RESEARCH: COVID-19
FOLDING PROJECT #17309 PROFILE

This project studies how the SARS-CoV-2 spike protein binds to human cells. By simulating these proteins, researchers want to understand how sugar molecules on the virus affect its shape and binding ability. This knowledge could help develop new drugs against 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: these projects are replacing 17304-6, as 17304-6 had to be stopped due to work server issues.

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SARS-CoV-2

Severe acute respiratory syndrome coronavirus 2

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

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receptor binding domain (RBD)

Receptor Binding Domain

The receptor binding domain (RBD) is a part of the spike protein on SARS-CoV-2 that binds to the ACE2 receptor on human cells, allowing the virus to infect.

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ACE2

Angiotensin-converting enzyme 2

ACE2 is a protein found on the surface of many human cells. It plays a role in regulating blood pressure and other bodily functions. The SARS-CoV-2 virus uses ACE2 as its entry point into human cells.

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glycosylation

The addition of sugar molecules to proteins or other biomolecules.

Glycosylation is a process where sugar molecules are attached to proteins. This can affect how proteins fold, interact with other molecules, and function.

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Markov State Models

Mathematical models used to describe the probabilistic transitions between different states of a system.

Markov State Models are computer simulations that help us understand how molecules move and change over time. They are used in drug discovery to study protein interactions and design new drugs.

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metastable states

Stable but transient states of a system that can persist for a certain amount of time before transitioning to another state.

Metastable states are like temporary resting places that molecules can occupy. Understanding these states is important for drug design because it can help us predict how proteins will behave when bound to a drug.