Toward Comprehensive Allosteric Control over Protein Activity

Reviewing the Structure-Function Paradigm in Polyglutamine Disorders: A Synergistic Perspective on Theoretical and Experimental Approaches

Polyglutamine (polyQ) disorders are a group of neurodegenerative diseases characterized by the excessive expansion of CAG (cytosine, adenine, guanine) repeats within host proteins. The quest to unravel the complex diseases mechanism has led researchers to adopt both theoretical and experimental methods, each offering unique insights into the underlying pathogenesis. This review emphasizes the significance of combining multiple approaches in the study of polyQ disorders, focusing on the structure-function correlations and the relevance of polyQ-related protein dynamics in neurodegeneration. By integrating computational/theoretical predictions with experimental observations, one can establish robust structure-function correlations, aiding in the identification of key molecular targets for therapeutic interventions. PolyQ proteins' dynamics, influenced by their length and interactions with other molecular partners, play a pivotal role in the polyQ-related pathogenic cascade. Moreover, conformational dynamics of polyQ proteins can trigger aggregation, leading to toxic assembles that hinder proper cellular homeostasis. Understanding these intricacies offers new avenues for therapeutic strategies by fine-tuning polyQ kinetics, in order to prevent and control disease progression. Last but not least, this review highlights the importance of integrating multidisciplinary efforts to advancing research in this field, bringing us closer to the ultimate goal of finding effective treatments against polyQ disorders.

ASM variants in the spotlight: A structure-based atlas for unraveling pathogenic mechanisms in lysosomal acid sphingomyelinase

Lysosomal acid sphingomyelinase (ASM), a critical enzyme in lipid metabolism encoded by the SMPD1 gene, plays a crucial role in sphingomyelin hydrolysis in lysosomes. ASM deficiency leads to acid sphingomyelinase deficiency, a rare genetic disorder with diverse clinical manifestations, and the protein can be found mutated in other diseases. We employed a structure-based framework to comprehensively understand the functional implications of ASM variants, integrating pathogenicity predictions with molecular insights derived from a molecular dynamics simulation in a lysosomal membrane environment. Our analysis, encompassing over 400 variants, establishes a structural atlas of missense variants of lysosomal ASM, associating mechanistic indicators with pathogenic potential. Our study highlights variants that influence structural stability or exert local and long-range effects at functional sites. To validate our predictions, we compared them to available experimental data on residual catalytic activity in 135 ASM variants. Notably, our findings also suggest applications of the resulting data for identifying cases suited for enzyme replacement therapy. This comprehensive approach enhances the understanding of ASM variants and provides valuable insights for potential therapeutic interventions.

Back in time to the Gly-rich prototype of the phosphate binding elementary function

Binding of nucleotides and their derivatives is one of the most ancient elementary functions dating back to the Origin of Life. We review here the works considering one of the key elements in binding of (di)nucleotide-containing ligands - phosphate binding. We start from a brief discussion of major participants, conditions, and events in prebiotic evolution that resulted in the Origin of Life. Tracing back to the basic functions, including metal and phosphate binding, and, potentially, formation of primitive protein-protein interactions, we focus here on the phosphate binding. Critically assessing works on the structural, functional, and evolutionary aspects of phosphate binding, we perform a simple computational experiment reconstructing its most ancient and generic sequence prototype. The profiles of the phosphate binding signatures have been derived in form of position-specific scoring matrices (PSSMs), their peculiarities depending on the type of the ligands have been analyzed, and evolutionary connections between them have been delineated. Then, the apparent prototype that gave rise to all relevant phosphate-binding signatures had also been reconstructed. We show that two major signatures of the phosphate binding that discriminate between the binding of dinucleotide- and nucleotide-containing ligands are GxGxxG and GxxGxG, respectively. It appears that the signature archetypal for dinucleotide-containing ligands is more generic, and it can frequently bind phosphate groups in nucleotide-containing ligands as well. The reconstructed prototype's key signature GxGGxG underlies the role of glycine residues in providing flexibility and interactions necessary for binding the phosphate groups. The prototype also contains other ancient amino acids, valine, and alanine, showing versatility towards evolutionary design and functional diversification.

