dataesr/scientific-paragraphs-categorization huggingface dataset:
Influence of isosteric oxazole/triazole replacement The above re-docking experiment of 1,2,3-triazoles T1 e T7 resulted lower score than that obtained for their oxazole analogues. Triazoles T3 and T7 exhibit much less inhibitory activity against VEGFR2 kinase compared to their known oxazole bioisosters T3-ox and AAZ (T3/T3-ox, IC 50 : 6950 nM/12. 8 nM and T7/AAZ, IC 50 : 42 400 nM/22 nM). Therefore we proposed that different electronic properties of oxazole/triazole core (the size and dipole moment orientation) could be responsible for disfavouring of 1,2,3-triazole derivatives in VEGFR2 TK AAZ binding site. The structures and dipole moments depicted on Fig. 13  were performed by Discovery Studio 3. 5 Visualizer [78]. VEGFR2 kinase surrounds the oxazole core of AAZ ligand (PDB: 1Y6A) by seven nonpolar amino acid residues: Phe916, Val914, Val897, Ala864, Leu838, Leu1033, and Cys917.
96 mM). (Fig. 10 ) The activities of new compounds were significantly lower than the ones obtained for their oxazole bioisosters (e. g. T3/T3-ox in Fig. 12  and T7/AAZ in Fig. 10 , resp. ). Despite the diminished activity, the triazole modulators T1, T3 and T7 inhibit VEGFR2 kinase by concentration dependent manner. Concerning the identical substructure, the inhibitory activity of 1,4-triazoles T1eT3, T6eT7 is depending on the decoration of their aryl part joined to N(1) of the triazole core. (Fig. 1 ) The different electronic properties of 1,2,3-triazole and oxazole fragments (size and orientation of the dipole moments, Fig. 13 ) were proposed to be responsible for low activities of triazoles T1eT3, T6eT7. The more polar triazole core binds less readily into VEGFR2 TK lipophilic oxazole binding pocket known  from PDB: 1Y6A or 1Y6B.
Chemical shifts are given in parts per million (ppm). IR spectra were acquired on FT-IR-ATR REACT IR 1000 (ASI Applied Systems) with diamond probe and MTS detector. ESI Mass spectral data were obtained by Esquire-LC-00075 spectrometer (Brucker Bioscience). Other mass spectra were performed on LC-MS (Agilent Technologies 1200 Series equipped with Mass spectrometer Agilent Technologies 6100 Quadrupole LC-MS). Elemental analyses for carbon, hydrogen and nitrogen were performed with an Eager 300 analyzer. Used abbreviations: EA: ethyl acetate, Boc: tertbutyloxycarbonate, Cy: cyclohexane, DCM: dichloromethane, EWG: electron withdrawing group (e. g. eCOOMe, -Boc, -Ts etc. ), FLC: Flash liquid chromatography, N,N 0 -DMED: N,N-dimethylethylenediamine, RT: room temperature, S-Phos: 2-dicyclohexylphosphino-2 0 ,6 0dimethoxybiphenyl [CAS 657408-07-6], TIPS: triisopropylsilyl, TLC: thin layer chromatography (SiO 2 /UV 254 ).
This method is based on a simulated annealing Monte Carlo algorithm to search for the lowest-energy arrangement of inorganic and organic building blocks with predefined linkages, initially introduced randomly in a simulation box with a given molar ratio. Thousands of plausible novel MOF structures were thus predicted. D. W. Lewis et al. further proposed the construction of a series of hypothetical Zeolitic Imidazolate frameworks (ZIFs) starting with various zeolite crystal structures and substituting the Si center and the Si-O-Si bridge by a Zn ion and the imidazole linker, respectively. These structures were geometry optimized using the Density Functional Theory and their stabilities were assessed through the determination of their total electronic energies  [57]. Later, the database of hypothetical MOFs was considerably enriched by the development of novel computational tools which aimed to explore the recombination of building blocks simply driven by geometric and topological consideration.
Acknowledgments G. M. thanks  A. Ghoufi  ( IPR UMR 6251 ,  Universit e de Rennes) ;  F. Salles ,  N. A. Ramsahye ,  P. G. Yot  ( ICGM UMR 5253 CNRS UM ENSCM );  Q. Ma ,  Q. Yang  and  C. L. Zhong  ( State Key Laboratory of Organic-Inorganic Composites, Beijing University of Chemical Technology );  A. Vittadini  ( ISTM-CNR, Dipartimento di Scienze Chimiche and INSTM, UdR Padova, Universit degli Studi di Padova );  V. Guillerm ,  H. Chevreau ,  F. Ragon ,  F. Nouar ,  E. Alvarez ,  C. Martineau ,  F. Taulelle ,  N. Guillou ,  T. Devic ,  P. Horcajada ,  C. Serre  and  G. F erey  ( Institut Lavoisier Versailles UMR 8180 CNRS Universit e VersailleseSaint-Quentin-en-Yvelines)  for their contributions to this work and the  Institut Universitaire de France  for the support.
