1. The document discusses various molecular modeling software and databases that can be used to measure bond lengths, bond angles, bond strengths, and compare protein and DNA structures between different species.
2. It provides instructions on how to use modeling programs like Jmol, Pymol, Rasmol and ACD Labs to obtain 3D structures from the Protein Data Bank and measure various parameters.
3. The document suggests possible research questions focusing on how factors like element identity, bond type, substituents, and lone pair electrons affect bond angles and lengths based on data collected from both 3D modeling and databases.
IB Chemistry on ICT, 3D software, Jmol, Pymol and Rasmol for Internal AssessmentLawrence kok
1. The document discusses measuring bond lengths, angles, and strengths using molecular modeling software like Jmol, PyMol, RasMol, and ACD Lab.
2. It also discusses using these software and databases like PDB, NCBI, UCSC and Ensembl to collect data on hydrogen bond distances between DNA/RNA base pairs across different species and cell types.
3. Limitations of molecular modeling are considered, like using multiple programs to validate results and checking against reliable databases like CRC and NIST. Accuracy of predicted structures from simulations alone is questioned.
IB Chemistry on ICT, 3D software, Jmol, Rasmol and Pymol for Internal AssessmentLawrence kok
The document provides a tutorial on using various 3D molecular modeling software like Jmol, Pymol, Rasmol and ACD Lab. It discusses how to use these software to generate 3D structures from SMILES or PDB files, optimize structures, measure bond lengths, angles and distances. Possible research questions are outlined focusing on how factors like element identity, double bonds, substituents affect bond angles based on data collected from the software and databases. Limitations of using computational methods are also discussed.
IB Chemistry on using ICT, 3D software with Jmol, Pymol, Rasmol and ACD for I...Lawrence kok
The document provides a tutorial on using various 3D molecular modeling software like Jmol, Pymol, ACD Lab and Rasmol. It discusses using these programs to measure properties like bond lengths, bond angles, hydrogen bonds and compare protein structures. Links are provided to download the software and view tutorials and examples of using the programs to analyze molecules from the Protein Data Bank and build organic structures. Limitations of computational modeling are also noted.
IB Chemistry on ICT, 3D software, Jmol, Pymol, Rasmol and ACD for Internal As...Lawrence kok
The document discusses measuring properties of bonds such as length, angle, and strength using various 3D modeling software. It also covers using these programs to analyze protein and enzyme structures from the Protein Data Bank by inputting four-letter codes. Details are provided on tools for molecular modeling and 3D representation in Jmol, PyMol, RasMol, and ACD Labs. Spectroscopic and chemistry databases are listed for reference.
IB Chemistry on ICT, 3D software, Jmol, Pymol and Rasmol for Internal AssessmentLawrence kok
1. The document discusses measuring bond lengths, angles, and strengths using molecular modeling software like Jmol, PyMol, RasMol, and ACD Lab.
2. It also discusses using these software and databases like PDB, NCBI, UCSC and Ensembl to collect data on hydrogen bond distances between DNA/RNA base pairs across different species and cell types.
3. Limitations of molecular modeling are considered, like using multiple programs to validate results and checking against reliable databases like CRC and NIST. Accuracy of predicted structures from simulations alone is questioned.
IB Chemistry on ICT, 3D software, Jmol, Rasmol and Pymol for Internal AssessmentLawrence kok
The document provides a tutorial on using various 3D molecular modeling software like Jmol, Pymol, Rasmol and ACD Lab. It discusses how to use these software to generate 3D structures from SMILES or PDB files, optimize structures, measure bond lengths, angles and distances. Possible research questions are outlined focusing on how factors like element identity, double bonds, substituents affect bond angles based on data collected from the software and databases. Limitations of using computational methods are also discussed.
IB Chemistry on using ICT, 3D software with Jmol, Pymol, Rasmol and ACD for I...Lawrence kok
The document provides a tutorial on using various 3D molecular modeling software like Jmol, Pymol, ACD Lab and Rasmol. It discusses using these programs to measure properties like bond lengths, bond angles, hydrogen bonds and compare protein structures. Links are provided to download the software and view tutorials and examples of using the programs to analyze molecules from the Protein Data Bank and build organic structures. Limitations of computational modeling are also noted.
IB Chemistry on ICT, 3D software, Jmol, Pymol, Rasmol and ACD for Internal As...Lawrence kok
The document discusses measuring properties of bonds such as length, angle, and strength using various 3D modeling software. It also covers using these programs to analyze protein and enzyme structures from the Protein Data Bank by inputting four-letter codes. Details are provided on tools for molecular modeling and 3D representation in Jmol, PyMol, RasMol, and ACD Labs. Spectroscopic and chemistry databases are listed for reference.
IB Chemistry on ICT, 3D software, Jmol, Pymol and Rasmol for Internal AssessmentLawrence kok
The document discusses using 3D modeling software and databases to collect data on bond angles and lengths of alcohols and haloalkanes. Data was collected from Jmol, Pymol, Rasmol, ACD Lab and databases like CRC and RSC and averaged. Limitations of computational methods are that they assume non-interacting molecules in isolation. Data from multiple sources should be compared and experimental data is most reliable.
Patent Cheminformatics: Identification of key compounds in patentsSorel Muresan
Patents can contain valuable chemical and biological information not found in scientific journals. This document discusses extracting key compounds from patents, including identifying sources for full-text patents, extracting compounds from text, and predicting key compounds through methods like frequency of group analysis. Predicting key compounds is important as they are often the most biologically active and suitable for further development. The document provides examples of extracting known drug compounds like Bextra, Aciphex, and Aricept from early patents through these methods.
Getting the Big Picture by Joining up the SAR dotsSorel Muresan
Getting the Big Picture by Joining up the SAR dots
This document discusses challenges in integrating structure and bioactivity data at large scales due to the volume and complexity of unstructured data from various sources. It describes efforts to extract chemical entities from text using natural language processing and to standardize structures. The Chemistry Connect knowledge base aims to enable searching across internal and external datasets by developing a chemical dictionary and common representation of concepts.
IB Chemistry on Free radical substitution, Addition and Nucleophilic substitu...Lawrence kok
This document describes various classes of organic compounds including alkanes, alkenes, alcohols, esters, and their properties. Alkanes are saturated hydrocarbons with the general formula CnH2n+2. Alkenes are unsaturated hydrocarbons containing carbon-carbon double bonds with the general formula CnH2n. Alcohols contain an -OH functional group and have the general formula CnH2n+1OH. Esters are formed from the condensation reaction between carboxylic acids and alcohols, producing water as a byproduct. Common chemical reactions for each class are also outlined such as combustion, addition, oxidation, and esterification
IB Chemistry on Standard Reduction Potential, Standard Hydrogen Electrode and...Lawrence kok
The document discusses standard electrode potentials and how they are measured. It explains that the standard hydrogen electrode is used as a reference with a potential of 0 V. Other half-cell potentials are measured against this to determine their standard electrode potential. Common half-cells include metal/metal ion, gas/ion, and ion/ion systems. Standard conditions of 1 M concentrations, 1 atm pressure, and 298K temperature must be used. The potentials of zinc/zinc ion, iron III/iron II, and chlorine/chloride ion half-cells are given as examples.
IB Chemistry on Redox, Reactivity Series and Displacement reactionLawrence kok
The document discusses the reactivity series of metals and non-metals. It explains that metals can be arranged based on their tendency to lose electrons and form positive ions through oxidation. More reactive metals oxidize less reactive ones in displacement reactions. Carbon and aluminum are strong reducing agents that can displace iron from its oxide to extract iron. The reactivity of non-metals increases from fluorine to iodine as they have a higher tendency to gain electrons and form negative ions through reduction reactions.