Living in trinity of extremes: Genomic and proteomic signatures of halophilic, thermophilic, and pH adaptation

Since nucleic acids and proteins of unicellular prokaryotes are directly exposed to extreme environmental conditions, it is possible to explore the genomic-proteomic compositional determinants of molecular mechanisms of adaptation developed by them in response to harsh environmental conditions. Using a wealth of currently available complete genomes/proteomes we were able to explore signatures of adaptation to three environmental factors, pH, salinity, and temperature, observing major trends in compositions of their nucleic acids and proteins. We derived predictors of thermostability, halophilic, and pH adaptations and complemented them by the principal components analysis. We observed a clear difference between thermophilic and salinity/pH adaptations, whereas latter invoke seemingly overlapping mechanisms. The genome-proteome compositional trade-off reveals an intricate balance between the work of base paring and base stacking in stabilization of coding DNA and r/tRNAs, and, at the same time, universal requirements for the stability and foldability of proteins regardless of the nucleotide biases. Nevertheless, we still found hidden fingerprints of ancient evolutionary connections between the nucleotide and amino acid compositions indicating their emergence, mutual evolution, and adjustment. The evolutionary perspective on the adaptation mechanisms is further studied here by means of the comparative analysis of genomic/proteomic traits of archaeal and bacterial species. The overall picture of genomic/proteomic signals of adaptation obtained here provides a foundation for future engineering and design of functional biomolecules resistant to harsh environments.

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.

Modulation of Allostery with Multiple Mechanisms by Hotspot Mutations in TetR

Modulating allosteric coupling offers unique opportunities for biomedical applications. Such efforts can benefit from efficient prediction and evaluation of allostery hotspot residues that dictate the degree of cooperativity between distant sites. We demonstrate that effects of allostery hotspot mutations can be evaluated qualitatively and semiquantitatively by molecular dynamics simulations in a bacterial tetracycline repressor (TetR). The simulations recapitulate the effects of these mutations on abolishing the induction function of TetR and provide a rationale for the different rescuabilities observed to restore allosteric coupling of the hotspot mutations. We demonstrate that the same noninducible phenotype could be the result of perturbations in distinct structural and energetic properties of TetR. Our work underscores the value of explicitly computing the functional free energy landscapes to effectively evaluate and rank hotspot mutations despite the prevalence of compensatory interactions and therefore provides quantitative guidance to allostery modulation for therapeutic and engineering applications.

Modulation of Allostery with Multiple Mechanisms by Hotspot Mutations in TetR

Modulating allosteric coupling offers unique opportunities for biomedical applications. Such efforts can benefit from efficient prediction and evaluation of allostery hotspot residues that dictate the degree of co-operativity between distant sites. We demonstrate that effects of allostery hotspot mutations can be evaluated qualitatively and semi-quantitatively by molecular dynamics simulations in a bacterial tetracycline repressor (TetR). The simulations recapitulate the effects of these mutations on abolishing the induction function of TetR and provide a rationale for the different degrees of rescuability observed to restore allosteric coupling of the hotspot mutations. We demonstrate that the same non-inducible phenotype could be the result of perturbations in distinct structural and energetic properties of TetR. Our work underscore the value of explicitly computing the functional free energy landscapes to effectively evaluate and rank hotspot mutations despite the prevalence of compensatory interactions, and therefore provide quantitative guidance to allostery modulation for therapeutic and engineering applications.

Exploration of Computational Aids for Effective Drug Designing and Management of Viral Diseases: A Comprehensive Review

BACKGROUND

Microbial diseases, specifically originating from viruses are the major cause of human mortality all over the world. The current COVID-19 pandemic is a case in point, where the dynamics of the viral-human interactions are still not completely understood, making its treatment a case of trial and error. Scientists are struggling to devise a strategy to contain the pandemic for over a year and this brings to light the lack of understanding of how the virus grows and multiplies in the human body.

METHODS

This paper presents the perspective of the authors on the applicability of computational tools for deep learning and understanding of host-microbe interaction, disease progression and management, drug resistance and immune modulation through in silico methodologies which can aid in effective and selective drug development. The paper has summarized advances in the last five years. The studies published and indexed in leading databases have been included in the review.

RESULTS

Computational systems biology works on an interface of biology and mathematics and intends to unravel the complex mechanisms between the biological systems and the inter and intra species dynamics using computational tools, and high-throughput technologies developed on algorithms, networks and complex connections to simulate cellular biological processes.

CONCLUSION

Computational strategies and modelling integrate and prioritize microbial-host interactions and may predict the conditions in which the fine-tuning attenuates. These microbial-host interactions and working mechanisms are important from the aspect of effective drug designing and fine- tuning the therapeutic interventions.

AlloMAPS 2: allosteric fingerprints of the AlphaFold and Pfam-trRosetta predicted structures for engineering and design

AlloMAPS 2 is an update of the Allosteric Mutation Analysis and Polymorphism of Signalling database, which contains data on allosteric communication obtained for predicted structures in the AlphaFold database (AFDB) and trRosetta-predicted Pfam domains. The data update contains Allosteric Signalling Maps (ASMs) and Allosteric Probing Maps (APMs) quantifying allosteric effects of mutations and of small probe binding, respectively. To ensure quality of the ASMs and APMs, we performed careful and accurate selection of protein sets containing high-quality predicted structures in both databases for each organism/structure, and the data is available for browsing and download. The data for remaining structures are available for download and should be used at user's discretion and responsibility. We believe these massive data can facilitate both diagnostics and drug design within the precision medicine paradigm. Specifically, it can be instrumental in the analysis of allosteric effects of pathological and rescue mutations, providing starting points for fragment-based design of allosteric effectors. The exhaustive character of allosteric signalling and probing fingerprints will be also useful in future developments of corresponding machine learning applications. The database is freely available at: http://allomaps.bii.a-star.edu.sg.

