Analytical method development by liquid chromatography
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This book discusses analytical methods developed for drug determination in pharmaceutical dosage forms and biological fluids using chromatography techniques like RP-HPLC and LC-MS/MS. Methods have been validated for categories of drugs including antihypertensives, antihyperlipidemics, skeletal muscle relaxants, NSAIDs, antibiotics, anticonvulsants, antivirals, and analeptics. The book is available for purchase worldwide in both physical and online stores. It describes the development and validation of analytical methods to quantify selected drugs according to FDA and cGMP guidelines.
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Analytical method development by liquid chromatography
Analytical methods development and validation play important roles in the discovery, development, and manufacture of pharmaceuticals. The current good manufacturing practice (cGMP) and Food Drug Administration (FDA) Guidelines insist for adoption of sound methods of analysis with greater sensitivity and reproducibility. This thesis describes analytical methods developed for drug determination in pharmaceutical dosage forms and biological matrixes including Chromatography (RP-HPLC) and Hyphenated Techniques (LC-MS/MS). Methods have been developed for separation and quantification of selected drugs from categories like Antihypertensive, Antihyperlipidemic, Skeletal Muscle Relaxant, Non-Steroidal Anti-inflammatory Drug (NSAID), Antibiotic, Anticonvulsant, Antiviral, and Analeptic.
Session 1 part 3
The drug discovery process involves several steps:
1) Hits from high-throughput screening are identified, which may have many potential scaffolds.
2) Hit-to-lead involves synthesizing many compounds to determine structure-activity relationships and improve properties.
3) Lead optimization aims to increase potency, selectivity, and in vivo efficacy while maintaining favorable properties. Efficient synthesis and parallel chemistry methods are important throughout the process.
Slicing and dicing curated protein targets: Analysing the drugged, druggable ...
Slicing and dicing curated protein targets: Analysing the drugged, druggable ...Guide to PHARMACOLOGY
Presented by team member Chris Southan in April 2015 at the BPS Focused meeting in Edinburgh: Exploiting the new pharmacology and application to drug discovery.Pharmacophore Modeling in Drug Designing
This document discusses pharmacophore modeling and computer-aided drug design. It begins with objectives of studying pharmacophore modeling methods and techniques for lead prioritization and optimization. An introduction defines pharmacophore as the schematic representation of bioactive functional groups and their distances. It then reviews surveys on G-protein coupled receptors in drug development and advances in pharmacophore modeling applications. The document outlines the process of pharmacophore-based drug design and provides an example using morphine. It also shows 3D pharmacophores and how computer-aided design is used. It concludes that pharmacophore approaches have been major tools in drug discovery and various methods have been applied successfully in virtual screening and lead optimization.
Pharmacophore modeling: A continuously evolving tool for computational drug d...
In the latest two or three years progressive
applications of pharmacophore modeling continue to appear in literature. Pharmacophore based parallel screening, for instance, has been introduced in 2006. Moreover, in 2008, a survey discussing the prospective impact of virtual screening techniques in the
discovery of bioactive natural products has been published.
Lecture 7 computer aided drug design
This lecture discusses computer aided drug design (CADD). CADD uses computational methods to aid in drug discovery and design. It involves identifying drug targets, generating potential drug molecule "hits" through virtual screening, and optimizing "leads" through modeling protein-ligand interactions and simulating the effects of molecular modifications. The key steps are target identification, validation of targets, lead identification through screening libraries or de novo design, lead optimization through docking simulations, and preclinical/clinical trials. CADD approaches like ligand-based, target-based, and structure-based drug design can speed up the drug development process and reduce costs compared to traditional experimental methods alone.
Pharmacophore Q&A
This document is a Q&A with Sean Ekins about his work developing pharmacophores for drug discovery. Some key points:
- He started using pharmacophores in 1996 to understand CYP2B6 substrates, and found them intuitive and useful for predicting new molecules.
- Pharmacophores allowed him to work on more complex endpoints beyond just P450 enzymes, including transporters.
- While some of his early work lacked high resolution images, the models still provided insights and suggested features to look for or avoid in new molecules.
- Over time he expanded his use of pharmacophores to understand target evolution, drug repurposing, environmental impacts, and more. Transporters are an area
Rational drug design method
This document discusses methods of rational drug design, including pharmacophore-based and structure-based approaches. Pharmacophore-based rational drug design identifies essential features like electrostatic interactions, hydrogen bonding, and aromatic interactions that define a receptor's active site. Structure-based rational drug design uses computational methods to model how ligands bind to proteins and predict their binding affinity and pose. The key steps are identifying the receptor's structure and function, designing drug molecules that fit the receptor, and testing candidates through synthesis and studies.
Recommended
Analytical method development by liquid chromatography
Analytical methods development and validation play important roles in the discovery, development, and manufacture of pharmaceuticals. The current good manufacturing practice (cGMP) and Food Drug Administration (FDA) Guidelines insist for adoption of sound methods of analysis with greater sensitivity and reproducibility. This thesis describes analytical methods developed for drug determination in pharmaceutical dosage forms and biological matrixes including Chromatography (RP-HPLC) and Hyphenated Techniques (LC-MS/MS). Methods have been developed for separation and quantification of selected drugs from categories like Antihypertensive, Antihyperlipidemic, Skeletal Muscle Relaxant, Non-Steroidal Anti-inflammatory Drug (NSAID), Antibiotic, Anticonvulsant, Antiviral, and Analeptic.
Session 1 part 3
The drug discovery process involves several steps:
1) Hits from high-throughput screening are identified, which may have many potential scaffolds.
2) Hit-to-lead involves synthesizing many compounds to determine structure-activity relationships and improve properties.
3) Lead optimization aims to increase potency, selectivity, and in vivo efficacy while maintaining favorable properties. Efficient synthesis and parallel chemistry methods are important throughout the process.
Slicing and dicing curated protein targets: Analysing the drugged, druggable ...
