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

Allosteric drugs: New principles and design approaches

Focusing on an important biomedical implication of allostery - design of allosteric drugs, we describe characteristics of allosteric sites, effectors, and their modes of actions distinguishing them from the orthosteric counterparts and calling for new principles and protocols in the quests for allosteric drugs. We show the importance of considering both binding affinity and allosteric signaling in establishing the structure-activity relationships (SARs) toward design of allosteric effectors, arguing that pairs of allosteric sites and their effector ligands - the site-effector pairs - should be generated and adjusted simultaneously in the framework of what we call directed design protocol. Key ideas and approaches for designing allosteric effectors including reverse perturbation, targeted and agnostic analysis are also discussed here. Several promising computational approaches are highlighted, along with the need for and potential advantages of utilizing generative models to facilitate discovery/design of new allosteric drugs.

Inhibition of insulin-degrading enzyme in human neurons promotes amyloid-β deposition

Alzheimer's disease (AD) is characterised by the aggregation and deposition of amyloid-β (Aβ) peptides in the human brain. In age-related late-onset AD, deficient degradation and clearance, rather than enhanced production, of Aβ contributes to disease pathology. In the present study, we assessed the contribution of the two key Aβ-degrading zinc metalloproteases, insulin-degrading enzyme (IDE) and neprilysin (NEP), to Aβ degradation in human induced pluripotent stem cell (iPSC)-derived cortical neurons. Using an Aβ fluorescence polarisation assay, inhibition of IDE but not of NEP, blocked the degradation of Aβ by human neurons. When the neurons were grown in a 3D extracellular matrix to visualise Aβ deposition, inhibition of IDE but not NEP, increased the number of Aβ deposits. The resulting Aβ deposits were stained with the conformation-dependent, anti-amyloid antibodies A11 and OC that recognise Aβ aggregates in the human AD brain. Inhibition of the Aβ-forming β-secretase prevented the formation of the IDE-inhibited Aβ deposits. These data indicate that inhibition of IDE in live human neurons grown in a 3D matrix increased the deposition of Aβ derived from the proteolytic cleavage of the amyloid precursor protein. This work has implications for strategies aimed at enhancing IDE activity to promote Aβ degradation in AD.

Coevolution-based prediction of key allosteric residues for protein function regulation

Allostery is fundamental to many biological processes. Due to the distant regulation nature, how allosteric mutations, modifications, and effector binding impact protein function is difficult to forecast. In protein engineering, remote mutations cannot be rationally designed without large-scale experimental screening. Allosteric drugs have raised much attention due to their high specificity and possibility of overcoming existing drug-resistant mutations. However, optimization of allosteric compounds remains challenging. Here, we developed a novel computational method KeyAlloSite to predict allosteric site and to identify key allosteric residues (allo-residues) based on the evolutionary coupling model. We found that protein allosteric sites are strongly coupled to orthosteric site compared to non-functional sites. We further inferred key allo-residues by pairwise comparing the difference of evolutionary coupling scores of each residue in the allosteric pocket with the functional site. Our predicted key allo-residues are in accordance with previous experimental studies for typical allosteric proteins like BCR-ABL1, Tar, and PDZ3, as well as key cancer mutations. We also showed that KeyAlloSite can be used to predict key allosteric residues distant from the catalytic site that are important for enzyme catalysis. Our study demonstrates that weak coevolutionary couplings contain important information of protein allosteric regulation function. KeyAlloSite can be applied in studying the evolution of protein allosteric regulation, designing and optimizing allosteric drugs, and performing functional protein design and enzyme engineering.

Exchange Broadening Underlies the Enhancement of IDE-Dependent Degradation of Insulin by Anionic Membranes

Insulin-degrading enzyme (IDE) is an evolutionarily conserved ubiquitous zinc metalloprotease implicated in the efficient degradation of insulin monomer. However, IDE also degrades monomers of amyloidogenic peptides associated with disease, complicating the development of IDE inhibitors. In this work, we investigated the effects of the lipid composition of membranes on the IDE-dependent degradation of insulin. Kinetic analysis based on chromatography and insulin's helical circular dichroic signal showed that the presence of anionic lipids in membranes enhances IDE's activity toward insulin. Using NMR spectroscopy, we discovered that exchange broadening underlies the enhancement of IDE's activity. These findings, together with the adverse effects of anionic membranes in the self-assembly of IDE's amyloidogenic substrates, suggest that the lipid composition of membranes is a key determinant of IDE's ability to balance the levels of its physiologically and pathologically relevant substrates and achieve proteostasis.

The Role of a Pathological Interaction between β-amyloid and Mitochondria in the Occurrence and Development of Alzheimer's Disease

Alzheimer's disease (AD) is one of the most common neurodegenerative diseases in existence. It is characterized by an impaired cognitive function that is due to a progressive loss of neurons in the brain. Extracellular β-amyloid (Aβ) plaques are the main pathological features of the disease. In addition to abnormal protein aggregation, increased mitochondrial fragmentation, altered expression of the genes involved in mitochondrial biogenesis, disruptions in the ER-mitochondria interaction, and mitophagy are observed. Reactive oxygen species are known to affect Aβ expression and aggregation. In turn, oligomeric and aggregated Aβ cause mitochondrial disorders. In this review, we summarize available knowledge about the pathological effects of Aβ on mitochondria and the potential molecular targets associated with proteinopathy and mitochondrial dysfunction for the pharmacological treatment of Alzheimer's disease.

Learning about allosteric drugs and ways to design them

While the accelerating quest for precision medicine requires new individually targeting and selective drugs, and the ability to work with so-called undruggable targets, the realm of allosteric drugs meeting this need remains largely uncharted. Generalizing the observations on two major drug targets with widely observed inherent allostery, GPCRs and kinases, we describe and discuss basic allosteric modes of action that are universally applicable in all types of structures and functions. Using examples of Class A GPCRs and CMGC protein kinases, we show how Allosteric Signalling and Probing Fingerprints can be used to identify potential allosteric sites and reveal effector-leads that may serve as a starting point for the development of allosteric drugs targeting these regulatory sites. A set of distinct characteristics of allosteric ligands was established, which highlights the versatility of their design and make them advantageous before their orthosteric counterparts in personalized medicine. We argue that rational design of allosteric drugs should begin with the search for latent sites or design of non-natural binding sites followed by fragment-based design of allosteric ligands and by the mutual adjustment of the site-ligand pair in order to achieve required effects. On the basis of the perturbative nature and reversibility of allosteric communication, we propose a generic protocol for computational design of allosteric effectors, enabling also the allosteric tuning of biologics, in obtaining allosteric control over protein functions.

Structural Bioinformatic Survey of Protein-Small Molecule Interfaces Delineates the Role of Glycine in Surface Pocket Formation

With a structural bioinformatic approach, we have explored amino acid compositions at PISA defined interfaces between small molecules and proteins that are contained in an optimized subset of 11,351 PDB files. The use of a series of restrictions, to prevent redundancy and biases from interactions between amino acids with charged side chains and ions, yielded a final data set of 45,230 protein-small molecule interfaces. We have compared occurrences of natural amino acids in surface exposed regions and binding sites for all the proteins of our data set. From our structural bioinformatic survey, the most relevant signal arose from the unexpected Gly abundance at enzyme catalytic sites. This finding suggested that Gly must have a fundamental role in stabilizing concave protein surface moieties. Subsequently, we have tried to predict the effect of in silico Gly mutations in hen egg white lysozyme to optimize those conditions that can reshape the protein surface with the appearance of new pockets. Replacing amino acids having bulky side chains with Gly in specific protein regions seems a feasible way for designing proteins with additional surface pockets, which can alter protein surface dynamics, therefore, representing controllable switches for protein activity.

