Tuning the "violin" of protein kinases: The role of dynamics-based allostery

Thermodynamic model for memory

A thermodynamic model for memory formation is proposed. Key points include: 1) Any thought or consciousness corresponds to a thermodynamic system of nerve cells. 2) The system concept of nerve cells can only be described by thermodynamics of condensed matter. 3) The memory structure is logically associated with the system structure or the normal structure of biology. 4) The development of our thoughts is processed irreversibly, and numerous states or thoughts can be generated. 5) Memory formation results from the reorganization and change of cellular structures (or memory structures), which are related to nerve cell skeleton and membrane. Their alteration can change the excitability of nerve cells and the pathway of neural impulse conduction. 6) Amnesia results from the loss of thermodynamic stability of the memory structure, which can be achieved by different ways. Some related phenomena and facts are discussed. The analysis shows that thermodynamics can account for the basic properties of memory.

CDK2 and CDK4: Cell Cycle Functions Evolve Distinct, Catalysis-Competent Conformations, Offering Drug Targets

Cyclin-dependent kinases (CDKs), particularly CDK4 and CDK2, are crucial for cell cycle progression from the Gap 1 (G1) to the Synthesis (S) phase by phosphorylating targets such as the Retinoblastoma Protein (Rb). CDK4, paired with cyclin-D, operates in the long G1 phase, while CDK2 with cyclin-E, manages the brief G1-to-S transition, enabling DNA replication. Aberrant CDK signaling leads to uncontrolled cell proliferation, which is a hallmark of cancer. Exactly how they accomplish their catalytic phosphorylation actions with distinct efficiencies poses the fundamental, albeit overlooked question. Here we combined available experimental data and modeling of the active complexes to establish their conformational functional landscapes to explain how the two cyclin/CDK complexes differentially populate their catalytically competent states for cell cycle progression. Our premise is that CDK catalytic efficiencies could be more important for cell cycle progression than the cyclin-CDK biochemical binding specificity and that efficiency is likely the prime determinant of cell cycle progression. We observe that CDK4 is more dynamic than CDK2 in the ATP binding site, the regulatory spine, and the interaction with its cyclin partner. The N-terminus of cyclin-D acts as an allosteric regulator of the activation loop and the ATP-binding site in CDK4. Integrated with a suite of experimental data, we suggest that the CDK4 complex is less capable of remaining in the active catalytically competent conformation, and may have a lower catalytic efficiency than CDK2, befitting their cell cycle time scales, and point to critical residues and motifs that drive their differences. Our mechanistic landscape may apply broadly to kinases, and we propose two drug design strategies: (i) allosteric Inhibition by conformational stabilization for targeting allosteric CDK4 regulation by cyclin-D, and (ii) dynamic entropy-optimized targeting which leverages the dynamic, entropic aspects of CDK4 to optimize drug binding efficacy.

Network pharmacology and molecular docking: combined computational approaches to explore the antihypertensive potential of Fabaceae species

Hypertension is a major global public health issue, affecting quarter of adults worldwide. Numerous synthetic drugs are available for treating hypertension; however, they often come with a higher risk of side effects and long-term therapy. Modern formulations with active phytoconstituents are gaining popularity, addressing some of these issues. This study aims to discover novel antihypertensive compounds in Cassia fistula, Senna alexandrina, and Cassia occidentalis from family Fabaceae and understand their interaction mechanism with hypertension targeted genes, using network pharmacology and molecular docking. Total 414 compounds were identified; initial screening was conducted based on their pharmacokinetic and ADMET properties, with a particular emphasis on adherence to Lipinski's rules. 6 compounds, namely Germichrysone, Benzeneacetic acid, Flavan-3-ol, 5,7,3',4'-Tetrahydroxy-6, 8-dimethoxyflavon, Dihydrokaempferol, and Epiafzelechin, were identified as effective agents. Most of the compounds found non-toxic against various indicators with greater bioactivity score. 161 common targets were obtained against these compounds and hypertension followed by compound-target network construction and protein-protein interaction, which showed their role in diverse biological system. Top hub genes identified were TLR4, MMP9, MAPK14, AKT1, VEGFA and HSP90AA1 with their respective associates. Higher binding affinities was found with three compounds Dihydrokaempferol, Flavan-3-ol and Germichrysone, -7.1, -9.0 and -8.0 kcal/mol, respectively. The MD simulation results validate the structural flexibility of two complexes Flavan-MMP9 and Germich-TLR4 based on no. of hydrogen bonds, root mean square deviations and interaction energies. This study concluded that C. fistula (Dihydrokaempferol, Flavan-3-ol) and C. occidentalis (Germichrysone) have potential therapeutic active constituents to treat hypertension and in future novel drug formulation.

Evolutionary sequence and structural basis for the distinct conformational landscapes of Tyr and Ser/Thr kinases

Protein kinases are molecular machines with rich sequence variation that distinguishes the two main evolutionary branches - tyrosine kinases (TKs) from serine/threonine kinases (STKs). Using a sequence co-variation Potts statistical energy model we previously concluded that TK catalytic domains are more likely than STKs to adopt an inactive conformation with the activation loop in an autoinhibitory "folded" conformation, due to intrinsic sequence effects. Here we investigated the structural basis for this phenomenon by integrating the sequence-based model with structure-based molecular dynamics (MD) to determine the effects of mutations on the free energy difference between active and inactive conformations, using a novel thermodynamic cycle involving many (n=108) protein-mutation free energy perturbation (FEP) simulations in the active and inactive conformations. The sequence and structure-based results are consistent and support the hypothesis that the inactive conformation "DFG-out Activation Loop Folded", is a functional regulatory state that has been stabilized in TKs relative to STKs over the course of their evolution via the accumulation of residue substitutions in the activation loop and catalytic loop that facilitate distinct substrate binding modes in trans and additional modes of regulation in cis for TKs.