Slicing and dicing curated protein targets: Analysing the drugged, druggable ...Guide to PHARMACOLOGY
Presented by team member Chris Southan in April 2015 at the BPS Focused meeting in Edinburgh: Exploiting the new pharmacology and application to drug discovery.Pharmacophore Modeling in Drug Designing
This document discusses pharmacophore modeling and computer-aided drug design. It begins with objectives of studying pharmacophore modeling methods and techniques for lead prioritization and optimization. An introduction defines pharmacophore as the schematic representation of bioactive functional groups and their distances. It then reviews surveys on G-protein coupled receptors in drug development and advances in pharmacophore modeling applications. The document outlines the process of pharmacophore-based drug design and provides an example using morphine. It also shows 3D pharmacophores and how computer-aided design is used. It concludes that pharmacophore approaches have been major tools in drug discovery and various methods have been applied successfully in virtual screening and lead optimization.
Pharmacophore modeling: A continuously evolving tool for computational drug d...
In the latest two or three years progressive
applications of pharmacophore modeling continue to appear in literature. Pharmacophore based parallel screening, for instance, has been introduced in 2006. Moreover, in 2008, a survey discussing the prospective impact of virtual screening techniques in the
discovery of bioactive natural products has been published.
Lecture 7 computer aided drug design
This lecture discusses computer aided drug design (CADD). CADD uses computational methods to aid in drug discovery and design. It involves identifying drug targets, generating potential drug molecule "hits" through virtual screening, and optimizing "leads" through modeling protein-ligand interactions and simulating the effects of molecular modifications. The key steps are target identification, validation of targets, lead identification through screening libraries or de novo design, lead optimization through docking simulations, and preclinical/clinical trials. CADD approaches like ligand-based, target-based, and structure-based drug design can speed up the drug development process and reduce costs compared to traditional experimental methods alone.
Pharmacophore Q&A
This document is a Q&A with Sean Ekins about his work developing pharmacophores for drug discovery. Some key points:
- He started using pharmacophores in 1996 to understand CYP2B6 substrates, and found them intuitive and useful for predicting new molecules.
- Pharmacophores allowed him to work on more complex endpoints beyond just P450 enzymes, including transporters.
- While some of his early work lacked high resolution images, the models still provided insights and suggested features to look for or avoid in new molecules.
- Over time he expanded his use of pharmacophores to understand target evolution, drug repurposing, environmental impacts, and more. Transporters are an area
Rational drug design method
This document discusses methods of rational drug design, including pharmacophore-based and structure-based approaches. Pharmacophore-based rational drug design identifies essential features like electrostatic interactions, hydrogen bonding, and aromatic interactions that define a receptor's active site. Structure-based rational drug design uses computational methods to model how ligands bind to proteins and predict their binding affinity and pose. The key steps are identifying the receptor's structure and function, designing drug molecules that fit the receptor, and testing candidates through synthesis and studies.
Pharmacophore mapping
The document discusses pharmacophores, which are abstract descriptions of molecular features necessary for molecular recognition between a ligand and biological macromolecule. A pharmacophore consists of 3D structural features like hydrophobic groups and hydrogen bond donors/acceptors. Pharmacophore mapping is used to define pharmacophoric features and align molecules to identify common binding elements responsible for biological activity. Pharmacophore models can be used in virtual screening to filter large databases and identify new compounds that may bind similarly to known active molecules. The document provides details on different approaches for pharmacophore generation and searching compound libraries.
Target Based Drug Combination Selection
The presentation outlines an algorithm to identify combinations of drug for a given therapeutic endpoint.
The objective is to target different stages of the disease pathway.
Chemoinformatics as employed by Ontomine, a US patent pending algorithm is employed for the same.
Research work plan for Drug Design
This is to help the young researchers to carry out their research in Pharmaceutical Chemistry, Medicinal Chemistry, Drug Design, Lead Optimization areas. I am providing the major important steps in the Synthesis of novel derivatives having some therapeutic potency.
Sorting bioactive wheat from database chaff
Abstract
Databases of bioactive compounds are crucial for pharmacology, drug discovery and chemical genomics as public sources approach ~ 100 million records. However, in recent years this famine-to-feast presents difficulties for searching chemical structures and linked activity data, particularly for those unfamiliar with the constitutive challenges of molecular representation in silico (PMID 25415348). A key problem is entries of structural variants of “the same thing” as pharmacological entities (i.e. representational multiplexing). For example, a 2009 comparison of three database subsets of ~1200 approved drugs recorded only 807 structures in-common (PMID 20298516). In addition, published counts of approved drugs vary widely. These issues have been continually encountered by the Guide to PHARMACOLOGY database (GtoPdb) team that, since 2009, has achieved the curation of ~5500 small molecules (including approved drugs) from papers. Concomitantly, we have noticed an increase in multiplexing as PubChem pushes towards 65 million compound identifiers (CIDs). Since one of our key objectives is to affinity-map ligands to their targets, we decided to assess this multiplexing problem in order to optimise our curation rules. The results have implications for the entire bioactivity information space. We began by compiling CID sets for seven different sources within PubChem encompassing approved drugs. Initially a 7x7 pairwise comparison matrix indicated low overlap between these sources. A Venn diagram was then made from the approved drug CIDs mapped by DrugBank, Therapeutic Target Database and ChEMBL. At 749, the three-way intersect was less than 35% of the union of all CIDs covered by the sets. Strikingly, this looks worse that the 2009 study (although the sources and comparison methods were different). We will present further analyses that go some way towards explaining these results. One of these is determining “same connectivity” statistics inside PubChem as a measure of multiplexing. For DrugBank, each approved drug was related to, on average, 19 different CIDs as structural variants. Analysis of multiplexing confirmed trends we had observed during individual drug curation. This included ~ 30% stereoisomer enumerations but, surprisingly, ~70% isotopic derivatives, dominated by patent-derived virtual deuteration. We also established the ratio of submissions (SIDs) to CIDs was 78. The paradox was that, despite this high “majority vote” support for approved drug CIDs curated by DrugBank, only 55% were in the 3-way consensus (figures for the other two curated sources were similar). Analysing by year in PubChem indicated how the recent expansion of vendor and patent-extraction structures contributes to both multiplexing and the SID: CID ratio. While approved drugs are strongly impacted, associated problems, such as split activity data and deciding the “correct” structures, affect essentially all public drug discovery chem
Sorting bioactive wheat from database chaff: Challenges of discerning correct...
