Biology subjects

Elazar, A.

Publications and source records attributed to Elazar, A..

4 recordsLinked to original sources

bioRxiv2022

Computational design of BclxL inhibitors that target transmembrane domain interactions

Several methods have been developed to explore interactions among water-soluble proteins or regions of proteins. However, techniques to target transmembrane domains have not been examined thoroughly. Here we developed a novel computational approach to design transmembrane 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 Bcl2 family through the transmembrane domain and that these interactions are necessary for BclxL control of cell death. Next, we designed sequences that specifically recognize and sequester the transmembrane domain of BclxL. Hence, we were able to prevent BclxL intra-membrane interactions and cancel its anti-apoptotic effect. These results advance our understanding of protein-protein interactions in membranes and provide new means to modulate them. Moreover, the success of our approach may trigger the development of a new generation of inhibitors targeting interactions between transmembrane domains.

biochemistry↗

bioRxiv2020

De novo designed receptor transmembrane domains enhance CAR-T cell cytotoxicity and attenuate cytokine release

De novo designed receptor transmembrane domains (TMDs) present opportunities for precise control of cellular receptor functions. We developed a de novo design strategy for generating programmed membrane proteins (proMPs): single-pass -helical TMDs that self-assemble through computationally defined and crystallographically validated interfaces. We used these proMPs to program specific oligomeric interactions into a chimeric antigen receptor (CAR) and found that both in vitro CAR T cell cytokine release and in vivo antitumor activity scaled linearly with the oligomeric state encoded by the receptor TMD, from monomers up to tetramers. All programmed CARs (proCARs) stimulated substantially lower T cell cytokine release relative to the commonly used CD28 TMD, which we show elevated cytokine release through lateral recruitment of the endogenous T cell costimulatory receptor CD28. Precise design using orthogonal and modular TMDs thus provides a new way to program receptor structure and predictably tune activity for basic or applied synthetic biology.

synthetic biology↗

bioRxiv2019

A lipophilicity-based energy function for membrane-protein modelling and design

Membrane-protein design is an exciting and increasingly successful research area which has led to landmarks including the design of stable and accurate membrane-integral proteins based on coiled-coil motifs. Design of topologically more complex proteins, such as most receptors, channels, and transporters, however, demands an energy function that balances contributions from intra-protein contacts and protein-membrane interactions. Recent advances in water-soluble all-atom energy functions have increased the accuracy in structure-prediction benchmarks. The plasma membrane, however, imposes different physical constraints on protein solvation. To understand these constraints, we recently developed a high-throughput experimental screen, called dsT{beta}L, and inferred apparent insertion energies for each amino acid at dozens of positions across the bacterial plasma membrane. Here, we express these profiles as lipophilicity energy terms in Rosetta and demonstrate that the new energy function outperforms previous ones in modelling and design benchmarks. Rosetta ab initio simulations starting from an extended chain recapitulate two-thirds of the experimentally determined structures of membrane-spanning homo-oligomers with <2.5 [A] root-mean-square deviation within the top-predicted five models. Furthermore, in two sequence-design benchmarks, the energy function improves discrimination of stabilizing point mutations and recapitulates natural membrane-protein sequences of known structure, thereby recommending this new energy function for membrane-protein modelling and design.

biochemistry↗

bioRxiv2018

Chance and pleiotropy dominate genetic diversity in complex bacterial environments

How does environmental complexity affect the evolution of single genes? Here, we measured the effects of a set of mutants of Bacillus subtilis glutamate dehydrogenase across 19 different environments - from homogenous single cell populations in liquid media to heterogeneous biofilms, plant roots and soil communities. The effects of individual gene mutations on organismal fitness were highly reproducible in liquid cultures. Strikingly, however, 84% of the tested alleles showed opposing fitness effects under different growth conditions (environmental pleiotropy). In biofilms and soil samples, different alleles dominated in parallel replica experiments. Accordingly, we found that in these heterogeneous cell communities the fate of mutations was dictated by a combination of selection and drift. The latter relates to programmed prophage excisions that occurred along biofilm development. Overall, per individual condition, by the combined action of selection, pleiotropy and chance, a wide range of glutamate dehydrogenase mutations persisted and sometimes fixated. However, across longer periods and multiple environments, nearly all this diversity would be lost - indeed, considering all environments and conditions we have tested, wild-type is the fittest allele.

microbiology↗