Evolutionary sequence and structural basis for the distinct conformational landscapes of Tyr and Ser/Thr kinases

Protein kinases are molecular machines with rich sequence variation that distinguishes the two main evolutionary branches - tyrosine kinases (TKs) from serine/threonine kinases (STKs). Using a sequence co-variation Potts statistical energy model we previously concluded that TK catalytic domains are more likely than STKs to adopt an inactive conformation with the activation loop in an autoinhibitory "folded" conformation, due to intrinsic sequence effects. Here we investigated the structural basis for this phenomenon by integrating the sequence-based model with structure-based molecular dynamics (MD) to determine the effects of mutations on the free energy difference between active and inactive conformations, using a novel thermodynamic cycle involving many (n=108) protein-mutation free energy perturbation (FEP) simulations in the active and inactive conformations. The sequence and structure-based results are consistent and support the hypothesis that the inactive conformation "DFG-out Activation Loop Folded", is a functional regulatory state that has been stabilized in TKs relative to STKs over the course of their evolution via the accumulation of residue substitutions in the activation loop and catalytic loop that facilitate distinct substrate binding modes in trans and additional modes of regulation in cis for TKs.

Machine learning approaches in predicting allosteric sites

Allosteric regulation is a fundamental biological mechanism that can control critical cellular processes via allosteric modulator binding to protein distal functional sites. The advantages of allosteric modulators over orthosteric ones have sparked the development of numerous computational approaches, such as the identification of allosteric binding sites, to facilitate allosteric drug discovery. Building on the success of machine learning (ML) models for solving complex problems in biology and chemistry, several ML models for predicting allosteric sites have been developed. In this review, we provide an overview of these models and discuss future perspectives powered by the field of artificial intelligence such as protein language models.

Allostery in Protein Tyrosine Phosphatases is Enabled by Divergent Dynamics

Dynamics-driven allostery provides important insights into the working mechanics of proteins, especially enzymes. In this study, we employ this paradigm to answer a basic question: in enzyme superfamilies, where the catalytic mechanism, active sites, and protein fold are conserved, what accounts for the difference in the catalytic prowess of the individual members? We show that when subtle changes in sequence do not translate to changes in structure, they do translate to changes in dynamics. We use sequentially diverse PTP1B, TbPTP1, and YopH as representatives of the conserved protein tyrosine phosphatase (PTP) superfamily. Using amino acid network analysis of group behavior (community analysis) and influential node dominance on networks (eigenvector centrality), we explain the dynamic basis of the catalytic variations seen between the three proteins. Importantly, we explain how a dynamics-based blueprint makes PTP1B amenable to allosteric control and how the same is abstracted in TbPTP1 and YopH.

Protein dynamics underlying allosteric regulation

Allostery is the mechanism by which information and control are propagated in biomolecules. It regulates ligand binding, chemical reactions, and conformational changes. An increasing level of experimental resolution and control over allosteric mechanisms promises a deeper understanding of the molecular basis for life and powerful new therapeutics. In this review, we survey the literature for an up-to-date biological and theoretical understanding of protein allostery. By delineating five ways in which the energy landscape or the kinetics of a system may change to give rise to allostery, we aim to help the reader grasp its physical origins. To illustrate this framework, we examine three systems that display these forms of allostery: allosteric inhibitors of beta-lactamases, thermosensation of TRP channels, and the role of kinetic allostery in the function of kinases. Finally, we summarize the growing power of computational tools available to investigate the different forms of allostery presented in this review.

Allosteric communication and signal transduction in proteins

Allostery is one of the cornerstones of biological function, as it plays a fundamental role in regulating protein activity. The modelling of allostery has gradually moved from a conformation-based framework, linked to structural changes, to dynamics-based allostery, whereby the effects of ligand binding propagate via signal transduction from the allosteric site to other regions of the protein via inter-residue interactions. Characterising such allosteric signalling pathways, which do not necessarily lead to conformational changes, has been pursued experimentally and complemented by computational analysis of protein networks to detect subtle dynamic propagation paths. Considering allostery from the perspective of signal transduction broadens the understanding of allosteric mechanisms, underscores the importance of protein topology, and can provide insights into allosteric drug design.

Drive-specific selection in multistable mechanical networks

Systems with many stable configurations abound in nature, both in living and inanimate matter, encoding a rich variety of behaviors. In equilibrium, a multistable system is more likely to be found in configurations with lower energy, but the presence of an external drive can alter the relative stability of different configurations in unexpected ways. Living systems are examples par excellence of metastable nonequilibrium attractors whose structure and stability are highly dependent on the specific form and pattern of the energy flow sustaining them. Taking this distinctively lifelike behavior as inspiration, we sought to investigate the more general physical phenomenon of drive-specific selection in nonequilibrium dynamics. To do so, we numerically studied driven disordered mechanical networks of bistable springs possessing a vast number of stable configurations arising from the two stable rest lengths of each spring, thereby capturing the essential physical properties of a broad class of multistable systems. We found that there exists a range of forcing amplitudes for which the attractor states of driven disordered multistable mechanical networks are fine-tuned with respect to the pattern of external forcing to have low energy absorption from it. Additionally, we found that these drive-specific attractor states are further stabilized by precise matching between the multidimensional shape of their orbit and that of the potential energy well they inhabit. Lastly, we showed evidence of drive-specific selection in an experimental system and proposed a general method to estimate the range of drive amplitudes for drive-specific selection.

