Cracking the chaperone code through the computational microscope.

The heat shock protein 90 kDa (Hsp90) chaperone machinery plays a crucial role in maintaining cellular homeostasis. Beyond its traditional role in protein folding, Hsp90 is integral to key pathways influencing cellular function in health and disease. Hsp90 operates through the modular assembly of large multiprotein complexes, with their composition, stability, and localization adapting to the cell's needs. Its functional dynamics are finely tuned by ligand binding and post-translational modifications (PTMs). Here, we discuss how to disentangle the intricacies of the complex code that governs the crosstalk between dynamics, binding, PTMs, and the functions of the Hsp90 machinery using computer-based approaches. Specifically, we outline the contributions of computational and theoretical methods to the understanding of Hsp90 functions, ranging from providing atomic-level insights into its dynamics to clarifying the mechanisms of interactions with protein clients, cochaperones, and ligands. The knowledge generated in this framework can be actionable for the design and development of chemical tools and drugs targeting Hsp90 in specific disease-associated cellular contexts. Finally, we provide our perspective on how computation can be integrated into the study of the fine-tuning of functions in the highly complex Hsp90 landscape, complementing experimental methods for a comprehensive understanding of this important chaperone system.

N-Glycosylation-Induced Pathologic Protein Conformations as a Tool to Guide the Selection of Biologically Active Small Molecules.

Post-translational modifications such as protein N-glycosylation, significantly influence cellular processes. Dysregulated N-glycosylation, exemplified in Grp94, a member of the Hsp90 family, leads to structural changes and the formation of epichaperomes, contributing to pathologies. Targeting N-glycosylation-induced conformations offers opportunities for developing selective chemical tools and drugs for these pathologic forms of chaperones. We here demonstrate how a specific Grp94 conformation induced by N-glycosylation, identified previously via molecular dynamics simulations, rationalizes the distinct behavior of similar ligands. Integrating dynamic ligand unbinding information with SAR development, we differentiate ligands productively engaging the pathologic Grp94 conformers from those that are not. Additionally, analyzing binding site stereoelectronic properties and QSAR models using cytotoxicity data unveils relationships between chemical, conformational properties, and biological activities. These findings facilitate the design of ligands targeting specific Grp94 conformations induced by abnormal glycosylation, selectively disrupting pathogenic protein networks while sparing normal mechanisms.

Structures, dynamics, complexes, and functions: From classic computation to artificial intelligence.

Computational approaches can provide highly detailed insight into the molecular recognition processes that underlie drug binding, the assembly of protein complexes, and the regulation of biological functional processes. Classical simulation methods can bridge a wide range of length- and time-scales typically involved in such processes. Lately, automated learning and artificial intelligence methods have shown the potential to expand the reach of physics-based approaches, ushering in the possibility to model and even design complex protein architectures. The synergy between atomistic simulations and AI methods is an emerging frontier with a huge potential for advances in structural biology. Herein, we explore various examples and frameworks for these approaches, providing select instances and applications that illustrate their impact on fundamental biomolecular problems.

N-Glycosylation as a Modulator of Protein Conformation and Assembly in Disease.

Glycosylation, a prevalent post-translational modification, plays a pivotal role in regulating intricate cellular processes by covalently attaching glycans to macromolecules. Dysregulated glycosylation is linked to a spectrum of diseases, encompassing cancer, neurodegenerative disorders, congenital disorders, infections, and inflammation. This review delves into the intricate interplay between glycosylation and protein conformation, with a specific focus on the profound impact of N-glycans on the selection of distinct protein conformations characterized by distinct interactomes-namely, protein assemblies-under normal and pathological conditions across various diseases. We begin by examining the spike protein of the SARS virus, illustrating how N-glycans regulate the infectivity of pathogenic agents. Subsequently, we utilize the prion protein and the chaperone glucose-regulated protein 94 as examples, exploring instances where N-glycosylation transforms physiological protein structures into disease-associated forms. Unraveling these connections provides valuable insights into potential therapeutic avenues and a deeper comprehension of the molecular intricacies that underlie disease conditions. This exploration of glycosylation's influence on protein conformation effectively bridges the gap between the glycome and disease, offering a comprehensive perspective on the therapeutic implications of targeting conformational mutants and their pathologic assemblies in various diseases. The goal is to unravel the nuances of these post-translational modifications, shedding light on how they contribute to the intricate interplay between protein conformation, assembly, and disease.

