A Method for Assessing the Robustness of Protein Structures by Randomizing Packing Interactions.
|Title||A Method for Assessing the Robustness of Protein Structures by Randomizing Packing Interactions.|
|Publication Type||Journal Article|
|Year of Publication||2022|
|Authors||Yadahalli S, Jayanthi LP, Gosavi S|
|Journal||Front Mol Biosci|
Many single-domain proteins are not only stable and water-soluble, but they also populate few to no intermediates during folding. This reduces interactions between partially folded proteins, misfolding, and aggregation, and makes the proteins tractable in biotechnological applications. Natural proteins fold thus, not necessarily only because their structures are well-suited for folding, but because their sequences optimize packing and fit their structures well. In contrast, folding experiments on the designed Top7 suggest that it populates several intermediates. Additionally, in protein design, where sequences are designed for natural and new non-natural structures, tens of sequences still need to be tested before success is achieved. Both these issues may be caused by the specific scaffolds used in design, i.e., some protein scaffolds may be more tolerant to packing perturbations and varied sequences. Here, we report a computational method for assessing the response of protein structures to packing perturbations. We then benchmark this method using designed proteins and find that it can identify scaffolds whose folding gets disrupted upon perturbing packing, leading to the population of intermediates. The method can also isolate regions of both natural and designed scaffolds that are sensitive to such perturbations and identify contacts which when present can rescue folding. Overall, this method can be used to identify protein scaffolds that are more amenable to whole protein design as well as to identify protein regions which are sensitive to perturbations and where further mutations should be avoided during protein engineering.
|Alternate Journal||Front Mol Biosci|
|PubMed Central ID||PMC9271847|