Visualization of Three-dimensional Protein Structure

Transcription

1 Visualization of Three-dimensional Protein Structure Man-Ho Tang Department of Physics, The Chinese University of Hong Kong Supervised by Peter Zwart, Banumathi Sankaran Lawrence Berkeley National Laboratory, Berkeley, CA, USA December 12, 2015 This report presents the procedure of protein crystallography carried out in practice to visualize the 3D structure of protein. Two of the main processes are focused: crystallization of protein, reconstruction of protein structure from diffraction data. A closer examination on refinement techniques used and difficulties faced during the reconstruction process using a software suite Phenix is also included. 1 Introduction Protein is a macromolecule comprising a chain of amino acids, with length ranging from tens to hundreds of residues. This seemingly one-dimensional structure curls up naturally into a characteristic three-dimensional structure as to attain a energetically favorable state, as described by the process named as Protein Folding. Since the functions of protein are highly determined by its geometric shape, the knowledge about protein structure helps scientists to study, understand and manipulate many biological reactions. Protein crystallography is a powerful tool to reveal the structure of protein. Generally, in crystallography, X-ray is being directed to the crystalline sample. The phases and intensities of 1

2 the scattered X-ray are then measured. With this diffraction data, crystalline structure can be deduced. 2 Overview of Protein Crystallography To start with, protein sample has to be extracted and purified at certain high concentration. Then the sample will be crystallized at various conditions, such as different ph values, temperature etc., to yield qualified crystals. Next, the protein crystal is put onto the beamline to gather diffraction data, which is then passed to several computer programs to generate the corresponding electron density map and thus the three-dimensional structure of the protein sample. Of all the above, the crystallization step and the reconstruction step at Advanced Light Source in Lawrence Berkeley National Lab will be further discussed in the following. 2.1 Crystallization Figure 1: Nano-dispenser for making crystallization plates (left) and light microscope for identifying qualified crystals (right) Different crystallizing conditions significantly and sensitively affects the quality of crystal, crystallographers try out different combination of solution conditions by a Trial and Error 2

3 approach in the aim to obtain single, clear and large crystals, which are needed for achieving high resolution in diffraction data during the succeeding process. Our group adopted the use of robotic nano-dispenser, Crystal Phoenix, to effectively and accurately implement as many as 96 crystallizations with at most three different solution conditions in a single crystallization plate. The robot is programed manually to carry out particular operation. With instruction from experienced chemists in our group, the optimal crystallizing conditions can be figured out efficiently. The qualified crystals are then identified by microscope and extracted for diffraction. 2.2 Reconstruction of Protein Structure Figure 2: An example of electron density map generated from diffraction data (left) and the protein structure calculated by fitting the electron density displayed in Coot (right) With the help of the software suite Phenix which is designed for the automated determination of molecular structures using X-ray crystallography, an electron density map can be generated from the diffraction data. Referring to this map, and usually together with the protein sequence, 3

4 the whole three-dimensional protein structure can be calculated and visualized. Figure 3: The simulated structure (color rods) with electron density map (blue contour surface) and difference map (red and green contour surfaces) Coot is one of the sub program in Phenix. It provides real-time GUI manual refinement on the structure. In addition to the electron density map, a density difference map can also be generated which shows the deviation of the electron density between the simulated model and the original data. When the simulated model contains too much electron density in a certain region, that part will be indicated by a red contour surface. On the other hand, when there is inadequate electron density, the region will be indicated by a green contour surface. Thus, we can manually refine the simulated structure by investigating the difference map and pass our modified structure to built-in program in Phenix for further refinement. A structure with about 200 residues requires typically rounds of refinement before the structure can be finalized. 4

5 3 Refinement Techniques and Difficulties The basic concept while carrying out manual refinement is to eliminate the deviation between simulated model and original data. Which is to say, according to the difference map, atoms should be removed or added in the region of red or green blobs respectively. Three examples of manual refinement on human carbonic anhydrase, protein samples submitted from George Whitesides Research Group in Department of Chemistry and Chemical Biology at Harvard University, will be shown in the following, with further discussion particularly on the third example. 3.1 Misaligned Residue Figure 4: The difference map shows the problematic region at residue 230 (left). After manual refinement is done, no significant blobs presents anymore. Taking a look at this structure Et1, the program at first cannot model well residue 230, which is an asparagine (Asn). There are obvious red and green blobs surrounding the residue. It is quite clear that the -CO-NH2 in the carboxamide group is misaligned. To solve the problem, the 5

