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GPR6 is an orphan G protein–coupled receptor with high constitutive activity found in D2-type dopamine receptor–expressing medium spiny neurons of the striatopallidal pathway, which is aberrantly hyperactivated in Parkinson's disease. Here, we solved crystal structures of GPR6 without the addition of a ligand (a pseudo-apo state) and in complex with two inverse agonists, including CVN424, which improved motor symptoms in patients with Parkinson's disease in clinical trials. In addition, we obtained a cryo–electron microscopy structure of the signaling complex between GPR6 and its cognate Gs heterotrimer. The pseudo-apo structure revealed a strong density in the orthosteric pocket of GPR6 corresponding to a lipid-like endogenous ligand. A combination of site-directed mutagenesis, native mass spectrometry, and computer modeling suggested potential mechanisms for high constitutive activity and inverse agonism in GPR6 and identified a series of lipids and ions bound to the receptor. The structures and results obtained in this study could guide the rational design of drugs that modulate GPR6 signaling. Editor's summary: The rigidity and immobility caused by the progression of Parkinson's disease are caused by loss of dopaminergic neurons in the substantia nigra. Dopamine replacement therapy offers only temporary relief with potentially severe side effects. Barekatain et al. performed structural analysis of GPR6, a G protein–coupled receptor important for the activity of dopaminergic neurons that stop movement. An inverse agonist for GPR6 that is currently in clinical trials ameliorates locomotor deficits related to Parkinson's disease. The authors' data provide the structural basis for the high basal activity of GPR6 and how other inverse agonists targeting GPR6 could be designed to provide a nondopaminergic treatment option for patients with Parkinson's disease. —Wei Wong [ABSTRACT FROM AUTHOR]

Low temperatures and cooling agents like menthol induce cold sensation by activating the peripheral cold receptors TRPM8 and TRPA1, cation channels belonging to the TRP channel family, while the reduction of potassium currents provides an additional and/or synergistic mechanism of cold sensation. Despite extensive studies over the past decades to identify the molecular receptors that mediate thermosensation, cold sensation is still not fully understood and many cold-sensitive peripheral neurons do not express the well-established cold sensor TRPM8. We found that the voltage-gated potassium channel KCNQ1 (Kv7.1), which is defective in cardiac LQT1 syndrome, is, in addition to its known function in the heart, a highly relevant and sex-specific sensor of moderately cold temperatures. We found that KCNQ1 is expressed in skin and dorsal root ganglion neurons, is sensitive to menthol and cooling agents, and is highly sensitive to moderately cold temperatures, in a temperature range at which TRPM8 is not thermosensitive. C-fiber recordings from KCNQ1-/- mice displayed altered action potential firing properties. Strikingly, only male KCNQ1-/- mice showed substantial deficits in cold avoidance at moderately cold temperatures, with a strength of the phenotype similar to that observed in TRPM8-/- animals. While sex-dependent differences in thermal sensitivity have been well documented in humans and mice, KCNQ1 is the first gene reported to play a role in sex-specific temperature sensation. Moreover, we propose that KCNQ1, together with TRPM8, is a key instrumentalist that orchestrates the range and intensity of cold sensation. [ABSTRACT FROM AUTHOR]

In this study, four depsides were isolated from Origanum dictamnus L. and Satureja pilosa Velen. medicinal plants and their structures were assessed by means of one-dimensional (1D)- and two-dimensional (2D)-nuclear magnetic resonance, high resolution mass spectrometry, and electronic circular dichroism analyses. The compound 1, herein reported for the first time, salvianolic acid P 2, clinopodic acid I 3, and clinopodic acid O 4 were all profiled in vitro on a panel of human (h) expressed carbonic anhydrases (CAs; EC 4.2.1.1) and preferential inhibition for the tumor-associated human carbonic anhydrase (hCA) IX and hCA XII over the constitutively expressed hCA I and hCA II isoforms was observed. X-ray crystallography allowed us to assess the binding mode of salvianolic acid P 2 to hCA II. The compounds exhibited significant cytotoxic effects on the human triple-negative breast cancer cell line MDA-MB-231, suggesting that this class of depsides are promising molecules for future investigation., (© 2024 Deutsche Pharmazeutische Gesellschaft.)

