*PLoS One ; 16(1): e0244026, 2021.*

##### RESUMO

It was recently shown that quantum annealing can be used as an effective, fast subroutine in certain types of matrix factorization algorithms. The quantum annealing algorithm performed best for quick, approximate answers, but performance rapidly plateaued. In this paper, we utilize reverse annealing instead of forward annealing in the quantum annealing subroutine for nonnegative/binary matrix factorization problems. After an initial global search with forward annealing, reverse annealing performs a series of local searches that refine existing solutions. The combination of forward and reverse annealing significantly improves performance compared to forward annealing alone for all but the shortest run times.

##### Assuntos

Algoritmos , Modelos Teóricos , Teoria Quântica*Bioorg Med Chem Lett ; 35: 127778, 2021 03 01.*

##### RESUMO

The discovery of a series of substituted diarylether compounds as retinoic acid related orphan receptor Î³t (RORÎ³t) agonists is described. Compound 1 was identified from deck mining as a RORÎ³t agonist. Hit-to-lead optimization led to the identification of lead compound 5, which possesses improved potency (10x). Extensive SAR exploration led to the identification of a potent and selective compound 22, that demonstrated an improved pharmacokinetic profile and a dose-dependent pharmacodynamic response. However, when dosed in a MC38 syngeneic tumor model, no evidence of efficacy was observed. ©2020 Elsevier Science Ltd. All rights reserved.

*Bioorg Med Chem Lett ; 30(12): 127204, 2020 06 15.*

##### RESUMO

Substituted benzyloxy aryl compound 2 was identified as an RORÎ³t agonist. Structure based drug design efforts resulted in a potent and selective tricyclic compound 19 which, when administered orally in an MC38 mouse tumor model, demonstrated a desired pharmacokinetic profile as well as a dose-dependent pharmacodynamic response. However, no perceptible efficacy was observed in this tumor model at the doses investigated.

*ACS Med Chem Lett ; 10(10): 1486-1491, 2019 Oct 10.*

##### RESUMO

C-terminal Src kinase (CSK) functions as a negative regulator of T cell activation through inhibitory phosphorylation of LCK, so inhibitors of CSK are of interest as potential immuno-oncology agents. Screening of an internal kinase inhibitor collection identified pyridazinone lead 1, and a series of modifications led to optimized compound 13. Compound 13 showed potent activity in biochemical and cellular assays in vitro and demonstrated the ability to increase T cell proliferation induced by T cell receptor signaling. Compound 13 gave extended exposure in mice upon oral dosing and produced a functional response (decrease in LCK phosphorylation) in mouse spleens at 6 h post dose.

*J Contam Hydrol ; 220: 66-97, 2019 Jan.*

##### RESUMO

Unsupervised Machine Learning (ML) is becoming increasingly popular for solving various types of data analytics problems including feature extraction, blind source separation, exploratory analyses, model diagnostics, etc. Here, we have developed a new unsupervised ML method based on Nonnegative Tensor Factorization (NTF) for identification of the original groundwater types (including contaminant sources) present in geochemical mixtures observed in an aquifer. Frequently, groundwater types with different geochemical signatures are related to different background and/or contamination sources. The characterization of groundwater mixing processes is a challenging but very important task critical for any environmental management project aiming to characterize the fate and transport of contaminants in the subsurface and perform contaminant remediation. This task typically requires solving complex inverse models representing groundwater flow and geochemical transport in the aquifer, where the inverse analysis accounts for available site data. Usually, the model is calibrated against the available data characterizing the spatial and temporal distribution of the observed geochemical types. Numerous different geochemical constituents and processes may need to be simulated in these models which further complicates the analyses. Additionally, the application of inverse methods may introduce biases in the analyses through the assumptions made in the model development process. Here, we substitute the model inversion with unsupervised ML analysis. The ML analysis does not make any assumptions about underlying physical and geochemical processes occurring in the aquifer. Our ML methodology, called NTFk, is capable of identifying (1) the unknown number of groundwater types (contaminant sources) present in the aquifer, (2) the original geochemical concentrations (signatures) of these groundwater types and (3) spatial and temporal dynamics in the mixing of these groundwater types. These results are obtained only from the measured geochemical data without any additional site information. In general, the NTFk methodology allows for interpretation of large high-dimensional datasets representing diverse spatial and temporal components such as state variables and velocities. NTFk has been tested on synthetic and real-world site three-dimensional datasets. The NTFk algorithm is designed to work with geochemical data represented in the form of concentrations, ratios (of two constituents; for example, isotope ratios), and delta notations (standard normalized stable isotope ratios).

