TY - JOUR
T1 - Network-based strategies can help mono- and poly-pharmacology drug discovery
T2 - A systems biology view
AU - Engin, H. Billur
AU - Gursoy, Attila
AU - Nussinov, Ruth
AU - Keskin, Ozlem
PY - 2014
Y1 - 2014
N2 - 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.
AB - 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.
KW - Modeling
KW - Network pharmacology
KW - Poly-pharmacology
KW - Protein-protein interaction inhibitors
KW - Protein-protein interfaces
KW - Systems biology
UR - http://www.scopus.com/inward/record.url?scp=84903728795&partnerID=8YFLogxK
U2 - 10.2174/13816128113199990066
DO - 10.2174/13816128113199990066
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AN - SCOPUS:84903728795
SN - 1381-6128
VL - 20
SP - 1201
EP - 1207
JO - Current Pharmaceutical Design
JF - Current Pharmaceutical Design
IS - 8
ER -