The availability of large, high-quality datasets is crucial for artificial intelligence design and discovery in chemistry. Despite the essential roles of solvents in chemistry, the rapid computational dataset generation of solution-phase molecular properties at the quantum mechanical level of theory was previously hampered by the complicated simulation procedure. Software toolkits that can automate the procedure to set up high-throughput explicit-solvent quantum chemistry (QC) calculations for arbitrary solutes and solvents in an open-source framework are still lacking. We developed AutoSolvate, an open-source toolkit, to streamline the workflow for QC calculation of explicitly solvated molecules. It automates the solvated-structure generation, force field fitting, configuration sampling, and the final extraction of microsolvated cluster structures that QC packages can readily use to predict molecular properties of interest. AutoSolvate is available through both a command line interface and a graphical user interface, making it accessible to the broader scientific community. To improve the quality of the initial structures generated by AutoSolvate, we investigated the dependence of solute–solvent closeness on solute/solvent identities and trained a machine learning model to predict the closeness and guide initial structure generation. Finally, we tested the capability of AutoSolvate for rapid dataset curation by calculating the outer-sphere reorganization energy of a large dataset of 166 redox couples, which demonstrated the promise of the AutoSolvate package for chemical discovery efforts. [ABSTRACT FROM AUTHOR]

Biased ligands selectively activating specific downstream signaling pathways (termed as biased activation) exhibit significant therapeutic potential. However, the conformational characteristics revealed are very limited for the biased activation, which is not conducive to biased drug development. Motivated by the issue, we combine extensive accelerated molecular dynamics simulations and an interpretable deep learning model to probe the biased activation features for two complex systems constructed by the inactive μOR and two different biased agonists (G-protein-biased agonist TRV130 and β-arrestin-biased agonist endomorphin2). The results indicate that TRV130 binds deeper into the receptor core compared to endomorphin2, located between W2936.48 and D1142.50, and forms hydrogen bonding with D1142.50, while endomorphin2 binds above W2936.48. The G protein-biased agonist induces greater outward movements of the TM6 intracellular end, forming a typical active conformation, while the β-arrestin-biased agonist leads to a smaller extent of outward movements of TM6. Compared with TRV130, endomorphin2 causes more pronounced inward movements of the TM7 intracellular end and more complex conformational changes of H8 and ICL1. In addition, important residues determining the two different biased activation states were further identified by using an interpretable deep learning classification model, including some common biased activation residues across Class A GPCRs like some key residues on the TM2 extracellular end, ECL2, TM5 intracellular end, TM6 intracellular end, and TM7 intracellular end, and some specific important residues of ICL3 for μOR. The observations will provide valuable information for understanding the biased activation mechanism for GPCRs. [ABSTRACT FROM AUTHOR]

We present a review of a series of contact maps for the determination of native interactions in proteins and nucleic acids based on a distance threshold. Such contact maps are mostly based on physical and chemical construction, and yet they are sensitive to some parameters (e.g., distances or atomic radii) and can neglect some key interactions. Furthermore, we also comment on a new class of contact maps that only requires geometric arguments. The contact map is a necessary ingredient to build a robust GōMartini model for proteins and their complexes in the Martini 3 force field. We present the extension of a popular structure-based Gō-like approach to the study of protein-sugar complexes, and the limitations of this approach are also discussed. The GōMartini approach was first introduced by Poma et al. (J. Chem. Theory Comput. 13, 1366 (2017)) in Martini 2 force field, and recently, it has gained the status of gold standard for protein simulation undergoing conformational changes in Martini 3 force field. We discuss several studies that have provided support for this approach in the context of the biophysical community. [ABSTRACT FROM AUTHOR]