The discovery of hidden guanylate cyclases (GCs) in the Homo sapiens proteome

Recent discoveries have established functional guanylate cyclase (GC) catalytic centers with low activity within kinase domains in plants. These crypto GCs generate guanosine 3',5'-cyclic monophosphate (cGMP) essential for both intramolecular and downstream signaling. Here, we have set out to search for such crypto GCs moonlighting in kinases in the H. sapiens proteome and identified 18 candidates, including the neurotropic receptor tyrosine kinase 1 (NTRK1). NTRK1 shows a domain architecture much like plant receptor kinases such as the phytosulfokine receptor, where a functional GC essential for downstream signaling is embedded within a kinase domain. In vitro characterization of the NTRK1 shows that the embedded NTRK1 GC is functional with a marked preference for Mn2+ over Mg2+. This therefore points to hitherto unsuspected roles of cGMP in intramolecular and downstream signaling of NTRK1 and the role of cGMP in NTRK1-dependent growth and neoplasia.

Protein Kinase Structure and Dynamics: Role of the αC-β4 Loop

Although the αC-β4 loop is a stable feature of all protein kinases, the importance of this motif as a conserved element of secondary structure, as well as its links to the hydrophobic architecture of the kinase core, has been underappreciated. We first review the motif and then describe how it is linked to the hydrophobic spine architecture of the kinase core, which we first discovered using a computational tool, Local Spatial Pattern (LSP) alignment. Based on NMR predictions that a mutation in this motif abolishes the synergistic high-affinity binding of ATP and a pseudo substrate inhibitor, we used LSP to interrogate the F100A mutant. This comparison highlights the importance of the αC-β4 loop and key residues at the interface between the N- and C-lobes. In addition, we delved more deeply into the structure of the apo C-subunit, which lacks ATP. While apo C-subunit showed no significant changes in backbone dynamics of the αC-β4 loop, we found significant differences in the side chain dynamics of K105. The LSP analysis suggests disruption of communication between the N- and C-lobes in the F100A mutant, which would be consistent with the structural changes predicted by the NMR spectroscopy.

Cooperative regulation of C1-domain membrane recruitment polarizes atypical protein kinase C

Recruitment of the Par complex protein atypical protein kinase C (aPKC) to a specific membrane domain is a key step in the polarization of animal cells. While numerous proteins and phospholipids interact with aPKC, how these interactions cooperate to control its membrane recruitment has been unknown. Here, we identify aPKC's C1 domain as a phospholipid interaction module that targets aPKC to the membrane of Drosophila neural stem cells (NSCs). The isolated C1 binds the NSC membrane in an unpolarized manner during interphase and mitosis and is uniquely sufficient among aPKC domains for targeting. Other domains, including the catalytic module and those that bind the upstream regulators Par-6 and Bazooka, restrict C1's membrane targeting activity-spatially and temporally-to the apical NSC membrane during mitosis. Our results suggest that aPKC polarity results from cooperative activation of autoinhibited C1-mediated membrane binding activity.

Allostery in Protein Tyrosine Phosphatases is Enabled by Divergent Dynamics

Dynamics-driven allostery provides important insights into the working mechanics of proteins, especially enzymes. In this study we employ this paradigm to answer a basic question: in enzyme superfamilies where the catalytic mechanism, active sites and protein fold are conserved, what accounts for the difference in the catalytic prowess of the individual members? We show that when subtle changes in sequence do not translate to changes in structure, they do translate to changes in dynamics. We use sequentially diverse PTP1B, TbPTP1, and YopH as the representatives of the conserved Protein Tyrosine Phosphatase (PTP) superfamily. Using amino acid network analysis of group behavior (community analysis) and influential node dominance on networks (eigenvector centrality), we explain the dynamic basis of catalytic variations seen between the three proteins. Importantly, we explain how a dynamics-based blueprint makes PTP1B amenable to allosteric control and how the same is abstracted in TbPTP1 and YopH.

Allostery Frustrates the Experimentalist

Proteins interact with other proteins, with nucleic acids, lipids, carbohydrates and various small molecules in the living cell. These interactions have been quantified and structurally characterized in numerous studies such that we today have a comprehensive picture of protein structure and function. However, proteins are dynamic and even folded proteins are likely more heterogeneous than they appear in most descriptions. One property of proteins that relies on dynamics and heterogeneity is allostery, the ability of a protein to change structure and function upon ligand binding to an allosteric site. Over the last decades the concept of allostery was broadened to embrace all types of long-range interactions across a protein including purely entropic changes without a conformational change in single protein domains. But with this re-definition came a problem: How do we measure allostery? In this opinion, we discuss some caveats arising from the quantitative description of single-domain allostery from an experimental perspective and how the limitations cannot be separated from the definition of allostery per se. Furthermore, we attempt to tie together allostery with the concept of frustration in an effort to investigate the links between these two complex, and yet general, properties of proteins. We arrive at the conclusion that the sensitivity to perturbation of allosteric networks in single protein domains is too large for the networks to be of significant biological relevance.