Sorting bioactive wheat from database chaff: Challenges of discerning correct...Guide to PHARMACOLOGY
Since 2009 the Guide to PHARMACOLOGY database (GtoPdb) team have curated 7586 ligands from papers, including approved drugs, clinical candidates , research compounds peptides and clinical antibodies (PMID 24234439). As PubChem pushes towards 70 million compound identifiers (CIDs), we have noticed the problem
of “multiplexing” during the curation of 5713 small molecules as CIDs. we encountered many representations (i.e. different CIDs) of the same pharmacological entities. Three types of variation dominate: stereochemistry, mixtures and isotopic analogues. These are known constitutive issues for chemical databases but in
recent years we observed this multiplexing was reaching
problematic proportions (i.e. more chaff), especially for clinically used drugs (i.e. proportionally less wheat)In Silico Drug Designing
This document describes the process of in silico drug design to target the hemagglutinin protein of the H1N1 influenza virus (swine flu). The key steps include: identifying hemagglutinin as the target, generating a homology model, identifying the active site, screening existing drugs and generating new ligands, performing rigid and flexible docking simulations to identify ligands that bind strongly to the active site, and selecting the best candidate to inhibit hemagglutinin function and potentially treat swine flu infections. The overall process takes an in silico approach to rational drug design against a specific viral protein target.
Presentation on insilico drug design and virtual screening
This presentation discusses in silico drug design and virtual screening techniques. It defines in silico drug design as using computational software to perform drug design based on knowledge of a biological target. The presentation outlines two main types of in silico drug design: ligand-based, which uses known ligands to derive a pharmacophore when the receptor is unknown, and structure-based, which relies on knowledge of the 3D receptor structure. It also describes virtual screening techniques as automatically evaluating large compound libraries for likelihood of binding to a target protein using computer programs based on ligand or structure models.
Pharmacophore mapping in Drug Development
Pharmocophores are set of functional group constraints responsible for the pharmacological activity of a compound.
Lecture 3 rational drug design
This document discusses rational drug design, which involves designing drugs based on knowledge of biological targets. It describes two main approaches: structure-based drug design, which relies on determining the 3D structure of the target using techniques like X-ray crystallography, and ligand-based drug design, which relies on knowledge of molecules that already bind to the target. Structure-based design involves identifying a drug target, determining its structure and function, then designing drugs that interact with it beneficially. Homology modeling can be used to model targets when experimental structures are unavailable. The document outlines the steps of structure-based design in rational drug development.
Analysing the drug targets in the human genome
This talk will be presented by Chris Southan, Database Curator and Chairperson of the NC-IUPHAR Drugs and Targets Annotation Subcommittee at the 17th World Congress of Basic and Clinical Pharmacology (WCP2014) taking place in Cape Town this month. The abstract for the talk can be read below:
Discerning the molecular mechanisms of action (mmoa) for drugs treating human diseases is crucially important. This talk will provide an overview of target numbers in IUPHAR/BPS Guide to PHARMACOLOGY, compare these to other sources and consider the wider implications for drug discovery. We have developed stringent mapping criteria for primary targets (i.e. identifying those direct protein interactions mechanistically causative for therapeutic efficacy). This includes inter-source corroboration by intersecting multiple drug sources inside PubChem to produce consensus structure sets. The analogous approach is used to intersect published target lists and database subsets at the UniProtKB/Swiss-Prot identity level. Our cumulative curation results reveal that structure representation differences, data provenance and variability of assay results, are major issues for experimental pharmacology and global database quality. While our activity mappings encompass some polypharmacology (e.g. dual inhibitors and kinase panel screens) our strategic choice is to annotate minimal rather than maximal target sets. The consequent increased precision gives our database high utility for data mining, linking and cross-referencing. Our small-molecule figures are currently converging to ~200 human protein primary targets for ~1000 consensus chemical structures of approved drugs. Target lists from other sources are typically larger and show a degree of discordance. Comparative analysis of these lists by their UniProt ID content and Gene Ontology distributions suggests differences in curatorial selection are the main cause of divergence. The global target landscape thus shows paradoxical trends. On the one hand, cumulative drug research output and recent expansions (e.g. epigenetic targets and orphan diseases) have pushed bioactive compounds from papers or patents to above 2 million and chemically modulatable human proteins above 1500 (PMID:24204758). On the other hand, reports of Phase II clinical efficacy failure, with implicit target de-validation, are frequent. In addition, our assessment of drug approval data from 2009 to 2013 indicates new targets (i.e. first-in-class mmoas) are so low as to threaten the sustainability of the pharmaceutical industry. Causes and consequences of these paradoxes, along with utilities for minimal and maximal druggable genomes, will be discussed.
Lecture 1 –Introduction to drug design and development
This document provides an overview of a lecture on drug design and development. It discusses four units that will be covered: drug design and development, drug targeting and identification, pharmacophore modeling, and computer aided drug design. It provides definitions of key terms like drug and pharmacology. It also summarizes the stages of new drug synthesis: drug discovery, pre-clinical development, and clinical development. Properties of an ideal drug and the role of bioinformatics in drug discovery are also briefly outlined.
Rational drug design
this power point is all about rational drug design and pharmacophore based drug design approaches...
Computer aided drug design(CADD)
Computer aided drug design uses computational methods to facilitate the design and discovery of new therapeutic solutions. There are two main types of drug design - ligand-based which relies on knowledge of molecules that bind to the target, and structure-based which relies on the 3D structure of the target. The main steps in structure-based design are target selection, binding site identification, molecular docking to predict how ligands bind to the target, and scoring to evaluate interactions. Computational tools are used for databases, molecular modeling, docking, screening, and predicting absorption and toxicity properties. These tools help speed up the drug design process and make it more efficient.
DRUG DESIGN BASED ON BIOINFORMATICS TOOLS
Drug design is a very complex process it takes many more times but using the these specific tools we can reduce complex process and save the time and produce a effective new drug that will be helpful in heath environment.
