RESEARCH: CANCER
FOLDING PROJECT #17649 PROFILE

This project is about finding new ways to design cancer drugs. Drug discovery often involves exploring different shapes of proteins, but this can take a long time even with powerful computers. The project explores using 'seeding' strategies to start the exploration process in different places, hoping to find useful protein shapes faster and more efficiently.

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

In drug discovery, particularly that of cancer, maximizing state exploration is a useful novel strategy – providing new protein states and conformations to point drug design methods at increases the likelihood that a potential binder and inhibitor may be found. However, in many cases a new state that is "useful for design" (ie.

ones distinct enough to be worth targeting to identify novel drugs) require a lot of sampling or simulation.

Sometimes, even exascale computers like Folding@home are not enough! Adaptive methods are very powerful here, but have the drawback of requiring system knowledge, or having to guess which protein features are worth adaptively exploring on, which may not always turn out to be true. Identifying druggable states or exploring conformational state space relevant to disease is an existing challenge.

The embarassingly parallel nature of Folding@home allows us to massively scale up our exploration.

However, the underlying methods still rely on luck to a large extent – we must discover the states in work units as the dataset grows in size and more work units are run.

This can be an incredibly inefficient process, wasting work units on regions of state space that are irrelevant or uninteresting to the question at hand.

Adaptive Seeding is a way to tackle this inefficiency.

Rather than applying a "boost" potential that alters the physics of our system, or having to do live-streamed analysis like Adaptive sampling, Adaptive Seeding sets up multiple starting structures across conformational space.

The intention is that having multiple distinct starting structures will increase the rate at which the landscape is traversed and lead to transitions/pathways connecting functional states in less simulation time, while preserving physics.

These projects seek to test different "seeding" approaches that yielded a different spread of starting structures.

Each unique structure starts at a different RUN.

As with other projects, we will be studying MET kinase.

17645: Run using starting structures generated using AI-methods like AlphaFold2
17646: Run using starting structures that are stemmed from "fixing" experimentally derived structures in the PDB
17649: A clone of 17645 but with 20X higher saving frequency for higher resolution dynamics
17650: A clone of 17650 but with 20X higher saving frequency for higher resolution dynamics.

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Drug discovery

The process of identifying and developing new medications.

Drug discovery is the complex process scientists use to find and develop new medications. It involves many steps, from identifying a potential drug target (like a protein involved in disease) to testing the drug's safety and effectiveness.

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Cancer

A group of diseases involving abnormal cell growth with the potential to invade or spread to other parts of the body.

Cancer is a broad term for diseases caused by uncontrolled cell growth. These cells can divide and spread rapidly, damaging healthy tissues and organs. There are many types of cancer, each affecting different parts of the body.

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Protein

A large biomolecule composed of amino acids, essential for various biological functions.

Proteins are the building blocks of life. They are made up of chains of smaller molecules called amino acids. Proteins perform many important tasks in our bodies, such as transporting oxygen, fighting infections, and breaking down food.

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Drug design

The process of creating and optimizing new medications using computer modeling and other techniques.

Drug design is a complex process that involves designing molecules that can interact with specific targets in the body to produce a desired effect. Scientists use computers and other tools to model these interactions and optimize the structure of potential drugs.

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Inhibitor

A molecule that binds to a target and reduces its activity.

Inhibitors are molecules that block or reduce the activity of other molecules. They are often used in medications to treat diseases by interfering with the function of harmful proteins.

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Folding@home

A distributed computing project that uses volunteer computing power to simulate protein folding.

Folding@home is a massive online project where people donate their computer's processing power to help scientists study how proteins fold. This helps researchers understand diseases and develop new drugs.

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Adaptive Seeding

A method for enhancing protein folding simulations by using multiple starting structures.

Adaptive Seeding is a technique used to speed up computer simulations of how proteins fold. Instead of starting with just one structure, researchers use many different starting points, which helps them explore the protein's possible shapes more efficiently.