Computational design of protein–protein interactions

Schreiber, Gideon; Fleishman, Sarel J.

doi:10.1016/j.sbi.2013.08.003

Cited by 57 publications

(53 citation statements)

References 49 publications

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“…Computational structure-based protein design is one of the most promising tools for engineering proteins with new functions, including the development of therapeutic proteins and protein assemblies [1–4]. Despite important successes, however, many of the current computational protein design tools often have low success rates, and designed proteins sometimes fail to achieve the functional properties of native proteins.…”

Section: Introductionmentioning

confidence: 99%

Algorithms for protein design

Gainza

Nisonoff

Donald

2016

Current Opinion in Structural Biology

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Computational structure-based protein design programs are becoming an increasingly important tool in molecular biology. These programs compute protein sequences that are predicted to fold to a target structure and perform a desired function. The success of a program's predictions largely relies on two components: (i) the input biophysical model, and (ii) the algorithm that computes the best sequence(s) and structure(s) according to the biophysical model. Improving both the model and the algorithm in tandem is essential to improving the success rate of current programs, and here we review recent developments in algorithms for protein design, emphasizing how novel algorithms enable the use of more accurate biophysical models. We conclude with a list of algorithmic challenges in computational protein design that we believe will be especially important for the design of therapeutic proteins and protein assemblies. Graphical Abstract*

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Section: Introductionmentioning

confidence: 99%

Algorithms for protein design

Gainza

Nisonoff

Donald

2016

Current Opinion in Structural Biology

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“…An advantage of gene editing is that modification will be inherited by the next generation [111, 112]. Techniques for modulating protein-protein interactions have been accumulated by artificial protein design experiments [113–116]. …”

Section: Discussionmentioning

confidence: 99%

In silico structure-based approaches to discover protein-protein interaction-targeting drugs

Shin

Christoffer

Kihara

2017

Methods

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A core concept behind modern drug discovery is finding a small molecule that modulates a function of a target protein. This concept has been successfully applied since the mid-1970s. However, the efficiency of drug discovery is decreasing because the druggable target space in the human proteome is limited. Recently, protein-protein interaction (PPI) has been identified as an emerging target space for drug discovery. PPI plays a pivotal role in biological pathways including diseases. Current human interactome research suggests that the number of PPIs ranges from 130,000 to 650,000, and only a small number of them have been targeted as drug targets. For traditional drug targets, in silico structure-based methods have been successful in many cases. However, their performance suffers on PPI interfaces because PPI interfaces are different in five major aspects: From a geometric standpoint, they have relatively large interface regions, flat geometry, and the interface surface shape tends to fluctuate upon binding. Also, their interactions are dominated by hydrophobic atoms, which is different from traditional binding-pocket-targeted drugs. Finally, PPI targets usually lack natural molecules that bind to the target PPI interface. Here, we first summarize characteristics of PPI interfaces and their known binders. Then, we will review existing in silico structure-based approaches for discovering small molecules that bind to PPI interfaces.

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“…The ability to identify interface residue hot spots is the basis for more complex redesign of interfaces and binding specificity (53,54). Considerable effort has therefore been put into the development of computational approaches to model the effect of point mutations on protein stability and binding affinity (33,34,36,55,56).…”

Section: Polar Interactions Across the Interface And Charges Play A Mmentioning

confidence: 99%

Crucial Roles of Single Residues in Binding Affinity, Specificity, and Promiscuity in the Cellulosomal Cohesin-Dockerin Interface

Slutzki

Reshef²,

Barak

et al. 2015

Journal of Biological Chemistry

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Background: Cellulosomal cohesin-dockerin interactions show intraspecies promiscuity but interspecies specificity. Results: A combination of computations and experiments reveals single cohesin residue mutations with dramatic effects not only on binding affinity but also on specificity and promiscuity. Conclusion: Natural interspecies specificity barriers in the cohesin-dockerin interaction are easily overcome by single mutations, indicating considerable plasticity. Significance: This study sheds light on the malleability and evolvability of a high affinity interaction.

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Computational design of protein–protein interactions

Cited by 57 publications

References 49 publications

Algorithms for protein design

Algorithms for protein design

In silico structure-based approaches to discover protein-protein interaction-targeting drugs

Crucial Roles of Single Residues in Binding Affinity, Specificity, and Promiscuity in the Cellulosomal Cohesin-Dockerin Interface

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