Structure-Based Statistical Mechanical Model Accounts for the Causality and Energetics of Allosteric Communication

Zinc-mediated conformational preselection mechanism in the allosteric control of DNA binding to the zinc transcriptional regulator (ZitR)

The zinc transcriptional regulator (ZitR) functions as a metalloregulator that fine tunes transcriptional regulation through zinc-dependent DNA binding. However, the molecular mechanism of zinc-driven allosteric control of the DNA binding to ZitR remains elusive. Here, we performed enhanced sampling accelerated molecular dynamics simulations to figure out the mechanism, revealing the role of protein dynamics in the zinc-induced allosteric control of DNA binding to ZitR. The results suggest that zinc-free ZitR samples distinct conformational states, only a handful of which are compatible with DNA binding. Remarkably, zinc binding reduces the conformational plasticity of the DNA-binding domain of ZitR, promoting the population shift in the ZitR conformational ensemble towards the DNA binding-competent conformation. Further co-binding of DNA to the zinc–ZitR complex stabilizes this competent conformation. These findings suggest that ZitR–DNA interactions are allosterically regulated in a zinc-mediated conformational preselection manner, highlighting the importance of conformational dynamics in the regulation of transcription factor family.

A study on allosteric communication in U1A-snRNA binding interactions: network analysis combined with molecular dynamics data

The allosteric regulation during the binding interactions between small nuclear RNAs (snRNAs) and the associated protein factors is critical to the function of spliceosomes in alternative RNA splicing. Although network models combined with molecular dynamics simulations have shown to be powerful tools for the analysis of protein allostery, the atomic-level simulations are, however, too expensive and with limited accuracy for the large-size systems. In this work, we use a residual network model combined with a coarse-grained Gaussian network model (GNM) to investigate the binding interactions between the snRNA and the human U1A protein which is a major component of the spliceosomal U1 small nuclear ribonucleoprotein particle, and to identify the residues that play an important role in the allosteric communication in U1A during this process. We also utilize the Girvan-Newman method to detect the structural organization in U1A-snRNA recognition and interactions. Our results reveal that: (Ι) not only the residues at the binding sites that are traditionally considered to play a major role in U1A-snRNA association, but those residues that are far away from the RNA binding interface participate in the U1A's allosteric signal transmission induced by the RNA binding; (Π) the structure of U1A protein is well organized with different communities acting different roles for its RNA binding and allosteric regulation. The study demonstrates that the combination of the residual network and elastic network models is an effective and efficient method which can be readily extended to the investigation of the allosteric communication for other macromolecular interaction systems.

Predicted dynamical couplings of protein residues characterize catalysis, transport and allostery

MOTIVATION

Protein function is intrinsically linked to native dynamics, but the systematic characterization of functionally relevant dynamics remains elusive besides specific examples. Here we exhaustively characterize three types of dynamical couplings between protein residues: co-directionality (moving along collinear directions), coordination (small fluctuations of the interatomic distance) and deformation (the extent by which perturbations applied at one residue modify the local structure of the other one), which we analytically compute through the torsional network model.

RESULTS

We find that ligand binding sites are characterized by large within-site coordination and co-directionality, much larger than expected for generic sets of residues with equivalent sequence distances. In addition, catalytic sites are characterized by high coordination couplings with other residues in the protein, supporting the view that the overall protein structure facilitates the catalytic dynamics. The binding sites of allosteric effectors are characterized by comparably smaller coordination and higher within-site deformation than other ligands, which supports their dynamic nature. Allosteric inhibitors are coupled to the active site more frequently through deformation than through coordination, while the contrary holds for activators. We characterize the dynamical couplings of the sodium-dependent Leucine transporter protein (LeuT). The couplings between and within sites progress consistently along the transport cycle, providing a mechanistic description of the coupling between the uptake and release of ions and substrate, and they highlight qualitative differences between the wild-type and a mutant for which chloride is necessary for transport.

AVAILABILITY AND IMPLEMENTATION

The program tnm is freely available at https://github.com/ugobas/tnm.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

PI3K inhibitors: review and new strategies

The search is on for effective specific inhibitors for PI3Kα mutants. PI3Kα, a critical lipid kinase, has two subunits, catalytic and inhibitory. PIK3CA, the gene that encodes the p110α catalytic subunit is a highly mutated protein in cancer. Dysregulation of PI3Kα signalling is commonly associated with tumorigenesis and drug resistance. Despite its vast importance, only recently the FDA approved the first drug (alpelisib by Novartis) for breast cancer. A second (GDC0077), classified as PI3Kα isoform-specific, is undergoing clinical trials. Not surprisingly, these ATP-competitive drugs commonly elicit severe concentration-dependent side effects. Here we briefly review PI3Kα mutations, focus on PI3K drug repertoire and propose new, to-date unexplored PI3Kα therapeutic strategies. These include (1) an allosteric and orthosteric inhibitor combination and (2) taking advantage of allosteric rescue mutations to guide drug discovery.