Allosteric regulation of substrate channeling: Salmonella typhimurium tryptophan synthase

The regulation of the synthesis of L-tryptophan (L-Trp) in enteric bacteria begins at the level of gene expression where the cellular concentration of L-Trp tightly controls expression of the five enzymes of the Trp operon responsible for the synthesis of L-Trp. Two of these enzymes, trpA and trpB, form an αββα bienzyme complex, designated as tryptophan synthase (TS). TS carries out the last two enzymatic processes comprising the synthesis of L-Trp. The TS α-subunits catalyze the cleavage of 3-indole D-glyceraldehyde 3′-phosphate to indole and D-glyceraldehyde 3-phosphate; the pyridoxal phosphate-requiring β-subunits catalyze a nine-step reaction sequence to replace the L-Ser hydroxyl by indole giving L-Trp and a water molecule. Within αβ dimeric units of the αββα bienzyme complex, the common intermediate indole is channeled from the α site to the β site via an interconnecting 25 Å-long tunnel. The TS system provides an unusual example of allosteric control wherein the structures of the nine different covalent intermediates along the β-reaction catalytic path and substrate binding to the α-site provide the allosteric triggers for switching the αββα system between the open (T) and closed (R) allosteric states. This triggering provides a linkage that couples the allosteric conformational coordinate to the covalent chemical reaction coordinates at the α- and β-sites. This coupling drives the α- and β-sites between T and R conformations to achieve regulation of substrate binding and/or product release, modulation of the α- and β-site catalytic activities, prevention of indole escape from the confines of the active sites and the interconnecting tunnel, and synchronization of the α- and β-site catalytic activities. Here we review recent advances in the understanding of the relationships between structure, function, and allosteric regulation of the complex found in Salmonella typhimurium.

Mechanistic Understanding of the Palmitoylation of Go Protein in the Allosteric Regulation of Adhesion Receptor GPR97

Adhesion G-protein-coupled receptors (aGPCRs)—a major family of GPCRs—play critical roles in the regulation of tissue development and cancer progression. The orphan receptor GPR97, activated by glucocorticoid stress hormones, is a prototypical aGPCR. Although it has been established that the palmitoylation of the C-terminal G_o protein is essential for G_o’s efficient engagement with the active GPR97, the detailed allosteric mechanism remains to be clarified. Hence, we performed extensive large-scale molecular dynamics (MD) simulations of the GPR97−G_o complex in the presence or absence of G_o palmitoylation. The conformational landscapes analyzed by Markov state models revealed that the overall conformation of GPR97 is preferred to be fully active when interacting with palmitoylated G_o protein. Structural and energetic analyses indicated that the palmitoylation of G_o can allosterically stabilize the critical residues in the ligand-binding pocket of GPR97 and increase the affinity of the ligand for GPR97. Furthermore, the community network analysis suggests that the palmitoylation of G_o not only allosterically strengthens the internal interactions between G_αo and G_βγ, but also enhances the coupling between G_o and GPR97. Our study provides mechanistic insights into the regulation of aGPCRs via post-translational modifications of the G_o protein, and offers guidance for future drug design of aGPCRs.

Prediction of Allosteric Communication Pathways in Proteins

MOTIVATION

Allostery in proteins is an essential phenomenon in biological processes. In this paper, we present a computational model to predict paths of maximum information transfer between active and allosteric sites. In this information theoretic study, we use mutual information as the measure of information transfer, where transition probability of information from one residue to its contacting neighbors is proportional to the magnitude of mutual information between the two residues. Starting from a given residue and using a Hidden Markov Model, we successively determine the neighboring residues that eventually lead to a path of optimum information transfer. The Gaussian approximation of mutual information between residue pairs is adopted. The limits of validity of this approximation are discussed in terms of a nonlinear theory of mutual information and its reduction to the Gaussian form.

RESULTS

Predictions of the model are tested on six widely studied cases, CheY Bacterial Chemotaxis, B-cell Lymphoma extra-large Bcl-xL, Human proline isomerase cyclophilin A (CypA), Dihydrofolate reductase DHFR, HRas GTPase, and Caspase-1. The communication transmission rendering the propagation of local fluctuations from the active sites throughout the structure in multiple paths correlate well with the known experimental data. Distinct paths originating from the active site may likely represent a multi functionality such as involving more than one allosteric site and/or preexistence of some other functional states. Our model is computationally fast and simple, and can give allosteric communication pathways, which are crucial for the understanding and control of protein functionality.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

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.

