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Файл:Ординатура / Хирургия / Библиотека им академика М.И. Перельмана / Книга_5344_Библиотеки_им_академика_М_И_Перельмана.pdf
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- •Acknowledgement
- •Author biographies
- •Professor Ahmed Al-Harrasi
- •Dr Saurabh Bhatia
- •Dr Ajmal Khan
- •1.1 Introduction
- •1.2 Properties of enzymes
- •1.3 Catalysis
- •1.4 The structure of enzymes
- •1.5 Structural features: primary and secondary structures
- •1.6 Nomenclature and classification
- •1.6.1 Class 1—oxidoreductase
- •1.6.2 Class 2—transferase
- •1.6.3 Class 3—hydrolases
- •1.6.4 Class 4—lyases
- •1.6.5 Class 5—isomerases
- •1.6.6 Class 6—ligases
- •1.7 The mechanism of action of enzymes
- •1.7.3 Covalent catalysis
- •1.8 Catalysis via chymotrypsin
- •1.8.1 Intermediary stages of chymotrypsin
- •1.8.2 Kinetic behavior of α-chymotrypsin
- •1.8.3 Selective proteolysis in creation of the catalytic sites of enzymes
- •1.8.4 Kinetic models for enzymes
- •1.8.5 Enzyme mediated acid–base (general) catalysis
- •1.8.6 Metallozymes
- •1.9 Enzyme inhibition
- •1.10 Pharmaceutical applications
- •1.10.1 Diagnostic applications of enzymes
- •1.10.2 Enzymes in therapeutics
- •1.11 Plants and algae enzyme systems
- •1.12 Enzyme safety
- •1.13 Enzyme structure determination
- •1.13.1 X-ray crystallography
- •1.13.2 NMR spectroscopy
- •1.13.3 Cryo-electron microscopy
- •1.14 Enzyme engineering and design
- •1.14.1 Directed evolution of enzymes
- •1.14.2 Rational design of enzymes
- •1.14.3 Applications of engineered enzymes
- •1.15 Enzymes in medicine and healthcare
- •1.15.1 Enzyme-targeted drug delivery
- •1.15.2 Enzymes as drug targets
- •1.15.3 Challenges and opportunities in enzyme drug discovery
- •1.15.4 Enzymes in gene therapy
- •1.15.5 Enzymes in personalized medicine
- •1.15.6 Enzyme biomarkers in disease diagnosis
- •1.15.7 Pharmacogenomics and enzyme variability
- •1.15.8 Enzyme-based therapies for personalized treatment
- •1.16 Enzymes in bioremediation
- •1.17 Enzymes in agriculture and crop production
- •1.18 Enzymes in waste management
- •References
- •2.1 Introduction
- •2.1.1 Sources of enzymes
- •2.2 Enzyme production technology
- •2.2.1 Selection of microorganisms
- •2.2.2 Medium selection
- •2.2.3 Production process
- •2.2.5 Cell debris removal
- •2.2.6 Nucleic acid removal
- •2.2.7 Precipitation of enzymes
- •2.2.8 Liquid–liquid partition
- •2.2.9 Chromatographic separation
- •2.2.10 Drying and packing
- •2.2.11 Regulation of microbial enzyme production
- •2.2.12 Induction
- •2.2.13 Feedback repression
- •2.2.14 Nutrient repression
- •2.3 Procedures involved in enzyme production
- •2.3.1 Source and location of enzymes
- •2.3.2 The variety of microorganisms
- •2.3.3 Media for fermentation
- •2.3.4 Fermentation
- •2.3.5 Enzyme extraction
- •2.3.7 Finishing operations
- •2.4 Recombinant proteins from algae
- •2.5 Enzyme immobilization techniques
- •2.5.1 Advantages and applications of enzyme immobilization
- •2.5.2 Methods of enzyme immobilization
- •2.6 Enzyme engineering for enhanced stability and activity
- •2.6.1 Protein engineering strategies
- •2.6.2 Improving enzyme thermostability
- •2.7 Upstream process intensification
- •2.7.1 High cell density fermentation
- •2.7.2 Solid-state fermentation
- •2.7.3 Continuous fermentation
- •2.7.4 Microbial consortia for enzyme production
- •2.7.5 In situ product removal strategies
- •2.8 Enzyme production from extreme environments
- •2.8.1 Psychrophiles (cold-loving)
- •2.9.4 Automation and robotics in downstream processing
- •References
- •2.8.2 Thermophiles (heat-loving)
- •2.8.3 Acidophiles (acid-loving)
- •2.8.4 Alkaliphiles (alkaline-loving)
- •2.8.5 Halophiles (salt-loving)
- •2.8.6 Applications of extremozymes in biotechnology
- •2.9 Downstream process intensification
- •2.9.1 Continuous chromatography
- •2.9.2 Process integration and optimization
- •3.1 Industrial enzymes
- •3.2 Bacterial α-amylases
- •3.3 Fungal α-amylases
- •3.4 Bacterial proteases
- •3.5 Fungal proteases
- •3.6 Glucose isomerase (d-xylose ketol-isomerase; EC. 5.3.1.5)
- •3.7 Penicillinase
- •3.8 Chloramphenicol acetyltransferase
- •3.9 Aminoglycoside antibiotic inactivating enzymes
- •3.10 Fibrinolytic enzymes
- •3.10.1 Streptokinase
- •3.10.2 Urokinase
- •3.10.3 Tissue plasminogen activator (t-PA)
- •3.11 Biotechnological applications of enzymes
- •3.11.1 Algae and plant research
- •3.11.2 Immobilization
- •3.12 Industrial enzymes
- •3.12.1 Glucoamylase
- •3.12.2 Cellulases
- •3.13 The role of enzymes in the synthesis of functional foods
- •3.13.1 Lipases
- •3.13.2 Proteases
- •3.13.3 Carbohydrate-modifying enzyme
- •3.13.4 Tannase
- •3.13.5 Asparaginase
- •3.13.6 The phytases
- •3.14 Enzymes used as additives to food
- •3.14.1 The enzymatic synthesis of dietary antioxidants
- •3.14.2 The use of ascorbyl esters
- •3.14.3 Polyphenolic esters
- •3.14.4 Synthesis of sugars esters surfactants by enzymes
- •References
- •4.1 Introduction
- •4.2 Types of immobilization
- •4.2.1 Surface immobilization by covalent coupling
- •4.2.2 Adsorption
- •4.2.3 Complexation and chelation
- •4.2.4 Within-support immobilization
- •4.2.5 Cell immobilization
- •4.2.6 Commercial production of enzymes
- •4.3 Genetic engineering for microbial enzyme production
- •4.3.1 Cloning methods
- •4.4 Protein studies for modification of commercial enzymes
- •4.5 Enzyme and cell immobilization
- •4.6 Immobilization methods
- •4.6.1 Adsorption methods