##### Assuntos

Água Subterrânea , Poluentes Químicos da Água , Monitoramento Ambiental , Isótopos*PLoS One ; 13(12): e0206653, 2018.*

##### RESUMO

D-Wave quantum annealers represent a novel computational architecture and have attracted significant interest. Much of this interest has focused on the quantum behavior of D-Wave machines, and there have been few practical algorithms that use the D-Wave. Machine learning has been identified as an area where quantum annealing may be useful. Here, we show that the D-Wave 2X can be effectively used as part of an unsupervised machine learning method. This method takes a matrix as input and produces two low-rank matrices as output-one containing latent features in the data and another matrix describing how the features can be combined to approximately reproduce the input matrix. Despite the limited number of bits in the D-Wave hardware, this method is capable of handling a large input matrix. The D-Wave only limits the rank of the two output matrices. We apply this method to learn the features from a set of facial images and compare the performance of the D-Wave to two classical tools. This method is able to learn facial features and accurately reproduce the set of facial images. The performance of the D-Wave shows some promise, but has some limitations. It outperforms the two classical codes in a benchmark when only a short amount of computational time is allowed (200-20,000 microseconds), but these results suggest heuristics that would likely outperform the D-Wave in this benchmark.

##### Assuntos

Aprendizado de Máquina , Modelos Teóricos , Teoria Quântica*Sci Rep ; 8(1): 11665, 2018 Aug 03.*

##### RESUMO

Fractured systems are ubiquitous in natural and engineered applications as diverse as hydraulic fracturing, underground nuclear test detection, corrosive damage in materials and brittle failure of metals and ceramics. Microstructural information (fracture size, orientation, etc.) plays a key role in governing the dominant physics for these systems but can only be known statistically. Current models either ignore or idealize microscale information at these larger scales because we lack a framework that efficiently utilizes it in its entirety to predict macroscale behavior in brittle materials. We propose a method that integrates computational physics, machine learning and graph theory to make a paradigm shift from computationally intensive high-fidelity models to coarse-scale graphs without loss of critical structural information. We exploit the underlying discrete structure of fracture networks in systems considering flow through fractures and fracture propagation. We demonstrate that compact graph representations require significantly fewer degrees of freedom (dof) to capture micro-fracture information and further accelerate these models with Machine Learning. Our method has been shown to improve accuracy of predictions with up to four orders of magnitude speedup.

*Sci Rep ; 8(1): 6919, 2018 May 02.*

##### RESUMO

Making predictions about flow and transport in an aquifer requires knowledge of the heterogeneous properties of the aquifer such as permeability. Computational methods for inverse analysis are commonly used to infer these properties from quantities that are more readily observable such as hydraulic head. We present a method for computational inverse analysis that utilizes a type of quantum computer called a quantum annealer. While quantum computing is in an early stage compared to classical computing, we demonstrate that it is sufficiently developed that it can be used to solve certain subsurface flow problems. We utilize a D-Wave 2X quantum annealer to solve 1D and 2D hydrologic inverse problems that, while small by modern standards, are similar in size and sometimes larger than hydrologic inverse problems that were solved with early classical computers. Our results and the rapid progress being made with quantum computing hardware indicate that the era of quantum-computational hydrology may not be too far in the future.