MutateX: an automated pipeline for in silico saturation mutagenesis of protein structures and structural ensembles

Mutations, which result in amino acid substitutions, influence the stability of proteins and their binding to biomolecules. A molecular understanding of the effects of protein mutations is both of biotechnological and medical relevance. Empirical free energy functions that quickly estimate the free energy change upon mutation (ΔΔG) can be exploited for systematic screenings of proteins and protein complexes. In silico saturation mutagenesis can guide the design of new experiments or rationalize the consequences of known mutations. Often software such as FoldX, while fast and reliable, lack the necessary automation features to apply them in a high-throughput manner. We introduce MutateX, a software to automate the prediction of ΔΔGs associated with the systematic mutation of each residue within a protein, or protein complex to all other possible residue types, using the FoldX energy function. MutateX also supports ΔΔG calculations over protein ensembles, upon post-translational modifications and in multimeric assemblies. At the heart of MutateX lies an automated pipeline engine that handles input preparation, parallelization and outputs publication-ready figures. We illustrate the MutateX protocol applied to different case studies. The results of the high-throughput scan provided by our tools can help in different applications, such as the analysis of disease-associated mutations, to complement experimental deep mutational scans, or assist the design of variants for industrial applications. MutateX is a collection of Python tools that relies on open-source libraries. It is available free of charge under the GNU General Public License from https://github.com/ELELAB/mutatex.

Human variation in the protein receptor ACE2 affects its binding affinity to SARS-CoV-2 in a variant-dependent manner

SARS-CoV-2 infection depend on the binding of the viral Spike glycoprotein (S) to the human receptor Angiotensin Converting Enzyme 2 (ACE2) to induce virus-cell membrane fusion. S protein evolved diverse amino acid changes that are possibly linked to more efficient binding to human ACE2, which might explain part of the increase in frequency of SARS-CoV-2 Variants Of Concern (VOCs). In this work, we investigated the role of ACE2 protein variations that are naturally found in human populations and its binding affinity with S protein from SARS-CoV-2 representative genotypes, based on a series of in silico approaches involving molecular modelling, docking and molecular dynamics simulations. Our results indicate that SARS-CoV-2 VOCs bind more efficiently to the human receptor ACE2 than the ancestral Wuhan genotype. Additionally, variations in the ACE2 protein can affect SARS-CoV-2 binding and protein-protein stability, mostly making the interaction weaker and unstable in some cases. We show that some VOCs, such as B.1.1.7 and P.1 are much less sensitive to ACE2 variants, while others like B.1.351 appear to be specifically optimized to bind to the widespread wild-type ACE2 protein.Communicated by Ramaswamy H. Sarma.

Prediction of allosteric sites and signaling: Insights from benchmarking datasets

Allostery is a pervasive mechanism that regulates protein activity through ligand binding at a site different from the orthosteric site. The universality of allosteric regulation complemented by the benefits of highly specific and potentially non-toxic allosteric drugs makes uncovering allosteric sites invaluable. However, there are few computational methods to effectively predict them. Bond-to-bond propensity analysis has successfully predicted allosteric sites in 19 of 20 cases using an energy-weighted atomistic graph. We here extended the analysis onto 432 structures of 146 proteins from two benchmarking datasets for allosteric proteins: ASBench and CASBench. We further introduced two statistical measures to account for the cumulative effect of high-propensity residues and the crucial residues in a given site. The allosteric site is recovered for 127 of 146 proteins (407 of 432 structures) knowing only the orthosteric sites or ligands. The quantitative analysis using a range of statistical measures enables better characterization of potential allosteric sites and mechanisms involved.

Allosteric perspective on the mutability and druggability of the SARS-CoV-2 Spike protein

Recent developments in the SARS-CoV-2 pandemic point to its inevitable transformation into an endemic disease, urging both refinement of diagnostics for emerging variants of concern (VOCs) and design of variant-specific drugs in addition to vaccine adjustments. Exploring the structure and dynamics of the SARS-CoV-2 Spike protein, we argue that the high-mutability characteristic of RNA viruses coupled with the remarkable flexibility and dynamics of viral proteins result in a substantial involvement of allosteric mechanisms. While allosteric effects of mutations should be considered in predictions and diagnostics of new VOCs, allosteric drugs advantageously avoid escape mutations via non-competitive inhibition originating from alternative distal locations. The exhaustive allosteric signaling and probing maps presented herein provide a comprehensive picture of allostery in the spike protein, making it possible to locate potential mutations that could work as new VOC “drivers” and to determine binding patches that may be targeted by newly developed allosteric drugs.