Acknowledgements Support from the  Indo-French Centre for the Promotion of Advanced Research (IFCPAR)  /  Centre Franco-Indien pour la Promotion de la Recherche Avancée (CEFIPRA)  is gratefully acknowledged (Project no. 4705-1 ). The  TEM-team platform (CEA, iBiTec-S)  is acknowledged for help with TEM images. The  "Service de Chimie Bioorganique et de Marquage" belongs to the Laboratory of Excellence in Research on Medication and Innovative Therapeutics   ĲANR-10-LABX-0033-LERMIT ).
The density functional code deMon2k employs a fitted density throughout (Auxiliary Density Functional Theory), which offers a great speed advantage without OPEN ACCESS sacrificing necessary accuracy. Powerful Quantum Mechanical/Molecular Mechanical (QM/MM) approaches are reviewed. Following an overview of the basic features of deMon2k that make it efficient while retaining accuracy, three QM/MM implementations are compared and contrasted. In the first, deMon2k is interfaced with the CHARMM MM code (CHARMM-deMon2k); in the second MM is coded directly within the deMon2k software; and in the third the Chemistry in Ruby (Cuby) wrapper is used to drive the calculations. Cuby is also used in the context of constrained-DFT/MM calculations. Each of these implementations is described briefly; pros and cons are discussed and a few recent applications are described briefly.
Since the pioneering work of Warshel and Karplus  [1]  and Warshel and Levitt  [2]  in the seventies many implementations of hybrid Quantum Mechanical/Molecular Mechanical (QM/MM) methodologies have ensued (see refs. [3] [4] [5] [6]  for recent reviews). This mini-review focuses exclusively on our recent work using the deMon2k Density Functional software  [7]  as the QM engine. deMon stands for density of Montreal since the earliest versions of the code were developed in the Salahub group at the Université de Montréal, in the late 1980s. A brief description of the program and its history may be found on the demon-software web site  [7]. The current version of deMon2k is maintained and developed by a loose international consortium known as the deMon Developers with a principal node at CINVESTAV in Mexico City handling licensing (free for academics) and distribution (see the web site for details).
The main features of the public release of deMon2k are: Additionally, the current developer version of deMon2k (4. 2. 5) adds the following features to the list: • Molecular mechanics energies, gradients and Hessian • QM/MM interface to CHARMM, Cuby and PUPIL • Constrained DFT and ADFT energies and gradients • Asymptotic molecular integral expansions for mixed SCF • Exact exchange with three-center electron repulsion integrals (ERIs) • X-ray absorption and emission spectroscopy • ROKS perturbation theory and Fukui functions • Magnetizability, rotational g-tensor and spin-spin coupling constants • BOMD property (NMR, , ) and analysis tools • Non-iterative CPKS solver for perturbation theory • VMT, LB94, B3LYP, PBE0 and M06-2X functionals • Hirshfeld (iterative), Becke and Voronoi population analyses • Plotting of Fukui functions, induced magnetic fields and perturbed or deformed densities Further details concerning theory, implementation and program features may be found in the deMon User's guide  [7].
The current deMon2k developer version can also be obtained from the CINVESTAV group (mail to: pcalamin@cinvestav. mx) or from a deMon2k developer. A Software Focus on deMon2k appeared in the Wiley WIRES series in 2011  [8]. That paper focused on the main methodological and implementation underpinnings of deMon2k, starting from the pioneering work on density-fitting of Dunlap, Connolly and Sabin  [9]  and proceeding through the formulation of Auxiliary DFT  [10] , in which the fitted density is used for both the Coulomb terms and the exchange-correlation terms. This lies at the heart of the efficiency of deMon2k and has allowed its extension to large systems, now containing a thousand or more atoms and tens of thousands of basis functions, or for the use of deMon2k in Born-Oppenheimer simulations containing a hundred or more atoms for tens or hundreds of picoseconds.
