pharmacophore is a part of a molecular structure that is responsible for a particular biological or pharmacological interaction that it undergoes. This identification leads to the development of designing a new drug.
In this slide I presented the Computer Aided Drug Design and its type :
1.Structure based Drug Design
2. Ligand based Drug Design and its Applications.
Molecular docking is a method for predicting how two molecules, such as a ligand and its protein target, will interact and fit together in three dimensions. Docking has become an important tool in drug discovery for identifying potential binding conformations between drug candidates and protein targets. The key steps in a typical docking workflow involve selecting the receptor and ligand molecules, then using software to computationally predict the orientation of binding and evaluate the fit through scoring functions. Popular molecular docking software packages include AutoDock, GOLD, and Glide. Applications of docking include virtual screening in drug discovery and lead optimization.
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.
Presentation on insilico drug design and virtual screeningJoon Jyoti Sahariah
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.
In this slide I presented the Computer Aided Drug Design and its type :
1.Structure based Drug Design
2. Ligand based Drug Design and its Applications.
Molecular docking is a method for predicting how two molecules, such as a ligand and its protein target, will interact and fit together in three dimensions. Docking has become an important tool in drug discovery for identifying potential binding conformations between drug candidates and protein targets. The key steps in a typical docking workflow involve selecting the receptor and ligand molecules, then using software to computationally predict the orientation of binding and evaluate the fit through scoring functions. Popular molecular docking software packages include AutoDock, GOLD, and Glide. Applications of docking include virtual screening in drug discovery and lead optimization.
This document discusses structure based drug design. It describes how drug design uses knowledge of biological targets to find new medications. Structure based drug design uses information about the 3D structure of protein targets to design ligands that bind to them. The main methods described are ligand-based drug design through database searching, and receptor-based drug design which builds ligands for a receptor. Molecular docking is also discussed as a key technique to predict how ligands bind to protein targets and identify potential drug candidates.
Energy minimization methods - Molecular ModelingChandni Pathak
Methods to minimize the energy of molecules during drug designing - Computational chemistry. According to the PCI syllabus, B.Pharm 8th Sem - Computer-Aided Drug Design (CADD).
molecular docking its types and de novo drug design and application and softw...GAUTAM KHUNE
This ppt deals with all the aspects related to molecular docking ,its types(rigid ,flexible and manual) and screening based on it and also deals with de novo drug design , various softwares available for docking methodologies and applications for molecular docking in new drug design
Molecular docking is a method to predict how two molecules, such as a ligand and a protein, will interact and bind to one another. The key steps in molecular docking include preparing the protein and ligand, analyzing the binding site, docking the ligand to the protein, scoring the docked poses, and validating the docking results. Molecular docking can be used for applications like hit identification in drug discovery and lead optimization.
Virtual screening uses computer-based methods to filter large databases of chemical compounds to identify a subset of compounds that are most likely to bind to and activate a target linked to a disease. It helps address the challenge of exploring the vast chemical space compared to the limited number of compounds that can be experimentally screened. The document discusses various virtual screening methods including ligand-based approaches like similarity searching and pharmacophore modeling as well as structure-based approaches like molecular docking that predict binding orientations. It also covers best practices for applying filters to select for drug-like and lead-like compounds.
This document discusses structure-based and ligand-based drug design approaches. Structure-based design uses the 3D structure of biological targets to dock potential drug molecules. Ligand-based design analyzes similar molecules that bind to the target to derive pharmacophore models or quantitative structure-activity relationships (QSAR) to predict new candidates. Specific structure-based methods covered include docking tools like AutoDock and CDOCKER, and accounting for protein and complex flexibility. Ligand-based methods discussed are QSAR techniques like Comparative Molecular Field Analysis (CoMSIA) and Field Analysis (CoMFA). In conclusion, computational approaches like these are valuable for drug discovery by facilitating the identification and testing of new ligand
This document discusses ligand-based drug design approaches. It defines ligand-based drug design as relying on knowledge of other molecules that bind to the biological target to derive a pharmacophore model or quantitative structure-activity relationship (QSAR) model. The most important method is pharmacophore modeling, which develops a model of interactions between ligands and the target receptor from the ligand perspective. Key ligand-based design approaches covered are pharmacophore modeling, QSAR, scaffold hoping, and pseudo receptors.
This document discusses structure-activity relationships (SAR) and quantitative structure-activity relationships (QSAR). SAR involves analyzing how changes to a molecule's structure affect its biological activity. QSAR establishes a mathematical relationship between biological activity and a molecule's geometric and chemical characteristics. SAR identifies important functional groups for binding through systematic structural modifications. QSAR analysis can be 2D, considering factors like those in Hansch analysis or Free-Wilson analysis, or 3D, considering steric and electrostatic values as well as hydrogen bonding abilities as in Comparative Molecular Field Analysis or Comparative Molecular Similarity Index Analysis.
