The experimental methods used by biotechnologists to determine the structures of proteins demand sophisticated equipment and time.
A host of computational methods are developed to predict the location of secondary structure elements in proteins for complementing or creating insights into experimental results.
Chou-Fasman algorithm is an empirical algorithm developed for the prediction of protein secondary structure
The experimental methods used by biotechnologists to determine the structures of proteins demand sophisticated equipment and time.
A host of computational methods are developed to predict the location of secondary structure elements in proteins for complementing or creating insights into experimental results.
Chou-Fasman algorithm is an empirical algorithm developed for the prediction of protein secondary structure
Protein aggregation is the most discussed topic as it is being linked to many neurodegenerative diseases. Here, in these slides I have tried to explain about protein aggregation and its mechanism.
Prediction of the three dimensional structure of a given protein sequence i.e. target protein from the amino acid sequence of a homologous (template) protein for which an X-ray or NMR structure is available based on an alignment to one or more known protein structures
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.
A protein microarray (or protein chip) is a high-throughput method used to track the interactions and activities of proteins, and to determine their function, and determining function on a large scale. Its main advantage lies in the fact that large numbers of proteins can be tracked in parallel.
INTRODUCTION
STRUCTURAL PROTEOMICS
WHAT IS THE IMPORTANCE OF STUDY OF PROTEIN
METHODS FOR SOLVING PROTEIN STRUCTURE
1. X- RAY CRYSTALLOGRAPHY
INTRODUCTION
PROCEDURE
LIMITATIONS
2.NUCLEAR MAGNETIC RESONANCE
PROTEIN STRUCTURE DETERMINATION
3. MASS SPECTROMETER
MALDI
ESI
STRUCTURE MODELING
APPLICATIONS
CONCLUSION
REFERENCES
Protein aggregation is the most discussed topic as it is being linked to many neurodegenerative diseases. Here, in these slides I have tried to explain about protein aggregation and its mechanism.
Prediction of the three dimensional structure of a given protein sequence i.e. target protein from the amino acid sequence of a homologous (template) protein for which an X-ray or NMR structure is available based on an alignment to one or more known protein structures
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.
A protein microarray (or protein chip) is a high-throughput method used to track the interactions and activities of proteins, and to determine their function, and determining function on a large scale. Its main advantage lies in the fact that large numbers of proteins can be tracked in parallel.
INTRODUCTION
STRUCTURAL PROTEOMICS
WHAT IS THE IMPORTANCE OF STUDY OF PROTEIN
METHODS FOR SOLVING PROTEIN STRUCTURE
1. X- RAY CRYSTALLOGRAPHY
INTRODUCTION
PROCEDURE
LIMITATIONS
2.NUCLEAR MAGNETIC RESONANCE
PROTEIN STRUCTURE DETERMINATION
3. MASS SPECTROMETER
MALDI
ESI
STRUCTURE MODELING
APPLICATIONS
CONCLUSION
REFERENCES
MULISA : A New Strategy for Discovery of Protein Functional Motifs and Residuescsandit
To predict and identify details regarding function
from protein sequences is an emergency task
since the growing number and diversity of protein s
equence. Here, we develop a novel approach
for identifying conservation residues and motifs of
ligand-binding proteins. In this method,
called MuLiSA (Multiple Ligand-bound Structure Alig
nment), we first superimpose the ligands
of ligand-binding proteins and then the residues of
ligand-binding sites are naturally aligned.
We identify important residues and patterns based o
n the z-scores of the residue entropy and
residue-segment entropy. After identifying new patt
ern candidates, the profiles of patterns are
generated to predict the protein function from only
protein sequences. We tested our approach
on ATP-binding proteins and HEM-binding proteins. T
he experiments show that MuLiSA can
identify the conservation residues and novel patter
ns which are really correlated with protein
functions of certain ligand-binding proteins. We fo
und that our MuLiSA can identify
conservation patterns and is better than traditiona
l alignments such as CE and CLUSTALW in
some ligand-binding proteins. We believe that our M
uLiSA is useful to discover ligand-binding
specificity-determining residues and functional imp
ortant patterns of proteins.
