Electron crystallography has been proven to be effective for structure determination of nano- and micron-sized crystals. In the past few years, 3D electron diffraction (3DED) techniques were used for the structure solution of various types of complex structures such as zeolites, metal-organic frameworks (MOF) and pharmaceutical compounds. However, unlike X-ray crystallography, electron diffraction has not yet become an independent technique for a complete structure determination due to relatively poorer diffraction intensities and often powder X-ray diffraction data are used for structure validation and refinement. Electron beam damage to the structures that are sensitive to high energy electrons and dynamical scattering are important factors to lead to the deviation of electron diffraction intensities from the squared amplitudes of the structure factors. In this thesis, we investigate various aspects around the 3D electron diffraction data quality and strategies for obtaining better data and structure models. We combined 3D electron diffraction methods and powder X-ray diffraction to determine the structure of an open-framework material and discussed the difficulties and limitations of electron diffraction for beam sensitive materials. Next, we illustrated the structure determination of a pharmaceutical compound, bismuth subgallate, using 3D electron diffraction. While severe beam damage and diffuse scattering were observed in the dataset collected with the conventional rotation electron diffraction (RED) method, the continuous rotation electron diffraction (cRED) method coupled with sample cooling significantly improved the data quality and made the structure solution possible. In order to better understand the potentials and limitations of the continuous rotation method, we collected multiple datasets from different crystals of a known structure and studied the data quality by evaluating the accuracy of the refined structure models. To tackle dynamical scattering in electron diffraction data, we explored a routine for structure refinement with dynamical intensity calculation using RED data from a known structure and discussed its potentials and limitations. / <p>At the time of the doctoral defense, the following papers were unpublished and had a status as follows: Paper 3: Manuscript. Paper 4: Manuscript.</p>

In this project a number of peptidyl transferase antibiotics were studied, specifically a group of aminohexose cytosine nucleoside antibiotics and their interaction with a selected number of highly conserved ribonucleic acid (RNA) motifs, designed to represent their possible binding site within the ribosome. This group of antibiotics shows a wide range of interesting properties, including antiviral and anti-tumour activity, and as they bind to a particularly conserved region in the ribosome, they are likely to be difficult for microorganisms to develop resistance to. It is hoped that once the mechanism of action of these antibiotics is better understood, that modifications to the antibiotics can be effectively made to create new or hybrid antibiotics with more selective antibacterial, or indeed antiviral or anti-tumour properties. The nuclear magnetic resonance (NMR) structure of the RNA binding, peptidyl tranferase inhibitor antibiotics amicetin, blasticidin S and gougerotin, in their native solution states, have been successfully determined. The structures all exhibit a stable conformation, stabilised by intramolecular hydrogen bonds. Amicetin was observed to be folded, distinctly different from the linear, extended conformation of amicetin previously determined by X-ray crystallography. The structure of blasticidin S was found to be very similar to its X-ray crystal structure. Gougerotin was shown to form a similar conformation to blasticidin S, save that the end chain of gougerotin was bent at right angles to the rest of the molecule, forming a structure similar to that of the major bound X-ray crystal structure of blasticidin S. All the solution structures showed a similar conformation in the analogous regions of their chemical structure, suggesting that hybrid antibiotics could be produced.Two highly conserved RNA motifs of Halobacterium halobium (H. h.) and Escherichia coli (E. coli) 23S ribosomal RNAs were chosen to investigate their interaction with amicetin. The NMR structure of the H. h. and E. coli. 29-mer RNA motifs have been determined; the motifs both form well folded A-form RNA conformations. The E. coli NMR structure differs from the X-ray crystal structure of the motif contained within the ribosome, as a highly conserved adenine residue, which resides in a bulge strongly implicated with amicetin binding, folds into the helix as opposed to being flipped out. Instead, an adjacent cytosine residue partially flips out; whereas in the crystal structure, it is folded within the helix. The NMR stuctures of the H. h. motif differs from the X-ray crystal structure of the motif, contained within the ribosome, as none of the bases are flipped out and a number of non-canonical base pairs are formed in the solution structure. To continue this study, a fully 13C and 15N isotopically labelled version of the H. h. RNA sample has been partially assigned, and an initial structure determination has been performed, using ultra high field 1 GHz spectroscopy.Addition of amicetin to both the H. h. and E. coli 29-mer RNA samples were accompanied by discrete changes to the spectra, suggesting weak interaction between the two components. These can be qualitatively interpreted to changes induced in the local conformation of the RNA motifs and the amicetin arising from the formation of a complex, between the amicetin and the bulge region of the particular motif.

