Development and integration of computational tools to decipher the structure & dynamics of biomolecules from low-resolution experimental data

概要

学位報告４

別紙４
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論 文 題 目 Development and integration of computational tools to decipher
the structure & dynamics of biomolecules from low-resolution experimental
data
（低解像度の実験データから生体分子の構造とダイナミクスを明らかにする計算
手法の開発と統合）

氏

名

阿斯

罕（ASI Han）

論 文 内 容 の 要 旨
Biomolecules, such as nucleic acids and proteins, are essential in all life processes
as they perform many vital cellular functions. The structural and dynamic
characterization of biomolecules is crucial in the endeavor to understand the
functional mechanisms of biomolecules. Computational structural biology has
advanced our understanding of the structure and dynamics of biomolecules by
leveraging data from many low-resolution experimental methods.
In this thesis, we explored a novel hybrid method to predict the conformational
state of biomolecules from 2D low-resolution X-ray Free-Electron Laser (XFEL)
diffraction data. In addition, we integrated multiple computational tools to
construct structural models of the green alga Chlamydomonas reinhardtii
(CraCRY) protein and characterize the intrinsically disordered region from 1D
low-resolution Small Angle X-ray Scattering (SAXS) experimental data.
XFEL is the latest generation of X-ray source which could enable the observation
of single molecules free of radiation damage. We proposed an algorithm for

学位関係

characterizing biomolecular conformational transitions by using a single 2D
low-resolution XFEL diffraction pattern with another known conformation. We
explored the strategy to obtain plausible 3D structural models by optimizing an
initial structural model to maximize the similarity between the target XFEL
diffraction pattern and simulated diffraction pattern from candidate models using
MC sampling. We tested the proposed algorithm on two biomolecules represented
by a set of Gaussian kernels using synthetic XFEL data. The results show that,
with the proposed algorithm, conformational transitions could be described from
2D XFEL data. In addition, we showed that the incident beam orientation has
some effect on the accuracy of the 3D structure modeling and discussed the
reasons for the inaccuracies for certain orientations.
Structural information on the CraCRY protein is key to elucidate its functional
mechanism. However, the C-terminal extension of CraCRY remains unknown and
is difficult to study due to its intrinsic disorder. Currently, the experimental data
available on full-length CraCRY is from Small Angle X-ray Scattering (SAXS)
experiments, which provide low-resolution information under near-native
conditions in solution. We combined protein structure prediction via AlphaFold2
and MD simulations to propose a complete 3D model of CraCRY in agreement with
experimental SAXS data.
Through the development of a novel hybrid method and the integration of multiple
computational tools, we have demonstrated that structural and dynamic
information on biomolecules can be obtained from low-resolution experimental
data.