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Exploring Structure and Function of Human Cold Sensing Protein TRPM8 with ROSETTA Comparative Models
Description
Transient Receptor Potential (TRP) channels are a diverse class of ion channels notable as polymodal sensors. TRPM8 is a TRP channel implicated in cold sensation, nociception, and a variety of human diseases, including obesity and cancer. Despite sustained interest in TRPM8 since its discovery in 2001, many of the molecular mechanisms that underlie function are not yet clear. Knowledge of these properties could have implications for medicine and physiological understanding of sensation and signaling. Structures of TRP channels have proven challenging to solve, but recent Cryoelectron microscopy (Cryo-EM) structures of TRPV1 provide a basis for homology-based modeling of TRP channel structures and interactions. I present an ensemble of 11,000 Rosetta computational homology models of TRPM8 based on the recent Cryo-EM apo structure of TRPV1 (PDB code:3J5P). Site-directed mutagenesis has provided clues about which residues are most essential for modulatory ligands to bind, so the models presented provide a platform to investigate the structural basis of TRPM8 ligand modulation complementary to existing functional and structural information. Menthol and icilin appear to interact with interfacial residues in the sensor domain (S1-S4). One consensus feature of these sites is the presence of local contacts to the S4 helix, suggesting this helix may be mechanistically involved with the opening of the pore. Phosphatidylinositol 4,5-bisphosphate (PIP2)has long been known to interact with the C-terminus of TRPM8, and some of the homology models contain plausible binding pockets where PIP2 can come into contact with charged residues known to be essential for PIP2 modulation. Future in silico binding experiments could provide testable hypothesis for in vitro structural studies, and experimental data (e.g. distance constraints from electron paramagnetic resonance spectroscopy [EPR]) could further refine the models.
ContributorsHelsell, Cole Vincent Maher (Author) / Van Horn, Wade (Thesis director) / Wang, Xu (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Department of Chemistry and Biochemistry (Contributor)
Created2015-05
Description
A distributed sensor network (DSN) is a set of spatially scattered intelligent sensors designed to obtain data across an environment. DSNs are becoming a standard architecture for collecting data over a large area. We need registration of nodal data across the network in order to properly exploit having multiple sensors. One major problem worth investigating is ensuring the integrity of the data received, such as time synchronization. Consider a group of match filter sensors. Each sensor is collecting the same data, and comparing the data collected to a known signal. In an ideal world, each sensor would be able to collect the data without offsets or noise in the system. Two models can be followed from this. First, each sensor could make a decision on its own, and then the decisions could be collected at a ``fusion center'' which could then decide if the signal is present or not. The fusion center can then decide if the signal is present or not based on the number true-or-false decisions that each sensor has made. Alternatively, each sensor could relay the data that it collects to the fusion center, and it could then make a decision based on all of the data that it then receives. Since the fusion center would have more information to base its decision on in the latter case--as opposed to the former case where it only receives a true or false from each sensor--one would expect the latter model to perform better. In fact, this would be the gold standard for detection across a DSN. However, there is random noise in the world that causes corruption of data collection, especially among sensors in a DSN. Each sensor does not collect the data in the exact same way or with the same precision. We classify these imperfections in data collections as offsets, specifically the offset present in the data collected by one sensor with respect to the rest of the sensors in the network. Therefore, reconsider the two models for a DSN described above. We can naively implement either of these models for data collection. Alternatively, we can attempt to estimate the offsets between the sensors and compensate. One could see how it would be expected that estimating the offsets within the DSN would provide better overall results than not finding estimators. This thesis will be structured as follows. First, there will be an extensive investigation into detection theory and the impact that different types of offsets have on sensor networks. Following the theory, an algorithm for estimating the data offsets will be proposed correct for the offsets. Next, we will look at Monte Carlo simulation results to see the impact on sensor performance of data offsets in comparison to a sensor network without offsets present. The algorithm is then implemented, and further experiments will demonstrate sensor performance with offset detection.
ContributorsMonardo, Vincent James (Author) / Cochran, Douglas (Thesis director) / Kierstead, Hal (Committee member) / Electrical Engineering Program (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
This thesis details the design process of a variable gain amplifier (VGA) based circuit which maintains a consistent output power over a wide range of input power signals. This effect is achieved by using power detection circuitry to adjust the gain of the VGA based on the current input power so that it is amplifier to a set power level. The paper details the theory behind this solutions as well as the design process which includes both simulations and physical testing of the actual circuit. It also analyses results of these tests and gives suggestions as to what could be done to further improve the design. The VGA based constant output power solution was designed as a section of a larger circuit which was developed as part of a senior capstone project, which is also briefly described in the paper.
ContributorsMeyer, Sheldon (Author) / Aberle, James (Thesis director) / Chakraborty, Partha (Committee member) / Electrical Engineering Program (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description
With uses in fields such as medicine, agriculture, and biotechnology, halogenases are useful enzymes in nature which add or substitute halogens onto other molecules. By doing so, they become necessary for biosynthesis and cross-coupling reactions. Halogenases can be classified by three main types of mechanisms: nucleophilic, radical, and electrophilic. From there, they can be further broken down by the halogen involved, the substrate needed, other proteins used, or molecules generated. A notable example is PrnA which is a tryptophan-7 halogenase that falls under the flavin-dependent definition with an electrophilic mechanism. Historically, research on these enzymes was slow until the use of bioinformatics rapidly accelerated discoveries to the point where halogenases like VirX1 can be identified from viruses. By reviewing the literature available on halogenase since their first analysis, a better understanding of their functions can be obtained. Also, with the application of bioinformatics, a phylogenetic analysis on the halogenases present in cyanobacteria can be conducted and compared.
ContributorsUsmani, Hibah (Author) / Zhu, Qiyun (Thesis director) / Neilan, Brett (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / School of Life Sciences (Contributor)
Created2024-05
Description
The objective of this paper is to find and describe trends in the fast Fourier transformed accelerometer data that can be used to predict the mechanical failure of large vacuum pumps used in industrial settings, such as providing drinking water. Using three-dimensional plots of the data, this paper suggests how a model can be developed to predict the mechanical failure of vacuum pumps.
ContributorsHalver, Grant (Author) / Taylor, Tom (Thesis director) / Konstantinos, Tsakalis (Committee member) / Fricks, John (Committee member) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
This Creative Project was carried out in coordination with the capstone project, Around the Corner Imaging with Terahertz Waves. This capstone project deals with a system designed to implement Around the Corner, or Non Line-of-Sight (NLoS) Imaging. This document discusses the creation of a GUI using MATLAB to control the Terahertz Imaging system. The GUI was developed in response to a need for synchronization, ease of operation, easy parameter modification, and data management. Along the way, many design decisions were made ranging from choosing a software platform to determining how variables should be passed. These decisions and considerations are discussed in this document. The resulting GUI has measured up to the design criteria and will be able to be used by anyone wishing to use the Terahertz Imaging System for further research in the field of Around the Corner or NLoS Imaging.
ContributorsWood, Jacob Cannon (Author) / Trichopoulos, Georgios (Thesis director) / Aberle, James (Committee member) / Electrical Engineering Program (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05