The conserved secondary structural RNA motifs of EncephaloMyoCarditis Virus (EMCV) have been well characterised biochemically and shown to play an important role in translation initiation by a novel cap-independent mechanism called Internal Ribosomal Entry Site (IRES). However, the three dimensional structure and interactions of these conserved motifs are not known, and hence the mechanism is not fully understood. The NMR results described in this thesis have provided, for the first time, new structural knowledge on the conformation of these motifs, their affinity for Mg2+ and their intermolecular interactions. RNA motifs selected from two separate domains (I and J) of the IRES structure were investigated using a range of 2D and 3D NMR techniques. The apical ‘hammerhead’ region of the I domain contains a highly conserved 16mer RNA which hosts a stable and mutationally sensitive G547CGA550 tetraloop. Sequence specific assignments were carried out on this motif, along with its Mg2+ complex, and a large number of NMR experimental constraints were generated for the RNA structure determination. Similarly, high resolution NMR structures of a distal 17mer RNA, which has been predicted to be a potential receptor for the GCGA tetraloop, and its Mg2+ complex were also produced. Thus, we were able to demonstrate that Mg2+ stabilises the RNA tertiary structure via non-specific interactions. Since the largest changes were induced at the tetraloop motif, we propose that Mg2+ stabilises the 16mer into an optimum conformation which is essential for IRES function. The determination of the structures of the above motifs led us to investigate the 16mer-17mer binary (1:1) complex at 1 GHz, in the presence of Mg2+. Significant changes were observed in the 1H and 31P chemical shift, NOE intensity and line width, clearly demonstrating RNA-RNA interactions taking place between the two components. The most interesting result to emerge was the distinct absence of NOEs from G547{NH} of the stable tetraloop, thus highlighting an important structural role for this functionally critical residue. Since no previous work has shown a clear interaction between the two RNAs, the results obtained in this project provide the first direct experimental evidence for intramolecular interactions in the I domain of EMCV IRES.Finally, we show how isotopically labelled RNAs can be successfully used as an aid in NMR assignment, analysis and structure determination. The J domain of EMCV IRES binds to eIF4GII protein and is essential for translation initiation. A suite of 3D NMR techniques were carried out on a highly enriched and uniformly 13C, 15N-labelled 39mer RNA. Several key features of the RNA, which may be involved in protein recognition, were identified. Further, a selectively 19F-labelled 16mer RNA from the I domain, was also studied to show how fluorine NMR can be used to probe RNA structure, dynamics and interactions. The RNA motifs of the EMCV IRES were shown to exhibit high stabilities, which are brought about by the complex folding of the various secondary structural elements involving RNA- Mg2+, RNA-RNA and RNA-protein tertiary interactions. It is these vital interactions that enable the IRES to recruit the ribosome in the translation initiation step of protein synthesis, and have laid a strong foundation for further NMR investigation of the whole IRES.

No description available.