Because the variational fitting of the Coulomb potential converges from below it is necessary to use a MinMax iterative scheme  [14]  in the SCF cycles (earlier codes that ignored this aspect often had convergence difficulties). With modern computer architectures, parallelization is imperative; deMon2k uses the Message Passing Interface in such a way that the efficiency of the serial code is preserved  [15]. Some early benchmarks were given in the WIRES paper; others appear below. The above-described features of deMon2k represent the state of play in 2011. Since that time, several key advances have been made that are crucial for the use of deMon2k for calculations and simulations on very large systems. These more recent features are described in somewhat greater detail in Section 2. They include the double asymptotic expansion for three-center ERIs  [16] , the asymptotic expansion for electrostatic embedding integrals  [17]  and, most recently a mixed SCF procedure that uses either direct or standard (store and retrieve) SCF approaches depending on whether the ERIs are of the near-field or far-field type  [18].
In Sections 3 to 5, three different QM/MM implementations are compared and contrasted as to their strengths, weaknesses and areas of applicability: (i) an interface between deMon2k and the CHARMM molecular mechanical software; (ii) a version coded directly in deMon2k and (iii) a multipurpose framework for composite calculations called Cuby (Chemistry in Ruby). For each of these the main features of the methodology and its implementation are presented, pointing out pros and cons and setting the bounds on system size etc. for its intended use. This is complemented for each by brief descriptions of one or two representative applications from the recent literature.
CHARMM-deMon Interface While there are many different QM/MM interfaces available to a number of molecular simulation softwares, compatibility with CHARMM  [25]  allows access to a broad range of simulation techniques including compatibility with the latest additive force-fields for proteins, nucleic acids, lipids and small molecules, polarizable force-fields such as the Drude polarizable force-field and links to free energy simulation techniques (Thermodynamic Integration (TI), Umbrella Sampling (US) and Free Energy Perturbation (FEP)). In addition to advantageous developments we can also rely on the enhanced sampling algorithms implemented in CHARMM versions c36 to c39, allowing efficient system propagation in a very complex energy space. For example, an FEP calculation for QM/MM systems with solvent molecules allows a direct evaluation of relative thermodynamic properties while avoiding the limitations of classical potential functions.
Free Energy Perturbation with CHARMM-deMon2k: Application to Ion Solvation One of the main goals of interfacing CHARMM and deMon2k was to enable free energy perturbation (FEP) simulations for particles of interest located in the QM region. To achieve this goal we have used the following protocol for slowly changing the system from one state to another through a number of intermediate alchemical steps. The Hamiltonian controlling this perturbation along the chosen path can be written as: H (λ,t) = λH A (t) + (1 -λ)H B (t) ( 17 ) where subscripts A and B correspond, respectively, to the initial and final states of the system. The corresponding Hamiltonians (HA and HB) encompass all of the objects in the mixed system (QM/MM); the approach is also known as the dual-topology scheme  [37]. The perturbation parameter (λ) is used to propagate the system of interest from one state to the other.
In-deMon2k QM/MM Nowadays, most QM/MM calculations are performed either from a QM driver program (CPMD, Gaussian 09) or from an MM master code (CHARMM, Gromacs). Some interface codes (ChemShell, Cuby, PUPIL)  [50] [51] [52] [53]  also exist, allowing connections between chosen QM and MM programs. If deMon2k is used as the driver for QM/MM calculations a unified input syntax is available along with a generalized output format. At this point it is also important to note that deMon2k QM, QM/MM and MM optimizations, molecular dynamics (MD) and frequency analyses use the same program branches and, therefore, are directly comparable. Moreover, electronic properties are readily available for QM and QM/MM calculations. In short, the in-deMon2k QM/MM implementation provides a user-friendly input for MPI QM/MM calculation with up to around 50,000 atoms.
Overview of Cuby Cuby  [51]  is a software framework for computational chemistry written in the ruby programming language (the name stands for Chemistry in Ruby). Its main purpose is to simplify the development and implementation of complex computational protocols consisting of multiple calculations. The calculations themselves are carried out externally via interfaces to existing program packages. This allows one to connect calculations using different methods implemented in different codes. Cuby is developed as a general framework for automation of complex calculations and it is already used in several different projects. In this paper, we will describe the QM/MM functionality implemented in Cuby but it is not the only purpose of the code. While this makes the implementation of the QM/MM calculations less efficient, it makes it more flexible than dedicated QM/MM software.
New computational protocols can be built out of existing modules without writing new code. We begin with a brief description of the architecture of the framework. At the lowest level, there are libraries allowing an object-oriented description of the data we work with, most importantly molecular geometries and the results of calculations applied on them. Above this layer, there is the core of a framework that, using the information from a structured input file, builds the complex calculation out of independent modules, handling the individual calculations and tasks, and manages the communication between the modules. All the method-specific functionality is implemented in these modules. There are two types of them. The first type of Cuby module is the "interface" which runs a calculation, the input is the molecular geometry and calculation setup and the output is the corresponding energy, gradient and other properties (as requested).
