scholarly journals Semi-Rigid (Aminomethyl) Piperidine-Based Pentadentate Ligands for Mn(II) Complexation

Molecules ◽  
2021 ◽  
Vol 26 (19) ◽  
pp. 5993
Author(s):  
Jonathan Martinelli ◽  
Edoardo Callegari ◽  
Zsolt Baranyai ◽  
Alberto Fraccarollo ◽  
Maurizio Cossi ◽  
...  
Keyword(s):  
Md Simulations ◽  
17O Nmr ◽  
Equilibrium Studies ◽  
Coordination Environment ◽  
Pentadentate Ligands ◽  
Tertiary Amino ◽  
Coordinated Water ◽  
Oxygen Donors ◽  
Complexation Equilibrium ◽  
Good Agreement

Two pentadentate ligands built on the 2-aminomethylpiperidine structure and bearing two tertiary amino and three oxygen donors (three carboxylates in the case of AMPTA and two carboxylates and one phenolate for AMPDA-HB) were developed for Mn(II) complexation. Equilibrium studies on the ligands and the Mn(II) complexes were carried out using pH potentiometry, 1H-NMR spectroscopy and UV-vis spectrophotometry. The Mn complexes that were formed by the two ligands were more stable than the Mn complexes of other pentadentate ligands but with a lower pMn than Mn(EDTA) and Mn(CDTA) (pMn for Mn(AMPTA) = 7.89 and for Mn(AMPDA-HB) = 7.07). 1H and 17O-NMR relaxometric studies showed that the two Mn-complexes were q = 1 with a relaxivity value of 3.3 mM−1 s−1 for Mn(AMPTA) and 3.4 mM−1 s−1 for Mn(AMPDA-HB) at 20 MHz and 298 K. Finally, the geometries of the two complexes were optimized at the DFT level, finding an octahedral coordination environment around the Mn2+ ion, and MD simulations were performed to monitor the distance between the Mn2+ ion and the oxygen of the coordinated water molecule to estimate its residence time, which was in good agreement with that determined using the 17O NMR data.

Hydrothermal Synthesis and Crystal Structure of a One-dimensional Cobalt (II) Coordination Polymer with Two Organic Ligands

2014 ◽  
Vol 69 (6) ◽  
pp. 699-703
Author(s):  
You-Jing Huang-Fu ◽  
Hui Pan ◽  
Xi-Cai Hao ◽  
Yan Bai ◽  
Dong-Bin Dang
Keyword(s):  
Coordination Polymer ◽  
Supramolecular Network ◽  
Coordination Environment ◽  
Synthesis And Crystal Structure ◽  
Distorted Octahedral ◽  
Vis Spectroscopy ◽  
A Chain ◽  
Coordinated Water ◽  
Oxygen Donors ◽  
Distorted Octahedral Coordination Environment

A new Co(II) coordination polymer [Co(Hdpa)2(dpdo)(H2O)2] (1) (H2dpa=2,2`-biphenyldicarboxylic acid, dpdo=4,4`-bipyridine-N,N`-dioxide) has been synthesized and characterized by IR and UV=Vis spectroscopy, elemental analysis, and single-crystal X-ray structure analysis. The Co(II) atom has a distorted octahedral coordination environment with a set of oxygen donors from two Hdpa- ligands, two dpdo ligands and two coordinated water molecules. Adjacent cobalt centers are bridged by dpdo ligands thereby generating a chain. In the solid state, the chains further interact with each other and form a 3D supramolecular network via C-H···π interactions and multiform hydrogen bonds.

scholarly journals Novel Pyrazolo[3,4-c]pyridine Antagonists with Nanomolar affinity for A1 / A3 Adenosine Receptors: Binding Kinetics and Exploration of their Binding Profile Using Mutagenesis Experiments, MD simulations and TI/MD calculations

2021 ◽  
Author(s):  
Margarita Stampelou ◽  
Anna Suchankova ◽  
Eva Tzortzini ◽  
Lakshiv Dhingra ◽  
Kerry Barkan ◽  
...  
Keyword(s):  
Drug Design ◽  
Transmembrane Helix ◽  
Rank Correlation ◽  
Membrane System ◽  
Md Simulations ◽  
Dissociation Rate ◽  
The Novel ◽  
Free Energies ◽  
Electronegative Group ◽  
Good Agreement

