Lecture Notes: Conversation with Professor Michael Levitt

Introduction

Special series of conversations featuring personalities from various campuses.
Today's guest: Professor Michael Levitt, Nobel laureate in Chemistry 2013, professor of structural biology at Stanford University.

Born in Pretoria, South Africa; grew up in South Africa, moved to the UK, then to Israel, and finally to Stanford in 1987.
Curiosity in science developed from an early age, influenced by his mother.
Had a playful childhood, initially more interested in social activities than academics.

Emphasizes luck as a significant factor in achieving the Nobel Prize.
His mother's commitment to education played a crucial role in his academic journey.
Education path:
- Skipped school to graduate early.
- At 17, attended King's College in London, focusing on physics.
- Worked with notable scientists, including Francis Crick and Max Perutz.
His discovery was largely based on computational biology during the 1970s, linking computers with biological processes.
His research led to the Nobel Prize, citing a connection between early childhood experiences and significant scientific achievements.

Discusses the unpredictability of success in science and the role of serendipity.
Importance of multidisciplinary approaches in breaking down academic silos.
Stanford's BioX program aims to foster interdisciplinary collaboration.

Molecular dynamics used to understand protein movement.
Emphasizes the importance of viewing proteins in motion rather than as static structures.
Computers play a pivotal role in modern biology and crystallography.
Talks about the evolution of computers and their impact on scientific research.

AI and machine learning have always been part of his work; sees them as tools for scientific advancement.
AI's ability to summarize and analyze large datasets has been transformative.
Reflects on the importance of curiosity and continuous learning in science.

Discusses the intersection of personal experiences and global issues like the COVID-19 pandemic.
Critiques the response to COVID-19, focusing on data analysis and societal reactions.
Believes in the resilience of humanity and the potential for improvement through technology.

Analyzed COVID-19 data early on, noting that most deaths were among older individuals with comorbidities.
Compared current pandemic responses with historical pandemics, suggesting more rational approaches.
Advocated for a balanced view of health risks and societal impacts from COVID-19.

Discussed differences between mRNA and traditional vaccines.
Expressed concerns about the speed of vaccine development and potential side effects.
Stressed the importance of robust data collection post-vaccine rollout.

Encourage curiosity, openness to new opportunities, and the importance of loving what you do.
Emphasizes that making mistakes is part of the learning process and necessary for growth.
Notes the importance of diversity in scientific inquiry and collaboration.

Concludes with a call for young people to embrace curiosity, pursue their passions, and be willing to challenge the status quo.
Highlights the role of technology, like AI, in enhancing human capabilities and fostering creativity.