Research 13

Coding the Building Blocks of Life: How BIOL 172 Brings Supercomputing into Biology 

Inside SCU’s redesigned molecular biology course where students use Python and high performance computing to simulate proteins, model disease, and explore biology at the atomic level. 

BIOL 172 at Santa Clara University reimagines molecular biology as a computational science. By integrating Python programming and high performance computing resources, Dr. Michelle McCully has redesigned the course to give students a hands-on way to explore how biological molecules behave, move, and interact at the atomic level. What was once primarily theoretical now becomes an interactive space for computational discovery. 

Modeling the Machines of Life 

BIOL 172, or Molecular Modeling, treats proteins as dynamic machines rather than static images in a textbook. Students in the course learn to understand how these molecules move and interact using the laws of physics. Specifically, they apply Newtonian mechanics to calculate the forces that individual atoms exert on one another within a protein.

The SARS-CoV-2 main protease visualized in PyMOL, generated from data simulated in BIOL 172 

To perform these complex tasks, students use Python, a versatile and widely used coding language. Alongside molecular viewers like PyMOL, Python allows students to manipulate and visualize biological structures in a digital environment. This computational approach gives them a deeper understanding of biological systems, observing phenomena that are too small to see with even the strongest microscope. 

A Strategic Shift Toward Computation 

The decision to redesign the course and integrate Python was driven by a need for departmental standardization and future readiness. Dr. McCully integrated Python programming for two key reasons: 

• To standardize coding across biology courses and build a consistent foundation for students 
• To equip students with a high-demand, career-ready skill beyond the classroom Beyond the classroom, Dr. McCully recognized that molecular modeling is a specialized field. Her goal is to ensure students walk away with a coding language they can confidently move forward with after graduation.

The Essential Power of WAVE HPC 

The high performance computing power of the WAVE cluster is a fundamental requirement for the course. Molecular dynamics simulations involve massive amounts of data and constant mathematical calculations. According to Dr. McCully, these simulations are far beyond the capabilities of a standard computer — running this level of work on a typical laptop would take months to complete. 

Before the university's WAVE HPC cluster was available, the course relied on national-level supercomputing grants. The transition to WAVE has been transformative. Using Open OnDemand, students can access a user-friendly graphical interface, allowing them to focus on learning how to apply scientific tools instead of just struggling with the mechanics of the tools themselves. 

"The difference after introducing WAVE was night and day." 

— Dr. Michelle McCully 

Hands-on Research: The COVID Protease Project 

The student experience in BIOL 172 is defined by real-world application. A key example is the SARS-CoV-2 protease project, which focuses on the virus that causes COVID-19. Students use Jupyter Notebooks on the cluster to simulate how drugs can bind to viral proteins to stop them from multiplying.

A potential drug inhibitor (cyan, sticks) docking into the SARS-CoV-2 main protease (pink, ribbons) 

During the lab, students engage in drug docking — choosing and testing various compounds to see if they fit into the active site of the protein. This process mirrors actual computational drug design, the same method used by scientists to develop effective treatments for global health crises. 

Impact on Student Learning and Confidence 

The redesign has led to a significant shift in student engagement and confidence. BIOL 172 attracts students from a range of disciplines, including: 

• Biology 
• Neuroscience 
• Biochemistry 
• Bioengineering 

While some arrive with significant computer science backgrounds, many have never coded before. Dr. McCully effectively teaches the basics of Python in just a few weeks, allowing students to bridge the gap between their scientific knowledge and technical application.

Students gain the confidence to read and understand code, ensuring they can use modern technology as a tool for research rather than a replacement for their own critical thinking. 

The Future of Interdisciplinary Science 

The success of BIOL 172 highlights the growing importance of high performance computing in life sciences education. By moving biology from the petri dish to the server, Santa Clara University is preparing the next generation of researchers to tackle complex biological problems with modern computational tools. 

As biology continues to become more data-driven, the skills learned in BIOL 172 will remain a vital asset for students entering the evolving world of scientific discovery. 

Based on an interview conducted by Ella Griffin, WAVE Student Marketing Assistant, May 19, 2026.