Harnessing Reversed Allosteric Communication: A Novel Strategy for Allosteric Drug Discovery

Allostery is a fundamental and extensive mechanism of intramolecular signal transmission. Allosteric drugs possess several unique pharmacological advantages over traditional orthosteric drugs, including greater selectivity, better physicochemical properties, and lower off-target toxicity. However, owing to the complexity of allosteric regulation, experimental approaches for the development of allosteric modulators are traditionally serendipitous. Recently, the reversed allosteric communication theory has been proposed, providing a feasible tool for the unbiased detection of allosteric sites. Herein, we review the latest research on the reversed allosteric communication effect using the examples of sirtuin 6, epidermal growth factor receptor, 3-phosphoinositide-dependent protein kinase 1, and Related to A and C kinases (RAC) serine/threonine protein kinase B and recapitulate the methodologies of reversed allosteric communication strategy. The novel reversed allosteric communication strategy greatly expands the horizon of allosteric site identification and allosteric mechanism exploration and is expected to accelerate an end-to-end framework for drug discovery.

Hidden allosteric sites and De-Novo drug design

INTRODUCTION

Hidden allosteric sites are not visible in apo-crystal structures, but they may be visible in holo-structures when a certain ligand binds and maintains the ligand intended conformation. Several computational and experimental techniques have been used to investigate these hidden sites but identifying them remains a challenge.

AREAS COVERED

This review provides a summary of the many theoretical approaches for predicting hidden allosteric sites in disease-related proteins. Furthermore, promising cases have been thoroughly examined to reveal the hidden allosteric site and its modulator.

EXPERT OPINION

In the recent past, with the development in scientific techniques and bioinformatics tools, the number of drug targets for complex human diseases has significantly increased but unfortunately most of these targets are undruggable due to several reasons. Alternative strategies such as finding cryptic (hidden) allosteric sites are an attractive approach for exploitation of the discovery of new targets. These hidden sites are difficult to recognize compared to allosteric sites, mainly due to a lack of visibility in the crystal structure. In our opinion, after many years of development, MD simulations are finally becoming successful for obtaining a detailed molecular description of drug-target interaction.

Recent advances in externally controlled ring-opening polymerisations

Switchable catalysis is a powerful tool in the polymer chemist's toolbox as it allows on demand access to a variety of polymer architectures. Switchable catalysts operate by the generation of a species which is chemically distinct in behaviour and structure to the precursor. This difference in catalytic activity has been exploited to allow spatiotemporal control over polymerisations in the synthesis of (co)polymers. Although switchable methodologies have been applied to other polymerisation mechanisms for quite some time, for ring opening polymerisation (ROP) reactions it is a relatively young area of research. Despite its infancy, the field is accelerating rapidly. Here, we review recent developments for selected external stimuli for ROP, including redox chemistry, light, allosteric and mechanical control. Furthermore, a brief review on switch catalysis involving exogeneous gases will also be provided, although this area differs from traditional switchable catalysis techniques. An outlook on the future of switchable catalysis is also provided.

Potential allosteric sites captured in glycolytic enzymes via residue-based network models: Phosphofructokinase, glyceraldehyde-3-phosphate dehydrogenase and pyruvate kinase

Likelihood of new allosteric sites for glycolytic enzymes, phosphofructokinase (PFK), glyceraldehyde-3-phosphate dehydrogenase (GADPH) and pyruvate kinase (PK) was evaluated for bacterial, parasitic and human species. Allosteric effect of a ligand binding at a site was revealed on the basis of low-frequency normal modes via C_α-harmonic residue network model. In bacterial PFK, perturbation of the proposed allosteric site outperformed the known allosteric one, producing a high amount of stabilization or reduced dynamics, on all catalytic regions. Another proposed allosteric spot at the dimer interface in parasitic PFK exhibited major stabilization effect on catalytic regions. In parasitic GADPH, the most desired allosteric response was observed upon perturbation of its tunnel region which incorporated key residues for functional regulation. Proposed allosteric site in bacterial PK produced a satisfactory allosteric response on all catalytic regions, whereas in human and parasitic PKs, a partial inhibition was observed. Residue network model based solely on contact topology identified the 'hub residues' with high betweenness tracing plausible allosteric communication pathways between distant functional sites. For both bacterial PFK and PK, proposed sites accommodated hub residues twice as much as the known allosteric site. Tunnel region in parasitic GADPH with the strongest allosteric effect among species, incorporated the highest number of hub residues. These results clearly suggest a one-to-one correspondence between the degree of allosteric effect and the number of hub residues in that perturbation site, which increases the likelihood of its allosteric nature.

