Allostery in Its Many Disguises: From Theory to Applications

Targeting allosteric regulation of cancer metabolism

Metabolic reprogramming is observed across all cancer types. Indeed, the success of many classic chemotherapies stems from their targeting of cancer metabolism. Contemporary research in this area has refined our understanding of tumor-specific metabolic mechanisms and has revealed strategies for exploiting these vulnerabilities selectively. Based on this growing understanding, new small-molecule tools and drugs have been developed to study and target tumor metabolism. Here, we highlight allosteric modulation of metabolic enzymes as an attractive mechanism of action for small molecules that target metabolic enzymes. We then discuss the mechanistic insights garnered from their application in cancer studies and highlight the achievements of this approach in targeting cancer metabolism. Finally, we discuss technological advances in drug discovery for allosteric modulators of enzyme activity.

Generic model for biological regulation

A substantial portion of molecules in an organism are involved in regulation of a wide spectrum of biological processes. Several models have been presented for various forms of biological regulation, including gene expression regulation and physiological regulation; however, a generic model is missing. Recently a new unifying theory in biology, poikilosis, was presented.  Poikilosis indicates that all systems display intrinsic heterogeneity, which is a normal state. The concept of poikilosis allowed development of a model for biological regulation applicable to all types of regulated systems. The perturbation-lagom-TATAR countermeasures-regulator (PLTR) model combines the effects of perturbation and lagom (allowed and sufficient extent of heterogeneity) in a system with tolerance, avoidance, repair, attenuation and resistance (TARAR) countermeasures, and possible regulators. There are three modes of regulation, two of which are lagom-related. In the first scenario, lagom is maintained, both intrinsic (passive) and active TARAR countermeasures can be involved. In the second mode, there is a shift from one lagom to another. In the third mode, reguland regulation, the regulated entity is the target of a regulatory shift, which is often irreversible or requires action of another regulator to return to original state. After the shift, the system enters to lagom maintenance mode, but at new lagom extent. The model is described and elaborated with examples and applications, including medicine and systems biology. Consequences of non-lagom extent of heterogeneity are introduced, along with a novel idea for therapy by reconstituting biological processes to lagom extent, even when the primary effect cannot be treated.

Generic model for biological regulation

A substantial portion of molecules in an organism are involved in regulation of a wide spectrum of biological processes. Several models have been presented for various forms of biological regulation, including gene expression regulation and physiological regulation; however, a generic model is missing. Recently a new unifying theory in biology, poikilosis, was presented.  Poikilosis indicates that all systems display intrinsic heterogeneity. The concept of poikilosis allowed development of a model for biological regulation applicable to all types of regulated systems. The perturbation-lagom-TATAR countermeasures-regulator (PLTR) model combines the effects of perturbation and lagom (allowed and sufficient extent of heterogeneity) in a system with tolerance, avoidance, repair, attenuation and resistance (TARAR) countermeasures, and possible regulators. There are three modes of regulation, two of which are lagom-related. In the first scenario, lagom is maintained, both intrinsic (passive) and active TARAR countermeasures can be involved. In the second mode, there is a shift from one lagom to another. In the third mode, reguland regulation, the regulated entity is the target of a regulatory shift, which is often irreversible or requires action of another regulator to return to original state. After the shift, the system enters to lagom maintenance mode, but at new lagom extent. The model is described and elaborated with examples and applications, including medicine and systems biology. Consequences of non-lagom extent of heterogeneity are introduced, along with a novel idea for therapy by reconstituting biological processes to lagom extent, even when the primary effect cannot be treated.

Time Evolution of the Millisecond Allosteric Activation of Imidazole Glycerol Phosphate Synthase

Deciphering the molecular mechanisms of enzymatic allosteric regulation requires the structural characterization of functional states and also their time evolution toward the formation of the allosterically activated ternary complex. The transient nature and usually slow millisecond time scale interconversion between these functional states hamper their experimental and computational characterization. Here, we combine extensive molecular dynamics simulations, enhanced sampling techniques, and dynamical networks to describe the allosteric activation of imidazole glycerol phosphate synthase (IGPS) from the substrate-free form to the active ternary complex. IGPS is a heterodimeric bienzyme complex whose HisH subunit is responsible for hydrolyzing glutamine and delivering ammonia for the cyclase activity in HisF. Despite significant advances in understanding the underlying allosteric mechanism, essential molecular details of the long-range millisecond allosteric activation of IGPS remain hidden. Without using a priori information of the active state, our simulations uncover how IGPS, with the allosteric effector bound in HisF, spontaneously captures glutamine in a catalytically inactive HisH conformation, subsequently attains a closed HisF:HisH interface, and finally forms the oxyanion hole in HisH for efficient glutamine hydrolysis. We show that the combined effector and substrate binding dramatically decreases the conformational barrier associated with oxyanion hole formation, in line with the experimentally observed 4500-fold activity increase in glutamine hydrolysis. The allosteric activation is controlled by correlated time-evolving dynamic networks connecting the effector and substrate binding sites. This computational strategy tailored to describe millisecond events can be used to rationalize the effect of mutations on the allosteric regulation and guide IGPS engineering efforts.

Landscape-Based Protein Stability Analysis and Network Modeling of Multiple Conformational States of the SARS-CoV-2 Spike D614G Mutant: Conformational Plasticity and Frustration-Induced Allostery as Energetic Drivers of Highly Transmissible Spike Variants

The structural and functional studies of the SARS-CoV-2 spike protein variants revealed an important role of the D614G mutation that is shared across many variants of concern (VOCs), suggesting the effect of this mutation on the enhanced virus infectivity and transmissibility. The recent structural and biophysical studies provided important evidence about multiple conformational substates of the D614G spike protein. The development of a plausible mechanistic model that can explain the experimental observations from a more unified thermodynamic perspective is an important objective of the current work. In this study, we employed efficient and accurate coarse-grained simulations of multiple structural substates of the D614G spike trimers together with the ensemble-based mutational frustration analysis to characterize the dynamics signatures of the conformational landscapes. By combining the local frustration profiling of the conformational states with residue-based mutational scanning of protein stability and network analysis of allosteric interactions and communications, we determine the patterns of mutational sensitivity in the functional regions and sites of variants. We found that the D614G mutation may induce a considerable conformational adaptability of the open states in the SARS-CoV-2 spike protein without compromising the folding stability and integrity of the spike protein. The results suggest that the D614G mutant may employ a hinge-shift mechanism in which the dynamic couplings between the site of mutation and the interprotomer hinge modulate the interdomain interactions, global mobility change, and the increased stability of the open form. This study proposes that mutation-induced modulation of the conformational flexibility and energetic frustration at the interprotomer interfaces may serve as an efficient mechanism for allosteric regulation of the SARS-CoV-2 spike proteins.