Structural determinants of cold activity and glucose tolerance of a family 1 glycoside hydrolase (GH1) from Antarctic Marinomonas sp. ef1.

Cold-active enzymes support life at low temperatures due to their ability to maintain high activity in the cold and can be useful in several biotechnological applications. Although information on the mechanisms of enzyme cold adaptation is still too limited to devise general rules, it appears that very diverse structural and functional changes are exploited in different protein families and within the same family. In this context, we studied the cold adaptation mechanism and the functional properties of a member of the glycoside hydrolase family 1 (GH1) from the Antarctic bacterium Marinomonas sp. ef1. This enzyme exhibits all typical functional hallmarks of cold adaptation, including high catalytic activity at 5 °C, broad substrate specificity, low thermal stability, and higher lability of the active site compared to the overall structure. Analysis of the here-reported crystal structure (1.8 Å resolution) and molecular dynamics simulations suggest that cold activity and thermolability may be due to a flexible region around the active site (residues 298-331), whereas the dynamic behavior of loops flanking the active site (residues 47-61 and 407-413) may favor enzyme-substrate interactions at the optimal temperature of catalysis (Topt) by tethering together protein regions lining the active site. Stapling of the N-terminus onto the surface of the ß-barrel is suggested to partly counterbalance protein flexibility, thus providing a stabilizing effect. The tolerance of the enzyme to glucose and galactose is accounted for by the presence of a "gatekeeping" hydrophobic residue (Leu178), located at the entrance of the active site.

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.

How aberrant N-glycosylation can alter protein functionality and ligand binding: An atomistic view.

Protein-assembly defects due to an enrichment of aberrant conformational protein variants are emerging as a new frontier in therapeutics design. Understanding the structural elements that rewire the conformational dynamics of proteins and pathologically perturb functionally oriented ensembles is important for inhibitor development. Chaperones are hub proteins for the assembly of multiprotein complexes and an enrichment of aberrant conformers can affect the cellular proteome, and in turn, phenotypes. Here, we integrate computational and experimental tools to investigte how N-glycosylation of specific residues in glucose-regulated protein 94 (GRP94) modulates internal dynamics and alters the conformational fitness of regions fundamental for the interaction with ATP and synthetic ligands and impacts substructures important for the recognition of interacting proteins. N-glycosylation plays an active role in modulating the energy landscape of GRP94, and we provide support for leveraging the knowledge on distinct glycosylation variants to design molecules targeting GRP94 disease-associated conformational states and assemblies.

Conformational Behavior of SARS-Cov-2 Spike Protein Variants: Evolutionary Jumps in Sequence Reverberate in Structural Dynamic Differences.

SARS-CoV-2 has evolved rapidly in the first 3 years of pandemic diffusion. The initial evolution of the virus appeared to proceed through big jumps in sequence changes rather than through the stepwise accumulation of point mutations on already established variants. Here, we examine whether this nonlinear mutational process reverberates in variations of the conformational dynamics of the SARS-CoV-2 Spike protein (S-protein), the first point of contact between the virus and the human host. We run extensive microsecond-scale molecular dynamics simulations of seven distinct variants of the protein in their fully glycosylated state and set out to elucidate possible links between the mutational spectrum of the S-protein and the structural dynamics of the respective variant, at global and local levels. The results reveal that mutation-dependent structural and dynamic modulations mostly consist of increased coordinated motions in variants that acquire stability and in an increased internal flexibility in variants that are less stable. Importantly, a limited number of functionally important substructures (the receptor binding domain, in particular) share the same time of movements in all variants, indicating efficient preorganization for functional regions dedicated to host interactions. Our results support a model in which the internal dynamics of the S-proteins from different strains varies in a way that reflects the observed random and non-stepwise jumps in sequence evolution, while conserving the functionally oriented traits of conformational dynamics necessary to support productive interactions with host receptors.

Integrating Protein Interaction Surface Prediction with a Fragment-Based Drug Design: Automatic Design of New Leads with Fragments on Energy Surfaces.

Protein-protein interactions (PPIs) have emerged in the past years as significant pharmacological targets in the development of new therapeutics due to their key roles in determining pathological pathways. Herein, we present fragments on energy surfaces, a simple and general design strategy that integrates the analysis of the dynamic and energetic signatures of proteins to unveil the substructures involved in PPIs, with docking, selection, and combination of drug-like fragments to generate new PPI inhibitor candidates. Specifically, structural representatives of the target protein are used as inputs for the blind physics-based prediction of potential protein interaction surfaces using the matrix of low coupling energy decomposition method. The predicted interaction surfaces are subdivided into overlapping windows that are used as templates to direct the docking and combination of fragments representative of moieties typically found in active drugs. This protocol is then applied and validated using structurally diverse, important PPI targets as test systems. We demonstrate that our approach facilitates the exploration of the molecular diversity space of potential ligands, with no requirement of prior information on the location and properties of interaction surfaces or on the structures of potential lead compounds. Importantly, the hit molecules that emerge from our ab initio design share high chemical similarity with experimentally tested active PPI inhibitors. We propose that the protocol we describe here represents a valuable means of generating initial leads against difficult targets for further development and refinement.

Evaluation of docking procedures reliability in affitins-partners interactions.

Affitins constitute a class of small proteins belonging to Sul7d family, which, in microorganisms such as Sulfolobus acidocaldarius, bind DNA preventing its denaturation. Thanks to their stability and small size (60-66 residues in length) they have been considered as ideal candidates for engineering and have been used for more than 10 years now, for different applications. The individuation of a mutant able to recognize a specific target does not imply the knowledge of the binding geometry between the two proteins. However, its identification is of undoubted importance but not always experimentally accessible. For this reason, computational approaches such as protein-protein docking can be helpful for an initial structural characterization of the complex. This method, which produces tens of putative binding geometries ordered according to a binding score, needs to be followed by a further reranking procedure for finding the most plausible one. In the present paper, we use the server ClusPro for generating docking models of affitins with different protein partners whose experimental structures are available in the Protein Data Bank. Then, we apply two protocols for reranking the docking models. The first one investigates their stability by means of Molecular Dynamics simulations; the second one, instead, compares the docking models with the interacting residues predicted by the Matrix of Local Coupling Energies method. Results show that the more efficient way to deal with the reranking problem is to consider the information given by the two protocols together, i.e. employing a consensus approach.

A Fe2+-dependent self-inhibited state influences the druggability of human collagen lysyl hydroxylase (LH/PLOD) enzymes.

Multifunctional human collagen lysyl hydroxylase (LH/PLOD) enzymes catalyze post-translational hydroxylation and subsequent glycosylation of collagens, enabling their maturation and supramolecular organization in the extracellular matrix (ECM). Recently, the overexpression of LH/PLODs in the tumor microenvironment results in abnormal accumulation of these collagen post-translational modifications, which has been correlated with increased metastatic progression of a wide variety of solid tumors. These observations make LH/PLODs excellent candidates for prospective treatment of aggressive cancers. The recent years have witnessed significant research efforts to facilitate drug discovery on LH/PLODs, including molecular structure characterizations and development of reliable high-throughput enzymatic assays. Using a combination of biochemistry and in silico studies, we characterized the dual role of Fe2+ as simultaneous cofactor and inhibitor of lysyl hydroxylase activity and studied the effect of a promiscuous Fe2+ chelating agent, 2,2'-bipyridil, broadly considered a lysyl hydroxylase inhibitor. We found that at low concentrations, 2,2'-bipyridil unexpectedly enhances the LH enzymatic activity by reducing the inhibitory effect of excess Fe2+. Together, our results show a fine balance between Fe2+-dependent enzymatic activity and Fe2+-induced self-inhibited states, highlighting exquisite differences between LH/PLODs and related Fe2+, 2-oxoglutarate dioxygenases and suggesting that conventional structure-based approaches may not be suited for successful inhibitor development. These insights address outstanding questions regarding druggability of LH/PLOD lysyl hydroxylase catalytic site and provide a solid ground for upcoming drug discovery and screening campaigns.

The worldwide spread of Aedes albopictus: New insights from mitogenomes.

The tiger mosquito (Aedes albopictus) is one of the most invasive species in the world and a competent vector for numerous arboviruses, thus the study and monitoring of its fast worldwide spread is crucial for global public health. The small extra-nuclear and maternally-inherited mitochondrial DNA represents a key tool for reconstructing phylogenetic and phylogeographic relationships within a species, especially when analyzed at the mitogenome level. Here the mitogenome variation of 76 tiger mosquitoes, 37 of which new and collected from both wild adventive populations and laboratory strains, was investigated. This analysis significantly improved the global mtDNA phylogeny of Ae. albopictus, uncovering new branches and sub-branches within haplogroup A1, the one involved in its recent worldwide spread. Our phylogeographic approach shows that the current distribution of tiger mosquito mitogenome variation has been strongly affected by clonal and sub-clonal founder events, sometimes involving wide geographic areas, even across continents, thus shedding light on the Asian sources of worldwide adventive populations. In particular, different starting points for the two major clades within A1 are suggested, with A1a spreading mainly along temperate areas from Japanese and Chinese sources, and A1b arising and mainly diffusing in tropical areas from a South Asian source.