Drugs targeting the four adenosine receptor (AR) subtypes can provide “soft" treatment of various significant diseases. Even for the two experimentally resolved AR subtypes the description of the orthosteric binding area and structure-activity relationships of ligands remains a demanding task due to the high similar amino acids sequence but also the broadness and flexibility of the ARs binding area. The identification of new pharmacophoric moieties and nanomolar leads and the exploration of their binding area with mutagenesis and state-of-the-art computational methods useful also for drug design purposes remains a challenging aim for all ARs. Here, we identified several low nanomolar ligands and potent competitive antagonists against A1R / A3R, containing the novel pyrazolo[3,4-c]pyridine pharmacophore for ARs, from a screen of an in-house library of only 52 compounds, originally designed for anti-proliferative activity. We identified L2-L10, A15, A17 with 3-aryl, 7-anilino and a electronegative group at 5-position as low micromolar to low nanomolar A1R / A3R antagonists. A17 has for A1R Kd = 5.62 nM and a residence time (RT) 41.33 min and for A3R Kd = 13.5 nM, RT = 47.23 min. The kinetic data showed that compared to the not potent or mediocre congeners the active compounds have similar association, for example at A1R Kon = 13.97 x106 M-1 (A17) vs Kon = 3.36 x106 M-1 (A26) but much lower dissociation rate Koff = 0.024 min-1 (A17) vs 0.134 min-1 (A26). Using molecular dynamics (MD) simulations and mutagenesis experiments we investigated the binding site of A17 showing that it can interact with an array of residues in transmembrane helix 5 (TM5), TM6, TM7 of A1R or A3R including residues E5.30, E5.28, T7.35 in A1R instead of Q5.28, V5.30 , L7.35 in A3R. A striking observation for drug design purposes is that for L2506.51A the binding affinity of A17 significantly increased at A1R. A17 provides a lead representative of a promising series and by means of the Thermodynamics Integration coupled with MD simulations (TI/MD) method, first applied here on whole GPCR- membrane system and showing a very good agreement between calculated and experimental relative binding free energies for A1R and A3R (spearman rank correlation p = 0.82 and 0.84, respectively), and kinetic experiments can lead to ligands with improved profile against ARs.

scholarly journals Molecular Dynamics Modellization and Simulation of Water Diffusion through Plant Cutin

1999 ◽  
Vol 54 (11) ◽  
pp. 896-902 ◽  
Author(s):  
Antonio Matas ◽  
Antonio Heredia
Keyword(s):  
Experimental Data ◽  
Molecular Dynamics ◽  
Structural Information ◽  
Md Simulations ◽  
Water Molecules ◽  
Plant Cuticle ◽  
X Ray Diffraction ◽  
Cross Link ◽  
X Ray ◽  
Good Agreement

Abstract A theoretical molecular modelling study has been conducted for cutin, the biopolyester that forms the main structural component of the plant cuticle. Molecular dynamics (MD) simulations, extended over several ten picoseconds, suggests that cutin is a moderately flexible netting with motional constraints mainly located at the cross-link sites of functional ester groups. This study also gives structural information essentially in accordance with previously reported experimental data, obtained from X -ray diffraction and nuclear magnetic resonance experiments. MD calculations were also performed to simulate the diffusion of water mole­cules through the cutin biopolymer. The theoretical analysis gives evidence that water perme­ation proceedes by a “hopping mechanism”. Coefficients for the diffusion of the water molecules in cutin were obtained from their mean-square displacements yielding values in good agreement with experimental data.

scholarly journals Electronic Effects of the Substituents on Relaxometric and CEST Behaviour of Ln(III)-DOTA-Tetraanilides

Inorganics ◽  
2019 ◽  
Vol 7 (4) ◽  
pp. 43
Author(s):  
Valeria Lagostina ◽  
Loredana Leone ◽  
Fabio Carniato ◽  
Giuseppe Digilio ◽  
Lorenzo Tei ◽  
...  
Keyword(s):  
Exchange Rate ◽  
Water Exchange ◽  
Chemical Exchange ◽  
Chemical Exchange Saturation Transfer ◽  
Saturation Transfer ◽  
Electronic Effects ◽  
17O Nmr ◽  
Water Exchange Rate ◽  
Coordinated Water ◽  
The Eu

Three different 1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetamide (DOTAM) derivatives bearing as amide N-substituents phenyl, p-methoxyphenyl and p-ethylbenzoate groups were synthesized and the 1H and 17O NMR relaxometric behaviour of the Gd(III)-chelates and chemical exchange saturation transfer (CEST) effect of the Eu(III) complexes were evaluated. The electronic properties of the substituents were shown to strongly influence the coordinated water exchange rate (kex), resulting in five times faster kex for the electron donating phenylmethoxy group compared to the electron withdrawing ethylbenzoate group.

