Through this Presentation YOUNG RESEARCHERS could understand the sequencing of peptide molecules(de-novo sequencing) using tandem mass spectrometric data manually.
De novo peptide sequencing is performed without prior knowledge of the amino acid sequence. It uses computational approaches to deduce the peptide sequence directly from mass spectrometry spectra. The main principle is to use mass differences between fragment ions like y and b ions to calculate amino acid residues. While it can identify previously unknown sequences, there is uncertainty in the complete sequence and difficulty determining directionality sometimes. Creative Proteomics offers de novo sequencing services using high-performance mass spectrometry and computational algorithms.
The document discusses the field of proteomics, which is the large-scale study of proteins, including their functions and structures. It defines proteomics and describes several areas within it, such as functional proteomics, expressional proteomics, and structural proteomics. It outlines typical proteomics experiments and some key methods used, including two-dimensional electrophoresis, mass spectrometry, and protein-protein interaction prediction methods like phylogenetic profiling.
Homology modeling is a technique used to predict the 3D structure of a protein based on the alignment of its amino acid sequence to known protein structures. It relies on the observation that structure is more conserved than sequence during evolution. The key steps in homology modeling include: 1) identifying a template structure through sequence alignment tools like BLAST, 2) correcting any errors in the initial alignment, 3) generating the protein backbone based on the template structure, 4) modeling any loops or missing regions, 5) adding side chains, 6) optimizing the model structure energetically, and 7) validating that the final model matches the template structure and has correct stereochemistry. Homology modeling is useful for applications like structure-based drug design
1) Pairwise sequence alignment is a method to compare two biological sequences like DNA, RNA, or proteins. It involves arranging the sequences in columns to highlight their similarities and differences.
2) There are many possible alignments between two sequences, but most imply too many mutations. The best alignment minimizes the number of mutations needed to explain the differences between the sequences.
3) For short protein sequences like "QKGSYPVRSTC" and "QKGSGPVRSTC", the optimal alignment implies one single mutation occurred since the sequences diverged from a common ancestor.
Comparative genomics involves comparing genomes to discover similarities and differences. It can provide insights into evolutionary relationships, help predict gene function, and aid in drug discovery. The first step is often aligning genome sequences using tools like BLAST or MUMmer. Genomes can then be compared at various levels, such as overall nucleotide statistics, genome structure, and coding/non-coding regions. Comparing gene and protein content across genomes helps predict functions. Conserved genomic features across species also aid prediction. Insights into genome evolution come from studying molecular events like inversions and duplications. Comparative genomics has impacted phylogenetics and drug target identification.
This document discusses sequence alignment methods. It describes global and local alignment, and algorithms used for alignment including dot matrix analysis, dynamic programming, and word/k-tuple methods as implemented in FASTA and BLAST programs. BLAST and FASTA are described as popular tools for sequence database searches that use heuristic methods and word matching to quickly identify regions of local similarity.
De novo peptide sequencing is performed without prior knowledge of the amino acid sequence. It uses computational approaches to deduce the peptide sequence directly from mass spectrometry spectra. The main principle is to use mass differences between fragment ions like y and b ions to calculate amino acid residues. While it can identify previously unknown sequences, there is uncertainty in the complete sequence and difficulty determining directionality sometimes. Creative Proteomics offers de novo sequencing services using high-performance mass spectrometry and computational algorithms.
The document discusses the field of proteomics, which is the large-scale study of proteins, including their functions and structures. It defines proteomics and describes several areas within it, such as functional proteomics, expressional proteomics, and structural proteomics. It outlines typical proteomics experiments and some key methods used, including two-dimensional electrophoresis, mass spectrometry, and protein-protein interaction prediction methods like phylogenetic profiling.
Homology modeling is a technique used to predict the 3D structure of a protein based on the alignment of its amino acid sequence to known protein structures. It relies on the observation that structure is more conserved than sequence during evolution. The key steps in homology modeling include: 1) identifying a template structure through sequence alignment tools like BLAST, 2) correcting any errors in the initial alignment, 3) generating the protein backbone based on the template structure, 4) modeling any loops or missing regions, 5) adding side chains, 6) optimizing the model structure energetically, and 7) validating that the final model matches the template structure and has correct stereochemistry. Homology modeling is useful for applications like structure-based drug design
1) Pairwise sequence alignment is a method to compare two biological sequences like DNA, RNA, or proteins. It involves arranging the sequences in columns to highlight their similarities and differences.
2) There are many possible alignments between two sequences, but most imply too many mutations. The best alignment minimizes the number of mutations needed to explain the differences between the sequences.
3) For short protein sequences like "QKGSYPVRSTC" and "QKGSGPVRSTC", the optimal alignment implies one single mutation occurred since the sequences diverged from a common ancestor.
Comparative genomics involves comparing genomes to discover similarities and differences. It can provide insights into evolutionary relationships, help predict gene function, and aid in drug discovery. The first step is often aligning genome sequences using tools like BLAST or MUMmer. Genomes can then be compared at various levels, such as overall nucleotide statistics, genome structure, and coding/non-coding regions. Comparing gene and protein content across genomes helps predict functions. Conserved genomic features across species also aid prediction. Insights into genome evolution come from studying molecular events like inversions and duplications. Comparative genomics has impacted phylogenetics and drug target identification.
This document discusses sequence alignment methods. It describes global and local alignment, and algorithms used for alignment including dot matrix analysis, dynamic programming, and word/k-tuple methods as implemented in FASTA and BLAST programs. BLAST and FASTA are described as popular tools for sequence database searches that use heuristic methods and word matching to quickly identify regions of local similarity.
Gene prediction is the process of determining where a coding gene might be in a genomic sequence. Functional proteins must begin with a Start codon (where DNA transcription begins), and end with a Stop codon (where transcription ends).
Proteomics is the study of the structure and function of proteins. It involves identifying and quantifying the proteins expressed by a genome or cell type. Key aspects of proteomics include protein separation techniques like gel electrophoresis, mass spectrometry to identify proteins, and analyzing protein interactions and post-translational modifications. While genomes provide the blueprint, proteomics helps understand the diversity of proteins expressed and how they function together to direct cellular activities. It is a promising tool for disease diagnosis by identifying protein biomarkers.
Protein NMR spectroscopy is a technique that uses the magnetic properties of atomic nuclei to determine the physical and chemical properties of molecules. It provides detailed information about molecular structure, dynamics, reaction state, and chemical environment. NMR spectroscopy is commonly used by chemists and biochemists to investigate organic molecules. It involves placing a sample in a strong magnetic field and exposing it to radiofrequency pulses to determine the number and types of atoms in the molecule. NMR has applications in chemistry for studying chemical bonds and in medicine for imaging tissues and detecting diseases.
