Computing allostery: from the understanding of biomolecular regulation and the discovery of cryptic sites to molecular design

Colombo, Giorgio

doi:10.1016/j.sbi.2023.102702

Cited by 12 publications

(7 citation statements)

References 46 publications

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“…Through MD simulations, we are able to directly observe and analyze the formation and dissociation of RNA–protein, RNA–RNA, and RNA–small molecule complexes unveiling the mechanisms that drive RNA recognition and modulation. , The use of computational approaches to explore the conformational variability of RNA molecules also paves the way for atomic-level insights into the mechanisms that govern allosteric regulation and signaling, thus expanding our potential to understand and manipulate RNA-driven regulatory processes. Predicting and designing events (such as single-point mutations or small molecule binding) that can alter the distribution between conformational states would allow the fine-tuned perturbation of the functional dynamics of these macromolecules. − The success of this approach has been widely proven in protein systems. − Despite the fact that proteins exhibit a greater degree of conformational variability than ncRNA, interesting findings emerge from investigations involving RNA, as well. ,− …”

Section: Computational Methods For Predicting Non-coding Rna–disease ...mentioning

confidence: 99%

Frontiers and Challenges of Computing ncRNAs Biogenesis, Function and Modulation

Rinaldi,

Moroni,

Rozza

et al. 2024

J. Chem. Theory Comput.

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Non-coding RNAs (ncRNAs), generated from nonprotein coding DNA sequences, constitute 98−99% of the human genome. Non-coding RNAs encompass diverse functional classes, including microRNAs, small interfering RNAs, PIWIinteracting RNAs, small nuclear RNAs, small nucleolar RNAs, and long non-coding RNAs. With critical involvement in gene expression and regulation across various biological and physiopathological contexts, such as neuronal disorders, immune responses, cardiovascular diseases, and cancer, non-coding RNAs are emerging as disease biomarkers and therapeutic targets. In this review, after providing an overview of non-coding RNAs' role in cell homeostasis, we illustrate the potential and the challenges of state-of-theart computational methods exploited to study non-coding RNAs biogenesis, function, and modulation. This can be done by directly targeting them with small molecules or by altering their expression by targeting the cellular engines underlying their biosynthesis. Drawing from applications, also taken from our work, we showcase the significance and role of computer simulations in uncovering fundamental facets of ncRNA mechanisms and modulation. This information may set the basis to advance gene modulation tools and therapeutic strategies to address unmet medical needs.

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Section: Computational Methods For Predicting Non-coding Rna–disease ...mentioning

confidence: 99%

Frontiers and Challenges of Computing ncRNAs Biogenesis, Function and Modulation

Rinaldi,

Moroni,

Rozza

et al. 2024

J. Chem. Theory Comput.

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“…Indeed, because of their functional roles like ligand binding 9 , promoting function via conformational changes 10 , and functional switching 11 , the propensity of loop regions to acquire mutations is evolutionarily advantageous. However, while previous studies have extensively explored the catalytic loops 6 , 7 , 12 , 13 , the role of functional remote loop regions remains limited in functional switching or large conformational change allostery 14 – 17 , especially, how new function is acquired via remote loop regions acquisitions/removals through evolution is poorly understood.…”

Section: Introductionmentioning

confidence: 99%

Remote loop evolution reveals a complex biological function for chitinase enzymes beyond the active site

Kozome,

Sljoka,

Laurino

2024

Nat Commun

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Loops are small secondary structural elements that play a crucial role in the emergence of new enzyme functions. However, the evolutionary molecular mechanisms how proteins acquire these loop elements and obtain new function is poorly understood. To address this question, we study glycoside hydrolase family 19 (GH19) chitinase—an essential enzyme family for pathogen degradation in plants. By revealing the evolutionary history and loops appearance of GH19 chitinase, we discover that one loop which is remote from the catalytic site, is necessary to acquire the new antifungal activity. We demonstrate that this remote loop directly accesses the fungal cell wall, and surprisingly, it needs to adopt a defined structure supported by long-range intramolecular interactions to perform its function. Our findings prove that nature applies this strategy at the molecular level to achieve a complex biological function while maintaining the original activity in the catalytic pocket, suggesting an alternative way to design new enzyme function.