Studying the Dynamics of a Complex G-Quadruplex System: Insights into the Comparison of MD and NMR Data.

Molecular dynamics (MD) simulations are coming of age in the study of nucleic acids, including specific tertiary structures such as G-quadruplexes. While being precious for providing structural and dynamic information inaccessible to experiments at the atomistic level of resolution, MD simulations in this field may still be limited by several factors. These include the force fields used, different models for ion parameters, ionic strengths, and water models. We address various aspects of this problem by analyzing and comparing microsecond-long atomistic simulations of the G-quadruplex structure formed by the human immunodeficiency virus long terminal repeat (HIV LTR)-III sequence for which nuclear magnetic resonance (NMR) structures are available. The system is studied in different conditions, systematically varying the ionic strengths, ion numbers, and water models. We comparatively analyze the dynamic behavior of the G-quadruplex motif in various conditions and assess the ability of each simulation to satisfy the nuclear magnetic resonance (NMR)-derived experimental constraints and structural parameters. The conditions taking into account K+-ions to neutralize the system charge, mimicking the intracellular ionic strength, and using the four-atom water model are found to be the best in reproducing the experimental NMR constraints and data. Our analysis also reveals that in all of the simulated environments residues belonging to the duplex moiety of HIV LTR-III exhibit the highest flexibility.

The Mitogenome Relationships and Phylogeography of Barn Swallows (Hirundo rustica).

The barn swallow (Hirundo rustica) poses a number of fascinating scientific questions, including the taxonomic status of postulated subspecies. Here, we obtained and assessed the sequence variation of 411 complete mitogenomes, mainly from the European H. r. rustica, but other subspecies as well. In almost every case, we observed subspecies-specific haplogroups, which we employed together with estimated radiation times to postulate a model for the geographical and temporal worldwide spread of the species. The female barn swallow carrying the Hirundo rustica ancestral mitogenome left Africa (or its vicinity) around 280 thousand years ago (kya), and her descendants expanded first into Eurasia and then, at least 51 kya, into the Americas, from where a relatively recent (<20 kya) back migration to Asia took place. The exception to the haplogroup subspecies specificity is represented by the sedentary Levantine H. r. transitiva that extensively shares haplogroup A with the migratory European H. r. rustica and, to a lesser extent, haplogroup B with the Egyptian H. r. savignii. Our data indicate that rustica and transitiva most likely derive from a sedentary Levantine population source that split at the end of the Younger Dryas (YD) (11.7 kya). Since then, however, transitiva received genetic inputs from and admixed with both the closely related rustica and the adjacent savignii. Demographic analyses confirm this species' strong link with climate fluctuations and human activities making it an excellent indicator for monitoring and assessing the impact of current global changes on wildlife.

Protein Allostery and Ligand Design: Computational Design Meets Experiments to Discover Novel Chemical Probes.

Herein we examine the determinants of the allosteric inhibition of the mitochondrial chaperone TRAP1 by a small molecule ligand. The knowledge generated is harnessed into the design of novel derivatives with interesting biological properties. TRAP1 is a member of the Hsp90 family of proteins, which work through sequential steps of ATP processing coupled to client-protein remodeling. Isoform selective inhibition of TRAP1 can provide novel information on the biomolecular mechanisms of molecular chaperones, as well as new insights into the development of small molecules with therapeutic potential. Our analysis of the interactions between an active first-generation allosteric ligand and TRAP1 shows how the small molecule induces long-range perturbations that influence the attainment of reactive poses in the active site. At the same time, the dynamic adaptation of the allosteric binding pocket to the presence of the first-generation compound sets the stage for the design of a set of second-generation ligands: the characterization of the formation/disappearance of pockets around the allosteric site that is used to guide optimize the ligands' fit for the allosteric site and improve inhibitory activities. The effects of the newly designed molecules are validated experimentally in vitro and in vivo. We discuss the implications of our approach as a promising strategy towards understanding the molecular determinants of allosteric regulation in chemical and molecular biology, and towards speeding up the design of allosteric small molecule modulators.