Secondary Structure Prediction of proteins Vijay Hemmadi
Secondary structure prediction has been around for almost a quarter of a century. The early methods suffered from a lack of data. Predictions were performed on single sequences rather than families of homologous sequences, and there were relatively few known 3D structures from which to derive parameters. Probably the most famous early methods are those of Chou & Fasman, Garnier, Osguthorbe & Robson (GOR) and Lim. Although the authors originally claimed quite high accuracies (70-80 %), under careful examination, the methods were shown to be only between 56 and 60% accurate (see Kabsch & Sander, 1984 given below). An early problem in secondary structure prediction had been the inclusion of structures used to derive parameters in the set of structures used to assess the accuracy of the method.
Some good references on the subject:
This document discusses multiple sequence alignment techniques. It begins with definitions of key terms like homology, similarity, and conservation. It then describes pairwise alignment and its applications. The rest of the document focuses on multiple sequence alignment methods like progressive alignment, iterative refinement, tree alignment, star alignment, and using genetic algorithms. It provides examples and explanations of popular multiple sequence alignment tools like Clustal W and T-Coffee.
Proteomics 2 d gel, mass spectrometry, maldi tofnirvarna gr
This document discusses proteomics techniques including 2D gel electrophoresis and mass spectrometry. It provides an overview of 2D gel electrophoresis, describing the key steps of sample preparation, running the first and second dimensions, visualizing and analyzing the results. Mass spectrometry techniques for proteomics including MALDI-TOF and electrospray ionization are also summarized. The document outlines several applications of these proteomics approaches such as protein identification, characterization of post-translational modifications, and organism identification.
Frederick Sanger developed two important methods for protein sequencing: 1) using fluorodinitrobenzene to determine the N-terminal amino acid, and 2) cleaving proteins into fragments and piecing their sequences together. The standard strategy involves separating chains, identifying terminal residues, cleaving the protein, sequencing fragments, and reconstructing the full sequence. The Edman degradation method allows sequential removal of residues from the N-terminus. Mass spectrometry techniques like peptide mass fingerprinting and tandem mass spectrometry now dominate protein sequencing.
Protein sequencing determines the order of amino acids in a protein. The two major methods are Edman degradation and mass spectrometry. Edman degradation involves labeling the N-terminal amino acid, cleaving it off, and identifying it, repeating the process one amino acid at a time to deduce the sequence. Mass spectrometry involves ionizing and separating protein fragments by mass/charge ratio to determine sequence. Protein sequencing is useful for identifying unknown proteins and characterizing modifications.
The SCOP database classifies protein structures hierarchically and describes evolutionary relationships between proteins. It was created in 1994 at the Centre for Protein Engineering and is maintained manually. SCOP links to the Protein Data Bank to obtain structural classifications for each protein structure directly and can also be searched to find a protein's structural class, fold, and domain information.
protein structure prediction methods. homology modelling, fold recognition, threading, ab initio methods. in short and easy form slides. after one time read you can easily understand methods for protein structure prediction.
2D-PAGE is a technique used to separate complex protein mixtures based on isoelectric point and molecular weight. It involves two sequential steps - isoelectric focusing and SDS-PAGE. In isoelectric focusing, proteins are separated based on their isoelectric point in an immobilized pH gradient. They are then separated by SDS-PAGE based on their molecular weight. The separated proteins can then be visualized through staining and identified through mass spectrometry. While useful for proteomic analysis, 2D-PAGE has limitations such as low reproducibility and dynamic range.
Data mining involves using machine learning and statistical methods to discover patterns in large datasets and is useful in bioinformatics for analyzing biological data. Bioinformatics analyzes data from sequences, molecules, gene expressions, and pathways. Data mining can help understand these rapidly growing biological datasets. Common data mining tools in bioinformatics include BLAST for sequence comparisons, Entrez for integrated database searching, and ORF Finder for identifying open reading frames. Data mining approaches are well-suited to the enormous volumes of data in bioinformatics databases.
1) The first protein sequencing was achieved in 1953 by Frederic Sanger who determined the amino acid sequence of bovine insulin.
2) Common strategies for protein sequencing include determining the number of subunits, disulfide bonds, amino acid composition, and sequencing fragments using Edman degradation or enzymatic cleavage.
3) Techniques like end-group analysis, solid-phase support, exopeptidases, and mass spectrometry help overcome challenges and complete the protein sequence.
This document provides an overview of several important protein databases:
- SWISS-PROT is an annotated protein sequence database that is maintained collaboratively and contains over 1.29 million entries. TrEMBL is a computer-annotated supplement to SWISS-PROT containing sequences not yet in SWISS-PROT.
- Structural databases like PDB, SCOP, and CATH provide protein structure information. PDB is an international repository for macromolecular structures. SCOP and CATH classify protein domains based on structural similarities and evolutionary relationships.
- Other databases mentioned include InterPro, GOA, Proteome Analysis, and GenBank, which provide functional annotation, gene ontology assignments, proteome analysis
Whole genome shotgun sequencing involves randomly breaking genomic DNA into small fragments, sequencing the fragments, and then reassembling the sequences using overlapping regions. The document outlines the history and procedure of shotgun sequencing. Genomic DNA is first fragmented, end-repaired, and size-selected into small, medium, and large fragments. Libraries are created for each size fragment and sequenced. A base caller filters poor calls and an assembler finds overlaps to generate continuous nucleotide sequences or contigs of the whole genome.
Immunoprecipitation (IP) is a technique used to purify and enrich proteins of interest from a protein mixture using antibodies. The general IP protocol involves incubating a cell lysate sample containing the target protein with antibody-bound beads, washing away non-specifically bound proteins, and then eluting the immunoprecipitated protein off the beads. Key factors that influence IP include the composition of wash and elution buffers, the type of solid support used, antibody specificity and amount, and pre-clearing the lysate sample. Controls like isotype controls and negative controls without antibody help assess the specificity of the IP results.
Proteomics and its applications
Proteomics involves the analysis of the entire complement of proteins in a cell, tissue or organism. It assesses protein activities, modifications, localization and interactions. Proteomics uses techniques like gel electrophoresis, mass spectrometry and liquid chromatography to separate and identify proteins. These techniques can be applied to discover disease biomarkers, develop diagnostic tools, and gain insights into disease pathogenesis and treatment. Proteomics has applications in studying various diseases including cancer, diabetes and infections. It provides insights into cellular processes and systems biology.
Protein microarrays allow high-throughput analysis of protein interactions and functions. They consist of large numbers of capture proteins immobilized on a surface to which labeled probe molecules are added to detect reactions by fluorescence. There are analytical arrays to study protein binding properties and functional arrays containing full-length proteins to assay enzymatic activity and detect antibodies. Protein microarrays have applications in diagnostics, proteomics, analyzing protein interactions and functions, antibody characterization, and treatment development.
A database is a structured collection of data that can be easily accessed, managed, and updated. It consists of files or tables containing records with fields. Database management systems provide functions like controlling access, maintaining integrity, and allowing non-procedural queries. Major databases include GenBank, EMBL, and DDBJ for nucleotide sequences and UniProt, PDB, and Swiss-Prot for proteins. The NCBI maintains many biological databases and provides tools for analysis.
Functional proteomics, methods and toolsKAUSHAL SAHU
INTRODUCTION
HISTORY
DEFINITION
PROTEOMICS
FUNCTIONAL PROTEOMICS
PROTEOMICS SOFTWARE
PROTEOMICS ANALYSIS
TOOLS FOR PROTEOM ANALYSIS
DIFFERENTS METHODS FOR STUDY OF FUNCTIONAL PROTEOMICS
APLLICATIONS
LIMITATIONS
CONCLUSION
Dr. Robert Langer - Simposio Internacional 'Terapias oncológicas avanzadas'Fundación Ramón Areces
Los días 15 y 16 de octubre de 2014, la Fundación Ramón Areces y la Real Academia Nacional de Farmacia, en colaboración con la Fundación de la Innovación Bankinter, reunieron en Madrid a algunos de los mayores expertos mundiales en nuevas terapias contra el cáncer. El Simposio Internacional, coordinado por la profesora y académica María José Alonso, analizó el momento actual de la lucha contra esta enfermedad. También fue un punto de encuentro para científicos de los más innovadores institutos de investigación en oncología, quienes debatieron sobre tres grandes temas: la Medicina Personalizada contra el cáncer, los nanomedicamentos en la terapia del cáncer y las terapias basadas en la inmunomodulación.
Evgeny nikolaev proteomics of body liquids as a source for potential methods ...igorod
The document discusses using mass spectrometry to analyze body fluids like urine, saliva, and exhaled breath condensate for medical diagnostics and biomarker discovery. It describes creating databases of accurate mass tags and retention times from mass spec analyses of peptides and proteins in body fluids to enable fast identification. Biomarkers found for diseases like COPD, pneumonia and changes after lung transplantation are mentioned.
Gene prediction is the process of determining where a coding gene might be in a genomic sequence. Functional proteins must begin with a Start codon (where DNA transcription begins), and end with a Stop codon (where transcription ends).
Proteomics is the study of the structure and function of proteins. It involves identifying and quantifying the proteins expressed by a genome or cell type. Key aspects of proteomics include protein separation techniques like gel electrophoresis, mass spectrometry to identify proteins, and analyzing protein interactions and post-translational modifications. While genomes provide the blueprint, proteomics helps understand the diversity of proteins expressed and how they function together to direct cellular activities. It is a promising tool for disease diagnosis by identifying protein biomarkers.
Protein NMR spectroscopy is a technique that uses the magnetic properties of atomic nuclei to determine the physical and chemical properties of molecules. It provides detailed information about molecular structure, dynamics, reaction state, and chemical environment. NMR spectroscopy is commonly used by chemists and biochemists to investigate organic molecules. It involves placing a sample in a strong magnetic field and exposing it to radiofrequency pulses to determine the number and types of atoms in the molecule. NMR has applications in chemistry for studying chemical bonds and in medicine for imaging tissues and detecting diseases.
Secondary Structure Prediction of proteins Vijay Hemmadi
Secondary structure prediction has been around for almost a quarter of a century. The early methods suffered from a lack of data. Predictions were performed on single sequences rather than families of homologous sequences, and there were relatively few known 3D structures from which to derive parameters. Probably the most famous early methods are those of Chou & Fasman, Garnier, Osguthorbe & Robson (GOR) and Lim. Although the authors originally claimed quite high accuracies (70-80 %), under careful examination, the methods were shown to be only between 56 and 60% accurate (see Kabsch & Sander, 1984 given below). An early problem in secondary structure prediction had been the inclusion of structures used to derive parameters in the set of structures used to assess the accuracy of the method.
Some good references on the subject:
This document discusses multiple sequence alignment techniques. It begins with definitions of key terms like homology, similarity, and conservation. It then describes pairwise alignment and its applications. The rest of the document focuses on multiple sequence alignment methods like progressive alignment, iterative refinement, tree alignment, star alignment, and using genetic algorithms. It provides examples and explanations of popular multiple sequence alignment tools like Clustal W and T-Coffee.
Proteomics 2 d gel, mass spectrometry, maldi tofnirvarna gr
This document discusses proteomics techniques including 2D gel electrophoresis and mass spectrometry. It provides an overview of 2D gel electrophoresis, describing the key steps of sample preparation, running the first and second dimensions, visualizing and analyzing the results. Mass spectrometry techniques for proteomics including MALDI-TOF and electrospray ionization are also summarized. The document outlines several applications of these proteomics approaches such as protein identification, characterization of post-translational modifications, and organism identification.
Frederick Sanger developed two important methods for protein sequencing: 1) using fluorodinitrobenzene to determine the N-terminal amino acid, and 2) cleaving proteins into fragments and piecing their sequences together. The standard strategy involves separating chains, identifying terminal residues, cleaving the protein, sequencing fragments, and reconstructing the full sequence. The Edman degradation method allows sequential removal of residues from the N-terminus. Mass spectrometry techniques like peptide mass fingerprinting and tandem mass spectrometry now dominate protein sequencing.
Protein sequencing determines the order of amino acids in a protein. The two major methods are Edman degradation and mass spectrometry. Edman degradation involves labeling the N-terminal amino acid, cleaving it off, and identifying it, repeating the process one amino acid at a time to deduce the sequence. Mass spectrometry involves ionizing and separating protein fragments by mass/charge ratio to determine sequence. Protein sequencing is useful for identifying unknown proteins and characterizing modifications.
The SCOP database classifies protein structures hierarchically and describes evolutionary relationships between proteins. It was created in 1994 at the Centre for Protein Engineering and is maintained manually. SCOP links to the Protein Data Bank to obtain structural classifications for each protein structure directly and can also be searched to find a protein's structural class, fold, and domain information.
protein structure prediction methods. homology modelling, fold recognition, threading, ab initio methods. in short and easy form slides. after one time read you can easily understand methods for protein structure prediction.
2D-PAGE is a technique used to separate complex protein mixtures based on isoelectric point and molecular weight. It involves two sequential steps - isoelectric focusing and SDS-PAGE. In isoelectric focusing, proteins are separated based on their isoelectric point in an immobilized pH gradient. They are then separated by SDS-PAGE based on their molecular weight. The separated proteins can then be visualized through staining and identified through mass spectrometry. While useful for proteomic analysis, 2D-PAGE has limitations such as low reproducibility and dynamic range.
Data mining involves using machine learning and statistical methods to discover patterns in large datasets and is useful in bioinformatics for analyzing biological data. Bioinformatics analyzes data from sequences, molecules, gene expressions, and pathways. Data mining can help understand these rapidly growing biological datasets. Common data mining tools in bioinformatics include BLAST for sequence comparisons, Entrez for integrated database searching, and ORF Finder for identifying open reading frames. Data mining approaches are well-suited to the enormous volumes of data in bioinformatics databases.
1) The first protein sequencing was achieved in 1953 by Frederic Sanger who determined the amino acid sequence of bovine insulin.
2) Common strategies for protein sequencing include determining the number of subunits, disulfide bonds, amino acid composition, and sequencing fragments using Edman degradation or enzymatic cleavage.
3) Techniques like end-group analysis, solid-phase support, exopeptidases, and mass spectrometry help overcome challenges and complete the protein sequence.
This document provides an overview of several important protein databases:
- SWISS-PROT is an annotated protein sequence database that is maintained collaboratively and contains over 1.29 million entries. TrEMBL is a computer-annotated supplement to SWISS-PROT containing sequences not yet in SWISS-PROT.
- Structural databases like PDB, SCOP, and CATH provide protein structure information. PDB is an international repository for macromolecular structures. SCOP and CATH classify protein domains based on structural similarities and evolutionary relationships.
- Other databases mentioned include InterPro, GOA, Proteome Analysis, and GenBank, which provide functional annotation, gene ontology assignments, proteome analysis
Whole genome shotgun sequencing involves randomly breaking genomic DNA into small fragments, sequencing the fragments, and then reassembling the sequences using overlapping regions. The document outlines the history and procedure of shotgun sequencing. Genomic DNA is first fragmented, end-repaired, and size-selected into small, medium, and large fragments. Libraries are created for each size fragment and sequenced. A base caller filters poor calls and an assembler finds overlaps to generate continuous nucleotide sequences or contigs of the whole genome.
Immunoprecipitation (IP) is a technique used to purify and enrich proteins of interest from a protein mixture using antibodies. The general IP protocol involves incubating a cell lysate sample containing the target protein with antibody-bound beads, washing away non-specifically bound proteins, and then eluting the immunoprecipitated protein off the beads. Key factors that influence IP include the composition of wash and elution buffers, the type of solid support used, antibody specificity and amount, and pre-clearing the lysate sample. Controls like isotype controls and negative controls without antibody help assess the specificity of the IP results.
Proteomics and its applications
Proteomics involves the analysis of the entire complement of proteins in a cell, tissue or organism. It assesses protein activities, modifications, localization and interactions. Proteomics uses techniques like gel electrophoresis, mass spectrometry and liquid chromatography to separate and identify proteins. These techniques can be applied to discover disease biomarkers, develop diagnostic tools, and gain insights into disease pathogenesis and treatment. Proteomics has applications in studying various diseases including cancer, diabetes and infections. It provides insights into cellular processes and systems biology.
Protein microarrays allow high-throughput analysis of protein interactions and functions. They consist of large numbers of capture proteins immobilized on a surface to which labeled probe molecules are added to detect reactions by fluorescence. There are analytical arrays to study protein binding properties and functional arrays containing full-length proteins to assay enzymatic activity and detect antibodies. Protein microarrays have applications in diagnostics, proteomics, analyzing protein interactions and functions, antibody characterization, and treatment development.
A database is a structured collection of data that can be easily accessed, managed, and updated. It consists of files or tables containing records with fields. Database management systems provide functions like controlling access, maintaining integrity, and allowing non-procedural queries. Major databases include GenBank, EMBL, and DDBJ for nucleotide sequences and UniProt, PDB, and Swiss-Prot for proteins. The NCBI maintains many biological databases and provides tools for analysis.
Functional proteomics, methods and toolsKAUSHAL SAHU
INTRODUCTION
HISTORY
DEFINITION
PROTEOMICS
FUNCTIONAL PROTEOMICS
PROTEOMICS SOFTWARE
PROTEOMICS ANALYSIS
TOOLS FOR PROTEOM ANALYSIS
DIFFERENTS METHODS FOR STUDY OF FUNCTIONAL PROTEOMICS
APLLICATIONS
LIMITATIONS
CONCLUSION
Dr. Robert Langer - Simposio Internacional 'Terapias oncológicas avanzadas'Fundación Ramón Areces
Los días 15 y 16 de octubre de 2014, la Fundación Ramón Areces y la Real Academia Nacional de Farmacia, en colaboración con la Fundación de la Innovación Bankinter, reunieron en Madrid a algunos de los mayores expertos mundiales en nuevas terapias contra el cáncer. El Simposio Internacional, coordinado por la profesora y académica María José Alonso, analizó el momento actual de la lucha contra esta enfermedad. También fue un punto de encuentro para científicos de los más innovadores institutos de investigación en oncología, quienes debatieron sobre tres grandes temas: la Medicina Personalizada contra el cáncer, los nanomedicamentos en la terapia del cáncer y las terapias basadas en la inmunomodulación.
Evgeny nikolaev proteomics of body liquids as a source for potential methods ...igorod
The document discusses using mass spectrometry to analyze body fluids like urine, saliva, and exhaled breath condensate for medical diagnostics and biomarker discovery. It describes creating databases of accurate mass tags and retention times from mass spec analyses of peptides and proteins in body fluids to enable fast identification. Biomarkers found for diseases like COPD, pneumonia and changes after lung transplantation are mentioned.
This document discusses nucleotide chemistry and nucleic acid chemistry. It covers the structures of nucleotides, nucleosides, and nucleic acids including DNA and RNA. Some key points include:
- Nucleotides are composed of a pentose sugar, phosphate group, and a nitrogenous base. DNA and RNA are polymers of nucleotides.
- DNA exists as a double helix with complementary base pairing between strands. It can undergo denaturation and renaturation.
- RNA includes tRNA, mRNA, rRNA and other non-coding RNA. tRNA forms a cloverleaf structure and carries amino acids. mRNA encodes proteins.
- Prokaryotes like bacteria have circular chromosomes without nuclei, while eukaryotes package
DNA Barcoding of Stone Fish Uranoscopus Oligolepis: Intra Species Delineation...journal ijrtem
Abstract: The present study addresses this issue by examining the patterning of Cytochrome Oxidase I diversity in the stone fish Uranoscopus oligolepis the structurally diverse group of Family Uranoscopidae. The sequences were analyzed for their species identification using BOLD’s identification engine. The COI sequences of U. oligolepis from different geographical regions were extracted from NCBI for intra species variation analysis. All sequences were aligned using Clustal W. The sequences were trimmed using software and phylogenetic tree was constructed with bootstrap test. The results showed that the cytosine content was high (31%). The least molar concentration was observed in guanine (19.5%) and Adenine (19.6%). Thymine was the second predominant in molar concentration next to thymine which is followed by adenine. The G+C content was found to be 49.6% and A+T content was 50.4%. Leucine and Alanine content was high in the amino acid composition. From the study it is assumed that the mitochondrial gene COI can be the potential barcoding region to identify an organism up to the species level. Keywords: COI, intra species, Uranoscopus oligolepis, barcoding, phylogenetic
Marine organisms produce complex chemicals as defenses against predators or competitors in the ocean environment. These chemicals show potential for developing new drugs, with some already in medical use. Ziconotide from cone snails is a potent non-opioid painkiller administered intrathecally. Ecteinascidin-743 from a Caribbean tunicate was the first marine-derived anticancer drug approved. It alkylates DNA and induces apoptosis. Both drugs show activity against cancers and have complex mechanisms of action involving ion channels or DNA damage, respectively. Marine natural products continue to offer possibilities for new pharmaceuticals.
Prions are infectious proteins that can replicate by converting normal prion proteins (PrP-sen) into an abnormal disease-causing form (PrP-res). PrP-res accumulates and forms amyloid fibers that are toxic to cells and ultimately cause fatal neurodegenerative diseases known as transmissible spongiform encephalopathies (TSEs). While prions do not contain genetic material, they propagate by inducing PrP-sen to adopt the abnormal PrP-res conformation. Polymerase chain reaction (PCR) is a technique used to amplify specific DNA sequences, allowing minute amounts of DNA to be analyzed. It involves repeated cycles of heating and cooling of the DNA to separate and copy the strands
This document summarizes a study that used PCR and cloning to analyze the 16S rRNA genes present in a natural marine bacterioplankton population from the Sargasso Sea. Researchers constructed a library of 51 small-subunit rRNA genes and sequenced five unique genes. In addition to genes from known marine Synechococcus and SAR11 lineages, they identified two new classes of genes belonging to alpha- and gamma-proteobacteria, confirming that many planktonic bacteria have not been previously recognized by microbiologists.
This document summarizes a study that investigated the effects of o-phenylenediamine (oPD) exposure on biochemical parameters in the liver and brain of zebrafish. Zebrafish were exposed to 1ppm and 5ppm of oPD for 15 days. Biological oxygen demand tests found moderate pollution in water treated with both concentrations of oPD. Exposure resulted in increased liver oxidative stress and alterations in liver detoxification enzymes and brain monoamine oxidase activity, suggesting oPD toxicity affects multiple organ systems. The study aims to understand the chronic effects and toxicity mechanism of oPD in aquatic animals like zebrafish.
Smart nanocarriers as novel drug delivery systems in cancer therapyFarshad Mirzavi
Smart nanocarriers as novel drug delivery systems in cancer therapy. The document discusses various types of nanocarriers including micelles, dendrimers, gold nanocarriers, super paramagnetic iron oxide nanoparticles, carbon nanotubes, and liposomes. It describes how these nanocarriers can be modified with ligands and polymers like PEG to actively target cancer cells and avoid immune system clearance. The nanocarriers need to accumulate at the target site and release their drug cargo in response to stimuli like pH or enzymes. Overall, the document provides an overview of smart nanocarrier drug delivery systems and their potential for improving cancer treatment.
Archakov A. from human genome project to human proteome projectigorod
The document discusses the transition from the Human Genome Project to the Human Proteome Project and Russia's participation in it. It outlines the main differences between genomics and proteomics, noting that the same genome can result in different proteomes. It then discusses the challenges and strategies for the Human Proteome Project, including focusing initially on comprehensively mapping the proteome of chromosome 18 as a pilot project using new highly sensitive technologies.
Drug repurposing in cancer & use of Artificial Intelligence(AI).pptxAmrendraKumar948416
Drug repurposing in cancer & use of Artificial Intelligence(AI)
DRUG REPURPOSING refers to the identification of clinically approved drugs with the known safety profiles and defined pharmacokinetic properties for new indications
PRECISION ONCOLOGY is an approach to cancer treatment that uses the genetic profile of the patient and the tumour to design and target the most effective therapy
What is Soft Repurposing and Hard Repurposing?
Repurposing of new cancer indication for established cancer medicines called as Soft Repurposing
Repurposing of non cancer medicine for oncology use called as Hard Repurposing
The document describes research analyzing the peptidome (collection of peptides) present in human lymph. Key findings include:
- Over 900 peptides were sequenced from human lymph at high resolution, mapping to over 480 proteins from intracellular and extracellular sources.
- Peptides showed evidence of being naturally processed from various self-antigens, like fibrinogen and complement C3.
- Pathway analysis revealed the lymph peptidome was associated with processes like acute phase response signaling and coagulation systems, reflecting its role as a filtrate of plasma.
- Peptides had a range of molecular functions and cellular origins, including mitochondria, ER, Golgi, cytosol, nucleus, and extracellular matrix proteins
Plasmids are small, extra-chromosomal DNA molecules capable of replicating independently of chromosomal DNA. They are commonly used as vectors to introduce foreign DNA into host cells. Restriction enzymes cut DNA at specific recognition sequences and are used in molecular cloning. Various techniques like gel electrophoresis, Southern blot, and DNA microarrays can analyze DNA sequences.