Pharmacophore modeling and docking techniques
Pharmacophore modeling and docking techniques are important in rational drug design. Pharmacophore modeling identifies common molecular features necessary for biological activity. It represents features as 3D structures, 2D substituents, or properties. Pharmacophore modeling is used in structure-based drug design through target identification and ligand-based design via virtual screening. Docking predicts ligand binding orientation to form stable complexes. It identifies correct poses and binding affinities to aid hit identification and drug discovery. Popular docking software includes AutoDock, GOLD, Hex and SANJEEVINI.
Drug Discovery Method (Bioinformatics)
The document discusses drug design and the drug development process. It describes the two main types of drug design: ligand-based drug design, which relies on knowledge of molecules that bind to the biological target, and structure-based drug design, which models the 3D structure of a protein target. The drug development process involves six main stages: hit identification, pre-clinical studies, manufacturing, clinical trials, regulatory evaluation, and marketing. Overall, drug discovery and development is a complex, expensive process that can take 15 years from initial screening to FDA approval and market launch.
Rational drug design
Rational drug design is a process that begins with knowledge of a biological target and aims to design small molecules that interact optimally with that target to produce a desired therapeutic effect. It involves analyzing the structures of active molecules and known targets, then designing new molecules that are predicted to specifically fit the target. This may involve modifying existing lead compounds or building new ones de novo. The goal is to develop drugs with greater potency, selectivity and fewer side effects than those found by traditional trial-and-error means. Cimetidine for reducing stomach acid is provided as an example of rational drug design, where histamine analogs were synthesized and optimized until an effective and safe product was obtained.
In silico drug design an intro
The document discusses in-silico drug design as an introduction. It notes that traditional drug discovery is often portrayed as a linear process starting with target and lead discovery, followed by lead optimization and pre-clinical studies. However, this traditional approach has high costs and time requirements and a 90% failure rate due to issues like poor pharmacokinetics, lack of efficacy, and toxicity. In-silico drug design uses computational methods like virtual screening, de novo design, and ADME/T prediction to help address these issues and identify drug targets.
pharmacophore mapping
Pharmacophore mapping and screening involves generating pharmacophore models to identify potential drug candidates. A pharmacophore represents the molecular features responsible for a drug's biological activity, including hydrophobic groups, charged groups, and hydrogen bond donors or acceptors. Pharmacophore mapping can be done through ligand-based or structure-based approaches. Ligand-based mapping uses a set of known active ligands to derive a pharmacophore model, while structure-based mapping docks candidate ligands into a protein target. Pharmacophore mapping software like Discovery Studio and Ligand Scout are used to generate pharmacophore models and screen compound libraries to discover new drug candidates in a more efficient manner than traditional drug development methods.
Assessing GtoPdb ligand content in PubChem
The document discusses the content of ligands from the IUPHAR/BPS Guide to PHARMACOLOGY database (GtoPdb) that is contained within PubChem. It finds that GtoPdb ligands have extensive overlap with several other sources within PubChem, including patents, DrugBank, vendor structures, bioassays, and ChEMBL. This overlap allows users to find additional information on GtoPdb ligands from these complementary sources within PubChem.
Curriculum Vitae
The curriculum vitae outlines the professional experience and qualifications of Polagani Srinivasa Rao, who has over 11 years of experience developing and validating analytical methods using LC-MS/MS to quantify pharmaceutical drugs, metabolites, and other compounds in biological samples under GLP and FDA regulations. He currently works as a Manager of Bioanalytical Research at Indoco Remides, where he leads projects involving method development, validation, sample preparation, and regulatory compliance. Rao also has publications in peer-reviewed journals and presents technical information at meetings and seminars.
A General Review on Bioanalytical Method Development & Validation for LC-MS/MS
Rapid growth in the use of LC-MS/MS for the analysis of drugs in biological matrices has been compelled by the need for timely and high-quality data at every stages in drug discovery and development process: from throughput screening of drug candidates and rapid data generation for pre-clinical studies to almost 'real-time' analysis of clinical samples. A well developed bioanalytical development and its validation plays a pivotal role in achieving the goals. . The aim behind this review is to enlighten the need of validation which provide a practical approach for determining the different parameters like selectivity, specifity, limit of detection, lower limit of quantitation, linearity, range, accuracy, precision, recovery, stability, ruggedness, and robustness to help the perfect studies of pharmacokinetic, toxic kinetic, bioavailability and bioequivalence. Bio-analysis study is for the quantitative determination of drug and their metabolites in biological fluids. Accurate and robust methods for quantitative analysis of drug and their metabolites are important for the successful conduct of pre-clinical, bio-pharmaceutics and clinical pharmacology. Ashutosh Badola | Preeti Joshi | Preeti Kothiyal"A General Review on Bioanalytical Method Development & Validation for LC-MS/MS" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-4 , June 2018, URL: http://www.ijtsrd.com/papers/ijtsrd14203.pdf http://www.ijtsrd.com/pharmacy/pharmaceutics/14203/a-general-review-on-bioanalytical-method-development-and-validation-for-lc-msms/ashutosh-badola
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Pharmacophore mapping
The document discusses pharmacophores, which are abstract descriptions of molecular features necessary for molecular recognition between a ligand and biological macromolecule. A pharmacophore consists of 3D structural features like hydrophobic groups and hydrogen bond donors/acceptors. Pharmacophore mapping is used to define pharmacophoric features and align molecules to identify common binding elements responsible for biological activity. Pharmacophore models can be used in virtual screening to filter large databases and identify new compounds that may bind similarly to known active molecules. The document provides details on different approaches for pharmacophore generation and searching compound libraries.
Target Based Drug Combination Selection
The presentation outlines an algorithm to identify combinations of drug for a given therapeutic endpoint.
The objective is to target different stages of the disease pathway.
Chemoinformatics as employed by Ontomine, a US patent pending algorithm is employed for the same.
Research work plan for Drug Design
This is to help the young researchers to carry out their research in Pharmaceutical Chemistry, Medicinal Chemistry, Drug Design, Lead Optimization areas. I am providing the major important steps in the Synthesis of novel derivatives having some therapeutic potency.
