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2013 ; 29
(12
): 1511-8
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An HMM-based algorithm for evaluating rates of receptor-ligand binding kinetics
from thermal fluctuation data
#MMPMID23599504
Ju L
; Wang YD
; Hung Y
; Wu CF
; Zhu C
Bioinformatics
2013[Jun]; 29
(12
): 1511-8
PMID23599504
show ga
MOTIVATION: 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. RESULTS:
The HMM method represents the bond state by a hidden variable with two values:
bound and unbound. The bond association/dissociation is visualized and
pinpointed. We apply the method to analyze a key receptor-ligand interaction in
the early stage of hemostasis and thrombosis: the von Willebrand factor (VWF)
binding to platelet glycoprotein Ib? (GPIb?). The numbers of bond lifetime and
waiting time events estimated by the HMM are much more than those estimated by a
descriptive statistical method from the same set of raw data. The kinetic
parameters estimated by the HMM are in excellent agreement with those by a
descriptive statistical analysis, but have much smaller errors for both wild-type
and two mutant VWF-A1 domains. Thus, the computerized analysis allows us to speed
up the analysis and improve the quality of estimates of receptor-ligand binding
kinetics.