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Proteins embedded in cell membranes translate a broad range of environmental cues---including the presence of nutrients, drugs, ions and photons---into molecular signals to induce appropriate cellular responses. Membrane proteins thus represent a control panel of the cell and constitute key drug targets for the treatment of a range of diseases. Designing medications to effectively modulate these proteins, however, remains exceedingly challenging and would benefit dramatically from an atomic-level understanding of how these proteins work. Here, I have used molecular dynamics (MD) simulations---which describe how every atom in a biological system evolves with high resolution in space and time---to reveal functional mechanisms for transporters and receptors, two essential classes of membrane proteins. This approach allowed us to address several long-standing questions in molecular biology. For example, we captured the complete process of substrate translocation through an alternating-access membrane transporter. These simulations, which revealed structural rearrangements in the protein that control substrate passage across the membrane as well as the driving forces underlying those transitions, suggest a structural foundation for the design of highly specific and more efficacious transporter-targeted medications. We also revealed the mechanism by which G protein--coupled receptors stimulate arrestins, intracellular regulators of cell signaling. By identifying atomic-level interactions at the GPCR--arrestin interface that drive arrestin activation, we provide a framework for designing drugs that could selectively block or stimulate arrestin signaling, thereby reducing unwanted side effects. In each study, we worked closely with our experimental collaborators to validate predictions derived from our computational results.

The brain is a remarkably complex structure, composed of hundreds of neurons in simple organisms and up to hundreds of billions of neurons in large mammals. The recent advent of optically-modulated, molecular tools for neuroscience ('optogenetics') has allowed unprecedented access to simultaneously modulate and observe the activity of hundreds of genetically-defined neurons with millisecond resolution. However, while optogenetics has enabled rapid advances in neuroscience, this powerful toolset remains constrained by a limited mechanistic understanding of light-gated molecules, including channelrhodopsins (ChRs). Here, I describe my efforts to understand structural and dynamical mechanisms of ChRs, using three complimentary approaches. First, to extend the available high-resolution ChR structural insights, I employed X-ray crystallography to determine the structures of natural and designed anion-conducting ChRs (ACRs). Next, I used a combination of these atomic-resolution structures, molecular dynamics (MD) computational simulation, and in vitro electrophysiology to assess functional dynamics of ACRs, leading to the identification of a variant with improved channel-closing kinetics. Finally, I used structure-guided genome mining, whole-cell patch clamp electrophysiology, and two-photon imaging to identify and characterize a new red-shifted excitatory channelrhodopsin with large photocurrents and high light sensitivity. Taken together, this work provides a framework for the engineering and discovery of better optogenetic tools and lays a foundation for future studies of channelrhodopsin biology

All cells are surrounded by a lipid bilayer that prevents many chemical species from crossing including key biomolecules. Transport proteins facilitate the passage of a wide range of molecules across the cell membrane. Molecular details of transport protein function, such as mechanisms of substrate specificity, gating, and conformational change can be gleaned from high-resolution structures. To this end, I utilized structural approaches to develop models for different transport mechanisms. In the first section, I focus on a family of sugar transporters called SWEETs. SWEETs play central roles in plant biology and are found across all lifeforms including humans. Their prokaryotic homologs, SemiSWEETs, are amongst the smallest natural transporters. I focused on SemiSWEET as a representative system for SWEET function and as a model for other more complex transporters. High resolution structures of SemiSWEET in all major conformational states revealed the movement of hydrophobic gate residues controls the accessibility of the substrate-binding binding pocket. A glucose-bound structure revealed the substrate recognition residues. Structural observations were corroborated by mutagenesis, sugar uptake experiments, and unguided molecular dynamic simulations. The simulations faithfully recapitulate the experimental structures while demonstrating that the substrate doesn't induce conformational changes, but instead takes a "free ride" through a stochastically fluctuating transporter. In addition to the characterization of SemiSWEET, I developed more general protein engineering strategies to facilitate structural studies. The final section details the molecular structure of the mitochondrial calcium uniporter, which required a transmembrane-targeting nanobody in order to achieve the highest resolution crystal structure.