Sorting bioactive wheat from database chaff
Abstract
Databases of bioactive compounds are crucial for pharmacology, drug discovery and chemical genomics as public sources approach ~ 100 million records. However, in recent years this famine-to-feast presents difficulties for searching chemical structures and linked activity data, particularly for those unfamiliar with the constitutive challenges of molecular representation in silico (PMID 25415348). A key problem is entries of structural variants of “the same thing” as pharmacological entities (i.e. representational multiplexing). For example, a 2009 comparison of three database subsets of ~1200 approved drugs recorded only 807 structures in-common (PMID 20298516). In addition, published counts of approved drugs vary widely. These issues have been continually encountered by the Guide to PHARMACOLOGY database (GtoPdb) team that, since 2009, has achieved the curation of ~5500 small molecules (including approved drugs) from papers. Concomitantly, we have noticed an increase in multiplexing as PubChem pushes towards 65 million compound identifiers (CIDs). Since one of our key objectives is to affinity-map ligands to their targets, we decided to assess this multiplexing problem in order to optimise our curation rules. The results have implications for the entire bioactivity information space. We began by compiling CID sets for seven different sources within PubChem encompassing approved drugs. Initially a 7x7 pairwise comparison matrix indicated low overlap between these sources. A Venn diagram was then made from the approved drug CIDs mapped by DrugBank, Therapeutic Target Database and ChEMBL. At 749, the three-way intersect was less than 35% of the union of all CIDs covered by the sets. Strikingly, this looks worse that the 2009 study (although the sources and comparison methods were different). We will present further analyses that go some way towards explaining these results. One of these is determining “same connectivity” statistics inside PubChem as a measure of multiplexing. For DrugBank, each approved drug was related to, on average, 19 different CIDs as structural variants. Analysis of multiplexing confirmed trends we had observed during individual drug curation. This included ~ 30% stereoisomer enumerations but, surprisingly, ~70% isotopic derivatives, dominated by patent-derived virtual deuteration. We also established the ratio of submissions (SIDs) to CIDs was 78. The paradox was that, despite this high “majority vote” support for approved drug CIDs curated by DrugBank, only 55% were in the 3-way consensus (figures for the other two curated sources were similar). Analysing by year in PubChem indicated how the recent expansion of vendor and patent-extraction structures contributes to both multiplexing and the SID: CID ratio. While approved drugs are strongly impacted, associated problems, such as split activity data and deciding the “correct” structures, affect essentially all public drug discovery chem
Sorting bioactive wheat from database chaff: Challenges of discerning correct...
Sorting bioactive wheat from database chaff: Challenges of discerning correct...Guide to PHARMACOLOGY
Since 2009 the Guide to PHARMACOLOGY database (GtoPdb) team have curated 7586 ligands from papers, including approved drugs, clinical candidates , research compounds peptides and clinical antibodies (PMID 24234439). As PubChem pushes towards 70 million compound identifiers (CIDs), we have noticed the problem
of “multiplexing” during the curation of 5713 small molecules as CIDs. we encountered many representations (i.e. different CIDs) of the same pharmacological entities. Three types of variation dominate: stereochemistry, mixtures and isotopic analogues. These are known constitutive issues for chemical databases but in
recent years we observed this multiplexing was reaching
problematic proportions (i.e. more chaff), especially for clinically used drugs (i.e. proportionally less wheat)In Silico Drug Designing
This document describes the process of in silico drug design to target the hemagglutinin protein of the H1N1 influenza virus (swine flu). The key steps include: identifying hemagglutinin as the target, generating a homology model, identifying the active site, screening existing drugs and generating new ligands, performing rigid and flexible docking simulations to identify ligands that bind strongly to the active site, and selecting the best candidate to inhibit hemagglutinin function and potentially treat swine flu infections. The overall process takes an in silico approach to rational drug design against a specific viral protein target.
Presentation on insilico drug design and virtual screening
This presentation discusses in silico drug design and virtual screening techniques. It defines in silico drug design as using computational software to perform drug design based on knowledge of a biological target. The presentation outlines two main types of in silico drug design: ligand-based, which uses known ligands to derive a pharmacophore when the receptor is unknown, and structure-based, which relies on knowledge of the 3D receptor structure. It also describes virtual screening techniques as automatically evaluating large compound libraries for likelihood of binding to a target protein using computer programs based on ligand or structure models.
Pharmacophore mapping in Drug Development
Pharmocophores are set of functional group constraints responsible for the pharmacological activity of a compound.
Lecture 3 rational drug design
This document discusses rational drug design, which involves designing drugs based on knowledge of biological targets. It describes two main approaches: structure-based drug design, which relies on determining the 3D structure of the target using techniques like X-ray crystallography, and ligand-based drug design, which relies on knowledge of molecules that already bind to the target. Structure-based design involves identifying a drug target, determining its structure and function, then designing drugs that interact with it beneficially. Homology modeling can be used to model targets when experimental structures are unavailable. The document outlines the steps of structure-based design in rational drug development.
Analysing the drug targets in the human genome
This talk will be presented by Chris Southan, Database Curator and Chairperson of the NC-IUPHAR Drugs and Targets Annotation Subcommittee at the 17th World Congress of Basic and Clinical Pharmacology (WCP2014) taking place in Cape Town this month. The abstract for the talk can be read below:
Discerning the molecular mechanisms of action (mmoa) for drugs treating human diseases is crucially important. This talk will provide an overview of target numbers in IUPHAR/BPS Guide to PHARMACOLOGY, compare these to other sources and consider the wider implications for drug discovery. We have developed stringent mapping criteria for primary targets (i.e. identifying those direct protein interactions mechanistically causative for therapeutic efficacy). This includes inter-source corroboration by intersecting multiple drug sources inside PubChem to produce consensus structure sets. The analogous approach is used to intersect published target lists and database subsets at the UniProtKB/Swiss-Prot identity level. Our cumulative curation results reveal that structure representation differences, data provenance and variability of assay results, are major issues for experimental pharmacology and global database quality. While our activity mappings encompass some polypharmacology (e.g. dual inhibitors and kinase panel screens) our strategic choice is to annotate minimal rather than maximal target sets. The consequent increased precision gives our database high utility for data mining, linking and cross-referencing. Our small-molecule figures are currently converging to ~200 human protein primary targets for ~1000 consensus chemical structures of approved drugs. Target lists from other sources are typically larger and show a degree of discordance. Comparative analysis of these lists by their UniProt ID content and Gene Ontology distributions suggests differences in curatorial selection are the main cause of divergence. The global target landscape thus shows paradoxical trends. On the one hand, cumulative drug research output and recent expansions (e.g. epigenetic targets and orphan diseases) have pushed bioactive compounds from papers or patents to above 2 million and chemically modulatable human proteins above 1500 (PMID:24204758). On the other hand, reports of Phase II clinical efficacy failure, with implicit target de-validation, are frequent. In addition, our assessment of drug approval data from 2009 to 2013 indicates new targets (i.e. first-in-class mmoas) are so low as to threaten the sustainability of the pharmaceutical industry. Causes and consequences of these paradoxes, along with utilities for minimal and maximal druggable genomes, will be discussed.