Protein Structure Prediction Using Support Vector Machine ijsc
Support Vector Machine (SVM) is used for predict the protein structural. Bioinformatics method use to protein structure prediction mostly depends on the amino acid sequence. In this paper, work predicted of 1-D, 2-D, and 3-D protein structure prediction. Protein structure prediction is one of the most important problems in modern computation biology. Support Vector Machine haves shown strong generalization ability protein structure prediction. Binary classification techniques of Support Vector Machine are implemented and RBF kernel function is used in SVM. This Radial Basic Function (RBF) of SVM produces better accuracy in terms of classification and the learning results.
PROTEIN STRUCTURE PREDICTION USING SUPPORT VECTOR MACHINEijsc
Support Vector Machine (SVM) is used for predict the protein structural. Bioinformatics method use to protein structure prediction mostly depends on the amino acid sequence. In this paper, work predicted of 1-
D, 2-D, and 3-D protein structure prediction. Protein structure prediction is one of the most important problems in modern computation biology. Support Vector Machine haves shown strong generalization ability protein structure prediction. Binary classification techniques of Support Vector Machine are implemented and RBF kernel function is used in SVM. This Radial Basic Function (RBF) of SVM produces better accuracy in terms of classification and the learning results.
Criterion based Two Dimensional Protein Folding Using Extended GA IJCSEIT Journal
In the dynamite field of biological and protein research, the protein fold recognition for long pattern
protein sequences is a great confrontation for many years. With that consideration, this paper contributes
to the protein folding research field and presents a novel procedure for mapping appropriate protein
structure to its correct 2D fold by a concrete model using swarm intelligence. Moreover, the model
incorporates Extended Genetic Algorithm (EGA) with concealed Markov model (CMM) for effectively
folding the protein sequences that are having long chain lengths. The protein sequences are preprocessed,
classified and then, analyzed with some parameters (criterion) such as fitness, similarity and sequence gaps
for optimal formation of protein structures. Fitness correlation is evaluated for the determination of
bonding strength of molecules, thereby involves in efficient fold recognition task. Experimental results have
shown that the proposed method is more adept in 2D protein folding and outperforms the existing
algorithms.
nternational Journal of Engineering Research and Development is an international premier peer reviewed open access engineering and technology journal promoting the discovery, innovation, advancement and dissemination of basic and transitional knowledge in engineering, technology and related disciplines.
Proteomics, definatio , general concept, signficanceKAUSHAL SAHU
INTRODUCTION
GENERAL CONCEPT
WHY PROTEIOMIC NECESERY?
WHAT PROTEOMIC CAN ANSWER?
PRTEOMICS- ANALYSIS AND IDENTIFICATION OF PROTEIN
TWO-DIMENSIONAL SDS-PAGE
MASS SPECTROMETERS
SIGNIFICANCE OF STUDY AN ITS IMPORTANCE
APPLICATIONS
CHALLENGES
CONCLUSIONS
REFERENCES
Validation of Clomipramine interactions identified by BioBind against experim...Marie-Julie Denelle
Based on the now accepted principle that
similar receptors bind similars ligands, we have developed BioBind, a patented comparison algorithm
dedicated to the retrieval and assessment of local surface similarities. Clomipramine appears to be a
good “real life” candidate to challenge BioBind. In a couple of hours, BioBind was able to retrieve all
known targets having structural data described in the literature and to provide a valuable list of unknown
yet sensible putative targets currently being experimentally validated. This analysis hence demonstrates the
robustness and relevance of BioBind.
Bioinformatics, application by kk sahu sirKAUSHAL SAHU
INTRODUCTION
HISTORY
WHAT IS BIOINFORMATICS
APPLICATIONS
DNA AND RNA LEVELS
CONCLUSION
REFRENCES
"Bioinformatics" to refer to the study of information processes in biotic systems. This definition placed bioinformatics as a field parallel to biophysics or biochemistry (biochemistry is the study of chemical processes in biological systems).
the field of bioinformatics has evolved such that the most pressing task now involves the analysis and interpretation of various types of data. This includes nucleotide and amino acid sequences, protein domains, and protein structures.
Operation “Blue Star” is the only event in the history of Independent India where the state went into war with its own people. Even after about 40 years it is not clear if it was culmination of states anger over people of the region, a political game of power or start of dictatorial chapter in the democratic setup.
The people of Punjab felt alienated from main stream due to denial of their just demands during a long democratic struggle since independence. As it happen all over the word, it led to militant struggle with great loss of lives of military, police and civilian personnel. Killing of Indira Gandhi and massacre of innocent Sikhs in Delhi and other India cities was also associated with this movement.
The French Revolution, which began in 1789, was a period of radical social and political upheaval in France. It marked the decline of absolute monarchies, the rise of secular and democratic republics, and the eventual rise of Napoleon Bonaparte. This revolutionary period is crucial in understanding the transition from feudalism to modernity in Europe.
For more information, visit-www.vavaclasses.com
Synthetic Fiber Construction in lab .pptxPavel ( NSTU)
Synthetic fiber production is a fascinating and complex field that blends chemistry, engineering, and environmental science. By understanding these aspects, students can gain a comprehensive view of synthetic fiber production, its impact on society and the environment, and the potential for future innovations. Synthetic fibers play a crucial role in modern society, impacting various aspects of daily life, industry, and the environment. ynthetic fibers are integral to modern life, offering a range of benefits from cost-effectiveness and versatility to innovative applications and performance characteristics. While they pose environmental challenges, ongoing research and development aim to create more sustainable and eco-friendly alternatives. Understanding the importance of synthetic fibers helps in appreciating their role in the economy, industry, and daily life, while also emphasizing the need for sustainable practices and innovation.
2024.06.01 Introducing a competency framework for languag learning materials ...Sandy Millin
http://sandymillin.wordpress.com/iateflwebinar2024
Published classroom materials form the basis of syllabuses, drive teacher professional development, and have a potentially huge influence on learners, teachers and education systems. All teachers also create their own materials, whether a few sentences on a blackboard, a highly-structured fully-realised online course, or anything in between. Despite this, the knowledge and skills needed to create effective language learning materials are rarely part of teacher training, and are mostly learnt by trial and error.
Knowledge and skills frameworks, generally called competency frameworks, for ELT teachers, trainers and managers have existed for a few years now. However, until I created one for my MA dissertation, there wasn’t one drawing together what we need to know and do to be able to effectively produce language learning materials.
This webinar will introduce you to my framework, highlighting the key competencies I identified from my research. It will also show how anybody involved in language teaching (any language, not just English!), teacher training, managing schools or developing language learning materials can benefit from using the framework.
Model Attribute Check Company Auto PropertyCeline George
In Odoo, the multi-company feature allows you to manage multiple companies within a single Odoo database instance. Each company can have its own configurations while still sharing common resources such as products, customers, and suppliers.
Embracing GenAI - A Strategic ImperativePeter Windle
Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
1. Computational study of Protein
From Scratch;
From Structure to Function
Topic:
Kinza Irshad
Soil and Ecosystem Ecology Lab,
COMSATS University Islamabad,
Abbottabad
5/28/2019 1
2. What is Protein?
Long chain polypeptides
Made up of 20 naturally occurring amino acids
Two amino acids have peptide bond, having double bond characteristic
Functional proteins are folded into 3D structure, containing helix, Beta sheets and loops
Helix and sheets are rigid part while loops are flexible
In 3D structure hydrophobic amino acids are located in core while hydrophilic are oriented at
surface.
5/28/2019 2
5. First Step; Protein Sequence
We are going to take start from Protein Sequence.
We can take protein sequence from database or can translate gene sequence into protein.
In both cases, we should ultimately have FASTA format.
5/28/2019 5
6. What is FASTA Format???
>MH08765.1 Serine_protease, Human
ELPDFTPLVEQASPAVVNISTRQKLPDRAMARGQLSIPDLEGLPPMFRDFLERSIPQVPRNPRGQQREAQSLGSGFIISN
DGYITNNHVVADADEILVRLSDRSEHKAKLIGADPRSDVAVLKIEAKNLPTLKLGDSNKLKVGEWVLAIGSPFGFDHSVTA
GIVSAKGRSLPNESYVPFIQTDVAINPGNSGGPLLNLQGEVVGINSQIFTRSGGFMGLSFAIPIDVALNVADQLKKAGKVS
RGWLGVVIQEVNKDLAESFGLDKPSGALVAQLVEDGPAAKGGLQVGDVILSLNGQSINESADLPHLVGNMKPGDKINL
DVIRNGQRKSLSMAVGSLPDDDEEIASMGAPGAERSSNRLGVTVADLTAEQRKSLDIQGGVVIKEVQDGPAAVIGLRPG
DVITHLDNKAVTSTKVFADVAKALPKNRSVSMRVLRQGRASFITFKLA
5/28/2019 6
Header Region
Protein
Sequence
in one
letter code
7. How To Get Protein Sequence from Database??
1. We are going to take example of largest and most frequently used NCBI nucleotide and
Protein database
https://www.ncbi.nlm.nih.gov/
2. There are two different types of format
◦ GenBank
◦ FASTA
5/28/2019 7
8. After Having Sequence What to Do?
In next step, We will try to figure out Physio-chemical properties of our target protein, including
Molecular weight, Iso-electric point, stability, etc.