Nuclear magnetic resonance (NMR) is one of the main approaches for protein struc- ture determination. The biggest advantage of this approach is that it can determine the three-dimensional structure of the protein in the solution phase. Thus, the natural dynamics of the protein can be studied. However, NMR protein structure determina- tion is an expertise intensive and time-consuming process. If the structure determi- nation process can be accelerated or even automated by computational methods, that will significantly advance the structural biology field. Our goal in this dissertation is to propose highly efficient and error tolerant methods that can work well on real and noisy data sets of NMR. Our first contribution in this dissertation is the development of a novel peak pick- ing method (WaVPeak). First, WaVPeak denoises the NMR spectra using wavelet smoothing. A brute force method is then used to identify all the candidate peaks. Af- ter that, the volume of each candidate peak is estimated. Finally, the peaks are sorted according to their volumes. WaVPeak is tested on the same benchmark data set that was used to test the state-of-the-art method, PICKY. WaVPeak shows significantly better performance than PICKY in terms of recall and precision. Our second contribution is to propose an automatic method to select peaks pro- duced by peak picking methods. This automatic method is used to overcome the limitations of fixed number-based methods. Our method is based on the Benjamini- Hochberg (B-H) algorithm. The method is used with both WaVPeak and PICKY to automatically select the number of peaks to return from out of hundreds of candidate peaks. The volume (in WaVPeak) and the intensity (in PICKY) are converted into p-values. Peaks that have p-values below some certain threshold are selected. Ex- perimental results show that the new method is better than the fixed number-based method in terms of recall. To improve precision, we tried to eliminate false peaks using consensus of the B-H selected peaks from both PICKY and WaVPeak. On average, the consensus method is able to identify more than 88% of the expected true peaks, whereas less than 17% of the selected peaks are false ones. Our third contribution is to propose for the first time, the 3D extension of the Median-Modified-Wiener-Filter (MMWF), and its novel variation named MMWF*. These spatial filters have only one parameter to tune: the window-size. Unlike wavelet denoising, the higher dimensional extension of the newly proposed filters is relatively easy. Thus, they can be applied to denoise multi-dimensional NMR-spectra. We tested the proposed filters and the Wiener-filter, an adaptive variant of the mean-filter, on a benchmark set that contains 16 two-dimensional and three-dimensional NMR- spectra extracted from eight proteins. Our results demonstrate that the adaptive spatial filters significantly outperform their non-adaptive versions. The performance of the new MMWF* on 2D/3D-spectra is even better than wavelet-denoising. Finally, we propose a novel framework that simultaneously conducts slice picking and spin system forming, an essential step in resonance assignment. Our framework then employs a genetic algorithm, directed by both connectivity information and amino acid typing information from the spin systems to assign the spin systems to residues. The inputs to our framework can be as few as two commonly used spectra, i.e., CBCA(CO)NH and HNCACB. Different from existing peak picking and resonance assignment methods that treat peaks as the units, our method is based on slices, which are one-dimensional vectors in three-dimensional spectra that correspond to certain (N, H) values. Experimental results on both benchmark simulated data sets and four real protein data sets demonstrate that our method significantly outperforms the state-of-the-art methods especially on the more challenging real protein data sets, while using a less number of spectra than those methods. Furthermore, we show that using the chemical shift assignments predicted by our method for the four real proteins can lead to accurate calculation of their final three-dimensional structures by using CS-ROSETTA server.

Structure determination of proteins is vital for the understanding of their function. It often relies on techniques that use intense X-ray pulses to create diffraction patterns of protein crystals, which then contain information on the three-dimensional structure of the crystallised protein. An emerging technique called Single Particle Imaging (SPI) aims to make possible the structure determination without the need for crystallisation of the proteins, by taking diffraction patterns from many individual proteins. Translating the diffraction patterns to spatial geometry is a daunting task that requires sophisticated algorithms which are not always able to determine the structure because of fundamental uncertainties in the recovery process. To improve the structure determination process, one can try to rotate the protein to a known orientation using electric fields before the measurement takes place. However, as a result of how these experiments are performed, the proteins may have water around them during this orientation phase. Using molecular dynamics (MD) on ubiquitin, a small protein found in all eukaryotic cells, it is shown that a layer of water around a protein does not only help to achieve orientation faster (compared to an identical protein without this layer), the water also provides the protein with increased structural stability.

京都大学 / 0048 / 新制・課程博士 / 博士(エネルギー科学) / 甲第20729号 / エネ博第357号 / 新制||エネ||70(附属図書館) / 京都大学大学院エネルギー科学研究科エネルギー基礎科学専攻 / (主査)教授 片平 正人, 教授 森井 孝, 教授 木下 正弘 / 学位規則第4条第1項該当 / Doctor of Energy Science / Kyoto University / DGAM

No description available.

