Folding funnels and conformational transitions via hinge-bending motions

Metastable States in the Hinge-Bending Landscape of an Enzyme in an Atomistic Cytoplasm Simulation

Many enzymes undergo major conformational changes to function in cells, particularly when they bind to more than one substrate. We quantify the large-amplitude hinge-bending landscape of human phosphoglycerate kinase (PGK) in a human cytoplasm. Approximately 70 μs of all-atom simulations, upon coarse graining, reveal three metastable states of PGK with different hinge angle distributions and additional substates. The "open" state was more populated than the "semi-open" or "closed" states. In addition to free energies and barriers within the landscape, we characterized the average transition state passage time of ≈0.3 μs and reversible substrate and product binding. Human PGK in a dilute solution simulation shows a transition directly from the open to closed states, in agreement with previous SAXS experiments, suggesting that the cell-like model environment promotes stability of the human PGK semi-open state. Yeast PGK also sampled three metastable states within the cytoplasm model, with the closed state favored in our simulation.

Regulation of phosphoglycerate kinase 1 and its critical role in cancer

Cells that undergo normal differentiation mainly rely on mitochondrial oxidative phosphorylation to provide energy, but most tumour cells rely on aerobic glycolysis. This phenomenon is called the "Warburg effect". Phosphoglycerate kinase 1 (PGK1) is a key enzyme in aerobic glycolysis. PGK1 is involved in glucose metabolism as well as a variety of biological activities, including angiogenesis, EMT, mediated autophagy initiation, mitochondrial metabolism, DNA replication and repair, and other processes related to tumorigenesis and development. Recently, an increasing number of studies have proven that PGK1 plays an important role in cancer. In this manuscript, we discussed the effects of the structure, function, molecular mechanisms underlying PGK1 regulation on the initiation and progression of cancer. Additionally, PGK1 is associated with chemotherapy resistance and prognosis in tumour patients. This review presents an overview of the different roles played by PGK1 during tumorigenesis, which will help in the design of experimental studies involving PGK1 and enhance the potential for the use of PGK1 as a therapeutic target in cancer. Video Abstract.

Worth the Weight: Sub-Pocket EXplorer (SubPEx), a Weighted Ensemble Method to Enhance Binding-Pocket Conformational Sampling

Structure-based virtual screening (VS) is an effective method for identifying potential small-molecule ligands, but traditional VS approaches consider only a single binding-pocket conformation. Consequently, they struggle to identify ligands that bind to alternate conformations. Ensemble docking helps address this issue by incorporating multiple conformations into the docking process, but it depends on methods that can thoroughly explore pocket flexibility. We here introduce Sub-Pocket EXplorer (SubPEx), an approach that uses weighted ensemble (WE) path sampling to accelerate binding-pocket sampling. As proof of principle, we apply SubPEx to three proteins relevant to drug discovery: heat shock protein 90, influenza neuraminidase, and yeast hexokinase 2. SubPEx is available free of charge without registration under the terms of the open-source MIT license: http://durrantlab.com/subpex/.

Worth the weight: Sub-Pocket EXplorer (SubPEx), a weighted-ensemble method to enhance binding-pocket conformational sampling

Structure-based virtual screening (VS) is an effective method for identifying potential small-molecule ligands, but traditional VS approaches consider only a single binding-pocket conformation. Consequently, they struggle to identify ligands that bind to alternate conformations. Ensemble docking helps address this issue by incorporating multiple conformations into the docking process, but it depends on methods that can thoroughly explore pocket flexibility. We here introduce Sub-Pocket EXplorer (SubPEx), an approach that uses weighted ensemble (WE) path sampling to accelerate binding-pocket sampling. As proof of principle, we apply SubPEx to three proteins relevant to drug discovery: heat shock protein 90, influenza neuraminidase, and yeast hexokinase 2. SubPEx is available free of charge without registration under the terms of the open-source MIT license: http://durrantlab.com/subpex/.

MCL-1 promiscuity and the structural resilience of its binding partners

The allosteric protein MCL-1 and its natural inhibitors, the BH3-only proteins PUMA, BIM, and NOXA regulate apoptosis by interacting promiscuously within an entangled binding network. Little is known about the transient processes and dynamic conformational fluctuations that are the basis for the formation and stability of the MCL-1/BH3-only complex. In this study, we designed photoswitchable versions of MCL-1/PUMA and MCL-1/NOXA, and investigated the protein response after an ultrafast photo-perturbation with transient infrared spectroscopy. We observed partial α-helical unfolding in all cases, albeit on strongly varying timescales (1.6 ns for PUMA, 9.7 ns for the previously studied BIM, and 85 ns for NOXA). These differences are interpreted as a BH3-only-specific "structural resilience" to defy the perturbation while remaining in MCL-1's binding pocket. Thus, the presented insights could help to better understand the differences between PUMA, BIM, and NOXA, the promiscuity of MCL-1, in general, and the role of the proteins in the apoptotic network.

