Mechanistic Model for the Hsp90-Driven Opening of Human Argonaute

Comparative structural insights and functional analysis for the distinct unbound states of Human AGO proteins

The four human Argonaute (AGO) proteins, critical in RNA interference and gene regulation, exhibit high sequence and structural similarity but differ functionally. We investigated the underexplored structural relationships of these paralogs through microsecond-scale molecular dynamics simulations. Our findings reveal that AGO proteins adopt similar, yet unsynchronized, open-close states. We observed similar and unique local conformations, interdomain distances and intramolecular interactions. Conformational differences at GW182/ZSWIM8 interaction sites and in catalytic/pseudo-catalytic tetrads were minimal. Tetrads display conserved movements, interacting with distant miRNA binding residues. We pinpointed long common protein subsequences with consistent molecular movement but varying solvent accessibility per AGO. We observed diverse conformational patterns at the post-transcriptional sites of the AGOs, except for AGO4. By combining simulation data with large datasets of experimental structures and AlphaFold's predictions, we identified proteins with genomic and proteomic similarities. Some of the identified proteins operate in the mitosis pathway, sharing mitosis-related interactors and miRNA targets. Additionally, we suggest that AGOs interact with a mitosis initiator, zinc ion, by predicting potential binding sites and detecting structurally similar proteins with the same function. These findings further advance our understanding for the human AGO protein family and their role in central cellular processes.

Ensemble Docking as a Tool for the Rational Design of Peptidomimetic Staphylococcus aureus Sortase A Inhibitors

Sortase A (SrtA) of Staphylococcus aureus has long been shown to be a relevant molecular target for antibacterial development. Moreover, the designed SrtA inhibitors act via the antivirulence mechanism, potentially causing less evolutional pressure and reduced antimicrobial resistance. However, no marketed drugs or even drug candidates have been reported until recently, despite numerous efforts in the field. SrtA has been shown to be a tough target for rational structure-based drug design (SBDD), which hampers the regular development of small-molecule inhibitors using the available arsenal of drug discovery tools. Recently, several oligopeptides resembling the sorting sequence LPxTG (Leu-Pro-Any-Thr-Gly) of the native substrates of SrtA were reported to be active in the micromolar range. Despite the good experimental design of those works, their molecular modeling parts are still not convincing enough to be used as a basis for a rational modification of peptidic inhibitors. In this work, we propose to use the ensemble docking approach, in which the relevant SrtA conformations are extracted from the molecular dynamics simulation of the LPRDA (Leu-Pro-Arg-Asp-Ala)-SrtA complex, to effectively represent the most significant and diverse target conformations. The developed protocol is shown to describe the known experimental data well and then is applied to a series of new peptidomimetic molecules resembling the active oligopeptide structures reported previously in order to prioritize structures from this work for further synthesis and activity testing. The proposed approach is compared to existing alternatives, and further directions for its development are outlined.

Frontiers and Challenges of Computing ncRNAs Biogenesis, Function and Modulation

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, PIWI-interacting 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-the-art 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.

The dynamics of t1 adenosine binding on human Argonaute 2: Understanding recognition with conformational selection

The control of expression in genetic regulation is a fundamental process for cell life. In RNA-mediated silencing, human Argonaute-2 protein (hAgo2) uses sequence information encoded in small RNAs (guide) to identify complementary sites in messenger RNAs (target) for repression. The specificity of this molecular recognition lies at the basis of the mechanisms that control the expression of thousands of genes, which necessarily requires a fine tuning of complex events. Among these, the binding of the first nucleotide of the target RNA (t1) is emerging as an important modulator of hAgo2-mediated machinery. Using atomistic molecular dynamics-derived analyses, we address the mechanism behind t1-dependent regulation and study the impact of different t1 nucleotides (t1A, t1C, t1G, t1U) on the conformational dynamics of both hAgo2 and guide-target RNAs. Only when an adenine is found at this position, t1 directly interacts with a specific hAgo2 binding pocket, favoring the stabilization of target binding. Our findings show that hAgo2 exploits a dynamic recognition mechanism of the t1-target thanks to a modulation of RNA conformations. Here, t1-adenine is the only nucleobase endowed with a dual binding mode: a T-shape and a co-planar conformation, respectively, orthogonal and parallel to the following base-pairs of guide-target duplex. This triggers a composite set of molecular interactions that stabilizes distinctive conformational ensembles. Our comparative analyses show characteristic traits of local and global dynamic interplay between hAgo2 and the RNA molecules and highlight how t1A binding acts as a molecular switch for target recognition and complex stabilization. Implications for future mechanistic studies are discussed.

Dissecting the Protein Dynamics Coupled Ligand Binding with Kinetic Models and Single-Molecule FRET

Protein-ligand interactions are crucial to many biological processes. Ligand binding and dissociation are the basic steps that allow proteins to function. Protein conformational dynamics have been shown to play important roles in ligand binding and dissociation. However, it is challenging to determine the ligand binding kinetics of dynamic proteins. Here, we undertook comprehensive single-molecule FRET (smFRET) measurements and kinetic model analysis to characterize the conformational dynamics coupled ligand binding of glutamine-binding protein (GlnBP). We showed that hinge and T118A mutations of GlnBP affect its conformational dynamics as well as the ligand binding affinity. Based on smFRET measurements, the kinetic model of ligand-GlnBP interactions was constructed. Using experimentally measured parameters, we solved the rate equations of the model and obtained the undetectable parameters of the model which allowed us to understand the ligand binding kinetics fully. Our results demonstrate that modulation of the conformational dynamics of GlnBP affects the ligand binding and dissociation rates. This study provides insights into the binding kinetics of ligands, which are related to the protein function itself.

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

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.