<p dir="ltr">In life sciences, the determination of macromolecular structures and their functions, particularly proteins and protein complexes, is of paramount importance, as these molecules play critical roles within cells. The specific physical interactions of macromolecules govern molecular and cellular functions, making the 3D structure elucidation of these entities essential for comprehending the mechanisms underlying life processes, diseases, and drug discovery. Cryo-electron microscopy (cryo-EM) has emerged as a promising experimental technique for obtaining 3D macromolecular structures. In the course of my research, I proposed CryoREAD, an innovative AI-based method for <i>de nov</i>o DNA/RNA structure modeling. This novel approach represents the first fully automated solution for DNA/RNA structure modeling from cryo-EM maps at near-atomic resolution. However, as the resolution decreases, structure modeling becomes significantly more challenging. To address this challenge, I introduced Emap2sec+, a 3D deep convolutional neural network designed to identify protein secondary structures, RNA, and DNA information from cryo-EM maps at intermediate resolutions ranging from 5-10 Å. Additionally, I presented Alpha-EM-Multimer, a groundbreaking method for automatically building full protein complexes from cryo-EM maps at intermediate resolution. Alpha-EM-Multimer employs a diffusion model to trace the protein backbone and subsequently fits the AlphaFold predicted single-chain structure to construct the complete protein complex. Notably, this method stands as the first to enable the modeling of protein complexes with more than 10,000 residues for cryo-EM maps at intermediate resolution, achieving an average TM-Score of predicted protein complexes above 0.8, which closely approximates the native structure. Furthermore, I addressed the recognition of local structural errors in predicted and experimental protein structures by proposing DAQ, an evaluation approach for experimental protein structure quality that utilizes detection probabilities derived from cryo-EM maps via a pretrained multi-task neural network. In the pursuit of evaluating protein complexes generated through computational methods, I developed GNN-DOVE and DOVE, leveraging convolutional neural networks and graph neural networks to assess the accuracy of predicted protein complex structures. These advancements in cryo-EM-based structural modeling and evaluation methodologies hold significant promise for advancing our understanding of complex macromolecular systems and their biological implications.</p>

No Capítulo 1, os fundamentos da cristalografia de raios X estão sucintamente descritos. No Capítulo 2, seis estruturas de pequenas moléculas contendo átomos pesados em sua constituição foram determinadas. As quais são resumidas a seguir: 1)[Ru2Cl5(CO)(PPh3)3], Mr = 1194,21, cristaliza-se no sistema monoclínico, grupo espacial P21/c com a =14,618(4)&#197, b=18,043(7)&#197, c=20,31(3)&#197; &#946=99,81(5)&#176; V=5277(8)&#1973; Z=4; Dcalç =1,503g/cm-3; &#955(MoK&#945) = 0,71073&#197; &#956 = 0,954 mm-1; F(000) = 2404; R=0,538 para 9281 reflexões independentes e 487 parâmetros refinados. Os átomos de Ru estão ligados em ponte através de três ânions Cl. Um átomo de Ru é coordenado a dois outros átomos de Cl e a um ligante PPh3, o outro átomo de Ru está coordenado a dois ligantes PPh3 e a uma molécula de CO. 2)[RuCl3(dppb)H2O], Mr = 