A catalytic dyad modulates conformational change in the CO2-fixing flavoenzyme 2-ketopropyl coenzyme M oxidoreductase/carboxylase

2-Ketopropyl-coenzyme M oxidoreductase/carboxylase (2-KPCC) is a member of the flavin and cysteine disulfide containing oxidoreductase family (DSOR) that catalyzes the unique reaction between atmospheric CO2 and a ketone/enolate nucleophile to generate acetoacetate. However, the mechanism of this reaction is not well understood. Here, we present evidence that 2-KPCC, in contrast to the well-characterized DSOR enzyme glutathione reductase, undergoes conformational changes during catalysis. Using a suite of biophysical techniques including limited proteolysis, differential scanning fluorimetry, and native mass spectrometry in the presence of substrates and inhibitors, we observed conformational differences between different ligand-bound 2-KPCC species within the catalytic cycle. Analysis of site-specific amino acid variants indicated that 2-KPCC-defining residues, Phe501-His506, within the active site are important for transducing these ligand induced conformational changes. We propose that these conformational changes promote substrate discrimination between H+ and CO2 to favor the metabolically preferred carboxylation product, acetoacetate.

Conservation and diversity in allosteric fingerprints of proteins for evolutionary-inspired engineering and design

Hand-in-hand work of physics and evolution delivered protein universe with diversity of forms, sizes, and functions. Pervasiveness and advantageous traits of allostery made it an important component of the protein function regulation, calling for thorough investigation of its structural determinants and evolution. Learning directly from nature, we explored here allosteric communication in several major folds and repeat proteins, including α/β and β-barrels, β-propellers, Ig-like fold, ankyrin and α/β leucine-rich repeat proteins, which provide structural platforms for many different enzymatic and signalling functions. We obtained a picture of conserved allosteric communication characteristic in different fold types, modifications of the structure-driven signalling patterns via sequence-determined divergence to specific functions, as well as emergence and potential diversification of allosteric regulation in multi-domain proteins and oligomeric assemblies. Our observations will be instrumental in facilitating the engineering and de novo design of proteins with allosterically regulated functions, including development of therapeutic biologics. In particular, results described here may guide the identification of the optimal structural platforms (e.g. fold type, size, and oligomerization states) and the types of diversifications/perturbations, such as mutations, effector binding, and order-disorder transition. The tunable allosteric linkage across distant regions can be used as a pivotal component in the design/engineering of modular biological systems beyond the traditional scaffolding function.

Single-cell RNA Seq reveals cellular landscape-specific characteristics and potential etiologies for adolescent idiopathic scoliosis

BACKGROUNDS

Abnormal vertebral growth and development have been found in adolescent idiopathic scoliosis (AIS) patients, and the proliferation and differentiation of bone development-related cells play important roles in its pathogenesis. However, a comprehensive single-cell-level differentiation roadmap in AIS has not been achieved.

METHODS

The present study compared the single-cell level cellular landscapes of spinal cancellous bone tissues between AIS patients and healthy subjects using high throughput single-cell RNA sequencing (scRNA-seq), which covers multiple cellular lineages including osteoblast, chondrocyte, osteoclast and related immunocytes. We constructed the differentiation trajectories of bone development-related cell lineages through pseudotime analysis, and the intercellular-communication networks between bone development-related cells and immunocytes were further developed.

RESULTS

A total of 11 distinct cell clusters were identified according to the genome-wide transcriptome profiles. t-Distributed stochastic neighbor embedding (t-SNE) analysis showed that mesenchymal stem cells (MSC) were classified into three subtypes: MSC-LOXL2, MSC-IGFBP5, and MSC-GJA1. Gene ontology (GO) analysis showed that MSC-GJA1 might possess greater osteoblast differentiation potential than the others. MSC-IGFBP5 was the specific MSC subtype observed only in AIS. There were two distinct gene expression clusters: OB-DPT and OB-OLFML2B, and the counts of osteoblasts derived from AIS was significantly less than that of non-AIS subjects. In AIS patients, MSC-IGFBP5 failed to differentiate into osteoblasts and exhibited negative regulation of cell proliferation and enhanced cell death. CPC-PCNA was found to be the specific chondrocyte progenitor cell (CPC) subtype observed only in AIS patients. The cell counts of OC-BIRC3 in AIS were less than those in controls. Pseudotime analysis suggested two possible distinct osteoclast differentiation patterns in AIS and control subjects. Monocytes in AIS mainly differentiated into OC-CRISP3.