Assessment of the Contribution of a Thermodynamic and Mechanical Destabilization of Myosin-Binding Protein C Domain C2 to the Pathomechanism of Hypertrophic Cardiomyopathy-Causing Double Mutation MYBPC3Δ25bp/D389V

Mutations in the gene encoding cardiac myosin-binding protein-C (MyBPC), a thick filament assembly protein that stabilizes sarcomeric structure and regulates cardiac function, are a common cause for the development of hypertrophic cardiomyopathy. About 10% of carriers of the Δ25bp variant of MYBPC3, which is common in individuals from South Asia, are also carriers of the D389V variant on the same allele. Compared with noncarriers and those with MYBPC3^Δ25bp alone, indicators for the development of hypertrophic cardiomyopathy occur with increased frequency in MYBPC3^Δ25bp/D389V carriers. Residue D389 lies in the IgI-like C2 domain that is part of the N-terminal region of MyBPC. To probe the effects of mutation D389V on structure, thermostability, and protein–protein interactions, we produced and characterized wild-type and mutant constructs corresponding to the isolated 10 kDa C2 domain and a 52 kDa N-terminal fragment that includes subdomains C0 to C2. Our results show marked reductions in the melting temperatures of D389V mutant constructs. Interactions of construct C0–C2 D389V with the cardiac isoforms of myosin-2 and actin remain unchanged. Molecular dynamics simulations reveal changes in the stiffness and conformer dynamics of domain C2 caused by mutation D389V. Our results suggest a pathomechanism for the development of HCM based on the toxic buildup of misfolded protein in young MYBPC3^Δ25bp/D389V carriers that is supplanted and enhanced by C-zone haploinsufficiency at older ages.

Mechanism of activation and the rewired network: New drug design concepts

Precision oncology benefits from effective early phase drug discovery decisions. Recently, drugging inactive protein conformations has shown impressive successes, raising the cardinal questions of which targets can profit and what are the principles of the active/inactive protein pharmacology. Cancer driver mutations have been established to mimic the protein activation mechanism. We suggest that the decision whether to target an inactive (or active) conformation should largely rest on the protein mechanism of activation. We next discuss the recent identification of double (multiple) same-allele driver mutations and their impact on cell proliferation and suggest that like single driver mutations, double drivers also mimic the mechanism of activation. We further suggest that the structural perturbations of double (multiple) in cis mutations may reveal new surfaces/pockets for drug design. Finally, we underscore the preeminent role of the cellular network which is deregulated in cancer. Our structure-based review and outlook updates the traditional Mechanism of Action, informs decisions, and calls attention to the intrinsic activation mechanism of the target protein and the rewired tumor-specific network, ushering innovative considerations in precision medicine.

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.

Global Dynamics Renders Protein Sites with High Functional Response

Deep mutational scanning enables examination of the effects of many mutations at each amino acid position in a query protein, readily disclosing positions that are particularly sensitive. Mutations in these positions alter protein function the most. Here, on the premise that dynamics underlie function, we explore to what extent the measured sensitivity to mutations could be linked to-perhaps be explained by-the structural dynamics of the protein. We employ a minimalist perturbation-response approach based on the Gaussian Network Model (GNM) on a data set of seven proteins with deep mutational scanning data. The analysis shows that the mutation-sensitive positions are often of capacity to modulate the global dynamics and to intermediate allosteric interactions in the structure. With that, upon strain perturbation, these positions decrease residue fluctuations the most, affecting function via entropy changes. This is particularly relevant for positions that are distant from binding sites or other functional regions of the protein and are sensitive to mutations, nevertheless. Our results indicate that mutations in these positions allosterically manipulate protein function.

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.

Computational Identification of a Putative Allosteric Binding Pocket in TMPRSS2

Camostat, nafamostat, and bromhexine are inhibitors of the transmembrane serine protease TMPRSS2. The inhibition of TMPRSS2 has been shown to prevent the viral infection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and other viruses. However, while camostat and nafamostat inhibit TMPRSS2 by forming a covalent adduct, the mode of action of bromhexine remains unclear. TMPRSS2 is autocatalytically activated from its inactive form, zymogen, through a proteolytic cleavage that promotes the binding of Ile256 to a putative allosteric pocket (A-pocket). Computer simulations, reported here, indicate that Ile256 binding induces a conformational change in the catalytic site, thus providing the atomistic rationale to the activation process of the enzyme. Furthermore, computational docking and molecular dynamics simulations indicate that bromhexine competes with the N-terminal Ile256 for the same binding site, making it a potential allosteric inhibitor. Taken together, these findings provide the atomistic basis for the development of more selective and potent TMPRSS2 inhibitors.

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.

