The cell-of-origin of high grade serous ovarian carcinoma (HGSOC) remains controversial, with fallopian tube epithelium (FTE) and ovarian surface epithelium (OSE) both considered candidates. Here, by ...using genetically engineered mouse models and organoids, we assessed the tumor-forming properties of FTE and OSE harboring the same oncogenic abnormalities. Combined RB family inactivation and Tp53 mutation in Pax8 + FTE caused Serous Tubal Intraepithelial Carcinoma (STIC), which metastasized rapidly to the ovarian surface. These events were recapitulated by orthotopic injection of mutant FTE organoids. Engineering the same genetic lesions into Lgr5 + OSE or OSE-derived organoids also caused metastatic HGSOC, although with longer latency and lower penetrance. FTE- and OSE-derived tumors had distinct transcriptomes, and comparative transcriptomics and genomics suggest that human HGSOC arises from both cell types. Finally, FTE- and OSE-derived organoids exhibited differential chemosensitivity. Our results comport with a dualistic origin for HGSOC and suggest that the cell-of-origin might influence therapeutic response.
Spikes in the time-derivative coupling (TDC) near surface crossings make the accurate integration of the time-dependent Schrödinger equation in nonadiabatic molecular dynamics simulations a ...challenge. To address this issue, we present an approximation to the TDC based on a norm-preserving interpolation (NPI) of the adiabatic electronic wave functions within each time step. We apply NPI and two other schemes for computing the TDC in numerical simulations of the Landau–Zener model, comparing the simulated transfer probabilities to the exact solution. Though NPI does not require the analytical calculation of nonadiabatic coupling matrix elements, it consistently yields unsigned population transfer probability errors of ∼0.001, whereas analytical calculation of the TDC yields errors of 0.0–1.0 depending on the time step, the offset of the maximum in the TDC from the beginning of the time step, and the coupling strength. The approximation of Hammes-Schiffer and Tully yields errors intermediate between NPI and the analytical scheme.
The standard model for photoinduced cis-trans isomerization about carbon double bonds is framed in terms of two electronic states and a one-dimensional reaction coordinate. We review recent work that ...suggests that a minimal picture of the reaction mechanism requires the consideration of at least two molecular coordinates and three electronic states. In this chapter, we emphasize the role of conical intersections and charge transfer in the photoisomerization mechanism.
The calculation of radial distribution functions (RDFs) from molecular dynamics trajectory data is a common and computationally expensive analysis task. The rate limiting step in the calculation of ...the RDF is building a histogram of the distance between atom pairs in each trajectory frame. Here we present an implementation of this histogramming scheme for multiple graphics processing units (GPUs). The algorithm features a tiling scheme to maximize the reuse of data at the fastest levels of the GPU’s memory hierarchy and dynamic load balancing to allow high performance on heterogeneous configurations of GPUs. Several versions of the RDF algorithm are presented, utilizing the specific hardware features found on different generations of GPUs. We take advantage of larger shared memory and atomic memory operations available on state-of-the-art GPUs to accelerate the code significantly. The use of atomic memory operations allows the fast, limited-capacity on-chip memory to be used much more efficiently, resulting in a fivefold increase in performance compared to the version of the algorithm without atomic operations. The ultimate version of the algorithm running in parallel on four NVIDIA GeForce GTX 480 (Fermi) GPUs was found to be 92 times faster than a multithreaded implementation running on an Intel Xeon 5550 CPU. On this multi-GPU hardware, the RDF between two selections of 1,000,000 atoms each can be calculated in 26.9
s per frame. The multi-GPU RDF algorithms described here are implemented in VMD, a widely used and freely available software package for molecular dynamics visualization and analysis.
Abstract
Roaming mechanisms, involving the brief generation of a neutral atom or molecule that stays in the vicinity before reacting with the remaining atoms of the precursor, are providing valuable ...insights into previously unexplained chemical reactions. Here, the mechanistic details and femtosecond time-resolved dynamics of H
3
+
formation from a series of alcohols with varying primary carbon chain lengths are obtained through a combination of strong-field laser excitation studies and ab initio molecular dynamics calculations. For small alcohols, four distinct pathways involving hydrogen migration and H
2
roaming prior to H
3
+
formation are uncovered. Despite the increased number of hydrogens and possible combinations leading to H
3
+
formation, the yield decreases as the carbon chain length increases. The fundamental mechanistic findings presented here explore the formation of H
3
+
, the most important ion in interstellar chemistry, through H
2
roaming occurring in ionic species.