IB Chemistry on Organic nomenclature and functional groups.Lawrence kok
The document discusses organic functional groups and their naming conventions. It provides the suffixes used to name different classes of organic compounds based on their functional groups, including -ane for alkanes, -ene for alkenes, -yne for alkynes, -ol for alcohols, and -one for ketones. It also gives examples of compound names and formulas for different functional groups like ethane for alkanes and ethene for alkenes.
IB Chemistry on Reactivity Series vs Electrochemical SeriesLawrence kok
The document discusses the reactivity and electrochemical series of group 1 alkali metals lithium, sodium, and potassium. While lithium has the most negative standard reduction potential, indicating it is most easily oxidized, potassium is the most reactive when reacting with water and acids due to lower kinetic barriers. The electrochemical series is a thermodynamic measurement based on standard potentials, while the reactivity series considers reaction kinetics. Thus, there is a correlation but not perfect agreement between the two series.
IB Chemistry on Crystal Field Theory and Splitting of 3d orbitalLawrence kok
The document discusses the properties and behaviors of transition metals. Transition metals are d-block elements that have partially filled d orbitals. They can exist in multiple oxidation states and form colored complexes due to their variable electron configurations. Transition metals are also good catalysts as their partially filled d orbitals allow them to easily gain or lose electrons and form weak bonds with reactants to lower the activation energy of chemical reactions.
IB Chemistry on Gibbs Free Energy, Equilibrium constant and Cell PotentialLawrence kok
The document discusses the relationship between thermodynamic quantities such as Gibbs free energy (ΔG), equilibrium constant (Kc), cell potential (Ecell), and their significance. It provides equations relating these quantities and explains how ΔG and Kc can be used to predict the spontaneity and extent of chemical reactions. Examples are given to show how ΔG decreases as the reaction progresses towards equilibrium, and how the values of ΔG and Kc indicate the position of the reaction mixture between reactants and products.
IB Chemistry on Absorption Spectrum and Line Emission/Absorption SpectrumLawrence kok
Transition metal complexes can have different colors due to the splitting of the metal ion's d orbitals caused by ligands. Ligands of varying strength cause varying degrees of d orbital splitting, represented by ΔE. Stronger ligands cause greater splitting and absorption of higher energy visible light, resulting in colors like violet or blue. Weaker ligands cause less splitting and absorption of lower energy visible light, appearing as colors like yellow or green. The spectrochemical series orders ligands from weakest to strongest field strength based on the color produced.
IB Chemistry on Redox Design and Nernst EquationLawrence kok
The document outlines research questions and procedures to investigate the effect of various factors on the emf and current of voltaic cells. Specifically, it will study how concentration, temperature, electrode size, salt bridge composition, and metal pairs affect measurements in zinc-copper and copper-copper cells. Tests will be conducted by varying one factor at a time while keeping others standard, and measuring the resulting emf and current.
IB Chemistry on Entropy and Law of ThermodynamicsLawrence kok
This document discusses entropy and the laws of thermodynamics. It defines entropy as a measure of molecular disorder or randomness, and explains that entropy increases as energy and matter disperse and become more randomly distributed. The second law of thermodynamics states that the entropy of the universe always increases for spontaneous processes. Reactions and phase changes that result in higher entropy (more disorder) of the products are spontaneous. The document provides examples and explanations of how entropy changes in different processes.
IB Chemistry on Stereoisomers, E/Z, Cis Trans, Geometric, Optical and Polarim...Lawrence kok
There are two types of isomerism: structural isomerism and stereoisomerism. Structural isomers have the same molecular formula but different structural formulas or arrangements of atoms. Stereoisomers have the same molecular formula and structural formula but different spatial arrangements of atoms. Examples of stereoiosmers include geometric isomers, which require a double bond or ring structure to prevent bond rotation, and optical isomers. The E/Z or Cahn-Ingold-Prelog system is used to name geometric isomers based on atomic mass priorities of substituents.
IB Chemistry on Structural Isomers and Benzene StructureLawrence kok
The document discusses organic functional groups and their naming conventions. It provides examples of common organic compound classes including alkanes, alkenes, alkynes, alcohols, ethers, ketones, aldehydes, carboxylic acids, esters, amides, amines, nitriles, and halogenoalkanes. It also discusses IUPAC nomenclature rules for systematically naming organic molecules based on functional groups, carbon chain length and position of substituents. Additionally, it briefly touches on isomerism, which refers to compounds with the same molecular formula but different structural or spatial arrangements of atoms.
IB Chemistry on ICT, 3D software, Jmol, Pymol and Rasmol for Internal AssessmentLawrence kok
The document discusses using 3D modeling software and databases to collect data on bond angles and lengths of alcohols and haloalkanes. Data was collected from Jmol, Pymol, Rasmol, ACD Lab and databases like CRC and RSC and averaged. Limitations of computational methods are that they assume non-interacting molecules in isolation. Data from multiple sources should be compared and experimental data is most reliable.
Patent Cheminformatics: Identification of key compounds in patentsSorel Muresan
Patents can contain valuable chemical and biological information not found in scientific journals. This document discusses extracting key compounds from patents, including identifying sources for full-text patents, extracting compounds from text, and predicting key compounds through methods like frequency of group analysis. Predicting key compounds is important as they are often the most biologically active and suitable for further development. The document provides examples of extracting known drug compounds like Bextra, Aciphex, and Aricept from early patents through these methods.
Getting the Big Picture by Joining up the SAR dotsSorel Muresan
Getting the Big Picture by Joining up the SAR dots
This document discusses challenges in integrating structure and bioactivity data at large scales due to the volume and complexity of unstructured data from various sources. It describes efforts to extract chemical entities from text using natural language processing and to standardize structures. The Chemistry Connect knowledge base aims to enable searching across internal and external datasets by developing a chemical dictionary and common representation of concepts.
IB Chemistry on Free radical substitution, Addition and Nucleophilic substitu...Lawrence kok
This document describes various classes of organic compounds including alkanes, alkenes, alcohols, esters, and their properties. Alkanes are saturated hydrocarbons with the general formula CnH2n+2. Alkenes are unsaturated hydrocarbons containing carbon-carbon double bonds with the general formula CnH2n. Alcohols contain an -OH functional group and have the general formula CnH2n+1OH. Esters are formed from the condensation reaction between carboxylic acids and alcohols, producing water as a byproduct. Common chemical reactions for each class are also outlined such as combustion, addition, oxidation, and esterification
IB Chemistry on Standard Reduction Potential, Standard Hydrogen Electrode and...Lawrence kok
The document discusses standard electrode potentials and how they are measured. It explains that the standard hydrogen electrode is used as a reference with a potential of 0 V. Other half-cell potentials are measured against this to determine their standard electrode potential. Common half-cells include metal/metal ion, gas/ion, and ion/ion systems. Standard conditions of 1 M concentrations, 1 atm pressure, and 298K temperature must be used. The potentials of zinc/zinc ion, iron III/iron II, and chlorine/chloride ion half-cells are given as examples.
IB Chemistry on Redox, Reactivity Series and Displacement reactionLawrence kok
The document discusses the reactivity series of metals and non-metals. It explains that metals can be arranged based on their tendency to lose electrons and form positive ions through oxidation. More reactive metals oxidize less reactive ones in displacement reactions. Carbon and aluminum are strong reducing agents that can displace iron from its oxide to extract iron. The reactivity of non-metals increases from fluorine to iodine as they have a higher tendency to gain electrons and form negative ions through reduction reactions.