Identification of Alternative Allosteric Sites in Glycolytic Enzymes for Potential Use as Species-Specific Drug Targets

Three allosteric glycolytic enzymes, phosphofructokinase, glyceraldehyde-3 phosphate dehydrogenase and pyruvate kinase, associated with bacterial, parasitic and human species, were explored to identify potential allosteric sites that would be used as prime targets for species-specific drug design purposes using a newly developed approach which incorporates solvent mapping, elastic network modeling, sequence and structural alignments. The majority of binding sites detected by solvent mapping overlapped with the interface regions connecting the subunits, thus appeared as promising target sites for allosteric regulation. Each binding site was then evaluated by its ability to alter the global dynamics of the receptor defined by the percentage change in the frequencies of the lowest-frequency modes most significantly and as anticipated, the most effective ones were detected in the vicinity of the well-reported catalytic and allosteric sites. Furthermore, some of our proposed regions intersected with experimentally resolved sites which are known to be critical for activity regulation, which further validated our approach. Despite the high degree of structural conservation encountered between bacterial/parasitic and human glycolytic enzymes, the majority of the newly presented allosteric sites exhibited a low degree of sequence conservation which further increased their likelihood to be used as species-specific target regions for drug design studies.

AlloMAPS: allosteric mutation analysis and polymorphism of signaling database

AlloMAPS database provides data on the causality and energetics of allosteric communication obtained with the structure-based statistical mechanical model of allostery (SBSMMA). The database contains data on allosteric signaling in three sets of proteins and protein chains: (i) 46 proteins with comprehensively annotated functional and allosteric sites; (ii) 1908 protein chains from PDBselect set of chains with low (<25%) sequence identity; (iii) 33 proteins with more than 50 known pathological SNPs in each molecule. In addition to energetics of allosteric signaling between known functional and regulatory sites, allosteric modulation caused by the binding to these sites, by SNPs, and by mutations designated by the user can be explored. Allosteric Signaling Maps (ASMs), which are produced via the exhaustive computational scanning for stabilizing and destabilizing mutations and for the modulation range caused by the sequence position are available for each protein/protein chain in the database. We propose to use this database for evaluating the effects of allosteric signaling in the search for latent regulatory sites and in the design of allosteric sites and effectors. The database is freely available at: http://allomaps.bii.a-star.edu.sg.

Conformational Changes Induced by S34Y and R98C Variants in the Death Domain of Myd88

Myeloid differentiating factor 88 (Myd88) is a universal adaptor protein that plays a critical role in innate immunity by mediating TLR downstream signaling. Myd88 death domain (DD) forms an oligomeric complex by association with other DD-containing proteins such as IRAK4. Despite its universal role, polymorphisms in Myd88 can result in several diseases. Previous studies have suggested that, out of several non-synonymous single-nucleotide polymorphisms (nsSNPs), the variants S34Y and R98C in the DD of Myd88 disrupt the formation of the Myddosome complex. Therefore, we performed molecular dynamics (MD) simulations on wild-type (Myd88^WT) and mutant (Myd88^S34Y, Myd88^R98C) DDs to evaluate the subtle conformational changes induced by these mutations. Our results suggest that the S34Y variant induces large structural transitions compared to the R98C variant as evidenced by residual flexibility at the variable loop regions, particularly in the H1-H2 loop, and variations in the collective modes of motion observed for wild-type and mutant Myd88 DDs. The residue interaction network strongly suggests a distortion in the interaction pattern at the location of the mutated residue between the wild type and mutants. Moreover, betweenness centrality values indicate that variations in the distribution of functionally important residues may be reflected by distinct residue signal transductions in both wild-type and mutant Myd88 DDs, which may influence the interaction with other DDs in TLR downstream signaling.

Combining Allosteric and Orthosteric Drugs to Overcome Drug Resistance

Historically, most drugs target protein orthosteric sites. The gradual emergence of resistance hampers their therapeutic effectiveness, posing a challenge to drug development. Coadministration of allosteric and orthosteric drugs provides a revolutionary strategy to circumvent drug resistance, as drugs targeting the topologically distinct allosteric sites can restore or even enhance the efficacy of orthosteric drugs. Here, we comprehensively review the latest successful examples of such combination treatments against drug resistance, with a focus on their modes of action and the underlying structural mechanisms. Our work supplies an innovative insight into such promising methodology against the recalcitrant drug resistance conundrum and will be instructive for future clinical therapeutics.

The Determination of HIV-1 RT Mutation Rate, Its Possible Allosteric Effects, and Its Implications on Drug Resistance

The high mutation rate of the human immunodeficiency virus type 1 (HIV-1) plays a major role in treatment resistance, from the development of vaccines to therapeutic drugs. In addressing the crux of the issue, various attempts to estimate the mutation rate of HIV-1 resulted in a large range of 10⁻⁵–10⁻³ errors/bp/cycle due to the use of different types of investigation methods. In this review, we discuss the different assay methods, their findings on the mutation rates of HIV-1 and how the locations of mutations can be further analyzed for their allosteric effects to allow for new inhibitor designs. Given that HIV is one of the fastest mutating viruses, it serves as a good model for the comprehensive study of viral mutations that can give rise to a more horizontal understanding towards overall viral drug resistance as well as emerging viral diseases.