The "violin model": Looking at community networks for dynamic allostery

Allosteric regulation of proteins continues to be an engaging research topic for the scientific community. Models describing allosteric communication have evolved from focusing on conformation-based descriptors of protein structural changes to appreciating the role of internal protein dynamics as a mediator of allostery. Here, we explain a "violin model" for allostery as a contemporary method for approaching the Cooper-Dryden model based on redistribution of protein thermal fluctuations. Based on graph theory, the violin model makes use of community network analysis to functionally cluster correlated protein motions obtained from molecular dynamics simulations. This Review provides the theory and workflow of the methodology and explains the application of violin model to unravel the workings of protein kinase A.

DYRK1A Inhibitors and Perspectives for the Treatment of Alzheimer's Disease

BACKGROUND

Alzheimer's disease (AD) is a chronic neurodegenerative disease and the most common form of dementia, especially in the elderly. Due to the increase in life expectancy, in recent years, there has been an excessive growth in the number of people affected by this disease, causing serious problems for health systems. In recent years, research has been intensified to find new therapeutic approaches that prevent the progression of the disease. In this sense, recent studies indicate that the dual-specificity tyrosine phosphorylation regulated kinase 1A (DYRK1A) gene, which is located on chromosome 21q22.2 and overexpressed in Down syndrome (DS), may play a significant role in developmental brain disorders and early onset neurodegeneration, neuronal loss and dementia in DS and AD. Inhibiting DYRK1A may serve to stop the phenotypic effects of its overexpression and, therefore, is a potential treatment strategy for the prevention of ageassociated neurodegeneration, including Alzheimer-type pathology.

OBJECTIVE

In this review, we investigate the contribution of DYRK1A inhibitors as potential anti-AD agents.

METHODS

A search in the literature to compile an in vitro dataset including IC50 values involving DYRK1A was performed from 2014 to the present day. In addition, we carried out structure-activity relationship studies based on in vitro and in silico data.

RESULTS

molecular modeling and enzyme kinetics studies indicate that DYRK1A may contribute to AD pathology through its proteolytic process, reducing its kinase specificity.

CONCLUSION

further evaluation of DYRK1A inhibitors may contribute to new therapeutic approaches for AD.

Characterisation of sequence-structure-function space in sensor-effector integrators of phytochrome-regulated diguanylate cyclases

Understanding the relationship between protein sequence, structure and function is one of the fundamental challenges in biochemistry. A direct correlation, however, is often not trivial since protein dynamics also play an important functional role-especially in signal transduction processes. In a subfamily of bacterial light sensors, phytochrome-activated diguanylate cyclases (PadCs), a characteristic coiled-coil linker element connects photoreceptor and output module, playing an essential role in signal integration. Combining phylogenetic analyses with biochemical characterisations, we were able to show that length and composition of this linker determine sensor-effector function and as such are under considerable evolutionary pressure. The linker length, together with the upstream PHY-specific domain, influences the dynamic range of effector activation and can even cause light-induced enzyme inhibition. We demonstrate phylogenetic clustering according to linker length, and the development of new linker lengths as well as new protein function within linker families. The biochemical characterisation of PadC homologs revealed that the functional coupling of PHY dimer interface and linker element defines signal integration and regulation of output functionality. A small subfamily of PadCs, characterised by a linker length breaking the coiled-coil pattern, shows a markedly different behaviour from other homologs. The effect of the central helical spine on PadC function highlights its essential role in signal integration as well as direct regulation of diguanylate cyclase activity. Appreciation of sensor-effector linkers as integrator elements and their coevolution with sensory modules is a further step towards the use of functionally diverse homologs as building blocks for rationally designed optogenetic tools.

Divergent kinase WNG1 is regulated by phosphorylation of an atypical activation sub-domain

Apicomplexan parasites like Toxoplasma gondii grow and replicate within a specialized organelle called the parasitophorous vacuole. The vacuole is decorated with parasite proteins that integrate into the membrane after trafficking through the parasite secretory system as soluble, chaperoned complexes. A regulator of this process is an atypical protein kinase called WNG1. Phosphorylation by WNG1 appears to serve as a switch for membrane integration. However, like its substrates, WNG1 is secreted from the parasite dense granules, and its activity must, therefore, be tightly regulated until the correct membrane is encountered. Here, we demonstrate that, while another member of the WNG family can adopt multiple multimeric states, WNG1 is monomeric and therefore not regulated by multimerization. Instead, we identify two phosphosites on WNG1 that are required for its kinase activity. Using a combination of in vitro biochemistry and structural modeling, we identify basic residues that are also required for WNG1 activity and appear to recognize the activating phosphosites. Among these coordinating residues are the 'HRD' Arg, which recognizes activation loop phosphorylation in canonical kinases. WNG1, however, is not phosphorylated on its activation loop, but rather on atypical phosphosites on its C-lobe. We propose a simple model in which WNG1 is activated by increasing ATP concentration above a critical threshold once the kinase traffics to the parasitophorous vacuole.

Quantitative Analysis of Dynamic Allostery

Dynamic allostery refers to one important class of allosteric regulation that does not involve noticeable conformational changes upon effector binding. In recent years, many "quasi"-dynamic allosteric proteins have been found to only experience subtle conformational changes during allosteric regulation. However, as enthalpic and entropic contributions are coupled to each other and even tiny conformational changes could bring in noticeable free energy changes, a quantitative description is essential to understand the contribution of pure dynamic allostery. Here, by developing a unified anisotropic elastic network model (uANM) considering both side-chain information and ligand heavy atoms, we quantitatively estimated the contribution of pure dynamic allostery in a dataset of known allosteric proteins by excluding the conformational changes upon ligand binding. We found that the contribution of pure dynamic allostery is generally small (much weaker than previously expected) and robustly exhibits an allosteric activation effect, which exponentially decays with the distance between the substrate and the allosteric ligand. We further constructed toy models to study the determinant factors of dynamic allostery in monomeric and oligomeric proteins using the uANM. Analysis of the toy models revealed that a short distance, a small angle between the two ligands, strong protein-ligand interactions, and weak protein internal interactions lead to strong dynamic allostery. Our study provides a quantitative estimation of pure dynamic allostery and facilitates the understanding of dynamic-allostery-controlled biological processes and the design of allosteric drugs and proteins.

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.

Principles of Kinase Allosteric Inhibition and Pocket Validation

With several marketed drugs, allosteric inhibition of kinases has translated to pharmacological effects and clinical benefits comparable to those from orthosteric inhibition. However, despite much effort over more than 20 years, the number of kinase targets associated with FDA-approved allosteric drugs is limited, suggesting the challenges in identifying and validating allosteric inhibitors. Here we review the principles of allosteric inhibition, summarize the discovery of allosteric MEK1/2 and BCR-ABL1 inhibitors, and discuss the approaches to screening and demonstrating the functional activity of allosteric pocket ligands.

Using Optical Tweezers to Monitor Allosteric Signals Through Changes in Folding Energy Landscapes

Signaling proteins are composed of conserved protein interaction domains that serve as allosteric regulatory elements of enzymatic or binding activities. The ubiquitous, structurally conserved cyclic nucleotide binding (CNB) domain is found covalently linked to proteins with diverse folds that perform multiple biological functions. Given that the structures of cAMP-bound CNB domains in different proteins are very similar, it remains a challenge to determine how this domain allosterically regulates such diverse protein functions and folds. Instead of a structural perspective, we focus our attention on the energy landscapes underlying the CNB domains and their responses to cAMP binding. We show that optical tweezers is an ideal tool to investigate how cAMP binding coupled to interdomain interactions remodel the energy landscape of the regulatory subunit of protein kinase A (PKA), which harbors two CNB domains. We mechanically manipulate and probe the unfolding and refolding behavior of the CNB domains as isolated structures or selectively as part of the PKA regulatory subunit, and in the presence and absence of cAMP. Optical tweezers allows us to dissect the changes in the energy landscape associated with cAMP binding, and to examine the allosteric interdomain interactions triggered by the cyclic nucleotide. This single molecule approach can be used to study other modular, multidomain signaling proteins found in nature.

Dynamic equilibria in protein kinases

Structural changes involved in protein kinase activation and ligand binding have been determined from a wealth of X-ray crystallographic evidence. Recent solution studies using NMR, EPR, HX-MS, and fluorescence techniques have deepened this understanding by highlighting the underlying energetics and dynamics of multistate conformational ensembles. This new research is showing how activation mechanisms and ligand binding alter the internal motions of kinases and enable allosteric coupling between distal regulatory regions and the active site.

The PHY Domain Dimer Interface of Bacteriophytochromes Mediates Cross-talk between Photosensory Modules and Output Domains

Protein dynamics play a major role for the catalytic function of enzymes, the interaction of protein complexes or signal integration in regulatory proteins. In the context of multi-domain proteins involved in light-regulation of enzymatic effectors, the central role of conformational dynamics is well established. Light activation of sensory modules is followed by long-range signal transduction to different effectors; rather than domino-style structural rearrangements, a complex interplay of functional elements is required to maintain functionality. One family of such sensor-effector systems are red-light-regulated phytochromes that control diguanylate cyclases involved in cyclic-dimeric-GMP formation. Based on structural and functional studies of one prototypic family member, the central role of the coiled-coil sensor-effector linker was established. Interestingly, subfamilies with different linker lengths feature strongly varying biochemical characteristics. The dynamic interplay of the domains involved, however, is presently not understood. Here we show that the PHY domain dimer interface plays an essential role in signal integration, and that a functional coupling with the coiled-coil linker element is crucial. Chimaeras of two biochemically different family members highlight the phytochrome-spanning helical spine as an essential structural element involved in light-dependent upregulation of enzymatic turnover. However, isolated structural elements can frequently not be assigned to individual characteristics, which further emphasises the importance of global conformational dynamics. Our results provide insights into the intricate processes at play during light signal integration and transduction in these photosensory systems and thus provide additional guidelines for a more directed design of novel sensor-effector combinations with potential applications as optogenetic tools.