IB Chemistry on Organic nomenclature and functional groups.Lawrence kok
The document discusses organic functional groups and their naming conventions. It provides the suffixes used to name different classes of organic compounds based on their functional groups, including -ane for alkanes, -ene for alkenes, -yne for alkynes, -ol for alcohols, and -one for ketones. It also gives examples of compound names and formulas for different functional groups like ethane for alkanes and ethene for alkenes.
IB Chemistry on Reactivity Series vs Electrochemical SeriesLawrence kok
The document discusses the reactivity and electrochemical series of group 1 alkali metals lithium, sodium, and potassium. While lithium has the most negative standard reduction potential, indicating it is most easily oxidized, potassium is the most reactive when reacting with water and acids due to lower kinetic barriers. The electrochemical series is a thermodynamic measurement based on standard potentials, while the reactivity series considers reaction kinetics. Thus, there is a correlation but not perfect agreement between the two series.
IB Chemistry on Crystal Field Theory and Splitting of 3d orbitalLawrence kok
The document discusses the properties and behaviors of transition metals. Transition metals are d-block elements that have partially filled d orbitals. They can exist in multiple oxidation states and form colored complexes due to their variable electron configurations. Transition metals are also good catalysts as their partially filled d orbitals allow them to easily gain or lose electrons and form weak bonds with reactants to lower the activation energy of chemical reactions.
IB Chemistry on Gibbs Free Energy, Equilibrium constant and Cell PotentialLawrence kok
The document discusses the relationship between thermodynamic quantities such as Gibbs free energy (ΔG), equilibrium constant (Kc), cell potential (Ecell), and their significance. It provides equations relating these quantities and explains how ΔG and Kc can be used to predict the spontaneity and extent of chemical reactions. Examples are given to show how ΔG decreases as the reaction progresses towards equilibrium, and how the values of ΔG and Kc indicate the position of the reaction mixture between reactants and products.
IB Chemistry on Absorption Spectrum and Line Emission/Absorption SpectrumLawrence kok
Transition metal complexes can have different colors due to the splitting of the metal ion's d orbitals caused by ligands. Ligands of varying strength cause varying degrees of d orbital splitting, represented by ΔE. Stronger ligands cause greater splitting and absorption of higher energy visible light, resulting in colors like violet or blue. Weaker ligands cause less splitting and absorption of lower energy visible light, appearing as colors like yellow or green. The spectrochemical series orders ligands from weakest to strongest field strength based on the color produced.
IB Chemistry on Redox Design and Nernst EquationLawrence kok
The document outlines research questions and procedures to investigate the effect of various factors on the emf and current of voltaic cells. Specifically, it will study how concentration, temperature, electrode size, salt bridge composition, and metal pairs affect measurements in zinc-copper and copper-copper cells. Tests will be conducted by varying one factor at a time while keeping others standard, and measuring the resulting emf and current.
IB Chemistry on Entropy and Law of ThermodynamicsLawrence kok
This document discusses entropy and the laws of thermodynamics. It defines entropy as a measure of molecular disorder or randomness, and explains that entropy increases as energy and matter disperse and become more randomly distributed. The second law of thermodynamics states that the entropy of the universe always increases for spontaneous processes. Reactions and phase changes that result in higher entropy (more disorder) of the products are spontaneous. The document provides examples and explanations of how entropy changes in different processes.
IB Chemistry on Stereoisomers, E/Z, Cis Trans, Geometric, Optical and Polarim...Lawrence kok
There are two types of isomerism: structural isomerism and stereoisomerism. Structural isomers have the same molecular formula but different structural formulas or arrangements of atoms. Stereoisomers have the same molecular formula and structural formula but different spatial arrangements of atoms. Examples of stereoiosmers include geometric isomers, which require a double bond or ring structure to prevent bond rotation, and optical isomers. The E/Z or Cahn-Ingold-Prelog system is used to name geometric isomers based on atomic mass priorities of substituents.
IB Chemistry on Structural Isomers and Benzene StructureLawrence kok
The document discusses organic functional groups and their naming conventions. It provides examples of common organic compound classes including alkanes, alkenes, alkynes, alcohols, ethers, ketones, aldehydes, carboxylic acids, esters, amides, amines, nitriles, and halogenoalkanes. It also discusses IUPAC nomenclature rules for systematically naming organic molecules based on functional groups, carbon chain length and position of substituents. Additionally, it briefly touches on isomerism, which refers to compounds with the same molecular formula but different structural or spatial arrangements of atoms.
IB Chemistry on Gibbs Free Energy vs Entropy on spontanietyLawrence kok
This document discusses key concepts in thermodynamics including:
1) The first law of thermodynamics states that energy cannot be created or destroyed, only transferred or changed in form. The change in internal energy of a system (ΔE) equals heat transferred (q) plus work done (w).
2) The second law of thermodynamics states that the entropy of the universe always increases for spontaneous processes. Entropy (S) is a measure of disorder or randomness at the molecular level. Spontaneous processes result in increased entropy of the universe (ΔSuni > 0).
3) The third law of thermodynamics states that the entropy of a perfectly crystalline substance is zero at absolute zero temperature
This document provides an overview of analytical techniques used in chemistry, including both classical and instrumental methods. Classical methods involve qualitative and quantitative analysis using chemical tests, flame tests, and titration. Instrumental methods discussed include various types of spectroscopy such as infrared spectroscopy, nuclear magnetic resonance spectroscopy, and chromatography techniques used for separation analysis. Specific analytical techniques are described including their applications and mechanisms. Key concepts covered include electromagnetic radiation, molecular vibration, factors that influence infrared absorption frequencies, and interpreting infrared spectra to determine functional groups in organic compounds.
IB Chemistry on Bond Enthalpy, Enthalpy formation, combustion and atomizationLawrence kok
This document discusses several methods to calculate enthalpy change (ΔH) for chemical reactions, including using average bond enthalpies, standard enthalpies of formation (ΔHf), standard enthalpies of combustion (ΔHc), and standard enthalpies of atomization (ΔHa). It provides examples of calculating ΔH for reactions involving CH4, CCl4, S8, carbon polymorphs, and the formation of C5H5N from carbon, hydrogen, and nitrogen. The document emphasizes that while average bond enthalpies can be used, ΔHf, ΔHc, and ΔHa are generally more accurate as they consider the specific bonds in the reaction.
IB Chemistry on Homologous series and functional groups of organic moleculesLawrence kok
The document discusses organic functional groups and their IUPAC nomenclature rules. It defines classes of organic compounds such as alkanes, alkenes, alkynes, alcohols, ethers, ketones, aldehydes, carboxylic acids, esters, amides, amines, nitriles and haloalkanes based on their functional groups. It provides examples and molecular formulas for different functional groups and discusses IUPAC nomenclature rules for systematically naming organic compounds including identifying the parent chain, functional group, substituents and their positions.
IB Chemistry on Nuclear Magnetic Resonance, Chemical Shift and Splitting PatternLawrence kok
This document discusses various analytical techniques used in chemistry, including both classical and instrumental methods. Classical methods involve qualitative and quantitative analysis using chemical tests, titrations, and gravimetric analysis. Instrumental methods discussed include various types of spectroscopy such as infrared spectroscopy, nuclear magnetic resonance spectroscopy, and chromatography techniques used for separation analysis. The document provides details on the principles, applications, and information provided by different analytical techniques.
IB Chemistry on Energetics experiment, Thermodynamics and Hess's LawLawrence kok
1. Heat is transferred from hot to cold objects due to a temperature difference, causing the average kinetic energy per particle to equalize.
2. Gases at the same temperature have the same average kinetic energy per particle regardless of mass. Heavier gases have lower average speeds than lighter gases at the same temperature.
3. The amount of heat required to change an object's temperature depends on its mass and specific heat capacity. Substances with higher specific heat capacities require more heat to change their temperature by 1°C.
