This research work aims to analyze experimental data about biochemical properties and their corresponding kinetics. In this research the attempt has been made to analyze protein and DNA structure using tools such as DAMBE and Jemboss. Some Molecular Visualization or Analysis tools are already developed that reads, analyses, and crosscorrelates experimental information which is useful for chemist, Organist Chemist, Biochemist and Druggist. In this research using ACD/ChemSketch compounds are stored in databases and SMILE code (Simplified Molecular Input Line Specification) is generated. A SMILE defines the molecules in the form of alphanumeric chains. In this research work chemical shift of every carbon atom of the molecule have been displayed by using NMR Prediction. Under this research CML codes of molecules have been developed and that codes have been used for molecular information like symmetry, and atom and bond attributes. Here multiple observations of the same molecule like conformational analysis and NMR prediction have been performed. Using Pubchem/NCBI additional miscellaneous information such as bioactivity analysis by structure & activity similarity and revised compound selection after addition of similar compounds have been analyzed. Under the research work geometric optimization of molecules, chemical structure visualization and calculation of electronic absorption spectra of chemical structure have been performed using ArgusLab tool. In this research Single Entry Point Calculation, Molecular Orbital calculation on grids for plotting HOMO and LUMO and ESP Mapped Density calculations have been also performed. Under the research work of different types of analysis like prediction of protein secondary structure, isoelectric point calculation etc. have been performed on nucleotide and protein sequence using DAMBE and Jemboss tools. The objective of this research work is to assist the organic and biochemist in each step of the synthesis planning process for prediction of molecular structure. This research work provides a series of methods and tools for chemical or biochemical applications. Built-in catalogs of fine chemicals or biochemical provide suitable starting materials for a synthesis or molecular structure prediction target. Using similarity searches or substructure searches the connection between the target compound and available starting materials has been achieved.
Table of Contents
I Introduction
1.1 Introduction
1.2 The Research Area, Problem Domain and Literature Survey
1.3 Relevance of research
1.4 Details of Remaining Chapters
1.5 References
II Computational Techniques, Tools and Technologies to support Bioinformatics
2.1 Introduction
2.2 ACD/ChemSketch
2.2.1 Introduction
2.2.2 ACD/ChemSketch includes
2.2.3 Structure Representation
2.2.4 IUPAC International Chemical Identifier
2.3 NMRPrediction
2.3.1 Introduction
2.4 ArgusLab
2.4.1 Introduction
2.4.2 Building of Benzene
2.5 DAMBE
2.5.1 Main Feature
2.5.2 Sequence Analysis
2.5.3 Codon Frequency
2.5.4 Nonsynonymous codon substitution
2.6 Jemboss
2.6.1 Introduction
2.6.2 Local and Remote File Manager
2.6.3 Jemboss Alignment Editor
2.6.4 Sequence List
2.6.5 Jemboss Alignment Editor
2.7 Chemical Markup Language (CML)
2.7.1 Introduction
2.7.2 Reading XML Documents
2.7.3 Examples of the molecules with CML
2.8 SMILES
2.8.1 Introduction
2.8.2 Canonicalization
2.8.3 SMILES Specification Rules
2.8.3.1 Atoms
2.8.3.2 Bonds
2.8.3.3 Branches
2.8.3.4 Cyclic Structures
2.8.3.5 Disconnected Structures
2.10 References
III Alignment of Pairs and Multiple Sequences and Phylogenetic Analysis
3.1 Introduction
3.2 Sequence Description
3.3 Pair wise Sequence Alignment
3.3.1 Local versus Global Alignment
3.3.2 Methods of Sequence Alignment
3.4 Multiple Sequence Alignment
3.4.1 Methods of Multiple Sequence Alignment
3.4.2 Application of Multiple Alignments
3.5 Phylogenetic Analysis
3.5.1 Methods of Phylogenetic Analysis
3.5.2 Computational Considerations
3.6 References
IV Similarities Search and Sequence Alignment
4.1 FASTA Algorithm
4.1.2 FASTA Implementation
4.2 BLAST Algorithm
4.2.1 BLAST Output
4.2.2 BLAST Services
4.2.3 FILTERING and GAPPED BLAST
4.2.4 FASTA and BLAST Algorithms Comparison
4.3 References
V Protein Structure and Cheminformatics
5.1 Introduction
5.2 Different Levels of Protein Structure
5.3 Prediction Methods
5.4 Secondary Structure Prediction
5.5 The Protein Folding Problem
5.6 Cheminformatics
5.6.1 Introduction
5.6.2 Challenges of Drug Design
5.6.3 The Drug Discovery Pipeline
5.6.4 Computer-Aided Drug Design (CADD)
5.6.5 Difficulties Implementing Denovo Design
5.7 References
VI Conformational Study of Molecules using Tools
6.1 Introduction
6.2 Experimental Work
6.2.1 Activity No.-1
6.2.2 Activity No.-2
6.2.3 Activity No.-3
6.2.3.1 Sequence Analysis Using Jemboss
6.2.3.2 Nucleotide Sequence Using DAMBE
6.2.3.1 Protein sequence Using Jemboss
6.3 Data Analysis and Experimental Outcome
6.4 Conclusions and Future Scope of Research
Objective & Research Themes
The research primarily aims to analyze experimental biochemical data and molecular kinetics to develop an integrated model for predicting molecular structures. The study leverages bioinformatics and cheminformatics methodologies, focusing on the processing of protein and DNA sequences, as well as the geometric and electronic analysis of small molecules through computational tools to assist in synthesis planning and pharmacological discovery.
