M Michael Gromiha 
PROTEIN MUTATIONS [EPUB ebook] 
Consequences on Structure, Functions, and Diseases

Proteins perform various functions in living organisms. However, any mutation in the amino acid residues of a protein affects its structure and function. Some of these mutations may lead to diseases. These disease-causing mutations have an impact on protein structure, stability, and its binding affinity to complexes. Moreover, the study of amino acid mutation in proteins is important for developing therapeutic strategies. It is a pertinent and timely endeavor to provide comprehensive insights on the consequences of these mutations.

The main highlights of this book are the effects of protein mutations on its various functions such as aggregation, folding, stability, binding affinity, and diseases, as well as a wide range of applications such as database development, computational algorithms, and drug design. It will be a platform to provide the up-to-date information and latest developments in the field and will serve as a single resource to get the information on comparative studies to delineate these mutational effects on protein folding, stability, and interactions, and for understanding the molecular basis of diseases.

Contents:

• Preface


• Acknowledgements


• Protein Structure, Folding, and Stability:
  
  
  
  • Deciphering the Modulatory Role of Mutations in Protein Aggregation Through In Silico Methods (R Prabakaran, Puneet Rawat, Sandeep Kumar, and M Michael Gromiha)
  
  
  • Computational Resources for Understanding and Predicting the Stability of Proteins Upon Mutations (P Ramakrishna Reddy, A Kulandaisamy, and M Michael Gromiha)
  
  
  • Exploring Important Factors Influencing the Folding Rates of Proteins and Their Mutants (Liang-Tsung Huang)
  
  
  • Computational Approaches for Understanding Protein Disorder Upon Mutation: Databases, Algorithms and Applications (Dhanusha Yesudhas, Ambuj Srivastava, S Lekshmi, and M Michael Gromiha)
  
  


• Protein Function and Binding Affinity:
  
  
  
  • Binding Affinity Changes Upon Mutation in Protein–Protein Complexes (Rahul Nikam, Fathima Ridha, Sherlyn Jemimah, Kumar Yugandhar, and M Michael Gromiha)
  
  
  • Bioinformatics Approaches for Understanding the Consequences of Mutations to the Binding Affinity of Protein–DNA Complexes (K Harini, Amit Phogat, and M Michael Gromiha)
  
  
  • Computational Resources for Understanding the Effect of Mutations in Binding Affinities of Protein–RNA Complexes (K Harini, Sowmya Ramaswamy Krishnan, M Sekijima, and M Michael Gromiha)
  
  
  • Computational Analysis on the Effect of Mutations for the Binding Affinity of Protein–Carbohydrate Complexes (N R Siva Shanmugam, S Lekshmi, and M Michael Gromiha)
  
  
  • Elucidating the Effects of Mutations on Protein Function (Govindarajan Sudha, and M Michael Gromiha)
  
  


• Disease Causing Mutations:
  
  
  
  • Computational Resources for Understanding Disease-Causing Mutations in Proteins: Applications to HIV (Sankaran Venkatachalam, Amit Phogat, and M Michael Gromiha)
  
  
  • Databases and Computational Algorithms for Identifying Cancer Hotspot Residues and Mutations in Proteins (Medha Pandey, Suraj Kumar Shah, and M Michael Gromiha)
  
  
  • Experimental and Computational Approaches for Deciphering Disease-Causing Mutations in Membrane Proteins (A Kulandaisamy, P Ramakrishna Reddy, Dmitrij Frishman, and M Michael Gromiha)
  
  
  • Decoding the Evolution of COVID-19 Through Mutational Studies on SARS-Co V-2 (Divya Sharma, Puneet Rawat, and M Michael Gromiha)
  
  
  • Transcriptome-Based Analysis for Understanding the Effects of Mutations in Neurodegenerative Diseases (Nela Pragathi Sneha, S Akila Parvathy Dharshini, Y-H Taguchi, and M Michael Gromiha)
  
  

Readership: Graduate Students and Researchers in Bioinformatics and Computational Biology.

Key Features:

• Single, unique source with concepts and applications to understand the mutational effects on protein structure, functions, and diseases


• Edited by an outstanding researcher, who significantly contributed on various aspects of protein mutations, with easily understandable illustrations


• A compilation of databases and online tools


• Provides systematic approaches for analysis and interpretation of mutation data


• Explains major sequence- and structure-based features for developing algorithms


• Applications of machine learning techniques to understand the consequences of mutations in proteins


• Up-to-date literature with latest developments