[PCR: basics and new developments].
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Abstract:
Since its discovery 10 years ago PCR has been introduced for a variety of practical applications. PCR has opened new dimensions particularly in laboratory diagnostics because of its sensitivity, accuracy and speed. In spite of the availability of user friendly kits, basic knowledge is of great importance for the user especially if PCR has to be optimized for special needs or when specific problems arise. The general mechanism of the reaction and the significance of the reaction components and the PCR conditions are discussed initially. Several recent developments in PCR (new enzymes, RNA-PCR, improvements of the specificity, prevention of contamination and development of new equipment) that are critical for the user are shortly introduced. Finally, "long PCR" is discussed in order to demonstrate that even 10 years after the invention of PCR significant new breakthroughs in the PCR technology are still possible.Cite
Pharmaceutical research has successfully incorporated a wealth of molecular modeling methods, within a variety of drug discovery programs, to study complex biological and chemical systems. The integration of computational and experimental strategies has been of great value in the identification and development of novel promising compounds. Broadly used in modern drug design, molecular docking methods explore the ligand conformations adopted within the binding sites of macromolecular targets. This approach also estimates the ligand-receptor binding free energy by evaluating critical phenomena involved in the intermolecular recognition process. Today, as a variety of docking algorithms are available, an understanding of the advantages and limitations of each method is of fundamental importance in the development of effective strategies and the generation of relevant results. The purpose of this review is to examine current molecular docking strategies used in drug discovery and medicinal chemistry, exploring the advances in the field and the role played by the integration of structure- and ligand-based methods.
Docking (animal)
Protein–ligand docking
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Flux Balance Analysis
Metabolic flux analysis
Computational model
Synthetic Biology
Crosstalk
Limiting
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Enzymes produced from bacteria and eukaryotic organisms are presently being used for a large variety of different biotechnological applications. The rapidly increasing demand for enzymes which are active towards novel and often non-natural substrates has triggered the development of novel molecular biological methods of enzyme isolation and design. The metagenome approach is a cultivation-independent method which allows the direct cloning and expression of environmental DNA thereby providing access to a wealth of so-far unknown biocatalysts. Additionally, newly identified or existing biocatalysts can be further optimized by different methods of directed evolution. Here, the principle of the metagenome approach is outlined and a strategy is presented for the optimization of a bacterial lipase using a combination of rational design and directed evolution.
Rational design
Identification
Isolation
Cloning (programming)
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Abstract Background Synthetic biology is used to develop cell factories for production of chemicals by constructively importing heterologous pathways into industrial microorganisms. In this work we present a retrosynthetic approach to the production of therapeutics with the goal of developing an in situ drug delivery device in host cells. Retrosynthesis, a concept originally proposed for synthetic chemistry, iteratively applies reversed chemical transformations (reversed enzyme-catalyzed reactions in the metabolic space) starting from a target product to reach precursors that are endogenous to the chassis. So far, a wider adoption of retrosynthesis into the manufacturing pipeline has been hindered by the complexity of enumerating all feasible biosynthetic pathways for a given compound. Results In our method, we efficiently address the complexity problem by coding substrates, products and reactions into molecular signatures. Metabolic maps are represented using hypergraphs and the complexity is controlled by varying the specificity of the molecular signature. Furthermore, our method enables candidate pathways to be ranked to determine which ones are best to engineer. The proposed ranking function can integrate data from different sources such as host compatibility for inserted genes, the estimation of steady-state fluxes from the genome-wide reconstruction of the organism's metabolism, or the estimation of metabolite toxicity from experimental assays. We use several machine-learning tools in order to estimate enzyme activity and reaction efficiency at each step of the identified pathways. Examples of production in bacteria and yeast for two antibiotics and for one antitumor agent, as well as for several essential metabolites are outlined. Conclusions We present here a unified framework that integrates diverse techniques involved in the design of heterologous biosynthetic pathways through a retrosynthetic approach in the reaction signature space. Our engineering methodology enables the flexible design of industrial microorganisms for the efficient on-demand production of chemical compounds with therapeutic applications.
Retrosynthetic analysis
Synthetic Biology
Metabolic Engineering
Metabolic pathway
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Background: Metabolism is one of the key parameters to be investigated and optimized in drug discovery projects. Metabolically unstable compounds or potential inhibitors of important enzymes should be detected as early as possible. As more compounds are synthesized than can be investigated experimentally, powerful computational methods are needed. Objective: We give an overview of state-of-the-art in-silico methods to predict experimental metabolic endpoints with a focus on the applicability in pharmaceutical industry. A macroscopic as well as a microscopic view of the metabolic fate and the interaction with metabolizing enzymes are given. Methods: Ligand-, protein- and rule-based approaches are presented. Conclusion: Although considerable progress has been made, the results of the calculations still need careful inspection. The domain of applicability of the models as well as methodological limitations have to be taken into account.