- Bioinformatics analysis of protein and DNA structure using tools such as DAMBE and Jemboss.
- Cheminformatics approach to chemical structure storage and prediction using ACD/ChemSketch and NMR Prediction.
- Geometric optimization and electronic spectra calculation of molecules utilizing ArgusLab.
- Application of data mining and visualization techniques to evaluate biological activity and molecular similarity.
- Development of a knowledge-based expert system for molecular structure prediction.
Excerpt from the Book
1.1 Introduction
This research work aims to analyze experimental data about biochemical properties and their corresponding kinetics. In this research the attempt has been made to analyze protein and DNA structure using tools such as DAMBE and Jemboss. Some Molecular Visualization or Analysis tools are already developed that reads, analyses, and cross-correlates experimental information which is useful for chemist, Organist Chemist, Biochemist and Druggist.
Under this research the analysis of different chemical and biochemical substances including drugs using tools like ACD/ChemSketch and NMR Prediction have been performed. The information obtained by the way of analysis that facilitates for in depth understanding of structures and that makes possible for a quantification of new chemical structure.
In this research using ACD/ChemSketch compounds are stored in databases and SMILE code (Simplified Molecular Input Line Specification) is generated. A SMILE defines the molecules in the form of alphanumeric chains. In this research work chemical shift of every carbon atom of the molecule have been displayed by using NMR Prediction.
Under this research CML codes of molecules have been developed and that codes have been used for molecular information like symmetry, and atom and bond attributes. Here multiple observations of the same molecule like conformational analysis and NMR prediction have been performed.
Summary of Chapters
I Introduction: Provides an overview of the research scope, the importance of bioinformatics in chemical data analysis, and outlines the structure of the thesis.
II Computational Techniques, Tools and Technologies to support Bioinformatics: Discusses various computational software tools used for molecular drawing, sequence manipulation, and chemical representation, including ACD/ChemSketch and Jemboss.
III Alignment of Pairs and Multiple Sequences and Phylogenetic Analysis: Examines methods for sequence alignment and the reconstruction of evolutionary relationships through phylogenetic tree construction.
IV Similarities Search and Sequence Alignment: Details the algorithms used for database similarity searching, focusing on FASTA and BLAST as heuristic tools for sequence comparison.
V Protein Structure and Cheminformatics: Reviews protein structure levels and computational approaches to drug design, addressing the protein folding problem and ligand-receptor interactions.
VI Conformational Study of Molecules using Tools: Documents the practical experimental activities performed during the research, including structural analysis and the application of tools for data evaluation and model building.
Keywords
Bioinformatics, Cheminformatics, Molecular Structure Prediction, Sequence Alignment, BLAST, FASTA, ACD/ChemSketch, Jemboss, DAMBE, ArgusLab, Protein Folding, Drug Design, Phylogenetic Analysis, Data Mining, Chemical Markup Language.
Frequently Asked Questions
What is the core focus of this research?
The research focuses on the intersection of bioinformatics and cheminformatics, specifically aimed at developing an integrated computational model for predicting the molecular structure of compounds based on their biochemical properties and sequence data.
What are the primary thematic areas covered?
The work covers molecular visualization, sequence alignment algorithms, protein structure prediction, cheminformatics data mining, and the conformational study of molecules using specific software packages.
What is the main objective of the thesis?
The primary goal is to assist organic chemists and biochemists in the synthesis planning process by providing a series of automated methods and tools for accurate molecular structure prediction.
Which scientific methodologies are employed?
The study employs a combination of statistical analysis, dynamic programming, and machine-learning-like approaches for sequence alignment (FASTA, BLAST), and utilizes molecular orbital calculations (HOMO/LUMO) and geometric optimization via ArgusLab.
What topics are explored in the main body?
The main body investigates protein sequence analysis, phylogenetic tree construction, nucleotide frequency assessment, and the systematic modeling of molecular geometry and bioactivity for drugs like alanine and glutamine.
Which keywords best characterize this work?
Key terms include Molecular Structure Prediction, Cheminformatics, Bioinformatics, FASTA, BLAST, Sequence Alignment, and protein folding.
How is the molecular structure of amino acids analyzed in this model?
The model uses tools like ACD/ChemSketch to define molecular structure in SMILE notation and NMR Prediction to calculate chemical shifts, integrating these into a knowledge-based system for structure prediction.
What is the significance of the computational results presented in Chapter 6?
Chapter 6 provides quantitative data, such as heat of formation, molecular orbital energies, and bioactivity analysis, which validate the efficacy of the proposed modeling approach in predicting molecular behavior and characteristics.
- Quote paper
- Dr. Binod Kumar (Author), 2010, Study and Analysis of Knowledgebase of Molecular Systems and to Develop Model for Prediction of Molecular Structure, Munich, GRIN Verlag, https://www.grin.com/document/509300