- •4.6.3 Ionic binding
- •4.6.4 Hydrophobic adsorption
- •4.6.6 Entrapment method
- •4.6.7 Covalent binding
- •4.6.8 Cross-linking
- •4.7 Choice of immobilization technique
- •4.7.1 Immobilization of l-amino acid acylase
- •4.7.2 Stabilization of soluble enzymes
- •4.8 Immobilization of cells
- •4.8.1 Immobilization of viable cells
- •4.8.2 Immobilized non-viable cells
- •4.8.3 Drawbacks of immobilizing eukaryotic cells
- •4.8.4 The effect of immobilization on enzyme properties
- •4.8.5 Immobilized enzyme reactors
- •4.8.6 Applications of immobilized enzymes and cells
- •4.9 Manufacture of commercial products
- •4.9.1 Production of l-amino acids
- •4.9.2 Production of high-fructose syrup
- •4.9.3 Immobilized enzyme and cell analytical applications
- •4.10 Immobilized enzymes for biomedical applications
- •4.11.1 Bioluminescence
- •4.11.2 The measurement of biomass using bioluminescence-based techniques
- •4.11.4 Biosensors relying on bioluminescence
- •4.12 Bioluminescence-based microbial biosensors
- •4.12.1 The microencapsulation process involves the utilization of polymers and cells
- •4.12.2 Microcapsule evaluation
- •4.12.4 Modern developments in cell encapsulation
- •4.13 Immobilization of microalgae
- •4.13.1 Techniques for immobilization
- •4.13.2 Use of cryopreserved algae
- •4.13.3 Removal of nitrogen and phosphorous
- •4.13.4 Disposal of metals
- •4.13.5 Biosensor development
- •References
- •5.1 Introduction
- •5.2 Principles of a biosensor
- •5.3 Different types of biosensors
- •5.3.1 Electrochemical biosensors
- •5.3.2 Thermometric biosensors
- •5.3.3 Optical biosensors
- •5.3.4 Piezoelectric biosensors
- •5.3.5 Whole-cell biosensors
- •5.3.6 Immunobiosensors
- •5.4 Applications of biosensors
- •5.4.1 Applications in medicine and health
- •5.4.2 Applications in industry
- •5.4.3 Applications in pollution control
- •5.4.4 Applications in the military
- •5.4.5 Immobilized enzymes and cell therapeutic applications
- •5.5 Recent advancements in biosensor technology
- •5.5.1 Electrochemical biosensors
- •5.5.2 Optical/visual biosensors
- •5.5.3 Silica, quartz/crystal, and glass biosensors
- •5.5.4 Nanomaterials-based biosensors
- •5.5.5 Fluorescent biosensors that are either genetically encoded or synthetic
- •5.7 Technological comparison of biosensors
- •5.9 Grand challenges in biosensors and biomolecular electronics
- •5.9.1 Sensitivity
- •5.9.2 Multiplex capability
- •5.9.3 Continuous monitoring in vivo
- •5.10.1 Sustainability to the ecosystem
- •References
- •6.1 Introduction
- •6.2 Types of biotransformation reactions
- •6.3 Sources of biocatalysts and techniques for biotransformation
- •6.3.1 Growing cells
- •6.3.2 Non-growing cells
- •6.3.3 Immobilized cells
- •6.3.4 Immobilized enzymes
- •6.4 Product recovery in biotransformations
- •6.5 Application of biotransformation in the production of pharmaceutical products
- •6.5.1 Biotransformation of steroids
- •6.5.2 Biotransformation of antibiotics
- •6.5.3 Biotransformation of arachidonic acid to prostaglandins
- •6.5.4 Biotransformation for the production of ascorbic acid
- •6.5.5 Biotransformation of glycerol to dihydroxyacetone
- •6.5.6 Biotransformation for the production of indigo
- •6.6 Mechanisms of enzyme action in biotransformation
- •6.6.1 Enzyme kinetics and biotransformation
- •6.6.2 Cofactors and coenzymes in biotransformation
- •6.6.3 Enzyme inhibition and activation
- •6.7 Biotransformation in environmental applications
- •6.7.1 Degradation of pollutants
- •6.7.2 Enzymatic breakdown of pesticides
- •6.8 Emerging technologies in biotransformation
- •6.8.1 Enzyme engineering and directed evolution
- •6.8.3 Biotransformation of lipids for healthy oils
- •6.9 Biotransformation challenges and future perspectives
- •6.9.1 Scalability issues in industrial applications
- •6.9.2 Regulatory and safety concerns
- •6.9.3 Challenges in enzyme storage and stability
- •6.9.4 Future trends and emerging areas of research
- •6.9.5 Biotransformation in biofuel production
- •6.9.6 Biotransformation in the cosmetic industry
- •6.9.7 Specialized enzyme systems: lignin-modifying enzymes in biotransformation
- •References
- •7.1 Introduction
- •7.2 Characterizations in genomics
- •7.3 Historical background
- •7.4 Genome sequencing
- •7.4.1 Clone-by-clone sequencing
- •7.4.2 Human whole-genome shotgun sequencing
- •7.4.3 Compilation of genome resources
- •7.5 Understanding bioinformatics and sequencing
- •7.6 Comparative genomics as a technique to understand evolution
- •7.6.2 Horizontal or lateral gene transfer
- •7.6.3 Genome similarity or homology
- •7.6.4 SNPs
- •7.6.5 Inferences from comparative genomics
- •7.6.6 Gene order comparisons (for phylogenetic inference)
- •7.6.7 Phylogenetic footprinting (computational method)
- •7.6.8 Origins, evolution and phenotypic impact of new genes
- •7.6.9 The concept of minimum genome size
- •7.6.10 Comparative genomics analysis of mitochondria and chloroplasts
- •7.7 Gene estimation and counting
- •7.7.1 Genome similarity, SNPs and comparative genomics
- •7.8 Genomes: genome evolution
- •7.8.1 Microbial genome reduction in bacteria
- •7.8.2 Role of duplications in the origin and evolution of the eukaryotic genome
- •7.8.3 Gene duplications increase genetic diversity and complexity
- •7.9 Algae bioinformatics
- •7.9.1 Scope of algae bioinformatics
- •7.9.2 What is involved in algae bioinformatics
- •7.9.3 Role of algae bioinformatics
- •7.9.4 Steps involved in obtaining the data for analysis using bioinformatics
