From Fuzzy to Function: The New Frontier of Protein–Protein Interactions

Pricer, Rachel; Gestwicki, Jason E.; Mapp, Anna K.

doi:10.1021/acs.accounts.6b00565

Cited by 45 publications

(54 citation statements)

References 33 publications

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“…Detailed accounts of PPIs and their inhibitors are already provided in several excellent reviews . Here, our scope is to focus on the plasticity of protein–protein complexes, and how to use this information to derive small‐molecule modulators (not just inhibitors but also promoters) of such an important class of targets …”

Section: Modulating Biological Functions By Targeting Protein–proteinmentioning

confidence: 99%

Designing Molecular Spanners to Throw in the Protein Networks

Serapian

Colombo

2020

Chemistry A European J

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Proteins govern most aspects of cellular life and, through specific interfaces, are typically involved in intricate protein–protein interaction (PPI) networks and signaling pathways. Subtle up‐ or downregulation of key protein functions and PPIs results in disease; still, the preferred option to contrast the role of a protein in disease and healthy conditions alike remains its outright shutdown through orthosteric ligands that block its active site. Here, we explore subtler alternatives to modulate proteins and PPIs. Driven by a view of proteins as dynamic entities, we discuss ways to identify allosteric binding sites, which, when targeted by tailored ligands, can induce significant changes in the active site of a protein, and lead to agonistic or antagonistic effects. We also summarize the selective regulation of specific PPIs—either direct or allosteric—and show that effects can be stabilizing as well as destabilizing, depending on how the conformational equilibrium of a protein is shifted.

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Section: Modulating Biological Functions By Targeting Protein–proteinmentioning

confidence: 99%

Designing Molecular Spanners to Throw in the Protein Networks

Serapian

Colombo

2020

Chemistry A European J

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“…In fact, proteins are conformationally dynamic and exhibit functional promiscuity. Conformational dynamism and heterogeneity enable context-specific functions to emerge in response to changing environmental conditions and, furthermore, allow a single structural motif to be used in multiple settings [ 38 ]. The conformational flexibility and heterogeneity of proteins represent their fuzziness.…”

Section: The Methodologies To Implement Fuzzy Sets and Process Fuzmentioning

confidence: 99%

The Fuzziness of the Molecular World and Its Perspectives

Gentili

2018

Molecules

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Scientists want to comprehend and control complex systems. Their success depends on the ability to face also the challenges of the corresponding computational complexity. A promising research line is artificial intelligence (AI). In AI, fuzzy logic plays a significant role because it is a suitable model of the human capability to compute with words, which is relevant when we make decisions in complex situations. The concept of fuzzy set pervades the natural information systems (NISs), such as living cells, the immune and the nervous systems. This paper describes the fuzziness of the NISs, in particular of the human nervous system. Moreover, it traces three pathways to process fuzzy logic by molecules and their assemblies. The fuzziness of the molecular world is useful for the development of the chemical artificial intelligence (CAI). CAI will help to face the challenges that regard both the natural and the computational complexity.

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“…Proteins function under rapidly changing extracellular signals and intracellular milieu, which is shaped by cellular diffusion and transport, stochastic gene expression, degradation, and other environmental fluctuations. These factors present stochastic conditions for protein evolution [ 16 , 17 , 18 ] leading to ‘noise’ in biological innovations [ 19 ], which is reflected by redundancies and ambiguities in sequences [ 20 ], structures [ 21 ], and functions [ 22 ]. On the one hand, proteins attempt to minimize functional noise.…”

Section: Adaptation To Stochastic Cellular Conditionsmentioning

confidence: 99%

Towards a Stochastic Paradigm: From Fuzzy Ensembles to Cellular Functions

Fuxreiter

2018

Molecules

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The deterministic sequence → structure → function relationship is not applicable to describe how proteins dynamically adapt to different cellular conditions. A stochastic model is required to capture functional promiscuity, redundant sequence motifs, dynamic interactions, or conformational heterogeneity, which facilitate the decision-making in regulatory processes, ranging from enzymes to membraneless cellular compartments. The fuzzy set theory offers a quantitative framework to address these problems. The fuzzy formalism allows the simultaneous involvement of proteins in multiple activities, the degree of which is given by the corresponding memberships. Adaptation is described via a fuzzy inference system, which relates heterogeneous conformational ensembles to different biological activities. Sequence redundancies (e.g., tandem motifs) can also be treated by fuzzy sets to characterize structural transitions affecting the heterogeneous interaction patterns (e.g., pathological fibrillization of stress granules). The proposed framework can provide quantitative protein models, under stochastic cellular conditions.

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From Fuzzy to Function: The New Frontier of Protein–Protein Interactions

Cited by 45 publications

References 33 publications

Designing Molecular Spanners to Throw in the Protein Networks

Designing Molecular Spanners to Throw in the Protein Networks

The Fuzziness of the Molecular World and Its Perspectives

Towards a Stochastic Paradigm: From Fuzzy Ensembles to Cellular Functions

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