Aqua{5,5′-dihydroxy-2,2′-[1,2-phenylenebis(nitrilomethylidyne)]diphenolato-κ4 O,N,N′,O′}zinc(II) trihydrate

2007 ◽  
Vol 63 (11) ◽  
pp. m2838-m2839 ◽  
Author(s):  
Naser Eltaher Eltayeb ◽  
Siang Guan Teoh ◽  
Suchada Chantrapromma ◽  
Hoong-Kun Fun ◽  
Kamarulazizi Ibrahim
Keyword(s):  
Schiff Base ◽  
Dihedral Angles ◽  
Water Molecules ◽  
Asymmetric Unit ◽  
Apical Position ◽  
Coordination Environment ◽  
Tetradentate Schiff Base ◽  
Solvent Water ◽  
Benzene Rings ◽  
Coordinated Water

In the title complex, [Zn(C20H14N2O4)(H2O)]·3H2O, the ZnII center is in an approximately square-pyramidal coordination environment with the two N and two O atoms of the tetradentate Schiff base ligand forming the basal plane and the coordinated water molecule in the apical position. Three solvent water molecules complete the asymmetric unit. The dihedral angles between the two outer benzene rings of the Schiff base and the central benzene ring are 12.64 (14) and 17.25 (14)°. In the crystal structure, intermolecular O—H...O hydrogen bonds link the molecules into sheets parallel to the ab plane.

Heat Transfer Predictions Using Accommodation Coefficients for a Dense Gas in a Micro/Nano-Channel

2008 ◽  
Author(s):  
S. V. Nedea ◽  
A. J. Markvoort ◽  
P. Spijker ◽  
A. A. van Steenhoven
Keyword(s):  
Heat Transfer ◽  
Heat Flux ◽  
Md Simulations ◽  
Heat Fluxes ◽  
Dense Gas ◽  
Nano Channel ◽  
Accommodation Coefficients ◽  
Gas Interactions ◽  
Wall Interactions ◽  
Good Agreement

The influence of gas-gas and gas-wall interactions on the heat flux predictions for a dense gas confined between two parallel walls of a micro/nano-channel is realized using combined Monte Carlo (MC) and Molecular Dynamics (MD) techniques. The accommodation coefficients are computed from explicit MD simulations. These MD coefficients are then used as effective accommodation coefficients in Maxwell-like boundary conditions in MC simulations. We find that heat flux predictions from MC based on these coefficients compare good with the results of explicit simulations except the case when there are hydrophobic gas-wall/gas-gas interactions. For this case an artificial wall was introduced in order to measure these MD accommodation coefficients at this artificial border. Good agreement is found then for both hydrophilic and hydrophobic gas-wall interactions and we show this by confronting the heat fluxes from explicit MD simulations with the the MC heat flux predictions for all the generic accommodation coefficients.

scholarly journals Building Machine Learning Force Fields of Proteins with Fragment-Based Approach and Transfer Learning

2021 ◽  
Author(s):  
Zheng Cheng ◽  
Jiahui Du ◽  
Lei Zhang ◽  
Jing Ma ◽  
Wei Li ◽  
...  
Keyword(s):  
Machine Learning ◽  
Density Functional ◽  
Force Fields ◽  
Density Functional Theory Calculations ◽  
Md Simulations ◽  
Target System ◽  
Functional Theory ◽  
Protein Functions ◽  
Data Library ◽  
Good Agreement

<p>Molecular dynamic (MD) simulation plays an essential role in understanding protein functions at atomic level. At present, MD simulations on proteins are mainly based on classical force fields. However, the accuracy of classical force fields for proteins is still insufficient for accurate descriptions of their structures and dynamical properties. Here we present a novel protocol to construct machine learning force field (MLFF) for a given protein with full quantum mechanics (QM) accuracy. In this protocol, the energy of the target system is obtained by fitting energies of its various subsystems constructed with the generalized energy-based fragmentation (GEBF) approach. To facilitate the construction of MLFF for various proteins, a protein’s data library is created to store all data of subsystems generated from trained proteins. With this protein’s data library, for a new protein only its subsystems with new topological types are required for the construction of the corresponding MLFF. This protocol is illustrated with two polypeptides, 4ZNN and 1XQ8 segment, as examples. The energies and forces predicted from this MLFF are in good agreement with those from density functional theory calculations, and dihedral angle distributions from GEBF-MLFF MD simulations can also well reproduce those from <i>ab initio</i> MD simulations. Therefore, this GEBF-ML protocol is expected to be an efficient and systematic way to build force fields for proteins and other biological systems with QM accuracy.<b></b></p>