Phenylketonuria (PKU) is a genetically inherited disease caused by a mutation of the gene encoding phenylalanine hydroxylase (PAH) and is the most common inborn error of amino acid metabolism. A deficiency of PAH leads to increased blood and brain levels of phenylalanine (Phe), which may cause permanent neurocognitive symptoms and developmental delays if untreated. Current management strategies for PKU consist of early detection through neonatal screening and implementation of a restrictive diet with minimal amounts of natural protein in combination with Phe-free supplements and low-protein foods to meet nutritional requirements. For milder forms of PKU, oral treatment with synthetic sapropterin (BH4), the cofactor of PAH, may improve metabolic control of Phe and allow for more natural protein to be included in the patient's diet. For more severe forms, daily injections of pegvaliase, a PEGylated variant of phenylalanine ammonia-lyase (PAL), may allow for normalization of blood Phe levels. However, the latter treatment has considerable drawbacks, notably a strong immunogenicity of the exogenous enzyme and the attached polymeric chains. Research for novel therapies of PKU makes use of innovative materials for drug delivery and state-of-the-art protein engineering techniques to develop treatments which are safer, more effective, and potentially permanent., (© 2024 Wiley‐VCH GmbH.)

The dissociation of ligands from proteins and other biomacromolecules occurs over a wide range of timescales. For most pharmaceutically relevant inhibitors, these timescales are far beyond those that are accessible by conventional molecular dynamics (MD) simulation. Consequently, to explore ligand egress mechanisms and compute dissociation rates, it is necessary to enhance the sampling of ligand unbinding. Random Acceleration MD (RAMD) is a simple method to enhance ligand egress from a macromolecular binding site, which enables the exploration of ligand egress routes without prior knowledge of the reaction coordinates. Furthermore, the τRAMD procedure can be used to compute the relative residence times of ligands. When combined with a machine-learning analysis of protein–ligand interaction fingerprints (IFPs), molecular features that affect ligand unbinding kinetics can be identified. Here, we describe the implementation of RAMD in GROMACS 2020, which provides significantly improved computational performance, with scaling to large molecular systems. For the automated analysis of RAMD results, we developed MD-IFP, a set of tools for the generation of IFPs along unbinding trajectories and for their use in the exploration of ligand dynamics. We demonstrate that the analysis of ligand dissociation trajectories by mapping them onto the IFP space enables the characterization of ligand dissociation routes and metastable states. The combined implementation of RAMD and MD-IFP provides a computationally efficient and freely available workflow that can be applied to hundreds of compounds in a reasonable computational time and will facilitate the use of τRAMD in drug design. [ABSTRACT FROM AUTHOR]

Stabilization of amyloidogenic immunoglobulin light chains (LCs) by binding of small molecule "kinetic stabilizers" is under development as a novel treatment for light chain amyloidosis. From a high‐throughput screen, we previously identified 16 full‐length (FL) LC stabilizers from five distinct chemotypes. We then obtained structural biological information on two classes of hits, coumarins and hydantoins, revealing that both chemotypes bind to a pocket at the VL−VL interface of the FL LC dimer. Here, we report crystal structures of three screening hits from two other chemotypes, diaryl hydrazones and sulfones, in complex with an amyloidogenic FL LC. While two of these hits bind to the previously identified pocket, one diaryl hydrazone binds to a different pocket bisected by the C2 symmetry axis of the dimer. These data further expand on the FL LC stabilizer‐binding surface that could be used in design of more potent FL LC aggregation inhibitors. [ABSTRACT FROM AUTHOR]

Caspase‐7 (C7), a cysteine protease involved in apoptosis, is a valuable drug target for its role in human diseases (e. g., Parkinson's, Alzheimer's, sepsis). The C7 allosteric site has great potential for small‐molecule targeting, but numerous drug discovery efforts have identified precious few allosteric inhibitors. Here we present the first selective, drug‐like inhibitor of C7 along with several other improved inhibitors based on our previous fragment hit. We also provide a rational basis for the impact of allosteric binding on the C7 catalytic cycle by using an integrated approach including X‐ray crystallography, stopped‐flow kinetics, and molecular dynamics simulations. Our findings suggest allosteric binding disrupts C7 pre‐acylation by neutralization of the catalytic dyad, displacement of substrate from the oxyanion hole, and altered dynamics of substrate binding loops. This work advances drug targeting efforts and bolsters our understanding of allosteric structure–activity relationships (ASARs). [ABSTRACT FROM AUTHOR]

