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Predictive Computational Toxicology to Support Drug Safety Assessment

Use of predictive technologies is an important aspect of many efforts in today’s research, development, and regulatory landscapes. Computational methods as predictive tools for supporting drug safety assessments is of widespread interest as the field of in silico assessments rapi ...

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Developmental Toxicity Prediction

Developmental toxicity may be estimated using commercial and noncommercial software that is already available in the market and/or literature, or models may be built from scratch using both commercial and noncommercial software packages. In this chapter, commonly available soft ...

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Modeling for Regulatory Purposes (Risk and Safety Assessment)

Chemicals provide many key building blocks that are converted into end‐use products or used in industrial processes to make products that benefit society. Ensuring the safety of chemicals and their associated products is a key regulatory mission. Current processes and procedures for e ...

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Biomonitoring-based Environmental Public Health Indicators

This chapter discusses the use ofbiomonitoring-based indicators of exposure to environmental pollutants in environmental health information systems. Matrices for biomonitoring, organization and standardization of surveillance programs, the use of intake and body bur ...

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Biomarkers

Biomarkers are characteristics objectively measured and evaluated as indicators of: normal biologic processes, pathogenic processes, or pharmacologic response(s) to a therapeutic intervention. In environmental research and risk assessment, biomarkers are frequent ...

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Regulatory Networks

The usefulness of mathematical models for the biological regulatory networks relies on the predictive capability of the models in order to suggest interesting hypotheses and suitable biological experiments. All mathematical frameworks dedicated to biological regulatory ...

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Gene Expression Networks

With the advent of microarrays and next-generation biotechnologies, the use of gene expression data has become ubiquitous in biological research. One potential drawback of these data is that they are very rich in features or genes though cost considerations allow for the use of only relativ ...

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Computational Reconstruction of Metabolic Networks from KEGG

Reconstruction of metabolic networks from metabolites, enzymes, and reactions is the foundation of the network-based study on metabolism. In this chapter, we describe a practical method for reconstructing metabolic networks from KEGG. This method makes use of organism-specific p ...

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QSAR and Metabolic Assessment Tools in the Assessment of Genotoxicity

In this chapter, a range of computational tools for applying QSAR and grouping/read-across methods are described, and their integrated use in the computational assessment of genotoxicity is illustrated through the application of selected tools to two case-study compounds—2-ami ...

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Classification Models for Safe Drug Molecules

Frequent failure of drug candidates during development stages remains the major deterrent for an early introduction of new drug molecules. The drug toxicity is the major cause of expensive late-stage development failures. An early identification/optimization of the most favorab ...

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Mutagenicity, Carcinogenicity, and Other End points

Aiming at understanding the structural and physical chemical basis of the biological activity of chemicals, the science of structure–activity relationships has seen dramatic progress in the last decades. Coarse-grain, qualitative approaches (e.g., the structural alerts), and f ...

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From QSAR to QSIIR: Searching for Enhanced Computational Toxicology Models

Quantitative structure activity relationship (QSAR) is the most frequently used modeling approach to explore the dependency of biological, toxicological, or other types of activities/properties of chemicals on their molecular features. In the past two decades, QSAR modeling has ...

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Methods for Building QSARs

Structure–activity relationship (SAR) and quantitative structure–activity relationship (QSAR) models are increasingly used in toxicology, ecotoxicology, and pharmacology for predicting the activity of the molecules from their physicochemical properties and/or t ...

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Engineering and Expression of Bibody and Tribody Constructs in Mammalian Cells and in the Yeast Pichia pastoris

Bibodies and tribodies are therapeutic antibody derivatives with sizes of approximately 75 and 100 kDa, respectively. This makes them smaller than full-size monoclonal antibodies, leading to better tissue penetration. Compared to the smaller scFv and Fab fragments, the bi- and tribo ...

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Folding Engineering Strategies for Efficient Membrane Protein Production in E. coli

Membrane proteins are notoriously difficult to produce at the high levels required for structural and biochemical characterization. Among the various expression systems used to date, the enteric bacterium Escherichia coli remains one of the best characterized and most versatil ...

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Use of E. coli for the Production of a Single Protein

E. coli has been widely used for recombinant protein production. Here, we introduce a novel expression method in E. coli, the Single Protein Production (SPP) system, in which E. coli is converted into a bioreactor producing only the target protein. In the SPP system, all E. coli cellular mRNAs are elimin ...

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Design and Generation of DVD-Ig Molecules for Dual-Specific Targeting

The dual variable domain immunoglobulin (DVD-IgTM) protein is a new type of dual-specific IgG. As a novel therapeutic class, the great potential of the DVD-Ig protein is to simultaneously target two mediators of disease by a single pharmaceutical entity. The molecule contains an Fc region and c ...

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Protein Design for Diversity of Sequences and Conformations Using Dead-End Elimination

Proteins, especially antibodies, are widely used as therapeutic and diagnostic agents. Computational �protein design is a powerful tool for improving the affinity and stability of these molecules. We describe a protein design method which employs the dead-end elimination (DEE) and undefined ...

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Engineering of Affibody Molecules for Therapy and Diagnostics

Affibody molecules are small and robust non-immunoglobulin affinity ligands capable of binding to a wide range of protein targets. They are selected from combinatorial libraries based on a 58 amino acid, three-alpha-helical Z-domain scaffold. They share no sequence or structural hom ...

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Expression, Purification, and Characterization of Engineered Antibody CH2 and VH Domains

Most of the FDA-approved therapeutic monoclonal antibodies are full-size IgG molecules with a molecular weight of about 150 kDa. A major problem for such large molecules is their poor penetration into tissues (e.g., solid tumors) and poor or absent binding to regions on the surface of some molecu ...

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