Concise parameters and factors to consider when designing a research study and a minute introduction to molecular docking as an approach in computational research studies.
This document discusses various bioinformatics approaches for analyzing molecular interactions, including protein-protein interaction, protein-ligand interaction, docking, pharmacophore, and virtual screening. It provides details on each topic, describing things like how protein-protein interactions occur and are classified, common methods for studying protein-ligand interactions, the basic process and types of docking, and the definition of a pharmacophore. The key topics covered are protein-protein interaction, protein-ligand interaction analysis through methods like docking, and virtual screening using pharmacophore models.
WE THE STUDENT OF PHARMACEUTICAL CHEMISTRY FROM GURUNANAK COLLEGE OF PHARMACY HAS PRESENTED QSRR, TO MAKE READERS EASILY AVAILABLE, A COMPLETE TOPIC OF MPHARM 1ST YEAR WHICH WILL MAKE THEIR STUDY AND TO COLLECT DATA MORE EASILY AT A PLACE.
The document discusses stages of drug discovery including compound sources, filtering, screening, target identification, validation, and lead identification and optimization. It describes principles of drug design such as designing new molecules, understanding structure-activity relationships, and analyzing absorption, distribution, metabolism, and excretion. Drug design approaches include knowing properties that make a molecule a drug and receptor, and designing drugs to fit receptors. Types of drug design discussed are theoretical using quantitative structure-activity relationships and structure-based techniques like docking, X-ray crystallography, and homology modeling.
The techniques of drug designing and in silico studies are well defines in this presentation. Mooreover, the various softwares which are used in new era for determining the drug targets inside the body are elaborated.
Drug discovery is an expensive and lengthy process involving high costs and extensive testing over 10-15 years. Computer-aided drug design techniques like molecular modeling, virtual screening, and quantitative structure-activity relationships (QSAR) are helping to improve the drug discovery process. Molecular docking uses computer models to predict how drug molecules bind to their protein targets. Key steps in docking include target and ligand preparation, docking simulations, and analysis of results. Factors like intermolecular forces, flexibility, and binding site selection influence docking accuracy. QSAR analyses seek mathematical correlations between compound structures and their biological activities to enable prediction of new candidates.
The Complete Guide for Metabolomics Methods and ApplicationBennie George
This document provides an overview of metabolomics methods and applications. It discusses untargeted metabolomics which scans for all small molecule ions to identify metabolites by comparing mass spectra to databases. Targeted metabolomics can now simultaneously quantify over 1000 metabolites compared to around 10 previously. The new targeted metabolomics approach features easier metabolite identification and streamlined data analysis. Potential applications of this approach discussed include clinical metabolomics, pharmacometabolomics, environmental metabolomics, food metabolomics, plant metabolomics, and transplant metabolomics.
The Complete Guide for Metabolomics Methods and ApplicationBennie George
Metabolomics(Metabolomics) is a new system of biological technology developed by the post-gene era, aimed at the determination of all small organisms within the metabolites. Compared to Genomics, Transcriptomics and Proteomics, metabolomics directly and accurately reflects the current state of the organism and tell us what happens to the organism instead of predicting what may happen! Metabolomics includes untargeted metabolomics, targeted Metabolomics and next-generation target metabolomics according to their detection of metabolites.
view more: http://www.creative-proteomics.com/services/menu-of-metabolomics-services.htm
Immunoassay methods and their application in pharmaceutical analysisSibasishDey1
This document discusses immunoassay methods and their applications in pharmaceutical analysis. It begins by defining immunoassays as tests that use antibody-antigen complexes to generate a measurable result. It then covers the basic principles, classifications, common immunoassay methods like RIA, ELISA, and advances in preparation, methodology, and instrumentation. Immunoassays are described as having wide applications in areas like disease diagnosis, therapeutic drug monitoring, and bioequivalence studies due to their ability to quantify a variety of compounds.
This document discusses various bioinformatics approaches for analyzing molecular interactions, including protein-protein interaction, protein-ligand interaction, docking, pharmacophore, and virtual screening. It provides details on each topic, describing things like how protein-protein interactions occur and are classified, common methods for studying protein-ligand interactions, the basic process and types of docking, and the definition of a pharmacophore. The key topics covered are protein-protein interaction, protein-ligand interaction analysis through methods like docking, and virtual screening using pharmacophore models.