*J Contam Hydrol ; 212: 134-142, 2018 05.*

##### RESUMO

Identification of the original groundwater types present in geochemical mixtures observed in an aquifer is a challenging but very important task. Frequently, some of the groundwater types are related to different infiltration and/or contamination sources associated with various geochemical signatures and origins. The characterization of groundwater mixing processes typically requires solving complex inverse models representing groundwater flow and geochemical transport in the aquifer, where the inverse analysis accounts for available site data. Usually, the model is calibrated against the available data characterizing the spatial and temporal distribution of the observed geochemical types. Numerous different geochemical constituents and processes may need to be simulated in these models which further complicates the analyses. In this paper, we propose a new contaminant source identification approach that performs decomposition of the observation mixtures based on Non-negative Matrix Factorization (NMF) method for Blind Source Separation (BSS), coupled with a custom semi-supervised clustering algorithm. Our methodology, called NMFk, is capable of identifying (a) the unknown number of groundwater types and (b) the original geochemical concentration of the contaminant sources from measured geochemical mixtures with unknown mixing ratios without any additional site information. NMFk is tested on synthetic and real-world site data. The NMFk algorithm works with geochemical data represented in the form of concentrations, ratios (of two constituents; for example, isotope ratios), and delta notations (standard normalized stable isotope ratios).

##### Assuntos

Água Subterrânea/química , Aprendizado de Máquina Supervisionado , Poluentes Químicos da Água/química , Monitoramento Ambiental/métodos , Isótopos/análise*Phys Rev E Stat Nonlin Soft Matter Phys ; 91(4): 042143, 2015 Apr.*

##### RESUMO

Brownian motion, the classical diffusive process, maximizes the Boltzmann-Gibbs entropy. The Tsallis q entropy, which is nonadditive, was developed as an alternative to the classical entropy for systems which are nonergodic. A generalization of Brownian motion is provided that maximizes the Tsallis entropy rather than the Boltzmann-Gibbs entropy. This process is driven by a Brownian measure with a random diffusion coefficient. The distribution of this coefficient is derived as a function of q for 1

*Chemistry ; 21(6): 2398-408, 2015 Feb 02.*

##### RESUMO

The marine natural products amphidinolideâ C (1) and F (4) differ in their side chains but share a common macrolide core with a signature 1,4-diketone substructure. This particular motif inspired a synthesis plan predicating a late-stage formation of this non-consonant ("umpoled") pattern by a platinum-catalyzed transannular hydroalkoxylation of a cycloalkyne precursor. This key intermediate was assembled from three building blocks (29, 41 and 47 (or 65)) by Yamaguchi esterification, Stille cross-coupling and a macrocyclization by ring-closing alkyne metathesis (RCAM). This approach illustrates the exquisite alkynophilicity of the catalysts chosen for the RCAM and alkyne hydroalkoxylation steps, which activate triple bonds with remarkable ease but left up to five other π-systems in the respective substrates intact. Interestingly, the inverse chemoselectivity pattern was exploited for the preparation of the tetrahydrofuran building blocks 47 and 65 carrying the different side chains of the two target macrolides. These fragments derive from a common aldehyde precursor 46 formed by an exquisitely alkene-selective cobalt-catalyzed oxidative cyclization of the diunsaturated alcohol 44, which left an adjacent acetylene group untouched. The northern sector 29 was prepared by a two-directional Marshall propargylation strategy, whereas the highly adorned acid subunit 41 derives from D-glutamic acid by an intramolecular oxa-Michael addition and a proline-mediated hydroxyacetone aldol reaction as the key steps; the necessary Me3 Sn-group on the terminus of 41 for use in the Stille coupling was installed via enol triflate 39, which was obtained by selective deprotonation/triflation of the ketone site of the precursor 38 without competing enolization of the ester also present in this particular substrate.