G protein coupled receptors (GPCRs) are a class of cell-surface receptors that mediate complex cellular responses to a myriad of physiological stimuli, from photons and neurotransmitters, to hormones, peptides, and even full proteins. GPCR signaling underlies almost all of physiology; this central importance to human health and disease is reflected in the fact that approximately 30% of all FDA approved drugs target GPCRs. Ligand action at GPCRs mediates intracellular signaling through heterotrimeric G proteins, as well as G protein-independent pathways. Over the past decade, a structural framework has allowed for a more precise understanding of ligand-mediated activation in rhodopsin-like GPCRs, as well as the molecular mechanism for GPCR signaling through the stimulatory G protein, Gs. My work expands this structural understanding of GPCR activation and signaling by exploring two novel signaling systems in the GPCR family for which structural information is lacking. First, I describe work on the structure of a peptide-activated mu-opioid receptor (muOR) in complex with the inhibitory G protein, Gi. As signaling through Gi is responsible for the beneficial aspects of opioids, the structure of this complex can help guide the design and discovery of novel therapeutics with reduced liabilities. I then show the structural mechanism of activation in a family C GPCR, the metabotropic glutamate receptor 5 (mGlu5). Family C receptors are unusual in that, as well as the GPCR-defining 7-transmembrane (7TM) domain, they possess relatively large amino-terminal extracellular domains (ECDs) that form obligate dimers and contain the orthosteric ligand-binding sites. Taken together, this work presents novel insights into GPCR activation and signaling.

G protein-coupled receptors (GPCRs) constitute the largest single family of transmembrane receptors in humans, and play important roles in the regulation of normal human physiology and the pathogenesis of disease. The muscarinic acetylcholine receptors are a subfamily of GPCRs, and mediate the parasympathetic effects of acetylcholine, in addition to playing critical roles in cognition, memory, and maintenance of metabolic homeostasis. The muscarinic receptors have long served as an important model system for understanding GPCR function in general. Moreover, muscarinic receptors are important targets in the treatment of disease, and are also responsible for many of the side effects of commonly used therapeutic drugs targeting other receptors. To better understand these important receptors, I employed X-ray crystallography to determine the structures of the M2 and M3 muscarinic receptors in inactive, antagonist-bound conformations. Next, I used these structures for computational ligand screening, leading to the identification of over a dozen new muscarinic ligands. Finally, I determined the structure of the M2 muscarinic receptor in an active conformation stabilized by an antibody fragment. Similarly, a second structure of the M2 receptor bound to a positive allosteric modulator was resolved, offering structural insights into the allosteric modulation of GPCRs by drug-like molecules. Taken together, this work provides a framework for the interpretation of the extensive and growing body of biological and pharmacological data regarding muscarinic receptor function, and lays a foundation for future studies of muscarinic receptor biology.

This dissertation covers work discussed in the following papers: "Spatial Graph Convolutions for Drug Discovery" describes new deep neural network architectures for modeling drug-receptor interactions. We argue that the future of predicting the interactions between a drug and its prospective target demands more than simply applying deep learning algorithms from other domains, like vision and natural language, to molecules. "Machine Learning Harnesses Molecular Dynamics to Discover New Opioid Chemotypes" describes an algorithm that leverages protein motion to enrich the search for active molecules. We then applied the method to find a new chemical scaffold that we experimentally verified is an agonist for the μ Opioid Receptor. "Kinetic Machine Learning Unravels Ligand-Directed Conformational Change of Opioid Receptor" describes differential pathways of deactivation and differential conformational states sampled by the μ Opioid Receptor in response to different opioid ligands.