We introduce an interface between PySpawn, a simulation package to run ab initio multiple spawning (AIMS) nonadiabatic dynamics, and OpenMolcas, a software package to perform multiconfigurational ...perturbations theory (CASPT2) electronic structure calculations. Our interface allows us to exploit all the functionalities of the two codes: the modular and efficient Python implementation of the AIMS algorithm and the extensive analysis tools offered by PySpawn, with the cutting-edge implementation of CASPT2 equations in OpenMolcas, including the recently introduced analytical gradients and different flavors. Both are fully open-source and free of charge, making the following implementation unique in the current plethora of software for nonadiabatic dynamics. This represents an important step toward a wider application of AIMS-based nonadiabatic dynamics combined with high-accuracy excited-state calculations. The importance and the need for such an implementation are demonstrated by application to the ultrafast relaxation of fulvene from S1 to S0, which is drastically affected by the potential energy surface on which the nuclear wavepacket is propagated. Additionally, the decay is influenced by the CASPT2 flavor adopted, posing interesting questions in the choice of one over the other and opening the door to deeper studies on the effect of CASPT2 formulations in nonadiabatic dynamics.We introduce an interface between PySpawn, a simulation package to run ab initio multiple spawning (AIMS) nonadiabatic dynamics, and OpenMolcas, a software package to perform multiconfigurational perturbations theory (CASPT2) electronic structure calculations. Our interface allows us to exploit all the functionalities of the two codes: the modular and efficient Python implementation of the AIMS algorithm and the extensive analysis tools offered by PySpawn, with the cutting-edge implementation of CASPT2 equations in OpenMolcas, including the recently introduced analytical gradients and different flavors. Both are fully open-source and free of charge, making the following implementation unique in the current plethora of software for nonadiabatic dynamics. This represents an important step toward a wider application of AIMS-based nonadiabatic dynamics combined with high-accuracy excited-state calculations. The importance and the need for such an implementation are demonstrated by application to the ultrafast relaxation of fulvene from S1 to S0, which is drastically affected by the potential energy surface on which the nuclear wavepacket is propagated. Additionally, the decay is influenced by the CASPT2 flavor adopted, posing interesting questions in the choice of one over the other and opening the door to deeper studies on the effect of CASPT2 formulations in nonadiabatic dynamics.
Methods based on a full configuration interaction (FCI) expansion in an active space of orbitals are widely used for modeling chemical phenomena such as bond breaking, multiply excited states, and ...conical intersections in small-to-medium-sized molecules, but these phenomena occur in systems of all sizes. To scale such calculations up to the nanoscale, we have developed an implementation of FCI in which electron repulsion integral transformation and several of the more expensive steps in σ vector formation are performed on graphical processing unit (GPU) hardware. When applied to a 1.7 × 1.4 × 1.4 nm silicon nanoparticle (Si72H64) described with the polarized, all-electron 6-31G** basis set, our implementation can solve for the ground state of the 16-active-electron/16-active-orbital CASCI Hamiltonian (more than 100,000,000 configurations) in 39 min on a single NVidia K40 GPU.
We introduce a new method for optimizing minimal energy conical intersections (MECIs), based on a sequential penalty constrained optimization in conjunction with a smoothing function. The method is ...applied to optimize MECI geometries using the multistate formulation of second-order multireference perturbation theory (MS-CASPT2). Resulting geometries and energetics for conjugated molecules including ethylene, butadiene, stilbene, and the green fluorescent protein chromophore are compared with state-averaged complete active space self-consistent field (SA-CASSCF) and, where possible, benchmark multireference single- and double-excitation configuration interaction (MRSDCI) optimizations. Finally, we introduce the idea of “minimal distance conical intersections”, which are points on the intersection seam that lie closest to some specified geometry such as the Franck−Condon point or a local minimum on the excited state.
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