PKA Cβ: a forgotten catalytic subunit of cAMP-dependent protein kinase opens new windows for PKA signaling and disease pathologies

3',5'-cyclic adenosine monophosphate (cAMP) dependent protein kinase or protein kinase A (PKA) has served as a prototype for the large family of protein kinases that are crucially important for signal transduction in eukaryotic cells. The PKA catalytic subunits are encoded by the two major genes PRKACA and PRKACB, respectively. The PRKACA gene encodes two known splice variants, the ubiquitously expressed Cα1 and the sperm-specifically expressed Cα2. In contrast, the PRKACB gene encodes several splice variants expressed in a highly cell and tissue-specific manner. The Cβ proteins are called Cβ1, Cβ2, Cβ3, Cβ4 and so-called abc variants of Cβ3 and Cβ4. Whereas Cβ1 is ubiquitously expressed, Cβ2 is enriched in immune cells and the Cβ3, Cβ4 and their abc variants are solely expressed in neuronal cells. All Cα and Cβ splice variants share a kinase-conserved catalytic core and a C-terminal tail encoded by exons 2 through 10 in the PRKACA and PRKACB genes, respectively. All Cα and Cβ splice variants with the exception of Cα1 and Cβ1 are hyper-variable at the N-terminus. Here, we will discuss how the PRKACA and PRKACB genes have developed as paralogs that encode distinct and functionally non-redundant proteins. The fact that Cα and Cβ splice variant mutations are associated with numerous diseases further opens new windows for PKA-induced disease pathologies.

Single Residue on the WPD-Loop Affects the pH Dependency of Catalysis in Protein Tyrosine Phosphatases

Catalysis by protein tyrosine phosphatases (PTPs) relies on the motion of a flexible protein loop (the WPD-loop) that carries a residue acting as a general acid/base catalyst during the PTP-catalyzed reaction. The orthogonal substitutions of a noncatalytic residue in the WPD-loops of YopH and PTP1B result in shifted pH-rate profiles from an altered kinetic pK a of the nucleophilic cysteine. Compared to wild type, the G352T YopH variant has a broadened pH-rate profile, similar activity at optimal pH, but significantly higher activity at low pH. Changes in the corresponding PTP1B T177G variant are more modest and in the opposite direction, with a narrowed pH profile and less activity in the most acidic range. Crystal structures of the variants show no structural perturbations but suggest an increased preference for the WPD-loop-closed conformation. Computational analysis confirms a shift in loop conformational equilibrium in favor of the closed conformation, arising from a combination of increased stability of the closed state and destabilization of the loop-open state. Simulations identify the origins of this population shift, revealing differences in the flexibility of the WPD-loop and neighboring regions. Our results demonstrate that changes to the pH dependency of catalysis by PTPs can result from small changes in amino acid composition in their WPD-loops affecting only loop dynamics and conformational equilibrium. The perturbation of kinetic pK a values of catalytic residues by nonchemical processes affords a means for nature to alter an enzyme's pH dependency by a less disruptive path than altering electrostatic networks around catalytic residues themselves.

Moonlighting Proteins Shine New Light on Molecular Signaling Niches

Plants as sessile organisms face daily environmental challenges and have developed highly nuanced signaling systems to enable suitable growth, development, defense, or stalling responses. Moonlighting proteins have multiple tasks and contribute to cellular signaling cascades where they produce additional variables adding to the complexity or fuzziness of biological systems. Here we examine roles of moonlighting kinases that also generate 3',5'-cyclic guanosine monophosphate (cGMP) in plants. These proteins include receptor like kinases and lipid kinases. Their guanylate cyclase activity potentiates the development of localized cGMP-enriched nanodomains or niches surrounding the kinase and its interactome. These nanodomains contribute to allosteric regulation of kinase and other molecules in the immediate complex directly or indirectly modulating signal cascades. Effects include downregulation of kinase activity, modulation of other members of the protein complexes such as cyclic nucleotide gated channels and potential triggering of cGMP-dependent degradation cascades terminating signaling. The additional layers of information provided by the moonlighting kinases are discussed in terms of how they may be used to provide a layer of fuzziness to effectively modulate cellular signaling cascades.

How fast are the motions of tertiary-structure elements in proteins?

Protein motions occur on multiple time and distance scales. Large-scale motions of protein tertiary-structure elements, i.e., domains, are particularly intriguing as they are essential for the catalytic activity of many enzymes and for the functional cycles of protein machines and motors. Theoretical estimates suggest that domain motions should be very fast, occurring on the nanosecond or microsecond time scales. Indeed, free-energy barriers for domain motions are likely to involve salt bridges, which can break in microseconds. Experimental methods that can directly probe domain motions on fast time scales have appeared only in recent years. This Perspective discusses briefly some of these techniques, including nuclear magnetic resonance and single-molecule fluorescence spectroscopies. We introduce a few recent studies that demonstrate ultrafast domain motions and discuss their potential roles. Particularly surprising is the observation of tertiary-structure element dynamics that are much faster than the functional cycles in some protein machines. These swift motions can be rationalized on a case-by-case basis. For example, fast domain closure in multi-substrate enzymes may be utilized to optimize relative substrate orientation. Whether a large mismatch in time scales of conformational dynamics vs functional cycles is a general design principle in proteins remains to be determined.

A pan-cancer assessment of alterations of the kinase domain of ULK1, an upstream regulator of autophagy

Autophagy is a key clearance process to recycle damaged cellular components. One important upstream regulator of autophagy is ULK1 kinase. Several three-dimensional structures of the ULK1 catalytic domain are available, but a comprehensive study, including molecular dynamics, is missing. Also, an exhaustive description of ULK1 alterations found in cancer samples is presently lacking. We here applied a framework which links -omics data to structural protein ensembles to study ULK1 alterations from genomics data available for more than 30 cancer types. We predicted the effects of mutations on ULK1 function and structural stability, accounting for protein dynamics, and the different layers of changes that a mutation can induce in a protein at the functional and structural level. ULK1 is down-regulated in gynecological tumors. In other cancer types, ULK2 could compensate for ULK1 downregulation and, in the majority of the cases, no marked changes in expression have been found. 36 missense mutations of ULK1, not limited to the catalytic domain, are co-occurring with mutations in a large number of ULK1 interactors or substrates, suggesting a pronounced effect of the upstream steps of autophagy in many cancer types. Moreover, our results pinpoint that more than 50% of the mutations in the kinase domain of ULK1, here investigated, are predicted to affect protein stability. Three mutations (S184F, D102N, and A28V) are predicted with only impact on kinase activity, either modifying the functional dynamics or the capability to exert effects from distal sites to the functional and catalytic regions. The framework here applied could be extended to other protein targets to aid the classification of missense mutations from cancer genomics studies, as well as to prioritize variants for experimental validation, or to select the appropriate biological readouts for experiments.