Allostery, and how to define and measure signal transduction

Here we ask: What is productive signaling? How to define it, how to measure it, and most of all, what are the parameters that determine it? Further, what determines the strength of signaling from an upstream to a downstream node in a specific cell? These questions have either not been considered or not entirely resolved. The requirements for the signal to propagate downstream to activate (repress) transcription have not been considered either. Yet, the questions are pivotal to clarify, especially in diseases such as cancer where determination of signal propagation can point to cell proliferation and to emerging drug resistance, and to neurodevelopmental disorders, such as RASopathy, autism, attention-deficit/hyperactivity disorder (ADHD), and cerebral palsy. Here we propose a framework for signal transduction from an upstream to a downstream node addressing these questions. Defining cellular processes, experimentally measuring them, and devising powerful computational AI-powered algorithms that exploit the measurements, are essential for quantitative science.

The dynamic properties of a nuclear coactivator binding domain are evolutionarily conserved

Evolution of proteins is constrained by their structure and function. While there is a consensus that the plasticity of intrinsically disordered proteins relaxes the structural constraints on evolution there is a paucity of data on the molecular details of these processes. The Nuclear Coactivator Binding Domain (NCBD) from CREB-binding protein is a protein interaction domain, which contains a hydrophobic core but is not behaving as a typical globular domain, and has been described as 'molten-globule like'. The highly dynamic properties of NCBD makes it an interesting model system for evolutionary structure-function investigation of intrinsically disordered proteins. We have here compared the structure and biophysical properties of an ancient version of NCBD present in a bilaterian animal ancestor living around 600 million years ago with extant human NCBD. Using a combination of NMR spectroscopy, circular dichroism and kinetics we show that although NCBD has increased its thermodynamic stability, it has retained its dynamic biophysical properties in the ligand-free state in the evolutionary lineage leading from the last common bilaterian ancestor to humans. Our findings suggest that the dynamic properties of NCBD have been maintained by purifying selection and thus are important for its function, which includes mediating several distinct protein-protein interactions.

Exploring species-specific inhibitors with multiple target sites on S. aureus pyruvate kinase using a computational workflow

Experimental evidence indicated that bacterial pyruvate kinase of glycolysis can be evaluated as an alternative target to eliminate infections, while antibiotic resistance poses a global threat. Here, we use a computational workflow to reveal and investigate the potential allosteric sites of methicillin-resistant S. aureus PK, which can help in designing species-specific drugs to inhibit activity of this organism. Residue interaction networks point to a known allosteric site at the small C-C interface, a potential allosteric site near the small interface (site #1), and a second potential allosteric site at the large interface (site #2). 2 µs-long molecular dynamics (MD) simulations with AMBER16 generate different conformations of one narrow target site. Known and potential allosteric sites on the selected conformers are investigated using ensemble docking with AutoDock Vina and a library of 2447 FDA-approved drugs. We determine 18 hits, comprising ergot-alkaloids, anti-cancer-agents, antivirals, analgesics, cardiac glycosides, all with a high docking z-score for three sites. 5 selected compounds with high, average and low z-scores are subjected to 50 ns-long MD simulations for MM-GBSA calculations. ΔG_bind values up to -49.3 kcal/mol at the C-C interface, up to -32.7 kcal/mol at site #1, and up to -53.3 kcal/mol at site #2 support the docking calculations. We investigate mitapivat and TT-232 as reference compounds under clinical trial, targeting human PK isomers. We suggest 18 FDA-approved hits from the docking calculations and TT-232 as potential inhibitors with multiple target sites on S. aureus PK. This study also proposes pharmacophores models for de novo drug design.Communicated by Ramaswamy H. Sarma.

A new approach for extracting information from protein dynamics

Increased ability to predict protein structures is moving research focus towards understanding protein dynamics. A promising approach is to represent protein dynamics through networks and take advantage of well-developed methods from network science. Most studies build protein dynamics networks from correlation measures, an approach that only works under very specific conditions, instead of the more robust inverse approach. Thus, we apply the inverse approach to the dynamics of protein dihedral angles, a system of internal coordinates, to avoid structural alignment. Using the well-characterized adhesion protein, FimH, we show that our method identifies networks that are physically interpretable, robust, and relevant to the allosteric pathway sites. We further use our approach to detect dynamical differences, despite structural similarity, for Siglec-8 in the immune system, and the SARS-CoV-2 spike protein. Our study demonstrates that using the inverse approach to extract a network from protein dynamics yields important biophysical insights.

Design and engineering of allosteric communications in proteins

Allostery in proteins plays an important role in regulating protein activities and influencing many biological processes such as gene expression, enzyme catalysis, and cell signaling. The process of allostery takes place when a signal detected at a site on a protein is transmitted via a mechanical pathway to a functional site and, thus, influences its activity. The pathway of allosteric communication consists of amino acids that form a network with covalent and non-covalent bonds. By mutating residues in this allosteric network, protein engineers have successfully established novel allosteric pathways to achieve desired properties in the target protein. In this review, we highlight the most recent and state-of-the-art techniques for allosteric communication engineering. We also discuss the challenges that need to be overcome and future directions for engineering protein allostery.