Most interfaces call an external program to perform the calculation, in that case, the interface automatically builds the input for that program, runs it and parses the output to get the results. Some interfaces do the calculation themselves, this is used for simple calculations such as adding empirical corrections to the underlying potential. Finally, there are interfaces implementing composite calculations, calling other interfaces to get partial results, which are then combined. This is the case of the QM/MM implementation in Cuby. The second type of Cuby module is an implementation of a computational "protocol", a driver that operates on the potential calculated by the interface(s). Cuby implements all the commonly used protocols such as geometry optimization, harmonic vibrational analysis, molecular dynamics and more.
The power of Cuby lies in the fact that all the modules can be arbitrarily combined, allowing combinations not available in the original software it calls. All these possibilities are available to the end user since the configuration of the modules and their connection is defined solely by means of a structured input file-no actual programming is needed. Figure  9  illustrates how such an input file for advanced QM/MM calculations (details are provided below) translates into a calculation built from the individual modules.
Numerical simulations based on QM/MM schemes are valuable tools to decipher the physicochemical mechanisms governing such processes. When simulating electron transfers it is advantageous to adopt a diabatic description where each electronic state corresponds to the localization of the charge excess on a specific molecular fragment (here FAD, W400, W377 or W324). The constrained DFT methodology (cDFT) allows such definitions of non-adiabatic states at the DFT level. The implementation of cDFT in deMon2k and its compatibility with Cuby has been reported in a previous article  [83]. In this review article we illustrate the use of Cuby to perform cDFT/MM MD simulations using deMon2k and CHARMM softwares to probe the transfer of one electron from W377 to W400°+. This electron transfer is the second step of the charge migration process in AtCry1 (see Figure  12 ), the first one being the transfer from W400 to FAD* (investigated recently in Ref  [84] ).
Acknowledgments D. R. S. is grateful to  NSERC  for ongoing Discovery Grant support. Substantial high-performance computing resources have been provided by  Compute Canada/WestGrid. The development of Cuby by J. Ř. is a part of the  Research  Project  RVO 61388963  of the  Institute of Organic Chemistry and Biochemistry AS CR , and was supported by the grant  P208/13/01214P  from the  Czech Science Foundation. The CINVESTAV group gratefully acknowledges support from  CONACYT  via a group project ( CB-179409 ) and computational time on the hybrid compute cluster Xiuhcoatl at CINVESTAV. D. M. R. acknowledges a  CONACYT PhD fellowship  ( 47922 ).
22 A similar change in secondary structure is observed in the doubly graed species in Fig. 2 , although for singly (3+) and doubly (4+) protonated peptide. It thus appears that although similar structural trends are observed in these two systems, the presence of the N-and C-terminal charges of the chromophores is inducing the transition from coil-like to helical to occur at a lower peptide protonation state. In order to recognize any commonalities between the physiologically relevant solution phase structure of the Ab 1-42 and the gas phase structure of the doubly graed Ab 12-28 studied here, a visualization of the NMR structure of Ab 1-42 (pdb code 1LFM) is included as an inset to Fig. 2  with the 12-28 region highlighted in green. There is a clear helical motif for the 12-28 region, which is also observed for the 4+ charge state in both wild and F19P alloforms.
Acknowledgments: We thank  A. Krajnc  for help with the NMR measurements and  I. Tüttő  for fruitful discussions. Funding: We acknowledge financial support by the  European Union/JST   FP7-NMP-2011-EU-Japan  project  LEMSUPER  (contract no. NMP3-SL-2011-283214 ), the  UK Engineering and Physical Sciences Research Council  (grant nos. EP/K027255  and  EP/K027212 ), the  Japan Science and Technology Agency  under the  ERATO Isobe Degenerate p-Integration Project , the  Japan Society of Promotion of Sciences  ( Grant-in-Aid for Specially Promoted Research  no. 25000003 ), and the  Hungarian National Research Fund (OTKA)  no. 105691. We thank the  European Synchrotron Radiation Facility , SPring-8, and RIKEN for access to synchrotron x-ray facilities, and the  Royal Society  for a  Newton International Fellowship  (G.
