An HMM-based algorithm for evaluating rates of receptor–ligand binding kinetics from thermal fluctuation data
Author(s) -
Lining Arnold Ju,
Yijie Dylan Wang,
Ying Hung,
C. F. Jeff Wu,
Cheng Zhu
Publication year - 2013
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btt180
Subject(s) - hidden markov model , dissociation (chemistry) , chemistry , algorithm , ligand (biochemistry) , computer science , biological system , artificial intelligence , receptor , biology , biochemistry
Abrupt reduction/resumption of thermal fluctuations of a force probe has been used to identify association/dissociation events of protein-ligand bonds. We show that off-rate of molecular dissociation can be estimated by the analysis of the bond lifetime, while the on-rate of molecular association can be estimated by the analysis of the waiting time between two neighboring bond events. However, the analysis relies heavily on subjective judgments and is time-consuming. To automate the process of mapping out bond events from thermal fluctuation data, we develop a hidden Markov model (HMM)-based method.
Accelerating Research
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom
Address
John Eccles HouseRobert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom