SCATTER PLOT IN EXCEL

                          << Some Introduction >>

 

                                                           SCATTER PLOT IN EXCEL

Objectives

• Enter and format data in an Excel spreadsheet in a form appropriate for graphing
• Create a scatter plot from spreadsheet data
• Insert a linear regression line (trendline) into the scatter plot
• Use the slope/intercept formula for the regression line to calculate a x value for a known y value
• Explore curve fitting to scatterplot data
• Create a connected point (line) graph
• Place a reference line in a graph 

                                                       LINEAR REGRESSION

In statistics, linear regression is an approach to modeling the relationship between a scalar variable y and one or more variables denoted X. In linear regression, models of the unknown parameters are estimated from the data using linear functions. Such models are called linear models. Most commonly, linear regression refers to a model in which the conditional mean of y given the value of X is an affine function of X. Less commonly, linear regression could refer to a model in which the median, or some other quantile of the conditional distribution of y given X is expressed as a linear function of X. Like all forms of regression analysis, linear regression focuses on the conditional probability distribution of y given X, rather than on the joint probability distribution of y and X, which is the domain of multivariate analysis.

                                                                           

                           Part 1 - Beer's Law Scatter Plot and Linear Regression

                                             Part 2 - Titration Data Plotting

ü 

ü                                                                               Finding the line of best fit

                                                      Quadratic regression

 

..::SMILE::..

''smile is sadaqah''

The simplified molecular input line entry specification or SMILES is a specification for unambiguously describing the structure of chemical molecules using short ASCII strings. SMILES strings can be imported by most molecule editors for conversion back into two-dimensionalthree-dimensional models of the molecules. drawings or

The original SMILES specification was developed by Arthur Weininger and David Weininger in the late 1980s. It has since been modified and extended by others, most notably by Daylight Chemical Information Systems Inc. In 2007, an open standard called "OpenSMILES" was developed by the Blue Obelisk open-source chemistry community. Other 'linear' notations include the Wiswesser Line Notation (WLN), ROSDAL and SLN (Tripos Inc).

In July 2006, the IUPAC introduced the InChI as a standard for formula representation. SMILES is generally considered to have the advantage of being slightly more human-readable than InChI; it also has a wide base of software support with extensive theoretical (e.g., graph theory) backing.

ADVANTAGE:

SMILES requires no special constructs, nor any special data type. Every character in it is part of the original specification of the American Standard Code for Information Interchange. A SMILES structure can reside in a database as a "varying character" or "string" data type. Moreover, any plain-text editor can produce a SMILES structure. 

MORE ABOUT SMILE:

SMILES contains the same information as might be found in an extended connection table. The primary reason SMILES is more useful than a connection table is that it is a linguistic construct, rather than a computer data structure. SMILES is a true language, albeit with a simple vocabulary (atom and bond symbols) and only a few grammar rules. SMILES representations of structure can in turn be used as "words" in the vocabulary of other languages designed for storage of chemical information (information about chemicals) and chemical intelligence (information about chemistry).

Part of the power of SMILES is that unique SMILES exist. With standard SMILES, the name of a molecule is synonymous with its structure; with unique SMILES, the name is universal. Anyone in the world who uses unique SMILES to name a molecule will choose the exact same name.

One other important property of SMILES is that it is quite compact compared to most other methods of representing structure. A typical SMILES will take 50% to 70% less space than an equivalent connection table, even binary connection tables. For example, a database of 23,137 structures, with an average of 20 atoms per structure, uses only 1.6 bytes per atom when represented with SMILES. In addition, ordinary compression of SMILES is extremely effective. The same database cited above was reduced to 27% of its original size by Ziv-Lempel compression (i.e. 0.42 bytes per atom).