WE THE STUDENT OF PHARMACEUTICAL CHEMISTRY FROM GURUNANAK COLLEGE OF PHARMACY HAS PRESENTED QSRR, TO MAKE READERS EASILY AVAILABLE, A COMPLETE TOPIC OF MPHARM 1ST YEAR WHICH WILL MAKE THEIR STUDY AND TO COLLECT DATA MORE EASILY AT A PLACE.
The document discusses stages of drug discovery including compound sources, filtering, screening, target identification, validation, and lead identification and optimization. It describes principles of drug design such as designing new molecules, understanding structure-activity relationships, and analyzing absorption, distribution, metabolism, and excretion. Drug design approaches include knowing properties that make a molecule a drug and receptor, and designing drugs to fit receptors. Types of drug design discussed are theoretical using quantitative structure-activity relationships and structure-based techniques like docking, X-ray crystallography, and homology modeling.
The techniques of drug designing and in silico studies are well defines in this presentation. Mooreover, the various softwares which are used in new era for determining the drug targets inside the body are elaborated.
Drug discovery is an expensive and lengthy process involving high costs and extensive testing over 10-15 years. Computer-aided drug design techniques like molecular modeling, virtual screening, and quantitative structure-activity relationships (QSAR) are helping to improve the drug discovery process. Molecular docking uses computer models to predict how drug molecules bind to their protein targets. Key steps in docking include target and ligand preparation, docking simulations, and analysis of results. Factors like intermolecular forces, flexibility, and binding site selection influence docking accuracy. QSAR analyses seek mathematical correlations between compound structures and their biological activities to enable prediction of new candidates.
The Complete Guide for Metabolomics Methods and ApplicationBennie George
This document provides an overview of metabolomics methods and applications. It discusses untargeted metabolomics which scans for all small molecule ions to identify metabolites by comparing mass spectra to databases. Targeted metabolomics can now simultaneously quantify over 1000 metabolites compared to around 10 previously. The new targeted metabolomics approach features easier metabolite identification and streamlined data analysis. Potential applications of this approach discussed include clinical metabolomics, pharmacometabolomics, environmental metabolomics, food metabolomics, plant metabolomics, and transplant metabolomics.
The Complete Guide for Metabolomics Methods and ApplicationBennie George
Metabolomics(Metabolomics) is a new system of biological technology developed by the post-gene era, aimed at the determination of all small organisms within the metabolites. Compared to Genomics, Transcriptomics and Proteomics, metabolomics directly and accurately reflects the current state of the organism and tell us what happens to the organism instead of predicting what may happen! Metabolomics includes untargeted metabolomics, targeted Metabolomics and next-generation target metabolomics according to their detection of metabolites.
view more: http://www.creative-proteomics.com/services/menu-of-metabolomics-services.htm
Immunoassay methods and their application in pharmaceutical analysisSibasishDey1
This document discusses immunoassay methods and their applications in pharmaceutical analysis. It begins by defining immunoassays as tests that use antibody-antigen complexes to generate a measurable result. It then covers the basic principles, classifications, common immunoassay methods like RIA, ELISA, and advances in preparation, methodology, and instrumentation. Immunoassays are described as having wide applications in areas like disease diagnosis, therapeutic drug monitoring, and bioequivalence studies due to their ability to quantify a variety of compounds.
This document discusses the key steps in the drug discovery process, including target identification and validation, lead identification, and lead optimization. It describes how identifying the biological target of a disease is the first step, followed by validating that target. Leads are then identified, which are compounds that show desired biological activity against the validated target. The leads undergo optimization to improve properties like potency. Methods for target identification, lead identification, and lead optimization are also outlined.
Metabolites have various functions, including fuel, structure, signaling, stimulatory and inhibitory effects on enzymes, catalytic activity of their own (usually as a cofactor to an enzyme), defense, and interactions with other organisms (e.g. pigments, odorants, and pheromones).