Engineering and exploiting synthetic allostery of NanoLuc luciferase

Allostery enables proteins to interconvert different biochemical signals and form complex metabolic and signaling networks. We hypothesize that circular permutation of proteins increases the probability of functional coupling of new N- and C- termini with the protein's active center through increased local structural disorder. To test this we construct a synthetically allosteric version of circular permutated NanoLuc luciferase that can be activated through ligand-induced intramolecular non-covalent cyclisation. This switch module is tolerant of the structure of binding domains and their ligands, and can be used to create biosensors of proteins and small molecules. The developed biosensors covers a range of emission wavelengths and displays sensitivity as low as 50pM and dynamic range as high as 16-fold and could quantify their cognate ligand in human fluids. We apply hydrogen exchange kinetic mass spectroscopy to analyze time resolved structural changes in the developed biosensors and observe ligand-mediated folding of newly created termini.

The Inherent Coupling of Intrinsically Disordered Regions in the Multidomain Receptor Tyrosine Kinase KIT

RTK KIT regulates a variety of crucial cellular processes via its cytoplasmic domain (CD), which is composed of the tyrosine kinase domain, crowned by the highly flexible domains—the juxtamembrane region, kinase insertion domain, and C-tail, which are key recruitment regions for downstream signalling proteins. To prepare a structural basis for the characterization of the interactions of KIT with its signalling proteins (KIT INTERACTOME), we generated the 3D model of the full-length CD attached to the transmembrane helix. This generic model of KIT in inactive state was studied by molecular dynamics simulation under conditions mimicking the natural environment of KIT. With the accurate atomistic description of the multidomain KIT dynamics, we explained its intrinsic (intra-domain) and extrinsic (inter-domain) disorder and represented the conformational assemble of KIT through free energy landscapes. Strongly coupled movements within each domain and between distant domains of KIT prove the functional interdependence of these regions, described as allosteric regulation, a phenomenon widely observed in many proteins. We suggested that KIT, in its inactive state, encodes all properties of the active protein and its post-transduction events.

Insights into Rational Design of a New Class of Allosteric Effectors with Molecular Dynamics Markov State Models and Network Theory

The development of drugs to restore protein function has been a major advance facilitated by molecular medicine. Allosteric regulation, a phenomenon widely observed in nature, in which a molecule binds to control a distance active site, holds great promise for regulating proteins, yet how to rationally design such a molecule remains a mystery. Over the past few years, we and others have developed several techniques based on molecular dynamics (MD) simulations: MD-Markov state models to capture global conformational substates, and network theory approach utilizing the interaction energy within the protein to confer local allosteric control. We focus on the key case study of the p53 Y220C mutation restoration by PK11000, a compound experimentally shown to reactivate p53 native function in Y220C mutant present tumors. We gain insights into the mutation and allosteric reactivation of the protein, which we anticipate will be applicable to de novo design to engineer new compounds not only for this mutation, but in other macromolecular systems as well.

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.

Distinct allosteric pathways in imidazole glycerol phosphate synthase from yeast and bacteria

Understanding the relationship between protein structures and their function is still an open question that becomes very challenging when allostery plays an important functional role. Allosteric proteins, in fact, exploit different ranges of motions (from sidechain local fluctuations to long-range collective motions) to effectively couple distant binding sites, and of particular interest is whether allosteric proteins of the same families with similar functions and structures also necessarily share the same allosteric mechanisms. Here, we compared the early dynamics initiating the allosteric communication of a prototypical allosteric enzyme from two different organisms, i.e., the imidazole glycerol phosphate synthase (IGPS) enzymes from the thermophilic bacteria and the yeast, working at high and room temperatures, respectively. By combining molecular dynamics simulations and network models derived from graph theory, we found rather distinct early allosteric dynamics in the IGPS from the two organisms, involving significatively different allosteric pathways in terms of both local and collective motions. Given the successful prediction of key allosteric residues in the bacterial IGPS, whose mutation disrupts its allosteric communication, the outcome of this study paves the way for future experimental studies on the yeast IGPS that could foster therapeutic applications by exploiting the control of IGPS enzyme allostery.

Computational Study on the Dynamics of Mycobacterium Tuberculosis RNA Polymerase Assembly

Gene regulation is an intricate phenomenon involving precise function of many macromolecular complexes. Molecular basis of this phenomenon is highly complex and cannot be fully understood using a single technique. Computational approaches can play a crucial role in overall understanding of functional and mechanistic features of a protein or an assembly. Large amounts of structural data pertaining to these complexes are publicly available. In this project, we took advantage of the availability of the structural information to unravel functional intricacies of Mycobacterium tuberculosis RNA polymerase upon interaction with RbpA. In this article, we discuss how the knowledge on protein structure and dynamics can be exploited to study function using various computational tools and resources. Overall, this article provides an overview of various computational methods which can be efficiently used to understand the role of any protein. We hope especially the nonexperts in the field could benefit from our article.

Design of novel cyanovirin-N variants by modulation of binding dynamics through distal mutations

We develop integrated co-evolution and dynamic coupling (ICDC) approach to identify, mutate, and assess distal sites to modulate function. We validate the approach first by analyzing the existing mutational fitness data of TEM-1 β-lactamase and show that allosteric positions co-evolved and dynamically coupled with the active site significantly modulate function. We further apply ICDC approach to identify positions and their mutations that can modulate binding affinity in a lectin, cyanovirin-N (CV-N), that selectively binds to dimannose, and predict binding energies of its variants through Adaptive BP-Dock. Computational and experimental analyses reveal that binding enhancing mutants identified by ICDC impact the dynamics of the binding pocket, and show that rigidification of the binding residues compensates for the entropic cost of binding. This work suggests a mechanism by which distal mutations modulate function through dynamic allostery and provides a blueprint to identify candidates for mutagenesis in order to optimize protein function.