IB Chemistry on Properties of Transition Metal and MagnetismLawrence kok
The document discusses the periodic table and properties of elements. It is divided into blocks based on orbital filling: s, p, d, and f blocks. Transition metals are in the d block and have partially filled d orbitals. They exhibit variable oxidation states, can form colored complexes, and show catalytic activity due to this electronic configuration. Magnetic properties depend on paired or unpaired electrons in the outer shell.
IB Chemistry on Mass Spectrometry, Index Hydrogen Deficiency and IsotopesLawrence kok
The document discusses index hydrogen deficiency (IHD), which is a measure of unsaturation in molecules. IHD is calculated based on the number of hydrogen atoms fewer than would be present in a saturated molecule with the same number of carbon atoms. The document provides examples of calculating IHD for various molecules containing double bonds, rings, and heteroatoms like nitrogen. It also describes how mass spectrometry can be used to determine IHD and identify molecular structures based on their fragmentation patterns.
Metabolic network mapping for metabolomicsDinesh Barupal
We present a novel approach to integrate biochemical pathway and chemical relationships to map all detected metabolites in network graphs (MetaMapp) using KEGG reactant pair database, Tanimoto chemical and NIST mass spectral similarity scores. In fetal and maternal lungs, and in maternal blood plasma from pregnant rats exposed to environmental tobacco smoke (ETS), 459 unique metabolites comprising 179 structurally identified compounds were detected by gas chromatography time of flight mass spectrometry (GC-TOF MS) and BinBase data processing. MetaMapp graphs in Cytoscape showed much clearer metabolic modularity and complete content visualization compared to conventional biochemical mapping approaches. Cytoscape visualization of differential statistics results using these graphs showed that overall, fetal lung metabolism was more impaired than lungs and blood metabolism in dams. Fetuses from ETS-exposed dams expressed lower lipid and nucleotide levels and higher amounts of energy metabolism intermediates than control animals, indicating lower biosynthetic rates of metabolites for cell division, structural proteins and lipids that are critical for in lung development.
MetaMapp graphs efficiently visualizes mass spectrometry based metabolomics datasets as network graphs in Cytoscape, and highlights metabolic alterations that can be associated with higher rate of pulmonary diseases and infections in children prenatally exposed to ETS. The MetaMapp scripts can be accessed at http://metamapp.fiehnlab.ucdavis.edu.
Design of compound libraries for fragment screening (Feb 2012 version)Peter Kenny
Slimmed down fragment screening library talk presented at University of Adelaide (Dec 2011) and Pharmaxis (Feb 2012). Includes dingo and Maria Sharapova (losing finalist at 2012 Australian Open). The photo for the title slide is of a range finder from the Admiral Graf Spee and was taken in Montevideo.
Bioinformatics combines biology, chemistry, statistics, and computer science to analyze and interpret biological data. It uses algorithms and techniques of computer science to solve complex biological problems. Some key areas of bioinformatics include organizing biological knowledge, performing sequence analysis, predicting protein structure, genome annotation, and comparative genomics. Bioinformatics is essential for applications like pharmaceutical research, gene therapy, forensic analysis, and understanding biological pathways and networks in systems biology.
Swiss-PdbViewer Introduction-Wenwen WangWenwen Wang
PDB Viewer is an useful software to show and analyze the protein spatial structure. It provides the user friendly interface to analyze several proteins at the same time. The proteins can be superimposed in order to deduce structural alignments and compare their active sites or any other relevant parts. Therefore, PDB Viewer is a necessary tool in nature science research.
This document provides an overview of essential bioinformatics resources for designing PCR primers and oligos for various applications. It begins by outlining general rules for PCR primer design, including recommendations for primer length, melting temperature, specificity, secondary structures, and other factors. It then describes several online tools and databases for designing primers for general purpose PCR, real-time qPCR, methylation studies, and other applications. These resources include Primer3, Primer3Plus, PrimerZ, and Vector NTI. Databases like NCBI Probe and RTPrimerDB provide validated primer sequences. The document emphasizes considering multiple design tools and validation of primers.
Verify3D is a web-based tool that evaluates the correctness of a protein structure model based on its 3D structural profile. It works by assigning structural classes to residues based on their location and environment, then comparing the results to profiles of good protein structures. The tool generates plots representing the average and raw scores for each residue, with higher average scores across residues indicating a more correct model structure. Verify3D is useful for protein structure prediction as it can verify models based on how well their 3D profiles match their amino acid sequences.
ChIP-sequencing is a method to identify genomic regions bound by specific proteins or modifications. It involves cross-linking proteins to DNA, immunoprecipitating the protein-DNA complexes, sequencing the retrieved DNA fragments to determine the genomic binding sites. The key steps are sample preparation involving cross-linking, fragmentation and enrichment, followed by high-throughput sequencing and computational analysis including mapping, peak calling, annotation and visualization of results.
Flow Cytometry Training talks - part 1
This forms the first session of the Garvan Flow , Flow Cytometry Training course. this is a 1 1/2 day training course aimed at giving new and experienced researchers a better understanding of cytometry in medical and biological research.
FIDO Case Study: Performance Comparison of Mulitmodal BiometricsFIDO Alliance
This document summarizes a study that compared the performance of different multimodal biometric authentication methods using face and fingerprint data. 771 participants provided biometric data that was categorized as "good" or "bad" quality based on capture conditions. Error rates and usability metrics like average attempts were then calculated for different fusion rules (AND, OR, parallel, serial) and compared to FIDO standards. The results showed that AND and parallel fusion met FIDO certification requirements for both good and bad quality data, while other methods only met requirements for good data. Overall, multimodal biometrics improved performance over unimodal approaches.
Basics of Primer designing.
Steps involved in designing primers for Prokaryotic expression
Steps involved in designing primers for Eukaryotic expression
This document provides an introduction and overview of the field of bioinformatics. It discusses how bioinformatics combines computer science and biology to analyze large amounts of biological data. Specifically, it mentions that bioinformatics uses algorithms and techniques from computer science to solve complex biological problems related to areas like molecular biology, genomics, drug discovery, and more. It also outlines some of the key applications of bioinformatics like sequence analysis, protein structure prediction, genome annotation, and comparative genomics. Finally, it provides brief descriptions of important biological databases and resources that bioinformaticians use to store and analyze genomic and protein sequence data.
This document discusses several genes related to stem cell pluripotency, including OCT4, SOX2, NANOG, and LIN28. It provides information on the functions of these genes obtained from searches of PubMed, NCBI Gene, and other bioinformatics databases. Details include OCT4's role in maintaining pluripotency, SOX2's interaction with OCT4 and DNA binding structure, alignments of NANOG mRNA and protein sequences between human and mouse, and conserved domains identified in human and mouse LIN28 proteins through BLAST and CDD searches.
This document provides an introduction to homology modeling using computational tools like I-TASSER and Phyre2. It discusses how homology modeling can be used to generate 3D structural models of proteins when an experimental structure is not available. The document addresses common questions from users and outlines the I-TASSER modeling pipeline. Hands-on exercises are provided to allow users to run homology modeling tools and examine the resulting models.
Texas Instruments’ Time of Flight Image Sensor 2017 teardown reverse costing ...Yole Developpement
A look into Texas Instruments’ system-on-chip, including Sony/Softkinetic’s time-of-flight pixel technology, for industrial applications
Today, Time-of-Flight (ToF) systems are among the most innovative technologies offering imaging companies an opportunity to lead the market. Every major player wants to integrate these devices to provide functions such as 3D imaging, proximity sensing, ambient light sensing and gesture recognition.