- •7.10 Functional genomics
- •7.10.1 Introduction to functional genomics
- •7.10.2 Transcriptomics: studying the RNA molecules
- •7.10.3 Proteomics: understanding the world of proteins
- •7.10.4 Metabolomics: exploring cellular metabolites
- •7.10.5 Interactomics investigating protein–protein interactions
- •7.11 Structural genomics
- •7.11.1 Introduction to structural genomics
- •7.11.2 The approaches used in the domain of structural genomics
- •7.11.3 Importance of structural genomics in drug design
- •7.12 Epigenomics and epigenetics
- •7.12.1 Epigenetic inheritance and diseases
- •7.13 Pharmacogenomics
- •7.13.1 The importance of personalized medicine
- •7.13.2 The impact of genetic variations on drug response
- •7.13.3 Additional insights on pharmacogenomics
- •7.13.4 Pharmacogenomic tests in the market
- •7.13.5 Challenges in implementing pharmacogenomics
- •7.14 Population genomics
- •7.14.1 Studying genetic variation across populations
- •7.14.2 Population genomics techniques
- •7.14.3 Understanding human migration and evolution through population genomics
- •7.14.4 Conservation genomics in endangered species
- •7.15 Microbiome genomics
- •7.15.1 Introduction to the human microbiome
- •7.15.2 Techniques in studying microbial communities
- •7.15.3 Role of microbiome in human health and disease
- •7.15.4 Environmental microbiomes and their importance
- •7.16 Synthetic biology and genome editing
- •7.16.1 Techniques like CRISPR/Cas9 in genome editing
- •7.17 Systems biology and genomics
- •7.17.1 Integrative approaches in genomics
- •7.17.2 Modeling biological systems and networks
- •7.17.3 Challenges and opportunities in systems biology
- •7.18 Genome-wide association studies (GWAS)
- •7.18.1 Introduction to GWAS
- •7.18.2 Techniques and platforms for GWAS
- •7.18.3 Challenges in interpreting GWAS results
- •7.19 Future of genomics
- •7.19.1 Next-generation sequencing technologies
- •7.19.2 Ethical considerations in genomics research
- •7.19.3 The role of AI and machine learning in genomics
- •7.19.4 Personalized medicine and its potential impact
- •8.1 Introduction
- •8.2 Types of proteomics
- •8.2.1 Structural proteomics
- •8.2.2 Functional proteomics (strategy)
- •8.2.3 Expression proteomics
- •8.3 Basic techniques involved in proteomics
- •8.3.1 Sequence alignment (algorithms)
- •8.3.2 Protein structure (annotation resources)
- •8.3.3 Protein structural investigation
- •8.3.4 Two-dimensional gel electrophoresis in proteomics
- •8.3.5 Domain fusion method (or rosetta stone method)
- •8.4 Complete proteome of Mycoplasma genitalium
- •8.5 Architecture and design of the nuclear pore complex
- •8.6 Functional genomics and systems biology
- •8.6.2 Transcriptome, proteome and genomes
- •8.6.3 DNA arrays: a potential genomic tool
- •8.6.4 Gene function determination from sequence information
- •8.6.5 Protein interactions
- •8.7 Synthetic genomics
- •8.8 Advanced techniques in proteomics
- •8.8.1 Mass spectrometry in proteomics
- •8.8.2 Tandem mass spectrometry
- •8.8.3 Quantitative proteomics using mass spectrometry
- •8.8.4 Other advanced techniques in proteomics
- •8.8.5 Chromatography in proteomics
- •8.9 Proteogenomics
- •8.9.1 Proteogenomics role in precision medicine
- •8.10 Single-cell proteomics
- •8.10.1 Technologies enabling single-cell proteomics
- •8.11 Clinical and diagnostic proteomics
- •8.12 Metaproteomics
- •8.13 Emerging topics in proteomics
- •8.13.1 Data-independent acquisition (DIA)
- •8.13.2 Top-down proteomics
- •8.13.3 Targeted proteomics and selected reaction monitoring (SRM)
- •8.13.4 Proteomics in plant research
- •8.14 Ethical and data management issues in proteomics
- •8.14.1 Open-source platforms for proteomic analysis
- •8.15 Cellular and molecular dynamics
- •8.15.1 Molecular mechanisms of protein function
- •8.15.2 Protein degradation pathways
- •8.15.4 Cellular signaling pathways
- •8.15.5 Proteomic analysis of signaling networks
- •8.15.6 Signaling pathway dysregulation in disease
- •8.15.7 Targeting signaling pathways in drug discovery
- •8.15.8 Crosstalk between signaling pathways
- •8.16 Membrane proteomics
- •8.16.1 Techniques for membrane protein analysis
- •8.16.2 Membrane protein structure and function
- •8.16.3 Membrane proteins in disease
- •8.16.4 Drug targeting of membrane proteins
- •8.17 Subcellular proteomics
- •8.17.3 Proteomics of cellular compartments
- •8.17.4 Techniques for subcellular proteomic analysis
- •References
- •9.1 Introduction
- •9.2 History of bioinformatics
- •9.3 Sequences and nomenclature
- •9.3.1 DNA sequences
- •9.3.2 Amino acid sequences of proteins
- •9.3.3 Types of sequences in nucleotide sequence databases
- •9.3.4 Databases
- •9.3.5 Search engines and analysis tools
- •9.3.6 Various indian databases
- •9.4 Investigation by means of bioinformatics tools
- •9.4.4 Detection of noncoding RNA
- •9.4.5 Genome annotation
- •9.4.6 Molecular phylogenetics
- •9.5 Computational approaches in bioinformatics
- •9.5.1 Algorithm development
- •9.5.2 Phylogenetic tree construction algorithms
- •9.5.3 Machine learning algorithms in bioinformatics
- •9.5.4 High-performance computing (HPC) in bioinformatics
- •9.5.5 Cloud computing in genomics
- •9.5.6 GPGPU (general-purpose computing on graphics processing units)
- •9.5.7 Big data analytics in bioinformatics
- •9.5.8 Systems biology modelling
- •9.5.9 Systems pharmacology
- •9.5.10 Multiscale modeling
- •9.5.11 Computational genomics