Catalytically active holo Homo sapiens adenosine deaminase I adopts a closed conformation

Homo sapiens adenosine deaminase 1 (HsADA1; UniProt P00813) is an immunologically relevant enzyme with roles in T-cell activation and modulation of adenosine metabolism and signaling. Patients with genetic deficiency in HsADA1 suffer from severe combined immunodeficiency, and HsADA1 is a therapeutic target in hairy cell leukemias. Historically, insights into the catalytic mechanism and the structural attributes of HsADA1 have been derived from studies of its homologs from Bos taurus (BtADA) and Mus musculus (MmADA). Here, the structure of holo HsADA1 is presented, as well as biochemical characterization that confirms its high activity and shows that it is active across a broad pH range. Structurally, holo HsADA1 adopts a closed conformation distinct from the open conformation of holo BtADA. Comparison of holo HsADA1 and MmADA reveals that MmADA also adopts a closed conformation. These findings challenge previous assumptions gleaned from BtADA regarding the conformation of HsADA1 that may be relevant to its immunological interactions, particularly its ability to bind adenosine receptors. From a broader perspective, the structural analysis of HsADA1 presents a cautionary tale for reliance on homologs to make structural inferences relevant to applications such as protein engineering or drug development.

Tetracycline Derivatives Inhibit Plasmodial Cysteine Protease Falcipain-2 through Binding to a Distal Allosteric Site

Allosteric inhibitors regulate enzyme activity from remote and usually specific pockets. As they promise an avenue for less toxic and safer drugs, the identification and characterization of allosteric inhibitors has gained great academic and biomedical interest in recent years. Research on falcipain-2 (FP-2), the major papain-like cysteine hemoglobinase of Plasmodium falciparum, might benefit from this strategy to overcome the low selectivity against human cathepsins shown by active site-directed inhibitors. Encouraged by our previous finding that methacycline inhibits FP-2 noncompetitively, here we assessed other five tetracycline derivatives against this target and characterized their inhibition mechanism. As previously shown for methacycline, tetracycline derivatives inhibited FP-2 in a noncompetitive fashion, with K_i values ranging from 121 to 190 μM. A possible binding to the S' side of the FP-2 active site, similar to that described by X-ray crystallography (PDB: 6SSZ) for the noncompetitive inhibitor E-chalcone 48 (EC48), was experimentally discarded by kinetic analysis using a large peptidyl substrate spanning the whole active site. By combining lengthy molecular dynamics (MD) simulations that allowed methacycline to diffuse from solution to different FP-2 surface regions and free energy calculations, we predicted the most likely binding mode of the ligand. Of note, the proposed binding pose explains the low differences in K_i values observed for the tested tetracycline derivatives and the calculated binding free energies match the experimental values. Overall, this study has implications for the design of novel allosteric inhibitors against FP-2 and sets the basis for further optimization of the tetracycline scaffold to produce more potent and selective inhibitors.

Enhanced specificity mutations perturb allosteric signaling in CRISPR-Cas9

CRISPR-Cas9 (clustered regularly interspaced short palindromic repeat and associated Cas9 protein) is a molecular tool with transformative genome editing capabilities. At the molecular level, an intricate allosteric signaling is critical for DNA cleavage, but its role in the specificity enhancement of the Cas9 endonuclease is poorly understood. Here, multi-microsecond molecular dynamics is combined with solution NMR and graph theory-derived models to probe the allosteric role of key specificity-enhancing mutations. We show that mutations responsible for increasing the specificity of Cas9 alter the allosteric structure of the catalytic HNH domain, impacting the signal transmission from the DNA recognition region to the catalytic sites for cleavage. Specifically, the K855A mutation strongly disrupts the allosteric connectivity of the HNH domain, exerting the highest perturbation on the signaling transfer, while K810A and K848A result in more moderate effects on the allosteric communication. This differential perturbation of the allosteric signal correlates to the order of specificity enhancement (K855A > K848A ~ K810A) observed in biochemical studies, with the mutation achieving the highest specificity most strongly perturbing the signaling transfer. These findings suggest that alterations of the allosteric communication from DNA recognition to cleavage are critical to increasing the specificity of Cas9 and that allosteric hotspots can be targeted through mutational studies for improving the system's function.

Design of a methotrexate-controlled chemical dimerization system and its use in bio-electronic devices

Natural evolution produced polypeptides that selectively recognize chemical entities and their polymers, ranging from ions to proteins and nucleic acids. Such selective interactions serve as entry points to biological signaling and metabolic pathways. The ability to engineer artificial versions of such entry points is a key goal of synthetic biology, bioengineering and bioelectronics. We set out to map the optimal strategy for developing artificial small molecule:protein complexes that function as chemically induced dimerization (CID) systems. Using several starting points, we evolved CID systems controlled by a therapeutic drug methotrexate. Biophysical and structural analysis of methotrexate-controlled CID system reveals the critical role played by drug-induced conformational change in ligand-controlled protein complex assembly. We demonstrate utility of the developed CID by constructing electrochemical biosensors of methotrexate that enable quantification of methotrexate in human serum. Furthermore, using the methotrexate and functionally related biosensor of rapamycin we developed a multiplexed bioelectronic system that can perform repeated measurements of multiple analytes. The presented results open the door for construction of genetically encoded signaling systems for use in bioelectronics and diagnostics, as well as metabolic and signaling network engineering.

Molecular Paradigms for Biological Mechanosensing

Many proteins in living cells are subject to mechanical forces, which can be generated internally by molecular machines, or externally, e.g., by pressure gradients. In general, these forces fall in the piconewton range, which is similar in magnitude to forces experienced by a molecule due to thermal fluctuations. While we would naively expect such moderate forces to produce only minimal changes, a wide variety of "mechanosensing" proteins have evolved with functions that are responsive to forces in this regime. The goal of this article is to provide a physical chemistry perspective on protein-based molecular mechanosensing paradigms used in living systems, and how these paradigms can be explored using novel computational methods.