G protein-coupled receptors (GPCRs) are transmembrane proteins that mediate complex cellular responses to hormones and neurotransmitters. GPCRs can activate many signaling pathways, either through interactions with heterotrimeric G proteins or through G protein-independent pathways. The function of GPCRs can be modulated by a variety of ligands with a broad range of efficacies, often in a signaling pathway specific manner. Understanding this complex signaling behavior requires insight into the molecular mechanisms of GPCR function. Recent advances in GPCR crystallography have elucidated the structure of a few prototypical receptors, rhodopsin and the β2 adrenergic receptor (β2AR), in both inactive and active conformations. Here, I describe my efforts to understand the structure and dynamics of GPCR activation. To extend the available model systems beyond rhodopsin and the β2AR, I describe the inactive-state structures of the μ and δ opioid receptors as well as a recently determined structure of an activated, agonist-bound μ opioid receptor. I also describe active state structures of the M2 muscarinic receptor and higher resolution structures of the activated β2AR bound its endogenous hormone adrenaline. Finally, I describe a set of studies utilizing 19F-fluorine nuclear magnetic resonance (NMR) and double electron-electron resonance spectroscopy to assess the conformational dynamics of β2AR activation. Together, these studies establish the conformational complexity associated with GPCR activation and how this structural plasticity is likely responsible for the broad versatility of GPCR signaling.

Synthetic biology is changing the way we engineer living systems by providing frameworks to manage information flow and designed system complexity. Applying these concepts to engineer useful input-output devices in human cells has paved the way for engineered receptor technologies. A particular subset of these, Chimeric Antigen Receptors (CARs), are FDA approved for treat cancer. CAR therapy functions by enabling engineered T-cells to sense a surface marker (or cue) on cancer and convert that into an anti-tumoral program. Yet, this technology cannot interpret soluble markers that can be hallmarks of the disease, especially those from G-protein coupled receptor (GPCR) signaling systems. The CAR technology also cannot execute arbitrary gene programs to modulate either tumor cell behavior, or host T cell behavior. In this thesis, to bridge these technological gaps, I develop a new molecular input-output device, CRISPR-ChaCha. The technology leverages the ligand sensing diversity of GPCRs with the genome targeting flexibility of CRISPR-Cas systems. I first determine a functional architecture to fuse GPCR signaling proteins and CRISPR-Cas activators. I then show that the CRISPR ChaCha is dose-dependent, reversible, and can activate multiple endogenous genes simultaneously in response to extracellular ligands. The system displays a high degree of modularity, which is the ability to swap components and maintain function. I adopt this modular design to diverse GPCRs that sense a broad spectrum of ligands and to function with an additional CRISPR-Cas protein. I also make perturbations to device function to derive CRISPR-ChaCha design rules, to later build next generation devices with little optimization required. We hope that this flexible input-output device can be used for "smart" therapeutics, and rational engineering of cellular behavior.

A long-standing objective of psychiatry has been the ability to both control and record the activity of precisely-defined populations of brain cells on the millisecond timescale most relevant for neural computation. Recent advances bring that goal increasingly near by leveraging the genetically-precise techniques of molecular biology with the high-speed, multiplexed command afforded by optical technologies to introduce and utilize light-sensitive neural activity control integrated with fast neural circuit imaging. In this thesis, I present exemplars of these technological advances and demonstrate their utility in illuminating the neural circuit basis of behaviors relevant to understanding psychiatric disease. I first show how fast neural circuit imaging may be integrated with optical neural control tools to develop insight into the role of genetically, developmentally, or projection defined populations of brain cells in mediating circuit-level physiological changes. I then demonstrate computational methods to analyze the resultant imaging data and apply fast circuit imaging to delineate links between hippocampal physiology and behavior in an animal model of depression. Finally, I present the development of a novel class of optically-activated, genetically-targetable control tools that permit optical control of G-protein coupled intracellular signaling; and the use of these molecular devices to determine causal roles of neuromodulatory inputs in reward processing. The development of these and similar optical modalities further improves the precision of questions addressable by the neuroscientist, and potentially the extent of disease treatable by the clinician.

Molecular dynamics (MD) simulation offers both high spatial and time resolution into biological processes at an all-atom level, but presents many unique computational challenges in terms of both system setup and compute time. To address the former, I introduce a software package, Dabble, that simplifies system building for MD simulation in a way that supports all commonly used force fields and simulation programs. To increase the accessibility of observing protein-ligand binding in simulations, I developed an adaptive sampling method that guides simulations towards interesting regions of protein-ligand conformational space while requiring no prior knowledge of binding pose or site. Together, these two computational methods improve the ability of researchers to use MD simulation for examining biological processes.

