Fabrication of stimuli-responsive nanogels for protein encapsulation and traceless release without introducing organic solvents, surfactants, or small-molecule cross-linkers

2021 ◽  
Author(s):  
Yue Zhang ◽  
Daowen Zhang ◽  
Jin-Tao Wang ◽  
Xiaojie Zhang ◽  
Yongfang Yang
Keyword(s):  
Functional Groups ◽  
Organic Solvents ◽  
Small Molecule ◽  
Organic Molecules ◽  
Secondary Structures ◽  
Stimuli Responsive ◽  
Protein Encapsulation ◽  
Small Organic Molecules

Stimuli-responsive nanogels were fabricated by reaction of proteins and polymers without using small-organic-molecules. Once the nanogels dissociated, the proteins were released with functional groups, secondary structures, and activities maintained.

Fabricating a super stable luminescent chemosensor with multi-stimuli-response to metal ions and small organic molecules through turn-on and turn-off effects

2017 ◽  
Vol 5 (18) ◽  
pp. 4511-4519 ◽  
Author(s):  
Yan Yang ◽  
Lian Chen ◽  
Feilong Jiang ◽  
Xiuyan Wan ◽  
Muxin Yu ◽  
...  
Keyword(s):  
Metal Ions ◽  
Organic Molecules ◽  
Stimuli Responsive ◽  
Small Organic Molecules ◽  
Turn On ◽  
Stimuli Response

A multi-stimuli-responsive luminescent Ln-MOF (1), with a combination of exceptionally high thermal, air and chemical stabilities, as a turn-on/turn-off chemosensor for metal ions and small organic molecules is reported.

scholarly journals C-H Functionalization via Iron-Catalyzed Carbene-Transfer Reactions

Molecules ◽  
2020 ◽  
Vol 25 (4) ◽  
pp. 880 ◽  
Author(s):  
Claire Empel ◽  
Sripati Jana ◽  
Rene M. Koenigs
Keyword(s):  
Functional Groups ◽  
Organic Molecules ◽  
Transfer Reactions ◽  
Iron Catalysts ◽  
Reaction Conditions ◽  
Carbene Complexes ◽  
Small Organic Molecules ◽  
Iron Heme ◽  
Over Time ◽  
Functionalization Reaction

The direct C-H functionalization reaction is one of the most efficient strategies by which to introduce new functional groups into small organic molecules. Over time, iron complexes have emerged as versatile catalysts for carbine-transfer reactions with diazoalkanes under mild and sustainable reaction conditions. In this review, we discuss the advances that have been made using iron catalysts to perform C-H functionalization reactions with diazoalkanes. We give an overview of early examples employing stoichiometric iron carbene complexes and continue with recent advances in the C-H functionalization of C(sp2)-H and C(sp3)-H bonds, concluding with the latest developments in enzymatic C-H functionalization reactions using iron-heme-containing enzymes.

scholarly journals Crystal structures of three functionalized chalcones: 4′-dimethylamino-3-nitrochalcone, 3-dimethylamino-3′-nitrochalcone and 3′-nitrochalcone

2020 ◽  
Vol 76 (10) ◽  
pp. 1599-1604
Author(s):  
Charlie L. Hall ◽  
Victoria Hamilton ◽  
Jason Potticary ◽  
Matthew E. Cremeens ◽  
Natalie E. Pridmore ◽  
...  
Keyword(s):  
Crystal Structure ◽  
Hydrogen Bonding ◽  
Crystal Structures ◽  
Functional Groups ◽  
Organic Molecules ◽  
Two Dimensional ◽  
Large Dataset ◽  
Acta Cryst ◽  
Small Organic Molecules ◽  
Hydrogen Bonding Interactions

The structure of three functionalized chalcones (1,3-diarylprop-2-en-1-ones), containing combinations of nitro and dimethylamino functional groups, are presented, namely, 1-[4-(dimethylamino)phenyl]-3-(3-nitrophenyl)prop-2-en-1-one, C17H16N2O3, Gp8m, 3-[3-(dimethylamino)phenyl]-1-(3-nitrophenyl)prop-2-en-1-one, C17H16N2O3, Hm7m and 1-(3-nitrophenyl)-3-phenylprop-2-en-1-one, C15H11NO3, Hm1-. Each of the molecules contains bonding motifs seen in previously solved crystal structures of functionalized chalcones, adding to the large dataset available for these small organic molecules. The structures of all three of the title compounds contain similar bonding motifs, resulting in two-dimensional planes of molecules formed via C—H...O hydrogen-bonding interactions involving the nitro- and ketone groups. The structure of Hm1- is very similar to the crystal structure of a previously solved isomer [Jing (2009). Acta Cryst. E65, o2510].

Hydration Free Energies of Organic Molecules in the FreeSolv Database Calculated with Polarized Atom In Molecules Atomic Charges and the GAFF Force Field.