This document provides an overview of quantitative structure-activity relationship (QSAR) modeling approaches. It discusses various 3D-QSAR methods including contour map analysis, statistical methods like linear regression, principal components analysis, and pattern recognition techniques like cluster analysis and artificial neural networks. The importance of statistical parameters for evaluating and selecting the best QSAR model is also highlighted. In summary, the document outlines different 3D-QSAR modeling techniques, statistical analyses used in QSAR studies, and how statistics help in model selection and evaluation.
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.
PHARMACOHORE MAPPING AND VIRTUAL SCRRENING FOR RESEARCH DEPARTMENTShikha Popali
THE PHARMACOPHORE MAPPING AND VIRTUAL SCRRENING , THESE PRESENTATION INCLUDES THE DEATIL ACCOUNT ON PHARMACOPHORE, MAPPING, ITS IDENTIFIATION FEATURES, ITS CONFORMATIONAL SEARCH, INSILICO DRUG DESIGN, VIRTUAL SCREENING, PHARMACOPHORE BASED SCREENING
This document discusses the identification and generation of pharmacophores. A pharmacophore is a specific 3D arrangement of functional groups within a molecule that are necessary for binding to an enzyme or receptor. Pharmacophore identification is important for understanding ligand-receptor interactions. Pharmacophore models are derived from the common features of known active molecules and define the spatial relationships between these features. Several computational methods can be used to generate pharmacophore hypotheses, including systematic search, distance geometry, and clique detection algorithms.
Pharmacophore modeling identifies key molecular features necessary for drug-target binding and biological response. It represents molecules schematically in 2D or 3D. Pharmacophore features include hydrogen bond donors/acceptors, aromaticity, hydrophobicity and hydrophilicity. Pharmacophore models are used for virtual screening to identify molecules that may activate or inhibit a target. There are two main types: ligand-based models extract common features of known ligands, while structure-based models define features from protein-ligand complex structures. Both aim to encode the optimal 3D arrangement of interactions between ligands and targets.
This document provides an overview of pharmacophore mapping and pharmacophore-based screening. It defines a pharmacophore as the pattern of molecular features responsible for a drug's biological activity. The key steps in pharmacophore modeling are identifying common binding elements in active compounds, generating potential ligand conformations, and determining the 3D relationships between pharmacophore elements. Pharmacophore models can be generated manually based on known active ligands or automatically using software. Receptor-based pharmacophore generation uses the 3D structure of the target protein to identify favorable binding sites. Overall, pharmacophore mapping is used in computer-aided drug design to identify novel ligands that interact with the same biological target.
The document discusses several approaches to designing enzyme inhibitors: structure-based drug design uses 3D enzyme structures to screen compounds and design inhibitors; fragment-based design starts with small fragments that bind weakly and are optimized; pharmacophore-based design identifies essential structural features compounds need to interact with the enzyme; other approaches include quantitative structure-activity relationship analysis, high-throughput screening, using natural products as starting points, targeting allosteric sites, covalent bonding, using peptide or protein inhibitors, and computational methods. The best approach depends on the target enzyme and desired inhibitor properties.
This document discusses pharmacophore approach in rational drug design. It begins by defining a pharmacophore as an abstract description of molecular features necessary for molecular recognition by a biological macromolecule. It then discusses pharmacophore mapping, methods of pharmacophore screening, and applications. Key steps in developing a pharmacophore model include selecting a training set of ligands, conformational analysis, molecular superposition, abstraction, and validation. Pharmacophore models can be used to retrieve potential drug leads from databases and design new molecules.
Principles and Applications of Structure Activity RelationshipNizam Ashraf
This document discusses structure-activity relationships (SARs) and quantitative structure-activity relationships (QSARs) in drug design. It explains that compounds with similar structures to an active drug are often biologically active as well, and studying their SARs can provide information about what parts of the structure are responsible for the drug's effects and side effects. QSARs attempt to mathematically relate biological activity to measurable physicochemical parameters like lipophilicity, electronic effects, and steric effects. Parameters like partition coefficients, Hammett constants, and Taft steric constants are used to represent these properties in equations. Hansch analysis and Craig plots are also discussed as methods to predict potential drug activity based on these quantitative relationships.
IDENTIFICATION OF ACTIVE PART : THE PHARMACOPHOREPRUTHVIRAJ K
Portion of the molecule containing the essential organic functional groups that directly interact with the receptor active site and are responsible for the activity are know as pharmacophore.
Pharmacophore model represents the binding mode of active molecules to their target.
A pharmacophore model differentiates between active and inactive molecule.