Lecture 1 –Introduction to drug design and development
This document provides an overview of a lecture on drug design and development. It discusses four units that will be covered: drug design and development, drug targeting and identification, pharmacophore modeling, and computer aided drug design. It provides definitions of key terms like drug and pharmacology. It also summarizes the stages of new drug synthesis: drug discovery, pre-clinical development, and clinical development. Properties of an ideal drug and the role of bioinformatics in drug discovery are also briefly outlined.
Rational drug design
this power point is all about rational drug design and pharmacophore based drug design approaches...
Computer aided drug design(CADD)
Computer aided drug design uses computational methods to facilitate the design and discovery of new therapeutic solutions. There are two main types of drug design - ligand-based which relies on knowledge of molecules that bind to the target, and structure-based which relies on the 3D structure of the target. The main steps in structure-based design are target selection, binding site identification, molecular docking to predict how ligands bind to the target, and scoring to evaluate interactions. Computational tools are used for databases, molecular modeling, docking, screening, and predicting absorption and toxicity properties. These tools help speed up the drug design process and make it more efficient.
DRUG DESIGN BASED ON BIOINFORMATICS TOOLS
Drug design is a very complex process it takes many more times but using the these specific tools we can reduce complex process and save the time and produce a effective new drug that will be helpful in heath environment.
Pharmacophore modeling and docking techniques
Pharmacophore modeling and docking techniques are important in rational drug design. Pharmacophore modeling identifies common molecular features necessary for biological activity. It represents features as 3D structures, 2D substituents, or properties. Pharmacophore modeling is used in structure-based drug design through target identification and ligand-based design via virtual screening. Docking predicts ligand binding orientation to form stable complexes. It identifies correct poses and binding affinities to aid hit identification and drug discovery. Popular docking software includes AutoDock, GOLD, Hex and SANJEEVINI.
Drug Discovery Method (Bioinformatics)
The document discusses drug design and the drug development process. It describes the two main types of drug design: ligand-based drug design, which relies on knowledge of molecules that bind to the biological target, and structure-based drug design, which models the 3D structure of a protein target. The drug development process involves six main stages: hit identification, pre-clinical studies, manufacturing, clinical trials, regulatory evaluation, and marketing. Overall, drug discovery and development is a complex, expensive process that can take 15 years from initial screening to FDA approval and market launch.
Rational drug design
Rational drug design is a process that begins with knowledge of a biological target and aims to design small molecules that interact optimally with that target to produce a desired therapeutic effect. It involves analyzing the structures of active molecules and known targets, then designing new molecules that are predicted to specifically fit the target. This may involve modifying existing lead compounds or building new ones de novo. The goal is to develop drugs with greater potency, selectivity and fewer side effects than those found by traditional trial-and-error means. Cimetidine for reducing stomach acid is provided as an example of rational drug design, where histamine analogs were synthesized and optimized until an effective and safe product was obtained.
In silico drug design an intro
The document discusses in-silico drug design as an introduction. It notes that traditional drug discovery is often portrayed as a linear process starting with target and lead discovery, followed by lead optimization and pre-clinical studies. However, this traditional approach has high costs and time requirements and a 90% failure rate due to issues like poor pharmacokinetics, lack of efficacy, and toxicity. In-silico drug design uses computational methods like virtual screening, de novo design, and ADME/T prediction to help address these issues and identify drug targets.
pharmacophore mapping
Pharmacophore mapping and screening involves generating pharmacophore models to identify potential drug candidates. A pharmacophore represents the molecular features responsible for a drug's biological activity, including hydrophobic groups, charged groups, and hydrogen bond donors or acceptors. Pharmacophore mapping can be done through ligand-based or structure-based approaches. Ligand-based mapping uses a set of known active ligands to derive a pharmacophore model, while structure-based mapping docks candidate ligands into a protein target. Pharmacophore mapping software like Discovery Studio and Ligand Scout are used to generate pharmacophore models and screen compound libraries to discover new drug candidates in a more efficient manner than traditional drug development methods.
Assessing GtoPdb ligand content in PubChem
The document discusses the content of ligands from the IUPHAR/BPS Guide to PHARMACOLOGY database (GtoPdb) that is contained within PubChem. It finds that GtoPdb ligands have extensive overlap with several other sources within PubChem, including patents, DrugBank, vendor structures, bioassays, and ChEMBL. This overlap allows users to find additional information on GtoPdb ligands from these complementary sources within PubChem.
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Curriculum Vitae
The curriculum vitae outlines the professional experience and qualifications of Polagani Srinivasa Rao, who has over 11 years of experience developing and validating analytical methods using LC-MS/MS to quantify pharmaceutical drugs, metabolites, and other compounds in biological samples under GLP and FDA regulations. He currently works as a Manager of Bioanalytical Research at Indoco Remides, where he leads projects involving method development, validation, sample preparation, and regulatory compliance. Rao also has publications in peer-reviewed journals and presents technical information at meetings and seminars.