CONCLUSIONS

Our single-cell analysis first revealed differences existed in the cellular states between AIS patients and healthy subjects and found the differentiation disruption of specific MSC and CPC clusters in AIS. Cell communication analysis provided the possible pathogenesis of osteoblast and chondrocyte differentiation dysfunction in AIS.

Insulin-degrading enzyme: an ally against metabolic and neurodegenerative diseases

Insulin-degrading enzyme (IDE) function goes far beyond its known proteolytic role as a regulator of insulin levels. IDE has a wide substrate promiscuity, degrading several proteins such as amyloid-β peptide, glucagon, islet amyloid polypeptide (IAPP) and insulin-like growth factors, that have diverse physiological and pathophysiological functions. Importantly, IDE plays other non-proteolytical functions such as a chaperone/dead-end chaperone, an E1-ubiquitin activating enzyme, and a proteasome modulator. It also responds as a heat shock protein, regulating cellular proteostasis. Notably, amyloidogenic proteins such as IAPP, amyloid-β and α-synuclein have been reported as substrates for IDE chaperone activity. This is of utmost importance as failure of IDE may result in increased protein aggregation, a key hallmark in the pathogenesis of beta cells in type 2 diabetes mellitus and of neurons in neurodegenerative diseases such as Alzheimer's and Parkinson's disease. In this review, we focus on the biochemical and biophysical properties of IDE and the regulation of its physiological functions. We further raise the hypothesis that IDE plays a central role in the pathological context of dysmetabolic and neurodegenerative diseases and discuss its potential as a therapeutic target. This article is protected by copyright. All rights reserved.

Degradation of Alzheimer's Amyloid-β by a Catalytically Inactive Insulin-Degrading Enzyme

It is known that insulin-degrading-enzyme (IDE) plays a crucial role in the clearance of Alzheimer's amyloid-β (Aβ). The cysteine-free IDE mutant (cf-E111Q-IDE) is catalytically inactive against insulin, but its effect on Aβ degradation is unknown that would help in the allosteric modulation of the enzyme activity. Herein, the degradation of Aβ(1-40) by cf-E111Q-IDE via a non-chaperone mechanism is demonstrated by NMR and LC-MS, and the aggregation of fragmented peptides is characterized using fluorescence and electron microscopy. cf-E111Q-IDE presented a reduced effect on the aggregation kinetics of Aβ(1-40) when compared with the wild-type IDE. Whereas LC-MS and diffusion ordered NMR spectroscopy revealed the generation of Aβ fragments by both wild-type and cf-E111Q-IDE. The aggregation propensities and the difference in the morphological phenotype of the full-length Aβ(1-40) and its fragments are explained using multi-microseconds molecular dynamics simulations. Notably, our results reveal that zinc binding to Aβ(1-40) inactivates cf-E111Q-IDE's catalytic function, whereas zinc removal restores its function as evidenced from high-speed AFM, electron microscopy, chromatography, and NMR results. These findings emphasize the catalytic role of cf-E111Q-IDE on Aβ degradation and urge the development of zinc chelators as an alternative therapeutic strategy that switches on/off IDE's function.

Expression of IDE and PITRM1 genes in ERN1 knockdown U87 glioma cells: effect of hypoxia and glucose deprivation

OBJECTIVE

The aim of the present investigation was to study the expression of genes encoding polyfunctional proteins insulinase (insulin degrading enzyme, IDE) and pitrilysin metallopeptidase 1 (PITRM1) in U87 glioma cells in response to inhibition of endoplasmic reticulum stress signaling mediated by ERN1/IRE1 (endoplasmic reticulum to nucleus signaling 1) for evaluation of their possible significance in the control of metabolism through ERN1 signaling as well as hypoxia, glucose and glutamine deprivations.

METHODS

The expression level of IDE and PITRM1 genes was studied in control and ERN1 knockdown U87 glioma cells under glucose and glutamine deprivations as well as hypoxia by quantitative polymerase chain reaction.