- •9.5.12 Functional genomics
- •9.5.13 Comparative genomics
- •9.5.14 Epigenomics
- •9.5.15 Metagenomics
- •9.6 Bioinformatics in precision medicine
- •9.7 Translational bioinformatics
- •9.8 Bioinformatics in drug discovery and development
- •9.8.2 AI-driven drug discovery
- •9.9 CRISPR and genome editing in bioinformatics
- •9.10 Integrative and multi-omics analysis
- •References
- •10.1 Protein and enzyme engineering
- •10.2 Designing macromolecules
- •10.3 Protein engineering versus enzyme engineering
- •10.4 Protein engineering
- •10.5 Foundation of protein (enzyme) engineering
- •10.6 Basic assumptions for protein engineering
- •10.7 Steps involved in protein engineering
- •10.7.1 Studying three-dimensional protein structure
- •10.7.2 Protein modeling
- •10.7.3 Perturbation theory
- •10.8 Methods of protein engineering
- •10.9 Mutagenesis and selection of mutant enzymes
- •10.10 Gene modifications or gene synthesis for protein engineering
- •10.11 Multi-enzyme systems
- •10.12 Chemical modification of enzyme
- •10.13 Some early achievements of protein engineering
- •10.14 Computational approaches in protein engineering
- •10.14.1 Molecular dynamics simulations
- •10.14.2 Quantum mechanical calculations
- •10.14.3 Docking and ligand optimization
- •10.14.4 Machine learning algorithms in protein design
- •10.15 Directed evolution techniques
- •10.15.1 Error-prone PCR
- •10.15.3 Saturation mutagenesis
- •10.15.4 Phage display
- •10.16 Post-translational modifications
- •10.16.1 Glycosylation engineering
- •10.16.2 Phosphorylation engineering
- •10.16.3 Methylation and acetylation
- •10.16.4 PEGylation for enzyme stability
- •10.17 Structural flexibility and allosteric regulation
- •10.17.1 Intraprotein communication pathways
- •10.17.3 Modulator design
- •10.17.4 Coupling allosteric regulation with catalytic function
- •10.18 Protein–protein and protein–ligand interactions
- •10.18.1 Characterizing binding sites
- •10.18.3 Interaction networks
- •10.18.4 Biophysical methods for interaction studies
- •10.19 Applications in synthetic biology
- •10.19.1 Metabolic pathway engineering
- •10.19.2 Genetically encoded sensors
- •10.19.3 Protein-based logic gates
- •10.19.4 Gene circuits for dynamic control
- •10.20 Engineering multi-functional proteins
- •10.20.1 Fusion proteins
- •10.20.2 Protein scaffolds
- •10.20.3 Modular protein design
- •10.20.4 Dual-enzyme systems
- •10.21 Ethical and safety considerations
- •10.21.1 Bioethics in protein engineering
- •10.21.2 Biosafety and environmental concerns
- •10.21.3 Intellectual property rights
- •10.21.4 Regulatory frameworks
- •10.22 Studies in protein engineering
- •10.22.1 Therapeutic proteins
- •10.22.2 Industrial enzymes
- •10.22.3 Diagnostic proteins
- •10.23 Single-molecule techniques in protein engineering
- •10.23.1 Atomic force microscopy
- •10.23.2 Single-molecule FRET
- •10.23.3 Optical tweezers
- •10.23.4 Patch-clamp technique
- •10.24 High throughput screening methods
- •10.24.1 Fluorescence-activated cell sorting (FACS)
- •10.24.3 Yeast surface display
- •10.24.4 Mass spectrometry-based methods
- •10.25 Protein engineering for nanotechnology
- •10.25.1 Protein-based nanocarriers
- •10.25.2 Biosensors
- •10.25.3 Protein nanowires and nanotubes
- •10.25.4 DNA–protein hybrid structures

Introduction to Pharmaceutical Biotechnology, Volume 2 (Second Edition)
electromagnetic energies, obviating the need for mechanical cable connections. The
potential to provide exact readings without the need for direct physical touch is
essential for achieving ultrahigh sensitivity in detecting proteins in fluids utilizing
gear constructed around quartz crystal biological sensors. Due to their unique
properties, silica, quartz, and glass are used to develop cutting-edge biosensors.
These biosensors use advanced technological advancements to enhance the efficacy
of bio-instrumentation within the medical domain. However, it is crucial to address
concerns about biological security and the associated financial implications [95].
5.5.4 Nanomaterials-based biosensors
A wide range of tiny materials, including silver, gold, silicon, and copper nanoparticles, in addition to materials made from carbon like graphite, graphene, and
nanotubes made of carbon, are used in biosensor immobilization. In addition, the
use of substances that involve nanoparticles has notable benefits in terms of
increased specificity and sensitivity in the advancement of electrochemical and
alternative biosensors. Because of their small size and resistance to oxidation,
nanoparticles of gold are seen as a viable material for use in nanotechnology [96].
For example, silver nanoparticles may corrode and adversely affect intra-body
operations like drug delivery. Utilizing nanomaterials in biosensors for biomedicine
has significant obstacles that must be effectively addressed. In addition, it is crucial
to consider the potential advantages and downsides of signal amplification systems
based on nanoparticles. However, nanoparticles are widely regarded as crucial
elements in bio-analytical instruments because they enhance sensitivity and improve
detection limits for single-molecule analysis. It is pertinent to acknowledge the
invention of platinum-based nanoparticles that were utilized for electrochemical
amplification, which resulted in a solitary label response mechanism for detecting
DNA at low concentrations. This information is pertinent because it is applicable to
the current setting [97].
