Chemical Perturbation of Oncogenic Protein Folding: from the Prediction of Locally Unstable Structures to the Design of Disruptors of Hsp90–Client Interactions

Paladino, Antonella; Woodford, Mark R.; Backe, Sarah J.; Sager, Rebecca; Kancherla, Priyanka; Daneshvar, Michael; Chen, Victor Z.; Bourboulia, Dimitra; Ahanin, Elham; Prodromou, Chrisostomos; Bergamaschi, Greta; Strada, Alessandro; Cretich, Marina; Gori, Alessandro; Veronesi, Marina; Bandiera, Tiziano; Vanna, Renzo; Bratslavsky, Gennady; Serapian, Stefano A.; Mollapour, Mehdi; Colombo, Giorgio

doi:10.1002/chem.202000615

Cited by 44 publications

(31 citation statements)

References 52 publications

(20 reference statements)

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“…The nature of the electrostatic interactions between the adaptor (positive) and the substrate (negative) opens to the design of negatively charged compounds to optimize electrostatic complementarity and assess LZTR1 recruitment properties. 43 …”

Section: Discussionmentioning

confidence: 99%

Structural Model for Recruitment of RIT1 to the LZTR1 E3 Ligase: Evidences from an Integrated Computational Approach

Paladino

D’Angelo

Noviello

et al. 2021

J. Chem. Inf. Model.

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Leucine-zipper transcription regulator 1 (LZTR1) is a highly mutated tumor suppressor gene, involved in the pathogenesis of several cancer types and developmental disorders. In proteasomal degradation, it acts as an adaptor protein responsible for the recognition and recruitment of substrates to be ubiquitinated in Cullin3-RING ligase E3 (CRL3) machinery. LZTR1 belongs to the BTB-Kelch family, a multi-domain protein where the Kelch propeller plays as the substrate recognition region and for which no experimental structure has been solved. Recently, large effort mutational analyses pointed to the role of disease-associated LZTR1 mutations in the RAS/MAPK signaling pathway and RIT1, a small Ras-related GTPase protein, has been identified by mass spectroscopy to interact with LZTR1. Hence, a better understanding of native structure, molecular mechanism, and substrate specificity would help clarifying the role of LZTR1 in pathological diseases, thus promoting advancement in the development of novel therapeutic strategies. Here, we address the interaction model between adaptor LZTR1 and substrate RIT1 by applying an integrated computational approach, including molecular modeling and docking techniques. We observe that the interaction model LZTR1-RIT1 is stabilized by an electrostatic bond network established between the two protein surfaces, which is reminiscent of homologous ubiquitin ligases complexes. Then, running MD simulations, we characterize differential conformational dynamics of the multi-domain LZTR1, offering interesting implications on the mechanistic role of specific point mutations. We identify G248R and R283Q as damaging mutations involved in the recognition process of the substrate RIT1 and R412C as a possible allosteric mutation from the Kelch to the C-term BTB-domain. Our findings provide important structural insights on targeting CRL3s for drug discovery.

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Section: Discussionmentioning

confidence: 99%

Structural Model for Recruitment of RIT1 to the LZTR1 E3 Ligase: Evidences from an Integrated Computational Approach

Paladino

D’Angelo

Noviello

et al. 2021

J. Chem. Inf. Model.

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“…Paladino and co-workers explored this route, identifying locally unstable substructures in native structures of Hsp90 client proteins [33] (Figure 2B). Such unstable substructures are indeed located in protein regions that have a high probability to unfold locally and exhibit conformational heterogeneity; however, they do not necessarily coincide with intrinsically disordered regions or unstructured loops.…”

Section: Interfering With the Chaperone Machinery: Targeting Hsp90 To Block Protein Foldingmentioning

confidence: 99%

Exploiting Folding and Degradation Machineries To Target Undruggable Proteins: What Can a Computational Approach Tell Us?

et al. 2021

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Advances in genomics and proteomics have unveiled an evergrowing number of key proteins and provided mechanistic insights into the genesis of pathologies. This wealth of data showed that changes in expression levels of specific proteins, mutations, and post-translational modifications can result in (often subtle) perturbations of functional protein-protein interaction networks, which ultimately determine disease phenotypes. Although many such validated pathogenic proteins have emerged as ideal drug targets, there are also several that escape traditional pharmacological regulation; these proteins have thus been labeled "undruggable". The challenges posed by undruggable targets call for new sorts of molecular intervention. One fascinating solution is to perturb a pathogenic protein's expression levels, rather than blocking its activities. In this Concept paper, we shall discuss chemical interventions aimed at recruiting undruggable proteins to the ubiquitin proteasome system, or aimed at disrupting proteinprotein interactions in the chaperone-mediated cellular folding machinery: both kinds of intervention lead to a decrease in the amount of active pathogenic protein expressed. Specifically, we shall discuss the role of computational strategies in understanding the molecular determinants characterizing the function of synthetic molecules typically designed for either type of intervention. Finally, we shall provide our perspectives and views on the current limitations and possibilities to expand the scope of rational approaches to the design of chemical regulators of protein levels.

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“…The recent series of studies by Colombo and colleague have reported results of computer-aided design and synthesis of new allosteric ligands with micromolar to nanomolar anticancer activities, demonstrating the power of computational approaches in discovering allosteric modulators that can probe the relationships between structure dynamics and function of the Hsp90 proteins and regulatory complexes with client proteins (Sattin et al, 2015 ; D'Annessa et al, 2017 ; Masgras et al, 2017 ; Ferraro et al, 2019 ; Hu et al, 2020 ; Sanchez-Martin et al, 2020 ). Computational targeting of the Hsp90 client proteins based on the prediction of locally unstable substructures in proteins was used to develop potent probes and peptides blocking Hsp90-client interactions (Colombo et al, 2020 ). Recent efforts have also produced small molecules that can inhibit the inter-chaperone protein-protein interactions for Hsp70 chaperone (Gestwicki and Shao, 2019 ).…”

Section: Exploiting Allosteric Mechanisms and Cryptic Binding Sites Fmentioning

confidence: 99%

Allosteric Regulation at the Crossroads of New Technologies: Multiscale Modeling, Networks, and Machine Learning

Verkhivker

Agajanian

et al. 2020

Front. Mol. Biosci.

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Chemical Perturbation of Oncogenic Protein Folding: from the Prediction of Locally Unstable Structures to the Design of Disruptors of Hsp90–Client Interactions

Abstract: Veronesi, Marina et al. (2020) Chemical perturbation of oncogenic protein folding: from the prediction of locally unstable structures to the design of disruptors of Hsp90-Client interactions. Chemistry -A European Journal, 26 (43). pp. 9459-9465.

Cited by 44 publications

References 52 publications

Structural Model for Recruitment of RIT1 to the LZTR1 E3 Ligase: Evidences from an Integrated Computational Approach

Structural Model for Recruitment of RIT1 to the LZTR1 E3 Ligase: Evidences from an Integrated Computational Approach

Exploiting Folding and Degradation Machineries To Target Undruggable Proteins: What Can a Computational Approach Tell Us?

Allosteric Regulation at the Crossroads of New Technologies: Multiscale Modeling, Networks, and Machine Learning

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