First-Principles-Based Simulations for G Protein-Coupled Receptor Activation and for Large-Scale Nonadiabatic Electron Dynamics

This thesis focuses on simulating large molecular systems within and beyond the Born-Oppenheimer framework from first principles. Two approaches have been developed for very different but important applications. The first one is a hybrid method based on classical force fields that predicts the high-energy ensemble of three-dimensional structures of a class of proteins critical in human physiology: the G protein-coupled receptors (GPCRs). GPCRs' functions rely on their activation marked by a series of conformational changes related to binding of certain ligands, but the short of experimental structures has hampered the study of their activation mechanism and drug discovery. Our method, combining homology modeling, hierarchical sampling, and nanosecond-scale molecular dynamics, is one of the very few computational methods that can predict their active-state conformations and is one of the most computationally inexpensive. It enables the conformational landscape and the first quantitative energy landscape of GPCR activation to be efficiently mapped out. This method, named ActiveGEnSeMBLE, allows the inactive- and active-state conformations of GPCRs without an experimental structure to be systematically predicted. We have validated the method with one of the most well-studied GPCRs, human &#946;2 adrenergic receptor (h&#946;2AR), and applied the method on a GPCR without an experimental structure, human somatostatin receptor 5 (hSSTR5). Insights on GPCR activation as well as structure prediction methods are discussed. The second one is a semiclassical approach for large-scale nonadiabatic dynamics of condensed systems in extreme conditions, termed Gaussian Hartree Approximated Quantum Mechanics (GHA-QM). Many nonadiabatic processes related to important applications (e.g. renewable energy) happen in large systems, but existing excited state dynamics methods are too computationally demanding for their long timescale simulations. GHA-QM is based on the electron force field (eFF) framework where we model electrons as Gaussian wavepackets and nuclei as classical point charges, and obtain a simplified solution to the time-dependent Schrödinger equation as the equation of motion. We employ a force field philosophy approximating the total energy as a sum of electronic kinetic energies, electrostatic energies and a Pauli correction, which corrects for the lack of explicit antisymmetry in the wavefunctions. New designs of the Pauli potential and preliminary results on hydrogen systems are discussed. With the new development, we hope to improve the accuracy and range of applications of eFF to simulate the nonadiabatic dynamics of hundreds of thousands of electrons on nanosecond timescale.</p

Conformational and Thermodynamic Landscape of GPCR Activation from Theory and Computation

We present a hybrid computational methodology to predict multiple energetically accessible conformations for G protein-coupled receptors (GPCRs) that might play a role in binding to ligands and different signaling partners. To our knowledge, this method, termed ActiveGEnSeMBLE, enables the first quantitative energy profile for GPCR activation that is consistent with the qualitative profile deduced from experiments. ActiveGEnSeMBLE starts with a systematic coarse grid sampling of helix tilts/rotations (∼13 trillion transmembrane-domain conformations) and selects the conformational landscape based on energy. This profile identifies multiple potential active-state energy wells, with the TM3–TM6 intracellular distance as an approximate activation coordinate. These energy wells are then sampled locally using a finer grid to find locally minimized conformation in each energy well. We validate this strategy using the inactive and active experimental structures of β_2 adrenergic receptor (hβ_2AR) and M2 muscarinic acetylcholine receptor. Structures of membrane-embedded hβ_2AR along its activation coordinate are subjected to molecular-dynamics simulations for relaxation and interaction energy analysis to generate a quantitative energy landscape for hβ_2AR activation. This landscape reveals several metastable states along this coordinate, indicating that for hβ_2AR, the agonist alone is not enough to stabilize the active state and that the G protein is necessary, consistent with experimental observations. The method’s application to somatostatin receptor SSTR5 (no experimental structure available) shows that to predict an active conformation it is better to start from an inactive structure template based on a close homolog than to start from an active template based on a distant homolog. The energy landscape for hSSTR5 activation is consistent with hβ_2AR in the role of the G protein. These results demonstrate the utility of the ActiveGEnSeMBLE method for predicting multiple conformations along the pathways for activating GPCRs and the corresponding energy landscapes, thereby providing detailed structural insights into the initial molecular events of GPCR function that are not easily accessible by experiments