RESULTS

It was found that the expression level of IDE and PITRM1 genes was down-regulated in ERN1 knockdown (without ERN1 protein kinase and endoribonuclease activity) glioma cells in comparison with the control glioma cells, being more significant for PITRM1 gene. We also found up-regulation of microRNA MIR7-2 and MIRLET7A2, which have specific binding sites in 3'-untranslated region of IDE and PITRM1 mRNAs, correspondingly, and can participate in posttranscriptional regulation of these mRNA expressions. Only inhibition of ERN1 endoribonuclease did not change significantly the expression of IDE and PITRM1 genes in glioma cells. The expression of IDE and PITRM1 genes is preferentially regulated by ERN1 protein kinase. We also showed that hypoxia down-regulated the expression of IDE and PITRM1 genes and that knockdown of ERN1 signaling enzyme function modified the response of these gene expressions to hypoxia. Glucose deprivation increased the expression level of IDE and PITRM1 genes, but ERN1 knockdown enhanced only the effect of glucose deprivation on PITRM1 gene expression. Glutamine deprivation did not affect the expression of IDE gene in both types of glioma cells, but up-regulated PITRM1 gene and this up-regulation was stronger in ERN1 knockdown cells.

CONCLUSIONS

Results of this investigation demonstrate that ERN1 knockdown significantly decreases the expression of IDE and PITRM1 genes by ERN1 protein kinase mediated mechanism. The expression of both studied genes was sensitive to hypoxia as well as glucose deprivation and dependent on ERN1 signaling in gene-specific manner. It is possible that the level of these genes expression under hypoxia and glucose deprivation is a result of complex interaction of variable endoplasmic reticulum stress related and unrelated regulatory factors and contributed to the control of the cell metabolism.

Recent advances in user-friendly computational tools to engineer protein function

Progress in technology and algorithms throughout the past decade has transformed the field of protein design and engineering. Computational approaches have become well-engrained in the processes of tailoring proteins for various biotechnological applications. Many tools and methods are developed and upgraded each year to satisfy the increasing demands and challenges of protein engineering. To help protein engineers and bioinformaticians navigate this emerging wave of dedicated software, we have critically evaluated recent additions to the toolbox regarding their application for semi-rational and rational protein engineering. These newly developed tools identify and prioritize hotspots and analyze the effects of mutations for a variety of properties, comprising ligand binding, protein-protein and protein-nucleic acid interactions, and electrostatic potential. We also discuss notable progress to target elusive protein dynamics and associated properties like ligand-transport processes and allosteric communication. Finally, we discuss several challenges these tools face and provide our perspectives on the further development of readily applicable methods to guide protein engineering efforts.

Mechanism of allosteric activation of SIRT6 revealed by the action of rationally designed activators

The recent discovery of activator compounds binding to an allosteric site on the NAD⁺-dependent protein lysine deacetylase, sirtuin 6 (SIRT6) has attracted interest and presents a pharmaceutical target for aging-related and cancer diseases. However, the mechanism underlying allosteric activation of SIRT6 by the activator MDL-801 remains largely elusive because no major conformational changes are observed upon activator binding. By combining molecular dynamics simulations with biochemical and kinetic analyses of wild-type SIRT6 and its variant M136A, we show that conformational rotation of 2-methyl-4-fluoro-5-bromo substituent on the right phenyl ring (R-ring) of MDL-801, which uncovers previously unseen hydrophobic interactions, contributes to increased activating deacetylation activity of SIRT6. This hypothesis is further supported by the two newly synthesized MDL-801 derivatives through the removal of the 5-Br atom on the R-ring (MDL-801-D1) or the restraint of the rotation of the R-ring (MDL-801-D2). We further propose that the 5-Br atom serves as an allosteric driver that controls the ligand allosteric efficacy. Our study highlights the effect of allosteric enzyme catalytic activity by activator binding and provides a rational approach for enhancing deacetylation activity.