651,88, cristaliza-se no sistema ortorrômbico, grupo espacial Pbca; com a=14,932(1) &#197, b=18,133 (3)&#197, c=20,59(3)&#197; V=5576,0(1)&#1973; Z=8; Dcalc =1,553g/cm-3; &#955(MoK&#945) = 0,71073&#197; &#956 = 0,985 mm-1; F(000)=2648; R=0,0461 para 4892 reflexões independentes e 316 parâmetros refinados. O complexo é hexacoordenado. Os átomos P encontram-se em posição cis, um em relação ao outro, formando um complexo próximo de uma estrutura octaédrica. Esta estrutura apresentou interação intermolecular Cl...H. A distância entre o H de uma molécula e o Cl é de 2,48(2)&#197. 3) FeC19H1919N19S19], Mr=377,28, cristaliza-se no sistema monoclínico, grupo espacial P21/n; com a=11,715(2)&#197, b=7,830(2)&#197, c=18,728(3)&#197; &#946=91,570(1)&#176; V=1717,1(6)&#1973; Z=4; Dcalc =1,459g/cm-3; &#955(MoK&#945) = 0,71073&#197; &#956 = 1,004 mm-1; F(000)=784; R=0,0453 para 3018 reflexões independentes e 218 parâmetros refinados. O complexo é formado por um átomo de ferro decacoordenado em uma extremidade e na outra existe um anel aromático, indicando que os radicais genéricos mostrados na Seção (2.5) são R\'=C\'H IND. 3\', X=S1 e R\"=fenil. 4)[pyH][RuCl4(dmso)(py)].(CH2Cl2)1/2, Mr=562,11 cristaliza-se no sistema triclínico, grupo espacial P1; com a= 7,7608(1)&#197, b=85451(1)&#197, c=15,095(5)&#197; &#945=88,27(2)&#186; &#946=79,33(2)&#186; &#947,=88,77(1)&#186; V=983,2(4)&#1973; Z=2; Dcalc=1,899gcm-3; &#955(CuK&#945)=1,54184 &#197; &#956=15,001 mm-1; F(000)=556; R=0,0886 para 2909 reflexões independentes e 204 parâmetros refinados. O Ru está octaedricamente coordenado a quatro átomos Cl coplanares, a um N do anel de uma piridina e ao dmso, em posição trans entre si. Um outro grupo piridina protonado, que forma o cátion da estrutura, completa a estrutura. 5)[RuCl2(CO)2(AsPh3)2, Mr =840,43, cristaliza-se no sistema monoclínico, grupo espacial P21/n; com a=710,520(4)&#197, b=25,823(5)&#197, c=12,780(2)&#197; &#946=100,7401(1)&#176; V=3411,0(1)&#1973; Z=4; Dcalc =1,637gcm-3; &#955(CuK&#945)=1,54184 &#197; &#956=7,576 mm-1; F(000)=1672; R=0,0739 para 4284 reflexões independentes e 406 parâmetros refinados. O átomo de Ru está ligado a dois átomos de Cl e a duas moléculas CO, que formam aproximadamente um plano entre si. Os CO\'s estão em posição trans em relação aos Cl\'s. O átomo de Ru também apresenta coordenação com duas PPh3. 6)[Ru2ClBr4(CO)(AsPh3).CH2Cl2)<, Mr=154,88 cristaliza-se no sistema monoclínico, grupo espacial P21/c; com a=14,766(2)&#197, b=18,519(2)&#197, c=20,730(4)&#197; &#946=100,085(1)&#176; V=5581,2(1)&#1973; Dcalc =1,839gcm-3; &#955(CuK&#945)=1,54184 &#197; &#956=10,947mm-1; F (000)=3004; R=0,0955 para 5738 reflexões independentes e 493 parâmetros refinados. O complexo é formado por dois átomos de Ru em ponte através de três ânions Br. Um átomo de Ru é também coordenado a um átomo Br, a um Cl e a um ligante trifenilfosfina. O outro átomo de Ru está ligado a duas trifenilarsinas e a uma molécula de monóxido de carbono. No capítulo 3, apresentam-se as conclusões e planos futuros / In Chapter 1, the basic principles of X-ray crystallography that have been used in this work are briefly described. In Chapter 2, six small molecule structures with heavy atoms are presented. They are summarized as follows: 1)[Ru2Cl5(CO)(PPh3)3], Mr = 1194,21, crystallizes in the monoclinic system, space group P21/c com a =14,618(4)&#197, b=18,043(7)&#197, c=20,31(3)&#197; &#946=99,81(5)&#176; V=5277(8)&#1973; Z=4; Dcalc =1,503g/cm-3; &#955(MoK&#945) = 0,71073&#197; &#956 = 0,954 mm-1; F(000) = 2404; R=0,538 for 9281 independent reflections and 487 refined parameters. This triply chloro-bridged binuclear complex is formed by two Ru atoms bridged through three chloride anions. One Ru atom is further coordinated to two non-bridging Cl atoms and a triphenylphosphine ligand, whereas the other is bonded to two PPh3 ligands and to a carbon monoxide molecule. 