Structural dynamics and allostery of Rab proteins: strategies for drug discovery and design

Rab proteins represent the largest family of the Rab superfamily guanosine triphosphatase (GTPase). Aberrant human Rab proteins are associated with multiple diseases, including cancers and neurological disorders. Rab subfamily members display subtle conformational variations that render specificity in their physiological functions and can be targeted for subfamily-specific drug design. However, drug discovery efforts have not focused much on targeting Rab allosteric non-nucleotide binding sites which are subjected to less evolutionary pressures to be conserved, hence are likely to offer subfamily specificity and may be less prone to undesirable off-target interactions and side effects. To discover druggable allosteric binding sites, Rab structural dynamics need to be first incorporated using multiple experimentally and computationally obtained structures. The high-dimensional structural data may necessitate feature extraction methods to identify manageable representative structures for subsequent analyses. We have detailed state-of-the-art computational methods to (i) identify binding sites using data on sequence, shape, energy, etc., (ii) determine the allosteric nature of these binding sites based on structural ensembles, residue networks and correlated motions and (iii) identify small molecule binders through structure- and ligand-based virtual screening. To benefit future studies for targeting Rab allosteric sites, we herein detail a refined workflow comprising multiple available computational methods, which have been successfully used alone or in combinations. This workflow is also applicable for drug discovery efforts targeting other medically important proteins. Depending on the structural dynamics of proteins of interest, researchers can select suitable strategies for allosteric drug discovery and design, from the resources of computational methods and tools enlisted in the workflow.

Can Conformational Changes of Proteins Be Represented in Torsion Angle Space? A Study with Rescaled Ridge Regression

Torsion angles are the natural degrees of freedom of protein structures. The ability to determine torsional variations corresponding to observed changes in Cartesian coordinates is highly valuable, notably to investigate the mechanisms of functional conformational changes or to develop computational models of protein dynamics. This issue is far from trivial in practice since the impact of modifying one torsion angle strongly depends on all other angles, and the compounding effects of small variations in bond lengths and valence angles can completely disrupt a protein fold. We demonstrate that naive strategies, such as directly comparing torsion angles between structures without correcting for variations in bond lengths and valence angles or fitting torsional variations without a proper regularization scheme, fail at producing an adequate representation of conformational changes in internal coordinates. In contrast, rescaled ridge regression, a method recently introduced to regularize multidimensional regressions with correlated explanatory variables, is shown to consistently identify a minimal set of torsion angles variations that closely reproduce changes in Cartesian coordinates. This torsional representation of conformational changes is shown to be robust to the choice of experimental structures. It also provides a better agreement with theoretical models of protein dynamics than the Cartesian representation, regarding notably the predominance of low-frequency normal modes in functional motions and the presence, in predicted equilibrium dynamics, of hints of natural selection for specific functional motions. The software is available at https://github.com/ugobas/tnm .

Probing Protein Allostery as a Residue-Specific Concept via Residue Response Maps

Allosteric regulation is a well-established phenomenon defined as a distal conformational or dynamical change of the protein upon allosteric effector binding. Here, we developed a novel approach to delineate allosteric effects in proteins. In this approach, we applied robust machine learning methods, including deep neural network and random forest, on extensive molecular dynamics (MD) simulations to distinguish otherwise similar allosteric states of proteins. Using the PDZ3 domain of PDS-95 as a model protein, we demonstrated that the allosteric effects could be represented as residue-specific properties through two-dimensional property-residue maps, which we refer to as "residue response maps". These maps were constructed through two machine learning methods and could accurately describe how different properties of various residues are affected upon allosteric perturbation on protein. Based on the "residue response maps", we propose allostery as a residue-specific concept, suggesting that all residues could be considered as allosteric residues because each residue "senses" the allosteric events through changing its single or multiple attributes in a quantitatively unique way. The "residue response maps" could be used to fingerprint a protein based on the unique patterns of residue responses upon binding events, providing a novel way to systematically describe the protein allosteric effects of each residue upon perturbation.

Emergence of allosteric drug-resistance mutations: new challenges for allosteric drug discovery

Allosteric drugs have several significant advantages over traditional orthosteric drugs, encompassing higher selectivity and lower toxicity. Although allosteric drugs have potential advantages as therapeutic agents to treat human diseases, allosteric drug-resistance mutations still occur, rendering these drugs ineffective. Here, we review the emergence of allosteric drug-resistance mutations with an emphasis on examples covering clinically important therapeutic targets, including Breakpoint cluster region-Abelson tyrosine kinase (Bcr-Abl), Akt kinase [also called Protein Kinase B (PKB)], isocitrate dehydrogenase (IDH), MAPK/ERK kinase (MEK), and SRC homology 2 domain-containing phosphatase 2 (SHP2). We also discuss challenges associated with tackling allosteric drug resistance and the possible strategies to overcome this issue.