Exploring the Allosteric Territory of Protein Function

While the pervasiveness of allostery in proteins is commonly accepted, we further show the generic nature of allosteric mechanisms by analyzing here transmembrane ion-channel viroporin 3a and RNA-dependent RNA polymerase (RdRp) from SARS-CoV-2 along with metabolic enzymes isocitrate dehydrogenase 1 (IDH1) and fumarate hydratase (FH) implicated in cancers. Using the previously developed structure-based statistical mechanical model of allostery (SBSMMA), we share our experience in analyzing the allosteric signaling, predicting latent allosteric sites, inducing and tuning targeted allosteric response, and exploring the allosteric effects of mutations. This, yet incomplete list of phenomenology, forms a complex and unique allosteric territory of protein function, which should be thoroughly explored. We propose a generic computational framework, which not only allows one to obtain a comprehensive allosteric control over proteins but also provides an opportunity to approach the fragment-based design of allosteric effectors and drug candidates. The advantages of allosteric drugs over traditional orthosteric compounds, complemented by the emerging role of the allosteric effects of mutations in the expansion of the cancer mutational landscape and in the increased mutability of viral proteins, leave no choice besides further extensive studies of allosteric mechanisms and their biomedical implications.

Insulin-degrading enzyme higher in subjects with metabolic syndrome

Metabolic syndrome (MS) is comprised of a cluster of abnormalities in glucose, lipid, and vascular homeostasis, which is most commonly linked to abdominal obesity. MS heralds increased risk for development of diabetes and is linked to impairment in insulin signaling. Insulin-degrading enzyme (IDE) is one of the mechanisms through which insulin blood levels are maintained. It has been previously suggested that controlling IDE levels could provide yet another potential therapeutic approach in diabetes. Here we aim to investigate whether changes in serum IDE levels correlate with the severity of MS. Using a highly sensitive ELISA assay of active IDE in human serum, we found a strong correlation between circulating IDE levels and circulating levels of triglycerides, insulin, and c-peptide and an inverse correlation with HDL cholesterol (HDLc). Serum IDE levels were higher in MS subjects than in control subjects. Hence, circulating IDE may serve as a tool to identify subjects with abnormal insulin metabolism, possibly those with MS that are at risk to develop diabetes.

Protein folding stability and binding interactions through the lens of evolution: a dynamical perspective

While the function of a protein depends heavily on its ability to fold into a correct 3D structure, billions of years of evolution have tailored proteins from highly stable objects to flexible molecules as they adapted to environmental changes. Nature maintains the fine balance of protein folding and stability while still evolving towards new function through generations of fine-tuning necessary interactions with other proteins and small molecules. Here we focus on recent computational and experimental studies that shed light onto how evolution molds protein folding and the functional landscape from a conformational dynamics' perspective. Particularly, we explore the importance of dynamic allostery throughout protein evolution and discuss how the protein anisotropic network can give rise to allosteric and epistatic interactions.

AlloSigMA 2: paving the way to designing allosteric effectors and to exploring allosteric effects of mutations

The AlloSigMA 2 server provides an interactive platform for exploring the allosteric signaling caused by ligand binding and/or mutations, for analyzing the allosteric effects of mutations and for detecting potential cancer drivers and pathogenic nsSNPs. It can also be used for searching latent allosteric sites and for computationally designing allosteric effectors for these sites with required agonist/antagonist activity. The server is based on the implementation of the Structure-Based Statistical Mechanical Model of Allostery (SBSMMA), which allows one to evaluate the allosteric free energy as a result of the perturbation at per-residue resolution. The Allosteric Signaling Map (ASM) providing a comprehensive residue-by-residue allosteric control over the protein activity can be obtained for any structure of interest. The Allosteric Probing Map (APM), in turn, allows one to perform the fragment-based-like computational design experiment aimed at finding leads for potential allosteric effectors. The server can be instrumental in elucidating of allosteric mechanisms and actions of allosteric mutations, and in the efforts on design of new elements of allosteric control. The server is freely available at: http://allosigma.bii.a-star.edu.sg.

