RESEARCH: COVID-19
FOLDING PROJECT #17328 PROFILE

This project studies how the spike protein of the virus that causes COVID-19 (SARS-CoV-2) attaches to human cells. Researchers are using computer simulations to see how the protein changes shape and interacts with its target, ACE2. They hope to understand how sugars on the protein affect its behavior and how binding to ACE2 alters its shape. This knowledge could help in designing new drugs to fight COVID-19.

Note: This TLDR is a simplication and may not be 100% accurate.

These projects involve the SARS-CoV-2 receptor binding domain (RBD) and its target receptor in humans, ACE2.

We are simulating these proteins alone and in complex with each other (and with and without glycosylation).

We will build Markov State Models using the Fah simulation data, which will help us identify the metastable states of each protein/protein complex.

Given these experiments, we hope to be able to explain the impact of glycosylation on RBD conformational dynamics as well as identify whether there are shifts in metastable states upon RBD:ACE2 binding.

Ultimately, the knowledge gained here will help infom drug design efforts. Note: 17313-6 replace 17307-9, as 17307-9 used a different, less stable integrator.

---

SARS-CoV-2

Severe acute respiratory syndrome coronavirus 2.

SARS-CoV-2 is the virus responsible for causing COVID-19. It's a type of coronavirus that spreads easily from person to person through respiratory droplets.

---

Receptor Binding Domain (RBD)

Receptor Binding Domain

The RBD is a specific part of the SARS-CoV-2 spike protein that binds to the ACE2 receptor on human cells, allowing the virus to enter and infect them.

---

ACE2

Angiotensin-converting enzyme 2

ACE2 is a protein found on the surface of many human cells. The SARS-CoV-2 RBD binds to ACE2, allowing the virus to enter and infect cells.

---

Glycosylation

The addition of sugar molecules to proteins.

Glycosylation is a common process in which sugar molecules are attached to proteins. It can affect protein folding, stability, and function.

---

Markov State Model

A statistical model used to describe the behavior of complex systems over time.

Markov State Models are used in computational biology to simulate and analyze the movement and interactions of molecules. They can help researchers understand how proteins fold, interact with each other, and function.

---

Metastable States

Transient states that a system can occupy before transitioning to another state.

Metastable states are like temporary resting points in the movement of molecules. Understanding these states can help researchers predict how proteins will behave and function.