On the Allosteric Effect of nsSNPs and the Emerging Importance of Allosteric Polymorphism

The molecular mechanisms of pathological non-synonymous single-nucleotide polymorphisms are still the object of intensive research. To this end, we explore here whether non-synonymous single-nucleotide polymorphisms can work via allosteric mechanisms. Using structure-based statistical mechanical model of allostery and analyzing energetics of the effects of mutations in a set of 27 proteins with at least 50 pathological SNPs in each molecule, we found that, indeed, some SNPs can work allosterically. We illustrate the molecular basis of disease phenotypes caused by allosteric SNPs with the case studies of human galactose 1-phosphate uridyltransferase (GALT) and glucose-6-phosphate dehydrogenase (G6PD). We also found that mutations of a number of other residues in the protein may cause modulation comparable to those observed for known pathological SNPs. In order to explain this, we propose a notion of allosteric polymorphism, which implies the presence of a number of critical positions in the protein sequence, whose mutations can allosterically disrupt the protein function and result in a disease phenotype. We conclude that the emerging importance of allosteric polymorphism calls for the development of computational framework for analyzing the allosteric effects of mutations and their role in the modulation of protein activity.

AlloDriver: a method for the identification and analysis of cancer driver targets

Identifying the variants that alter protein function is a promising strategy for deciphering the biological consequences of somatic mutations during tumorigenesis, which could provide novel targets for the development of cancer therapies. Here, based on our previously developed method, we present a strategy called AlloDriver that identifies cancer driver genes/proteins as possible targets from mutations. AlloDriver utilizes structural and dynamic features to prioritize potentially functional genes/proteins in individual cancers via mapping mutations generated from clinical cancer samples to allosteric/orthosteric sites derived from three-dimensional protein structures. This strategy exhibits desirable performance in the reemergence of known cancer driver mutations and genes/proteins from clinical samples. Significantly, the practicability of AlloDriver to discover novel cancer driver proteins in head and neck squamous cell carcinoma (HNSC) was tested in a real case of human protein tyrosine phosphatase, receptor type K (PTPRK) through a L1143F driver mutation located at the allosteric site of PTPRK, which was experimentally validated by cell proliferation assay. AlloDriver is expected to help to uncover innovative molecular mechanisms of tumorigenesis by perturbing proteins and to discover novel targets based on cancer driver mutations. The AlloDriver is freely available to all users at http://mdl.shsmu.edu.cn/ALD.

15-deoxy-Δ12,14-Prostaglandin J2 inhibits human soluble epoxide hydrolase by a dual orthosteric and allosteric mechanism

Human soluble epoxide hydrolase (hsEH) is an enzyme responsible for the inactivation of bioactive epoxy fatty acids, and its inhibition is emerging as a promising therapeutical strategy to target hypertension, cardiovascular disease, pain and insulin sensitivity. Here, we uncover the molecular bases of hsEH inhibition mediated by the endogenous 15-deoxy-Δ12,14-Prostaglandin J2 (15d-PGJ2). Our data reveal a dual inhibitory mechanism, whereby hsEH can be inhibited by reversible docking of 15d-PGJ2 in the catalytic pocket, as well as by covalent locking of the same compound onto cysteine residues C423 and C522, remote to the active site. Biophysical characterisations allied with in silico investigations indicate that the covalent modification of the reactive cysteines may be part of a hitherto undiscovered allosteric regulatory mechanism of the enzyme. This study provides insights into the molecular modes of inhibition of hsEH epoxy-hydrolytic activity and paves the way for the development of new allosteric inhibitors.

Emerging roles of allosteric modulators in the regulation of protein-protein interactions (PPIs): A new paradigm for PPI drug discovery

Protein-protein interactions (PPIs) are closely implicated in various types of cellular activities and are thus pivotal to health and disease states. Given their fundamental roles in a wide range of biological processes, the modulation of PPIs has enormous potential in drug discovery. However, owing to the general properties of large, flat, and featureless interfaces of PPIs, previous attempts have demonstrated that the generation of therapeutic agents targeting PPI interfaces is challenging, rendering them almost "undruggable" for decades. To date, rapid progress in chemical and structural biology techniques has promoted the exploitation of allostery as a novel approach in drug discovery. By attaching to allosteric sites that are topologically and spatially distinct from PPI interfaces, allosteric modulators can achieve improved physiochemical properties. Thus, allosteric modulators may represent an alternative strategy to target intractable PPIs and have attracted intense pharmaceutical interest. In this review, we first briefly introduce the characteristics of PPIs and then present different approaches for investigating PPIs, as well as the latest methods for modulating PPIs. Importantly, we comprehensively review the recent progress in the development of allosteric modulators to inhibit or stabilize PPIs. Finally, we conclude with future perspectives on the discovery of allosteric PPI modulators, especially the application of computational methods to aid in allosteric PPI drug discovery.