Electronic Structures of Group 9 Metallocorroles with Axial Ammines

The electronic structures of metallocorroles (tpfc)M(NH_3)_2 and (tfc)M(NH_3)_2 (tpfc is the trianion of 5,10,15-(tris)pentafluorophenylcorrole, tfc is the trianion of 5,10,15-trifluorocorrole, and M = Co, Rh, Ir) have been computed using first principles quantum mechanics [B3LYP flavor of Density Functional Theory (DFT) with Poisson−Boltzmann continuum solvation]. The geometry was optimized for both the neutral systems (formal M^(III) oxidation state) and the one-electron oxidized systems (formally M^(IV)). As expected, the M^(III) systems have a closed shell d^6 configuration; for all three metals, the one-electron oxidation was calculated to occur from a ligand-based orbital (highest occupied molecular orbital (HOMO) of B_1 symmetry). The ground state of the formal M^(IV) system has M^(III)-Cπ character, indicating that the metal remains d^6, with the hole in the corrole π system. As a result the calculated M^(IV/III) reduction potentials are quite similar (0.64, 0.67, and 0.56 V vs SCE for M = Ir, Rh and Co, respectively), whereas the differences would have been large for purely metal-based oxidations. Vertically excited states with substantial metal character are well separated from the ground state in one-electron-oxidized cobalt (0.27 eV) and rhodium (0.24 eV) corroles, but become closer in energy in the iridium (0.15 eV) analogues. The exact splittings depend on the chosen functional and basis set combination and vary by ~0.1 eV

SRIBO: An Efficient and Resilient Single-Range and Inertia Based Odometry for Flying Robots

Positioning with one inertial measurement unit and one ranging sensor is commonly thought to be feasible only when trajectories are in certain patterns ensuring observability. For this reason, to pursue observable patterns, it is required either exciting the trajectory or searching key nodes in a long interval, which is commonly highly nonlinear and may also lack resilience. Therefore, such a positioning approach is still not widely accepted in real-world applications. To address this issue, this work first investigates the dissipative nature of flying robots considering aerial drag effects and re-formulates the corresponding positioning problem, which guarantees observability almost surely. On this basis, a dimension-reduced wriggling estimator is proposed accordingly. This estimator slides the estimation horizon in a stepping manner, and output matrices can be approximately evaluated based on the historical estimation sequence. The computational complexity is then further reduced via a dimension-reduction approach using polynomial fittings. In this way, the states of robots can be estimated via linear programming in a sufficiently long interval, and the degree of observability is thereby further enhanced because an adequate redundancy of measurements is available for each estimation. Subsequently, the estimator's convergence and numerical stability are proven theoretically. Finally, both indoor and outdoor experiments verify that the proposed estimator can achieve decimeter-level precision at hundreds of hertz per second, and it is resilient to sensors' failures. Hopefully, this study can provide a new practical approach for self-localization as well as relative positioning of cooperative agents with low-cost and lightweight sensors

Acoustic emission source location method and experimental verification for structures containing unknown empty areas

Acoustic emission (AE) localization plays an important role in the prediction and control of potential hazardous sources in complex structures. However, existing location methods have less discussion on the presence of unknown empty areas. This paper proposes an AE source location method for structures containing unknown empty areas (SUEA). Firstly, this method identifies the shape, size, and location of empty areas in the unknown region by exciting the active AE sources and using the collected AE arrivals. Then, the unknown AE source can be located considering the identified empty areas. The lead break experiments were performed to verify the effectiveness and accuracy of the proposed method. Five specimens were selected containing empty areas with different positions, shapes, and sizes. Results show the average location accuracy of the SUEA increased by 78% compared to the results of the existing method. It can provide a more accurate solution for locating AE sources in complex structures containing unknown empty areas such as tunnels, bridges, railroads, and caves in practical engineering

Computational predictions of corroles as a class of Hsp90 inhibitors

Corroles have been shown experimentally to cause cell cycle arrest, and there is some evidence that this might be attributed to an inhibitory effect of corroles on Heat shock protein 90 (Hsp90), which is known to play a vital role in cancer cell proliferation. In this study, we used molecular dynamics to examine the interaction of gallium corroles with Hsp90, and found that they can bind preferentially to the ATP-binding N-terminal site. We also found that structural variations of the corrole ring can influence the binding energies and affinities of the corrole to Hsp90. We predict that both the biscarboxylated corrole (4-Ga) and a proposed 3,17-bis-sulfonated corrole (7-Ga) are promising alternatives to Ga(III) 5,10,15-tris(pentafluorophenyl)-2,17-bis(sulfonic acid)-corrole (1-Ga) as anti-cancer agents

The Predicted Ensemble of Low-Energy Conformations of Human Somatostatin Receptor Subtype 5 and the Binding of Antagonists