2018 ◽  
Author(s):  
Maximiliano Riquelme ◽  
Alejandro Lara ◽  
David L. Mobley ◽  
Toon Vestraelen ◽  
Adelio R Matamala ◽  
...  
Keyword(s):  
Force Field ◽  
Functional Groups ◽  
Electrostatic Interactions ◽  
Organic Molecules ◽  
Force Fields ◽  
Chemical Elements ◽  
Atomic Charges ◽  
Free Energies ◽  
Molecular Systems ◽  
Solvent Model

<div>Computer simulations of bio-molecular systems often use force fields, which are combinations of simple empirical atom-based functions to describe the molecular interactions. Even though polarizable force fields give a more detailed description of intermolecular interactions, nonpolarizable force fields, developed several decades ago, are often still preferred because of their reduced computation cost. Electrostatic interactions play a major role in bio-molecular systems and are therein described by atomic point charges.</div><div>In this work, we address the performance of different atomic charges to reproduce experimental hydration free energies in the FreeSolv database in combination with the GAFF force field. Atomic charges were calculated by two atoms-in-molecules approaches, Hirshfeld-I and Minimal Basis Iterative Stockholder (MBIS). To account for polarization effects, the charges were derived from the solute's electron density computed with an implicit solvent model and the energy required to polarize the solute was added to the free energy cycle. The calculated hydration free energies were analyzed with an error model, revealing systematic errors associated with specific functional groups or chemical elements. The best agreement with the experimental data is observed for the MBIS atomic charge method, including the solvent polarization, with a root mean square error of 2.0 kcal mol<sup>-1</sup> for the 613 organic molecules studied. The largest deviation was observed for phosphor-containing molecules and the molecules with amide, ester and amine functional groups.</div>

QUBEKit: Automating the Derivation of Force Field Parameters from Quantum Mechanics

2019 ◽  
Author(s):  
Joshua Horton ◽  
Alice Allen ◽  
Leela Dodda ◽  
Daniel Cole
Keyword(s):  
Quantum Mechanics ◽  
Force Field ◽  
Organic Molecules ◽  
Force Fields ◽  
Liquid Density ◽  
Small Organic Molecules ◽  
Automated Generation ◽  
Energy Of Hydration ◽  
Novel Method ◽  
Force Field Parameters

<div><div><div><p>Modern molecular mechanics force fields are widely used for modelling the dynamics and interactions of small organic molecules using libraries of transferable force field parameters. For molecules outside the training set, parameters may be missing or inaccurate, and in these cases, it may be preferable to derive molecule-specific parameters. Here we present an intuitive parameter derivation toolkit, QUBEKit (QUantum mechanical BEspoke Kit), which enables the automated generation of system-specific small molecule force field parameters directly from quantum mechanics. QUBEKit is written in python and combines the latest QM parameter derivation methodologies with a novel method for deriving the positions and charges of off-center virtual sites. As a proof of concept, we have re-derived a complete set of parameters for 109 small organic molecules, and assessed the accuracy by comparing computed liquid properties with experiment. QUBEKit gives highly competitive results when compared to standard transferable force fields, with mean unsigned errors of 0.024 g/cm3, 0.79 kcal/mol and 1.17 kcal/mol for the liquid density, heat of vaporization and free energy of hydration respectively. This indicates that the derived parameters are suitable for molecular modelling applications, including computer-aided drug design.</p></div></div></div>

QUBEKit: Automating the Derivation of Force Field Parameters from Quantum Mechanics

2019 ◽  
Author(s):  
Joshua Horton ◽  
Alice Allen ◽  
Leela Dodda ◽  
Daniel Cole
Keyword(s):  
Quantum Mechanics ◽  
Force Field ◽  
Organic Molecules ◽  
Force Fields ◽  
Liquid Density ◽  
Small Organic Molecules ◽  
Automated Generation ◽  
Energy Of Hydration ◽  
Novel Method ◽  
Force Field Parameters

<div><div><div><p>Modern molecular mechanics force fields are widely used for modelling the dynamics and interactions of small organic molecules using libraries of transferable force field parameters. For molecules outside the training set, parameters may be missing or inaccurate, and in these cases, it may be preferable to derive molecule-specific parameters. Here we present an intuitive parameter derivation toolkit, QUBEKit (QUantum mechanical BEspoke Kit), which enables the automated generation of system-specific small molecule force field parameters directly from quantum mechanics. QUBEKit is written in python and combines the latest QM parameter derivation methodologies with a novel method for deriving the positions and charges of off-center virtual sites. As a proof of concept, we have re-derived a complete set of parameters for 109 small organic molecules, and assessed the accuracy by comparing computed liquid properties with experiment. QUBEKit gives highly competitive results when compared to standard transferable force fields, with mean unsigned errors of 0.024 g/cm3, 0.79 kcal/mol and 1.17 kcal/mol for the liquid density, heat of vaporization and free energy of hydration respectively. This indicates that the derived parameters are suitable for molecular modelling applications, including computer-aided drug design.</p></div></div></div>

scholarly journals Interaction Mechanisms between Lithium Polysulfides/Sulfide and Small Organic Molecules

ACS Omega ◽  
2021 ◽  
Vol 6 (7) ◽  
pp. 4995-5000 ◽  
Author(s):  
Jiaxiang Zhang ◽  
Junwen Yang ◽  
Ziyue Liu ◽  
Bin Zheng
Keyword(s):  
Organic Molecules ◽  
Small Organic Molecules ◽  
Interaction Mechanisms
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