Influence of Disease-Causing Mutations on Protein Structural Networks

The interactions between residues in a protein tertiary structure can be studied effectively using the approach of protein structure network (PSN). A PSN is a node-edge representation of the structure with nodes representing residues and interactions between residues represented by edges. In this study, we have employed weighted PSNs to understand the influence of disease-causing mutations on proteins of known 3D structures. We have used manually curated information on disease mutations from UniProtKB/Swiss-Prot and their corresponding protein structures of wildtype and disease variant from the protein data bank. The PSNs of the wildtype and disease-causing mutant are compared to analyse variation of global and local dissimilarity in the overall network and at specific sites. We study how a mutation at a given site can affect the structural network at a distant site which may be involved in the function of the protein. We have discussed specific examples of the disease cases where the protein structure undergoes limited structural divergence in their backbone but have large dissimilarity in their all atom networks and vice versa, wherein large conformational alterations are observed while retaining overall network. We analyse the effect of variation of network parameters that characterize alteration of function or stability.

Inhibition of Nonfunctional Ras

Intuitively, functional states should be targeted; not nonfunctional ones. So why could drugging the inactive K-Ras4BG12Cwork-but drugging the inactive kinase will likely not? The reason is the distinct oncogenic mechanisms. Kinase driver mutations work by stabilizing the active state and/or destabilizing the inactive state. Either way, oncogenic kinases are mostly in the active state. Ras driver mutations work by quelling its deactivation mechanisms, GTP hydrolysis, and nucleotide exchange. Covalent inhibitors that bind to the inactive GDP-bound K-Ras4BG12C conformation can thus work. By contrast, in kinases, allosteric inhibitors work by altering the active-site conformation to favor orthosteric drugs. From the translational standpoint this distinction is vital: it expedites effective pharmaceutical development and extends the drug classification based on the mechanism of action. Collectively, here we postulate that drug action relates to blocking the mechanism of activation, not to whether the protein is in the active or inactive state.

Analyzing In Silico the Relationship Between the Activation of the Edema Factor and Its Interaction With Calmodulin

Molecular dynamics (MD) simulations have been recorded on the complex between the edema factor (EF) of Bacilllus anthracis and calmodulin (CaM), starting from a structure with the orthosteric inhibitor adefovir bound in the EF catalytic site. The starting structure has been destabilized by alternately suppressing different co-factors, such as adefovir ligand or ions, revealing several long-distance correlations between the conformation of CaM, the geometry of the CaM/EF interface, the enzymatic site and the overall organization of the complex. An allosteric communication between CaM/EF interface and the EF catalytic site, highlighted by these correlations, was confirmed by several bioinformatics approaches from the literature. A network of hydrogen bonds and stacking interactions extending from the helix V of of CaM, and the residues of the switches A, B and C, and connecting to catalytic site residues, is a plausible candidate for the mediation of allosteric communication. The greatest variability in volume between the different MD conditions was also found for cavities present at the EF/CaM interface and in the EF catalytic site. The similarity between the predictions from literature and the volume variability might introduce the volume variability as new descriptor of allostery.

Allosteric inhibition explained through conformational ensembles sampling distinct "mixed" states

Allosteric modulation provides an effective avenue for selective and potent enzyme inhibition. Here, we summarize and critically discuss recent advances on the mechanisms of allosteric partial agonists for three representative signalling enzymes activated by cyclic nucleotides: the cAMP-dependent protein kinase (PKA), the cGMP-dependent protein kinase (PKG), and the exchange protein activated by cAMP (EPAC). The comparative analysis of partial agonism in PKA, PKG and EPAC reveals a common emerging theme, i.e. the sampling of distinct “mixed” conformational states, either within a single domain or between distinct domains. Here, we show how such “mixed” states play a crucial role in explaining the observed functional response, i.e. partial agonism and allosteric pluripotency, as well as in maximizing inhibition while minimizing potency losses. In addition, by combining Nuclear Magnetic Resonance (NMR), Molecular Dynamics (MD) simulations and Ensemble Allosteric Modeling (EAM), we also show how to map the free-energy landscape of conformational ensembles containing “mixed” states. By discussing selected case studies, we illustrate how MD simulations and EAM complement NMR to quantitatively relate protein dynamics to function. The resulting NMR- and MD-based EAMs are anticipated to inform not only the design of new generations of highly selective allosteric inhibitors, but also the choice of multidrug combinations.