Allostery in Its Many Disguises: From Theory to Applications

Allosteric regulation plays an important role in many biological processes, such as signal transduction, transcriptional regulation, and metabolism. Allostery is rooted in the fundamental physical properties of macromolecular systems, but its underlying mechanisms are still poorly understood. A collection of contributions to a recent interdisciplinary CECAM (Center Européen de Calcul Atomique et Moléculaire) workshop is used here to provide an overview of the progress and remaining limitations in the understanding of the mechanistic foundations of allostery gained from computational and experimental analyses of real protein systems and model systems. The main conceptual frameworks instrumental in driving the field are discussed. We illustrate the role of these frameworks in illuminating molecular mechanisms and explaining cellular processes, and describe some of their promising practical applications in engineering molecular sensors and informing drug design efforts.

Chokepoints in Mechanical Coupling Associated with Allosteric Proteins: The Pyruvate Kinase Example

Although the critical role of allostery in controlling enzymatic processes is well appreciated, there is a current dearth in our understanding of its underlying mechanisms, including communication between binding sites. One potential key aspect of intersite communication is the mechanical coupling between residues in a protein. Here, we introduce a graph-based computational approach to investigate the mechanical coupling between distant parts of a protein, highlighting effective pathways via which protein motion can transfer energy between sites. In this method, each residue is treated as a node on a weighted, undirected graph, in which the edges are defined by locally correlated motions of those residues and weighted by the strength of the correlation. The method was validated against experimental data on allosteric regulation in the human liver pyruvate kinase as obtained from full-protein alanine-scanning mutagenesis (systematic mutation) studies, as well as computational data on two G-protein-coupled receptors. The method provides semiquantitative information on the regulatory importance of specific structural elements. It is shown that these elements are key for the mechanical coupling between distant parts of the protein by providing effective pathways for energy transfer. It is also shown that, although there are a multitude of energy transfer pathways between distant parts of a protein, these pathways share a few common nodes that represent effective "chokepoints" for the communication.

Toward Comprehensive Allosteric Control over Protein Activity

Universality of allosteric signaling in proteins, molecular machines, and receptors complemented by the great advantages of prospected allosteric drugs in the highly specific, non-competitive, and modulatory nature of their actions calls for deeper theoretical understanding of allosteric communication. We present a computational model that makes it possible to tackle the problem of modulating the energetics of protein allosteric communication. In the context of the energy landscape paradigm, allosteric signaling is always a result of perturbations, such as ligand binding, mutations, and intermolecular interactions. The calculation of local partition functions in the protein harmonic model with perturbations allows us to evaluate the energetics of allosteric communication at the single-residue level. In this framework, Allosteric Signaling Maps are proposed as a tool to exhaustively describe allosteric communication in the protein, to tune already existing signaling, and to design new elements of regulation for taking the protein activity under allosteric control.

Perspective: The promises of a holistic view of proteins-impact on antibody engineering and drug discovery

The reductionist approach is prevalent in biomedical science. However, increasing evidence now shows that biological systems cannot be simply considered as the sum of its parts. With experimental, technological, and computational advances, we can now do more than view parts in isolation, thus we propose that an increasing holistic view (where a protein is investigated as much as a whole as possible) is now timely. To further advocate this, we review and discuss several studies and applications involving allostery, where distant protein regions can cross-talk to influence functionality. Therefore, we believe that an increasing big picture approach holds great promise, particularly in the areas of antibody engineering and drug discovery in rational drug design.

Dissecting conformational changes in APP's transmembrane domain linked to ε-efficiency in familial Alzheimer's disease

The mechanism by which familial Alzheimer's disease (FAD) mutations within the transmembrane domain (TMD) of the Amyloid Precursor Protein (APP) affect ε-endoproteolysis is only poorly understood. Thereby, mutations in the cleavage domain reduce ε-efficiency of γ-secretase cleavage and some even shift entry into production lines. Since cleavage occurs within the TMD, a relationship between processing and TMD structure and dynamics seems obvious. Using molecular dynamic simulations, we dissect the dynamic features of wild-type and seven FAD-mutants into local and global components. Mutations consistently enhance hydrogen-bond fluctuations upstream of the ε-cleavage sites but maintain strong helicity there. Dynamic perturbation-response scanning reveals that FAD-mutants target backbone motions utilized in the bound state. Those motions, obscured by large-scale motions in the pre-bound state, provide (i) a dynamic mechanism underlying the proposed coupling between binding and ε-cleavage, (ii) key sites consistent with experimentally determined docking sites, and (iii) the distinction between mutants and wild-type.

