Single-molecule force spectroscopy(SMFS)measurements of the dynamics of biomolecules typically require identifying massive events and states from large data sets,such as extracting rupture forces from force-extension ...Single-molecule force spectroscopy(SMFS)measurements of the dynamics of biomolecules typically require identifying massive events and states from large data sets,such as extracting rupture forces from force-extension curves(FECs)in pulling experiments and identifying states from extension-time trajectories(ETTs)in force-clamp experiments.The former is often accomplished manually and hence is time-consuming and laborious while the latter is always impeded by the presence of baseline drift.In this study,we attempt to accurately and automatically identify the events and states from SMFS experiments with a machine learning approach,which combines clustering and classification for event identification of SMFS(ACCESS).As demonstrated by analysis of a series of data sets,ACCESS can extract the rupture forces from FECs containing multiple unfolding steps and classify the rupture forces into the corresponding conformational transitions.Moreover,ACCESS successfully identifies the unfolded and folded states even though the ETTs display severe nonmonotonic baseline drift.Besides,ACCESS is straightforward in use as it requires only three easy-to-interpret parameters.As such,we anticipate that ACCESS will be a useful,easy-to-implement and high-performance tool for event and state identification across a range of single-molecule experiments.展开更多
Infrared absorption spectra of gaseous CH2Cl2 in the regions of 1200-12000 cm^-1 were measured using a Bruker IFS 120HR Fourier transform spectrometer in conjunction with a nmltipass cell. 47 vibrational levels of ove...Infrared absorption spectra of gaseous CH2Cl2 in the regions of 1200-12000 cm^-1 were measured using a Bruker IFS 120HR Fourier transform spectrometer in conjunction with a nmltipass cell. 47 vibrational levels of overtone and combinational spectral lines of the CH stretching （v1, v6）, bending （v2）, and rocking （v8） modes were analyzed and assigned. Utilizing the normal mode model and considering the coupling among CH stretching, bending and rocking vibrations, values of the harmonic frequency wi, the anharmonic constant xij, and the coefficients of Fermi and the Darling-Dennison resonances of v1, v6, v2 and v8 modes were also determined from experimental spectral data with nonlinear least-square fitting. These spectral constants reproduced the experimental levels very well. These results showed that Fermi resonance between CH stretching and rocking vibrations （kiss=-254.63 cm^-1） is stronger than that between CH stretching and bending vibrations （k122 = 54.87 cm^-1 ）; and that Darling-Dennison resonances between CH stretching and bending vibrations （k166=-215.28 cm^-1） is also much stronger than that between CH bending and rocking vibrations （k2288=5.72 cm^-1）.展开更多
基金the support from the Physical Research Platform in the School of Physics of Sun Yat-sen University(PRPSP,SYSU)Project supported by the National Natural Science Foundation of China(Grant No.12074445)the Open Fund of the State Key Laboratory of Optoelectronic Materials and Technologies of Sun Yat-sen University(Grant No.OEMT-2022-ZTS-05)。
文摘Single-molecule force spectroscopy(SMFS)measurements of the dynamics of biomolecules typically require identifying massive events and states from large data sets,such as extracting rupture forces from force-extension curves(FECs)in pulling experiments and identifying states from extension-time trajectories(ETTs)in force-clamp experiments.The former is often accomplished manually and hence is time-consuming and laborious while the latter is always impeded by the presence of baseline drift.In this study,we attempt to accurately and automatically identify the events and states from SMFS experiments with a machine learning approach,which combines clustering and classification for event identification of SMFS(ACCESS).As demonstrated by analysis of a series of data sets,ACCESS can extract the rupture forces from FECs containing multiple unfolding steps and classify the rupture forces into the corresponding conformational transitions.Moreover,ACCESS successfully identifies the unfolded and folded states even though the ETTs display severe nonmonotonic baseline drift.Besides,ACCESS is straightforward in use as it requires only three easy-to-interpret parameters.As such,we anticipate that ACCESS will be a useful,easy-to-implement and high-performance tool for event and state identification across a range of single-molecule experiments.
基金This work was supported by National Natural Science Foundation of China （Grant No. 10274077, 20103007 and 29703007）. The authors would like to thank Wei Chu, Yong-qiang Xu and Guo-sheng Cheng for their kind help.
文摘Infrared absorption spectra of gaseous CH2Cl2 in the regions of 1200-12000 cm^-1 were measured using a Bruker IFS 120HR Fourier transform spectrometer in conjunction with a nmltipass cell. 47 vibrational levels of overtone and combinational spectral lines of the CH stretching （v1, v6）, bending （v2）, and rocking （v8） modes were analyzed and assigned. Utilizing the normal mode model and considering the coupling among CH stretching, bending and rocking vibrations, values of the harmonic frequency wi, the anharmonic constant xij, and the coefficients of Fermi and the Darling-Dennison resonances of v1, v6, v2 and v8 modes were also determined from experimental spectral data with nonlinear least-square fitting. These spectral constants reproduced the experimental levels very well. These results showed that Fermi resonance between CH stretching and rocking vibrations （kiss=-254.63 cm^-1） is stronger than that between CH stretching and bending vibrations （k122 = 54.87 cm^-1 ）; and that Darling-Dennison resonances between CH stretching and bending vibrations （k166=-215.28 cm^-1） is also much stronger than that between CH bending and rocking vibrations （k2288=5.72 cm^-1）.