Towards the Idea of Molecular Brains

How can single cells without nervous systems perform complex behaviours such as habituation, associative learning and decision making, which are considered the hallmark of animals with a brain? Are there molecular systems that underlie cognitive properties equivalent to those of the brain? This review follows the development of the idea of molecular brains from Darwin’s “root brain hypothesis”, through bacterial chemotaxis, to the recent discovery of neuron-like r-protein networks in the ribosome. By combining a structural biology view with a Bayesian brain approach, this review explores the evolutionary labyrinth of information processing systems across scales. Ribosomal protein networks open a window into what were probably the earliest signalling systems to emerge before the radiation of the three kingdoms. While ribosomal networks are characterised by long-lasting interactions between their protein nodes, cell signalling networks are essentially based on transient interactions. As a corollary, while signals propagated in persistent networks may be ephemeral, networks whose interactions are transient constrain signals diffusing into the cytoplasm to be durable in time, such as post-translational modifications of proteins or second messenger synthesis. The duration and nature of the signals, in turn, implies different mechanisms for the integration of multiple signals and decision making. Evolution then reinvented networks with persistent interactions with the development of nervous systems in metazoans. Ribosomal protein networks and simple nervous systems display architectural and functional analogies whose comparison could suggest scale invariance in information processing. At the molecular level, the significant complexification of eukaryotic ribosomal protein networks is associated with a burst in the acquisition of new conserved aromatic amino acids. Knowing that aromatic residues play a critical role in allosteric receptors and channels, this observation suggests a general role of π systems and their interactions with charged amino acids in multiple signal integration and information processing. We think that these findings may provide the molecular basis for designing future computers with organic processors.

Extracting Dynamical Correlations and Identifying Key Residues for Allosteric Communication in Proteins by correlationplus

Extracting dynamical pairwise correlations and identifying key residues from large molecular dynamics trajectories or normal-mode analysis of coarse-grained models are important for explaining various processes like ligand binding, mutational effects, and long-distance interactions. Efficient and flexible tools to perform this task can provide new insights about residues involved in allosteric regulation and protein function. In addition, combining and comparing dynamical coupling information with sequence coevolution data can help to understand better protein function. To this aim, we developed a Python package called correlationplus to calculate, visualize, and analyze pairwise correlations. In this way, the package aids to identify key residues and interactions in proteins. The source code of correlationplus is available under LGPL version 3 at https://github.com/tekpinar/correlationplus. The current version of the package (0.2.0) can be installed with common installation methods like conda or pip in addition to source code installation. Moreover, docker images are also available for usage of the code without installation.

Allosteric pockets and dynamic residue network hubs of falcipain 2 in mutations including those linked to artemisinin resistance

Continually emerging resistant strains of malarial parasites to current drugs present challenges. Understanding the underlying resistance mechanisms, especially those linked to allostery is, thus, highly crucial for drug design. This forms the main concern of the paper through a case study of falcipain 2 (FP-2) and its mutations, some of which are linked to artemisinin (ART) drug resistance. Here, we applied a variety of in silico approaches and tools that we developed recently, together with existing computational tools. This included novel essential dynamics and dynamic residue network (DRN) analysis algorithms. We identified six pockets demonstrating dynamic differences in the presence of some mutations. We observed striking allosteric effects in two mutant proteins. In the presence of M245I, a cryptic pocket was detected via a unique mechanism in which Pocket 2 fused with Pocket 6. In the presence of the A353T mutation, which is located at Pocket 2, the pocket became the most rigid among all protein systems analyzed. Pocket 6 was also highly stable in all cases, except in the presence of M245I mutation. The effect of ART linked mutations was more subtle, and the changes were at residue level. Importantly, we identified an allosteric communication path formed by four unique averaged BC hubs going from the mutated residue to the catalytic site and passing through the interface of three identified pockets. Collectively, we established and demonstrated that we have robust tools and a pipeline that can be applicable to the analysis of mutations.

Structure-based design of a photoswitchable affibody scaffold

Photo-control of affinity reagents offers a general approach for high-resolution spatiotemporal control of diverse molecular processes. In an effort to develop general design principles for a photo-controlled affinity reagent, we took a structure-based approach to the design of a photoswitchable Z-domain, among the simplest of affinity reagent scaffolds. A chimera, designated Z-PYP, of photoactive yellow protein (PYP) and the Z-domain, was designed based on the concept of mutually exclusive folding. NMR analysis indicated that, in the dark, the PYP domain of the chimera was folded, and the Z-domain was unfolded. Blue light caused loss of structure in PYP and a two- to sixfold change in the apparent affinity of Z-PYP for its target as determined using size exclusion chromatography, UV-Vis based assays, and enyzme-linked immunosorbent assay (ELISA). A thermodynamic model indicated that mutations to decrease Z-domain folding energy would alter target affinity without loss of switching. This prediction was confirmed experimentally with a double alanine mutant in helix 3 of the Z-domain of the chimera (Z-PYP-AA) showing >30-fold lower dark-state binding and no loss in switching. The effect of decreased dark-state binding affinity was tested in a two-hybrid transcriptional control format and enabled pronounced light/dark differences in yeast growth in vivo. Finally, the design was transferable to the αZ-Taq affibody enabling tunable light-dependent binding both in vitro and in vivo to the Z-Taq target. This system thus provides a framework for the focused development of light switchable affibodies for a range of targets.

Hemoglobin allostery and pharmacology

The oxygen demands of the human body require the constant circulation of blood carrying an enormous concentration of hemoglobin (Hb). Oxygen transport depends not only on the amount of Hb, but also on the control over the affinity of the protein for the gas, which can be optimized for the environmental conditions by changes in the concentration of effectors (hydrogen ions, chloride, CO2, and DPG) inside the red cell. Some pathological conditions affecting Hb may benefit from pharmacological interventions to increase or decrease its affinity for oxygen, or otherwise modify its properties, or alter its biosynthesis. Examples of such conditions include sickle cell anemia, thalassemias and inherited hemoglobinopathies. Effective and safe drugs such as voxelotor, bezafibrate and efaproxiral are available that significantly increase or decrease Hb oxygen affinity. Some medical conditions not directly affecting the blood or its oxygen carrying capacity may also be relieved by the manipulation of Hb. For example, the standard treatment of acute cyanide poisoning requires the oxidation of a fraction of the Hb in the bloodstream so that it efficiently scavenges cyanide. Tumors are often extremely hypoxic and therefore strongly resistant to radiotherapy; the sensitivity of cancerous tissue to X-rays may be increased by improved oxygenation through drugs binding Hb. This review attempts to provide a systematic exploration of the pharmacology of Hb, its molecular basis, and its intended and possible uses.