A General Review on Bioanalytical Method Development & Validation for LC-MS/MS
Rapid growth in the use of LC-MS/MS for the analysis of drugs in biological matrices has been compelled by the need for timely and high-quality data at every stages in drug discovery and development process: from throughput screening of drug candidates and rapid data generation for pre-clinical studies to almost 'real-time' analysis of clinical samples. A well developed bioanalytical development and its validation plays a pivotal role in achieving the goals. . The aim behind this review is to enlighten the need of validation which provide a practical approach for determining the different parameters like selectivity, specifity, limit of detection, lower limit of quantitation, linearity, range, accuracy, precision, recovery, stability, ruggedness, and robustness to help the perfect studies of pharmacokinetic, toxic kinetic, bioavailability and bioequivalence. Bio-analysis study is for the quantitative determination of drug and their metabolites in biological fluids. Accurate and robust methods for quantitative analysis of drug and their metabolites are important for the successful conduct of pre-clinical, bio-pharmaceutics and clinical pharmacology. Ashutosh Badola | Preeti Joshi | Preeti Kothiyal"A General Review on Bioanalytical Method Development & Validation for LC-MS/MS" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-4 , June 2018, URL: http://www.ijtsrd.com/papers/ijtsrd14203.pdf http://www.ijtsrd.com/pharmacy/pharmaceutics/14203/a-general-review-on-bioanalytical-method-development-and-validation-for-lc-msms/ashutosh-badola
HPLC In Pharmaceutical sciences
This document summarizes the uses of high-performance liquid chromatography (HPLC) in pharmaceutical sciences. HPLC is widely used in pharmaceutical industries for drug discovery, development, and manufacturing. It is used for separation, identification, and quantification of compounds. Some key applications of HPLC include drug purity testing, stability studies, impurity profiling, and analytical method development and validation. HPLC plays a vital role throughout the drug development process from early research to quality control of final drug products.
Bioanalysis significance 12 oct 2022.ppt
Bioanalysis is the quantitative measurement of drugs, metabolites, and biological molecules in biological systems. It plays an important role in drug discovery and development by supporting pharmacokinetic studies. The drug development process involves preclinical and clinical stages where bioanalysis is used to determine safety, identify metabolites, and understand pharmacokinetics. Techniques like liquid chromatography-mass spectrometry are commonly used for bioanalysis of small molecules and large molecules during drug development.
Bioanlytical method development
it is important method for determination of concentration of drug and its metabolite present in biological fluids.
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This document provides classifications and dosages for drugs acting on the autonomic nervous system, including cholinergic drugs, anticholinergic drugs, ganglionic stimulants, ganglionic blocking agents, adrenergic drugs, α-adrenergic blocking drugs, and β-adrenergic blocking drugs. It lists the generic and brand names, dosages, and administration routes for these drugs in concise tables and charts.
Pharmacological Classification of Drugs with Doses and Preparations ( PDFDriv...
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analogue based drug design and discovery.pptx
1. Analog based drug design and discovery involves identifying candidate drug compounds, synthesizing and characterizing them, and screening them for therapeutic efficacy through various techniques.
2. The general principles of drug discovery are to select a disease target, identify a bioassay, find a lead compound, purify and test the lead compound, determine the structure-activity relationship, and improve target interaction and pharmacokinetic parameters.
3. Lead discovery aims to find drug-like molecules that can progress into preclinical and clinical development trials with the goal of becoming a marketed medication. Analog design modifies existing bioactive compounds to create new molecules with similar chemical and biological properties.
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This cover letter summarizes an applicant's 8+ years of experience in drug metabolism, pharmacokinetics, and preclinical formulation research. They established a DMPK lab and led due diligence programs that resulted in out-licensing of new chemical entities. The applicant has expertise in designing and interpreting in vitro and in vivo pharmacokinetic studies for small molecules and experience with PK-PD modeling.
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A Review on Step-by-Step Analytical Method Validation
When analytical method is utilized to generate results about the characteristics of drug related samples it is essential that the results are trustworthy. They may be utilized as the basis for decisions relating to administering the drug to patients. Analytical method validation required during drug development and manufacturing and these analytical methods are fit for their intended purpose. To comply with the requirements of GMP pharmaceutical industries should have an overall validation policy which documents how validation will be performed. The purpose of this validation is to show that processes involved in the development and manufacture of drug, production and analytical testing can be performed in an effective and reproducible manner. This review article provides guidance on how to perform validation characteristics for the analytical method which are utilized in pharmaceutical analysis.
Drug recommendation using recurrent neural networks augmented with cellular a...
Drug recommendation systems are systems that have the capability to recommend drugs. On a daily basis, a huge amount of data is being generated by the patients. All this valuable data can be properly utilized to create a reliable drug recommendation system. In this paper, we recommend a system for drug recommendations. The main scope of our system is to predict the correct medication based on reviews and ratings. Our proposed system uses natural language processing techniques (NLP), recurrent neural networks (RNN), and cellular automata (CA). We also considered various metrics like precision, recall, accuracy, F1 score, and ROC curve as measures of our system’s performance. NLP techniques are being used for gathering useful information from patient data, and RNN is a machine learning methodology that works really well in analyzing textual data. The system considers various patient data attributes like age, gender, dosage, medical history, and symptoms in order to make appropriate predictions. The proposed system has the potential to help medical professionals make informed drug recommendations.
Project Presentation m.pharm pharmceutical analysis
This document presents a proposal for developing and validating a new RP-HPLC method for the simultaneous estimation of evogliptin and metformin hydrochloride in bulk and pharmaceutical dosage forms. The objectives are to develop a sensitive and accurate RP-HPLC method, validate the method according to ICH guidelines, and apply the method to analyze samples. The methodology will involve collecting literature on existing methods, developing the separation conditions, and validating the method parameters such as linearity, range, precision, specificity, accuracy, ruggedness and robustness. Data will be collected using HPLC and UV spectrophotometry and analyzed statistically.
Gang Xing - Summary
The document summarizes the author's major contributions in two areas:
1. Drug target discovery and mechanistic study through developing platforms for metabolic fluxomics analysis, LC-MS/MS based metabolomic and proteomic studies to screen and validate drug targets.
2. Drug development including in vitro enzyme assays and cell-based assays for compound screening, and LC-MS/MS studies in disease models to prove target engagement and pathway analysis.
The author has technical expertise in spectroscopy, enzyme studies, protein expression and purification, chromatography, metabolomics, and experience in the pharmaceutical industry and drug development.