Metabolome refers to the complete set of chemical compounds involved in an organism's metabolism (such as metabolic intermediates, hormones and other signaling molecules, and secondary metabolites)
Metabolomics is the scientific study of chemical processes involving metabolites. Metabolomics is a relatively new member to the ‘-omics’ family of systems biology technologies.
In silico drug design uses computer simulation and modeling to aid the drug discovery process. There are two main approaches: ligand-based drug design which relies on knowledge of molecules that bind to the target, and structure-based drug design which uses the 3D structure of the target. The basic steps are to select a disease target, validate the target, determine the target structure, screen compound libraries through docking simulations to identify potential drug leads, optimize lead compounds, and progress to preclinical and clinical testing. In silico methods help eliminate compounds that may have toxicity or interaction issues early in the discovery process.
Proteomics is a discipline that analyzes the dynamics of protein components, including expression levels and modification states from a holistic perspective, understands the interactions and connections between proteins, reveals the function of proteins and the laws of cell life, and studies all proteins in cells and their behaviours. Creative Proteomics can provide a comprehensive range of proteomics services to help you better conduct research in the drug discovery process, which include: protein gel and imaging analysis, protein identification, protein quantification, top-down proteomics, peptidomics, post-translational modification analysis, and protein-protein interaction. https://www.creative-proteomics.com/services/protein-gel-and-imaging-analysis.htm
Proteomics is a discipline that analyzes the dynamics of protein components, including expression levels and modification states from a holistic perspective, understands the interactions and connections between proteins, reveals the function of proteins and the laws of cell life, and studies all proteins in cells and their behaviours. Creative Proteomics can provide a comprehensive range of proteomics services to help you better conduct research in the drug discovery process, which includes: protein gel and imaging analysis, protein identification, protein quantification, top-down proteomics, peptidomics, post-translational modification analysis, and protein-protein interaction. https://www.creative-proteomics.com/services/protein-gel-and-imaging-analysis.htm
Proteomics is a discipline that analyzes the dynamics of protein components, including expression levels and modification states from a holistic perspective, understands the interactions and connections between proteins, reveals the function of proteins and the laws of cell life, and studies all proteins in cells and their behaviours. Creative Proteomics can provide a comprehensive range of proteomics services to help you better conduct research in the drug discovery process, which includes: protein gel and imaging analysis, protein identification, protein quantification, top-down proteomics, peptidomics, post-translational modification analysis, and protein-protein interaction. https://www.creative-proteomics.com/services/protein-gel-and-imaging-analysis.htm
Metabolomics is the large-scale study of small molecule metabolites within organisms. It analyzes substrates and products of metabolism that are influenced by genetic and environmental factors, providing insights into biochemical activity and molecular phenotypes. Metabolomics studies involve collecting samples, extracting and preparing metabolites, and using techniques like chromatography-mass spectrometry to measure metabolite levels. Statistical analysis of metabolomics data uses multivariate methods to identify relationships between variables and discover biomarkers or characterize changes related to factors like diseases, genetics, and environment. Applications of metabolomics include improving agriculture, discovering disease biomarkers, and enabling more personalized medicine through comprehensive metabolic profiling.
Microorganisms such as bacteria, actinomycetes, and fungi are ubiquitous on our planet. They are widely distributed in soil, water, the human body and other environments. Microorganisms and their activities are of great importance to biogeochemical cycles and to all biological systems. Creative Proteomics provides a one-stop proteomics service from sample collection, protein separation, to protein quantification and bioinformatics analysis. We offer both relative quantification (including iTRAQ, TMT and SILAC) and absolute quantification (such as SRM/MRM and PRM) approaches to help you discover, detect and quantify proteins in a broad array of samples. https://www.creative-proteomics.com/services/proteomics-service.htm
Microorganisms such as bacteria, actinomycetes, and fungi are ubiquitous on our planet. They are widely distributed in soil, water, the human body and other environments. Microorganisms and their activities are of great importance to biogeochemical cycles and to all biological systems. Creative Proteomics provides a one-stop proteomics service from sample collection, protein separation, to protein quantification and bioinformatics analysis. We offer both relative quantification (including iTRAQ, TMT and SILAC) and absolute quantification (such as SRM/MRM and PRM) approaches to help you discover, detect and quantify proteins in a broad array of samples. https://www.creative-proteomics.com/services/proteomics-service.htm
In silico drug designing is the drug design which can be carried out in silicon chip,i.e., within computers. The slides are helpful to know a brief description about in silico drug designing.