The document discusses various topics related to computer-aided drug design (CADD), including:
1) The definitions of drug-likeness, druggability, and the Rule of Five for screening drug-like molecules. The Rule of Five outlines molecular properties important for a drug's absorption and metabolism.
2) Pharmacophore-based and ligand-based virtual screening methods which use the structure of known active ligands to search compound libraries for similar molecules.
3) The role of virtual screening in CADD to select compounds for biological testing from large databases using techniques like structure-based docking and ligand-based similarity searching. Scoring functions are also used to rank compounds.
The document discusses pharmacophore modeling and mapping. It defines a pharmacophore as the spatial arrangement of chemical features responsible for a drug's biological activity. Pharmacophore modeling involves identifying active ligands, extracting pharmacophoric features, conformational searching, and generating pharmacophore hypotheses. Pharmacophore mapping methods include constrained systematic search, clique detection, and maximum likelihood approaches. HipHop is described as performing an exhaustive search of all possible pharmacophore combinations from a training set. Applications of pharmacophore include de novo ligand design using programs like NEWLEAD and PhDD, and lead optimization to improve properties like potency, selectivity, and ADMET.
Pharmacophore Mapping and Virtual Screening (Computer aided Drug design)AkshayYadav176
Pharmacophore Mapping and Virtual Screening (Computer aided Drug design)
Concept of pharmacophore, Pharmacophore mapping, Identification of pharmacophore features and pharmacophore modeling, Conformation search used in pharmacophore mapping, Virtual screening.
Lecture 10 pharmacophore modeling and sar paradoxRAJAN ROLTA
The document discusses pharmacophore modeling, which involves identifying the 3D arrangement of functional groups necessary for a molecule to bind to a target site and trigger a biological response. It notes that pharmacophore modeling is important for understanding receptor-ligand interactions and for drug design. Two types are described: ligand-based, which extracts common chemical features from known ligands in the absence of the target structure, and structure-based, which generates features from the target or target-ligand complex structure. Pharmacophore models can be used for virtual screening to identify molecules that encode the required interaction pattern. The document also discusses the structure-activity relationship and notes that similar molecules do not always have similar activities, known as the SAR paradox.
Pharmacophore Modeling and Docking Techniques.pptDrVivekChauhan1
Pharmacophore modeling and molecular docking techniques are important computational methods used in drug design and discovery. Pharmacophore models identify the essential molecular features responsible for biological activity. Molecular docking predicts how drug molecules bind to protein targets. The document discusses key concepts like pharmacophores, bioisosterism, and molecular docking workflows. It also covers common docking software and factors that influence docking results like intramolecular forces and target preparation. Overall, the document provides an overview of pharmacophore modeling and molecular docking techniques that are widely applied in rational drug design.
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.
This document provides an overview of the key concepts in medicinal chemistry that will be covered in the class. It discusses the history and evolution of medicinal chemistry, defining drugs and their properties, drug discovery and design processes, and the pharmacokinetic and pharmacodynamic phases of drug action. The goal of medicinal chemistry is to design and synthesize new drug molecules through understanding their interactions with biological targets and structure-activity relationships.
Hey students here i am attaching the powerpoint presenatation on the Receptor/enzyme-interaction and its analysis, Receptor/enzyme cavity size prediction, predicting
the functional components of cavities and the concept regarding the fragment based drug design.
The document discusses lead identification and optimization in drug design. It describes the general drug discovery process which includes target validation, assay development, high-throughput screening, hit to lead identification, and lead optimization stages. Lead optimization is one of the most important steps and involves modifying lead compounds to improve potency, selectivity, and pharmacokinetic parameters. Structure-based and ligand-based drug design approaches are used, along with in silico tools to predict properties like toxicity and ensure drug-likeness. Key steps in structure-based design include identifying the binding site and growing fragments in an iterative process until an optimized lead is obtained.
This document discusses several programs used for automatic pharmacophore identification: Catalyst/HipHop, DISCO, and GASP. These programs differ in their algorithms for ligand alignment and handling of conformational flexibility. Catalyst/HipHop uses quantitative activity data to derive pharmacophores. DISCO compares interatomic distances between ligand and hypothetical receptor points. GASP applies genetic algorithms to superimpose flexible ligands without constraints. Pharmacophore identification is important for computer-aided drug design when the target receptor structure is unknown.
Medicinal chemistry involves the design and synthesis of pharmaceutical agents to benefit humanity. It includes structure-activity relationships, receptor interactions, and absorption/metabolism properties of compounds. Combinatorial chemistry produces large libraries of similar molecules for screening via techniques like solid phase synthesis and parallel/mixed synthesis. Quantitative structure-activity relationship analysis uses parameters like lipophilicity, electronic effects, and steric hindrance to develop mathematical models correlating biological activity to a compound's physicochemical properties.
