Study and Analysis of Knowledgebase of Molecular Systems and to Develop Model for Prediction of Molecular Structure

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

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.