Proteomics is the study of the proteome, which is the entire set of proteins expressed by a genome, cell, tissue or organism. This document discusses several techniques used in proteomics including 2D gel electrophoresis, mass spectrometry, and protein databases. It provides examples of applications such as biomarker identification for disease diagnosis and drug target discovery. Limitations include the complexity of proteomes and no single technique being adequate for complete analysis. Overall, proteomics techniques help further our understanding of protein structure, function and interactions to gain insights into biological processes and diseases.
Computational (In Silico) Pharmacology.pdfssuser515ca21
This document provides an overview of computational pharmacology and its applications. It discusses molecular modeling and simulation techniques like molecular docking, dynamics simulations, and QSAR modeling. It also covers pharmacokinetic and pharmacodynamic modeling to predict how drugs move through and act on the body. Computational pharmacology uses these in silico methods to better understand drug effects at a cellular level without extensive experimentation.
Natural products are an important source for drug discovery. The drug discovery process involves several steps including target identification, validation, lead identification and optimization through screening compounds for activity against the target. Promising lead compounds then undergo preclinical testing in labs and animal models before progressing to human clinical trials. Computational tools also play an important role in drug design, such as identifying binding sites on target proteins and modeling molecular interactions to optimize lead compounds. Natural products, especially toxins from venom, continue to provide templates for rational drug design.
In silico drug design/Molecular dockingKannan Iyanar
This document discusses rational drug design using computational methods. It begins by explaining how drugs work by binding to biological targets like proteins. It then discusses the need for new drugs to treat new diseases or improve current treatments. The document outlines several methods for screening and designing new drugs, including studying natural products, making modifications, and rational drug design based on understanding the molecular disease process. It describes using the 3D structure of protein targets and molecular docking to design ligands that selectively bind targets. The goals of drug design are to find molecules that effectively bind targets while also having suitable absorption, distribution, metabolism, excretion and toxicity properties. Computational methods can help streamline the drug discovery process.
Liquid chromatography-mass spectrometry (LC-MS) is a powerful analytical technique that combines liquid chromatography with mass spectrometry. LC-MS can characterize biologics and biosimilars by providing information on molecular weight, structure, and quantity. It has advantages like accuracy, specificity, selectivity, and speed. LC-MS is used in areas like drug discovery, clinical analysis, proteomics, and pharmaceutical applications. Advances in mass spectrometry techniques allow for characterization of protein primary and higher order structures important for biologics development.
In spite of extensive effort by industry and academia to develop new drugs, there are still several diseases that are in need of therapeutic agents and have yet to be developed.
10 years the identification rate of disease-associated targets has been higher than the therapeutics identification rate.
Nevertheless, it is apparent that computational tools provide high hopes that many of the diseases under investigation can be brought under control.
Computer aided drug design uses computational approaches to aid in the drug discovery process. There are several key approaches including ligand based approaches which identify characteristics of known active ligands, target based approaches which use information about the biological target, and structure based drug design which utilizes 3D structural information. The main steps in drug design include target identification and validation, lead identification and optimization, and preclinical and clinical trials. Computational tools are used throughout the process for tasks like molecular docking, ADMET prediction, and structure activity relationship analysis.
Genomics and proteomics have many applications in fields like medicine, biotechnology, and social sciences. Genomics allows for better understanding of disease bases and drug responses by integrating genomic data with other data types. Proteomics identifies protein structures, functions, and interactions through techniques like identifying biomarkers, studying post-translational modifications, and analyzing protein expression profiles. These 'omics technologies continue to provide insights into disease mechanisms and potential drug targets.
This document discusses the use of metabolomics in chemical-biological defense scenarios. Metabolomics allows for the analysis of small molecule mixtures in bodily fluids and tissues using techniques like NMR spectroscopy and mass spectrometry. Integrated analysis of metabolites can enable early detection, appropriate response, and improved health outcomes in exposure cases. Both targeted and untargeted metabolomics approaches are used. Key challenges include analyzing samples with low metabolite concentrations and resolving signal overlaps. Metabolomics reveals how chemicals impact biological systems even when the chemicals themselves cannot be directly detected.