Toc
This document is the table of contents for the 6th edition of the textbook "Essentials of Medical Pharmacology" by KD Tripathi. The textbook is divided into 14 sections covering general pharmacological principles and various classes of drugs. Each section contains multiple chapters on specific drug classes or therapeutic areas. The table of contents provides the chapter titles and page numbers for each of the 69 chapters and 2 appendices contained in the textbook. The textbook appears to provide an overview of medical pharmacology targeting medical students and clinicians.
Markers.pptx
This document discusses biological and chemical markers for quality control of herbal medicines. It notes that careful selection of plant material and a standardized manufacturing process are needed to keep herbal medicine constituents constant for reproducible results. DNA-based molecular markers and chemical markers are described as tools for identifying plants, detecting adulteration, assessing quality, and standardizing herbal medicines. The document outlines various applications of both DNA and chemical markers in herbal drug technology, authentication, identification, and quality control.
A Review HPLC Method Development and Validation
Due to its very effective separations and often high detection sensitivity, HPLC is the most widely used separation method in contemporary pharmaceutical and biomedical analysis. The majority of medications in multiple component dosage forms can be examined using the HPLC method due to its many benefits, including speed, specificity, accuracy, precision, and ease of automation. The development and validation of HPLC procedures are crucial to novel discoveries, the creation of pharmaceutical medications, and numerous other investigations involving both humans and animals. To compare a defined characteristic of the drug substance or drug product to predetermined acceptance criteria for that characteristic, an analytical technique is designed. This review provides details on the numerous steps that go into developing and validating an HPLC technique. According to ICH Guidelines, validating an HPLC technique include testing for system appropriateness as well as accuracy, precision, specificity, linearity, range and limit of detection, limit of quantification, robustness, and other performance characteristics. Ajay Sanjay Salvi | Mohini S. Khamkar | Dr. Lahu D. Hingane "A Review: HPLC Method Development and Validation" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-7 | Issue-4, August 2023, URL: https://www.ijtsrd.com/papers/ijtsrd58595.pdf Paper Url:https://www.ijtsrd.com/pharmacy/other/58595/a-review-hplc-method-development-and-validation/ajay-sanjay-salvi
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Analytical method development by liquid chromatography
- 1. By Prafulla Kumar Sahu
- 2. Development and Validation of Analytical Methods for the Assay of Selected Drugs in Pharmaceutical Dosage forms and Biological fluids LAP Lambert Academic Publishing ( 2011-10-25 ) Book Details: ISBN-13: 978-3-8443-2869-1 ISBN-10: 3844328696 EAN: 9783844328691 Book language: English By (author) : Prafulla Kumar Sahu M. Mathrusri Annapurna Number of pages: 352 Published at: 2011-10-25 Category: Pharmacy
- 3. Abstract for the book Analytical methods development and validation play important roles in the discovery, development, and manufacture of pharmaceuticals. The current good manufacturing practice (cGMP) and Food Drug Administration (FDA) Guidelines insist for adoption of sound methods of analysis with greater sensitivity and reproducibility. This thesis describes analytical methods developed for drug determination in pharmaceutical dosage forms and biological matrixes including Chromatography (RP-HPLC) and Hyphenated Techniques (LC-MS/MS). Methods have been developed for separation and quantification of selected drugs from categories like Antihypertensive, Antihyperlipidemic, Skeletal Muscle Relaxant, Non-Steroidal Anti- inflammatory Drug (NSAID), Antibiotic, Anticonvulsant, Antiviral, an d Analeptic.
- 4. Availability on stores and online • This book is available world wide as well as online to purchase: • http://www.libri.de/shop/action/productDetails/16743772/prafulla_kuma r_sahu_m_mathrusri_annapurna_analytical_method_development_by_li quid_chromatography_3844328696.html • http://www.amazon.com/Analytical-Method-development-Liquid- Chromatography/dp/3844328696/ref=sr_1_1_title_0_main?s=books&ie= UTF8&qid=1321689950&sr=1-1 • http://www.zvab.com/displayBookDetails.do?itemId=182636179&b=1 • http://www.bod.com/index.php?id=3435&objk_id=589686 • https://www.morebooks.de/store/gb/book/analytical-method- development-by-liquid-chromatography/isbn/978-3-8443-2869-1 • http://www.amazon.co.jp/Analytical-Method-Development-Liquid- Chromatography/dp/3844328696 • http://www.amazonka.pl/analytical-method-development-by-liquid- chromatography_m-mathrusri-annapurna-prafulla-kumar- sahu,99903103722.bhtml
- 5. • http://www.petlaczasu.pl/analytical-method-development/b00475522 • http://www.terrashop.de/Englisches-Buch/Analytical-Method- development-by-Liquid-Chromatography-Prafulla-Kumar-Sahu-M- Mathrusri-Annapurna-ISBN-3844328696/art/84432869A/ • http://www.en.zvab.com/displayBookDetails.do?itemId=182636179&b=1 • http://www.buch.ch/shop/home/artikeldetails/analytical_method_develo pment_by_liquid_chromatography/m_mathrusri_annapurn/ISBN3-8443- 2869-6/ID30422551.html • http://www.page74.com/public/book- details.jsp?group1=2&bid=3844328696&q=Annapurna+M • http://www.amazon.co.jp/chromatography-liquid-methods- %E6%B4%8B%E6%9B%B8- %E3%83%9A%E3%83%BC%E3%83%91%E3%83%BC%E3%83%90%E3%83% 83%E3%82%AF/s?ie=UTF8&keywords=Chromatography%5Cc%20Liquid%2 0- %20methods&rh=n%3A52033011%2Ck%3AChromatography%5Cc%20Liqu id%20-%20methods%2Cp_n_binding_browse-bin%3A87853051&page=1 • http://www.amazon.co.jp/Analytical-Method-Development-Liquid- Chromatography/dp/3844328696/ref=sr_1_1?s=english- books&ie=UTF8&qid=1321692234&sr=1-1 • http://www.amazon.de/Analytical-Method-development-Liquid- Chromatography/dp/3844328696/ref=sr_1_2?s=books-intl- de&ie=UTF8&qid=1321692251&sr=1-2
- 6. Analytical Method Development by Liquid Chromatography Thank You Development and validation of Analytical Methods for the Assay of drugs in Pharmaceutical dosage forms and Biological fluids