6 chi angle at the corresponding carbon atom has to be rotated to fit into the blue electron density. As shown in figure 4, the difference map no longer shows significant blobs after refinement. 3.2 Side-Chain Double Conformations Figure 5: The difference map shows the problematic region at residue 230 (left). After manual refinement is done, no significant blobs presents anymore. Here is one of the structure 12BTA, the program at first cannot model well residue 130, which is an aspartic acid (Asp). There are also both red and green blobs around the residue, however, the original model already fits quite well in the blue density. This can be interpreted that it should not be just the dislocation of side chain. Also, the blue electron density is a bit bulky around the whole side chain, and there is some blue density bulging out. All of the above can be the indication of presence of side-chain double conformation. This is possible when the side chain are switching between two competing energetically favourable states. To solve the problem, side-chain double conformation is added and fitted into the extra density manually. As seen in figure 5, the structure is improved after refinement. 6

7 Since the side-chain double, or even triple, conformations are fairly common in protein while the program can rarely identify them automatically, manually adding double conformations is an usual and important step to refine the protein structure. 3.3 Main-Chain Conformations Figure 6: The region around residue 46 contains some noticeable green blobs which remained problematic even after several rounds of refinements Around residue 46, which is a proline, of 12BTA, a large green region remained presence even after more than ten rounds of refinements. This region is suspicious in the sense that the green blob is too large to be thermal noise, instead there must some hidden structure. However, neither moving around residue or adding side-chain double conformation give satisfactory refinement result. In our work, as human carbonic anhydrase is a common protein which is studied frequently in different research projects, lots of its structure have been solved and publicized onto Protein Data Bank. We have taken the chance to look over the solved structures in the data base to 7

8 see if there could be any insight. During the search, we found the structure 3U45. While superposing 3U45 with our structure 12BTA, the structure orientation of 3U45 matches well with the green blobs in 12BTA. Figure 7: The difference map of 12BTA at residue 46 (left), and the resultant map after the superposition with 3U45 (right) This shows that there is possibly main-chain double conformations at residue 46. Our group added main-chain conformation to 12BTA based on 3U45 and ran several rounds of refinements. As shown in figure 8, the result is surprisingly promising. In the investigation on two other related structure, 8BTA and Et1, the main-chain conformations at residue 46 are also found. Besides, two more regions (residues 7-10 and residues 73-76) are likewise found with main-chain conformations. 8

9 Figure 8: We rebuild 12BTA as indicated by the green chains (left), and the result is promising after refinement (right) Figure 9: Residues of 12BTA with one main chain (left), main-chain conformation is then added to eliminate the density difference (right) 9

10 4 Discussion Our group discovered three regions of main-chain conformations in all of the three human carbonic anhydrase sample. We found no related publicized structure showing the main-chain conformations. We believe it is the high resolution of our diffraction data that leads us to discover these hidden structure. Although side-chain of protein usually dominantly determine the specificity of protein, such as the ligand-binding property, main-chain conformations can potentially affect the functions of protein indirectly. Moreover, visualizing protein in an accurate form is in itself a crucial matter for research studies. Therefore, our group plan to develop a program which can update all publicized structure of human carbonic anhydrase by adding main-chain conformations. Meanwhile, resembling side-chain conformations, main-chain conformations should be universal to all other proteins. It is likely that high resolution of diffraction data can also help to reveal the main-chain conformations in other proteins. Thus benefiting our understanding of knowing how the shape of a protein can affect its functions as a whole. 5 Acknowledgment I would like to gratefully thank my research supervisor Dr. Peter Zwart and Dr. Banumathi Sankaran who has given me the chance to join their group to work and learn throughout the five months. Also, Dr. Jose Henrique Pereira who taught me techniques about crystallization of protein. It is my pleasure to be a participant of the Overseas Program for Undergraduate Student (OPUS), special thanks to the program coordinators Prof. Chu Ming Chung and Prof. Luk Kam Biu. 10