2) 3(dppb)H2O], Mr = 651,88, crystallizes in the orthorhombic system, space group Pbca; a=14,932(1) &#197, b=18,133 (3)&#197, c=20,59(3)&#197; V=5576,0(1)&#1973; Z=8; Dcalc =1,553g/cm-3; &#955(MoK&#945) = 0,71073&#197; &#956 = 0,985 mm-1; F(000)=2648; R=0,0461 for 4892 independent reflections and 316 refined parameters. The complex is hexacoordinated. The P atoms are in cis position to each other, forming a octhaedrical structure. This structure shows an intermolecular interaction between one Cl atom from one complex and a water hydrogen of a neighboring complex in the lattice, with Cl...H distance of 2,48(2)A. 3)[FeC19H1919N19S19], Mr=377,28, crystallizes in the monoclinic system, space group P21/n; a=11,715(2)&#197, b=7,830(2)&#197, c=18,728(3)&#197; &#946=91,570(1)&#176; V=1717,1(6)&#1973; Z=4; Dcalc =1,459g/cm-3; &#955(MoK&#945) = 0,71073&#197; &#956 = 1,004 mm-1; F(000)=784; R=0,0453 for 3018 indepen dent reflections and 218 refined parameters. This complex shows a decacoordinated Fe atom in one end of the molecule and an aromatic ring in the other, showing that the gereric radicals in Section (2.5) are R\'= CH3, X=Sl and R\" =phenyl. 4)[pyH][RuCl4(dmso)(py)].(CH2Cl2)1/2, Mr=562,11, crystallizes in the triclinic system, space group P1; a= 7,7608(1)&#197, b=85451(1)&#197, c=15,095(5)&#197; &#945=88,27(2)&#186; &#946=79,33(2)&#186; &#947,=88,77(1)&#186; V=983,2(4)&#1973; Z=2; Dcalç=1,899gcm-3; &#955(CuK&#945)=1,54184 &#197; &#956=15,001 mm-1; F(000)=556; R=0,0886 for 2909 independent reflections and 204 refined parameters. The Ru ion is octahedrally coordinated to four co-planar chloride atoms and to the nitrogen of the pyridine ring, which are trans to each other. Another protonated pyridine group, which forms the counter-cation complete the crystal struet ure. 5)[RuCl2(CO)2(AsPh3)2, Mr =840,43, crystalizes in the monoclinic system, space group P21/n; a=710,520(4)&#197, b=25,823(5)&#197, c=12,780(2)&#197; &#946=100,7401(1)&#176; V=3411,0(1)&#1973; Z=4; Dcalc =1,637gcm-3; &#955(CuK&#945)=1,54184 &#197; &#956=7,576 mm-1; F(000)=1672; R=0,0739 for 4284 independent reflections and 406 refined parameters. This complex shows a Ru atom bonded to two Cl atoms and to two CO molecules, which aproximatelly form a plane between then. The CO\'s are trans to the chlorides and the Ru further presents a coordination to two PPh3. 6) [Ru2ClBr4(CO)(AsPh3).CH2Cl2)<, Mr=154,88, crystallizes in the monoclinic system, space group P21/c; com a=14,766(2)&#197, b=18,519(2)&#197, c=20,730(4)&#197; &#946=100,085(1)&#176; V=5581,2(1)&#1973; Dcalc =1,839gcm-3; &#955(CuK&#945)=1,54184 &#197; &#956=10,947mm-1; F (000)=3004; R=0,0955 for 5738 independent reflections and 493 refined parameters. This complex is formed by two Ru atoms bridged by three Br anions. One Ru atom is further coordenated to a Br atom, to a CI atom and to a triphenylphosphine ligand, whereas the other is bonded to two AsPh3 and to a carbon monoxide molecule. In chapter 3, conclusions and future plans are given.