Fersht, Sir Alan (Roy), (born 21 April 1943), Herchel Smith Professor of Organic Chemistry, University of Cambridge, 1988–2010; Fellow, since 1988, and Master, since 2012, Gonville and Caius College, Cambridge; Hon. Director, Cambridge Centre for Protein Engineering (formerly MRC Unit for Protein Function and Design), 1989–2010; Emeritus Group Leader, MRC Laboratory of Molecular Biology, Cambridge, since 2010

2019 ◽  
Vol 1 (1) ◽  
pp. 1-3
Author(s):  
Venki Ramakrishnan ◽  
Mejd Alsari

Venkatraman ‘Venki’ Ramakrishnan is the President of The Royal Society and Group Leader at the MRC Laboratory of Molecular Biology. In 2009 he shared the Nobel Prize in Chemistry ‘for studies of the structure and function of the ribosome’. In this interview he explains why governments should invest more in basic scientific research rather than simply on applied science and engineering. He also discusses interdisciplinarity, collaborations, and public engagement.


Molecules ◽  
2019 ◽  
Vol 24 (13) ◽  
pp. 2358
Author(s):  
Xin Liang ◽  
Wen Zhu ◽  
Zhibin Lv ◽  
Quan Zou

Molecular computing and bioinformatics are two important interdisciplinary sciences that study molecules and computers. Molecular computing is a branch of computing that uses DNA, biochemistry, and molecular biology hardware, instead of traditional silicon-based computer technologies. Research and development in this area concerns theory, experiments, and applications of molecular computing. The core advantage of molecular computing is its potential to pack vastly more circuitry onto a microchip than silicon will ever be capable of—and to do it cheaply. Molecules are only a few nanometers in size, making it possible to manufacture chips that contain billions—even trillions—of switches and components. To develop molecular computers, computer scientists must draw on expertise in subjects not usually associated with their field, including organic chemistry, molecular biology, bioengineering, and smart materials. Bioinformatics works on the contrary; bioinformatics researchers develop novel algorithms or software tools for computing or predicting the molecular structure or function. Molecular computing and bioinformatics pay attention to the same object, and have close relationships, but work toward different orientations.


Author(s):  
Carlos Eduardo Sequeiros-Borja ◽  
Bartłomiej Surpeta ◽  
Jan Brezovsky

Abstract Progress in technology and algorithms throughout the past decade has transformed the field of protein design and engineering. Computational approaches have become well-engrained in the processes of tailoring proteins for various biotechnological applications. Many tools and methods are developed and upgraded each year to satisfy the increasing demands and challenges of protein engineering. To help protein engineers and bioinformaticians navigate this emerging wave of dedicated software, we have critically evaluated recent additions to the toolbox regarding their application for semi-rational and rational protein engineering. These newly developed tools identify and prioritize hotspots and analyze the effects of mutations for a variety of properties, comprising ligand binding, protein–protein and protein–nucleic acid interactions, and electrostatic potential. We also discuss notable progress to target elusive protein dynamics and associated properties like ligand-transport processes and allosteric communication. Finally, we discuss several challenges these tools face and provide our perspectives on the further development of readily applicable methods to guide protein engineering efforts.


2019 ◽  
Vol 2019 ◽  
pp. 1-15 ◽  
Author(s):  
Lucas F. Ribeiro ◽  
Vanesa Amarelle ◽  
Liliane F. C. Ribeiro ◽  
María-Eugenia Guazzaroni

All biosensing platforms rest on two pillars: specific biochemical recognition of a particular analyte and transduction of that recognition into a readily detectable signal. Most existing biosensing technologies utilize proteins that passively bind to their analytes and therefore require wasteful washing steps, specialized reagents, and expensive instruments for detection. To overcome these limitations, protein engineering strategies have been applied to develop new classes of protein-based sensor/actuators, known as protein switches, responding to small molecules. Protein switches change their active state (output) in response to a binding event or physical signal (input) and therefore show a tremendous potential to work as a biosensor. Synthetic protein switches can be created by the fusion between two genes, one coding for a sensor protein (input domain) and the other coding for an actuator protein (output domain) by domain insertion. The binding of a signal molecule to the engineered protein will switch the protein function from an “off” to an “on” state (or vice versa) as desired. The molecular switch could, for example, sense the presence of a metabolite, pollutant, or a biomarker and trigger a cellular response. The potential sensing and response capabilities are enormous; however, the recognition repertoire of natural switches is limited. Thereby, bioengineers have been struggling to expand the toolkit of molecular switches recognition repertoire utilizing periplasmic binding proteins (PBPs) as protein-sensing components. PBPs are a superfamily of bacterial proteins that provide interesting features to engineer biosensors, for instance, immense ligand-binding diversity and high affinity, and undergo large conformational changes in response to ligand binding. The development of these protein switches has yielded insights into the design of protein-based biosensors, particularly in the area of allosteric domain fusions. Here, recent protein engineering approaches for expanding the versatility of protein switches are reviewed, with an emphasis on studies that used PBPs to generate novel switches through protein domain insertion.


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