Powerful Protein Binders from Designed Polypeptides and Small Organic Molecules-A General Concept for Protein Recognition

2011 ◽  
Vol 123 (8) ◽  
pp. 1863-1867 ◽  
Author(s):  
Lotta T. Tegler ◽  
Guillaume Nonglaton ◽  
Frank Büttner ◽  
Karin Caldwell ◽  
Tony Christopeit ◽  
...  
2011 ◽  
Vol 50 (8) ◽  
pp. 1823-1827 ◽  
Author(s):  
Lotta T. Tegler ◽  
Guillaume Nonglaton ◽  
Frank Büttner ◽  
Karin Caldwell ◽  
Tony Christopeit ◽  
...  

2015 ◽  
Vol 65 (2) ◽  
pp. 105-116 ◽  
Author(s):  
Hanqing Liu ◽  
Zhigang Tu ◽  
Fan Feng ◽  
Haifeng Shi ◽  
Keping Chen ◽  
...  

Abstract A virosome is an innovative hybrid drug delivery system with advantages of both viral and non-viral vectors. Studies have shown that a virosome can carry various biologically active molecules, such as nucleic acids, peptides, proteins and small organic molecules. Targeted drug delivery using virosome-based systems can be achieved through surface modifications of virosomes. A number of virosome- -based prophylactic and therapeutic products with high safety profiles are currently available in the market. Cancer treatment is a big battlefield for virosome-based drug delivery systems. This review provides an overview of the general concept, preparation procedures, working mechanisms, preclinical studies and clinical applications of virosomes in cancer treatment.


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

Author(s):  
Mohamed R. Rizk ◽  
Muhammad G. Gamal ◽  
Amina Mazhar ◽  
Mohamed El-Deab ◽  
Bahgat El-Anadouli

In this work, we report a single-step preparation of porous Ni-based foams thin layer atop Cu substrate via a facile dynamic hydrogen bubble template technique (DHBT). The prepared porous Ni-based...


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