Immune-based therapies for cancer are powerful, lasting, and generally less toxic than most other cancer treatment paradigms. Consequently, the development of new immunotherapeutic agents and the study of the interplay between tumors and the immune system have emerged as central lines of research for this nascent field of medicine. Here, I describe my efforts to improve an existing cancer immunotherapy (Interleukin-2), to study an experimental immunotherapeutic agent (Interleukin-15), and to generate novel protein therapeutics against an emerging target of cancer immune evasion (CD47). These studies highlight a structure- and mechanism-based approach to protein engineering in the development of next-generation cancer immunotherapies.

G protein coupled receptors (GPCRs) are seven transmembrane proteins that are expressed in all eukaryotic cells and tissues. These receptors play key roles in human physiology and disease. The goal of my work is to understand the molecular detail of ligand recognition by GPCRs, and how this process leads to conformational changes that manifest as cellular signaling. Meeting this goal will advance our knowledge of membrane protein biology. It will also reveal structural targets and physicochemical logic to aid pharmaceutical design. The age of GPCR structural biology recently arrived with the first x-ray structures of rhodopsin and the beta2 adrenergic receptor (beta2AR). However, membrane proteins are constantly fluctuating entities. Dynamic behavior is intrinsic to their function. As such, static x-ray structures alone are inadequate. Herein, I develop biophysical techniques to study these dynamic receptors. Using NMR spectroscopy, I characterize conformational changes in the extracellular region of the beta2AR, a surface rich with potential for drug design. I also explore the signaling properties of monomeric GPCRs and conformational changes of other macromolecules using single-molecule fluorescence. While many questions about GPCRs remain, I hope this work is a small step towards understanding these important, fascinating, and beautiful molecules.

G protein coupled receptor proteins (GPCRs) couple extracellular soluble ligand binding to intracellular signaling pathway activation. GPCRs are excellent drug targets due to their positioning at the plasma membrane upstream of signaling cascades, and due to their ability to respond to ligand binding with a range of signaling outputs. Crystallography has revealed the structure of drugs bound to the inactive and active state GPCRs at high resolution; each crystal structure represents a single, low-energy GPCR conformation. Crystal structures have also defined the canonical activation mechanism for GPCRs as an opening up of the intracellular surface; for Family A GPCRs, the intracellular portion of transmembrane helix 6 (TM6) undergoes the largest conformational change upon ligand binding. Here I present the design and development of two novel fusion proteins for GPCR crystallography. Crystal structures of the M3 muscarinic receptor fused to both novel crystallization aids improved the resolution of the overall structure and extended the view of residues comprising TM6. In addition to the states seen by crystallography, recent spectroscopy studies revealed that GPCRs sample a wide variety of conformations. This raises the question of when and whether high-energy (non-crystallographic) conformations are relevant for GPCR function. In this work, I both employ and validate a high-pressure electron paramagnetic resonance (EPR) spectroscopy technique to understand the basal and ligand activation of an archetypal GPCR, the Beta-2 adrenergic receptor (β2AR). The studies demonstrate a pre-existing equilibrium between inactive and active receptor states, providing a structure-based explanation for the observed phenomenon of basal activity. Clinically, inverse agonists are used to inhibit basal activity of GPCRs, and these high-pressure studies also reveal a structural mechanism for inverse agonists: they inhibit the outward movement of TM6. Studies of β2AR endogenous and synthetic agonists under ambient and pressurized conditions reveal a distinct conformational profile for each agonist. These conformational differences may be responsible for different ligand efficacies towards two signaling pathways downstream of GPCRs: arrestin-mediated versus G-protein-mediated signaling. Overall, these studies provide further support for a general mechanism for GPCR activation, conformational selection. The ability to fine-tune drug efficacy is the next frontier in GPCR drug discovery. To this end, I contributed to a collaborative drug discovery project to find novel β2AR allosteric ligands by docking to a hypothetical allosteric binding site, at a distinct location from where endogenous ligands bind. We built upon the principles of conformational selection, searching for negative modulators by docking to the inactive crystal structure, and finding positive modulators from active-state structure docking. Some of the new allosteric ligands discovered have signal bias properties, targeting arrestin over G-protein coupling. Though the underlying mechanisms of ligand bias are difficult to assess by most physiologic and biophysical methods, EPR spectroscopy revealed subtle differences in the conformational ensemble, which may correspond to arrestin versus G protein-specific drug effects.