Accessing Transient Binding Pockets by Protein Engineering and Yeast Surface Display Screening

The binding pocket of some therapeutic targets can acquire multiple conformations that, to some extent, depend on the protein dynamics and the interaction with other molecules. The inability to reach the binding pocket can impose a substantial or even insurmountable barrier for the de novo identification or optimization of small-molecule ligands. Herein, we describe a protocol for the engineering of a target protein and a yeast display FACS sorting strategy to identify protein variants with a stable transient binding pocket with improved binding for a cryptic site-specific ligand. This strategy may facilitate drug discovery using the resulting protein variants with accessible binding pockets for ligand screening.

Allostery: Allosteric Cancer Drivers and Innovative Allosteric Drugs

Here, we discuss the principles of allosteric activating mutations, propagation downstream of the signals that they prompt, and allosteric drugs, with examples from the Ras signaling network. We focus on Abl kinase where mutations shift the landscape toward the active, imatinib binding-incompetent conformation, likely resulting in the high affinity ATP outcompeting drug binding. Recent pharmacological innovation extends to allosteric inhibitor (GNF-5)-linked PROTAC, targeting Bcr-Abl1 myristoylation site, and broadly, allosteric heterobifunctional degraders that destroy targets, rather than inhibiting them. Designed chemical linkers in bifunctional degraders can connect the allosteric ligand that binds the target protein and the E3 ubiquitin ligase warhead anchor. The physical properties and favored conformational state of the engineered linker can precisely coordinate the distance and orientation between the target and the recruited E3. Allosteric PROTACs, noncompetitive molecular glues, and bitopic ligands, with covalent links of allosteric ligands and orthosteric warheads, increase the effective local concentration of productively oriented and placed ligands. Through covalent chemical or peptide linkers, allosteric drugs can collaborate with competitive drugs, degrader anchors, or other molecules of choice, driving innovative drug discovery.

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.

Low-energy electron holography imaging of conformational variability of single-antibody molecules from electrospray ion beam deposition

Molecular imaging at the single-molecule level of large and flexible proteins such as monoclonal IgG antibodies is possible by low-energy electron holography after chemically selective sample preparation by native electrospray ion beam deposition (ES-IBD) from native solution conditions. The single-molecule nature of the measurement allows the mapping of the structural variability of the molecules that originates from their intrinsic flexibility and from different adsorption geometries. Additionally, we can distinguish gas-phase–related conformations and conformations induced by the landing of the molecules on the surface. Our results underpin the relation between the gas-phase structure of protein ions created by native electrospray ionization (ESI) and the native protein structure and are of relevance for structural biology applications in the gas phase.

Imaging of proteins at the single-molecule level can reveal conformational variability, which is essential for the understanding of biomolecules. To this end, a biologically relevant state of the sample must be retained during both sample preparation and imaging. Native electrospray ionization (ESI) can transfer even the largest protein complexes into the gas phase while preserving their stoichiometry and overall shape. High-resolution imaging of protein structures following native ESI is thus of fundamental interest for establishing the relation between gas phase and solution structure. Taking advantage of low-energy electron holography’s (LEEH) unique capability of imaging individual proteins with subnanometer resolution, we investigate the conformational flexibility of Herceptin, a monoclonal IgG antibody, deposited by native electrospray mass-selected ion beam deposition (ES-IBD) on graphene. Images reconstructed from holograms reveal a large variety of conformers. Some of these conformations can be mapped to the crystallographic structure of IgG, while others suggest that a compact, gas-phase–related conformation, adopted by the molecules during ES-IBD, is retained. We can steer the ratio of those two types of conformations by changing the landing energy of the protein on the single-layer graphene surface. Overall, we show that LEEH can elucidate the conformational heterogeneity of inherently flexible proteins, exemplified here by IgG antibodies, and thereby distinguish gas-phase collapse from rearrangement on surfaces.

Hidden allosteric sites and De-Novo drug design

INTRODUCTION

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

AREAS COVERED

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

EXPERT OPINION

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

Intrinsically disordered proteins: Chronology of a discovery

Intrinsic disorder is a new reality that appears to penetrate every corner of modern protein science. It is difficult to imagine that only 20 years ago the situation was completely different, and almost nobody had heard about 'structure-less' but functional proteins. As a matter of fact, for many at that time, this idea was completely heretical when viewed in light of the then dominating lock-and-key model describing the protein structure-function relationship, where a unique amino acid sequence defines a unique crystal-like 3D structure that serves as a prerequisite for a unique function of a protein. It seems like the entire field of protein intrinsic disorder has magically emerged at the turn of the century due to a revelation to a small group of researchers. Although this may very well be true, literature shows that the first observations contradicting the lock-and-key view of protein functionality started to appear almost immediately after this model was proposed. The goal of this article is to provide a brief chronology (though admittedly a subjective one) of the events in the field of protein science that eventually culminated in the discovery of the protein intrinsic disorder phenomenon. The entire process represents a good example of the "dwarf standing on the shoulders of giants" (Latin: nanos gigantum humeris insidentes) metaphor, where the truth is discovered by building on previous discoveries.

