2022 Undergraduate Research Symposium: Neel Patel and Mariana Sierra The Kristen Rat Sarcoma (KRAS) protein, encoded by the KRAS gene, is a signal transducer that plays a crucial role in regulating cell proliferation. KRAS mutations have been known to cause lung, colorectal, and pancreatic cancers. Previously, KRAS was considered an “undruggable” target. However, with better understanding of the protein’s biology paired with advanced new technologies, the FDA approved the first KRAS inhibitor (sotorasib) for lung cancer patients with the KRASG12C mutation in 2021, expressing the recent interest of targeted drugs for KRAS. In clinical trials, sotorasib proved ineffective for pancreatic and colorectal cancers with the G12C mutation. Irrespective of mutant identity, oncogenic KRAS requires activation by the guanine nucleotide exchange factor (GEF) Son of Sevenless 1 (SOS1), highlighting an exploitable vulnerability with broad therapeutic applicability. The goal of this study is to develop novel pan-KRAS inhibitors by targeting the KRAS-SOS1 interactions through computational modeling. To start, we applied Gaussian accelerated molecular dynamics (GaMD) simulation, an advanced conformational sampling method, to collect the nature of the KRAS protein motion in solution. Then, the clustering analysis method was used to assemble KRAS conformational structures into ten groups for later virtual screening and docking simulations. We aim to address 20 to 30 compounds to later be experimentally assessed for their (1) ability to disrupt the KRAS-SOS1 interactions and (2) cytotoxicity in KRAS mutation-bearing cell lines. The work will provide insights in the drug efficacy of KRAS inhibitors and give rise to a novel set of KRAS candidates to be used in clinical oncogenic treatments.

1. Identification of Novel
Inhibitors Targeting KRAS-
SOS1 Interactions by
Structure-Based Drug
Design
Neel Patel; Mindy Huang; Mariana Sierra

2. INTRODUCTION
• KRAS mutants responsible for large majority
of cancers
• Previous efforts to target KRAS specific
mutations have clinincaly underperformed due
to strong patient resistance
García-Olmo D. (2017) KRAS. In: Schwab M. (eds) Encyclopedia of Cancer. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-
662-46875-3_6870
Goal: Develop a KRAS-SOS1 interaction inhibitor
through computational tools such as molecular dynamics,
clustering analysis, and molecular docking/screening

3. Methods

4. Methods :
• Molecular Dynamics (MD) is a
computationally deterministic method used to
capture biomolecules’ nature in solutions
• Gaussian Accelerated Molecular Dynamics
(GaMD) simulations were created
• Conventional MD with additional energy input
allows us to sample more protein conformations
Molecular Dynamics Simulations
Clustering Analysis
• Allows the grouping of a trajectory into
similar clusters to drastically reduce
number of distinct frames

5. Methods :
• Virtual Screening consists of the ability to analyze large compound databases and filter these into potential inhibitors
• Each compound is assigned a dockig score to which binding strength is correlated to
Virtual Screening and Molecular Docking

6. Results:
• GaMD simulations have been performed for a
total of 1 microsecond on each of the three
structures
• Simulatoins were run with constant number of
particles, pressure, and temperature to
maintain biological accuracy
• Upon visual review, computational prediction
of KRAS conformations is determined to be
successful
GaMD motion picture for one frame of the NMR structure of KRAS
with residues within 6 Å of binding site highlighted in red
Molecular Dynamics Simulations

7. Results:
• Clustering anlaysis of the simulations
predicted 10 clusters in which similar
frames of the simulation were assigned to
Clustering Analysis
• Decreases computational cost while
maintaining biological accuracy
• Clusters will be used for virtual screening
and molecular docking in the future
NMR Frame 1 NMR Frame 5 Crystal Structure
Middle structures for first three clusters per KRAS structure is shown above with the binding site highlighted in red

8. Future Directions & Limitations
• What compound library should one use?
• Virtual screening and molecular docking simulations will
be performed on the binding sites of the three selected
KRAS structures
• Once potential inhibitors are predicted, each will be
tested on oncogenic KRAS cell lines
• Return to MD to verify hit compound results

9. Acknowledgements
PI: Mindy Huang
ymhuang@wayne.edu
Thank you to Dr. Huang and Mariana
for serving as mentors during the
study
Check out our lab!
www.ymhuanglab.wayne.edu/
Contact me:
Neel Patel: neelpatel1022@wayne.edu