scholarly journals Lysis of membrane lipids promoted by small organic molecules: Reactivity depends on structure but not lipophilicity

2020 ◽  
Vol 6 (17) ◽  
pp. eaaz8598
Author(s):  
Hannah M. Britt ◽  
Aruna S. Prakash ◽  
Sanna Appleby ◽  
Jackie A. Mosely ◽  
John M. Sanderson

Several organic molecules of low molecular weight (<150 Da) are demonstrated to have substantial membrane-lytic potential despite having a low predicted lipophilicity (logD < 1 at neutral pH). In aqueous liposome dispersions, 38 aromatic compounds were tested for their ability to either promote lipid hydrolysis or directly participate in chemical reactions with lipid molecules. Behaviors observed included acyl transfer from the lipid to form a lipidated compound, both with and without concomitant lysolipid formation; increases in the rate of lipid hydrolysis without lipidation; and no reactivity. The variation in activity, including a notably higher activity for heterocycles such as amino-substituted benzimidazoles and indazoles, demonstrates the potential to predict or “design-in” lytic activity once the rules that govern reactivity are better understood. The nature of this chemical instability has significant ramifications for the use or presence of lipids in diverse fields such as materials chemistry, food chemistry, and cell physiology.

2019 ◽  
Vol 7 (13) ◽  
pp. 11062-11068 ◽  
Author(s):  
Chuanjiang Jian ◽  
Ning Tao ◽  
Long Xu ◽  
Miaochang Liu ◽  
Xiaobo Huang ◽  
...  

Author(s):  
Carmen Socaciu

The metabolome (by analogy to genome, transcriptome, proteome) represents generally the total metabolite pool of a living organism, the entire complement of all the low molecular weight metabolites (small organic molecules, i.e. sugars, amino acids, flavours, acids, pigments, hormones) in biological samples such as a leaf, fruit, food, blood, etc. Metabolomics refers either to plants, microorganisms, food or animal and human organisms. Different specific aspects of fingerprinting, metabolic profile and metabolite target analysis are presented. A critical discussion of methodologies used in metabolomics is presented. Finally, there are mentioned the advantages offered by metabolomics versus genomics and their applications, i.e. a tremendous number of measurements to be done in short time and with high resolution and sensitivity, to realize “maps” of plants and their derived products.


2019 ◽  
Vol 6 (7) ◽  
pp. 936-941 ◽  
Author(s):  
Tangxin Xiao ◽  
Lixiang Xu ◽  
Jie Wang ◽  
Zheng-Yi Li ◽  
Xiao-Qiang Sun ◽  
...  

The supramolecular self-folding of UPy-based monomers with low molecular weight driven by multiple non-covalent interactions has been developed.


2020 ◽  
Author(s):  
Colin R. Bridges ◽  
Andryj M. Borys ◽  
Vanessa Béland ◽  
Joshua R. Gaffen ◽  
Thomas Baumgartner

Low molecular weight organic molecules that can accept multiple electrons at high<br>reduction potentials are sought after as electrode materials for high-energy sustainable batteries. To date their synthesis has been difficult, and organic scaffolds for electron donors significantly outnumber electron acceptors. Herein, we report two highly electron deficient phosphaviologen derivatives from a phosphorus-bridged 4,4-bipyridine and characterize their electrochemical properties. Phosphaviologen sulfide (PVS) and P-methyl phosphaviologen (PVM) accept two and three electrons at high reduction potentials, respectively. PVM can reversibly accept 3 electrons between 3-3.6 V vs. Li/Li+ with an equivalent molecular weight of 102 g/(mol e-) (262 mAh/g), making it a promising scaffold for sustainable organic electrode materials having high specific energy densities.


Author(s):  
Joshua Horton ◽  
Alice Allen ◽  
Leela Dodda ◽  
Daniel Cole

<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>


Author(s):  
Joshua Horton ◽  
Alice Allen ◽  
Leela Dodda ◽  
Daniel Cole

<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>


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

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