Engineering an Allosteric Control of Protein Function

Allosteric regulation in proteins is fundamental to many important biological processes. Allostery has been employed to control protein functions by regulating protein activity. Engineered allosteric regulation allows controlling protein activity in subsecond time scale and has a broad range of applications, from dissecting spatiotemporal dynamics in biochemical cascades to applications in biotechnology and medicine. Here, we review the concept of allostery in proteins and various approaches to identify allosteric sites and pathways. We then provide an overview of strategies and tools used in allosteric protein regulation and their utility in biological applications. We highlight various classes of proteins, where regulation is achieved through allostery. Finally, we analyze the current problems, critical challenges, and future prospective in achieving allosteric regulation in proteins.

Allosteric Priming of E. coli CheY by the Flagellar Motor Protein FliM

Phosphorylation of Escherichia coli CheY protein transduces chemoreceptor stimulation to a highly cooperative flagellar motor response. CheY binds to the N-terminal peptide of the FliM motor protein (FliM_N). Constitutively active D13K-Y106W CheY has been an important tool for motor physiology. The crystal structures of CheY and CheY ⋅ FliM_N with and without D13K-Y106W have shown FliM_N-bound CheY contains features of both active and inactive states. We used molecular dynamics (MD) simulations to characterize the CheY conformational landscape accessed by FliM_N and D13K-Y106W. Mutual information measures identified the central features of the long-range CheY allosteric network between D57 phosphorylation site and the FliM_N interface, namely the closure of the α4-β4 hinge and inward rotation of Y- or W106 with W58. We used hydroxy-radical foot printing with mass spectroscopy (XFMS) to track the solvent accessibility of these and other side chains. The solution XFMS oxidation rate correlated with the solvent-accessible area of the crystal structures. The protection of allosteric relay side chains reported by XFMS confirmed the intermediate conformation of the native CheY ⋅ FliM_N complex, the inactive state of free D13K-Y106W CheY, and the MD-based network architecture. We extended the MD analysis to determine temporal coupling and energetics during activation. Coupled aromatic residue rotation was a graded rather than a binary switch, with Y- or W106 side-chain burial correlated with increased FliM_N affinity. Activation entrained CheY fold stabilization to FliM_N affinity. The CheY network could be partitioned into four dynamically coordinated sectors. Residue substitutions mapped to sectors around D57 or the FliM_N interface according to phenotype. FliM_N increased sector size and interactions. These sectors fused between the substituted K13-W106 residues to organize a tightly packed core and novel surfaces that may bind additional sites to explain the cooperative motor response. The community maps provide a more complete description of CheY priming than proposed thus far.

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

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

Ligand-Binding-Site Structure Shapes Allosteric Signal Transduction and the Evolution of Allostery in Protein Complexes

The structure of ligand-binding sites has been shown to profoundly influence the evolution of function in homomeric protein complexes. Complexes with multichain binding sites (MBSs) have more conserved quaternary structure, more similar binding sites and ligands between homologs, and evolve new functions slower than homomers with single-chain binding sites (SBSs). Here, using in silico analyses of protein dynamics, we investigate whether ligand-binding-site structure shapes allosteric signal transduction pathways, and whether the structural similarity of binding sites influences the evolution of allostery. Our analyses show that: 1) allostery is more frequent among MBS complexes than in SBS complexes, particularly in homomers; 2) in MBS homomers, semirigid communities and critical residues frequently connect interfaces and thus they are characterized by signal transduction pathways that cross protein-protein interfaces, whereas SBS homomers usually not; 3) ligand binding alters community structure differently in MBS and SBS homomers; and 4) except MBS homomers, allosteric proteins are more likely to have homologs with similar binding site than nonallosteric proteins, suggesting that binding site similarity is an important factor driving the evolution of allostery.