Human somatostatin receptor subtype 5 (hSSTR5) regulates cell proliferation and hormone secretion. However, the identification of effective therapeutic small-molecule ligands is impeded because experimental structures are not available for any SSTR subtypes. Here, we predict the ensemble of low-energy 3D structures of hSSTR5 using a modified GPCR Ensemble of Structures in Membrane BiLayer Environment (GEnSeMBLE) complete sampling computational method. We find that this conformational ensemble displays most interhelical interactions conserved in class A G protein-coupled receptors (GPCRs) plus seven additional interactions (e.g., Y2.43–D3.49, T3.38–S4.53, K5.64–Y3.51) likely conserved among SSTRs. We then predicted the binding sites for a series of five known antagonists, leading to predicted binding energies consistent with experimental results reported in the literature. Molecular dynamics (MD) simulation of 50 ns in explicit water and lipid retained the predicted ligand-bound structure and formed new interaction patterns (e.g. R3.50–T6.34) consistent with the inactive μ-opioid receptor X-ray structure. We suggest more than six mutations for experimental validation of our prediction. The final predicted receptor conformations and antagonist binding sites provide valuable insights for designing new small-molecule drugs targeting SSTRs

A Kinetic Pressure Effect on Calcite Dissolution in Seawater

This study provides laboratory data of calcite dissolution rate as a function of seawater undersaturation state (1-Ω) under variable pressure. ^(13)C-labeled calcite was dissolved in unlabeled seawater and the evolving δ^(13)C composition of the fluid was monitored over time to evaluate the dissolution rate. Results show that dissolution rates are enhanced by a factor of 2-4 at 700 dbar compared to dissolution at the same Ω under ambient pressure (10 dbar). This dissolution rate enhancement under pressure applies over an Ω range of 0.65 to 1 between 10 dbar and 700 dbar. Above 700 dbar (up to 2500 dbar), dissolution rates become independent of pressure. The observed enhancement is well beyond the uncertainty associated with the thermodynamic properties of calcite under pressure (partial molar volume ΔV), and thus should be interpreted as a kinetic pressure effect on calcite dissolution. Dissolution at ambient pressure and higher pressures yield non-linear dissolution kinetics, the pressure effect does not significantly change the reaction order n in Rate = k(1-Ω^)n, which is shown to vary from 3.1±0.3 to 3.8±0.5 from 10 dbar to 700 dbar over Ω = 0.65 to 0.9. Furthermore, two different dissolution mechanisms are indicated by a discontinuity in the rate-undersaturation relationship, and seen at both ambient and higher pressures. The discontinuity, Ω_(critical) = 0.87±0.05 and 0.90±0.03 at 10 dbar and 1050 dbar respectively, are similar within error. The reaction order, n, at Ω > 0.9 is 0.47±0.27 and 0.46±0.15 at 10 dbar and 700 dbar respectively. This Ω_(critical) is considered to be the threshold between step retreat dissolution and defect-assisted dissolution. The kinetic enhancement of dissolution rate at higher pressures is related to a decrease in the interfacial energy barrier at dissolution sites. The impact of pressure on the calcite dissolution kinetics implies that sinking particles would dissolve at shallower depth than previously thought

Phase diagrams on composition-spread Fey_yTe1−x_{1-x}Sex_x films

Fe$_y$Te$_{1-x}$Se$_x$, an archetypical iron-based high-temperature superconductor with a simple structure but rich physical properties, has attracted lots of attention because the two end compositions, Se content $x = 0$ and 1, exhibit antiferromagnetism and nematicity, respectively, making it an ideal candidate for studying their interactions with superconductivity. However, what is clearly lacking to date is a complete phase diagram of Fe$_y$Te$_{1-x}$Se$_x$ as functions of its chemical compositions since phase separation usually occurs from $x\sim 0.6$ to 0.9 in bulk crystals. Moreover, fine control of its composition is experimentally challenging because both Te and Se are volatile elements. Here we establish a complete phase diagram of Fe$_y$Te$_{1-x}$Se$_x$, achieved by high-throughput film synthesis and characterization techniques. An advanced combinatorial synthesis process enables us to fabricate an epitaxial composition-spread Fe$_y$Te$_{1-x}$Se$_x$ film encompassing the entire Se content $x$ from 0 to 1 on a single piece of CaF$_2$ substrate. The micro-region composition analysis and X-ray diffraction show a successful continuous tuning of chemical compositions and lattice parameters, respectively. The micro-scale pattern technique allows the mapping of electrical transport properties as a function of relative Se content with an unprecedented resolution of 0.0074. Combining with the spin patterns in literature, we build a detailed phase diagram that can unify the electronic and magnetic properties of Fe$_y$Te$_{1-x}$Se$_x$. Our composition-spread Fe$_y$Te$_{1-x}$Se$_x$ films, overcoming the challenges of phase separation and precise control of chemical compositions, provide an ideal platform for studying the relationship between superconductivity and magnetism.Comment: 13 pages,5 figures and Supplementary Material 3 pages,3 figure