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“…57 Such paucity of medical options is indicative of the difficult druggability of K-Ras4B and the allosteric diversity of its oncogenic aberrations, 37,38,42 justifying the continued interest in this GTPase and its allosteric mechanisms. Computational techniques 21,23,58 are essential to obtain an atomistic understanding of the determinants of allosteric regulation: 21,23−25 not only is this fundamental to drive the design of better, more "personalized" allosteric drugs and of tailored biocatalysts but also, e.g., 9,25 in the field of molecular diagnostics. While the time scales accessible by atomistic simulations (now on the microsecond scale) remain on the short side when it comes to capturing complete allosteric conformational changes, 28 a number of solutions, including coarsegraining and enhanced sampling MD, have become available over the years (cf.…”

Section: ■ Introductionmentioning

confidence: 99%

“…Computational techniques ,, are essential to obtain an atomistic understanding of the determinants of allosteric regulation: ,− not only is this fundamental to drive the design of better, more “personalized” allosteric drugs and of tailored biocatalysts but also, e.g. , , in the field of molecular diagnostics.…”

Section: Introductionmentioning

confidence: 99%

Decrypting Allostery in Membrane-Bound K-Ras4B Using Complementary In Silico Approaches Based on Unbiased Molecular Dynamics Simulations

Castelli,

Marchetti,

Osuna

et al. 2023

J. Am. Chem. Soc.

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Protein functions are dynamically regulated by allostery, which enables conformational communication even between faraway residues, and expresses itself in many forms, akin to different "languages": allosteric control pathways predominating in an unperturbed protein are often unintuitively reshaped whenever biochemical perturbations arise (e.g., mutations). To accurately model allostery, unbiased molecular dynamics (MD) simulations require integration with a reliable method able to, e.g., detect incipient allosteric changes or likely perturbation pathways; this is because allostery can operate at longer time scales than those accessible by plain MD. Such methods are typically applied singularly, but we here argue their joint application�as a "multilingual" approach�could work significantly better. We successfully prove this through unbiased MD simulations (∼100 μs) of the widely studied, allosterically active oncotarget K-Ras4B, solvated and embedded in a phospholipid membrane, from which we decrypt allostery using four showcase "languages": Distance Fluctuation analysis and the Shortest Path Map capture allosteric hotspots at equilibrium; Anisotropic Thermal Diff usion and Dynamical Non-Equilibrium MD simulations assess perturbations upon, respectively, either superheating or hydrolyzing the GTP that oncogenically activates K-Ras4B. Chosen "languages" work synergistically, providing an articulate, mutually coherent, experimentally consistent picture of K-Ras4B allostery, whereby distinct traits emerge at equilibrium and upon GTP cleavage. At equilibrium, combined evidence confirms prominent allosteric communication from the membrane-embedded hypervariable region, through a hub comprising helix α5 and sheet β5, and up to the active site, encompassing allosteric "switches" I and II (marginally), and two proposed pockets. Upon GTP cleavage, allosteric perturbations mostly accumulate on the switches and documented interfaces.

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Computing allostery: from the understanding of biomolecular regulation and the discovery of cryptic sites to molecular design

Cited by 12 publications

References 46 publications

Frontiers and Challenges of Computing ncRNAs Biogenesis, Function and Modulation

Frontiers and Challenges of Computing ncRNAs Biogenesis, Function and Modulation

Remote loop evolution reveals a complex biological function for chitinase enzymes beyond the active site

Decrypting Allostery in Membrane-Bound K-Ras4B Using Complementary In Silico Approaches Based on Unbiased Molecular Dynamics Simulations

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