Similarly, the coupling of semiconductor quantum dots and iron oxide nanocrystals, which possess optical and magnetic characteristics, can be successfully
achieved using tumor-targeted ligands. These ligands, including monoclonal antibodies, peptides, or small molecules, exhibit a strong affinity and specificity towards
tumor antigens, hence facilitating precise targeting of tumors. The utilization of
quantum dots technology holds the potential for comprehending the intricacies of
the tumor microenvironment in the context of therapeutic interventions and
facilitating the administration of nanomedicine. The assessment of beam size, which
may be micro, milli and nano cantilever biosensors, is subject to severe examination
owing to its prospective applications across diverse disciplines [98].
5.5.5 Fluorescent biosensors that are either genetically encoded or synthetic
The utilization of genetically encoded or synthetic fluorescence in creating tagged
biosensors has facilitated the comprehension of biological processes, including a
diverse range of biochemical pathways occurring inside the cellular environment.
The development of fluorescent-tagged antibodies was first intended to visualize
5-23

Introduction to Pharmaceutical Biotechnology, Volume 2 (Second Edition)
fixed cells. Utilizing natural amino acids, small-molecular interactions with substances, and additional messengers are unique approaches offered because of this
approach, which has undoubtedly contributed to the development of sensors [99].
Recently, fluorescent biosensors have been developed that enable the analysis of
motor proteins through single-molecule detection, which allows for the precise
determination of analyte concentration. The technique that is used for probe
identification and evaluation looks to present some difficulties, notwithstanding
the benefits that have been discussed previously. The discovery of green fluorescent
protein and other fluorescent proteins has yielded numerous benefits in optical probe
design and efficiency. In the preceding decade, there has been significant progress in
genetically encoded biosensors targeting chemicals associated with energy production, reactive oxygen species, and cyclic adenosine monophosphate (cAMP).
Similarly, cyclic guanosine monophosphate (cGMP) serves as a crucial signaling
molecule and holds significance as a pharmacological target within the cardiovascular system [100]. Given these circumstances, researchers have successfully created
biosensors based on Förster resonance energy transfer (FRET) to enable the
visualization of cellular levels of cGMP, cAMP, and Ca
2+
. Several of these sensors
have high efficacy in primary culture and in vivo imaging of live cells. Several crucial
elements have been successfully identified in developing sensors for live-animal
imaging. The utilization of optimized methodologies, such as small-angle x-ray
scattering for the development of calcium sensors and fluorescence resonance energy
transfer probes for kinase sensing, is widely acknowledged as the most effective
biosensor techniques in contemporary physiology in this manner, a few biosensors
utilizing microbial and cell organelle systems were designed to detect and analyze
specific targets [100]. As previously elucidated, electrochemical, electromechanical,
and optical biosensors have been devised to detect miRNA more efficiently than
alternative molecular methodologies. The development of living tissue imaging
through the utilization of small chemical biological sensors has resulted in an
improved knowledge of cellular activity and the finding of many molecules, such as
DNA, RNA, and miRNA. The advancement in this domain necessitates the
adoption of a comprehensive genomic methodology employing enhanced opticalbased genetic biosensors. The current consensus in the scientific community is that
optical-based biosensors, which utilize a mix of fluorescence and tiny molecules/
nanomaterials, have demonstrated significant advancements in both their practical
applications and sensitivity [101].
5.6 Microbial biosensors utilizing synthetic biology and genetic/
protein engineering techniques
Current development in environmental monitoring and bioremediation involves the
application of advanced technologies rooted in genetic/protein engineering and
synthetic biology. These technologies enable the programming of microorganisms to
exhibit desired signal outputs, sensitivity, and selectivity. For instance, the utilization of live cells possessing enzymatic activity for the degradation of xenobiotic
substances holds significant potential for broader applications in bioremediation
5-24

Introduction to Pharmaceutical Biotechnology, Volume 2 (Second Edition)
[102]. In a similar vein, researchers have devised microbial fuel-based biosensors
with the objective of monitoring levels of biochemical oxygen demand and assessing
toxicity within the surrounding environment. Bacterial organisms can break down
organic substrates and produce electrical energy through fermentation. The technology encompasses utilizing a bio-electrochemical apparatus that regulates the
capacity of microbial respiration to transform organic substrates into electrical
energy directly. Despite the potential advantages, microbial biosensors are constrained by limits related to their low power density, which affects both production
and operational costs. There is a current focus on improving performance and
reducing costs through novel systemic approaches. These approaches leverage
technologies to create self-powered engineered microbial biosensors, which hold
promise for considerable advancements. Microbial biosensors have demonstrated
promising applications in detecting pesticides and heavy metals [91]. Eukaryotic
microorganisms possess certain advantages over prokaryotic cells in this area. The
primary reason for developing whole-cell biosensors is their ability to detect heavy
metal selectively and sensitively and pesticide toxicity.
Moreover, eukaryotic microorganisms of increased complexity exhibit a broader
range of sensitivity towards various hazardous compounds, hence bearing significance for higher organisms. The applications of microbial biosensors encompass a
wide range of fields, including but not limited to environmental monitoring and
energy production. Novel biosensors with heightened sensitivity, as opposed to
selectivity, can be achieved by implementing innovative methodologies that involve
utilizing microbial sources ranging from single cellular eukaryotic to modified
prokaryotes. In the future, the utilization of microbial biosensors is expected to
expand significantly, particularly in the areas of environmental metal pollution
monitoring and sustainable energy production [103].
5.7 Technological comparison of biosensors
In the preceding sections, an examination was conducted on the many classifications
of biosensors and their respective utilization. This section conducts a comparative
analysis of biosensors concerning their technological aspects, specificity and detection limits, linear ranges, analysis durations, costs, and mobility. Electrochemical
sensors have witnessed significant advancements in recent years, particularly in highthroughput methods. These methods have emphasized enhancing the detection limit,
reducing analysis time, and improving portability [86]. As a result, there has been a
notable expansion in the consumer market for affordable biosensors, specifically
those designed for glucose monitoring and pregnancy tests. These biosensors employ
immobilization strips with lateral-flow technology, which utilize anti-human chorionic gonadotropin. Utilizing polymers and nanomaterials for immobilizing
analytes is crucial for enhancing sensitivity and improving the detection limit.