Use of Molecular Dynamics Simulations in Structure-Based Drug Discovery

BACKGROUND

Traditional drug discovery is a lengthy process which involves a huge amount of resources. Modern-day drug discovers various multidisciplinary approaches amongst which, computational ligand and structure-based drug designing methods contribute significantly. Structure-based drug designing techniques require the knowledge of structural information of drug target and drug-target complexes. Proper understanding of drug-target binding requires the flexibility of both ligand and receptor to be incorporated. Molecular docking refers to the static picture of the drug-target complex(es). Molecular dynamics, on the other hand, introduces flexibility to understand the drug binding process.

OBJECTIVE

The aim of the present study is to provide a systematic review on the usage of molecular dynamics simulations to aid the process of structure-based drug design.

METHOD

This review discussed findings from various research articles and review papers on the use of molecular dynamics in drug discovery. All efforts highlight the practical grounds for which molecular dynamics simulations are used in drug designing program. In summary, various aspects of the use of molecular dynamics simulations that underline the basis of studying drug-target complexes were thoroughly explained.

RESULTS

This review is the result of reviewing more than a hundred papers. It summarizes various problems that use molecular dynamics simulations.

CONCLUSION

The findings of this review highlight how molecular dynamics simulations have been successfully implemented to study the structure-function details of specific drug-target complexes. It also identifies the key areas such as stability of drug-target complexes, ligand binding kinetics and identification of allosteric sites which have been elucidated using molecular dynamics simulations.

Mitochondrial Homeostasis and Signaling in Parkinson's Disease

The loss of dopaminergic (DA) neurons in the substantia nigra leads to a progressive, long-term decline of movement and other non-motor deficits. The symptoms of Parkinson’s disease (PD) often appear later in the course of the disease, when most of the functional dopaminergic neurons have been lost. The late onset of the disease, the severity of the illness, and its impact on the global health system demand earlier diagnosis and better targeted therapy. PD etiology and pathogenesis are largely unknown. There are mutations in genes that have been linked to PD and, from these complex phenotypes, mitochondrial dysfunction emerged as central in the pathogenesis and evolution of PD. In fact, several PD-associated genes negatively impact on mitochondria physiology, supporting the notion that dysregulation of mitochondrial signaling and homeostasis is pathogenically relevant. Derangement of mitochondrial homeostatic controls can lead to oxidative stress and neuronal cell death. Restoring deranged signaling cascades to and from mitochondria in PD neurons may then represent a viable opportunity to reset energy metabolism and delay the death of dopaminergic neurons. Here, we will highlight the relevance of dysfunctional mitochondrial homeostasis and signaling in PD, the molecular mechanisms involved, and potential therapeutic approaches to restore mitochondrial activities in damaged neurons.

Both intra and inter-domain interactions define the intrinsic dynamics and allosteric mechanism in DNMT1s

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Dynamics and allosteric potentials of the RFTS domain are proposed.

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Hinge sites located at the RFTS-CD interface are key regulators for inter-domain interactions.

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Network analysis reveals local allosteric networks and inter-domain communication pathways in DNMT1.

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A potential allosteric site at the TRD interface for DNMT1 is identified.

DNA methyltransferase 1 (DNMT1), a large multidomain enzyme, is believed to be involved in the passive transmission of genomic methylation patterns via methylation maintenance. Yet, the molecular mechanism of interaction networks underlying DNMT1 structures, dynamics, and its biological significance has yet to be fully characterized. In this work, we used an integrated computational strategy that combined coarse-grained and atomistic simulations with coevolution information and network modeling of the residue interactions for the systematic investigation of allosteric dynamics in DNMT1. The elastic network modeling has proposed that the high plasticity of RFTS has strengthened the correlated behaviors of DNMT1 structures through the hinge sites located at the RFTS-CD interface, which mediate the collective motions between domains. The perturbation response scanning (PRS) analysis combined with the enrichment analysis of disease mutations have further highlighted the allosteric potential of the RFTS domain. Furthermore, the long-range paths connect the intra-domain interactions through the TRD interface and catalytic interface, emphasizing some key inter-domain interactions as the bridges in the global allosteric regulation of DNMT1. The observed interplay between conserved intra-domain networks and dynamical plasticity encoded by inter-domain interactions provides insights into the intrinsic dynamics and functional evolution, as well as the design of allosteric modulators of DNMT1 based on the TRD interface.

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.

