Automatic Expansion of 3D Motif Palette for RNA Tertiary Structure Design
Abby Mausey
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07/28/2020
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This presentation discusses the methods used to create an updated library of RNA structural motifs and the code used to process the structures.
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- [00:00:00.680]Hello, my name is Abby Mausey,
- [00:00:03.030]and I am going to present the research project
- [00:00:05.450]that I've been working on this summer,
- [00:00:07.460]which is the Automatic Expansion of 3D Motif Palette
- [00:00:11.010]for RNA Tertiary Structure Design.
- [00:00:15.120]RNA is a component of a multitude of biological systems.
- [00:00:19.160]To perform these cellular functions,
- [00:00:21.550]RNAs must fold into complex 3D structures.
- [00:00:25.940]RNA's tertiary structure is unique,
- [00:00:28.400]as it is composed of discrete
- [00:00:30.210]and module building blocks known as motifs.
- [00:00:33.490]These motifs can be approximated as static Lego blocks,
- [00:00:37.290]and have been assembled into a diverse set
- [00:00:39.570]of new RNA nanostructures,
- [00:00:41.790]for therapeutic and engineering applications.
- [00:00:45.280]Currently, motifs included into new RNAs,
- [00:00:48.950]must be manually selected by experts,
- [00:00:51.590]which potentially may lead to a suboptimal solution
- [00:00:55.170]to the given RNA design challenge.
- [00:00:58.000]The goal of this project is to generate
- [00:01:00.100]a self updating library of motifs to be used in RNA design.
- [00:01:04.720]There are a few critical steps I used
- [00:01:06.920]to create this library,
- [00:01:08.660]such as, learning how to use Python,
- [00:01:11.270]extracting data from the protein data bank,
- [00:01:14.220]pulling the different motifs from each PDB code,
- [00:01:17.200]and saving this information to a new CIF.
- [00:01:21.150]I started with no programming experience at all.
- [00:01:24.520]I've made significant progress in understanding
- [00:01:27.060]how to write computer programs in the Python language.
- [00:01:30.750]Learning Python has enabled me to make progress
- [00:01:33.530]in writing the self updating library of motifs.
- [00:01:37.060]Figure one shows an example code I worked with to try
- [00:01:40.030]to understand strings, lists, for loops, if statements,
- [00:01:45.290]and print statements more thoroughly.
- [00:01:48.560]After I learned how to use Python,
- [00:01:50.750]the first step of this project was to download
- [00:01:53.270]all of the current RNA structures
- [00:01:55.340]from the protein data bank or PDB.
- [00:01:59.200]I have written Python function that queries
- [00:02:01.590]the PDB for each known RNA structure,
- [00:02:04.650]and downloads a crystallographic information file or CIF
- [00:02:08.580]for each of them to a common folder,
- [00:02:11.220]I access this list of RNA structures
- [00:02:13.740]from the non-redundant set of structures curated
- [00:02:16.370]by the Motif 3D Atlas.
- [00:02:18.900]Further, these CIFs contain all of the atomic coordinates
- [00:02:21.760]for the entire RNA structure.
- [00:02:24.800]Figure two shows PDB 2R8S that was extracted and rendered
- [00:02:29.930]in the software PyMOL.
- [00:02:31.860]Each PDB, like 2R8S was solved
- [00:02:35.550]via high resolution techniques
- [00:02:37.630]such as X-ray crystallography,
- [00:02:39.960]or cryo electron microscopy.
- [00:02:43.170]We further had to process these files to find all
- [00:02:46.100]of the RNA motifs contained in the larger RNA structure.
- [00:02:50.290]These include loops, junctions, and helices.
- [00:02:54.030]When new structures are identified,
- [00:02:56.140]they'll be processed using DSSR
- [00:02:58.810]or Dissecting the Spacial Structure of RNA
- [00:03:01.660]to separate them into their constituent motifs.
- [00:03:04.960]In order to extract the motifs using Python,
- [00:03:08.040]the next step was to filter through each
- [00:03:10.060]of the individual CIFs again,
- [00:03:12.080]and separate out each line of relevant information,
- [00:03:15.260]so that the motif coordinates could be extracted.
- [00:03:18.570]Once these lines were extracted,
- [00:03:20.710]keys were made to find three specific types
- [00:03:23.010]of information, known as the residue identity,
- [00:03:26.230]chain identity, and residue number.
- [00:03:28.980]These keys hold the information to know
- [00:03:31.290]which residues correspond to a specific type of motif.
- [00:03:35.010]An example of this is shown in figure four,
- [00:03:38.030]which has all of the isolated motifs from the 2R8S PDB.
- [00:03:43.310]Some motifs interact with one another via hydrogen bonding,
- [00:03:47.210]and this is called a tertiary contact.
- [00:03:50.120]This problem was taken into account when writing the code,
- [00:03:53.390]and figure three shows the tertiary contacts
- [00:03:56.080]in the 2R8S PDB highlighted in the red color.
- [00:04:01.910]The code I wrote produced a massive amount of data,
- [00:04:05.090]and the number of motifs I was able
- [00:04:07.040]to successfully isolate are shown here.
- [00:04:09.730]This code is currently still running,
- [00:04:12.000]and more motifs are being isolated as we speak.
- [00:04:15.090]So, all of the numbers here will drastically increase
- [00:04:17.700]by the time the code is finished.
- [00:04:20.480]The future of this project includes making
- [00:04:22.660]new RNA structures from the motifs found
- [00:04:25.400]from this updated library.
- [00:04:27.820]To do this, RNA structures will be probed
- [00:04:30.650]with chemical mapping techniques to confirm
- [00:04:32.720]that they will retain their structure.
- [00:04:34.940]Figures five and six, show visually how
- [00:04:37.950]we will assemble motifs into nano structures,
- [00:04:40.790]and probe their structure via chemical mapping.
- [00:04:44.670]By creating a centralized location
- [00:04:46.840]for all known RNA structural motifs,
- [00:04:49.640]and designing successful RNA structures,
- [00:04:52.390]from the use of the motif database,
- [00:04:54.910]this research will achieve its long term goal.
- [00:04:57.990]Thank you to Dr. Joseph Yesselman
- [00:04:59.860]for allowing me to be on his team this summer,
- [00:05:02.410]and teaching me so many things,
- [00:05:04.530]as well as Christopher Jurich for being an excellent mentor,
- [00:05:07.590]and Python tutor.
- [00:05:09.120]Special thanks to the University of Nebraska-Lincoln,
- [00:05:12.350]and the Union University Department of Chemistry,
- [00:05:15.250]as well as the National Science Foundation
- [00:05:17.430]for their generous grant for me to do my research.
- [00:05:20.610]Thank you for watching my presentation.
- [00:05:22.360]I look forward to some great discussions with you all.
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