Sony/Softkinetic has been investigating this technology deeply, providing a unique pixel technology to several image sensor manufacturers in three application areas: consumer, automotive and industrial. For industrial applications, Sony/Softkinetic has licensed its technology to Texas Instruments, which is providing ToF imagers for human detection or robot-human interaction.
The OPT8241 3D ToF imager is packaged using Chip-On-Glass (COG) technology. The device comprises a system-on-chip (SoC) and glass filter in the same component in thin, 0.7 mm-thick, packaging.
This report analyzes the complete component, from the glass near-infrared band-pass filter to the collector based on ToF pixel licenses developed by Sony/Softkinetic and adapted by Texas Instruments. The report includes a complete cost analysis and price estimation of the device based on a detailed description of the package, and the ToF imager.
It also features a complete ToF pixel technology comparison with the Infineon/pmd, STMicroelectronics and Melexis automotive ToF imagers, which are all also based on Sony/Softkinetic technology, with details on the companies’ design choices.
More information on that report at http://www.i-micronews.com/reports.html
Finding PDB files of molecules, locating binding sites, positioning ligand to a macromolecule, building grid and grid parameter file, performing molecular docking, and analysis of docking results by looking over various energy parameters and uses in drug discovery technology.
Cox2007-Protein_fabrication_automationJ. Colin Cox
Protein fabrication automation (PFA) is a process that facilitates the rapid de novo construction of any desired open reading frame (ORF) from synthetic oligonucleotides with low effort, high speed, and little human interaction. PFA integrates software for sequence design and data management, a liquid-handling robot, a robust inside-out nucleation (ION) PCR scheme for gene assembly from oligonucleotides, and a genetic selection system to enrich correctly assembled full-length synthetic ORFs. The process is robust and scalable, enabling the parallel synthesis of closely related protein variants for applications in protein engineering and design.
Welcome to the June 25-26, 2018 Workshop on – 2 Day Workshop on Transcriptomic Data Analysis….
Below you should see an embedded video stream. You can open the stream to fill the full screen to observe or join the workshop as a participant with the link that was emailed to you. If you did not get the link, use the chat box on the bottom right to request the link with your registered email ID.
Homology Modelling through modeller and its analysis using Ramachandran Plot
Modeller practical. Full tutorial created by Zarlish Attique
https://salilab.org/modeller/
The document discusses performing molecular dynamics simulations using GROMACS to minimize the energy of a protein structure. It describes converting protein data files, setting up the simulation box, running the simulation with tools like grompp and mdrun, and analyzing the results by visualizing trajectories and the minimized protein structure.
Similar to IB Chemistry on ICT, 3D software, Jmol, Rasmol and Pymol for Internal Assessment (20)
IA on efficiency of immobilized enzyme amylase (yeast extract) in alginate be...Lawrence kok
Sodium alginate reacts with calcium chloride to form calcium alginate beads that can immobilize enzymes like amylase from yeast extract. These beads were added to a solution of starch and iodine, which produces a blue-black color. As the immobilized amylase breaks down the starch into maltose and simple sugars over 3 minutes, the blue-black color fades. The rate of starch hydrolysis was measured by the decrease in absorbance of the blue-black color over time using a colorimeter.
IA on effect of duration on efficiency of immobilized MnO2 in alginate beads ...Lawrence kok
Sodium alginate and calcium chloride were used to immobilize MnO2 catalyst particles in alginate beads. MnO2-loaded beads were prepared using 3% sodium alginate and 2% calcium chloride solutions and tested in the decomposition of hydrogen peroxide over 4 days. The rate of reaction and efficiency decreased slightly each day, from an initial rate of 0.1976 kPas-1 and 100% efficiency on day 1 to 0.1528 kPas-1 and 77% efficiency on day 4, demonstrating the durability of the immobilized MnO2 catalyst beads over multiple reuse cycles.
IA on effect of concentration of sodium alginate and calcium chloride in maki...Lawrence kok
The document investigates the effect of sodium alginate and calcium chloride concentration on forming alginate beads. Various concentrations of sodium alginate (1%, 2%, 3%) and calcium chloride (1%, 2%, 3%) were used to form beads. 3% sodium alginate added to 2% calcium chloride produced the strongest, biggest beads. This combination will be used to immobilize the catalyst MnO2 in alginate beads so that it can be reused instead of being discarded after reaction with H2O2.
IA on effect of duration (steeping time) on polyphenol (tannins) of tea, usin...Lawrence kok
This document examines the effect of steeping time on the polyphenol content of green tea, as measured by potassium permanganate titration. Green tea bags were steeped in a water bath at 90C for durations ranging from 1 to 5 minutes. The polyphenol content was found to increase linearly with steeping time, ranging from 1247 mg/L after 1 minute to 2078 mg/L after 5 minutes. The titration procedure involved adding tea steeped for different times to a solution with an indicator, and titrating with potassium permanganate solution until the endpoint was reached.
IA on polyphenol quantification using potassium permanganate titration (Lowen...Lawrence kok
This document describes the quantification of polyphenols using potassium permanganate titration. Some key points:
1. Polyphenols are antioxidants found in fruits like grapes, berries, and cider that can be quantified using a redox titration with potassium permanganate.
2. The procedure involves preparing a 0.004M potassium permanganate solution and titrating fruit extracts with it using indigo carmine as an indicator, until the solution turns greenish yellow at the endpoint.
3. The volume of permanganate used corresponds to the amount of polyphenols present, with green grapes containing the most at 665 mg/L tannic acid equivalents based on the titration
A review of the growth of the Israel Genealogy Research Association Database Collection for the last 12 months. Our collection is now passed the 3 million mark and still growing. See which archives have contributed the most. See the different types of records we have, and which years have had records added. You can also see what we have for the future.
This slide is special for master students (MIBS & MIFB) in UUM. Also useful for readers who are interested in the topic of contemporary Islamic banking.
How to Fix the Import Error in the Odoo 17Celine George
An import error occurs when a program fails to import a module or library, disrupting its execution. In languages like Python, this issue arises when the specified module cannot be found or accessed, hindering the program's functionality. Resolving import errors is crucial for maintaining smooth software operation and uninterrupted development processes.
Reimagining Your Library Space: How to Increase the Vibes in Your Library No ...Diana Rendina
Librarians are leading the way in creating future-ready citizens – now we need to update our spaces to match. In this session, attendees will get inspiration for transforming their library spaces. You’ll learn how to survey students and patrons, create a focus group, and use design thinking to brainstorm ideas for your space. We’ll discuss budget friendly ways to change your space as well as how to find funding. No matter where you’re at, you’ll find ideas for reimagining your space in this session.
Walmart Business+ and Spark Good for Nonprofits.pdfTechSoup
"Learn about all the ways Walmart supports nonprofit organizations.
You will hear from Liz Willett, the Head of Nonprofits, and hear about what Walmart is doing to help nonprofits, including Walmart Business and Spark Good. Walmart Business+ is a new offer for nonprofits that offers discounts and also streamlines nonprofits order and expense tracking, saving time and money.
The webinar may also give some examples on how nonprofits can best leverage Walmart Business+.
The event will cover the following::
Walmart Business + (https://business.walmart.com/plus) is a new shopping experience for nonprofits, schools, and local business customers that connects an exclusive online shopping experience to stores. Benefits include free delivery and shipping, a 'Spend Analytics” feature, special discounts, deals and tax-exempt shopping.
Special TechSoup offer for a free 180 days membership, and up to $150 in discounts on eligible orders.
Spark Good (walmart.com/sparkgood) is a charitable platform that enables nonprofits to receive donations directly from customers and associates.
Answers about how you can do more with Walmart!"