This document describes a study on using mid-infrared absorption spectroscopy for label-free detection of phospholipid biomarkers. Phospholipids exhibit strong absorption resonances in the mid-infrared region and are detectable using this technique. The study explores separating phospholipid biomarkers using on-chip capillary electrophoresis in a PDMS microfluidic chip, and then performing label-free detection of the separated biomarkers using mid-infrared absorption spectroscopy by interrogating the biomarkers in the microfluidic channel. Initial experiments detect a phospholipid called phosphatidic acid dissolved in a non-aqueous solvent using this approach, demonstrating the feasibility of the technique for label-free phospholipid sensing.
RNA interference (RNAi) technology uses small interfering RNAs (siRNAs) or microRNAs (miRNAs) to block gene expression. The document discusses RNAi mechanisms, applications for cancer treatment and hypercholesterolemia, production of siRNAs and miRNAs, and potential human side effects. RNAi is a promising approach being studied for developing therapies against diseases like liver cancer, respiratory infections, and high cholesterol levels. Companies are investigating RNAi therapeutics and developing methods for effective in vivo delivery of siRNAs and miRNAs to target tissues.
The document describes a new fluorescent biosensor platform called Nomad that can measure changes in intracellular second messenger concentrations after GPCR activation in live cells. The Nomad biosensors localize to the plasma membrane but undergo a conformational change and vesicularization upon increases in second messengers like cAMP, calcium, or DAG. This allows their redistribution to be detected using high-content screening. The biosensors come in three versions corresponding to different second messengers and can be multiplexed to simultaneously measure different signaling pathways and receptor internalization. The Nomad biosensors provide a robust, homogeneous, and reagent-free assay for high-throughput screening of GPCR activity.
The document discusses biotechnology and its applications in various fields such as agriculture, food processing, and genetic engineering. It also covers topics such as DNA, genes, nucleic acids, and how genetic material is structured. Biotechnology uses scientific principles from various disciplines and has potential applications in areas like producing antibiotics, improving crops, and treating wastewater.
brief overview on oligonucleotide, oligonucleoside and its application in medicine. given the basic knowledge as well about the DNA and its composition.
EFFECT OF RESVERETROL ON HUMAN BREAST CANCER (MCF-7) CELL LINEAbhishek Banerjee
This document summarizes a study on the effect of resveratrol on human breast cancer MCF-7 cell lines. The study found that resveratrol inhibited the viability of MCF-7 cells in a dose-dependent manner, with an IC50 value of 125μM. Treatment with resveratrol induced apoptosis in the cells, as shown by DNA fragmentation, phosphatidylserine externalization, and morphological changes observed under electron microscopy. The apoptosis was further confirmed by the activation of apoptotic proteins like t-Bid and cleavage of α-fodrin. The study concludes that resveratrol shows promise as an anti-cancer agent for its ability to induce apoptosis in breast cancer cells.
This document summarizes a study on the effect of resveratrol on human breast cancer (MCF-7) cell lines. The study found that resveratrol inhibited the viability of MCF-7 cells in a dose-dependent manner, with an IC50 value of 125μM. Tests showed that resveratrol induced apoptosis in MCF-7 cells, as evidenced by cellular morphology changes, DNA fragmentation, and activation of apoptotic proteins like t-Bid and cleavage of α-fodrin. The study concludes that resveratrol shows potential as a promising drug for cancer treatment based on its ability to selectively induce apoptosis in cancer cells.
The cost of acquiring information by natural selectionCarl Bergstrom
This is a short talk that I gave at the Banff International Research Station workshop on Modeling and Theory in Population Biology. The idea is to try to understand how the burden of natural selection relates to the amount of information that selection puts into the genome.
It's based on the first part of this research paper:
The cost of information acquisition by natural selection
Ryan Seamus McGee, Olivia Kosterlitz, Artem Kaznatcheev, Benjamin Kerr, Carl T. Bergstrom
bioRxiv 2022.07.02.498577; doi: https://doi.org/10.1101/2022.07.02.498577
PPT on Direct Seeded Rice presented at the three-day 'Training and Validation Workshop on Modules of Climate Smart Agriculture (CSA) Technologies in South Asia' workshop on April 22, 2024.
Signatures of wave erosion in Titan’s coastsSérgio Sacani
The shorelines of Titan’s hydrocarbon seas trace flooded erosional landforms such as river valleys; however, it isunclear whether coastal erosion has subsequently altered these shorelines. Spacecraft observations and theo-retical models suggest that wind may cause waves to form on Titan’s seas, potentially driving coastal erosion,but the observational evidence of waves is indirect, and the processes affecting shoreline evolution on Titanremain unknown. No widely accepted framework exists for using shoreline morphology to quantitatively dis-cern coastal erosion mechanisms, even on Earth, where the dominant mechanisms are known. We combinelandscape evolution models with measurements of shoreline shape on Earth to characterize how differentcoastal erosion mechanisms affect shoreline morphology. Applying this framework to Titan, we find that theshorelines of Titan’s seas are most consistent with flooded landscapes that subsequently have been eroded bywaves, rather than a uniform erosional process or no coastal erosion, particularly if wave growth saturates atfetch lengths of tens of kilometers.
SDSS1335+0728: The awakening of a ∼ 106M⊙ black hole⋆Sérgio Sacani
Context. The early-type galaxy SDSS J133519.91+072807.4 (hereafter SDSS1335+0728), which had exhibited no prior optical variations during the preceding two decades, began showing significant nuclear variability in the Zwicky Transient Facility (ZTF) alert stream from December 2019 (as ZTF19acnskyy). This variability behaviour, coupled with the host-galaxy properties, suggests that SDSS1335+0728 hosts a ∼ 106M⊙ black hole (BH) that is currently in the process of ‘turning on’. Aims. We present a multi-wavelength photometric analysis and spectroscopic follow-up performed with the aim of better understanding the origin of the nuclear variations detected in SDSS1335+0728. Methods. We used archival photometry (from WISE, 2MASS, SDSS, GALEX, eROSITA) and spectroscopic data (from SDSS and LAMOST) to study the state of SDSS1335+0728 prior to December 2019, and new observations from Swift, SOAR/Goodman, VLT/X-shooter, and Keck/LRIS taken after its turn-on to characterise its current state. We analysed the variability of SDSS1335+0728 in the X-ray/UV/optical/mid-infrared range, modelled its spectral energy distribution prior to and after December 2019, and studied the evolution of its UV/optical spectra. Results. From our multi-wavelength photometric analysis, we find that: (a) since 2021, the UV flux (from Swift/UVOT observations) is four times brighter than the flux reported by GALEX in 2004; (b) since June 2022, the mid-infrared flux has risen more than two times, and the W1−W2 WISE colour has become redder; and (c) since February 2024, the source has begun showing X-ray emission. From our spectroscopic follow-up, we see that (i) the narrow emission line ratios are now consistent with a more energetic ionising continuum; (ii) broad emission lines are not detected; and (iii) the [OIII] line increased its flux ∼ 3.6 years after the first ZTF alert, which implies a relatively compact narrow-line-emitting region. Conclusions. We conclude that the variations observed in SDSS1335+0728 could be either explained by a ∼ 106M⊙ AGN that is just turning on or by an exotic tidal disruption event (TDE). If the former is true, SDSS1335+0728 is one of the strongest cases of an AGNobserved in the process of activating. If the latter were found to be the case, it would correspond to the longest and faintest TDE ever observed (or another class of still unknown nuclear transient). Future observations of SDSS1335+0728 are crucial to further understand its behaviour. Key words. galaxies: active– accretion, accretion discs– galaxies: individual: SDSS J133519.91+072807.4
Sexuality - Issues, Attitude and Behaviour - Applied Social Psychology - Psyc...PsychoTech Services
A proprietary approach developed by bringing together the best of learning theories from Psychology, design principles from the world of visualization, and pedagogical methods from over a decade of training experience, that enables you to: Learn better, faster!
