One of the core problems in the analysis of protein tandem mass spectrometry data is the peptide assignment problem: determining, for each observed spectrum, the peptide sequence that was responsible for generating the spectrum. Two primary classes of methods are used to solve this problem:database search and de novo peptide sequencing. State-of-the-art methods for de novo sequencing employ machine learning methods, whereas most database search engines use hand-designed score functions to evaluate the quality of a match between an observed spectrum and a candidate peptide from the database. We hypothesize that machine learning models for de novo sequencing implicitly learn a score function that captures the relationship between peptides and spectra, and thus may be re-purposed as a score function for database search. Because this score function is trained from massive amounts of mass spectrometry data, it could potentially outperform existing, hand-designed database search tools. To test this hypothesis, we re-engineered Casanovo, which has been shown to provide state-of-the-art de novo sequencing capabilities, to assign scores to given peptide-spectrum pairs. We then evaluated the statistical power of this Casanovo score function, Casanovo-DB, to detect peptides on a benchmark of three mass spectrometry runs from three different species. Our results show that, at a 1% peptide-level false discovery rate threshold, Casanovo-DB outperforms existing hand-designed score functions by 35% to 88%. In addition, we show that re-scoring with the Percolator post-processor benefits Casanovo-DB more than other score functions, further increasing the number of detected peptides.

Proper chromosome segregation in mitosis relies on the correct attachment of kinetochores to the plus ends of microtubules. Kinetochores are protein complexes that assemble onto centromeres and bind microtubules. Microtubules are dynamic polymers of 𝛼- and 𝛽-tubulin subunits with an intrinsic structural polarity due to the repeated head-to-tail orientation of the heterodimer subunits in the lattice. This polarity results in a faster growing plus end and a slower growing minus end. Kinetochores are thought to initially bind to the microtubule lattice and then achieve plus end attachment by the action of plus end directed motor proteins or by the microtubule tip disassembling to the attachment point. While the plus end attachment is essential for mitotic fidelity, it remains unknown if the kinetochores themselves have an intrinsic polarity preference. Using total internal reflectance fluorescence microscopy, we have found that individual kinetochores assembled on centromeric DNA have a strong preference for binding the plus ends of stabilized microtubules in the absence of motor proteins and ATP or microtubule dynamics. Furthermore, using optical trapping we are able to measure the rupture forces of kinetochores on both ends of microtubules and have found that the observed preference for plus ends is matched by a greater binding strength at plus end tips. These results together give insight into how kinetochores could efficiently form plus end tip attachments and how they likely play a part in cell cycle regulation by using tension to sense a correct attachment. A better understanding of the specific mechanisms of kinetochore microtubule binding is valuable for understanding control of mitotic progression and could potentially inform more targeted anti-cancer therapies that focus specifically on dividing cells without impacting regular cell function.

 Injectable biomaterials can be used for targeted, local delivery of drugs and small protein factors. However, designing a biomaterial that is self-healing, bioresorbable, highly-defined, and allows for the independent release of multiple protein drugs remains a challenge. Interpenetrating network (IPN) hydrogels formed by physical crosslinks provide a solution as they combine the properties of two networks into one material, as well as form gels that are injectable and self-healing. Our project aims to produce the first ever reported fully recombinant protein-based IPN hydrogel that can be used to deliver multiple drugs simultaneously. Recombinant protein-based polymers are advantageous for forming biomaterials due to their bioactivity, biocompatibility, and tunability. Each biopolymer contains coiled-coil proteins linked by a flexible hydrophilic linker that is bisected by a click-like chemistry protein system, known as a polyproteam. These polyproteams allow drugs or protein factors to be covalently ligated to the networks, so that drug delivery is dependent on material erosion instead of diffusion. We characterized the material’s properties using rheometry to measure material stiffness, percent strain at which the material liquifies, and self-healing behavior. Then, we tested the ability of our hydrogel to deliver drugs by ligating epidermal growth factor and insulin growth factor to the hydrogel and measured the release of protein over time through a Western Blot. The bioactivity of the growth factors was confirmed by culturing with human mesenchymal stem cells (hMSCs) and using a Western Blot to measure activation of the ERK signaling pathway. If successful, the IPN hydrogel can be used for clinical applications, as a tool for drug delivery.

Current technology to control 3D cell function takes advantage of bioorthogonal photochemistry to immobilize proteins into materials by using photocages—photoremovable molecular groups that block protein activity. However, diffusion limitations necessitate patterning times ranging from hours to weeks, far longer than the timescales of many biological processes. Protein activation aids signaling events within the extracellular matrix (ECM), leading to downstream changes in cell fate and physiological responses in our bodies. In order to probe and investigate biological systems, hydrogel materials provide an ideal synthetic platform, due to their polymeric, water-swollen characteristics that mimic the native ECM. In this project, I will use light to control the spatial and temporal presentation of biochemical cues through the photoactivation of proteins within hydrogels. We hypothesize that the kinetics of the protein activity between solution and biomaterial studies should correlate, given their dose-dependent response to light exposure—by varying the intensities of light and time intervals of exposure. By characterizing the photoactivatable protein system and controlling protein activity, we intend to use this platform to photoactivate biologically relevant proteins to control signaling that occurs on shorter time scales, applicable to biochemical processes.

Mutations in ß-myosin heavy chain (MHC) are implicated in familial cardiomyopathies. Such mutations can modify myosin motor function or modulate the number of heads participating in contraction; changes at the protein level in turn affect sarcomere performance and ultimately lead to pathologic cardiac remodeling. Our aim is to better understand the pathogenesis of familial dilated cardiomyopathy (DCM) by studying how the R369Q mutation, which resides on loop 4 of the ß-MHC structure and participates in the interaction with actin, modulates the structure and dynamics of pre-powerstroke myosin. Previously, we have employed molecular dynamics to simulate and study the pre-powerstroke state at atomistic scale. Measurements of root mean square deviation (RMSD) and root mean square fluctuation (RMSF) for each of the six simulations demonstrated that R369Q myosin had a higher average RMSD over the course of the simulation and higher RMSF per residue than did wild type; this suggests that the overall structure of the R369Q ß-MHC is less structurally stable than the wild type. Additionally, we observed a significant loss of several contacts between Switch I and a flexible loop in the Upper 50 kDa Domain in the R369Q structure. Thus, we postulate that the R369Q mutation introduces structural instability into the myosin structure and disrupts the inter-protein communication of structural changes that drives the ATPase cycle. Here, we expand on these results with analysis of a stem cell-derived cardiomyocyte model and Brownian dynamics simulations. Analysis of myofibrils, the contractile organelles of cardiomyocytes, from cultured cells will confirm my previous computational work and give further insight into nucleotide-binding pocket coordination while Brownian dynamics will reveal changes in actomyosin interactions. A multifaceted analysis of the R369Q mutation from computational and experimental approaches will consolidate the mechanism of the mutation, providing a foundation for design of a therapeutic to ameliorate contractile dysfunction.