How to Make a Field Mandatory in Odoo 17Celine George
In Odoo, making a field required can be done through both Python code and XML views. When you set the required attribute to True in Python code, it makes the field required across all views where it's used. Conversely, when you set the required attribute in XML views, it makes the field required only in the context of that particular view.
ISO/IEC 27001, ISO/IEC 42001, and GDPR: Best Practices for Implementation and...PECB
Denis is a dynamic and results-driven Chief Information Officer (CIO) with a distinguished career spanning information systems analysis and technical project management. With a proven track record of spearheading the design and delivery of cutting-edge Information Management solutions, he has consistently elevated business operations, streamlined reporting functions, and maximized process efficiency.
Certified as an ISO/IEC 27001: Information Security Management Systems (ISMS) Lead Implementer, Data Protection Officer, and Cyber Risks Analyst, Denis brings a heightened focus on data security, privacy, and cyber resilience to every endeavor.
His expertise extends across a diverse spectrum of reporting, database, and web development applications, underpinned by an exceptional grasp of data storage and virtualization technologies. His proficiency in application testing, database administration, and data cleansing ensures seamless execution of complex projects.
What sets Denis apart is his comprehensive understanding of Business and Systems Analysis technologies, honed through involvement in all phases of the Software Development Lifecycle (SDLC). From meticulous requirements gathering to precise analysis, innovative design, rigorous development, thorough testing, and successful implementation, he has consistently delivered exceptional results.
Throughout his career, he has taken on multifaceted roles, from leading technical project management teams to owning solutions that drive operational excellence. His conscientious and proactive approach is unwavering, whether he is working independently or collaboratively within a team. His ability to connect with colleagues on a personal level underscores his commitment to fostering a harmonious and productive workplace environment.
Date: May 29, 2024
Tags: Information Security, ISO/IEC 27001, ISO/IEC 42001, Artificial Intelligence, GDPR
-------------------------------------------------------------------------------
Find out more about ISO training and certification services
Training: ISO/IEC 27001 Information Security Management System - EN | PECB
ISO/IEC 42001 Artificial Intelligence Management System - EN | PECB
General Data Protection Regulation (GDPR) - Training Courses - EN | PECB
Webinars: https://pecb.com/webinars
Article: https://pecb.com/article
-------------------------------------------------------------------------------
For more information about PECB:
Website: https://pecb.com/
LinkedIn: https://www.linkedin.com/company/pecb/
Facebook: https://www.facebook.com/PECBInternational/
Slideshare: http://www.slideshare.net/PECBCERTIFICATION
हिंदी वर्णमाला पीपीटी, hindi alphabet PPT presentation, hindi varnamala PPT, Hindi Varnamala pdf, हिंदी स्वर, हिंदी व्यंजन, sikhiye hindi varnmala, dr. mulla adam ali, hindi language and literature, hindi alphabet with drawing, hindi alphabet pdf, hindi varnamala for childrens, hindi language, hindi varnamala practice for kids, https://www.drmullaadamali.com
How to Build a Module in Odoo 17 Using the Scaffold MethodCeline George
Odoo provides an option for creating a module by using a single line command. By using this command the user can make a whole structure of a module. It is very easy for a beginner to make a module. There is no need to make each file manually. This slide will show how to create a module using the scaffold method.
How to Build a Module in Odoo 17 Using the Scaffold Method
IB Chemistry on ICT, 3D software, Jmol, Rasmol and Pymol for Internal Assessment
1. Measure number H2 bonds
Measure bond length/angle
Measure bond strength
Similarity/diff in enzyme/DNA structure diff (species)
Protein 1, 2 , 3O structure
Presence of disulfide bond
Presence alpha and beta pleated sheet
Organic softwarefor 3D model
Click here download Rasmol Click here download PyMolClick here download ACD Click here download Jmol Click here Chem EDDL
Click here ChemDraw editor
Click here download(Accelrys)
Click here chemical search.
Click here CRC database Click here RSC Databooklet
Modelling and 3D representation
Chemistry Database
Click here Spectra database(OhioState) Click here Spectra database (NIST)
Click here chem finder.
Spectroscopic Database
Click here download Swiss PDB Viewer
Modelling and 3D representation
Click here crystallography database.
✓ ✓
2. Measure number H2 bonds
Measure bond length/angle
Measure bond strength
Similarity/diff in enzyme/DNA structure diff (species)
Protein 1, 2 , 3O structure
Presence of disulfide bond
Presence alpha and beta pleated sheet
Click here J mol protein video
Type PDB code – 1BOU
Right click – select console
Select all
Colour gray
Select 39-46
Colour blue
Right click
Select proteins – by residue name – cyc
Right click – Style – scheme –ball stick
Right click – Select all
Zoom in
Measure distanceusing ruler bet cyc
Chemical viewer 3D structure (Jmol)
Uses molecular modelling
1
J mol executable file
Console
Type in above
Measure distance
final product
final product
J mol executable file
1
Designing CH3COOH molecule
Open model kit
Drag to bond – choose carbon
Drag to bond – choose oxygen
Choose double bond – cursor center
Model kit – Minimize structure
Choose ruler for measurement
Measure bond length C = O
Measure bond length C - O
Model kit to
design molecule
Click here J mol tutorial
2
2
3
4
3
4
Click here J mol download
3. Measure number H2 bonds
Measure bond length/angle
Measure bond strength
Similarity/diff in enzyme/DNA structure diff (species)
Protein 1, 2 , 3O structure
Presence of disulfide bond
Presence alpha and beta pleated sheet
J mol executable file
Type -PDB ID - 4 letter code to J mol
Protein Data Bank
Protein database key in - PDB 4 letter code
Click here - List all pdb source
Click here J mol tutorial
Minimise structure– (most stable form)
Model kit – press minimise
Click here J mol download
1
2
3
Click here - List all pdb insulin
H bonds
Bond length/angle
Uses molecular modelling
Model kit to
design molecule
Measure
distance/angle
4
Get structure from
PDB and MOL
Right click to get console
1
2
3
Chemical viewer 3D structure (Jmol)
Click here for pdb files
4
4. Measure number H2 bonds
Measure bond length/angle
Measure bond strength
Similarity/diff in enzyme/DNA structure diff (species)
Protein 1, 2 , 3O structure
Presence of disulfide bond
Presence alpha and beta pleated sheet
Organic softwarefor 3D model (Pymol)
download pdb file text
1
1
Click here - Protein Data Bank
Protein database key in - PDB 4 letter code
3
Click here download PyMol
Click here Pymol video tutorialClick here Pymol video tutorial
Click file – open your download pdb file
from Protein Data bank
Get to command term – Type fetch 3CSY
H - Hide – S - Show cartoon – C – Type by ss
Distance bet 2 atoms
Click here for pdb files
2
Press S – sequence at bottom screen.
Right click – zoom in
Select amino acid 1 – 60 by dragging
Look 3CSY – H – hide everything
Look sele – S – Show stick
Wizard – Measure – select 2 atom measure distance – done
Look sele – A – action – find polar contact to any atom – yellow bond
4
Uses molecular modelling
2
3
5. Measure number H2 bonds
Measure bond length/angle
Measure bond strength
Similarity/diff in enzyme/DNA structure diff (species)
Protein 1, 2 , 3O structure
Presence of disulfide bond
Presence alpha and beta pleated sheet
Organic softwarefor 3D model (Rasmol)
Click here resources Rasmol
Click here download Rasmol
RasMol - exploring structure of molecules.