##### Assuntos

Macrolídeos/síntese química , Catálise , Cobalto/química , Ciclização , Cicloparafinas/química , Macrolídeos/química , Oxirredução , Platina/química , Estereoisomerismo*Angew Chem Int Ed Engl ; 52(36): 9534-8, 2013 Sep 02.*

*Phys Rev E Stat Nonlin Soft Matter Phys ; 86(1 Pt 1): 011126, 2012 Jul.*

##### RESUMO

Renormalization-group operators are used to classify stochastic processes on two time scales. Repeated application of one operator is associated with the long-time behavior of the process while the other is associated with the short-time behavior of the process. This approach is shown to be robust even in the presence of nonstationary increments and infinite second moments. Fixed points of the operators can be used for further subclassification of processes when appropriate limits exist. Several processes are classified using the renormalization-group scheme. The processes to be classified include advection-diffusion in an ergodic velocity field, and a model of diffusion in the human bronchial tree.

##### Assuntos

Algoritmos , Difusão , Modelos Químicos , Modelos Estatísticos , Simulação por Computador*J Am Chem Soc ; 133(37): 14710-26, 2011 Sep 21.*

##### RESUMO

Dimeric pyrrole-imidazole alkaloids represent a rich and topologically unique class of marine natural products. This full account will follow the progression of efforts that culminated in the enantioselective total syntheses of the most structurally ornate members of this family: the axinellamines, the massadines, and palau'amine. A bio-inspired approach capitalizing on the pseudo-symmetry of the members of this class is recounted, delivering a deschloro derivative of the natural product core. Next, the enantioselective synthesis of the chlorocyclopentane core featuring a scalable, catalytic, enantioselective Diels-Alder reaction of a 1-siloxydiene is outlined in detail. Finally, the successful divergent conversion of this core to each of the aforementioned natural products, and the ensuing methodological developments, are described.

##### Assuntos

Alcaloides/síntese química , Guanidinas/síntese química , Imidazóis/síntese química , Pirróis/síntese química , Compostos de Espiro/síntese química , Técnicas de Química Sintética , Estereoisomerismo*Phys Rev E Stat Nonlin Soft Matter Phys ; 82(3 Pt 1): 032102, 2010 Sep.*

##### RESUMO

We construct a family of stochastic processes with nonstationary, correlated increments which allow a priori independent selections of both fractal dimension and mean-square displacement. The family is essentially fractional Brownian motion (fBm) run with a nonlinear clock (fBm-nlc). The fractal dimension of fBm-nlc is shown to be the same as that of the underlying fBm process. We also compute the p-variation and discuss the problems in using this to differentiate between diffusive processes. The fBm-nlc process illustrates that the range of anomalous diffusive processes has not been adequately explored.

*ACS Chem Biol ; 5(2): 195-202, 2010 Feb 19.*

##### RESUMO

Sceptrin, a natural compound produced by various marine sponges, was tested for its effect on cell motility. We report for the first time that sceptrin inhibits cell motility in several cancer cell lines. The compound shows no toxicity at concentrations that are double the amount of sceptrin required for maximal inhibitory effect. Both random and factor-induced migration were impaired, suggesting that sceptrin targets a central process of cell motility machinery. Activity of de novo synthesized sceptrin was indistinguishable from sceptrin purified from Agelas nakamurai, and the inhibitory activity was found to be, at least partially, due to sceptrin's capability to inhibit cell contractility. Additionally, sceptrin was found to bind to monomeric actin, further suggesting a mechanism involving the actin cytoskeleton. Close analogues of sceptrin were synthesized, tested for their effect on cell motility, and found to be either equimolar or less potent compared to the parental compound. Inadvertent cell motility is a key contributing factor in various human diseases, including cancer and chronic inflammation. Marine compounds isolated from sponges have been proven to be an excellent source of metabolites that show biological activities. Given the recently achieved total synthesis of sceptrin in multigram quantities, sceptrin could prove to be an attractive lead molecule for further preclinical testing and development for therapeutic purposes, as well as a useful research tool to elucidate the mechanisms involved in cell motility.