Allosteric regulation of glutamate dehydrogenase deamination activity

Glutamate dehydrogenase (GDH) is a key enzyme interlinking carbon and nitrogen metabolism. Recent discoveries of the GDH specific role in breast cancer, hyperinsulinism/hyperammonemia (HI/HA) syndrome, and neurodegenerative diseases have reinvigorated interest on GDH regulation, which remains poorly understood despite extensive and long standing studies. Notwithstanding the growing evidence of the complexity of allosteric network behind GDH regulation, identifications of allosteric factors and associated mechanisms are paramount to deepen our understanding of the complex dynamics that regulate GDH enzymatic activity. Combining structural analyses of cryo-electron microscopy data with molecular dynamic simulations, here we show that the cofactor NADH is a key player in the GDH regulation process. Our structural analysis indicates that, binding to the regulatory sites in proximity of the antenna region, NADH acts as a positive allosteric modulator by enhancing both the affinity of the inhibitor GTP binding and inhibition of GDH catalytic activity. We further show that the binding of GTP to the NADH-bound GDH activates a triangular allosteric network, interlinking the inhibitor with regulatory and catalytic sites. This allostery produces a local conformational rearrangement that triggers an anticlockwise rotational motion of interlinked alpha-helices with specific tilted helical extension. This structural transition is a fundamental switch in the GDH enzymatic activity. It introduces a torsional stress, and the associated rotational shift in the Rossmann fold closes the catalytic cleft with consequent inhibition of the deamination process. In silico mutagenesis examinations further underpin the molecular basis of HI/HA dominant mutations and consequent over-activity of GDH through alteration of this allosteric communication network. These results shed new light on GDH regulation and may lay new foundation in the design of allosteric agents.

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.

Synergistic Allostery in Multiligand-Protein Interactions

Amide hydrogen-deuterium exchange mass spectrometry is powerful for describing combinatorial coupling effects of a cooperative ligand pair binding at noncontiguous sites: adenosine at the ATP-pocket and a docking peptide (PIFtide) at the PIF-pocket, on a model protein kinase PDK1. Binding of two ligands to PDK1 reveal multiple hotspots of synergistic allostery with cumulative effects greater than the sum of individual effects mediated by each ligand. We quantified this synergism and ranked these hotspots using a difference in deuteration-based approach, which showed that the strongest synergistic effects were observed at three of the critical catalytic loci of kinases: the αB-αC helices, and HRD-motif loop, and DFG-motif. Additionally, we observed weaker synergistic effects at a distal GHI-subdomain locus. Synergistic changes in deuterium exchange observed at a distal site but not at the intermediate sites of the large lobe of the kinase reveals allosteric propagation in proteins to operate through two modes. Direct electrostatic interactions between polar and charged amino acids that mediate targeted relay of allosteric signals, and diffused relay of allosteric signals through soft matter-like hydrophobic core amino acids. Furthermore, we provide evidence that the conserved β-3 strand lysine of protein kinases (Lys111 of PDK1) functions as an integrator node to coordinate allosteric coupling of the two ligand-binding sites. It maintains indirect interactions with the ATP-pocket and mediates a critical salt bridge with a glutamate (Glu130) of αC helix, which is conserved across all kinases. In summary, allosteric propagation in cooperative, dual-liganded enzyme targets is bidirectional and synergistic and offers a strategy for combinatorial drug development.

Disorder driven allosteric control of protein activity

Studies of protein allostery increasingly reveal an involvement of the back and forth order-disorder transitions in this mechanism of protein activity regulation. Here, we investigate the allosteric mechanisms mediated by structural disorder using the structure-based statistical mechanical model of allostery (SBSMMA) that we have previously developed. We show that SBSMMA accounts for the energetics and causality of allosteric communication underlying dimerization of the BirA biotin repressor, activation of the sortase A enzyme, and inhibition of the Rac1 GTPase. Using the SBSMMA, we also show that introducing structural order or disorder in various regions of esterases can originate tunable allosteric modulation of the catalytic triad. On the basis of obtained results, we propose that operating with the order-disorder continuum allows one to establish an allosteric control scale for achieving desired modulation of the protein activity.

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Back and forth order-disorder transitions can induce allosteric signaling.

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Allosteric signaling originated by order/disorder follow universal rules.

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Allosteric control scale facilitates engineering of the protein activity regulation.

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.

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.

Accurate Representation of Protein-Ligand Structural Diversity in the Protein Data Bank (PDB)

The number of available protein structures in the Protein Data Bank (PDB) has considerably increased in recent years. Thanks to the growth of structures and complexes, numerous large-scale studies have been done in various research areas, e.g., protein-protein, protein-DNA, or in drug discovery. While protein redundancy was only simply managed using simple protein sequence identity threshold, the similarity of protein-ligand complexes should also be considered from a structural perspective. Hence, the protein-ligand duplicates in the PDB are widely known, but were never quantitatively assessed, as they are quite complex to analyze and compare. Here, we present a specific clustering of protein-ligand structures to avoid bias found in different studies. The methodology is based on binding site superposition, and a combination of weighted Root Mean Square Deviation (RMSD) assessment and hierarchical clustering. Repeated structures of proteins of interest are highlighted and only representative conformations were conserved for a non-biased view of protein distribution. Three types of cases are described based on the number of distinct conformations identified for each complex. Defining these categories decreases by 3.84-fold the number of complexes, and offers more refined results compared to a protein sequence-based method. Widely distinct conformations were analyzed using normalized B-factors. Furthermore, a non-redundant dataset was generated for future molecular interactions analysis or virtual screening studies.

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.