Stored in a PDB. (Protein Data Bank) file
Go to File > Open, look PDB file you want
download pdb file text
3
1
4
Click on file – open your download pdb file
from Protein Data bank - (3B6F)
5
Open file – 3B6F
Command term – type - restrict dna – colour blue
Select – setting – pick distance – measure distance bet 2 atoms
Rasmol command term
Click here to view command terms
6
Click here - Protein Data Bank
Protein database key in - PDB 3B6F
2
Press setting – pick bond distance and angle
Zoom in – press shift and left click
Select distance atoms and angles to measure
Command term – type hbonds 50 – colour red
Uses molecular modelling
3
Click here for pdb files
6. Measure number H2 bonds
Measure bond length/angle
Measure bond strength
Similarity/diff in enzyme/DNA structure diff (species)
Protein 1, 2 , 3O structure
Presence of disulfide bond
Presence alpha and beta pleated sheet
Organic softwarefor 3D model (ACD Lab)
Click here download ACD Lab
Finish product in 3D viewer
Uses molecular modelling
1
Draw chloromethane
Press copy to 3D or press 3D viewer
Measure C – CI bond length/ H – C – CI bond angle
Press 3D Optimizationbefore measurement
Compareit to J mol
Compareit to CRC Data booklet
Compareit to Chem EDDL
Compute the average bond length /angle H - C - CI
Measure distance Measure distanceSelect atom
1
Draw chlorobenzene
Press copy to 3D or press 3D viewer
Measure C – CI bond length/ bond angle
Press optimizationbefore measurement
Compareit to J mol
Compareit to CRC Data booklet
Compareit to Chem EDDL
Compute the average bond length /angle
Finish product in 3D viewer
22
33
7. Measure number H2 bonds
Measure bond length/angle
Measure bond strength
Similarity/diff in enzyme/DNA structure diff (species)
Protein 1, 2 , 3O structure
Presence of disulfide bond
Presence alpha and beta pleated sheet
Click here download ACD Lab
Finish product in 3D viewer
Uses molecular modelling
1
Select tools
Generate structurefrom
SMILES and InChI
Paste it from Protein databank
Measure distance Measure bond angleSelect tools – generate structure from SMILES/InChI
Draw chlorobenzene
Press copy to 3D or press 3D viewer
Measure C – CI bond length/ bond angle
Press optimizationbefore measurement
Compareit to J mol
Compareit to CRC Data booklet
Compareit to Chem EDDL
Compute the average bond length /angle
Finish product in 3D viewer
Structure from SMILES
Structure from InChI
Click here to get in Protein Databank
Select tools
Calculateall properties
2
3
Generate 3D view
Press 3D Optimization bef measure bond length
1
Organic softwarefor 3D model (ACD Lab)
2
3
8. Possible ResearchQuestion
Data Collection from 3D modelling (4ECC)
Bond angle Jmol Pymol Rasmol ACD Lab Average
∠CF4 109.013 109.011 109.021 109.021 109.012
∠CCI4 109.011 109.032 109.022 109.031 109.021
∠CBr4 109.021 109.011 109.021 109.021 109.013
∠CI4 109.011 109.021 109.011 109.011 109.110
Data Collection from Database (4ECC)
Bond angle CRC RSC Chemspi Chemfind Average
∠CF4 109.011 109.012 109.023 109.012 109.011
∠CCI4 109.011 109.012 109.012 109.031 109.013
∠CBr4 109.011 109.012 109.011 109.024 109.011
∠CI4 109.011 109.022 109.012 109.011 109.120
vs
Data Collection using 3D modelling
Data Collection using Database
Click here Jmol Click here PyMol
Click here RasmolClick here ACD
How element with diff EN affect bond angle/length
How double bond C=O affect bond angle/length
Will size/EN of substituted gp affect bond angle
Will diff/bulky alkyl substituted gp affect bond angle
How lone pair electron affect bond angle
VSEPR
- Factoraffectingbond angle for 3/4/5/6 electron charged center
- How EN/size/type alkyl gp substituent, double bond
or number lone pair electrons (1 or 2) affect bond angle
..
ECC = 3
ECC = 4
..
..
..
..
ECC = 5
..
Bond angle Jmol Pymol Rasmol ACD Lab Average
∠F2O 103.013 103.011 103.021 103.021 103.012
∠CI2O 110.011 110.032 110.022 110.031 110.021
∠Br2O 111.021 111.011 111.021 111.021 111.013
∠I2O 111.011 111.021 112.011 112.011 112.111
Bond angle CRC RSC Chemspi Chemfind Average
∠F2O 103.011 103.010 103.011 103.022 103.011
∠CI2O 110.021 110.022 110.022 110.031 110.022
∠Br2O 111.011 111.012 111.011 111.012 111.012
∠I2O 111.012 111.011 112.012 112.012 112.102
F
׀
F - C – F
׀
F
O
F F
CI
׀
CI - C – CI
׀
CI
O
CI CI
9. Possible ResearchQuestion Data Collection using 3D modelling
Data Collection using Database
Click here Jmol Click here PyMol
Click here RasmolClick here ACD
How element with diff EN affect bond angle/length
How double bond C=O affect bond angle/length
Will size/EN of substituted gp affect bond angle
Will diff/bulky alkyl substituted gp affect bond angle
How lone pair electron affect bond angle
..
ECC = 3
ECC = 4
..
..
..
..
ECC = 5
..
Evaluationand Limitationusing 3D modelling
Must use a variety of sources/programmeto verify/validatethe validity and reliability of data collected
Average is computedfrom diff software and checked with databaseto confirm.
Check on methodological limitationusing 3D model. (MUST perform 3D Optimization to most stable form structure.
Criticaland skeptical of result produced by computationalchemistry.
Major limitationof computation,they assume non-interactingmolecule. (Ideal situation, ex molecule in vacuum or isolated state)
Most appropriatemolecule are those whose coordinates are not theoreticalbut derive from experimentalstructuraldetermination
(using X ray diffraction)
Be carefulof predicted arrangement from simulation /3D model
Datasources are supported using diff method/3D model/database
Certain databaselike NIST and CRC are more reliable source
Check if there is a good agreement bet CRC, diff databases and 3D model predictionbefore making conclusion
Computation programmeis always based on approximationand we cannot conclusive prove anything
Reflect of validity and reliability of data
Is model a true representation of reality?
VSEPR
- Factoraffectingbond angle for 3/4/5/6 electron charged center
- How EN/size/type alkyl gp substituent, double bond
or number lone pair electrons (1 or 2) affect bond angle
10. Bond angle
104.5°
B C SO
F
F
F
H
H O O
O
C
O
O
O
B X
F
F
F
C
H
H
x
x
O S
O O
C
O
x
x
O
2-
2-
O
x
x
:
||
BF3 CH2O SO3 CO3
2-
= =
ECC = 3
3 bond pair
Bond angle
120° Trigonal
planar
✓
E
L
E
C
T
R
O
N
C
H
A
R
G
E
C
E
N
T
E
R
O3
O
O O
:
O
O
:
O
NO2
N
OO
N
OO
NO2
-
N
OO
:
N
OO
:
SO2
OO
-
-
S
:
S
OO :
ECC = 3
2 bond pair
1 lone pair
Bent ✓
Equal repulsion
Electron
Distribution
(TRIGONAL PLANAR)
Unequal repulsion
Electron
Distribution
(TRIGONAL PLANAR)
How element with diff EN affect bond angle/length
How double bond C=O affect bond angle/length
Will size/EN of substituted gp affect bond angle
Will diff/bulky alkyl substituted gp affect bond angle
How lone pair electron affect bond angle
Possible ResearchQuestion (VSEPR)
Factoraffecting bond angle for 3 electroncharged center?