Dissecting a novel allosteric mechanism of cruzain: A computer-aided approach

Trypanosoma cruzi is the causative agent of Chagas disease, a neglected infection affecting millions of people in tropical regions. There are several chemotherapeutic agents for the treatment of this disease, but most of them are highly toxic and generate resistance. Currently, the development of allosteric inhibitors constitutes a promising research field, since it can improve the accessibility to more selective and less toxic medicines. To date, the allosteric drugs prediction is a state-of-the-art topic in rational structure-based computational design. In this work, a simulation strategy was developed for computational discovery of allosteric inhibitors, and it was applied to cruzain, a promising target and the major cysteine protease of T. cruzi. Molecular dynamics simulations, binding free energy calculations and network-based modelling of residue interactions were combined to characterize and compare molecular distinctive features of the apo form and the cruzain-allosteric inhibitor complexes. By using geometry-based criteria on trajectory snapshots, we predicted two main allosteric sites suitable for drug targeting. The results suggest dissimilar mechanisms exerted by the same allosteric site when binding different potential allosteric inhibitors. Finally, we identified the residues involved in suboptimal paths linking the identified site and the orthosteric site. The present study constitutes the first approximation to the design of cruzain allosteric inhibitors and may serve for future pharmacological intervention. Here, no major effects on active site structure were observed due to compound binding (modification of distance and angles between catalytic residues), which indicates that allosteric regulation in cruzain might be mediated via alterations of its dynamical properties similarly to allosteric inhibition of human cathepsin K (HCatK). The current findings are particularly relevant for the design of allosteric modulators of papain-like cysteine proteases.

Singular value decomposition for the correlation of atomic fluctuations with arbitrary angle

Many proteins exhibit a critical property called allostery, which enables intra-molecular transmission of information between distal sites. Microscopically, allosteric response is closely related to correlated atomic fluctuations. Conventional correlation analysis correlates the atomic fluctuations at two sites by taking the dot product (DP) between the fluctuations, which accounts only for the parallel and antiparallel components. Here, we present a singular value decomposition (SVD) method that analyzes the correlation coefficient of fluctuation dynamics with an arbitrary angle between the correlated directions. In a model allosteric system, the second PDZ domain (PDZ2) in the human PTP1E protein, approximately one third of the strong correlations have near-perpendicular directions, which are underestimated in the conventional method. The discrimination becomes more prominent for residue pairs with larger separation. The results of the proposed SVD method are more consistent with the experimentally determined PDZ2 dynamics than those of conventional method. In addition, the SVD method improved the prediction accuracy of the allosteric sites in a dataset of 23 known allosteric monomer proteins. The proposed method may inspire extended investigation not only into allostery, but also into protein dynamics and drug design.

Solution NMR Spectroscopy for the Study of Enzyme Allostery

Allostery is a ubiquitous biological regulatory process in which distant binding sites within a protein or enzyme are functionally and thermodynamically coupled. Allosteric interactions play essential roles in many enzymological mechanisms, often facilitating formation of enzyme-substrate complexes and/or product release. Thus, elucidating the forces that drive allostery is critical to understanding the complex transformations of biomolecules. Currently, a number of models exist to describe allosteric behavior, taking into account energetics as well as conformational rearrangements and fluctuations. In the following Review, we discuss the use of solution NMR techniques designed to probe allosteric mechanisms in enzymes. NMR spectroscopy is unequaled in its ability to detect structural and dynamical changes in biomolecules, and the case studies presented herein demonstrate the range of insights to be gained from this valuable method. We also provide a detailed technical discussion of several specialized NMR experiments that are ideally suited for the study of enzymatic allostery.

Protein Ensembles: How Does Nature Harness Thermodynamic Fluctuations for Life? The Diverse Functional Roles of Conformational Ensembles in the Cell

All soluble proteins populate conformational ensembles that together constitute the native state. Their fluctuations in water are intrinsic thermodynamic phenomena, and the distributions of the states on the energy landscape are determined by statistical thermodynamics; however, they are optimized to perform their biological functions. In this review we briefly describe advances in free energy landscape studies of protein conformational ensembles. Experimental (nuclear magnetic resonance, small-angle X-ray scattering, single-molecule spectroscopy, and cryo-electron microscopy) and computational (replica-exchange molecular dynamics, metadynamics, and Markov state models) approaches have made great progress in recent years. These address the challenging characterization of the highly flexible and heterogeneous protein ensembles. We focus on structural aspects of protein conformational distributions, from collective motions of single- and multi-domain proteins, intrinsically disordered proteins, to multiprotein complexes. Importantly, we highlight recent studies that illustrate functional adjustment of protein conformational ensembles in the crowded cellular environment. We center on the role of the ensemble in recognition of small- and macro-molecules (protein and RNA/DNA) and emphasize emerging concepts of protein dynamics in enzyme catalysis. Overall, protein ensembles link fundamental physicochemical principles and protein behavior and the cellular network and its regulation.

