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Breaking Leventhal's Paradox: How do proteins fold in milliseconds?
Protein folding has long been an important research topic in biology, especially in the field of structural biology. Recent research shows that the use of libraries of protein backbone fragments improves the efficiency of structure prediction, thereby breaking the traditional Leventhal paradox, which states that proteins cannot explore all possible combinations in a biologically reasonable time .
Why is protein folding so important?
The structure of a protein determines its function, and understanding the process of protein folding is critical to studying various biological processes and developing new treatments. However, depending on a protein's free energy map, the number of folding states it can assume grows exponentially. This makes accurate modeling of proteins a challenge in practice.
Proteins can assume thousands of states, and the corresponding test combinations are extremely large.
Taking advantage of protein fragment libraries
In order to effectively reduce the search space for protein folding, researchers began to use protein scaffold fragment libraries. These fragment libraries consist of short polypeptide fragments, typically between 5 and 15 residues in length. Fragments that do not contain side chains are more effective in focusing on the conformation of the main chain, and optimized structures can be found faster using these fragments.
Construction and application of fragment library
The construction of fragment libraries requires analysis of protein databases. First, a set of representative structures is selected, from which contiguous peptide sequences are extracted as fragments. These fragments are then clustered based on similarities in spatial structure to reduce the number of combinations that need to be considered. Through this approach, researchers can effectively reduce complexity to make model predictions faster.
The clustering process of fragments makes the constructed model more stable and consistent with realistic geometric structures.
Practical application of loop modeling
In homology modeling, fragment libraries are often used to predict loops in structures. These regions are often difficult to model because the space between them is difficult to estimate accurately. You can reduce the space that needs to be considered by modeling the loop area as a series of overlapping segments.
Balance of complexity and speed
Although using a fragment library can reduce the complexity of the search space, it is still an exponential increase. However, efficiency can be improved by taking advantage of the characteristics of short fragments. Using fragments of length no longer than 15 was able to capture approximately 91% of the fragments in the PDB, with an accuracy of only 2.0 angstroms.
This finding demonstrates that compiling efficient fragment libraries is critical to facilitate protein structure prediction.
Future research directions
With the advancement of computing technology, future protein structure prediction studies may rely more on fragment libraries to obtain accurate and rapid results. This will not only support basic biological research, but also accelerate the development and design of new drugs.
However, there are still many unknown areas waiting for researchers to explore, especially when following the assumption of local stable structures. Is this enough to cover the variable folding process of proteins?