Drug discovery begins with identifying a biological target associated with a disease. Targets are validated through techniques like gene silencing to confirm their role in the disease process. Potential drug candidates, or leads, are identified through screening libraries of compounds or rational drug design. Leads undergo optimization to improve their safety, efficacy, and other properties. The entire drug discovery and development process takes an average of 15 years and over $800 million, with high failure rates contributing to the rising costs of drug development.
This document discusses the key steps in the drug discovery process, including target identification and validation, lead identification, and lead optimization. It describes how identifying the biological target of a disease is the first step, followed by validating that target. Leads are then identified, which are compounds that show desired biological activity against the validated target. The leads undergo optimization to improve properties like potency. Methods for target identification, lead identification, and lead optimization are also outlined.
Metabolites have various functions, including fuel, structure, signaling, stimulatory and inhibitory effects on enzymes, catalytic activity of their own (usually as a cofactor to an enzyme), defense, and interactions with other organisms (e.g. pigments, odorants, and pheromones).
Metabolome refers to the complete set of chemical compounds involved in an organism's metabolism (such as metabolic intermediates, hormones and other signaling molecules, and secondary metabolites)
Metabolomics is the scientific study of chemical processes involving metabolites. Metabolomics is a relatively new member to the ‘-omics’ family of systems biology technologies.
In silico drug design uses computer simulation and modeling to aid the drug discovery process. There are two main approaches: ligand-based drug design which relies on knowledge of molecules that bind to the target, and structure-based drug design which uses the 3D structure of the target. The basic steps are to select a disease target, validate the target, determine the target structure, screen compound libraries through docking simulations to identify potential drug leads, optimize lead compounds, and progress to preclinical and clinical testing. In silico methods help eliminate compounds that may have toxicity or interaction issues early in the discovery process.
Proteomics is a discipline that analyzes the dynamics of protein components, including expression levels and modification states from a holistic perspective, understands the interactions and connections between proteins, reveals the function of proteins and the laws of cell life, and studies all proteins in cells and their behaviours. Creative Proteomics can provide a comprehensive range of proteomics services to help you better conduct research in the drug discovery process, which include: protein gel and imaging analysis, protein identification, protein quantification, top-down proteomics, peptidomics, post-translational modification analysis, and protein-protein interaction. https://www.creative-proteomics.com/services/protein-gel-and-imaging-analysis.htm
Proteomics is a discipline that analyzes the dynamics of protein components, including expression levels and modification states from a holistic perspective, understands the interactions and connections between proteins, reveals the function of proteins and the laws of cell life, and studies all proteins in cells and their behaviours. Creative Proteomics can provide a comprehensive range of proteomics services to help you better conduct research in the drug discovery process, which includes: protein gel and imaging analysis, protein identification, protein quantification, top-down proteomics, peptidomics, post-translational modification analysis, and protein-protein interaction. https://www.creative-proteomics.com/services/protein-gel-and-imaging-analysis.htm
Proteomics is a discipline that analyzes the dynamics of protein components, including expression levels and modification states from a holistic perspective, understands the interactions and connections between proteins, reveals the function of proteins and the laws of cell life, and studies all proteins in cells and their behaviours. Creative Proteomics can provide a comprehensive range of proteomics services to help you better conduct research in the drug discovery process, which includes: protein gel and imaging analysis, protein identification, protein quantification, top-down proteomics, peptidomics, post-translational modification analysis, and protein-protein interaction. https://www.creative-proteomics.com/services/protein-gel-and-imaging-analysis.htm
Metabolomics is the large-scale study of small molecule metabolites within organisms. It analyzes substrates and products of metabolism that are influenced by genetic and environmental factors, providing insights into biochemical activity and molecular phenotypes. Metabolomics studies involve collecting samples, extracting and preparing metabolites, and using techniques like chromatography-mass spectrometry to measure metabolite levels. Statistical analysis of metabolomics data uses multivariate methods to identify relationships between variables and discover biomarkers or characterize changes related to factors like diseases, genetics, and environment. Applications of metabolomics include improving agriculture, discovering disease biomarkers, and enabling more personalized medicine through comprehensive metabolic profiling.