Transcription factor protein interactomes reveal genetic determinants in heart disease.

Congenital heart disease (CHD) is present in 1% of live births, yet identification of causal mutations remains challenging. We hypothesized that genetic determinants for CHDs may lie in the protein interactomes of transcription factors whose mutations cause CHDs. Defining the interactomes of two transcription factors haplo-insufficient in CHD, GATA4 and TBX5, within human cardiac progenitors, and integrating the results with nearly 9,000 exomes from proband-parent trios revealed an enrichment of de novo missense variants associated with CHD within the interactomes. Scoring variants of interactome members based on residue, gene, and proband features identified likely CHD-causing genes, including the epigenetic reader GLYR1. GLYR1 and GATA4 widely co-occupied and co-activated cardiac developmental genes, and the identified GLYR1 missense variant disrupted interaction with GATA4, impairing in vitro and in vivo function in mice. This integrative proteomic and genetic approach provides a framework for prioritizing and interrogating genetic variants in heart disease.

SARS-CoV-2 Spike Protein Mutations and Escape from Antibodies: A Computational Model of Epitope Loss in Variants of Concern.

The SARS-CoV-2 spike (S) protein is exposed on the viral surface and is the first point of contact between the virus and the host. For these reasons it represents the prime target for Covid-19 vaccines. In recent months, variants of this protein have started to emerge. Their ability to reduce or evade recognition by S-targeting antibodies poses a threat to immunological treatments and raises concerns for their consequences on vaccine efficacy. To develop a model able to predict the potential impact of S-protein mutations on antibody binding sites, we performed unbiased multi-microsecond molecular dynamics of several glycosylated S-protein variants and applied a straightforward structure-dynamics-energy based strategy to predict potential changes in immunogenic regions on each variant. We recover known epitopes on the reference D614G sequence. By comparing our results, obtained on isolated S-proteins in solution, to recently published data on antibody binding and reactivity in new S variants, we directly show that modifications in the S-protein consistently translate into the loss of potentially immunoreactive regions. Our findings can thus be qualitatively reconnected to the experimentally characterized decreased ability of some of the Abs elicited against the dominant S-sequence to recognize variants. While based on the study of SARS-CoV-2 spike variants, our computational epitope-prediction strategy is portable and could be applied to study immunoreactivity in mutants of proteins of interest whose structures have been characterized, helping the development/selection of vaccines and antibodies able to control emerging variants.

HIF1α-dependent induction of the mitochondrial chaperone TRAP1 regulates bioenergetic adaptations to hypoxia.

The mitochondrial paralog of the Hsp90 chaperone family TRAP1 is often induced in tumors, but the mechanisms controlling its expression, as well as its physiological functions remain poorly understood. Here, we find that TRAP1 is highly expressed in the early stages of Zebrafish development, and its ablation delays embryogenesis while increasing mitochondrial respiration of fish larvae. TRAP1 expression is enhanced by hypoxic conditions both in developing embryos and in cancer models of Zebrafish and mammals. The TRAP1 promoter contains evolutionary conserved hypoxic responsive elements, and HIF1α stabilization increases TRAP1 levels. TRAP1 inhibition by selective compounds or by genetic knock-out maintains a high level of respiration in Zebrafish embryos after exposure to hypoxia. Our data identify TRAP1 as a primary regulator of mitochondrial bioenergetics in highly proliferating cells following reduction in oxygen tension and HIF1α stabilization.

Targeting the mitochondrial chaperone TRAP1: strategies and therapeutic perspectives.

TRAP1, the mitochondrial isoform of heat shock protein (Hsp)90 chaperones, is a key regulator of metabolism and organelle homeostasis in diverse pathological states. While selective TRAP1 targeting is an attractive goal, classical active-site-directed strategies have proved difficult, due to high active site conservation among Hsp90 paralogs. Here, we discuss advances in developing TRAP1-directed strategies, from lead modification with mitochondria delivery groups to the computational discovery of allosteric sites and ligands. Specifically, we address the unique opportunities that targeting TRAP1 opens up in tackling fundamental questions on its biology and in unveiling new therapeutic approaches. Finally, we show how crucial to this endeavor is our ability to predict the activities of TRAP1-selective allosteric ligands and to optimize target engagement to avoid side effects.