Biocatalytic hydroamination of alkenes is an efficient and selective method to synthesize natural and unnatural amino acids. Phenylalanine ammonia-lyases (PALs) have been previously engineered to access a range of substituted phenylalanines and heteroarylalanines, but their substrate scope remains limited, typically including only arylacrylic acids. Moreover, the enantioselectivity in the hydroamination of electron-deficient substrates is often poor. Here, we report the structure-based engineering of PAL from Planctomyces brasiliensis (PbPAL), enabling preparative-scale enantioselective hydroaminations of previously inaccessible yet synthetically useful substrates, such as amide- and ester-containing fumaric acid derivatives. Through the elucidation of cryo-electron microscopy (cryo-EM) PbPAL structure and screening of the structure-based mutagenesis library, we identified the key active site residue L205 as pivotal for dramatically enhancing the enantioselectivity of hydroamination reactions involving electron-deficient substrates. Our engineered PALs demonstrated exclusive α-regioselectivity, high enantioselectivity, and broad substrate scope. The potential utility of the developed biocatalysts was further demonstrated by a preparative-scale hydroamination yielding tert-butyl protected l-aspartic acid, widely used as intermediate in peptide solid-phase synthesis., (© 2024 The Authors. Angewandte Chemie International Edition published by Wiley-VCH GmbH.)

A new series of nucleoside derivatives was prepared from the reaction of 4-aminoantipyrene with different sugar moieties. In addition, ampyrone's reaction with different aromatic aldehydes gave the corresponding Schiff base derivatives, which were also synthesized. Both molecular docking and in vitro antiviral activities at different concentrations of different synthesized compounds against SARS-CoV-2 were screened. All newly synthesized compounds were characterized on the basis of IR, 1H NMR and 13C NMR spectral data and physical data. The compounds were screened for potential cytotoxic activities. The molecular docking analysis showed that compounds 6b, 6e, 6c, 6f and 6d exhibited relatively higher binding energies (−8.1, −8.1, −8.3, −8.4 and −8.7 kcal/mol, respectively) compared to all the other compounds. However, the different compounds did not show any promising in vitro antiviral activities against SARS-CoV-2. [ABSTRACT FROM AUTHOR]

Characterization of the aromatic ammonia-lyase from Loktanella atrilutea (LaAAL) revealed reduced activity towards canonical AAL substrates: l-Phe, l-Tyr, and l-His, contrasted by its pronounced efficiency towards 3,4-dimethoxy-l-phenylalanine. Assessing the optimal conditions, LaAAL exhibited maximal activity at pH 9.5 in the ammonia elimination reaction route, distinct from the typical pH ranges of most PALs and TALs. Within the exploration of the ammonia source for the opposite, synthetically valuable ammonia addition reaction, the stability of LaAAL exhibited a positive correlation with the ammonia concentration, with the highest stability in 4 M ammonium carbamate of unadjusted pH of ~9.5. While the enzyme activity increased with rising temperatures yet, the highest operational stability and highest stationary conversions of LaAAL were observed at 30 °C. The substrate scope analysis highlighted the catalytic adaptability of LaAAL in the hydroamination of diverse cinnamic acids, especially of meta-substituted and di-/multi-substituted analogues, with structural modelling exposing steric clashes between the substrates' ortho-substituents and catalytic site residues. LaAAL showed a predilection for ammonia elimination, while classifying as a tyrosine ammonia-lyase (TAL) among the natural AAL classes. However, its distinctive attributes, such as genomic context, unique substrate specificity and catalytic fingerprint, suggest a potential natural role beyond those of known AAL classes., (© 2024 Wiley-VCH GmbH.)

