Methodological approaches for the analysis of transmembrane domain interactions: A systematic review

Duart, Gerard; Grau, Brayan; Mingarro, Ismael; Martínez-Gil, Luis

doi:10.1016/j.bbamem.2021.183712

Cited by 4 publications

(5 citation statements)

References 99 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Several methods have been described for the identification of TMD–TMD interactions, including in vitro, in vivo, and in silico approaches ( 41 ). To determine whether the TMD of BclxL interacts with other TMDs from the Bcl2 family, we chose BLaTM ( 14 ) and an adapted BiFC assay ( 25 ).…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Computational design of BclxL inhibitors that target transmembrane domain interactions

Duart

Elazar

Weinstein

et al. 2023

Proc. Natl. Acad. Sci. U.S.A.

Self Cite

View full text Add to dashboard Cite

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.

show abstract

Section: Discussionmentioning

confidence: 99%

“…BlaTM and BiFC assays were carried out as described previously ( 13 , 41 ). The design of the inhibitors was started with the modeling of the BclxL–BclxL homointeraction.…”

Section: Methodsmentioning

confidence: 99%

Computational design of BclxL inhibitors that target transmembrane domain interactions

Duart

Elazar

Weinstein

et al. 2023

Proc. Natl. Acad. Sci. U.S.A.

Self Cite

View full text Add to dashboard Cite

show abstract

“…Several methods have been described for the identification of TMD-TMD interactions, including in vitro, in vivo, and in silico approaches (61). To determine whether the TMD of BclxL interacts with other TMDs from the Bcl2 family, we chose BLaTM (19) and an adapted BiFC assay (24).…”

Section: Discussionmentioning

confidence: 99%

Computational design of BclxL inhibitors that target transmembrane domain interactions

Duart

Elazar

Weinstein

et al. 2022

Preprint

Self Cite

View full text Add to dashboard Cite

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.

show abstract

“…Some studies have been started to pay attention to probing TMP-TMP interactions. Duart et al made a systematic review of methodological approaches for the analysis of transmembrane domain interactions [ 41 ]. Khazen et al proposed PPIMem, a novel approach for predicting transmembrane protein-protein complexes [ 28 ].…”

Section: Introductionmentioning

confidence: 99%

Analysis and prediction of interactions between transmembrane and non-transmembrane proteins

Lu,

Jiang,

Chen

et al. 2024

BMC Genomics

View full text Add to dashboard Cite

Background Most of the important biological mechanisms and functions of transmembrane proteins (TMPs) are realized through their interactions with non-transmembrane proteins(nonTMPs). The interactions between TMPs and nonTMPs in cells play vital roles in intracellular signaling, energy metabolism, investigating membrane-crossing mechanisms, correlations between disease and drugs. Results Despite the importance of TMP-nonTMP interactions, the study of them remains in the wet experimental stage, lacking specific and comprehensive studies in the field of bioinformatics. To fill this gap, we performed a comprehensive statistical analysis of known TMP-nonTMP interactions and constructed a deep learning-based predictor to identify potential interactions. The statistical analysis describes known TMP-nonTMP interactions from various perspectives, such as distributions of species and protein families, enrichment of GO and KEGG pathways, as well as hub proteins and subnetwork modules in the PPI network. The predictor implemented by an end-to-end deep learning model can identify potential interactions from protein primary sequence information. The experimental results over the independent validation demonstrated considerable prediction performance with an MCC of 0.541. Conclusions To our knowledge, we were the first to focus on TMP-nonTMP interactions. We comprehensively analyzed them using bioinformatics methods and predicted them via deep learning-based solely on their sequence. This research completes a key link in the protein network, benefits the understanding of protein functions, and helps in pathogenesis studies of diseases and associated drug development.

show abstract

Methodological approaches for the analysis of transmembrane domain interactions: A systematic review

Cited by 4 publications

References 99 publications

Computational design of BclxL inhibitors that target transmembrane domain interactions

Computational design of BclxL inhibitors that target transmembrane domain interactions

Computational design of BclxL inhibitors that target transmembrane domain interactions

Analysis and prediction of interactions between transmembrane and non-transmembrane proteins

Contact Info

Product

Resources

About