These properties open many doors to the chemical information programmer. Examples of uses for SMILES are:

• Keys for database access
• Mechanism for researchers to exchange chemical information
• Entry system for chemical data
• Part of languages for artificial intelligence or expert systems in chemistry 

                           Example of SMILES:

SMILES^TM as a simple yet comprehensive chemical language in which molecules and reactions can be specified using ASCII characters representing atom and bond symbols. SMILES^TM contains the same information as is found in an extended connection table but with several advantages. A SMILES^TM string is human understandable, very compact, and if canonicalized represents a unique string that can be used as a universal identifier for a specific chemical structure. In addition, a chemically correct and comprehensible depiction can be made from any SMILES^TM string symbolizing either a molecule or reaction.

SMILES^TM development was initiated by David Weininger in the late 1980s using the concept of a graph with nodes as atoms and edges as bonds to represent a molecule. Parentheses are used to indicate branching points and numeric labels designate ring connection points. The basic SMILES^TM grammar also includes as well as isotopic information, configuration about double bonds, and chirality leading to what is known as isomeric SMILES^TM.

Some simple SMILES^TM examples:

Ethanol	CCO
Acetic acid	CC(=O)O
Cyclohexane	C1CCCCC1
Pyridine	c1cnccc1
Trans-2-butene	C/C=C/C
L-alanine	N[C@@H](C)C(=O)O
Sodium chloride	[Na+].[Cl-]
Displacement reaction	C=CCBr>>C=CCI

    Since its inception, SMILES^TM has been modified and expanded by Daylight to include not only new features but two additional chemical languages: SMARTS^®, an expansion of SMILES^TM allowing specification of molecular patterns and properties for substructure searching with varying levels of specificity, and SMIRKS^®, a restricted version of reaction SMARTS^® involving changes in atom-bond patterns that define generic reactions.

There are my work..enjoy it..and smile always..

......::::PROTEIN DATA BANK::::....

                         assalamualaikum..

alhamdulilah,ALLAH know better.I'm trying hardly to do the best.For the sake of ummah,lets purify our heart learning something new so that can be practised soon for beneficial and halal purpose.    

''Innama a'mal binniat'' 

                          PROTEIN DNA BANK               

                              Introduction

What is PDB?

(1) The PDB is the Protein Data Bank, a single worlwide repository for 3D structural data of biological molecules.

(2) A PDB is a file, typically with a "pdb" file extension, contains 3D structural data of a particular biological molecule. In short, a PDB file is broken into two sections: (i) a header that contains much background information on the molecule in question such as authors and experimental conditions, (ii) 3D coordinate data that contain the vital experimental data in the form of 3D cartesian coordinates, B-factors, atom information, and more.

 .......::::colour for mission

           PROTEIN DATA BANK::::.....

 

                         How can PDB's be visualized?

     Protein Data Bank files, containing some form of macromolecular coordinate set, are visualized via graphic computing. A myriad of advanced molecular visualization programs are used in academic and industrial setting, and some of these are specific to the field of research or the techniques used to collect the coordinate data. For example, X-ray crystallographers use O, XtalView, MAIN, or other programs for crystallographic modeling. These allow the researcher to model the coordinate set into the electron density from the collected X-ray data.

However, PDB files are "final" deposited coordinates. This means that the depositor has made their best effort to provide a final model that is as accurate as they could make it. Programs like Molscript, Pymol, SwissPDBview/DeepView, Molmol, SETOR, DINO and others are routinely used to visualize deposited coordinates.

In order to produce molecular graphics, one requires the following: graphics workstation computer, some form of molecular graphics software, and most importantly, training.

Symmation has been formally trained in X-ray crystallography and bioinformatics. We have the software and computer equipment, aside from our 8 years of experience. We are able to provide a complete solution to molecular graphics visualization that includes raw data interpretation, remodeling, refinement, structure analysis, and of course publication-quality graphics.

We can reduce your costs of operation, whatever sector you are in. Request information on PDB visualization and read our client testimonials that speak on our expertise!

 SUBTILISIN_3LPA

SIMPLE INFO:

        Subtilisin (serine endopeptidase) is a non-specific protease (a protein-digesting enzyme) initially obtained from Bacillus subtilis.

