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In the present study, we report the liquid exfoliation method to prepare few-layer MoSe2 nanosheets for electrochemical energy storage application. As an electrode for supercapacitor MoSe2 nanosheets manifests specific capacitance of 15F/g at a constant current density of 0.1 Ag−1 and retains the efficiency of 95% over the twelve cycles which is due to the sheet-like morphology that offers maximum electrolyte accessible surface area.

African trypanosomiasis is caused by Trypanosoma brucei subspecies and available drugs against it, are unsatisfactory due to poor pharmacokinetic properties. Trypanosomal Alternative Oxidase (TAO) is an attractive target for anti-trypanosome rational drug discovery because it is essential for parasite-specific ATP generation and absent in the mammalian host. In this study, 360 filtered ligands from the Universal Natural Product Database were virtually screened and docked on T. brucei brucei TAO (PDB-ID 3VVA). From the virtual screening, 10 ligands with binding energy from -10.6 to -9.0 kcal/mol were selected as hits and further subjected pharmacokinetic and toxicity analyses where all of them passed Lipinski's rule of five. Also, the compounds were non-mutagenic, non-tumorigenic and could cross the blood brain barrier. The two topmost hits (UNPD29179; megacerotonic acid and UNPD41551; a quinazoline derivative) interacted with `four glutamates (Glu123, Glu162, Glu213 and Glu266) close to di-iron (2 iron elements) at the catalytic site of the enzyme. Subsequently, 100 ns MD simulations of the two topmost hits were performed using GROMACS where high RMSD values of 0.75 nm (TAO-UNPD29179) and 0.52 nm (TAO- UNPD41551), low residues fluctuations and consistent values of radius of gyration were observed. Moreover, Solvent Accessible Surface Area showed a consistent value of 160 nm2 for both complexes while TAO-UNPD29179 had higher number of hydrogen bonds than the TAO-UNPD41551. Similarly, MM/PBSA calculations indicated that UNPD29179 had higher free binding energy with TAO than UNPD41551. The data suggest that megacerotonic acid and a quinazoline derivative could be potential inhibitors of TAO with improved pharmacokinetic properties.Communicated by Ramaswamy H. Sarma.

Motivation The solvent accessible surface is an essential structural property measure related to the protein structure and protein function. Relative solvent accessible area (RSA) is a standard measure to describe the degree of residue exposure in the protein surface or inside of protein. However, this computation will fail when the residues information is missing. Results In this article, we proposed a novel method for estimation RSA using the Cα atom distance matrix with the deep learning method (EAGERER). The new method, EAGERER, achieves Pearson correlation coefficients of 0.921–0.928 on two independent test datasets. We empirically demonstrate that EAGERER can yield better Pearson correlation coefficients than existing RSA estimators, such as coordination number, half sphere exposure and SphereCon. To the best of our knowledge, EAGERER represents the first method to estimate the solvent accessible area using limited information with a deep learning model. It could be useful to the protein structure and protein function prediction. Availabilityand implementation The method is free available at https://github.com/cliffgao/EAGERER. Supplementary information Supplementary data are available at Bioinformatics online.

Coarse-grained (CG) models of biomolecules have been widely used in protein/ribonucleic acid (RNA) three-dimensional structure prediction, docking, drug design, and molecular simulations due to their superiority in computational efficiency. Most of these applications strongly depend on the reasonable estimation of solvation free energy, which requires the accurate calculation of solvent accessible surface area (SASA). Although algorithms for SASA calculations with all-atom protein and RNA structures have been well-established, accurately estimating the SASA based on CG structures is extremely challenging. In this work, we developed a deep learning-based SASA estimator (DeepCGSA), which can provide almost perfect SASA estimation based on CG structures of protein and RNA molecules. Extensive testing analysis showed that for three types of widely used CG protein models, including the Cα-based, Cα-Cβ, and Martini models, the correlation coefficients between the predicted values and the reference values can be as high as 0.95-0.99, which perform dramatically better than available methods. In addition, the new method can be used for CG RNA structures and unfolded protein structures with much improved accuracy. We anticipate that DeepCGSA will be highly useful in the protein/RNA structure prediction, drug design, and other applications, in which accurate estimations of SASA for CG biomolecular structures are critically important.

The interest in porous organic materials derived from norbornenes is driven by versatile chemistry of norbornenes, fine-tunable structure of these polymers, high accessible surface area, and large ...

The effect of atomic transfer radical polymerization (ATRP) polymers on the structure and dynamics of a 14.5 kDa RNA binding protein, Rho130, was assessed using NMR. A near-homogeneous sample was generated by optimizing initiator coupling to maximize the number of modified Lys residues. The reactivity of individual Lys residues was correlated with the average solvent accessible surface area from molecular dynamics (MD) simulations and influenced by local interactions. Larger structural changes were seen with the addition of the initiator alone than with polymer growth. Structural changes were localized to the N-terminal helical domain of the protein and MD simulations suggest stabilization of the terminus of one helix by the addition of the ATRP initiator and an initiator-induced change in interhelical angles. Relaxation dispersion shows that polymer addition, but not attachment of the initiator, causes a reduction in the microsecond-millisecond dynamics of the hydrophobic core.

