{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,5,9]],"date-time":"2024-05-09T08:10:06Z","timestamp":1715242206389},"reference-count":34,"publisher":"Oxford University Press (OUP)","issue":"12","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2013,6,15]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Motivation: Abrupt reduction\/resumption of thermal fluctuations of a force probe has been used to identify association\/dissociation events of protein\u2013ligand 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.<\/jats:p><jats:p>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\u2013ligand interaction in the early stage of hemostasis and thrombosis: the von Willebrand factor (VWF) binding to platelet glycoprotein Ib\u03b1 (GPIb\u03b1). 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\u2013ligand binding kinetics.<\/jats:p><jats:p>Contact: \u00a0jeffwu@isye.gatech.edu or cheng.zhu@bme.gatech.edu<\/jats:p>","DOI":"10.1093\/bioinformatics\/btt180","type":"journal-article","created":{"date-parts":[[2013,4,19]],"date-time":"2013-04-19T00:55:58Z","timestamp":1366332958000},"page":"1511-1518","source":"Crossref","is-referenced-by-count":1,"title":["An HMM-based algorithm for evaluating rates of receptor\u2013ligand binding kinetics from thermal fluctuation data"],"prefix":"10.1093","volume":"29","author":[{"given":"Lining","family":"Ju","sequence":"first","affiliation":[{"name":"1 Coulter Department of Biomedical Engineering, Georgia Institute of Technology, 2H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, 3Department of Statistics and Biostatistics, Rutgers University, Newark, NJ 07102, USA and 4Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA 30318, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yijie Dylan","family":"Wang","sequence":"additional","affiliation":[{"name":"1 Coulter Department of Biomedical Engineering, Georgia Institute of Technology, 2H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, 3Department of Statistics and Biostatistics, Rutgers University, Newark, NJ 07102, USA and 4Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA 30318, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ying","family":"Hung","sequence":"additional","affiliation":[{"name":"1 Coulter Department of Biomedical Engineering, Georgia Institute of Technology, 2H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, 3Department of Statistics and Biostatistics, Rutgers University, Newark, NJ 07102, USA and 4Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA 30318, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chien-Fu Jeff","family":"Wu","sequence":"additional","affiliation":[{"name":"1 Coulter Department of Biomedical Engineering, Georgia Institute of Technology, 2H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, 3Department of Statistics and Biostatistics, Rutgers University, Newark, NJ 07102, USA and 4Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA 30318, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Cheng","family":"Zhu","sequence":"additional","affiliation":[{"name":"1 Coulter Department of Biomedical Engineering, Georgia Institute of Technology, 2H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, 3Department of Statistics and Biostatistics, Rutgers University, Newark, NJ 07102, USA and 4Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA 30318, USA"},{"name":"1 Coulter Department of Biomedical Engineering, Georgia Institute of Technology, 2H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, 3Department of Statistics and Biostatistics, Rutgers University, Newark, NJ 07102, USA and 4Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA 30318, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2013,4,18]]},"reference":[{"key":"2023012810441832500_btt180-B1","doi-asserted-by":"crossref","first-page":"22831","DOI":"10.1074\/jbc.M110.103358","article-title":"Destabilization of the A1 domain in von Willebrand factor dissociates the A1A2A3 tri-domain and provokes spontaneous binding to glycoprotein Ibalpha and platelet activation under shear stress","volume":"285","author":"Auton","year":"2010","journal-title":"J. Biol. 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