Subtilisins belong to subtilases, a group of serine proteases that initiate the nucleophilic attack on the peptide (amide) bond through a serine residue at the active site. They are physically and chemically well-characterized enzymes. Subtilisins typically have molecular weights of about 20,000 to 45,000 dalton. They can be obtained from soil bacteria, for example, Bacillus amyloliquefaciens. Subtilisins are secreted in large amounts from many Bacillus species.

Subtilisins are widely used in commercial products, for example, in laundry^[2] and dishwashing detergents, cosmetics, food processing^[3], skin care ointments^[4], contact lens cleaners, and for research purposes in synthetic organic chemistry.

The structure of subtilisin has been determined by X-ray crystallography. It is a 275-residue globular protein with several alpha-helices, and a large beta-sheet. It is structurally unrelated to the chymotrypsin-clan of serine proteases, but uses the same type of catalytic triad in the active site. This makes it the classic example of convergent evolution.

In molecular biology using B. subtilis as a model organism, the gene encoding subtilisin (aprE) is often the second gene of choice after amyE for integrating reporter constructs into, due to its dispensability.

		EXAMPLE:

      PROLYL AMINOPEPTIDASE 3CTZ

                                                                 

                                                  SIMPLE INFO:                                     

Structure of human cytosolic X-prolyl aminopeptidase

Prolyl aminopeptidase from Serratia marcescens specifically catalyzes the removal of N-termlnal proline residues from peptides. We have solved its three-dimensional structure at 2.3 A resolution by the multiple isomorphous replacement method. The enzyme consists of two contiguous domains. The larger domain shows the general topology of the a/0 hydrolase fold, with a central eight-stranded /?-sheet and six helices. The smaller domain consists of six helices. The catalytic triad (SerllS, His296, and Asp268) is located near the large cavity at the interface between the two domains. Cys271, which is sensitive to SH reagents, is located near the catalytic residues, in spite of the fact that the enzyme is a serine peptidase. The specific residues which make up the hydrophobic pocket line the smaller domain, and the specificity of the exo-type enzyme originates from this smaller domain, which blocks the N-terminal of PI proline.

LEX A REPRESSOR             SIMPLE INFO Repressor LexA or LexA is a repressor enzyme (EC 3.4.21.88) that represses SOS response genes coding for DNA polymerases required for repairing DNA damage. LexA is intimately linked to RecA in the biochemical cycle of DNA damage and repair. RecA binds to DNA-bound LexA causing LexA to cleave itself in a process called autoproteolysis. DNA damage can be inflicted by the action of antibiotics. Bacteria require topoisomerases such as DNA gyrase or topoisomerase IV for DNA replication. Antibiotics such as ciprofloxacin are able to prevent the action of these molecules by attaching themselves to the gyrase - DNA complex. This is counteracted by the polymerase repair molecules from the SOS response. Unfortunately the action is partly counterproductive because ciprofloxacin is also involved in the synthetic pathway to RecA type molecules which means that the bacteria responds to an antibiotic by starting to produce more repair proteins. These repair proteins can lead to eventual benevolent mutations which can render the bacteria resistant to ciprofloxacin. Mutations are traditionally thought of as happening as a random process and as a liability to the organism. Many strategies exist in a cell to curb the rate of mutations. Mutations on the other hand can also be part of a survival strategy. For the bacteria under attack from an antibiotic, mutations help to develop the right biochemistry needed for defense. Certain polymerases in the SOS pathway are error-prone in their copying of DNA which leads to mutations. While these mutations are often lethal to the cell, they can also lead to mutations which improve the bacteria's survival. In the specific case of topoisomerases, some bacteria have mutated one of their amino acids so that the ciproflaxin can only create a weak bond to the topoisomerase. This is one of the methods that bacteria use to become resistant to antibiotics. Impaired LexA proteolysis has been shown to interfere with ciprofloxacin resistance.[1] This offers potential for combination therapy that combine quinolones with strategies aimed at interfering with the action of LexA either directly, or via RecA.

LInk:

http://www.symmation.com/content/protein-data-bank.php http://jb.oxfordjournals.org/content/126/3/559.full.pdf    http://www.rcsb.org/pdb/results/results.do?outformat=&qrid=33BF0382&tabtoshow=Current