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

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

Microsecond Molecular Dynamics Simulations of Influenza Neuraminidase Suggest a Mechanism for the Increased Virulence of Stalk-Deletion Mutants

Deletions in the stalk of the influenza neuraminidase (NA) surface protein are associated with increased virulence, but the mechanisms responsible for this enhanced virulence are unclear. Here we use microsecond molecular dynamics simulations to explore the effect of stalk deletion on enzymatic activity, contrasting NA proteins from the A/swine/Shandong/N1/2009 strain both with and without a stalk deletion. By modeling and simulating neuraminidase apo glycoproteins embedded in complex-mixture lipid bilayers, we show that the geometry and dynamics of the neuraminidase enzymatic pocket may differ depending on stalk length, with possible repercussions on the binding of the endogenous sialylated-oligosaccharide receptors. We also use these simulations to predict previously unrecognized druggable “hotspots” on the neuraminidase surface that may prove useful for future efforts aimed at structure-based drug design.

Independent Evolution of Winner Traits without Whole Genome Duplication in Dekkera Yeasts

Dekkera yeasts have often been considered as alternative sources of ethanol production that could compete with S. cerevisiae. The two lineages of yeasts independently evolved traits that include high glucose and ethanol tolerance, aerobic fermentation, and a rapid ethanol fermentation rate. The Saccharomyces yeasts attained these traits mainly through whole genome duplication approximately 100 million years ago (Mya). However, the Dekkera yeasts, which were separated from S. cerevisiae approximately 200 Mya, did not undergo whole genome duplication (WGD) but still occupy a niche similar to S. cerevisiae. Upon analysis of two Dekkera yeasts and five closely related non-WGD yeasts, we found that a massive loss of cis-regulatory elements occurred in an ancestor of the Dekkera yeasts, which led to improved mitochondrial functions similar to the S. cerevisiae yeasts. The evolutionary analysis indicated that genes involved in the transcription and translation process exhibited faster evolution in the Dekkera yeasts. We detected 90 positively selected genes, suggesting that the Dekkera yeasts evolved an efficient translation system to facilitate adaptive evolution. Moreover, we identified that 12 vacuolar H+-ATPase (V-ATPase) function genes that were under positive selection, which assists in developing tolerance to high alcohol and high sugar stress. We also revealed that the enzyme PGK1 is responsible for the increased rate of glycolysis in the Dekkera yeasts. These results provide important insights to understand the independent adaptive evolution of the Dekkera yeasts and provide tools for genetic modification promoting industrial usage.

Insulin and mTOR Pathway Regulate HDAC3-Mediated Deacetylation and Activation of PGK1

Phosphoglycerate kinase 1 (PGK1) catalyzes the reversible transfer of a phosphoryl group from 1, 3-bisphosphoglycerate (1, 3-BPG) to ADP, producing 3-phosphoglycerate (3-PG) and ATP. PGK1 plays a key role in coordinating glycolytic energy production with one-carbon metabolism, serine biosynthesis, and cellular redox regulation. Here, we report that PGK1 is acetylated at lysine 220 (K220), which inhibits PGK1 activity by disrupting the binding with its substrate, ADP. We have identified KAT9 and HDAC3 as the potential acetyltransferase and deacetylase, respectively, for PGK1. Insulin promotes K220 deacetylation to stimulate PGK1 activity. We show that the PI3K/AKT/mTOR pathway regulates HDAC3 S424 phosphorylation, which promotes HDAC3-PGK1 interaction and PGK1 K220 deacetylation. Our study uncovers a previously unknown mechanism for the insulin and mTOR pathway in regulation of glycolytic ATP production and cellular redox potential via HDAC3-mediated PGK1 deacetylation.

Insights into mechanism kinematics for protein motion simulation

Background

The high demanding computational requirements necessary to carry out protein motion simulations make it difficult to obtain information related to protein motion. On the one hand, molecular dynamics simulation requires huge computational resources to achieve satisfactory motion simulations. On the other hand, less accurate procedures such as interpolation methods, do not generate realistic morphs from the kinematic point of view. Analyzing a protein’s movement is very similar to serial robots; thus, it is possible to treat the protein chain as a serial mechanism composed of rotational degrees of freedom. Recently, based on this hypothesis, new methodologies have arisen, based on mechanism and robot kinematics, to simulate protein motion. Probabilistic roadmap method, which discretizes the protein configurational space against a scoring function, or the kinetostatic compliance method that minimizes the torques that appear in bonds, aim to simulate protein motion with a reduced computational cost.

Results

In this paper a new viewpoint for protein motion simulation, based on mechanism kinematics is presented. The paper describes a set of methodologies, combining different techniques such as structure normalization normalization processes, simulation algorithms and secondary structure detection procedures. The combination of all these procedures allows to obtain kinematic morphs of proteins achieving a very good computational cost-error rate, while maintaining the biological meaning of the obtained structures and the kinematic viability of the obtained motion.