The knotted proteins are a class of rare but biologically important proteins, due to the special topology of their native structure. Here we present a simple in silico method to identify the key residues for knotting and unknotting in a knotted protein, using the trefoil protein MJ0366 as an example. We first simulate the folding process via the annealing molecular dynamics (AMD) simulations in the coarse-grained "Go"-like model. From the folding trajectories, we monitor the knotting process using the quantity "length of knot tails". In the meantime, we analyze the evolution of the local geometry of the Cα trace with the help of the Discrete Frenet Frame (DFF). We identify the key residues by correlating the local geometry at each residue with the variable "length of knot tails" in the folding process, where a higher correlation coefficient indicates that the residue is more important for knotting. We validate our method by comparing with the experimental results in the literature. With the same method, we further predict the key residues for unknotting MJ0366 using the AMD simulations in both the coarse-grained "Go"-like model and all-atom (AA) force field model, respectively. We find that the key residues for unknotting are partially overlapped with those for knotting, indicating that the pathways for unknotting and knotting are generally similar except for the existence of some non-native contact interactions in the unknotting process. This in silico method can provide a new insight for understanding the knotting and unknotting processes of a knotted protein. [ABSTRACT FROM AUTHOR]

The present analysis has been performed in the wet‐lab and computational environments. First, the synthesis of the latest heterocyclic compounds containing the alkyl organic compound fragment of acetate and glycine acid were obtained and then their crystal structure and biological activity were studied. (Z)‐ethyl‐2‐(3‐oxo‐1,3‐diphenylprop‐1‐enylamino) acetate (1) was initially retrieved on the supported reaction of dibenzene gas with glycine alkyl organic compound‐complex within the presence of Y(OTF)3 catalyst in liquid medium. At an identical time, ethyl‐3,5‐diphenyl‐1H‐pyrrole‐2‐carboxylate (2) was synthesized from the interaction of amino alkane with tert‐BuOK in the presence of tert‐BuOH/DMFA solvent. The structure of the latest compounds has been studied by 1H, 13C NMR. Additionally, the crystal structure of ethyl‐3,5‐diphenyl‐1H‐pyrrole‐2‐carboxylate (2) is conferred. Moreover, computational drug‐likeness and pharmacokinetics indicated the compounds' good drug‐like molecules and friendly pharmacokinetics, making the compound valuable candidates to be explored for additional structural modification to act as a potential inhibitor of AChE and α‐glycosidase enzymes. [ABSTRACT FROM AUTHOR]

Ternary complexes of vanadium(IV) and titanium(IV) containing macrocyclic chelate ring were synthesized from dibasic tetra‐dentate Schiff bases as primary (LH2) and succinic acid (SA) as secondary ligand. Their stable formation was confirmed on the basis of spectro‐analytical evidences and octahedral geometry has been proposed for mononuclear ternary complexes, [M(L)SA] (M = Ti4+, V4+). The proposed structure of the complexes has been optimized by quantum mechanical calculations. Some of the complexes have good antioxidant property and considerable inhibition capacity against selected pathogenic microorganisms. Molecular docking of a ligand against SARS‐CoV‐2 main protease (6 LU7) revealed binding affinity comparable to chloroquine used as standard. The ADMET analysis showed that it is noncarcinogenic and less toxic indicating as good candidate against SARS‐CoV‐2 infection. [ABSTRACT FROM AUTHOR]

HIV protease (HIVPR) is a key target in AIDS therapeutics. All ten FDA-approved drugs that compete with substrates in binding to this dimeric enzyme's active site have become ineffective due to the emergence of drug resistant mutants. Blocking the dimerization interface of HIVPR is thus being explored as an alternate strategy. The latest drug, darunavir (DRV), which exhibited a high genetic barrier to viral resistance, is said to have a dual mode of action – (i) binding to the dimeric active site, and (ii) preventing the dimerization by binding to the HIVPR monomer. Despite several reports on DRV complexation with dimeric HIVPR, the mode and mechanism of the binding of DRV to the HIVPR monomer are poorly understood. In this study, we utilized all-atomic MD simulations and umbrella sampling techniques to identify the best possible binding mode of DRV to the monomeric HIVPR and its mechanism of association. The results suggest that DRV binds between the active site and the flap of the monomer, and the flap plays a crucial role in directing the drug to bind and driving the other protein domains to undergo induced fit changes for stronger complexation. The obtained binding mode of DRV was validated by comparing with various mutational data from clinical isolates to reported in vitro mutations. The identified binding pose was also able to successfully reproduce the experimental Ki value in the picomolar range. The residue-level information extracted from this study could accelerate the structure-based drug designing approaches targeting HIVPR dimerization. [ABSTRACT FROM AUTHOR]