Structural and molecular bases of angiotensin-converting enzyme inhibition by bovine casein-derived peptides: an in silico molecular dynamics approach

The angiotensin-converting enzyme (ACE) plays a key role in blood pressure regulation process, and its inhibition is one of the main drug targets for the treatment of hypertension. Though various peptides from milk proteins are well-known for their ACE-inhibitory capacity, research devoted to understand the molecular bases of such property remain scarce, specifically for such peptides. Therefore, in this work, computational molecular docking and molecular dynamics calculations were performed to enlighten the intermolecular interactions involved in ACE inhibition by six different casein-derived peptides (FFVAPFPEVFGK, FALPQYLK, ALNEINQFYQK, YLGYLEQLLR, HQGLPQEVLNENLLR and NAVPITPTLNR). Two top ranked docking poses for each peptide (one with N- and the other C-terminal peptide extremity oriented towards the ACE active site) were selected for dynamic simulations (50 ns; GROMOS53A6 force field), and the results were correlated to in vitro ACE inhibition capacity. Two molecular features appeared to be essential for peptides to present high ACE inhibition capacity in vitro: i) to interact with the S1 active site residues (Ala354, Glu384, and Tyr523) by hydrogen bonds; ii) to interact with Zn²⁺ coordinated residues (His383, His387, and Glu411) by short-lenght hydrogen bonds, as observed in the cases of ALNEINQFYQK (IACE = 80.7%), NAVPITPTLNR (IACE = 80.7%), and FALPQYLK (IACE = 79.0%). Regardless of the temporal stability of these strong interactions, they promoted some disruption of Zn²⁺ tetrahedral coordination during the molecular dynamics trajectories, and were pointed as the main reason for the greatest ACE inhibition by these peptides. On the other hand, peptides with intermediate inhibition capacity (50% < I_ACE < 45%) interacted mainly by weaker interactions (e.g.: electrostatic and hydrophobic) with the Zn²⁺ coordinated residues, and were not able to change significantly its tetrahedral coordination structure. These findings may: i) assist the discrimination in silico of "good" and "bad" ACE-inhibitory peptides from other food sources, and/or ii) aid in designing de novo new molecules with ACE-inhibitory capacity. Communicated by Ramaswamy Sarma.

Single-molecule FRET methods to study the dynamics of proteins at work

Feynman commented that "Everything that living things do can be understood in terms of the jiggling and wiggling of atoms". Proteins can jiggle and wiggle large structural elements such as domains and subunits as part of their functional cycles. Single-molecule fluorescence resonance energy transfer (smFRET) is an excellent tool to study conformational dynamics and decipher coordinated large-scale motions within proteins. smFRET methods introduced in recent years are geared toward understanding the time scales and amplitudes of function-related motions. This review discusses the methodology for obtaining and analyzing smFRET temporal trajectories that provide direct dynamic information on transitions between conformational states. It also introduces correlation methods that are useful for characterizing intramolecular motions. This arsenal of techniques has been used to study multiple molecular systems, from membrane proteins through molecular chaperones, and we examine some of these studies here. Recent exciting methodological novelties permit revealing very fast, submillisecond dynamics, whose relevance to protein function is yet to be fully grasped.

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

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

Dynamic regulatory features of the protein tyrosine kinases

The SRC, Abelson murine leukemia viral oncogene homolog 1, TEC and C-terminal SRC Kinase families of non-receptor tyrosine kinases (collectively the Src module kinases) mediate an array of cellular signaling processes and are therapeutic targets in many disease states. Crystal structures of Src modules kinases provide valuable insights into the regulatory mechanisms that control activation and generate a framework from which drug discovery can advance. The conformational ensembles visited by these multidomain kinases in solution are also key features of the regulatory machinery controlling catalytic activity. Measurement of dynamic motions within kinases substantially augments information derived from crystal structures. In this review, we focus on a body of work that has transformed our understanding of non-receptor tyrosine kinase regulation from a static view to one that incorporates how fluctuations in conformational ensembles and dynamic motions influence activation status. Regulatory dynamic networks are often shared across and between kinase families while specific dynamic behavior distinguishes unique regulatory mechanisms for select kinases. Moreover, intrinsically dynamic regions of kinases likely play important regulatory roles that have only been partially explored. Since there is clear precedence that kinase inhibitors can exploit specific dynamic features, continued efforts to define conformational ensembles and dynamic allostery will be key to combating drug resistance and devising alternate treatments for kinase-associated diseases.

Dynamic allostery-based molecular workings of kinase:peptide complexes

A dense interplay between structure and dynamics underlies the working of proteins, especially enzymes. Protein kinases are molecular switches that are optimized for their regulation rather than catalytic turnover rates. Using long-simulations dynamic allostery analysis, this study describes an exploration of the dynamic kinase:peptide complex. We have used protein kinase A (PKA) as a model system as a generic prototype of the protein kinase superfamily of signaling enzymes. Our results explain the role of dynamic coupling of active-site residues that must work in coherence to provide for a successful activation or inhibition response from the kinase. Amino acid networks-based community analysis allows us to ponder the conformational entropy of the kinase:nucleotide:peptide ternary complex. We use a combination of 7 peptides that include 3 types of PKA-binding partners: Substrates, products, and inhibitors. The substrate peptides provide for dynamic insights into the enzyme:substrate complex, while the product phospho-peptide allows for accessing modes of enzyme:product release. Mapping of allosteric communities onto the PKA structure allows us to locate the more unvarying and flexible dynamic regions of the kinase. These distributions, when correlated with the structural elements of the kinase core, allow for a detailed exploration of key dynamics-based signatures that could affect peptide recognition and binding at the kinase active site. These studies provide a unique dynamic allostery-based perspective to kinase:peptide complexes that have previously been explored only in a structural or thermodynamic context.