Reversing allosteric communication: From detecting allosteric sites to inducing and tuning targeted allosteric response

The omnipresence of allosteric regulation together with the fundamental role of structural dynamics in this phenomenon have initiated a great interest to the detection of regulatory exosites and design of corresponding effectors. However, despite a general consensus on the key role of dynamics most of the earlier efforts on the prediction of allosteric sites are heavily crippled by the static nature of the underlying methods, which are either structure-based approaches seeking for deep surface pockets typical for “traditional” orthosteric drugs or sequence-based techniques exploiting the conservation of protein sequences. Because of the critical role of global protein dynamics in allosteric signaling, we investigate the hypothesis of reversibility in allosteric communication, according to which allosteric sites can be detected via the perturbation of the functional sites. The reversibility is tested here using our structure-based perturbation model of allostery, which allows one to analyze the causality and energetics of allosteric communication. We validate the “reverse perturbation” hypothesis and its predictive power on a set of classical allosteric proteins, then, on the independent extended benchmark set. We also show that, in addition to known allosteric sites, the perturbation of the functional sites unravels rather extended protein regions, which can host latent regulatory exosites. These protein parts that are dynamically coupled with functional sites can also be used for inducing and tuning allosteric communication, and an exhaustive exploration of the per-residue contributions to allosteric effects can eventually lead to the optimal modulation of protein activity. The site-effector interactions necessary for a specific mode and level of allosteric communication can be fine-tuned by adjusting the site’s structure to an available effector molecule and by the design or selection of an appropriate ligand.

Recent advances in the development of allosteric drugs allow one to fully appreciate the sheer power of allosteric effectors in the avoiding toxicity, receptor desensitization and modulatory rather than on/off mode of action, compared to the traditional orthosteric compounds. The detection of allosteric sites is one of the major challenges in the quest for allosteric drugs. This work proposes a “reverse perturbation” approach for identifying allosteric sites as a result of a perturbation applied to the functional ones. We show that according to the traditional Monod-Changeux-Jacob’s definition of allostery, considering non-overlapping regulatory and functional sites is a critical prerequisite for the successful detection of allosteric sites. Using the reverse perturbation method, it is possible to determine wide protein regions with a potential to induce an allosteric response and to adjust its strength. Further studies on inducing and fine-tuning of allosteric signalling seem to be of a great importance for efficient design of non-orthosteric ligands in the development of novel drugs.

Allosteric Effects between the Antibody Constant and Variable Regions: A Study of IgA Fc Mutations on Antigen Binding

Therapeutic antibodies have shifted the paradigm of disease treatments from small molecules to biologics, especially in cancer therapy. Despite the increasing number of antibody candidates, much remains unknown about the antibody and how its various regions interact. Recent findings showed that the antibody constant region can govern localization effects that are useful in reducing side effects due to systemic circulation by the commonly used IgG isotypes. Given their localized mucosal effects, IgA antibodies are increasingly promising therapeutic biologics. While the antibody Fc effector cell activity has been a focus point, recent research showed that the Fc could also influence antigen binding, challenging the conventional idea of region-specific antibody functions. To investigate this, we analysed the IgA antibody constant region and its distal effects on the antigen binding regions using recombinant Pertuzumab IgA1 and IgA2 variants. We found that mutations in the C-region reduced Her2 binding experimentally, and computational structural analysis showed that allosteric communications were highly dependent on the antibody hinge, providing strong evidence that we should consider antibodies as whole proteins rather than a sum of functional regions.

A computational study for rational HIV-1 non-nucleoside reverse transcriptase inhibitor selection and the discovery of novel allosteric pockets for inhibitor design

HIV drug resistant mutations that render the current Highly Active Anti-Retroviral Therapy (HAART) cocktail drugs ineffective are increasingly reported. To study the mechanisms of these mutations in conferring drug resistance, we computationally analyzed 14 reverse transcriptase (RT) structures of HIV-1 on the following parameters: drug-binding pocket volume, allosteric effects caused by the mutations, and structural thermal stability. We constructed structural correlation-based networks of the mutant RT-drug complexes and the analyses support the use of efavirenz (EFZ) as the first-line drug, given that cross-resistance is least likely to develop from EFZ-resistant mutations. On the other hand, rilpivirine (RPV)-resistant mutations showed the highest cross-resistance to the other non-nucleoside RT inhibitors. With significant drug cross-resistance associated with the known allosteric drug-binding site, there is a need to identify new allosteric druggable sites in the structure of RT. Through computational analyses, we found such a novel druggable pocket on the HIV-1 RT structure that is comparable with the original allosteric drug site, opening the possibility to the design of new inhibitors.

Modeling the full length HIV-1 Gag polyprotein reveals the role of its p6 subunit in viral maturation and the effect of non-cleavage site mutations in protease drug resistance

HIV polyprotein Gag is increasingly found to contribute to protease inhibitor resistance. Despite its role in viral maturation and in developing drug resistance, there remain gaps in the knowledge of the role of certain Gag subunits (e.g. p6), and that of non-cleavage mutations in drug resistance. As p6 is flexible, it poses a problem for structural experiments, and is hence often omitted in experimental Gag structural studies. Nonetheless, as p6 is an indispensable component for viral assembly and maturation, we have modeled the full length Gag structure based on several experimentally determined constraints and studied its structural dynamics. Our findings suggest that p6 can mechanistically modulate Gag conformations. In addition, the full length Gag model reveals that allosteric communication between the non-cleavage site mutations and the first Gag cleavage site could possibly result in protease drug resistance, particularly in the absence of mutations in Gag cleavage sites. Our study provides a mechanistic understanding to the structural dynamics of HIV-1 Gag, and also proposes p6 as a possible drug target in anti-HIV therapy.