Docking studies play a critical role in the current workflow of drug discovery. However, limitations may often arise through factors including inadequate ligand sampling, a lack of protein flexibility, scoring function inadequacies (e.g., due to metals, co‐factors, etc.), and difficulty in retaining explicit water molecules. Herein, we present a novel CHARMM‐based induced fit docking (CIFDock) workflow that can circumvent these limitations by employing all‐atom force fields coupled to enhanced sampling molecular dynamics procedures. Self‐guided Langevin dynamics simulations are used to effectively sample relevant ligand conformations, side chain orientations, crystal water positions, and active site residue motion. Protein flexibility is further enhanced by dynamic sampling of side chain orientations using an expandable rotamer library. Steps in the procedure consisting of fixing individual components (e.g., the ligand) while sampling the other components (e.g., the residues in the active site of the protein) allow for the complex to adapt to conformational changes. Ultimately, all components of the complex—the protein, ligand, and waters—are sampled simultaneously and unrestrained with SGLD to capture any induced fit effects. This modular flexible docking procedure is automated using CHARMM scripting, interfaced with SLURM array processing, and parallelized to use the desired number of processors. We validated the CIFDock procedure by performing cross‐docking studies using a data set comprised of 21 pharmaceutically relevant proteins. Five variants of the CHARMM‐based SWISSDOCK scoring functions were created to quantify the results of the final generated poses. Results obtained were comparable to, or in some cases improved upon, commercial docking program data. [ABSTRACT FROM AUTHOR]

Several applications arise from the confinement of proteins on surfaces because their stability and biological activity are enhanced. It is also known that the way in which a protein adsorbs on the surface is important for its biological function since its active sites should not be obstructed. In this study, the adsorption properties of hen egg-white lysozyme, HEWL, into a negatively charged silica pore is examined by employing a coarse-grained model and constant-pH Monte Carlo simulations. The role of electrostatic interactions is taken into account via including the Debye-Hückel potentials into the Ca structure-based model. We evaluate the effects of pH, salt concentration, and pore radius on the protein preferential orientation and spatial distribution of its residues regarding the pore surface. By mapping the residues that stay closer to the pore surface, we find that the increase of pH leads to orientational changes of the adsorbed protein when the solution pH gets closer to the HEWL isoelectric point. Under these conditions, the pKa shift of these important residues caused by the adsorption into the charged confining surface results in a HEWL charge distribution that stabilizes the adsorption in the observed protein orientation. We compare our observations to the results of the pKa shift for HEWL available in the literature and to some experimental data. [ABSTRACT FROM AUTHOR]

Membrane proteins play critically important roles in many cellular activities such as ions and small molecule transportation, signal recognition, and transduction. In order to fulfill their functions, these proteins must be placed in different membrane environments and a variety of protein-lipid interactions may affect the behavior of these proteins. One of the key effects of protein-lipid interactions is their ability to change the dynamics status of membrane proteins, thus adjusting their functions. Here, we present a multi-scaled normal mode analysis (mNMA) method to study the dynamics perturbation to the membrane proteins imposed by lipid bi-layer membrane fluctuations. In mNMA, channel proteins are simulated at all-atom level while the membrane is described with a coarse-grained model. mNMA calculations clearly show that channel gating motion can tightly couple with a variety of membrane deformations, including bending and twisting. We then examined bi-channel systems where two channels were separated with different distances. From mNMA calculations, we observed both positive and negative gating correlations between two neighboring channels, and the correlation has a maximum as the channel center-to-center distance is close to 2.5 times of their diameter. This distance is larger than recently found maximum attraction distance between two proteins embedded in membrane which is 1.5 times of the protein size, indicating that membrane fluctuation might impose collective motions among proteins within a larger area. The hybrid resolution feature in mNMA provides atomic dynamics information for key components in the system without costing much computer resource. We expect it to be a conventional simulation tool for ordinary laboratories to study the dynamics of very complicated biological assemblies. The source code is available upon request to the authors. [ABSTRACT FROM AUTHOR]