This perspective highlights the utilization of lateral-flow technology to facilitate the
targeted delivery of samples to a particular location, enabling specified interactions
to occur, as opposed to random interactions [104]. Numerous biosensors mentioned
earlier have utilized this approach, facilitating the advancement of biofabrication
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processes that leverage contact and non-contact-based structuring approaches.
Using nanoparticles such as gold-, silver-, and silicon-based biofabrication has
developed novel methodologies. Furthermore, using polymer coatings on these
nanoparticles has led to a significant breakthrough in contact-based electrochemical
detecting. The first advantage associated with electrochemical sensors of this nature
is their high sensitivity and specificity, enabling real-time examination [105].
Nevertheless, the regeneration capacity or long-term viability of polymers and other
materials remains restricted. Nonetheless, the lower cost associated with these
electrochemical sensors renders them more economically accessible. The utilization
of contact-based sensing for single-analyte detection offers significant benefits, such
as the ability to do real-time measurements of molecules with a high degree of
specificity. Both the sensitivity and the specificity of single-compound recognition
have been enhanced through the development of various transducers, such as FRET
(fluorescence resonance energy transfer) and luminous resonating transmitting
energy, fluorescent-based transducers, and surface-plasma resonator-based transducers. Because of the overlap in the emitted signals, these methods are restricted in
their ability to identify several analytes [106]. Nevertheless, resonance energy
transfer techniques have often been used to detect numerous analytes. This is
particularly valuable in clinical diagnosis due to the distinct biomarkers in patients
and associated diseases. The use of micro- or nano-cantilevers as transducers in the
biofabrication of electrochemical sensors shows promising prospects in identifying
various analytes. Additionally, it has been noted that non-contact-based sensors
using 3D bioprinting methods, such as inkjet or laser direct writing, provide
improved results. However, these technologies have significant cost and customization stability limits. It is worth noting that most of these high-throughput
biosensors have been integrated with electrochemical sensing techniques for targeted
applications. Several highly significant amperometry electrochemical biosensors,
characterized by their sensitivity, real-time capabilities, and portability, have been
successfully developed for the purpose of disease diagnosis through the analysis of
bodily fluids [107]. Electrochemical biosensors, when utilized in conjunction with
biofabrication techniques, have a notable advantage in detecting single analytes with
high specificity, real-time analytical capabilities, and cost-effectiveness, hence
facilitating device portability. Optical-based biosensors represent a significant
advancement in the field of biosensing, namely in the domain of fiber-optic
chemistry. Hydrogel-based cross-linking is the preferred method for detecting single
molecules, such as DNA or peptides, owing to its advantageous characteristics of
high loading capacity and hydrophilicity. Subsequent advancements in optical
biosensor technology have yielded enhanced capabilities for DNA measurement,
hence expanding its utilization in the fields of biomedicine and forensic research. The
incorporation of biological constituents, including enzyme groups, antibody and
antigen combinations, and nucleic acids, has brought about substantial advancements in the realm of optical biosensor technology [108]. In addition, the biosensing
system may be expanded to include microorganisms, animal or plant cells, and tissue
sections. Optical fingerprint recognition systems were made possible by recent
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progress in molecular optoelectronics. The use of integrated optics technology
allows for incorporating both passive and active optical components onto a single
substrate, simplifying the development of compact sensing devices with diminished
dimensions. This objective is accomplished by integrating several sensors onto a
single microchip. In the present scenario, high-quality polymer compounds can
fabricate hybrid assemblies for optical biosensors. Ongoing progress in surface
anatomy studies has improved optic-based biosensor equipment using advanced
methods like high-end electrons and atomic strength microscopy. Despite these
factors, the detection limit of optical biosensors has not yet reached the femto level
due to the high equipment cost and lack of device portability. To achieve this
objective, recent advancements in optical technology have led to the development of
nanomechanical biosensors that utilize microcantilevers and surface resonance
technology [109]. These revolutionary biosensors have enabled the creation of
DNA chips capable of conducting real-time analysis with high specificity and
sensitivity. The advantages of optical biosensors primarily encompass rapid analysis,
immunity to electrical or magnetic interference, and the ability to provide a wide
range of information. However, a significant limitation of this approach is the
substantial expense associated with specific instrumentation prerequisites.
Additional challenges in optical biosensors include the complexity of immobilization, particularly in the context of biofabrication, as well as the crucial necessity for
a sterile environment. These issues must be effectively addressed to fully harness the
potential of optical biosensors. The utilization of biofabrication techniques in the
development of mechanical devices yields superior outcomes in the context of massbased biosensors. Both electrochemical and optical biosensors utilize this technology
to develop advanced biosensors. Significant progress in micro- and nanofabrication
technologies has facilitated mechanical devices’ emergence using nanoscale dimensions components [110]. The capacity to generate these structures by implementing
semiconductor processing techniques has effectively merged the principles of
biophysics and bioengineering, leading to advancements in the development of
practical biosensors at the micro- and nano-electromechanical scale, which can be
manufactured in significant quantities. Fluorescence or gold nanoparticles have
effectively labeled glass, silicon, and quartz materials. While the precision of these
biosensors in detecting single molecules is higher, the feasibility of low-cost mass
production is limited. Numerous obstacles still need to be addressed in the field of
mass-based sensors, particularly in developing improved capture agents that can be
fabricated at the nanoscale utilizing microelectronic fabrication techniques. These
advancements are crucial for enabling high-throughput analysis. It is noteworthy to
underline the significant potential applications of semiconductor materials and
quantum dot technologies in this context. Nevertheless, existing biosensor innovations exhibit a deficiency in their capacity to conduct quantitative trials concurrently
and instantaneously for extensive panels. However, micro and nano cantilevered
fabrication can provide like capability [111].
One significant advancement in biosensors is the identification of genetically
encoded or synthetic fluorescence biosensors, which enable the examination of
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molecular mechanisms underlying various biological processes. While the potential
of these sensors for detecting single molecules and measuring specific analytes is
significant, the methodology, probe preparation, and detection process pose
challenges and necessitate the use of sophisticated instruments. When considering
biomaterials, it is worth noting that microbial fuel-based biosensors provide
notable characteristics such as high sensitivity and selectivity. However, developing a
microbial strain for mass production and genetic engineering purposes necessitates
intricate procedures and incurs significant costs. Microbial biosensors provide an
additional benefit to their prospective application as tools for biological remediation, a
field of study that bears considerable significance in ecosystem surveillance [112].
