Modulating Protein Interactions by Rational and Computational Design

2009 ◽  
pp. 357-380
2015 ◽  
Vol 112 (34) ◽  
pp. 10714-10719 ◽  
Author(s):  
Yun Mou ◽  
Po-Ssu Huang ◽  
Fang-Ciao Hsu ◽  
Shing-Jong Huang ◽  
Stephen L. Mayo

Homodimers are the most common type of protein assembly in nature and have distinct features compared with heterodimers and higher order oligomers. Understanding homodimer interactions at the atomic level is critical both for elucidating their biological mechanisms of action and for accurate modeling of complexes of unknown structure. Computation-based design of novel protein–protein interfaces can serve as a bottom-up method to further our understanding of protein interactions. Previous studies have demonstrated that the de novo design of homodimers can be achieved to atomic-level accuracy by β-strand assembly or through metal-mediated interactions. Here, we report the design and experimental characterization of a α-helix–mediated homodimer with C2 symmetry based on a monomeric Drosophila engrailed homeodomain scaffold. A solution NMR structure shows that the homodimer exhibits parallel helical packing similar to the design model. Because the mutations leading to dimer formation resulted in poor thermostability of the system, design success was facilitated by the introduction of independent thermostabilizing mutations into the scaffold. This two-step design approach, function and stabilization, is likely to be generally applicable, especially if the desired scaffold is of low thermostability.


2012 ◽  
Vol 80 (10) ◽  
pp. 2426-2436 ◽  
Author(s):  
Chioko Nagao ◽  
Nozomi Izako ◽  
Shinji Soga ◽  
Samia Haseeb Khan ◽  
Shigeki Kawabata ◽  
...  

2013 ◽  
Vol 41 (5) ◽  
pp. 1141-1145 ◽  
Author(s):  
Timothy M. Jacobs ◽  
Brian Kuhlman

The computer-based design of PPIs (protein–protein interactions) is a challenging problem because large desolvation and entropic penalties must be overcome by the creation of favourable hydrophobic and polar contacts at the target interface. Indeed, many computationally designed interactions fail to form when tested in the laboratory. In the present article, we highlight strategies our laboratory has been pursuing to make interface design more tractable. Our general approach has been to make use of structural motifs found in native proteins that are predisposed to interact with a particular binding geometry, and then further bolster these anchor points with favourable hydrophobic contacts. We describe the use of three different anchor points, i.e. β-strand pairing, metal binding and the docking of α-helix into a groove, to successfully design new interfaces. In several cases, high-resolution crystal structures show that the design models closely match the experimental structure. In addition, we have tested the use of buried hydrogen-bond networks as a source of affinity and specificity at interfaces. In these cases, the designed complexes did not form, highlighting the challenges associated with designing buried polar interactions.


2021 ◽  
Author(s):  
Longxing Cao ◽  
Brian Coventry ◽  
Inna Goreshnik ◽  
Buwei Huang ◽  
Joon Sung Park ◽  
...  

The design of proteins that bind to a specific site on the surface of a target protein using no information other than the three-dimensional structure of the target remains an outstanding challenge. We describe a general solution to this problem which starts with a broad exploration of the very large space of possible binding modes and interactions, and then intensifies the search in the most promising regions. We demonstrate its very broad applicability by de novo design of binding proteins to 12 diverse protein targets with very different shapes and surface properties. Biophysical characterization shows that the binders, which are all smaller than 65 amino acids, are hyperstable and bind their targets with nanomolar to picomolar affinities. We succeeded in solving crystal structures of four of the binder-target complexes, and all four are very close to the corresponding computational design models. Experimental data on nearly half a million computational designs and hundreds of thousands of point mutants provide detailed feedback on the strengths and limitations of the method and of our current understanding of protein-protein interactions, and should guide improvement of both. Our approach now enables targeted design of binders to sites of interest on a wide variety of proteins for therapeutic and diagnostic applications.


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