Molecular Biology

2016 ◽  
Author(s):  
Aysha Divan ◽  
Janice Royds
Keyword(s):  
Synthetic Biology ◽  
Personalized Medicine ◽  
Molecular Biology ◽  
Dna Fingerprinting ◽  
Genetically Modified Organisms ◽  
Building Blocks ◽  
New Drugs ◽  
Human History ◽  
Short Introduction ◽  
Wide Range

Molecular biology is the story of the molecules of life, their relationships, and how these interactions are controlled. Its applications are wide and growing; the power of molecular biology can now be harnessed to treat diseases, solve crimes, map human history, and produce genetically modified organisms and crops. Starting with the building blocks established by Darwin, Wallace, and Mendel, and the discovery of the structure of DNA in 1953, Molecular Biology: A Very Short Introduction considers the wide range of applications for molecular biology today, including the development of new drugs and DNA fingerprinting, and looks forward to two key areas of evolving research: personalized medicine and synthetic biology.

scholarly journals Engineering a Minimal Cloning Vector from a pUC18 Plasmid Backbone with an Extended Multiple Cloning Site

2018 ◽  
Author(s):  
Jens Staal ◽  
Wouter De Schamphelaire ◽  
Rudi Beyaert
Keyword(s):  
Synthetic Biology ◽  
Molecular Biology ◽  
Restriction Enzyme ◽  
Essential Role ◽  
Building Blocks ◽  
Cloning Vector ◽  
Multiple Cloning Site ◽  
Unique Restriction ◽  
Plasmid Backbone

Minimal plasmids play an essential role in many intermediate steps in molecular biology. They can for example be used to assemble building blocks in synthetic biology or be used as intermediate cloning plasmids that are ideal for PCR-based mutagenesis methods. A small backbone also opens up for additional unique restriction enzyme cloning sites. Here we describe the generation of pICOz, a 1185 bp fully functional high-copy cloning plasmid with an extended multiple cloning site (MCS). To our knowledge, this is the smallest high-copy cloning vector ever described.

DNA fingerprinting.

1989 ◽  
Vol 35 (9) ◽  
pp. 1832-1837 ◽  
Author(s):  
A H Cawood
Keyword(s):  
Molecular Biology ◽  
Dna Fingerprinting ◽  
Validation Studies ◽  
Population Biology ◽  
Dna Fingerprints ◽  
Forensic Biology ◽  
Human Dna ◽  
Wide Range ◽  
Individual Specificity ◽  
Mode Of Inheritance

Abstract Hypervariable tandem-repetitive minisatellite regions of human DNA can be used to generate individual-specific DNA fingerprints. Validation studies have demonstrated the reliability of the analysis, the mode of inheritance of the minisatellites, and the unparalleled degree of individual specificity. The uses of hypervariable probes in forensic biology, paternity testing, and the resolution of a wide range of problems in genetics, molecular biology, population biology, and medicine are illustrated.

scholarly journals La Biología Sintética; reto biotecnológico y bioético en las Ciencias de la Vida

2020 ◽  
Author(s):  
Ignacio Ventura ◽  
Isaias Sanmartín ◽  
Ana Lloret ◽  
Francisco Revert ◽  
Jesús Ángel Prieto
Keyword(s):  
Synthetic Biology ◽  
Molecular Biology ◽  
Genetically Modified Organisms ◽  
Genetically Modified ◽  
The Other ◽  
Active Principle ◽  
Artificial Cells ◽  
In The Wild ◽  
The Difference ◽  
Environmental Level

Synthetic biology represents a scientific and bioethical challenge for the future, both at the environmental level, as well as in the human and other species improvement. Therefore, the work will mainly address two aspects. The synthesis in the laboratory of artificial cells for the manufacture of a pharmaceutical active principle and, on the other hand, the bioethical reflection on the potential of these techniques, noting the difference in the limits of the synthesis of life and creation of life. Currently, there are an estimated 1.7 million known species out of the estimated 14 million in the wild. In the last 10 years, more than 3,000 patents have been generated for genetically modified organisms. We have advanced in the fields of bioengineering for the improvement of beer-producing species, bakeries, etc. provide to the advancement of molecular biology.

scholarly journals Engineering a Minimal 1185 Bp Cloning Vector from a Puc18 Plasmid Backbone with an Extended Multiple Cloning Site

2018 ◽  
Author(s):  
Jens Staal ◽  
Wouter De Schamphelaire ◽  
Rudi Beyaert
Keyword(s):  
Synthetic Biology ◽  
Molecular Biology ◽  
Restriction Enzyme ◽  
Essential Role ◽  
Building Blocks ◽  
Cloning Vector ◽  
Multiple Cloning Site ◽  
Unique Restriction ◽  
Plasmid Backbone