Insulin-Degrading Enzyme in the Fight against Alzheimer's Disease

After decades of research and clinical trials there is still no cure for Alzheimer's disease (AD). While impaired clearance of amyloid beta (Aβ) peptides is considered as one of the major causes of AD, it was recently complemented by a potential role of other toxic amyloidogenic species. Insulin-degrading enzyme (IDE) is the proteolytic culprit of various β-forming peptides, both extracellular and intracellular. On the basis of demonstrated allosteric activation of IDE against Aβ, it is possible to propose a new strategy for the targeted IDE-based cleansing of different toxic aggregation-prone peptides. Consequently, specific allosteric activation of IDE coupled with state-of-the-art compound delivery and CRISP-Cas9 technique of transgene insertion can be instrumental in the fight against AD and related neurodegenerative maladies.

An engineered photoswitchable mammalian pyruvate kinase

Changes in allosteric regulation of glycolytic enzymes have been linked to metabolic reprogramming involved in cancer. Remarkably, allosteric mechanisms control enzyme function at significantly shorter time-scales compared to the long-term effects of metabolic reprogramming on cell proliferation. It remains unclear if and how the speed and reversibility afforded by rapid allosteric control of metabolic enzymes is important for cell proliferation. Tools that allow specific, dynamic modulation of enzymatic activities in mammalian cells would help address this question. Towards this goal, we have used molecular dynamics simulations to guide the design of mPKM2 internal light/oxygen/voltage-sensitive domain 2 (LOV2) fusion at position D24 (PiL[D24]), an engineered pyruvate kinase M2 (PKM2) variant that harbours an insertion of the light-sensing LOV2 domain from Avena Sativa within a region implicated in allosteric regulation by fructose 1,6-bisphosphate (FBP). The LOV2 photoreaction is preserved in the PiL[D24] chimera and causes secondary structure changes that are associated with a 30% decrease in the Km of the enzyme for phosphoenolpyruvate resulting in increased pyruvate kinase activity after light exposure. Importantly, this change in activity is reversible upon light withdrawal. Expression of PiL[D24] in cells leads to light-induced increase in labelling of pyruvate from glucose. PiL[D24] therefore could provide a means to modulate cellular glucose metabolism in a remote manner and paves the way for studying the importance of rapid allosteric phenomena in the regulation of metabolism and enzyme control.

Machine Learning and Network Analysis of Molecular Dynamics Trajectories Reveal Two Chains of Red/Ox-specific Residue Interactions in Human Protein Disulfide Isomerase

The human protein disulfide isomerase (hPDI), is an essential four-domain multifunctional enzyme. As a result of disulfide shuffling in its terminal domains, hPDI exists in two oxidation states with different conformational preferences which are important for substrate binding and functional activities. Here, we address the redox-dependent conformational dynamics of hPDI through molecular dynamics (MD) simulations. Collective domain motions are identified by the principal component analysis of MD trajectories and redox-dependent opening-closing structure variations are highlighted on projected free energy landscapes. Then, important structural features that exhibit considerable differences in dynamics of redox states are extracted by statistical machine learning methods. Mapping the structural variations to time series of residue interaction networks also provides a holistic representation of the dynamical redox differences. With emphasizing on persistent long-lasting interactions, an approach is proposed that compiled these time series networks to a single dynamic residue interaction network (DRIN). Differential comparison of DRIN in oxidized and reduced states reveals chains of residue interactions that represent potential allosteric paths between catalytic and ligand binding sites of hPDI.

Reprint of Pharmacological and molecular characterization of the positive allosteric modulators of metabotropic glutamate receptor 2

The metabotropic glutamate receptor 2 (mGlu₂) plays an important role in the presynaptic control of glutamate release and several mGlu₂ positive allosteric modulators (PAMs) have been under assessment for their potential as antipsychotics. The binding mode of mGlu₂ PAMs is better characterized in functional terms while few data are available on the relationship between allosteric and orthosteric binding sites. Pharmacological studies characterizing binding and effects of two different chemical series of mGlu₂ PAMs are therefore carried out here using the radiolabeled mGlu₂ agonist ³[H]-LY354740 and mGlu₂ PAM ³[H]-2,2,2-TEMPS. A multidimensional approach to the PAM mechanism of action shows that mGlu₂ PAMs increase the affinity of ³[H]-LY354740 for the orthosteric site of mGlu2 as well as the number of ³[H]-LY354740 binding sites. ³[H]-2,2,2-TEMPS binding is also enhanced by the presence of LY354740. New residues in the allosteric rat mGlu2 binding pocket are identified to be crucial for the PAMs ligand binding, among these Tyr^3.40 and Asn^5.46. Also of remark, in the described experimental conditions S731A (Ser^5.42) residue is important only for the mGlu₂ PAM LY487379 and not for the compound PAM-1: an example of the structural differences among these mGlu₂ PAMs. This study provides a summary of the information generated in the past decade on mGlu₂ PAMs adding a detailed molecular investigation of PAM binding mode. Differences among mGlu₂ PAM compounds are discussed as well as the mGlu2 regions interacting with mGlu₂ PAM and NAM agents and residues driving mGlu2 PAM selectivity. This article is part of the Special Issue entitled 'Metabotropic Glutamate Receptors, 5 years on'.