THE USE OF MASS SPECTROMETRY TO STUDY ZN-METALLOPROTEASE-SUBSTRATE INTERACTIONS

Zinc metalloproteases (ZnMPs) participate in diverse biological reactions, encompassing the synthesis and degradation of all the major metabolites in living organisms. In particular, ZnMPs have been recognized to play a very important role in controlling the concentration level of several peptides and/or proteins whose homeostasis has to be finely regulated for the correct physiology of cells. Dyshomeostasis of aggregation-prone proteins causes pathological conditions and the development of several different diseases. For this reason, in recent years, many analytical approaches have been applied for studying the interaction between ZnMPs and their substrates and how environmental factors can affect enzyme activities. In this scenario, mass spectrometric methods occupy a very important role in elucidating different aspects of ZnMPs-substrates interaction. These range from identification of cleavage sites to quantitation of kinetic parameters. In this work, an overview of all the main achievements regarding the application of mass spectrometric methods to investigating ZnMPs-substrates interactions is presented. A general experimental protocol is also described which may prove useful to the study of similar interactions. © 2020 John Wiley & Sons Ltd. Mass Spec Rev.

Attenuation of subcutaneous insulin induced amyloid mass in vivo using Lumbrokinase and Serratiopeptidase

The protein misfolded structure called amyloids is related with extensive range of pathologies like local amyloidosis and neurodegenerative diseases. Several studies have reported the potential of insulin to generate local amyloidosis under certain state. Reports also showed that fibrils of insulin generated local amyloid mass due to continuous subcutaneous injection in mouse as well as rat. The present study was designed to examine the consequence of insulin fibril injections in rats, as well as the ability of enzymes, Lumbrokinase (LK) and Serratiopeptidase (SP) in diminishing this amyloid mass progression. The results showed that insulin fibrils generated amyloid masses in rats after subcutaneous injection for two weeks which was significantly condensed in size for the groups injected with insulin fibrils combined with LK or SP. At higher doses of LK and SP, the absence of amyloid structure was observed in histopathological studies. Light microscopy, polarized microscopy as well as Lumia live in vivo imaging system was used to analyze the results. In conclusion, the overall outcome of this study showed the anti-amyloid potential of enzyme LK and SP in the attenuation of local amyloidosis.

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.

Integrated Computational Approaches and Tools forAllosteric Drug Discovery

Understanding molecular mechanisms underlying the complexity of allosteric regulationin proteins has attracted considerable attention in drug discovery due to the benefits and versatilityof allosteric modulators in providing desirable selectivity against protein targets while minimizingtoxicity and other side effects. The proliferation of novel computational approaches for predictingligand-protein interactions and binding using dynamic and network-centric perspectives has ledto new insights into allosteric mechanisms and facilitated computer-based discovery of allostericdrugs. Although no absolute method of experimental and in silico allosteric drug/site discoveryexists, current methods are still being improved. As such, the critical analysis and integration ofestablished approaches into robust, reproducible, and customizable computational pipelines withexperimental feedback could make allosteric drug discovery more efficient and reliable. In this article,we review computational approaches for allosteric drug discovery and discuss how these tools can beutilized to develop consensus workflows for in silico identification of allosteric sites and modulatorswith some applications to pathogen resistance and precision medicine. The emerging realization thatallosteric modulators can exploit distinct regulatory mechanisms and can provide access to targetedmodulation of protein activities could open opportunities for probing biological processes and insilico design of drug combinations with improved therapeutic indices and a broad range of activities.

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.

DPP-4 inhibitor improves learning and memory deficits and AD-like neurodegeneration by modulating the GLP-1 signaling

Glucagon-like peptide-1 (GLP-1) signaling in the brain plays an important role in the regulation of glucose metabolism, which is impaired in Alzheimer's disease (AD). Here, we detected the GLP-1 and GLP-1 receptor (GLP-1R) in AD human brain and APP/PS1/Tau transgenic (3xTg) mice brain, finding that they were both decreased in AD human and mice brain. Enhanced GLP-1 exerts its protective effects on AD, however, this is rapidly degraded into inactivated metabolites by dipeptidyl peptidase-4 (DPP-4), resulting in its extremely short half-time. DPP-4 inhibitors, thus, was applied to improve the level of GLP-1 and GLP-1R expression in the hippocampus and cortex of AD mice brains. It is also protected learning and memory and synaptic proteins, increased the O-Glycosylation and decreased abnormal phosphorylation of tau and neurofilaments (NFs), degraded intercellular β-amyloid (Aβ) accumulation and alleviated neurodegeneration related to GLP-1 signaling pathway.