Minimal plasmids play an essential role in many intermediate steps in molecular biology. They can for example be used to assemble building blocks in synthetic biology or be used as intermediate cloning plasmids that are ideal for PCR-based mutagenesis methods. A small backbone also opens up for additional unique restriction enzyme cloning sites. Here we describe the generation of a ~1kb fully functional cloning plasmid with an extended multiple cloning site (MCS). To our knowledge, this is the smallest high-copy cloning vector ever described.

scholarly journals 25 years and still going strong: 2′-O-(pyren-1-yl)methylribonucleotides – versatile building blocks for applications in molecular biology, diagnostics and materials science

2017 ◽  
Vol 15 (46) ◽  
pp. 9760-9774 ◽  
Author(s):  
Patrick J. Hrdlicka ◽  
Saswata Karmakar
Keyword(s):  
Molecular Biology ◽  
Materials Science ◽  
Building Blocks ◽  
Biophysical Properties ◽  
The Past ◽  
Wide Range

This review highlights the synthesis, biophysical properties, and wide range of applications of oligonucleotides modified with 2′-O-(pyren-1-yl)methyl-RNA monomers reported over the past 25 years.

scholarly journals A Generalized Similarity Metric for Predicting Peptide Binding Affinity

2019 ◽  
Author(s):  
Jacob Rodriguez ◽  
Siddharth Rath ◽  
Jonathan Francis-Landau ◽  
Yekta Demirci ◽  
Burak Berk Üstündağ ◽  
...  
Keyword(s):  
Amino Acids ◽  
Amino Acid ◽  
Binding Affinity ◽  
Building Blocks ◽  
Similarity Score ◽  
New Drugs ◽  
Similarity Metric ◽  
Spearman Rank ◽  
Wide Range ◽  
Similarity Matrices

AbstractThe ability to capture the relationship between similarity and functionality would enable the predictive design of peptide sequences for a wide range of implementations from developing new drugs to molecular scaffolds in tissue engineering and biomolecular building blocks in nanobiotechnology. Similarity matrices are widely used for detecting sequence homology but depend on the assumption that amino acid mutational frequencies reflected by each matrix are relevant to the system in which they are applied. Increasingly, neural networks and other statistical learning models solve problems related to functional prediction but avoid using known features to circumvent unconscious bias. We demonstrated an iterative alignment method that enhances predictive power of similarity matrices based on a similarity metric, the Total Similarity Score. A generalized method is provided for application to amino acid sequences from inorganic and organic systems by benchmarking it on the debut quartz-binder set and 3 peptide-protein sets from the Immune Epitope Database. Pearson and Spearman Rank Correlations show that by treating the gapless Total Similarity Score as a predictor of relative binding affinity, prediction of test data has a 0.5-0.7 Pearson and Spearman Rank correlation. with respect to size of the dataset. Since the benchmarks used herein are from a solid-binding peptide and a protein-peptide system, our proposed method could prove to be a highly effective general approach for establishing the predictive sequence-function relationships of among the peptides with different sequences and lengths in a wide range of biotechnology, nanomedicine and bioinformatics applications.Author SummaryThe significance of this work is to expand the applicability of a known metric for describing the function of tiny proteins also called peptides. The Total Similarity Score (TSS) can describe how ‘similar’ a peptide, or a group of peptides are to another group of sequences with a known or suspected function. A peptide/group of peptides will always have a high TSS if it contains the same or ‘similar’ amino acids in the same positions. This metric can therefore be used to select peptides for useful functions based purely on conserved amino acids in unknown positions. The greedy search algorithm used to learn how similar amino acids are to each other has been shown to be marginally effective in this larger dataset. Therefore, we argue that the TSS metric is a highly useful one for predicting peptide affinity but a different machine learning algorithm should be applied to make full use of it.

Factors Affecting Molecular Self-Assembly and Its Mechanism

2012 ◽  
Vol 9 (1) ◽  
pp. 43 ◽  
Author(s):  
Hueyling Tan
Keyword(s):  
Self Assembly ◽  
Building Blocks ◽  
Molecular Engineering ◽  
Molecular Structures ◽  
Polymer Science ◽  
New Approach ◽  
Factors Affecting ◽  
Dna Structures ◽  
Self Assembling ◽  
Wide Range

Molecular self-assembly is ubiquitous in nature and has emerged as a new approach to produce new materials in chemistry, engineering, nanotechnology, polymer science and materials. Molecular self-assembly has been attracting increasing interest from the scientific community in recent years due to its importance in understanding biology and a variety of diseases at the molecular level. In the last few years, considerable advances have been made in the use ofpeptides as building blocks to produce biological materials for wide range of applications, including fabricating novel supra-molecular structures and scaffolding for tissue repair. The study ofbiological self-assembly systems represents a significant advancement in molecular engineering and is a rapidly growing scientific and engineering field that crosses the boundaries ofexisting disciplines. Many self-assembling systems are rangefrom bi- andtri-block copolymers to DNA structures as well as simple and complex proteins andpeptides. The ultimate goal is to harness molecular self-assembly such that design andcontrol ofbottom-up processes is achieved thereby enabling exploitation of structures developed at the meso- and macro-scopic scale for the purposes oflife and non-life science applications. Such aspirations can be achievedthrough understanding thefundamental principles behind the selforganisation and self-synthesis processes exhibited by biological systems.