Microorganisms such as bacteria, actinomycetes, and fungi are ubiquitous on our planet. They are widely distributed in soil, water, the human body and other environments. Microorganisms and their activities are of great importance to biogeochemical cycles and to all biological systems. Creative Proteomics provides a one-stop proteomics service from sample collection, protein separation, to protein quantification and bioinformatics analysis. We offer both relative quantification (including iTRAQ, TMT and SILAC) and absolute quantification (such as SRM/MRM and PRM) approaches to help you discover, detect and quantify proteins in a broad array of samples. https://www.creative-proteomics.com/services/proteomics-service.htm
Microorganisms such as bacteria, actinomycetes, and fungi are ubiquitous on our planet. They are widely distributed in soil, water, the human body and other environments. Microorganisms and their activities are of great importance to biogeochemical cycles and to all biological systems. Creative Proteomics provides a one-stop proteomics service from sample collection, protein separation, to protein quantification and bioinformatics analysis. We offer both relative quantification (including iTRAQ, TMT and SILAC) and absolute quantification (such as SRM/MRM and PRM) approaches to help you discover, detect and quantify proteins in a broad array of samples. https://www.creative-proteomics.com/services/proteomics-service.htm
In silico drug designing is the drug design which can be carried out in silicon chip,i.e., within computers. The slides are helpful to know a brief description about in silico drug designing.
Proteomics is the study of the proteome, which is the entire set of proteins expressed by a genome, cell, tissue or organism. This document discusses several techniques used in proteomics including 2D gel electrophoresis, mass spectrometry, and protein databases. It provides examples of applications such as biomarker identification for disease diagnosis and drug target discovery. Limitations include the complexity of proteomes and no single technique being adequate for complete analysis. Overall, proteomics techniques help further our understanding of protein structure, function and interactions to gain insights into biological processes and diseases.
Computational (In Silico) Pharmacology.pdfssuser515ca21
This document provides an overview of computational pharmacology and its applications. It discusses molecular modeling and simulation techniques like molecular docking, dynamics simulations, and QSAR modeling. It also covers pharmacokinetic and pharmacodynamic modeling to predict how drugs move through and act on the body. Computational pharmacology uses these in silico methods to better understand drug effects at a cellular level without extensive experimentation.
Natural products are an important source for drug discovery. The drug discovery process involves several steps including target identification, validation, lead identification and optimization through screening compounds for activity against the target. Promising lead compounds then undergo preclinical testing in labs and animal models before progressing to human clinical trials. Computational tools also play an important role in drug design, such as identifying binding sites on target proteins and modeling molecular interactions to optimize lead compounds. Natural products, especially toxins from venom, continue to provide templates for rational drug design.
In silico drug design/Molecular dockingKannan Iyanar
This document discusses rational drug design using computational methods. It begins by explaining how drugs work by binding to biological targets like proteins. It then discusses the need for new drugs to treat new diseases or improve current treatments. The document outlines several methods for screening and designing new drugs, including studying natural products, making modifications, and rational drug design based on understanding the molecular disease process. It describes using the 3D structure of protein targets and molecular docking to design ligands that selectively bind targets. The goals of drug design are to find molecules that effectively bind targets while also having suitable absorption, distribution, metabolism, excretion and toxicity properties. Computational methods can help streamline the drug discovery process.
Liquid chromatography-mass spectrometry (LC-MS) is a powerful analytical technique that combines liquid chromatography with mass spectrometry. LC-MS can characterize biologics and biosimilars by providing information on molecular weight, structure, and quantity. It has advantages like accuracy, specificity, selectivity, and speed. LC-MS is used in areas like drug discovery, clinical analysis, proteomics, and pharmaceutical applications. Advances in mass spectrometry techniques allow for characterization of protein primary and higher order structures important for biologics development.
In spite of extensive effort by industry and academia to develop new drugs, there are still several diseases that are in need of therapeutic agents and have yet to be developed.
10 years the identification rate of disease-associated targets has been higher than the therapeutics identification rate.