##### Assuntos

Produtos Biológicos/farmacologia , Movimento Celular/efeitos dos fármacos , Pirróis/farmacologia , Agelas/química , Animais , Produtos Biológicos/química , Linhagem Celular Tumoral , Proliferação de Células/efeitos dos fármacos , Sobrevivência Celular/efeitos dos fármacos , Quimiotaxia/efeitos dos fármacos , Células HeLa , Humanos , Pseudópodes/efeitos dos fármacos , Pirróis/química*Phys Rev E Stat Nonlin Soft Matter Phys ; 79(3 Pt 1): 032101, 2009 Mar.*

##### RESUMO

If the mean-square displacement of a stochastic process is proportional to t;{beta} , beta not equal1 , then it is said to be anomalous. We construct a family of Markovian stochastic processes with independent nonstationary increments and arbitrary but a priori specified mean-square displacement. We label the family as an extended Brownian motion and show that they satisfy a Langevin equation with time-dependent diffusion coefficient. If the time derivative of the variance of the process is homogeneous, then by computing the fractal dimension it can be shown that the complexity of the family is the same as that of the Brownian motion. For two particles initially separated by a distance x , the finite-size Lyapunov exponent (FSLE) measures the average rate of exponential separation to a distance ax . An analytical expression is developed for the FSLEs of the extended Brownian processes and numerical examples presented. The explicit construction of these processes illustrates that contrary to what has been stated in the literature, a power-law mean-square displacement is not necessarily related to a breakdown in the classical central limit theorem (CLT) caused by, for example, correlation (fractional Brownian motion or correlated continuous-time random-walk schemes) or infinite variance (Levy motion). The classical CLT, coupled with nonstationary increments, can and often does give rise to power-law moments such as the mean-square displacement.

*Acc Chem Res ; 42(4): 530-41, 2009 Apr 21.*

##### RESUMO

IUPAC defines chemoselectivity as "the preferential reaction of a chemical reagent with one of two or more different functional groups", a definition that describes in rather understated terms the single greatest obstacle to complex molecule synthesis. Indeed, efforts to synthesize natural products often become case studies in the art and science of chemoselective control, a skill that nature has practiced deftly for billions of years but man has yet to master. Confrontation of one or perhaps a collection of functional groups that are either promiscuously reactive or stubbornly inert has the potential to unravel an entire strategic design. One could argue that the degree to which chemists can control chemoselectivity pales in comparison to the state of the art in stereocontrol. In this Account, we hope to illustrate how the combination of necessity and tenacity leads to the invention of chemoselective chemistry for the construction of complex molecules. In our laboratory, a premium is placed upon selecting targets that would be difficult or impossible to synthesize using traditional techniques. The successful total synthesis of such molecules demands a high degree of innovation, which in turn enables the discovery of new reactivity and principles for controlling chemoselectivity. In devising an approach to a difficult target, we choose bond disconnections that primarily maximize skeletal simplification, especially when the proposed chemistry is poorly precedented or completely unknown. By choosing such a strategy--rather than adapting an approach to fit known reactions--innovation and invention become the primary goal of the total synthesis. Delivery of the target molecule in a concise and convergent manner is the natural consequence of such endeavors, and invention becomes a prerequisite for success.

##### Assuntos

Produtos Biológicos/síntese química , Alcaloides/síntese química , Alcaloides/química , Produtos Biológicos/química , Compostos Heterocíclicos de 4 ou mais Anéis/síntese química , Compostos Heterocíclicos de 4 ou mais Anéis/química , Imidazóis/química , Alcaloides Indólicos/síntese química , Alcaloides Indólicos/química , Indóis/síntese química , Indóis/química , Lactonas/síntese química , Lactonas/química , Lignanas/síntese química , Lignanas/química , Neuropeptídeos/síntese química , Neuropeptídeos/química , Pirróis/química*Phys Rev E Stat Nonlin Soft Matter Phys ; 78(5 Pt 1): 052101, 2008 Nov.*

##### RESUMO

This Brief Report examines Levy motion in a slit pore with sticky boundaries, i.e., boundaries that absorb particles for a random amount of time. A set of equations is developed that can explicitly be solved for mean travel distance to a plane for a particle released from the origin and can iteratively be used to compute mean first-passage time (MFPT). Results from the theory compare favorably with Monte Carlo simulations.