RESEARCH: COVID-19
FOLDING PROJECT #17322 PROFILE

This project studies how sugar molecules (glycosylation) affect the shape and behavior of proteins involved in COVID-19 infection. By simulating these proteins, scientists aim to understand how glycosylation influences their interaction and identify potential drug targets.

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.

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SARS-CoV-2

Severe acute respiratory syndrome coronavirus 2

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

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Receptor Binding Domain (RBD)

The part of a virus protein that binds to a host cell receptor

The RBD is a region on the surface of some viral proteins that allows them to attach to specific receptors on host cells. This binding is essential for the virus to enter and infect the cell.

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ACE2

Angiotensin-converting enzyme 2

ACE2 is a protein found on the surface of many human cells. SARS-CoV-2 uses ACE2 as a receptor to enter and infect these cells.

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Glycosylation

The process of adding sugar molecules to proteins

Glycosylation is a common modification of proteins that can affect their structure, function, and stability. It plays a role in many biological processes, including immune response, cell signaling, and protein folding.

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Markov State Models

Mathematical models used to describe the dynamics of complex systems

Markov State Models are a type of computational tool used to simulate and analyze the behavior of complex systems over time. They are often applied in biophysics to study protein folding, molecular interactions, and cellular processes.

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Metastable States

Temporary, stable states of a system that are not its lowest energy state

Metastable states are like temporary resting points for complex systems. They represent configurations that are relatively stable but not the most stable. Understanding these states can help us understand how systems transition between different configurations and how they respond to changes.