Nevertheless, submitting the advancement and dissemination of genetically
modified varieties to thorough scrutiny in alignment with suitable legal frameworks
and ethical standards is crucial to concurrently guarantee the efficient administration of cultivation expenses. It is essential to advance diverse micro and nano
biosensor frameworks, including innovations based on galvanic or optically bioelectronic ideas, to attain devices with enhanced sensitivity and reduced size. It is
recommended that these foundations include a synergistic blend of macromolecules
or biological material polymers and nanoparticles [113]. A typical diagram of the
progression of biosensor creation is shown in figure 5.14.
Figure 5.14. (A) schematic diagram depicting the typical progression of biosensor creation. (A) Flowchart
outlining the steps involved in biosensor development: (1) Identification of the target protein, (2) Selection via
phage display, (3) Synthesis of peptides, (4) Diagnosis using quartz crystal microbalance (QCM), (5) Detection
via biosensors. (B) Explanation of QCM’s fundamental principle, wherein the attachment of the target protein to
immobilized peptides results in a frequency alteration in the oscillation of the quartz crystal. (C) Explanation of
electrochemical impedance spectroscopy (EIS) principle, where the binding of the target protein to immobilized
peptides leads to increased resistance to the reaction of an introduced redox couple.
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5.8 Prospective challenges, and inherent limitations associated with
biosensor technology
Contemporary methodologies used in exploring biological sensors include amalgamating several technological modalities, including electrochemical in nature, electromechanical in nature, and fluorescence-based biological sensors, incorporating
mutated microorganisms. Specific biosensors exhibit significant potential for use
in illness detection and therapy. The increasing demand and necessity for utilizing
biosensors in rapid and cost-effective analysis necessitate the development of
biofabrication techniques. These techniques will enable the identification of cellular
to whole-animal activity with a high level of accuracy in detecting single molecules.
Subsequently, directing the biosensors towards functioning under multiplex situations is essential. In the given scenario, it is necessary to employ both 2D and 3D
detection techniques, utilizing advanced transducers, in order to effectively identify
and measure minuscule analytes of signi fi cance [114]. Several significant discoveries
were achieved in this study, involving patterning at various levels using both
contact-based and non-contact-based methods. The subsequent stage of advancement should strive to uncover regenerative biosensors that possess enhanced
durability for prolonged utilization. In this occurrence, there is potential for
developing novel diagnostic biosensors that may be utilized in therapeutic applications. This advancement would offer significant benefits to both medical practitioners and those seeking treatment, as it would contribute to a more comprehensive
comprehension of diseases and their corresponding therapies in the long term. Given
these circumstances, it can be observed that using a biosensor based on fluorescence
resonance energy transfer has proven to be a highly effective diagnostic method for
evaluating the effectiveness of imatinib treatment in cases of chronic myeloid
leukemia [115]. Using aptamers, affibodies, peptide arrays, and molecularly
imprinted polymers represents conventional instances of potential study methodologies in this domain. Limited success is also attained with promising compounds
for innovative medicinal, antibacterial, and drug delivery purposes. Advancements
in this field have led to the rise of biosensors with electrochemical reactions as
reliable analytical equipment for detecting bird influenza virus infections in complex
matrices. A recent paper has elucidated the aptitude functions of affinity-based
biosensors in sports medicine and doping control analysis. Recently, a diverse range
of wearable electrochemical biosensors has been comprehensively examined. These
biosensors have explicitly been evaluated for their ability to provide real-time and
noninvasive analysis of electrolytes and metabolites in bodily fluids. This analysis
aims to serve as an indicator of an individual’s health state. Another intriguing
application is evaluating meat and fish quality using hypoxanthine biosensors via
manufacturing techniques [87]. Significant progress has been made in using
biosensors to detect bacteria, viruses, and poisons used in biological warfare.
Scholars have investigated the use of a wide range of biosensor devices, including
but not limited to electrochemical, nucleic acid, optical, and piezoelectric sensors.
The advancements possess significant potential for use within military, healthcare,
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defense, and security domains. Integrating nanomaterials and polymers with diverse
biosensors will yield hybrid devices with improved application functionality.
Furthermore, the utilization of synthetic biology techniques in the development of
microbial biosensors is expected to make a significant contribution to both environmental monitoring and the management of energy consumption [116]. The significance of employing microbial fuel cells for water treatment and, as the authors of
this paper emphasized, power sources for environmental sensors. From a larger
standpoint, we have emphasized categorizing biosensors, their prospective applications, and critical attributes such as their capacity for analyte detection, analysis
time, portability, cost, and customization [117].
5.9 Grand challenges in biosensors and biomolecular electronics
In the field of multidisciplinary research that spans the fields of chemistry, physics,
biological engineering, advanced materials, nanotechnologies, biotechnology, and
medical science, the function that biosensors perform is essential. They are now in an
established role because of the biomedical sciences and medicine. Given the
persistent and ongoing impact of the COVID-19 pandemic on world health, the
utilization of biosensors has emerged as an increasingly crucial component in health
diagnostics and illness observation [118]. Technological advancements have greatly
enhanced the development of biosensors in the interdisciplinary subject of chemistry.
This is evident via the emergence of improved sensing technologies in both academic
and industrial settings. The initial biosensor was devised during the 1950s specifically
to detect oxygen. Since their inception, biosensors have significantly improved their
sensing capabilities, modalities, flexibility, and applications.