Toward Allosterically Increased Catalytic Activity of Insulin-Degrading Enzyme against Amyloid Peptides

The physiological role of insulin-degrading enzyme (IDE) in the intracytosolic clearance of amyloid β (Aβ) and other amyloid-like peptides supports a hypothesis that human IDE hyperactivation could be therapeutically beneficial for the treatment of late-onset Alzheimer's disease (AD). The major challenge standing in the way of this goal is increasing the specific catalytic activity of IDE against the Aβ substrate. There were previous indications that the allosteric mode of IDE activity regulation could potentially provide a highly specific path toward degradation of amyloid-like peptides, while not dramatically affecting activity against other substrates. Recently developed theoretical concepts are used here to explore potential allosteric modulation of the IDE activity as a result of single-residue mutations. Five candidates are selected for experimental follow-up and allosteric free energy calculations: Ser137Ala, Lys396Ala, Asp426Ala, Phe807Ala, and Lys898Ala. Our experiments show that three mutations (Ser137Ala, Phe807Ala, and Lys898Ala) decrease the K_m of the Aβ substrate. Mutation Lys898Ala results in increased catalytic activity of IDE; on the other hand, Lys364Ala does not change the activity and Asp426Ala diminishes it. Quantifying effects of mutations in terms of allosteric free energy, we show that favorable mutations lead to stabilization of the catalytic sites and other function-relevant distal sites as well as increased dynamics of the IDE-N and IDE-C halves that allow efficient substrate entrance and cleavage. A possibility for intramolecular upregulation of IDE activity against amyloid peptides via allosteric mutations calls for further investigations in this direction. Ultimately, we are hopeful it will lead to the development of IDE-based drugs for the treatment of the late-onset form of AD characterized by an overall impairment of Aβ clearance.

Protein function machinery: from basic structural units to modulation of activity

Contemporary protein structure is a result of the trade off between the laws of physics and the evolutionary selection. The polymer nature of proteins played a decisive role in establishing the basic structural and functional units of soluble proteins. We discuss how these elementary building blocks work in the hierarchy of protein domain structure, co-translational folding, as well as in enzymatic activity and molecular interactions. Next, we consider modulators of the protein function, such as intermolecular interactions, disorder-to-order transitions, and allosteric signaling, acting via interference with the protein's structural dynamics. We also discuss the post-translational modifications, which is a complementary intricate mechanism evolved for regulation of protein functions and interactions. In conclusion, we assess an anticipated contribution of discussed topics to the future advancements in the field.

Intrinsic K-Ras dynamics: A novel molecular dynamics data analysis method shows causality between residue pair motions

K-Ras is the most frequently mutated oncogene in human cancers, but there are still no drugs that directly target it in the clinic. Recent studies utilizing dynamics information show promising results for selectively targeting mutant K-Ras. However, despite extensive characterization, the mechanisms by which K-Ras residue fluctuations transfer allosteric regulatory information remain unknown. Understanding the direction of information flow can provide new mechanistic insights for K-Ras targeting. Here, we present a novel approach –conditional time-delayed correlations (CTC) – using the motions of all residue pairs of a protein to predict directionality in the allosteric regulation of the protein fluctuations. Analyzing nucleotide-dependent intrinsic K-Ras motions with the new approach yields predictions that agree with the literature, showing that GTP-binding stabilizes K-Ras motions and leads to residue correlations with relatively long characteristic decay times. Furthermore, our study is the first to identify driver-follower relationships in correlated motions of K-Ras residue pairs, revealing the direction of information flow during allosteric modulation of its nucleotide-dependent intrinsic activity: active K-Ras Switch-II region motions drive Switch-I region motions, while α-helix-3L7 motions control both. Our results provide novel insights for strategies that directly target mutant K-Ras.

Allostery: An Overview of Its History, Concepts, Methods, and Applications

The concept of allostery has evolved in the past century. In this Editorial, we briefly overview the history of allostery, from the pre-allostery nomenclature era starting with the Bohr effect (1904) to the birth of allostery by Monod and Jacob (1961). We describe the evolution of the allostery concept, from a conformational change in a two-state model (1965, 1966) to dynamic allostery in the ensemble model (1999); from multi-subunit (1965) proteins to all proteins (2004). We highlight the current available methods to study allostery and their applications in studies of conformational mechanisms, disease, and allosteric drug discovery. We outline the challenges and future directions that we foresee. Altogether, this Editorial narrates the history of this fundamental concept in the life sciences, its significance, methodologies to detect and predict it, and its application in a broad range of living systems.