Evidence of Jet Activity from the Secondary Black Hole in the OJ 287 Binary S...Sérgio Sacani
Wereport the study of a huge optical intraday flare on 2021 November 12 at 2 a.m. UT in the blazar OJ287. In the binary black hole model, it is associated with an impact of the secondary black hole on the accretion disk of the primary. Our multifrequency observing campaign was set up to search for such a signature of the impact based on a prediction made 8 yr earlier. The first I-band results of the flare have already been reported by Kishore et al. (2024). Here we combine these data with our monitoring in the R-band. There is a big change in the R–I spectral index by 1.0 ±0.1 between the normal background and the flare, suggesting a new component of radiation. The polarization variation during the rise of the flare suggests the same. The limits on the source size place it most reasonably in the jet of the secondary BH. We then ask why we have not seen this phenomenon before. We show that OJ287 was never before observed with sufficient sensitivity on the night when the flare should have happened according to the binary model. We also study the probability that this flare is just an oversized example of intraday variability using the Krakow data set of intense monitoring between 2015 and 2023. We find that the occurrence of a flare of this size and rapidity is unlikely. In machine-readable Tables 1 and 2, we give the full orbit-linked historical light curve of OJ287 as well as the dense monitoring sample of Krakow.
Embracing Deep Variability For Reproducibility and Replicability
Abstract: Reproducibility (aka determinism in some cases) constitutes a fundamental aspect in various fields of computer science, such as floating-point computations in numerical analysis and simulation, concurrency models in parallelism, reproducible builds for third parties integration and packaging, and containerization for execution environments. These concepts, while pervasive across diverse concerns, often exhibit intricate inter-dependencies, making it challenging to achieve a comprehensive understanding. In this short and vision paper we delve into the application of software engineering techniques, specifically variability management, to systematically identify and explicit points of variability that may give rise to reproducibility issues (eg language, libraries, compiler, virtual machine, OS, environment variables, etc). The primary objectives are: i) gaining insights into the variability layers and their possible interactions, ii) capturing and documenting configurations for the sake of reproducibility, and iii) exploring diverse configurations to replicate, and hence validate and ensure the robustness of results. By adopting these methodologies, we aim to address the complexities associated with reproducibility and replicability in modern software systems and environments, facilitating a more comprehensive and nuanced perspective on these critical aspects.
https://hal.science/hal-04582287
TOPIC OF DISCUSSION: CENTRIFUGATION SLIDESHARE.pptxshubhijain836
Centrifugation is a powerful technique used in laboratories to separate components of a heterogeneous mixture based on their density. This process utilizes centrifugal force to rapidly spin samples, causing denser particles to migrate outward more quickly than lighter ones. As a result, distinct layers form within the sample tube, allowing for easy isolation and purification of target substances.
Microbial interaction
Microorganisms interacts with each other and can be physically associated with another organisms in a variety of ways.
One organism can be located on the surface of another organism as an ectobiont or located within another organism as endobiont.
Microbial interaction may be positive such as mutualism, proto-cooperation, commensalism or may be negative such as parasitism, predation or competition
Types of microbial interaction
Positive interaction: mutualism, proto-cooperation, commensalism
Negative interaction: Ammensalism (antagonism), parasitism, predation, competition
I. Mutualism:
It is defined as the relationship in which each organism in interaction gets benefits from association. It is an obligatory relationship in which mutualist and host are metabolically dependent on each other.
Mutualistic relationship is very specific where one member of association cannot be replaced by another species.
Mutualism require close physical contact between interacting organisms.
Relationship of mutualism allows organisms to exist in habitat that could not occupied by either species alone.
Mutualistic relationship between organisms allows them to act as a single organism.
Examples of mutualism:
i. Lichens:
Lichens are excellent example of mutualism.
They are the association of specific fungi and certain genus of algae. In lichen, fungal partner is called mycobiont and algal partner is called
II. Syntrophism:
It is an association in which the growth of one organism either depends on or improved by the substrate provided by another organism.
In syntrophism both organism in association gets benefits.
Compound A
Utilized by population 1
Compound B
Utilized by population 2
Compound C
utilized by both Population 1+2
Products
In this theoretical example of syntrophism, population 1 is able to utilize and metabolize compound A, forming compound B but cannot metabolize beyond compound B without co-operation of population 2. Population 2is unable to utilize compound A but it can metabolize compound B forming compound C. Then both population 1 and 2 are able to carry out metabolic reaction which leads to formation of end product that neither population could produce alone.
Examples of syntrophism:
i. Methanogenic ecosystem in sludge digester
Methane produced by methanogenic bacteria depends upon interspecies hydrogen transfer by other fermentative bacteria.
Anaerobic fermentative bacteria generate CO2 and H2 utilizing carbohydrates which is then utilized by methanogenic bacteria (Methanobacter) to produce methane.
ii. Lactobacillus arobinosus and Enterococcus faecalis:
In the minimal media, Lactobacillus arobinosus and Enterococcus faecalis are able to grow together but not alone.
