RESEARCH: CANCER
FOLDING PROJECT #17650 PROFILE

This project explores new ways to find useful shapes of proteins for cancer drug discovery. Traditional methods are slow and rely on luck. Adaptive Seeding uses multiple starting protein shapes to explore more of the possible shapes faster, potentially finding better drug targets.

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.

---

Drug discovery

The process of identifying and developing new medications.

Drug discovery is the complex journey of finding and creating new medicines. It involves many steps, from identifying a target (like a protein involved in disease) to testing potential drugs and eventually bringing them to market.

---

Cancer

A group of diseases characterized by the uncontrolled growth and spread of abnormal cells.

Cancer is a serious illness where cells in the body grow uncontrollably. This can damage organs and tissues, leading to various health problems. There are many types of cancer, each affecting different parts of the body.

---

Protein

Large biomolecules essential for various biological processes.

Proteins are the building blocks of life. They perform many crucial functions in our bodies, such as transporting molecules, catalyzing reactions, and providing structural support.

---

Drug design

The process of creating new drugs by modifying existing molecules or designing novel ones.

Drug design involves scientists using their knowledge of biology and chemistry to create new medications. They aim to develop drugs that can effectively target specific diseases while minimizing side effects.

---

Inhibitor

A substance that slows down or blocks the activity of a specific enzyme or protein.

Inhibitors are molecules that can stop or reduce the action of other molecules, like enzymes. This can be helpful in treating diseases by blocking harmful processes.

---

Folding@home

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

Folding@home is a massive scientific project that harnesses the power of many computers to simulate how proteins fold. This helps researchers understand how proteins work and develop new drugs.

---

Adaptive methods

Algorithms that adjust their parameters based on the data they are processing.

Adaptive methods are computer programs that learn and improve as they work. They can be used in various fields to find better solutions or make more accurate predictions.

---

Adaptive Seeding

A technique used in protein folding simulations to improve exploration of conformational space.

Adaptive Seeding is a strategy used in computer simulations to explore different shapes that proteins can take. It involves starting the simulation from multiple points, which helps find more diverse and useful protein structures.