Applicability domain
Computational model
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Synthetic Biology
Metabolic Engineering
Rational design
Metabolic pathway
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The ability to rapidly assess and optimize heterologous pathway function is critical for effective metabolic engineering. Here, we develop a systematic approach to pathway analysis based on correlations between targeted proteins and metabolites and apply it to the microbial production of isopentenol, a promising biofuel. Starting with a seven-gene pathway, we performed a correlation analysis to reduce pathway complexity and identified two pathway proteins as the primary determinants of efficient isopentenol production. Aided by the targeted quantification of relevant pathway intermediates, we constructed and subsequently validated a conceptual model of isopentenol pathway function. Informed by our analysis, we assembled a strain which produced isopentenol at a titer 1.5 g/L, or 46% of theoretical yield. Our engineering approach allowed us to accurately identify bottlenecks and determine appropriate pathway balance. Paired with high-throughput cloning techniques and analytics, this strategy should prove useful for the analysis and optimization of increasingly complex heterologous pathways.
Metabolic Engineering
Heterologous
Pathway Analysis
Metabolic pathway
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Environmental matrices are highly diverse in their composition and range from simple (e.g. water) to highly complex (e.g. organic soils/biosolids). Analysis of microbial gene expression from such substrates is done for variety of purposes which could range from bio-surveillance to elucidation of biological function of a target microbe. Quantitative real-time PCR (RT-qPCR) has become a technique of choice for studying such bio-processes, due to its unique ability to both detect and quantify a target transcript in real-time. Challenges in extracting inhibitor-free, structurally intact RNA, amenable for a sensitive technique like RT-qPCR, has however proved to be a major impediment in our ability to rigorously implement this highly versatile technology. Despite these 'substrate defined' limitations, many attempts have been made to implement the RT-qPCR technology. Efforts like these have given us invaluable insight into the expression status of a particular transcript and hence, the biological functioning of the microbe, specifically under natural in situ conditions. As a result, it has enhanced our understanding of the role and diversity of many microbial populations which, previously was not possible using conventional molecular approaches. In this article, we have sought to summarize such technical problems faced by molecular environmental microbiologist and solutions developed to mitigate those challenges.
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The last 20 years have seen the widespread and routine application of methods in molecular biology such as molecular cloning, recombinant protein expression, and the polymerase chain reaction. This has had implications not only for the study of toxicological mechanisms but also for the exploitation of enzymes involved in xenobiotic clearance. The engineering of P450s has been performed with several purposes. The first and most fundamental has been to enable successful recombinant expression in host systems such as bacteria. This in turn has led to efforts to solubilize the proteins as a prerequisite to crystallization and structure determination. Lagging behind has been the engineering of enzyme activity, hampered in part by our still-meager comprehension of fundamental structure–function relationships in P450s. However, the emerging technique of directed evolution holds promise in delivering both engineered enzymes for use in biocatalysis and incidental improvements in our understanding of sequence–structure and sequence–function relationships, provided that data mining can extract the fundamental correlations underpinning the data. From the very first studies on recombinant P450s, efforts were directed toward constructing fusions between P450s and redox partners in the hope of generating more efficient enzymes. While this aim has been allowed to lie fallow for some time, this area merits further investigation as does the development of surface-displayed P450 systems for biocatalytic and biosensor applications. The final application of engineered P450s will require other aspects of their biology to be addressed, such as tolerance to heat, solvents, and high substrate and product concentrations. The most important application of these enzymes in toxicology in the near future is likely to be the biocatalytic generation of drug metabolites for the pharmaceutical industry. Further tailoring will be necessary for specific toxicological applications, such as in bioremediation.
Protein Engineering
Biocatalysis
Synthetic Biology
Cloning (programming)
Structural Biology
Directed Molecular Evolution
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The successful engineering of secondary metabolite production relies on the availability of detailed computational models of metabolism. In this brief review we discuss the types of models used for synthetic biology and their application for the engineering of metabolism. We then highlight some of the major modeling challenges, in particular the need to make informative model predictions based on incomplete and uncertain information. This issue is particularly pressing in the synthetic biology of secondary metabolism, due to the genetic diversity of microbial secondary metabolite producers, the difficulty of enzyme-kinetic characterization of the complex biosynthetic machinery, and the need for engineered pathways to function efficiently in heterologous hosts. We argue that an explicit quantitative consideration of the resulting uncertainty of metabolic models can lead to more informative predictions to guide the design of improved production hosts for bioactive secondary metabolites.
Synthetic Biology
Secondary metabolism
Metabolic Engineering
Secondary metabolite
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