We will use very popular tool here, named Expasy Protparam.
https://web.expasy.org/protparam/
The input is protein sequence in FASTA format.
Genbank format is not acceptable
5/28/2019 8
9. Prediction of Secondary Structure Elements
There are three different structural forms of proteins, primary, secondary, and tertiary
structure.
In secondary structure, there will be three different type of element, alpha-helix, beta-sheets
and loops.
Two different type of algorithms used to predict secondary structure elements
I. Ab-initio Based
II. Homology Based
5/28/2019 9
10. Prediction of Secondary Structure Elements
Ab-initio algorithms are stand alone algorithms, identifying the secondary structure elements
of using intrinsic tendencies of amino acids to be in particular confirmation. For example,
glycine and proline, they love to stay in loops only
Homology-based algorithms make prediction based on secondary structure of homolgous.
Structures are more conserved as compared to sequence.
5/28/2019 10
11. PSI-PRED; A Homology-Based Tool
We will use Psi-Pred a homology based tool to predict secondary structure
http://bioinf.cs.ucl.ac.uk/psipred/
The submitted protein sequence will be searched in protein database through BLAST to search
the homologous sequences, based on query coverage and E-value.
The tool will align the homologous sequences (MSA) to get information about conservancy.
The conserved regions should ideally have same secondary structural elements.
5/28/2019 11
13. Signal Peptide Prediction
Signal peptide in defining localization of protein in the cells.
Present at N-terminal of newly synthesized protein
Predominantly hydrophobic amino acids
Important to predict especially if we want to clone the gene into
expression system.
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14. Signal Peptide Prediction
Commonly used algorithm for the prediction of
signal peptide is SignalP4.1
http://www.cbs.dtu.dk/services/SignalP/
Input sequence is FASTA format
5/28/2019 14
15. Is Our Protein is Transmembrane ?
In cell, proteins are either globular or
transmembrane.
Transmembrane proteins can be
i. Transmembrane helical
ii. Beta-barrels
To make structural prediction of transmembrane
protein TMHMM (Transmembrane Hidden Markov
Model) algorithm is used.
http://www.cbs.dtu.dk/services/TMHMM/
5/28/2019 15
16. Prediction of Domains & Motifs in Protein Structure
InterPro online server will be used to identify the domains
https://www.ebi.ac.uk/interpro/
The input sequence will be in FASTA format.
InterPro used homology search to identify the domains and mortifies.
5/28/2019 16
18. 3D Structure predication of a protein
Protein structure prediction is the inference of the three-dimensional structure of
a protein from its amino acid sequence—that is, the prediction of its folding and its secondary
and tertiary structure from its primary structure.
Structure prediction is fundamentally different from the inverse problem of protein design.
Protein structure prediction is one of the most important goals pursued by bioinformatics
and theoretical chemistry; it is highly important in medicine (for example, in drug design)
and biotechnology (for example, in the design of novel enzymes).
19. 3D Structure Prediction of Protein
3D structure prediction is one of most complicated computational process
Important step for protein structure analysis
There are three experimental techniques to determine 3D structure of proteins
i. X-ray Crystallography
ii. NMR
iii. Cryo-Electron Microscopy
5/28/2019 DEPARTMENT OF BIOCHEMISTRY & BIOTECHNOLOGY 19
21. 5/28/2019 21
End of Session No 1
Lets do some practical work
Accession # MH045598
https://www.ncbi.nlm.nih.gov/
https://web.expasy.org/protparam/
http://bioinf.cs.ucl.ac.uk/psipred/
http://www.cbs.dtu.dk/services/SignalP/
https://www.ebi.ac.uk/interpro/
https://zhanglab.ccmb.med.umich.edu/I-TASSER/