Out-of-Equilibrium Biophysical Chemistry: The Case for Multidimensional, Integrated Single-Molecule Approaches

Out-of-equilibrium processes are ubiquitous across living organisms and all structural hierarchies of life. At the molecular scale, out-of-equilibrium processes (for example, enzyme catalysis, gene regulation, and motor protein functions) cause biological macromolecules to sample an ensemble of conformations over a wide range of time scales. Quantifying and conceptualizing the structure–dynamics to function relationship is challenging because continuously evolving multidimensional energy landscapes are necessary to describe nonequilibrium biological processes in biological macromolecules. In this perspective, we explore the challenges associated with state-of-the-art experimental techniques to understanding biological macromolecular function. We argue that it is time to revisit how we probe and model functional out-of-equilibrium biomolecular dynamics. We suggest that developing integrated single-molecule multiparametric force–fluorescence instruments and using advanced molecular dynamics simulations to study out-of-equilibrium biomolecules will provide a path towards understanding the principles of and mechanisms behind the structure–dynamics to function paradigm in biological macromolecules.

Epistasis shapes the fitness landscape of an allosteric specificity switch

Epistasis is a major determinant in the emergence of novel protein function. In allosteric proteins, direct interactions between inducer-binding mutations propagate through the allosteric network, manifesting as epistasis at the level of biological function. Elucidating this relationship between local interactions and their global effects is essential to understanding evolution of allosteric proteins. We integrate computational design, structural and biophysical analysis to characterize the emergence of novel inducer specificity in an allosteric transcription factor. Adaptive landscapes of different inducers of the designed mutant show that a few strong epistatic interactions constrain the number of viable sequence pathways, revealing ridges in the fitness landscape leading to new specificity. The structure of the designed mutant shows that a striking change in inducer orientation still retains allosteric function. Comparing biophysical and functional properties suggests a nonlinear relationship between inducer binding affinity and allostery. Our results highlight the functional and evolutionary complexity of allosteric proteins.

Epistasis plays an important role in the evolution of novel protein functions because it determines the mutational path a protein takes. Here, the authors combine functional, structural and biophysical analyses to characterize epistasis in a computationally redesigned ligand-inducible allosteric transcription factor and found that epistasis creates distinct biophysical and biological functional landscapes.

Dynamic Cellular Cartography: Mapping the Local Determinants of Oligodendrocyte Transcription Factor 2 (OLIG2) Function in Live Cells Using Massively Parallel Fluorescence Correlation Spectroscopy Integrated with Fluorescence Lifetime Imaging Microscopy (mpFCS/FLIM)

Compartmentalization and integration of molecular processes through diffusion are basic mechanisms through which cells perform biological functions. To characterize these mechanisms in live cells, quantitative and ultrasensitive analytical methods with high spatial and temporal resolution are needed. Here, we present quantitative scanning-free confocal microscopy with single-molecule sensitivity, high temporal resolution (∼10 μs/frame), and fluorescence lifetime imaging capacity, developed by integrating massively parallel fluorescence correlation spectroscopy with fluorescence lifetime imaging microscopy (mpFCS/FLIM); we validate the method, use it to map in live cell location-specific variations in the concentration, diffusion, homodimerization, DNA binding, and local environment of the oligodendrocyte transcription factor 2 fused with the enhanced Green Fluorescent Protein (OLIG2-eGFP), and characterize the effects of an allosteric inhibitor of OLIG2 dimerization on these determinants of OLIG2 function. In particular, we show that cytoplasmic OLIG2-eGFP is largely monomeric and freely diffusing, with the fraction of freely diffusing OLIG2-eGFP molecules being f_D,free^cyt = (0.75 ± 0.10) and the diffusion time τ_D,free^cyt = (0.5 ± 0.3) ms. In contrast, OLIG2-eGFP homodimers are abundant in the cell nucleus, constituting ∼25% of the nuclear pool, some f_D,bound^nuc = (0.65 ± 0.10) of nuclear OLIG2-eGFP is bound to chromatin DNA, whereas freely moving OLIG2-eGFP molecules diffuse at the same rate as those in the cytoplasm, as evident from the lateral diffusion times τ_D,free^nuc = τ_D,free^cyt = (0.5 ± 0.3) ms. OLIG2-eGFP interactions with chromatin DNA, revealed through their influence on the apparent diffusion behavior of OLIG2-eGFP, τ_D,bound^nuc (850 ± 500) ms, are characterized by an apparent dissociation constant K_d,app^OLIG2-DNA = (45 ± 30) nM. The apparent dissociation constant of OLIG2-eGFP homodimers was estimated to be K_d,app^{(OLIG2-eGFP)2} ≈ 560 nM. The allosteric inhibitor of OLIG2 dimerization, compound NSC 50467, neither affects OLIG2-eGFP properties in the cytoplasm nor does it alter the overall cytoplasmic environment. In contrast, it significantly impedes OLIG2-eGFP homodimerization in the cell nucleus, increasing five-fold the apparent dissociation constant, K_{d,app,NSC50467}^{(OLIG2-eGFP)2} ≈ 3 μM, thus reducing homodimer levels to below 7% and effectively abolishing OLIG2-eGFP specific binding to chromatin DNA. The mpFCS/FLIM methodology has a myriad of applications in biomedical research and pharmaceutical industry. For example, it is indispensable for understanding how biological functions emerge through the dynamic integration of location-specific molecular processes and invaluable for drug development, as it allows us to quantitatively characterize the interactions of drugs with drug targets in live cells.