Is it EN/size/type alkyl gp substituent, double bond or number lone pair electrons (1 or 2)
:
11. How element with diff EN affect bond angle/length
How double bond C=O affect bond angle/length
Will size/EN of substituted gp affect bond angle
Will diff/bulky alkyl substituted gp affect bond angle
How lone pair electron affect bond angle
Bond angle
109.5°
Bond angle
104.5°
O
Bond angle
107°
Tetrahedral
Trigonal
Pyrimidal
N
H
N
:
O
SO3
2-PH3NH3
O
HH
H2O
O
F2O
F F
S
CICI
SCI2
N
H H
NH2
- -
Bent
CIO3
-
H H
P
H H H
H
H
H
P
H
H
H
:
O O
S
O
S
O
:
O
2-
2-
CI
O
OO
CI
:
O
O
-
:
CH4
C
H
NH4
+ BH4
- PCI4
+
H
H
H
H
C
H
H
H
N
H
H H
H
H
N
H
H
H
H
B
HH H
H
B
H
H
H
CI
CI
CI
CI
P
CI
CI
CI
P
CI
-
-
+
+
+
+
::
:
::
::
: :
::
:
:
:
:
:
Lone
Pair
Bonding
Pair
E
L
E
C
T
R
O
N
C
H
A
R
G
E
C
E
N
T
E
R
2 bond pair
2 lone pair
ECC = 4
3 bond pair
1 lone pair
✓
ECC = 4
4 bond pair
✓
-
✓
Unequal repulsion
Unequal repulsion
Electron
Distribution
(TETRAHEDRAL)
Equal repulsion
Electron
Distribution
(TETRAHEDRAL)
Factoraffecting bond angle for 4 electroncharged center?
Is it EN/size/type alkyl gp substituent, double bond or number lone pair electrons (1 or 2)
:
12.
Bond angle
180° Linear
Bond angle
<90°
T shape
Bond angle
< 90° , < 120°
Trigonal
Bipyrimidal
Bond angle
90° , 120°
P CI
CI
CI
CI
CI
S
F
F
F
F
Te
CI
CI
CI
CI
CI
F
F
F
CI
F
F
F
I
CI
CI
CI
CI
I
CI
CI
I
F
F
F
F
Xe
F
F
O
O
+
I
I
I
Xe
CI
CI
I
F
F
:
::
:
::
:
::
::
:
::
:
::
:
::
::
::
::
::
::
::
::
::
: : :
BrF
F
F
Br
F
F
F
: :
:
: :
:
::
:
-
PCI5
SF4 TeCI4 (IF4)+ XeO2F2
(I3)-
(ICI2)- XeF2
-
Bonding
Pair
Lone
Pair
E
L
E
C
T
R
O
N
C
H
A
R
G
E
C
E
N
T
E
R
:
:
:
:
ECC = 5
5 bond pair
✓
ECC = 5
4 bond pair
1 lone pair
Seesaw ✓
ECC = 5
3 bond pair
2 lone pair
✓
ECC = 5
2 bond pair
3 lone pair
F
F Xe
F
F
Xe
F
F
::
:
::
::
::
+
+
✓
Equal repulsion
Unequal repulsion
Unequal repulsion
Electron Distribution
(TRIGONAL BIPYRIMIDAL)
Electron Distribution
(TRIGONAL BIPYRIMIDAL)
How element with diff EN affect bond angle/length
How double bond C=O affect bond angle/length
Will size/EN of substituted gp affect bond angle
Will diff/bulky alkyl substituted gp affect bond angle
How lone pair electron affect bond angle
Factoraffecting bond angle for 5 electroncharged center?
Is it EN/size/type alkyl gp substituent, double bond or number lone pair electrons (1 or 2)
:
13. Linear
Square planar
F
S
SF6
F
F
F
F
F
PCI6
-
P
CI
CI
CI
CI
CI
CI
IF5O
I
O
||
F
F
F
F
F
Square pyrimidal
CI
Sb
CI
CICI
CI
(SbCI5)2- BrF5
Xe
F
FF
F
Xe
XeF4
F
F
F
Br
F
FF
F
O
Xe
|| F
FF
F
F
Te
F
FF
F
XeOF4 (TeF5)-
-
CICI
I
CICI
(ICI4)- -
2-
:
-
Lone
Pair
Bonding
Pair
::
::
:
::::
::::
:
: :
:
:
:
:
:
:
:
::
::
:
(XeF3) -
F
(XeF2)2-
F
F
Xe
E
L
E
C
T
R
O
N
C
H
A
R
G
E
C
E
N
T
E
R
Lone pair in equatorial first, then axial
Lone pair in equatorial first, then axial
:
:
:
:
-
2-
Minimise repulsion
Minimise repulsion
ECC = 6
6 bond pair
Bond angle
90° Octahedral ✓
ECC = 6
5 bond pair
1 lone pair
Bond angle
< 90° ✓
4 bond pair
2 lone pair
✓
3 bond pair
3 lone pair
T shape ✓
2 bond pair
4 lone pair
Bond angle
180°
✓
Equal repulsion
Unequal repulsion
Bond angle
90°
Electron Distribution
(OCTAHEDRAL)
Electron Distribution
(OCTAHEDRAL)
Unequal repulsion
Electron Distribution
(OCTAHEDRAL)
Factoraffecting bond angle for 6 electroncharged center?
Is it EN/size/type alkyl gp substituent, double bond or number lone pair electrons (1 or 2)
How element with diff EN affect bond angle/length
How double bond C=O affect bond angle/length
Will size/EN of substituted gp affect bond angle
Will diff/bulky alkyl substituted gp affect bond angle
How lone pair electron affect bond angle
Bond angle
< 90°
:
:
14. Valence Shell Electron Pair Repulsion
Predict molecular shape/geometry Shape determine by electron pair/
electron charge centers/ECC
Bonding/lone pair – repel each other
Bonding/lone pair arrangethemselves as far as possible
(minimise repulsion)
Valence
Shell
Electron
Pair
Repulsion
N
H
HH
..
Principles of VSEPR
Shape of molecule
Determinenumber valence e around centralatom1
2 Single, double, triple bond , lone pair act as ECC
3
4 Lone pair-lonepair > Lone pair-bondingpair >
bonding pair- bonding pair repulsion
5
6 ECC or electron pair position in equatorialfirst, then axial
Lewis structure
VSEPR
..
N
H
H
H
Geometry
4 ECC
3 bonding pair
1 lone pair
Trigonal pyrimidal
1
2
3
Bond pair electron
• Occupy smaller region
space bet nuclei
• Repulsion less
Lone pair electron
nucleus
>
Bonding pair electron
Concept Map
nuclei
Lone pair electron
• Electron pair occupy
greater space
• Repel any bonding pair nearby
• Lone pair repulsion > bonding pair repulsion
Double bond
•Repulsion greater
•Angle smaller, 111.4°
B
F
F
F
Single bond
•Equal repulsion
•Angle 120°
120°
120°
120°
space occupy
by electron
space occupy
by electron
15. ValenceShell Electron Pair Repulsion
Bonding/lone pair arrangethemselves as far as possible
(minimise repulsion)
Principles of VSEPR
Determinenumber valence e around centralatom1
2 Single, double, triple bond , lone pair act as ECC
3 Bonding/lone pair repel each other
Lone /lone pair > Lone /bond pair > bond/bond pair repulsion
4
5
For 5/6 ECC: lone pair in equatorial first, then axial
..
N
HHH
3 bonding pair
1 lone pair
4 ECCN – central atom
3 ECC
C
H
=O
H
2 ECC
O
H H
4 ECC
> >
1 lone pair2 lone pair 0 lone pair
Repulsion greater - Bond angle smaller
Repulsion
greater
Repulsion
greater
✓
ECC far apart – Bond angle greatest – minimise repulsion
6
Lone pair need more space
Multiple bonds more space
Unequal repulsionEqual repulsion
90°
120°
109.5°
107°
180°
H – C ≡ N