Conclusions

The procedure presented in this paper, implements different modules to perform the simulation of the conformational change suffered by a protein when exerting its function. The combination of a main simulation procedure assisted by a secondary structure process, and a side chain orientation strategy, allows to obtain a fast and reliable simulations of protein motion.

Comparing neural-network scoring functions and the state of the art: applications to common library screening

We compare established docking programs, AutoDock Vina and Schrödinger's Glide, to the recently published NNScore scoring functions. As expected, the best protocol to use in a virtual-screening project is highly dependent on the target receptor being studied. However, the mean screening performance obtained when candidate ligands are docked with Vina and rescored with NNScore 1.0 is not statistically different than the mean performance obtained when docking and scoring with Glide. We further demonstrate that the Vina and NNScore docking scores both correlate with chemical properties like small-molecule size and polarizability. Compensating for these potential biases leads to improvements in virtual screen performance. Composite NNScore-based scoring functions suited to a specific receptor further improve performance. We are hopeful that the current study will prove useful for those interested in computer-aided drug design.

The molecular dynamics of Trypanosoma brucei UDP-galactose 4'-epimerase: a drug target for African sleeping sickness

During the past century, several epidemics of human African trypanosomiasis, a deadly disease caused by the protist Trypanosoma brucei, have afflicted sub-Saharan Africa. Over 10 000 new victims are reported each year, with hundreds of thousands more at risk. As current drug treatments are either highly toxic or ineffective, novel trypanocides are urgently needed. The T. brucei galactose synthesis pathway is one potential therapeutic target. Although galactose is essential for T. brucei survival, the parasite lacks the transporters required to intake galactose from the environment. UDP-galactose 4'-epimerase (TbGalE) is responsible for the epimerization of UDP-glucose to UDP-galactose and is therefore of great interest to medicinal chemists. Using molecular dynamics simulations, we investigate the atomistic motions of TbGalE in both the apo and holo states. The sampled conformations and protein dynamics depend not only on the presence of a UDP-sugar ligand, but also on the chirality of the UDP-sugar C4 atom. This dependence provides important insights into TbGalE function and may help guide future computer-aided drug discovery efforts targeting this protein.

Biomolecular dynamics: order-disorder transitions and energy landscapes

While the energy landscape theory of protein folding is now a widely accepted view for understanding how relatively weak molecular interactions lead to rapid and cooperative protein folding, such a framework must be extended to describe the large-scale functional motions observed in molecular machines. In this review, we discuss (1) the development of the energy landscape theory of biomolecular folding, (2) recent advances toward establishing a consistent understanding of folding and function and (3) emerging themes in the functional motions of enzymes, biomolecular motors and other biomolecular machines. Recent theoretical, computational and experimental lines of investigation have provided a very dynamic picture of biomolecular motion. In contrast to earlier ideas, where molecular machines were thought to function similarly to macroscopic machines, with rigid components that move along a few degrees of freedom in a deterministic fashion, biomolecular complexes are only marginally stable. Since the stabilizing contribution of each atomic interaction is on the order of the thermal fluctuations in solution, the rigid body description of molecular function must be revisited. An emerging theme is that functional motions encompass order-disorder transitions and structural flexibility provides significant contributions to the free energy. In this review, we describe the biological importance of order-disorder transitions and discuss the statistical-mechanical foundation of theoretical approaches that can characterize such transitions.

Excited states of ribosome translocation revealed through integrative molecular modeling

The dynamic nature of biomolecules leads to significant challenges when characterizing the structural properties associated with function. While X-ray crystallography and imaging techniques (such as cryo-electron microscopy) can reveal the structural details of stable molecular complexes, strategies must be developed to characterize configurations that exhibit only marginal stability (such as intermediates) or configurations that do not correspond to minima on the energy landscape (such as transition-state ensembles). Here, we present a methodology (MDfit) that utilizes molecular dynamics simulations to generate configurations of excited states that are consistent with available biophysical and biochemical measurements. To demonstrate the approach, we present a sequence of configurations that are suggested to be associated with transfer RNA (tRNA) movement through the ribosome (translocation). The models were constructed by combining information from X-ray crystallography, cryo-electron microscopy, and biochemical data. These models provide a structural framework for translocation that may be further investigated experimentally and theoretically to determine the precise energetic character of each configuration and the transition dynamics between them.

Molecular dynamics simulations and drug discovery

This review discusses the many roles atomistic computer simulations of macromolecular (for example, protein) receptors and their associated small-molecule ligands can play in drug discovery, including the identification of cryptic or allosteric binding sites, the enhancement of traditional virtual-screening methodologies, and the direct prediction of small-molecule binding energies. The limitations of current simulation methodologies, including the high computational costs and approximations of molecular forces required, are also discussed. With constant improvements in both computer power and algorithm design, the future of computer-aided drug design is promising; molecular dynamics simulations are likely to play an increasingly important role.