scholarly journals Characterizing Moisture Uptake and Plasticization Effects of Water on Amorphous Amylose Starch Models Using Molecular Dynamics Methods

2020 ◽  
Author(s):  
Jeffrey Sanders ◽  
Mayank Misra ◽  
Thomas JL Mustard ◽  
David J. Giesen ◽  
Teng Zhang ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Moisture Content ◽  
Force Field ◽  
Moisture Sorption ◽  
Md Simulations ◽  
A Value ◽  
Moisture Sorption Isotherm ◽  
Molecular Dynamics Methods ◽  
Grand Canonical ◽  
Good Agreement

<p>Dynamics and thermophysical properties of amorphous starch were explored using molecular dynamics (MD) simulations. Using the OPLS3e force field, simulations of short amylose chains in water were performed to determine force field accuracy. Using well-tempered metadynamics, a free energy map of the two glycosidic angles of an amylose molecule was constructed and compared with other modern force fields. Good agreement of torsional sampling for both solvated and amorphous amylose starch models was observed. Using combined grand canonical Monte Carlo (GCMC)/MD simulations, a moisture sorption isotherm curve is predicted along with temperature dependence. Concentration-dependent activation energies for water transport agree quantitatively with previous experiments. Finally, the plasticization effect of moisture content on amorphous starch was investigated. Predicted glass transition temperature (Tg) depression as a function of moisture content is in line with experimental trends. Further, our calculations provide a value for the dry Tg for amorphous starch, a value which no experimental value is available.</p><div><br></div>

scholarly journals catena-Poly[[diaqua(1H-imidazo[4,5-f][1,10]phenanthroline)cobalt(II)]-μ-sulfato]

2009 ◽  
Vol 65 (6) ◽  
pp. m618-m618 ◽  
Author(s):  
Jian Yu
Keyword(s):  
Three Dimensional ◽  
Title Complex ◽  
Water Molecules ◽  
Coordination Environment ◽  
One Dimensional ◽  
Distorted Octahedral Coordination ◽  
Dimensional Network ◽  
Distorted Octahedral ◽  
Coordinated Water ◽  
Distorted Octahedral Coordination Environment

The CoIIion in the title complex, [Co(SO4)(C13H8N4)(H2O)2]n, has a slightly distorted octahedral coordination environment formed by two O atoms from two symmetry-related bridging sulfate ligands, two N atoms from a bis-chelating 1H-imidazo[4,5-f][1,10]phenanthroline (IPL) ligand and two O atoms from coordinated water molecules. The bridging sulfate ligands connect CoIIions to form a one-dimensional chain along theb-axis direction. In the crystal structure, intermolecular O—H...O, O—H...N and N—H...O hydrogen bonds link the chains into a three-dimensional network.

Poly[diaquadi-μ6-succinato-μ5-succinato-dierbium(III)]

2006 ◽  
Vol 62 (4) ◽  
pp. m738-m740 ◽  
Author(s):  
Gui-Ying Dong ◽  
Guang-Hua Cui ◽  
Jin Lin
Keyword(s):  
Crystal Structure ◽  
Hydrogen Bonds ◽  
Title Compound ◽  
Three Dimensional ◽  
Water Molecules ◽  
Asymmetric Unit ◽  
Coordination Environment ◽  
Trigonal Prismatic Coordination ◽  
Coordinated Water ◽  
Trigonal Prismatic

In the title compound, [Er2(C4H4O4)3(H2O)2] n , the asymmetric unit consists of two ErIII cations, three succinate anions and two coordinated water molecules. Both ErIII ions are in a tricapped trigonal–prismatic coordination environment. The Er atoms are bridged into a three-dimensional framework by succinate anions, which exhibit anti and gauche conformations with different coordination modes. The crystal structure is stabilized by O—H...O hydrogen bonds [O...O = 2.715 (8)–2.936 (8) Å].

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