In contrast to conventional biosensing platforms that operate on bulk surfaces,
contemporary biosensors exhibit enhanced versatility and compatibility. These
include disposable paper-based biosensing devices, printable biochips, wearable
biosensors, implantable biosensors, ingestible biosensors, and biosensors assisted by
artificial intelligence. The development of sophisticated biosensing platforms is
facilitating the transition into the era of digital health, hence contributing to
improved healthcare outcomes [119 ]. Moreover, a biosensor can achieve a degree
of sensitivity to detect individual cells and even individual molecules. The nanopore
technology currently available for detecting individual DNA or RNA molecules has
achieved a noteworthy advancement in the field of biosensors and has played a
crucial role in the efforts to combat the COVID-19 pandemic [120]. According to a
recent study, using a mobile phone microscope has demonstrated the capability to
identify a solitary molecule. This breakthrough discovery presents a significant
potential for point-of-care diagnostics since it offers substantially improved sensitivity. Ordinary papers lateral circulation tests, once paired with the procedure
known as Clustered Regularly Interspaced Short Palindromic Repeats/Cas enzymes
(CRISPR/Cas), can detect SARS-CoV-2 infections. These assays demonstrate
adequate sensitivity when used with CRISPR/Cas technology.
Furthermore, these assays can also be implemented in a wearable platform. The
rising incidence of chronic and lifestyle diseases, such as diabetes, has led to an
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increased utilization of biosensors across multiple industries. In addition to widely
utilized point-of-care equipment such as oximetry, pregnancy test strips, and glucose
test strips, the market also offers continuous glucose monitoring systems. Biosensors
have consistently exhibited efficacy in biological science and healthcare, owing to
their appealing attributes, including notable sensitivity, exceptional specificity,
convenient mobility, accessibility for end-users, prompt delivery of results, and
compatibility with various technologies and devices [121]. The rapid expansion of
the global biosensors market is primarily attributed to the enhanced functionality of
biosensors and the escalating need for efficient and affordable point-of-care testing.
Projections indicate a compound annual growth rate (CAGR) of 7.9% from 2021 to
2028. The advancement of biosensors holds promise for various applications in
healthcare. However, the full integration of biosensors into clinical practice to
enhance healthcare outcomes is still in the process of development. This is mostly
owing to several significant hurdles that need to be addressed [122].
5.9.1 Sensitivity
Identifying substances, including cytokines that modify proteins after translation,
and moving cells with cancer presents a notable obstacle owing to the considerable
background signal in clinical specimens. Using nanomaterials-based amplifiers of
signals is one of the most common ways to make something more sensitive. These
methods use nanomaterials’ big surface area to their advantage, which lets many
biorecognition molecules stick to them [123]. Nanozymes have emerged as an
exciting field, presenting benefits regarding stability, cost-effectiveness, sensitivity,
and response speed. Nevertheless, more improvements are needed to increase their
accuracy. Utilizing CRISPR/Cas technology in biosensors has emerged as an
essential step forward since 2017, primarily due to its remarkable levels of precision
and sensitivity in comparison to the commonly used nucleic acid-based signal
amplification approaches to determining nucleic acids or another analyte. Using a
CRISPR/Cas12a autocatalytic feedback amplification network enables the very
effective identification of genomic DNA in clinical samples, resulting in unparalleled
sensitivity within the molar range.
Furthermore, there are situations in which the process of sampling presents
difficulty owing to the restricted quantities of bodily fluids, such as human breath,
tears, and cerebrospinal fluid, in addition to the obstacles connected with the
development of assays that are capable of detecting minute quantities of analytes
[124]. Therefore, the collaboration between sampling, assay development, and
device engineering is necessary to achieve optimal detection. Cytokines, tiny
proteins, can be found in cerebral fluid in minimal quantities. The impact of
cytokine-binding proteins, inhibitors, and soluble cytokine receptors on the behavior
of cytokines inside biological systems has been observed. Interferences inside the
matrix of biological samples can potentially induce erroneous positive results.
Hence, to ensure precision in measurements, it is imperative to carefully consider
and explicitly specify the procedures and conditions of sample collection and
handling. To facilitate the acquisition of accurate data on cytokine levels within
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the brain or spinal cord, we have devised a portable apparatus capable of detecting
cytokines with high sensitivity directly within these anatomical regions. This
innovative technology eliminates the need for sample collection and enables realtime analysis of living organisms. In addition to implementing signal amplification
methodologies in bioassays, the engineering of devices is crucial for enhancing
sensitivity [125].
5.9.2 Multiplex capability
Multiplexing assays are of great significance in clinical practice for precision
diagnostics since they ultimately depict disease characteristics and accurate biological markers. A multiplex assay offers the advantage of concurrently detecting
many analytes, enabling high-throughput sample analysis. This approach decreases
the time required for conducting the assay and the amount of sample input needed
and minimizes the variances that may arise when performing single-plex assays. The
use of multiplexed biological sensors has many obstacles, such as constrained signal
readouts, interaction concerns, and restrictions in sensitivities [126]. Multiplex bead
binding assays, specifically Luminex multiplex assays, are widely utilized in
biomedical science and clinical research. They can do a concurrent analysis of
many analytes inside a clinical sample. The driving force for advancing the
subsequent iteration of bead-based multiplex analysis is achieving cost-efficiency
and tests that do not need specialized instruments. The simultaneous measurement
of more than three analytes without signal overlap poses a significant challenge for
electrochemical biosensors. Optical biosensors offer enhanced capabilities for
conducting multiple analyses by integrating various optical tags, including surface
plasmon resonance (SPR), surface-enhanced Raman scattering (SERS), and upconverting nanoparticles. Furthermore, the progression of printing technologies has
enabled the development of bioassays that can perform many tests simultaneously
[127]. By leveraging advancements in microfluidic technology and assay development, a lateral-flow assay successfully identified seven pathogenic single nucleotide
polymorphisms inside a solitary test strip, exhibiting a remarkable sensitivity of 0.04
−1
pg ml
. While there are several potentials for multiplexed analysis, only a limited
number of high-throughput platforms have been successfully applied in point-ofcare detection. The main obstacles in this field are the insufficient reproducibility of
detection, and the lack of robustness in the devices used [128].
5.9.3 Continuous monitoring in vivo
The provision of efficient healthcare services is contingent upon the utilization of
technological advancements that enable the continuous monitoring of physiological
parameters, hence ensuring the ongoing assessment of an individual’s health status.
Contemporary biosensing technologies necessitate integrating multiplexing capabilities, rapid reaction time, minimal sample volume and heightened sensitivity [129].
Furthermore, the achievement of in situ real-time monitoring poses an additional
challenge for biosensors; that is, the improvements in electronic and microfabrication processes have substantially improved the employment of wearable devices
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