Mechanical mapping of single membrane proteins at submolecular resolution

The capacity of proteins to carry out different functions is related to their ability to undergo conformation changes, which depends on the flexibility of protein structures. In this work, we applied a novel imaging mode based on indentation force spectroscopy to map quantitatively the flexibility of individual membrane proteins in their native, folded state at unprecedented submolecular resolution. Our results enabled us to correlate protein flexibility with crystal structure and showed that α-helices are stiff structures that may contribute importantly to the mechanical stability of membrane proteins, while interhelical loops appeared more flexible, allowing conformational changes related to function.

Pyrone-based inhibitors of metalloproteinase types 2 and 3 may work as conformation-selective inhibitors

Matrix metalloproteinases are zinc-containing enzymes capable of degrading all components of the extracellular matrix. Owing to their role in human disease, matrix metalloproteinase have been the subject of extensive study. A bioinorganic approach was recently used to identify novel inhibitors based on a maltol zinc-binding group, but accompanying molecular-docking studies failed to explain why one of these inhibitors, AM-6, had approximately 2500-fold selectivity for MMP-3 over MMP-2. A number of studies have suggested that the matrix-metalloproteinase active site is highly flexible, leading some to speculate that differences in active-site flexibility may explain inhibitor selectivity. To extend the bioinorganic approach in a way that accounts for MMP-2 and MMP-3 dynamics, we here investigate the predicted binding modes and energies of AM-6 docked into multiple structures extracted from matrix-metalloproteinase molecular dynamics simulations. Our findings suggest that accounting for protein dynamics is essential for the accurate prediction of binding affinity and selectivity. Additionally, AM-6 and other similar inhibitors likely select for and stabilize only a subpopulation of all matrix-metalloproteinase conformations sampled by the apo protein. Consequently, when attempting to predict ligand affinity and selectivity using an ensemble of protein structures, it may be wise to disregard protein conformations that cannot accommodate the ligand.

Seeing the forest for the trees: fluorescence studies of single enzymes in the context of ensemble experiments

Enzymes are remarkable molecular machines that make many difficult biochemical reactions possible under mild biological conditions with incredible precision and efficiency. Our understanding of the working principles of enzymes, however, has not reached the level where one can readily deduce the mechanism and the catalytic rates from an enzyme's structure. Resolving the dynamics that relate the three-dimensional structure of an enzyme to its function has been identified as a key issue. While still challenging to implement, single-molecule techniques have emerged as one of the most useful methods for studying enzymes. We review enzymes studied using single-molecule fluorescent methods but placing them in the context of results from other complementary experimental work done on bulk samples. This review primarily covers three enzyme systems--flavoenzymes, dehydrofolate reductase, and adenylate kinase--with additional enzymes mentioned where appropriate. When the single-molecule experiments are discussed together with other methods aiming at the same scientific question, the weakness, strength, and unique contributions become clear.

Computer-aided drug-discovery techniques that account for receptor flexibility

Protein flexibility plays a critical role in ligand binding to both orthosteric and allosteric sites. We here review some of the computer-aided drug-design techniques currently used to account for protein flexibility, ranging from methods that probe local receptor flexibility in the region of the protein immediately adjacent to the binding site, to those that account for general flexibility in all protein regions.

The mechanism of ubiquitination in the cullin-RING E3 ligase machinery: conformational control of substrate orientation

In cullin-RING E3 ubiquitin ligases, substrate binding proteins, such as VHL-box, SOCS-box or the F-box proteins, recruit substrates for ubiquitination, accurately positioning and orienting the substrates for ubiquitin transfer. Yet, how the E3 machinery precisely positions the substrate is unknown. Here, we simulated nine substrate binding proteins: Skp2, Fbw7, beta-TrCP1, Cdc4, Fbs1, TIR1, pVHL, SOCS2, and SOCS4, in the unbound form and bound to Skp1, ASK1 or Elongin C. All nine proteins have two domains: one binds to the substrate; the other to E3 ligase modules Skp1/ASK1/Elongin C. We discovered that in all cases the flexible inter-domain linker serves as a hinge, rotating the substrate binding domain, optimally and accurately positioning it for ubiquitin transfer. We observed a conserved proline in the linker of all nine proteins. In all cases, the prolines pucker substantially and the pucker is associated with the backbone rotation toward the E2/ubiquitin. We further observed that the linker flexibility could be regulated allosterically by binding events associated with either domain. We conclude that the flexible linker in the substrate binding proteins orients the substrate for the ubiquitin transfer. Our findings provide a mechanism for ubiquitination and polyubiquitination, illustrating that these processes are under conformational control.