We study the folding process in the shallowly knotted protein MJ0366 within two variants of a structure-based model. We observe that the resulting topological pathways are much richer than identified in previous studies. In addition to the single knot-loop events, we find novel, and dominant, two-loop mechanisms. We demonstrate that folding takes place in a range of temperatures and the conditions of most successful folding are at temperatures which are higher than those required for the fastest folding. We also demonstrate that nascent conditions are more favorable to knotting than off-ribosome folding. [ABSTRACT FROM AUTHOR]

We use a structure-based coarse grained model to elucidate stretching of three cohesin-dockerin complexes that are found in the cellulosome. The average strength of mechanostability is comparable to that of the I27 domain of titin, but the force profiles depend on the pulling direction and anisotropy effects can be substantial. Even though the force profiles for individual cohesins and dockerins are similar, those for their complexes are visibly distinct for any pulling direction. [ABSTRACT FROM AUTHOR]

Folded conformations of proteins in thermodynamically stable states have long lifetimes. Before it folds into a stable conformation, or after unfolding from a stable conformation, the protein will generally stray from one random conformation to another leading thus to rapid fluctuations. Brief structural changes therefore occur before folding and unfolding events. These short-lived movements are easily overlooked in studies of folding/unfolding for they represent momentary excursions of the protein to explore conformations in the neighborhood of the stable conformation. The present study looks for precursory signatures of protein folding/unfolding within these rapid fluctuations through a combination of three techniques: (1) ultrafast shape recognition, (2) time series segmentation, and (3) time series correlation analysis. The first procedure measures the differences between statistical distance distributions of atoms in different conformations by calculating shape similarity indices from molecular dynamics simulation trajectories. The second procedure is used to discover the times at which the protein makes transitions from one conformation to another. Finally, we employ the third technique to exploit spatial fingerprints of the stable conformations; this procedure is to map out the sequences of changes preceding the actual folding and unfolding events, since strongly correlated atoms in different conformations are different due to bond and steric constraints. The aforementioned high-frequency fluctuations are therefore characterized by distinct correlational and structural changes that are associated with rate-limiting precursors that translate into brief segments. Guided by these technical procedures, we choose a model system, a fragment of the protein transthyretin, for identifying in this system not only the precursory signatures of transitions associated with α helix and β hairpin, but also the important role played by weaker correlations in such protein folding dynamics. [ABSTRACT FROM AUTHOR]

The activation of GABAA receptors by the neurotransmitter gamma-aminobutyric acid mediates the rapid inhibition response in the central nervous system of mammals. Many neurological and mental health disorders arise from alterations in the structure or function of these pentameric ion channels. GABAA receptors are targets for numerous drugs, including benzodiazepines, which bind to α1β2γ2 GABAA receptors with high affinity to a site in the extracellular domain, between subunits α1 and γ2. It has been established experimentally that the binding of these drugs depends on the presence of one particular amino acid in the α1 subunit: histidine 102. However, the specific role it plays in the intermolecular interaction has not been elucidated. In this work, we applied in silico methods to understand whether certain protonation and rotamer states of α1His102 facilitate the binding of modulators. We analysed diazepam binding, a benzodiazepine, and the antagonist flumazenil to the GABAA receptor using molecular dynamics simulations and adaptive biasing force simulations. The binding free energy follows changes in the protonation state for both ligands, and rotameric states of α1His102 were specific for the different compounds, suggesting distinct preferences for positive allosteric modulators and antagonists. Moreover, in the presence of diazepam and favoured by a neutral tautomer, we identified a water molecule that links loops A, B, and C and may be relevant to the modulation mechanism. [ABSTRACT FROM AUTHOR]