Metabolite Likeness for selection of pharmaceutical drug librariesAnkit Dhaundiyal
This document discusses using metabolite-likeness as a criterion for designing and selecting pharmaceutical drug libraries for drug discovery. It compares drugs and compounds from libraries to metabolites in terms of molecular properties and structural similarity. Drugs were found to be more similar to metabolites than typical library compounds based on molecular descriptors like connectivity fingerprints. The document concludes more mechanistic filters are needed that account for drug transporters in addition to molecular properties.
The document discusses drug discovery, which involves identifying compounds that can potentially become drugs. The process begins with drug screening of many compounds to find "hits" that show activity in a relevant disease assay. If further testing of a hit compound or its derivatives continues to show promise, it becomes a "lead" compound. The drug discovery process can then involve optimizing lead compounds using various technologies and approaches like compound-centered drug design, target-centered drug design, high-throughput screening, and structure-based rational drug design to develop candidate drugs for testing and potential marketing.
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.
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2. What is pharmacophore?
• The pharmacophore is the group of these properties that form a vital
part of a drug .
• An ensemble of steric and electronic features that is necessary to
ensure the optimal supramolecular interactions with a specific
biological target and to trigger (or block) its biological response".
• A pharmacophore model explains how structurally diverse ligands can
bind to a common receptor site.
• Pharmacophore models can be used to identify through de novo design
or virtual screening novel ligands that will bind to the same receptor.
3. Pharmacophore -Features
• Typical pharmacophore features include hydrophobic centroids,
aromatic rings, hydrogen bond acceptors or donors, cations, and
anions. These pharmacophoric points may be located on the ligand
itself or may be projected points presumed to be located in the
receptor.
• The features need to match different chemical groups with similar
properties, in order to identify novel ligands. Ligand-receptor
interactions are typically “polar positive”, “polar negative” or
“hydrophobic”. A well-defined pharmacophore model includes both
hydrophobic volumes and hydrogen bond vectors.
4. Process for developing a pharmacophore model
They generally involves the following steps:
• Select a training set of ligands – Choose a structurally diverse set of molecules that will be used for
developing the pharmacophore model. As a pharmacophore model should be able to discriminate between
molecules with and without bioactivity, the set of molecules should include both active and inactive
compounds.
• Conformational analysis – Generate a set of low energy conformations that is likely to contain the bioactive
conformation for each of the selected molecules.
• Molecular superimposition – Superimpose ("fit") all combinations of the low-energy conformations of the
molecules. Similar (bioisosteric) functional groups common to all molecules in the set might be fitted (e.g.,
phenyl rings or carboxylic acid groups). The set of conformations (one conformation from each active
molecule) that results in the best fit is presumed to be the active conformation.
• Abstraction – Transform the superimposed molecules into an abstract representation. For example,
superimposed phenyl rings might be referred to more conceptually as an 'aromatic ring' pharmacophore
element. Likewise, hydroxy groups could be designated as a 'hydrogen-bond donor/acceptor' pharmacophore
element.
• Validation – A pharmacophore model is a hypothesis accounting for the observed biological activities of a set
of molecules that bind to a common biological target. The model is only valid insofar as it is able to account
for differences in biological activity of a range of molecules.
5. Applications
• In modern computational chemistry, pharmacophores are used to define the
essential features of one or more molecules with the same biological activity.
• A database of diverse chemical compounds can then be searched for more
molecules which share the same features arranged in the same relative
orientation.
• Pharmacophores are also used as the starting point for developing 3D-QSAR
models. Such tools and a related concept of "privileged structures", which are
"defined as molecular frameworks which are able of providing useful ligands
for more than one type of receptor or enzyme target by judicious structural
modifications" aid in drug discovery.
6. Pharmacophore in Drug Design and Discovery
• A pharmacophore model is a geometrical description of the chemical functionalities required of a
ligand to interact with the receptor. modern medicinal chemistry is to reduce the overall cost -
discovery and development of a new drug, by identifying the most promising candidates to focus
on the experimental efforts.
• Experimental screening for lead structure determination suffers from limitation with respect to the
possible number of compounds that can be submitted to a high-throughput bio-assay and with the
low number of hits obtained that is in the range of 0.1%.
• The pharmacophore approach has proven to be successful, allowing (i) the perception and
understanding of key interactions between a target and a ligand and (ii) the enrichment of hit rates
obtained in experimental screening of subsets that have been obtained from in silico screening
experiments.
• Pharmacophore mapping is one of the major elements of drug design in the absence of structural
data of the target receptor.it can be used as queries for retrieving potential leads from structural
databases (lead discovery), for designing molecules with specific desired attributes (lead
optimization), and for assessing similarity and diversity of molecules using pharmacophore
fingerprints.
• It can also be used to align molecules based on the 3D arrangement of chemical features or to
develop predictive 3D QSAR models.