The synergistic relationship between E. faecalis and L. arobinosus occurs in which E. faecalis require folic acid
Mending Clothing to Support Sustainable Fashion_CIMaR 2024.pdfSelcen Ozturkcan
Ozturkcan, S., Berndt, A., & Angelakis, A. (2024). Mending clothing to support sustainable fashion. Presented at the 31st Annual Conference by the Consortium for International Marketing Research (CIMaR), 10-13 Jun 2024, University of Gävle, Sweden.
Mending Clothing to Support Sustainable Fashion_CIMaR 2024.pdf
De-novo sequencing of PEPTIDES
1. CiguatoxinConotoxin Snake toxin4 Spider toxin
Sequencing of Venompeptides
Rajesh. R P, Scientist, Sathyabama Institute of Science and Technology
2. Conus is a large genus of small to large predatory sea snails, marine
gastropod molluscs, with the common names of cone snails or cone shells
Conidae Currently contains over 800 recognized species cones.
Cone snails use a hypodermic-like modified radula tooth and a venom gland to
attack and paralyze their prey before engulfing it.
Cone snail venoms are mainly made of cocktail of peptides and proteins.
The venoms contain many different types of peptide toxins that vary in their effects;
some are extremely toxic.
The sting of small cones is no worse than a bee sting, but the sting of a few of the
larger species of tropical cone snails can be serious, occasionally even fatal to human
beings.
6. C. striatus, a Clade I species
(A) and C. tulipa, a Clade II
species (B).
1) C. striatus extends its
proboscis, harpoons the fish
and through a “lightning-
strike cabal” of toxins
causes an almost
instantaneous
immobilization of prey.
2) C. tulipa probably goes
after schools of fish hiding in
reefs at night using a net
strategy; once it has
engulfed the school with its
highly distensible rostrum, it
uses a “nirvana cabal of
toxins” to make the fish
quiescent for stinging them
and causing an irreversible
neuromuscular paralysis.
Conus Strategies for Catching Fish
7. Conotoxin Library- “CONOSERVER”
• Marine gastropods, better known as cone snails from Conus genus, produce a
mixture of venomous peptides for capturing prey, defense and deterring
competitors.
• These conopeptides can generally be divided into two broad classes, the
disulfide rich conotoxins which contain two or more disulfide bonds and the
disulfide poor which contain one or no disulfide bond.
• Conotoxins are small peptides ranging from 5-40 amino acids in length.
• Each cone snail may contain up to 200 peptides and given there are over 700
cone snail species, the library of bioactive peptides is huge (with a broad
estimate of thousands of unknown conopeptides .
• The targets for these toxins are a range of membrane bound receptors and ion
channels, thus exhibiting great potential as therapeutics themselves or as leads
to therapeutics.
8. B.M.Olivera et al ; current opinion in neurobiology 1999,9:772-777
Effects of different peptides from Conus geographus venom on mice
behavior
9. Applications of conotoxins
• Diagnosis of rare neuromuscular disorder
• Anticonvulsant, Anesthetic
• Pain killer (alternative to morphine)
• Basic bench research-(using toxins for neurophysiological studies).
• treatment of neurological diseases such as multiple sclerosis, shingles,
diabetic neuropathy and other painful neurological conditions.
• Many other target yet to be discovered as with unknown function many
conotoxins have been reported.
• Ziconotide (SNX-111; Prialt) is an atypical analgesic agent for the
amelioration of severe and chronic pain whic is Derived from Conus
magus
11. • Conotoxins feature a vast array of post translational modifications (PTMs).
• PTMs are chemical or structural changes to the residues of a peptide that are not
encoded in the peptide gene.
• PTMs are introduced by specialized enzymes that change the nature of a specific
residue. It is believed that the enzymes involved identify their targets by their signal
and/or propeptide sequence.
POST TRANSLATIONAL MODIFICATIONS
12. De Novo Peptide Sequencing
"de novo peptide sequencing" is, peptide sequencing performed without prior knowledge
of the amino acid sequence.
Mass spectrometers do have the advantage when it comes to generating sequence data
for peptides in low femtomole quantities.
However, Edman degradation will always enjoy the advantage when pmol quantities of a
peptide are available.
At higher pmol quantities (2-10 pmol) and 99% purity, Edman will often provide the exact
amino acid sequence without ambiguity for a limited run of amino acids, 6-30 amino
acids. HIGH PURITY UP TO 99% required
MS/MS enjoys sensitivity, and speed, and does not require an external standard for each
amino acid or amino acid variant.
Even crude mixture could be analysed using Mass Spectrometry based denova
sequencing. LESS PURITY or CRUDE MAY WORK
Another advantage is that MS/MS sequencing is never stopped by a blocked amino
terminus, as is the case for Edman degradation.
13. Peptide de novo sequencing is the analytical process that derives a peptide’s
amino acid sequence from its tandem mass spectrum (MS/MS) without the
assistance of a sequence database.
It is in contrast to another popular peptide identification approach –
“database search”, which searches in a given database to find the target
peptide. A clear advantage of de novo sequencing is that it works for both
database and novel peptides.
Basic Principle
In a tandem mass spectrometer, the peptide is fragmented along the peptide
backbone and the resulting fragment ions are measured to produce the
MS/MS spectrum.
Depending on the fragmentation methods used, different fragment ion types
can be produced. The most widely used fragmentation methods today are
Collision-Induced Dissociation (CID) and Electron-Transfer Dissociation
(ETD). CID produces mostly b and y-ions; and ETD produces mostly c and
z-ions.
15. C C S Q D C R VC I O C C P Y
17
01
C C S Q D C R VC I O C C P Y
1701
A venom peptide with mass 1701(M+H) from vermivorous cone snail Conus figulinus
16. 6 Cysteines: 3-disulfide Bridge
756
AF New-16- TCEP-NEM
08-08-2011
REDUCTION USING TCEP(Tris-(2-Carboxyethyl)phosphine) AND
SUBSEQUENT ALKYLATION NEM(N-Ethylmaleimide )
C C S Q D C R VC I O C C P Y
C= NEM LABELLED
1702.8
0_F181: +MS
2209.1
2335.2
2458.4
0_H121: +MS
0
1
2
3
4
5
4x10
Intens.
0.0
0.2
0.4
0.6
0.8
1.0
4x10
1700 1800 1900 2000 2100 2200 2300 2400 2500 m/z
23. Contact Me:
Dr. R. P. Rajesh,Ph.D,
Scientist C,
Molecular & Nanomedical Sciences
Sathyabama Institute of Science and Technology, Chennai-119
Ph: 8072968170
+919994189582