Stereospecific, Palladium-catalyzed C(sp3)–H Alkenylation and Alkynylation of a Proline Derivative Enabled by 8-Aminoquinoline as a Directing Group

2020 ◽  
Author(s):  
Aleksandra Balliu ◽  
Aaltje Roelofje Femmigje Strijker ◽  
Michael Oschmann ◽  
Monireh Pourghasemi Lati ◽  
Oscar Verho
Keyword(s):  
Carboxylic Acid ◽  
Building Blocks ◽  
Wide Range ◽  
Palladium Catalyzed ◽  
Directing Group ◽  
High Yields ◽  
Vinyl Iodides ◽  
Initial Results

<p>In this preprint, we present our initial results concerning a stereospecific Pd-catalyzed protocol for the C3 alkenylation and alkynylation of a proline derivative carrying the well utilized 8‑aminoquinoline directing group. Efficient C–H alkenylation was achieved with a wide range of vinyl iodides bearing different aliphatic, aromatic and heteroaromatic substituents, to furnish the corresponding C3 alkenylated products in good to high yields. In addition, we were able show that this protocol can also be used to install an alkynyl group into the pyrrolidine scaffold, when a TIPS-protected alkynyl bromide was used as the reaction partner. Furthermore, two different methods for the removal of the 8-aminoquinoline auxiliary are reported, which can enable access to both <i>cis</i>- and <i>trans</i>-configured carboxylic acid building blocks from the C–H alkenylation products.</p>

Efficient Prediction of Structural and Electronic Properties of Hybrid 2D Materials Using DFT and Machine Learning

2018 ◽  
Author(s):  
Sherif Tawfik ◽  
Olexandr Isayev ◽  
Catherine Stampfl ◽  
Joseph Shapter ◽  
David Winkler ◽  
...  
Keyword(s):  
Machine Learning ◽  
Band Gap ◽  
Density Functional ◽  
2D Materials ◽  
Van Der Waals ◽  
Building Blocks ◽  
Machine Learning Techniques ◽  
Interlayer Distance ◽  
Computational Screening ◽  
Wide Range

Materials constructed from different van der Waals two-dimensional (2D) heterostructures offer a wide range of benefits, but these systems have been little studied because of their experimental and computational complextiy, and because of the very large number of possible combinations of 2D building blocks. The simulation of the interface between two different 2D materials is computationally challenging due to the lattice mismatch problem, which sometimes necessitates the creation of very large simulation cells for performing density-functional theory (DFT) calculations. Here we use a combination of DFT, linear regression and machine learning techniques in order to rapidly determine the interlayer distance between two different 2D heterostructures that are stacked in a bilayer heterostructure, as well as the band gap of the bilayer. Our work provides an excellent proof of concept by quickly and accurately predicting a structural property (the interlayer distance) and an electronic property (the band gap) for a large number of hybrid 2D materials. This work paves the way for rapid computational screening of the vast parameter space of van der Waals heterostructures to identify new hybrid materials with useful and interesting properties.

Probing the Substrate Promiscuity of Isopentenyl Phosphate Kinase as a Platform for Hemiterpene Analogue Production

2019 ◽  
Author(s):  
Sean Lund ◽  
Taylor Courtney ◽  
Gavin Williams
Keyword(s):  
Synthetic Biology ◽  
Building Blocks ◽  
Isoprenoid Biosynthesis ◽  
Thermoplasma Acidophilum ◽  
Substrate Promiscuity ◽  
Enzymatic Pathways ◽  
First Time ◽  
Rate Limiting ◽  
Alcohol Dependent ◽  
Isopentenyl Phosphate

Isoprenoids are a large class of natural products with wide-ranging applications. Synthetic biology approaches to the manufacture of isoprenoids and their new-to-nature derivatives are limited due to the provision in Nature of just two hemiterpene building blocks for isoprenoid biosynthesis. To address this limitation, artificial chemo-enzymatic pathways such as the alcohol-dependent hemiterpene pathway (ADH) serve to leverage consecutive kinases to convert exogenous alcohols to pyrophosphates that could be coupled to downstream isoprenoid biosynthesis. To be successful, each kinase in this pathway should be permissive of a broad range of substrates. For the first time, we have probed the promiscuity of the second enzyme in the ADH pathway, isopentenyl phosphate kinase from Thermoplasma acidophilum, towards a broad range of acceptor monophosphates. Subsequently, we evaluate the suitability of this enzyme to provide non-natural pyrophosphates and provide a critical first step in characterizing the rate limiting steps in the artificial ADH pathway.<br>

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