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.

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.

Allosteric Methods and Their Applications: Facilitating the Discovery of Allosteric Drugs and the Investigation of Allosteric Mechanisms

Allostery, or allosteric regulation, is the phenomenon in which protein functional activity is altered by the binding of an effector at an allosteric site that is topographically distinct from the orthosteric, active site. As one of the most direct and efficient ways to regulate protein function, allostery has played a fundamental role in innumerable biological processes of all living organisms, including enzyme catalysis, signal transduction, cell metabolism, and gene transcription. It is thus considered as "the second secret of life". The abnormality of allosteric communication networks between allosteric and orthosteric sites is associated with the pathogenesis of human diseases. Allosteric modulators, by attaching to structurally diverse allosteric sites, offer the potential for differential selectivity and improved safety compared with orthosteric drugs that bind to conserved orthosteric sites. Harnessing allostery has thus been regarded as a novel strategy for drug discovery. Despite much progress having been made in the repertoire of allostery since the turn of the millennium, the identification of allosteric drugs for therapeutic targets and the elucidation of allosteric mechanisms still present substantial challenges. These challenges are derived from the difficulties in the identification of allosteric sites and mutations, the assessment of allosteric protein-modulator interactions, the screening of allosteric modulators, and the elucidation of allosteric mechanisms in biological systems. To address these issues, we have developed a panel of allosteric services for specific allosteric applications over the past decade, including (i) the creation of the Allosteric Database, with the aim of providing comprehensive allosteric information such as allosteric proteins, modulators, sites, pathways, etc., (ii) the construction of the ASBench benchmark of high-quality allosteric sites for the development of computational methods for predicting allosteric sites, (iii) the development of Allosite and AllositePro for the prediction of the location of allosteric sites in proteins, (iv) the development of the Alloscore scoring function for the evaluation of allosteric protein-modulator interactions, (v) the development of Allosterome for evolutionary analysis of query allosteric sites/modulators within the human proteome, (vi) the development of AlloDriver for the prediction of allosteric mutagenesis, and (vii) the development of AlloFinder for the virtual screening of allosteric modulators and the investigation of allosteric mechanisms. Importantly, we have validated computationally predicted allosteric sites, mutations, and modulators in the real cases of sirtuin 6, casein kinase 2α, phosphodiesterase 10A, and signal transduction and activation of transcription 3. Furthermore, our developed allosteric methods have been widely exploited by other users around the world for allosteric research. Therefore, these allosteric services are expected to expedite the discovery of allosteric drugs and the investigation of allosteric mechanisms.

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.

Resveratrol Sustains Insulin-Degrading Enzyme Activity toward Aβ42

Alzheimer's disease (AD), the most common cause of dementia in the elderly, is the sixth leading cause of death in the United States. We hypothesize that the impaired clearance of Aβ42 from the brain is partly responsible for the onset of sporadic AD. In this work, we evaluated the activity of insulin-degrading enzyme (IDE) toward Aβ42 in the presence of resveratrol, a polyphenol found in red wine and grape juice. By liquid chromatography/mass spectrometry, we identified initial cleavage sites in the absence and presence of resveratrol that carry biological relevance connected to the amyloidogenic properties of Aβ42. Incubation with resveratrol results in a substantial increase in Aβ42 fragmentation compared to the control, signifying that the polyphenol sustains IDE-dependent degradation of Aβ42 and its fragments. Our findings suggest that therapeutic and/or preventative approaches combining resveratrol and IDE may hold promise for sporadic AD.

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.

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.