Computational and Experimental Approaches in Protein Engineering and Design

Dr Aditya Kumar Padhi is an Assistant Professor at the School of Biochemical Engineering, Indian Institute of Technology (IIT-BHU), Varanasi, India. He earned his Ph.D. from the Indian Institute of Technology, Delhi (IIT Delhi) in 2015 and currently leads the Laboratory for Computational Biology and Biomolecular Design (LCBD) at IIT-BHU. His lab specializes in Computational Biology, Protein Design, Structural and Translational Informatics, Computational Biophysics, Antimicrobial Resistance, Predictive Modelling, Biomolecular Simulations, Conformational Analyses, Machine Learning, and Disease Mechanisms Professor Timir Tripathi is a Professor of Molecular Biology, School of Life Sciences, North-Eastern Hill University, Shillong, India. Earlier, he served as the Regional Director of Indira Gandhi National Open University. His previous role was Senior Assistant Professor and Principal Investigator at the Department of Biochemistry, NEHU, Shillong. He holds a Ph.D. from Jawaharlal Nehru University, New Delhi. His primary research focus is studying the conformational dynamics, interaction, and stabilization of the complexes formed by intrinsically disordered neuropathological protein aggregates, their properties of liquid-liquid phase separation, interaction, and roles in nucleocytoplasmic transport in neurodegenerative diseases. Professor Tripathi is an Associate Fellow of the Indian National Science Academy, New Delhi, and an elected member of the National Academy of Sciences, India, the Royal Society of Chemistry, and the Royal Society of Biology, UK

• 1. Fundamentals of protein structure and function2. Introduction to the principles of protein engineering3. Computational methods and tools for protein design and optimization4. Experimental methods in protein engineering: techniques and applications5. Engineering antibodies for therapeutic applications6. Techniques and applications of directed evolution7. Machine learning and artificial intelligence in protein design8. Computational protein design for disease mutations and antimicrobial resistance9. Case studies in protein engineering: successes and challenges10. Designing protein-based vaccines for immunotherapy11. Nanobody engineering for next-generation therapeutics12. Molecular dynamics simulations in protein design and engineering13. Biophysical characterization methods for evaluating therapeutic proteins14. Incorporating non-natural amino acids in protein design and expanding the chemical space of proteins.15. Methods to enhance protein stability and solubility for improved functional efficacy16. Engineering allosteric regulation and control mechanisms in proteins17. Design of protein scaffolds for biomaterials and tissue engineering18. High-throughput screening techniques for identifying therapeutic proteins19. Advancements in protein conjugation techniques for engineering and design applications20. Challenges in AI-based approaches for intrinsically disordered proteins21. The role of machine learning in drug discovery and therapeutic protein design