensive collection and harmonization of systems-wide target selectivity data, enabling better utilization and control for multi-targeted activities in the drug development process. Additional areas of future developments include model-based strategies for drug combination screening and improved pre-clinical validation options with animal models.
Avainsanat: 317 Pharmacy
3111 Biomedicine
Polypharmacology
efficacy-toxicity ratio
drug repositioning
multi-target drug design
profiling strategies
screening libraries
drug combination therapies
computational models
data resources
web-tools
TARGET INTERACTION NETWORKS
PROTEIN INVERSE DOCKING
LIGAND-BINDING-SITES
SIDE-EFFECT TARGETS
DE-NOVO DESIGN
WEB SERVER
COMPUTATIONAL METHODS
KINASE INHIBITOR
SMALL-MOLECULE
CANCER-CELLS
Vertaisarvioitu: Kyllä
Tekijänoikeustiedot: unspecified
Pääsyrajoitteet: openAccess
Rinnakkaistallennettu versio: acceptedVersion


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