Proteins are macromolecular nanomachines that perform a wide variety of essential functions in living organisms. Distinct types of proteins in the cell serve as molecular sensors and signalers, sunlight-harvesting antennas and transducers, molecular motors for transport and metabolic energy storage, and oxidizers and reducers of physiological metal ions, to name a few. To achieve these complex functions, proteins are not static building blocks, but instead adopt multiple conformations in distinct functional states. These functions are inherently dynamic, meaning that methods capable of resolving dynamic behavior are necessary to fully elucidate protein function. Many bulk fluorescence methods have been used to study proteins by averaging together the signals from many copies of the same protein. However, such methods fail to capture distributions in protein conformations (e.g. mixtures of active and inactive states) and unsynchronized dynamics among these conformations (e.g. transition rates from inactive to active states under various conditions). Single-molecule fluorescence spectroscopy of proteins, on the other hand, allows direct observation of distributions and dynamics by watching only one protein at a time. In particular, a special device known as the Anti-Brownian ELectrokinetic (ABEL) trap can hold single fluorescently labeled proteins in solution for several seconds of spectroscopic observation without surface attachment, encapsulation, or the use of large beads. The ABEL trap combines fluorescence-based position estimation obtained by scanning a laser spot with the application of electrokinetic feedback forces to counter the Brownian motion of single proteins, one at a time. In this Dissertation I will describe my use of the ABEL trap technique to study dynamics of a variety of biomolecules, with emphasis on two proteins: the [beta]2-adrenergic receptor ([beta]2AR), an essential cellular signaling protein, and the peridinin-chlorophyll-protein (PCP), a sunlight-harvesting pigment-protein complex found in algae. In [beta]2AR, I observed a shift in protein conformation and in time scales of protein dynamics upon binding of an activating drug. In PCP, I observed two distinct classes of conformational change, indicating light-induced conformational flexibility, which may play a physiological role. Ongoing projects include resolving conformational substeps in FoF1 ATP synthase and measuring electron transfer kinetics of the multicopper oxidase Fet3p.

In this thesis, I mainly worked on the structural and functional characterization of a mitochondrial calcium channel named MCU. Mitochondrial calcium plays critical roles in a wide range of fundamental cellular processes, including controlling the rate of ATP production, regulating the initiation of cell death and shaping cytosolic calcium signaling. Since fifty years ago when it was first demonstrated that fully energized mitochondria can rapidly load up calcium ions (Ca2+), the machinery behind this process has been extensively explored. This uptake is mediated by a highly selective calcium channel called the mitochondrial calcium uniporter (MCU), which resides on the inner mitochondrial membrane. The molecular identity of the uniporter was only uncovered relatively recently. MCU bears no discernable sequence similarity to other known channels and represents a new class in ion channels with its unique selectivity and conductance properties. In this thesis, I used both X-ray crystallography and single-particle cryo-electron microscopy to determine the structures of MCU from two species containing all domains, and I established rapid and efficient functional characterization platforms in cells and in liposomes. Unexpectedly, the stoichiometry, overall architecture, and local structural details of the new structures differed markedly from the NMR cMCU structure. The physiological relevance of those structures was corroborated by the observation of a consistent architecture across species and chemical environments, and by the systematical functional assays. Structural and functional characterizations provided insights into Ca2+ coordination, selectivity, and permeation, establishing a framework for understanding the mechanism of MCU function.