Nevertheless, it is apparent that computational tools provide high hopes that many of the diseases under investigation can be brought under control.
Computer aided drug design uses computational approaches to aid in the drug discovery process. There are several key approaches including ligand based approaches which identify characteristics of known active ligands, target based approaches which use information about the biological target, and structure based drug design which utilizes 3D structural information. The main steps in drug design include target identification and validation, lead identification and optimization, and preclinical and clinical trials. Computational tools are used throughout the process for tasks like molecular docking, ADMET prediction, and structure activity relationship analysis.
Genomics and proteomics have many applications in fields like medicine, biotechnology, and social sciences. Genomics allows for better understanding of disease bases and drug responses by integrating genomic data with other data types. Proteomics identifies protein structures, functions, and interactions through techniques like identifying biomarkers, studying post-translational modifications, and analyzing protein expression profiles. These 'omics technologies continue to provide insights into disease mechanisms and potential drug targets.
This document discusses the use of metabolomics in chemical-biological defense scenarios. Metabolomics allows for the analysis of small molecule mixtures in bodily fluids and tissues using techniques like NMR spectroscopy and mass spectrometry. Integrated analysis of metabolites can enable early detection, appropriate response, and improved health outcomes in exposure cases. Both targeted and untargeted metabolomics approaches are used. Key challenges include analyzing samples with low metabolite concentrations and resolving signal overlaps. Metabolomics reveals how chemicals impact biological systems even when the chemicals themselves cannot be directly detected.
Drug discovery begins with identifying a biological target associated with a disease. Targets are validated through techniques like gene silencing to confirm their role in the disease process. Potential drug candidates, or leads, are identified through screening libraries of compounds or rational drug design. Leads undergo optimization to improve their safety, efficacy, and other properties. The entire drug discovery and development process takes an average of 15 years and over $800 million, with high failure rates contributing to the rising costs of drug development.
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4. Interaction Parameters 🖜
Interaction parameter refers to the
cellular, macromolecular, and atomistic
effects of pathogenic and physiological
interactions in a biological system.
Every research study is designed to assay
for key interaction parameters.
5. Interaction Parameters Assays(I.P.A)
This is the jargon that defines the
experiment type that will carried out
to assess the interaction parameters
in any biological system.
There are two types. They are:
• Biophysical interactions assays
• Biological consequence(s) assays
What is
I.P.A?
Types of
I.P.A
🖜
7. Biophysical Interaction Assays
What are these assays?
Biophysical interactions, which are the macro
and micro- molecular associations in the
living system are assayed through the
following experimental methods.
• Macromolecular Crystallography e.g protein
crystallography
• Computer Aided Drug Design e.g molecular
docking, molecular dynamics simulation.
• Gravimetric Analysis e.g Quartz Crystal
Microbalance(QCM)
• Biolayer Interferometry(BLI).
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8. Biological Consequence Assays
What are these?
We assess the outcome of the biomolecular
interactions taking place in the living
system.
These biological outcomes can be
transcriptomic, proteomic, cellular and/or
morphological.
• Blots e.g western blot, northern blot
• Enzyme-linked Immunosorbent Assay(ELISA)
• Spectrophotometry
• Microscopy
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9. Nota Bene!
How do I choose the right assays
for my study?
🖜
It's vital to remember that identifying and
understanding the relevant biomolecular
pathway(s) will help you choose the best
assay(s) to utilize in your research project.
This only suggests that the selection of an
assay is dependent upon the biomolecular
pathway(s) of the pathogenic condition being
investigated in every given research.
11. Molecular docking?
● The goal of ligand-protein
docking/protein-protein
docking is to predict the
predominant binding mode(s)
of a ligand with a protein
of known three-dimensional
structure.
12. Steps involved in molecular docking
Accession and Preparation of implicated
protein targets.
Protei
ns
Accession and Preparation of
compounds/ligands/drugs of study.
Ligand
s
Molecular docking and visualization of the
docking analysis.
D-R
Complex
14. WHY PROTEINS?
The knowledge of your protein
target is the most crucial of all
molecular docking steps.
Protein(s) of study
shouldn’t be retrieved
without prior
understanding of its
structure(tertiary
structure-3D) as this tells
us a lot about it
function(s).