Foldit – Man And His Ability To Solve Puzzles
Posted On May 15, 2020
Science is also using the gaming technology in their line of work. Scientists at the University of Washington have developed a game in which protein folding becomes a puzzle – Foldit(“Fold it”). The goal for every player is to crack the high score by minimizing the energy of the protein. You don’t need any previous biochemical knowledge. You will learn the different ways to edit the amino acid chain (pull apart, twist, fold back, and so on) in a playful manner with instructions in the first levels. The rest is more like a puzzle or a puzzle game. You face the competition of other players or even work in a team. Thus, many people search for the huge search space of possible 3D structures at the same time. The advantage, however, is not that many people deal with the problem at the same time (you could also simply distribute the calculation over many computers).
An Introduction to Foldit
Foldit is a puzzle game far from riot games such as Valorant which may often be used with some third party applications such as zaros boosting. Contrary to this effect, foldit requires only the players ability to solve the puzzle from all angles possible without real need of any third party application.
To make this a little more understandable, imagine the search space as a kind of landscape – ideally a mountain range. In this mountain, you want to climb the highest mountain; without knowing where it is. The highest mountain is the right result, so to speak. Many search algorithms are structured in such a way that they start at a random point and then always go uphill. For example, you can repeat this a hundred times and hopefully then have found the highest mountain. Perhaps you are only on the second-highest mountain, although the highest peak is right next to you.
First, you have to go back down to the highest mountain. The search algorithm cannot recognize this; he has no visual insight and is instructed to only ever go uphill.
The second advantage is the different search strategies that people use to solve problems. None of these strategies generally have to be the best. Different strategies can lead to success with different proteins. Some players are rather good at solving rough structures, others more fine structures.
The scientific goal of Foldit is not necessarily to decipher the structure of a single protein (although the players have already done that too). The goal is rather to look at the players’ approaches and to pack them into algorithms in order to be able to decode the structure of many proteins.
So you have already recognized in which areas the strengths of the players are and where the weaknesses. For example, people find it difficult to start folding from the simple chain shape. It is much easier to rearrange an existing structure.
If a player has the option of choosing from different balls as the starting point, he intuitively chooses the one closest to the solution. In places where algorithms would randomly decide the next step (for example, jumping to a random point on the map and walking uphill there again), people make smarter decisions than chance.