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Abstract AlphaFold2 has revolutionized protein structure prediction from amino‐acid sequence. In addition to protein structures, high‐resolution dynamics information about various protein regions is important for understanding protein function. Although AlphaFold2 has neither been designed nor trained to predict protein dynamics, it is shown here how the information returned by AlphaFold2 can be used to predict dynamic protein regions at the individual residue level. The approach, which is termed cdsAF2, uses the 3D protein structure returned by AlphaFold2 to predict backbone NMR NHS2order parameters using a local contact model that takes into account the contacts made by each peptide plane along the backbone with its environment. By combining for each residue AlphaFold2's pLDDT confidence score for the structure prediction accuracy with the predictedS2value using the local contact model, an estimator is obtained that semi‐quantitatively captures many of the dynamics features observed in experimental backbone NMR NHS2order parameter profiles. The method is demonstrated for a set nine proteins of different sizes and variable amounts of dynamics and disorder.
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Engineering gain‐of‐function mutants of a WW domain by dynamics and structural analysis
Abstract Proteins gain optimal fitness such as foldability and function through evolutionary selection. However, classical studies have found that evolutionarily designed protein sequences alone cannot guarantee foldability, or at least not without considering local contacts associated with the initial folding steps. We previously showed that foldability and function can be restored by removing frustration in the folding energy landscape of a model WW domain protein, CC16, which was designed based on Statistical Coupling Analysis (SCA). Substitutions ensuring the formation of five local contacts identified as “on‐path” were selected using the closest homolog native folded sequence, N21. Surprisingly, the resulting sequence, CC16‐N21, bound to Group I peptides, while N21 did not. Here, we identified single‐point mutations that enable N21 to bind a Group I peptide ligand through structure and dynamic‐based computational design. Comparison of the docked position of the CC16‐N21/ligand complex with the N21 structure showed that residues at positions 9 and 19 are important for peptide binding, whereas the dynamic profiles identified position 10 as allosterically coupled to the binding site and exhibiting different dynamics between N21 and CC16‐N21. We found that swapping these positions in N21 with matched residues from CC16‐N21 recovers nature‐like binding affinity to N21. This study validates the use of dynamic profiles as guiding principles for affecting the binding affinity of small proteins.
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- Award ID(s):
- 1901709
- PAR ID:
- 10451573
- Publisher / Repository:
- Wiley Blackwell (John Wiley & Sons)
- Date Published:
- Journal Name:
- Protein Science
- Volume:
- 32
- Issue:
- 9
- ISSN:
- 0961-8368
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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