ACKNOWLEDGMENTS. This work used the platforms of the  Grenoble Instruct Centre (Integrated Structural Biology Grenoble ;  Unité Mixte de Service 3518 ) with support from the  French Infrastructure for Integrated Structural Biology  ( ANR-10-INSB-05-02 ) and  Grenoble Alliance for Integrated Structural and Cell Biology  ( ANR-10-LABX-49-01 ) within the  Grenoble Partnership for Structural Biology. Financial support is acknowledged from the  French Agence Nationale de la Recherche (ANR)  through  ANR Jeunes Chercheuses et Jeunes Chercheurs  ProteinDisorder (M. R. J. ),  ANR MALZ TAUSTRUCT  (M. B. ), and  ANR Complex-Dynamics  (M. B. ). J. K. is a fellow of the  Marie Curie action "IDPbyNMR" of the European Commission  (Contract  264257 ).
0% Au/CeO 2 NC600 catalyst the actual reduction degree under the {111} nanofacets is expected to be smaller than under the remaining {100} extended facets. At this respect it is interesting to analyze the shift of the binding energies of the Au 4f 7/2 signals in the XPS spectra of the two catalysts. According to data in Table  2 , when going from the 0. 4% Au/CeO 2 NC catalyst to 1. 0% Au/CeO 2 NC600, the signals corresponding to both types of Au atoms move to lower binding energies (as expected for an overall more reduced state of the support), but the shift corresponding to the more positive species (ΔBE(Au 2 ) = 0. 4 eV) is smaller than that of the less positive one (ΔBE(Au 1 ) = 0. 6 eV). These results agree well with both a larger reduction degree in the 1. 0% Au/ CeO 2 NC600 catalyst and the differences in the spatial distribution of Ce 3+ species between the two types of facets.
The images were collected every 5°(for the CeO 2 NC) and 2°(for 0. 4% Au/CeO 2 NC and 1. 0% Au/CeO 2 NC600 samples). The tilt range varied from -65°to +55°for CeO 2 NC, -68°to +68°, and -68°to +54°in the case of 0. 4% Au/CeO 2 NC and 1. 0% Au/CeO 2 NC600 samples, respectively. To reconstruct the tomograms, the registered tilt series were aligned using the FEI Inspect 3D and TomoJ (a plug-in of ImageJ)  59  software, employing the simultaneous iterative reconstruction algorithm (SIRT) with 20 iterations. The visualization was achieved using AMIRA 4. 0. XPS data were collected with a Kratos Axis Ultra DLD instrument, equipped with monochromatized Al Kα (1486. 6 eV). Self-supported pellets of the catalysts were oxidized at 250 °C under flowing 5% O 2 /He (60 mL•min -1 ) and further evacuated under ultrahigh vacuum at 250 °C.
This pretreatment was performed in a catalytic cell coupled to the XPS spectrometer, allowing a clean transfer of the pretreated samples to the analysis chamber. The spectra were collected in the fixed analyzer transmission (FAT) mode, with pass energy of 20 eV. Surface charging effects were compensated with the Kratos coaxial neutralization system, and the binding energy (BE) scale was corrected with respect to the Ce 4+ u‴ signal at 917. 0 eV. 60  Spectra processing was performed with CasaXPS software. Temperature-programmed reduction with hydrogen (TPR-H 2 ) analyses were performed on 150 mg of catalyst using a Pfeiffer Vacuum Thermostar GSD301T1 mass spectrometer. The samples were first pretreated under 5% O 2 /He atmosphere at 500 °C for 1 h. Then, the samples were cooled down under the same atmosphere down to 150 °C.
■ ACKNOWLEDGMENTS The authors acknowledge funding from  MINECO/FEDER  ( MAT2013-40823R  and  CSD09-00013 ). Financial resources from the  European Union Seventh Framework Programme  under Grant Agreement  312483 - ESTEEM2  ( Integrated Infrastructure Initiative-I3 ) are also acknowledged. A. B. H. and X. C. thank the  Ramoń y Cajal Program  from the  Spanish Ministry of Economy. M. T. acknowledges  FPU Grants Program  from the  Spanish Ministry of Education.
4a ). The first one can be associated with the formation of radical cation species on the three triarylamine units (E 1/2 ¼ 0. 32 V) while the second one can be attributed to the corresponding dications (E 1/2 ¼ 1. 31 V). Spectroelectrochemical data were then monitored by applying increasing potentials to a solution of compound 3 in TCE (containing 0. 1 M of nBu 4 NPF 6 ). For potentials above the first oxidation potential, a clear signature corresponding to the presence of radical cations was recorded with the appearance of new absorption bands at 645 and 756 nm, as observed when previously irradiated with light (Fig. 4b ). For potentials above the second oxidation potential, no clear signature of the dication was observed, but this species has already been reported to be not stable. [15]  Finally, we checked by optical microscopy the structures of the self-assemblies obtained after oxidation, and confirmed the presence of thin fibers even when doped in the form of their radical cations (Fig.