State-selective frustration as a key driver of allosteric pluripotency

Allosteric pluripotency arises when an allosteric effector switches from agonist to antagonist depending on the experimental conditions. For example, the Rp-cAMPS ligand of Protein Kinase A (PKA) switches from agonist to antagonist as the MgATP concentration increases and/or the kinase substrate affinity or concentration decreases. Understanding allosteric pluripotency is essential to design effective allosteric therapeutics with minimal side effects. Allosteric pluripotency of PKA arises from divergent allosteric responses of two homologous tandem cAMP-binding domains, resulting in a free energy landscape for the Rp-cAMPS-bound PKA regulatory subunit R1a in which the ground state is kinase inhibition-incompetent and the kinase inhibition-competent state is excited. The magnitude of the free energy difference between the ground non-inhibitory and excited inhibitory states (ΔG_R,Gap) relative to the effective free energy of R1a binding to the catalytic subunit of PKA (ΔG_R:C) dictates whether the antagonism-to-agonism switch occurs. However, the key drivers of ΔG_R,Gap are not fully understood. Here, by analyzing an R1a mutant that selectively silences allosteric pluripotency, we show that a major determinant of ΔG_R,Gap unexpectedly arises from state-selective frustration in the ground inhibition-incompetent state of Rp-cAMPS-bound R1a. Such frustration is caused by steric clashes between the phosphate-binding cassette and the helices preceding the lid, which interact with the phosphate and base of Rp-cAMPS, respectively. These clashes are absent in the excited inhibitory state, thus reducing the ΔG_R,Gap to values comparable to ΔG_R:C, as needed for allosteric pluripotency to occur. The resulting model of allosteric pluripotency is anticipated to assist the design of effective allosteric modulators.

The Rp-cAMPS ligand of protein kinase A switches from agonist to antagonist depending on metabolite and proteomic contexts. We show that the state-selective frustration is a key driver of this allosteric pluripotency phenomenon.

Combining steady state and temperature jump IR spectroscopy to investigate the allosteric effects of ligand binding to dsDNA

Changes in the structural dynamics of double stranded (ds)DNA upon ligand binding have been linked to the mechanism of allostery without conformational change, but direct experimental evidence remains elusive. To address this, a combination of steady state infrared (IR) absorption spectroscopy and ultrafast temperature jump IR absorption measurements has been used to quantify the extent of fast (∼100 ns) fluctuations in (ds)DNA·Hoechst 33258 complexes at a range of temperatures. Exploiting the direct link between vibrational band intensities and base stacking shows that the absolute magnitude of the change in absorbance caused by fast structural fluctuations following the temperature jump is only weakly dependent on the starting temperature of the sample. The observed fast dynamics are some two orders of magnitude faster than strand separation and associated with all points along the 10-base pair duplex d(GCATATATCC). Binding the Hoechst 33258 ligand causes a small but consistent reduction in the extent of these fast fluctuations of base pairs located outside of the ligand binding region. These observations point to a ligand-induced reduction in the flexibility of the dsDNA near the binding site, consistent with an estimated allosteric propagation length of 15 Å, about 5 base pairs, which agrees well with both molecular simulation and coarse-grained statistical mechanics models of allostery leading to cooperative ligand binding.

Making the invisible visible: Toward structural characterization of allosteric states, interaction networks, and allosteric regulatory mechanisms in protein kinases

Despite the established view of protein kinases as dynamic and versatile allosteric regulatory machines, our knowledge of allosteric functional states, allosteric interaction networks, and the intrinsic folding energy landscapes is surprisingly limited. We discuss the latest developments in structural characterization of allosteric molecular events underlying protein kinase dynamics and functions using structural, biophysical, and computational biology approaches. The recent studies highlighted progress in making the invisible aspects of protein kinase 'life' visible, including the determination of hidden allosteric states and mapping of allosteric energy landscapes, discovery of new mechanisms underlying ligand-induced modulation of allosteric activity, evolutionary adaptation of kinase allostery, and characterization of allosteric interaction networks as the intrinsic driver of kinase adaptability and signal transmission in the regulatory assemblies.

Biochemical, structural and dynamical studies reveal strong differences in the thermal-dependent allosteric behavior of two extremophilic lactate dehydrogenases

In this work, we combined biochemical and structural investigations with molecular dynamics (MD) simulations to analyze the very different thermal-dependent allosteric behavior of two lactate dehydrogenases (LDH) from thermophilic bacteria. We found that the enzyme from Petrotoga mobilis (P. mob) necessitates an absolute requirement of the allosteric effector (fructose 1, 6-bisphosphate) to ensure functionality. In contrast, even without allosteric effector, the LDH from Thermus thermophilus (T. the) is functional when the temperature is raised. We report the crystal structure of P. mob LDH in the Apo state solved at 1.9 Å resolution. We used this structure and the one from T. the, obtained previously, as a starting point for MD simulations at various temperatures. We found clear differences between the thermal dynamics, which accounts for the behavior of the two enzymes. Our work demonstrates that, within an allosteric enzyme, some areas act as local gatekeepers of signal transmission, allowing the enzyme to populate either the T-inactive or the R-active states with different degrees of stringency.

Dimeric allostery mechanism of the plant circadian clock photoreceptor ZEITLUPE

In Arabidopsis thaliana, the Light-Oxygen-Voltage (LOV) domain containing protein ZEITLUPE (ZTL) integrates light quality, intensity, and duration into regulation of the circadian clock. Recent structural and biochemical studies of ZTL indicate that the protein diverges from other members of the LOV superfamily in its allosteric mechanism, and that the divergent allosteric mechanism hinges upon conservation of two signaling residues G46 and V48 that alter dynamic motions of a Gln residue implicated in signal transduction in all LOV proteins. Here, we delineate the allosteric mechanism of ZTL via an integrated computational approach that employs atomistic simulations of wild type and allosteric variants of ZTL in the functional dark and light states, together with Markov state and supervised machine learning classification models. This approach has unveiled key factors of the ZTL allosteric mechanisms, and identified specific interactions and residues implicated in functional allosteric changes. The final results reveal atomic level insights into allosteric mechanisms of ZTL function that operate via a non-trivial combination of population-shift and dynamics-driven allosteric pathways.

