Computational design of BclxL inhibitors that target transmembrane domain interactions

Abstract

Several methods have been developed to explore interactions among water-soluble proteins or regions of proteins. However, techniques to target transmembrane domains (TMDs) have not been examined thoroughly despite their importance. Here, we developed a computational approach to design sequences that specifically modulate protein–protein interactions in the membrane. To illustrate this method, we demonstrated that BclxL can interact with other members of the B cell lymphoma 2 (Bcl2) family through the TMD and that these interactions are required for BclxL control of cell death. Next, we designed sequences that specifically recognize and sequester the TMD of BclxL. Hence, we were able to prevent BclxL intramembrane interactions and cancel its antiapoptotic effect. These results advance our understanding of protein–protein interactions in membranes and provide a means to modulate them. Moreover, the success of our approach may trigger the development of a generation of inhibitors targeting interactions between TMDs.

De novo-designed transmembrane proteins bind and regulate a cytokine receptor

“…1 ). There is little experimental evidence to date concerning the sequence−structure principles for how to encode the antiparallel interaction of small-X 6 -small TM domains 31 , 35 , 36 , contrasting with previous designs that relied heavily on receptor mimicry 19 or well-known sequence motifs for encoding TM interactions, for example, GxxxG 11 , 17 . Thus, we tested the ability of the data-driven modeling approach to effectively encode a CHAMP sequence de novo through specific complementary interactions with the target’s unique TM molecular surface in defining the desired complex.…”

“…Specific CHAMP algorithm adjustments 11 included (1) implementation in RosettaMP to increase user accessibility; (2) ranking designs on interface packing over Rosetta energy scores; and (3) using an idealized structural bioinformatics-derived molecular model for the CHAMP−mEpoR complex, versus natural templates. Finally, human visual evaluation was cited as critical in past designs 11 , 19 but introduces user disparities and limits reproducibility. Our adaptations automate model building, design and final sequence ranked selection, facilitating broader community use.…”

“…The first proof-of-concept de novo design debuted the computed helical antimembrane protein (CHAMP) algorithm, wherein engineered TM peptides bound and selectively distinguished two highly similar single-pass integrin TM domains via association of mutual high-affinity TM GxxxG dimerization motifs presented on both the binder and target TM domains 11 , 17 . Computational design-informed mutagenesis was recently shown to be effective in improving the potency of natural TM domain mimic polypeptides inhibiting protein homo-oligomerization events 18 , 19 .…”

Interaction of Substrates with γ-Secretase at the Level of Individual Transmembrane Helices—A Methodological Approach

“…Approach 2 is thus a promising way of economically exploring a multitude of potential heterotypic TMD interactions. Apart from substrate enzyme interactions in intramembrane proteolysis, the efficient detection of heterotypic TMD−TMD interactions may also prove useful in other biological contexts [ 53 , 54 , 55 ].…”