Solution nuclear magnetic resonance structure of membrane-integral diacylglycerol kinase

Escherichia coli diacylglycerol kinase (DAGK) represents a family of integral membrane enzymes that is unrelated to all other phosphotransferases. We have determined the three-dimensional structure of the DAGK homotrimer with the use of solution nuclear magnetic resonance. The third transmembrane helix from each subunit is domain-swapped with the first and second transmembrane segments from an adjacent subunit. Each of DAGK's three active sites resembles a portico. The cornice of the portico appears to be the determinant of DAGK's lipid substrate specificity and overhangs the site of phosphoryl transfer near the water-membrane interface. Mutations to cysteine that caused severe misfolding were located in or near the active site, indicating a high degree of overlap between sites responsible for folding and for catalysis.

Database of ligand-induced domain movements in enzymes

BACKGROUND

Conformational change induced by the binding of a substrate or coenzyme is a poorly understood stage in the process of enzyme catalysed reactions. For enzymes that exhibit a domain movement, the conformational change can be clearly characterized and therefore the opportunity exists to gain an understanding of the mechanisms involved. The development of the non-redundant database of protein domain movements contains examples of ligand-induced domain movements in enzymes, but this valuable data has remained unexploited.

DESCRIPTION

The domain movements in the non-redundant database of protein domain movements are those found by applying the DynDom program to pairs of crystallographic structures contained in Protein Data Bank files. For each pair of structures cross-checking ligands in their Protein Data Bank files with the KEGG-LIGAND database and using methods that search for ligands that contact the enzyme in one conformation but not the other, the non-redundant database of protein domain movements was refined down to a set of 203 enzymes where a domain movement is apparently triggered by the binding of a functional ligand. For these cases, ligand binding information, including hydrogen bonds and salt-bridges between the ligand and specific residues on the enzyme is presented in the context of dynamical information such as the regions that form the dynamic domains, the hinge bending residues, and the hinge axes.

CONCLUSION

The presentation at a single website of data on interactions between a ligand and specific residues on the enzyme alongside data on the movement that these interactions induce, should lead to new insights into the mechanisms of these enzymes in particular, and help in trying to understand the general process of ligand-induced domain closure in enzymes. The website can be found at: http://www.cmp.uea.ac.uk/dyndom/enzymeList.do.

Structural flexibility in hydrated proteins

The flexibility of protein structures is important in allowing the variety of motions, covering a wide range of magnitudes and frequencies, essential to biological activity. Protein flexibility is also implicated in denaturation, allowing proteins to take up nonactive conformations that have free energies close to that of the native state. High-frequency dielectric measurement can be used to study the flexibility of proteins by probing the relaxation of dipolar constituents of their structures. In this work, 14 hydrated globular proteins are investigated using this method. Four relaxation processes are identified, one of which, with a relaxation time of 19 ns, can be correlated with the sum of the number densities of protein glycine and alanine residues. A second with a relaxation time of 2 ns shows a dependence on the number of threonine residues. It is concluded that the dipolar peptide groups of the protein backbone associated with these residues are responsible for these dielectric responses, with the lower frequency dispersion being due to backbone mobility in the hydrophobic environment of the protein core and the higher frequency response being associated with mobility on the more hydrophilic protein surface. The correlation of protein backbone flexibility with particular side chains indicates that these protein motions are under the direct control of the amino acid sequence of the protein.

Recent developments in structural proteomics for protein structure determination

The major challenges in structural proteomics include identifying all the proteins on the genome-wide scale, determining their structure-function relationships, and outlining the precise three-dimensional structures of the proteins. Protein structures are typically determined by experimental approaches such as X-ray crystallography or nuclear magnetic resonance (NMR) spectroscopy. However, the knowledge of three-dimensional space by these techniques is still limited. Thus, computational methods such as comparative and de novo approaches and molecular dynamic simulations are intensively used as alternative tools to predict the three-dimensional structures and dynamic behavior of proteins. This review summarizes recent developments in structural proteomics for protein structure determination; including instrumental methods such as X-ray crystallography and NMR spectroscopy, and computational methods such as comparative and de novo structure prediction and molecular dynamics simulations.

The role of dynamics in allosteric regulation

The biomolecular conformational changes often associated with allostery are, by definition, dynamic processes. Recent publications have disclosed the role of pre-existing equilibria of conformational substates in this process. In addition, the role of dynamics as an entropic carrier of free energy of allostery has been investigated. Recent work thus shows that dynamics is pivotal to allostery, and that it constitutes much more than just the move from the 'T'-state to the 'R'-state. Emerging computational studies have described the actual pathways of allosteric change.