Landscape-Based Mutational Sensitivity Cartography and Network Community Analysis of the SARS-CoV-2 Spike Protein Structures: Quantifying Functional Effects of the Circulating D614G Variant

We developed and applied a computational approach to simulate functional effects of the global circulating mutation D614G of the SARS-CoV-2 spike protein. All-atom molecular dynamics simulations are combined with deep mutational scanning and analysis of the residue interaction networks to investigate conformational landscapes and energetics of the SARS-CoV-2 spike proteins in different functional states of the D614G mutant. The results of conformational dynamics and analysis of collective motions demonstrated that the D614 site plays a key regulatory role in governing functional transitions between open and closed states. Using mutational scanning and sensitivity analysis of protein residues, we identified the stability hotspots in the SARS-CoV-2 spike structures of the mutant trimers. The results suggest that the D614G mutation can induce the increased stability of the open form acting as a driver of conformational changes, which may result in the increased exposure to the host receptor and promote infectivity of the virus. The network community analysis of the SARS-CoV-2 spike proteins showed that the D614G mutation can enhance long-range couplings between domains and strengthen the interdomain interactions in the open form, supporting the reduced shedding mechanism. This study provides the landscape-based perspective and atomistic view of the allosteric interactions and stability hotspots in the SARS-CoV-2 spike proteins, offering a useful insight into the molecular mechanisms underpinning functional effects of the global circulating mutations.

Allosteric Type and Pathways Are Governed by the Forces of Protein-Ligand Binding

Allostery is central to many cellular processes, by up- or down-regulating target function. However, what determines the allosteric type remains elusive and currently it is impossible to predict whether the allosteric compounds would activate or inhibit target function before experimental studies. We demonstrated that the allosteric type and allosteric pathways are governed by the forces imposed by ligand binding to target protein using the anisotropic network model and developed an allosteric type prediction method (AlloType). AlloType correctly predicted 13 of the 16 allosteric systems in the data set with experimentally determined protein and complex structures as well as verified allosteric types, which was also used to identify allosteric pathways. When applied to glutathione peroxidase 4, a protein with no complex structure information, AlloType could still be able to predict the allosteric type of the recently reported allosteric activators, demonstrating its potential application in designing specific allosteric drugs and uncovering allosteric mechanisms.

Allosteric conformational ensembles have unlimited capacity for integrating information

Integration of binding information by macromolecular entities is fundamental to cellular functionality. Recent work has shown that such integration cannot be explained by pairwise cooperativities, in which binding is modulated by binding at another site. Higher-order cooperativities (HOCs), in which binding is collectively modulated by multiple other binding events, appear to be necessary but an appropriate mechanism has been lacking. We show here that HOCs arise through allostery, in which effective cooperativity emerges indirectly from an ensemble of dynamically interchanging conformations. Conformational ensembles play important roles in many cellular processes but their integrative capabilities remain poorly understood. We show that sufficiently complex ensembles can implement any form of information integration achievable without energy expenditure, including all patterns of HOCs. Our results provide a rigorous biophysical foundation for analysing the integration of binding information through allostery. We discuss the implications for eukaryotic gene regulation, where complex conformational dynamics accompanies widespread information integration.

Divalent ligand-monovalent molecule binding

Simultaneous binding of a divalent ligand to two identical monovalent molecules is a widespread phenomenon in biology and chemistry. Here, we describe how two such monovalent molecules B bind to a divalent ligand AA to form the intermediate and final complexes AA·B and AA·B2. Cases wherein the total concentration [AA]T is either much larger or much smaller than the total concentration [B]T have been studied earlier, but a systematic description of comparable concentrations [AA]T and [B]T is missing. Here, we present numerical and analytical results for the concentrations [AA·B] and [AA·B2] for the entire range 0 < [B]T/[AA]T < ∞. Specifically, we theoretically study three types of experimental procedures: dilution of AA and B at fixed [B]T/[AA]T, addition of AA at fixed [B]T, and addition of B at fixed [AA]T. When [AA]T and [B]T are comparable, the concentrations of free ligands and molecules both decrease upon binding. Such depletion is expected to be important in cellular contexts, e.g., in antigen detection and in coincidence detection of proteins or lipids.

Entropy-based distance cutoff for protein internal contact networks

Protein structure networks (PSNs) have long been used to provide a coarse yet meaningful representation of protein structure, dynamics, and internal communication pathways. An important question is what criteria should be applied to construct the network so that to include relevant interresidue contacts while avoiding unnecessary connections. To address this issue, we systematically considered varying residue distance cutoff length and the probability threshold for contact formation to construct PSNs based on atomistic molecular dynamics in order to assess the amount of mutual information within the resulting representations. We found that the minimum in mutual information is universally achieved at the cutoff length of 5 Å, irrespective of the applied contact formation probability threshold in all considered, distinct proteins. Assuming that the optimal PSNs should be characterized by the least amount of redundancy, which corresponds to the minimum in mutual information, this finding suggests an objective criterion for cutoff distance and supports the existing preference towards its customary selection around 5 Å length, typically based to date on heuristic criteria.

Epistasis and intramolecular networks in protein evolution

Proteins are molecular machines composed of complex, highly connected amino acid networks. Their functional optimization requires the reorganization of these intramolecular networks by evolution. In this review, we discuss the mechanisms by which epistasis, that is, the dependence of the effect of a mutation on the genetic background, rewires intramolecular interactions to alter protein function. Deciphering the biophysical basis of epistasis is crucial to our understanding of evolutionary dynamics and the elucidation of sequence-structure-function relationships. We featured recent studies that provide insights into the molecular mechanisms giving rise to epistasis, particularly at the structural level. These studies illustrate the convoluted and fascinating nature of the intramolecular networks co-opted by epistasis during the evolution of protein function.