GH11 xylanases are versatile small-molecular-weight single-polypeptide chain monofunctional enzymes. This family of glycoside hydrolases has important applications in food, feed and chemical industries. We designed mutants for improved thermal stability with substitutions in the first six residues of the N-terminal region and evaluated the stability in silico. The first six residues RTITNN of native xylanase have been mutated accordingly to introduce β structure, increase hydrophobic clusters and enhance conformational rigidity in the molecule. To design stable mutants, the approach consisted of constructing root mean square fluctuation (RMSF) plots of both mesophilic and thermophilic xylanases to check the localized backbone displacement maxima, identify the hydrophobic interaction cluster in and around the peaks of interest, construct mutants by substituting appropriate residues based on beta propensity, hydrophobicity, side chain occupancy and conformational rigidity. This resulted in the decreased number of possible substitutions from 19 to 6 residues. Introduction of conformational rigidity by substitution of asparagine residues at 5th and 6th residue position with proline and valine enhanced the stability. Deletion of N-terminal region increased the stability probably by reducing entropic factors. The structure and stability of GH11 xylanase and resultant mutants were analyzed by root mean square deviation, RMSF, radius of gyration and solvent accessible surface area analysis. The stability of the mutants followed the order N-del > Y1P5 >Y1V5 > ATRLM. The contribution of N-terminal end to overall stability of the molecule is significant because of the proximity of the C-terminal end to the N-terminal end which reinforces long-range interactions. Communicated by Ramaswamy H. Sarma.

In humans, cystatin C mediated amyloid aggregation is quite detrimental. It is deemed to actuate intra-cerebral haemorrhaging, stroke, paralysis and further, turns out to be fatal under exigent circumstances. Especially, the domain swapped dimerization of cystatin C is the pathogenic trigger that propels its amyloidosis. Targeting the protein at this initial pathogenic stage could be effective in arresting cystatin C amyloid formation and its eventual aggregation. In our current analysis, using a logically assertive coherent computational pipeline, we have proffered an efficacious peptide based therapeutic (due to its benefits over small molecules) against the domain swapped cystatin C amyloid like dimer (CCAD) pre-fibril. Wherein, the tripeptide, ‘LVN’ has effectually decreased the average beta sheet content (a distinct pathogenic aspect of amyloids) of CCAD from 49 to 43%. Findings from discrete molecular dynamics simulation through intramolecular hydrogen bond analysis, covariance matrix, free energy landscape and solvent accessible surface area have further substantiated that, upon interaction, LVN has steered CCAD from its distinct pathogenic behaviour. Besides, the thermal unfolding simulation indicated that due to LVN’s confluence with CCAD, the phase transition of the complex to a flexible state from a rigid phase, occurs with a relatively lower temperature and energy, compared to peptide unbound pathogenic CCAD. Hence, the consistent findings from various computational tools anticipate that LVN tripeptide could be a potent promising candidate in mitigating cystatin C amyloid aggregation in humans.

This paper presents a computational study to design tailor-made metal–organic frameworks (MOFs) for efficient CO₂ capture in humid conditions. Target-specific MOFs were generated in our computational platform incorporating the Monte Carlo tree search and recurrent neural networks according to the objective function values that combine three requirements of high adsorption performance, experimental accessibility of designed materials, and good hydrophobicity (i.e., the low Henry coefficient of water in pore space) to be applied in humid conditions. With a given input of 27 different combinations of metal node and topology net information extracted from experimental MOFs, our approach successfully designed promising and novel metal–organic frameworks for CO₂ capture, satisfying the three requirements in good balance. Furthermore, the detailed analysis of the structure–property relationship identified that moderate Dᵢ (the diameter of the largest included sphere) of 14.18 A and accessible surface area (ASA) of 1750 m²/g values are desirable for high-performing MOFs for CO₂ capture, which is attributed to the trade-off relationship between good adsorption selectivity (small pore size is desired) and high adsorption capacity (sufficient pore size is necessary).

Porous organic polymers (POPs) consisting of open interconnected pores offer a broad and vast accessible surface area, and thus have been explored extensively in both academia and industry for numerous applications including heterogeneous catalysis, gas separation, gas adsorption/storage, and ion exchange. Introducing the benefits of microporous polymers into the extended π-conjugated organic polymer gives rise to novel materials, namely, conjugated microporous polymers (CMPs), which endow even more intriguing properties/applications, especially in optoelectronics, energy storage, and sensors. In particular, within the domain of CMPs, luminescent CMPs enjoy the advantage of possessing aggregation-induced emission (AIE) and long-range exciton migration accompanied by the intrinsic properties such as microporosity and high surface area. The significant host–guest interactions and fast analyte diffusion facilitated by the microporous environment along with the efficient exciton migration through the polymer network will be fundamental for fast and highly sensitive chemical sensing. The unique structural features in conjunction with the selective properties and encouraging applications of the fluorescent CMPs have triggered a great deal of interest, which have led to rapid progress in the development of structurally diverse fluorescent CMPs. In this review, we present a comprehensive summary of all the advances in the development of fluorescent CMPs based on tetraphenyl ethene (TPE), phenylene, and polycyclic aromatic hydrocarbons (PAHs) and boron- and nitrogen-based π-systems and their emerging applications in numerous fields as well as our perspectives on future research.

Highly efficient capacitive deionization (CDI) relies on unimpeded transport of salt ions to the electrode surface. Graphene is an ideal candidate to provide superb conditions for ion adsorption as it possesses high theoretical surface area and electrical conductivity. When ions are stored solely within the electric double layers (EDLs), a hydrophilic graphene surface with hierarchical pores can maximize the accessible surface area and promote the ion transport. In the case of synergistic ion storage via electrostatic adsorption and faradaic redox reaction, graphene can act as both the electron highway and the reciprocal spacer to provide surface-confined effects. Substantially, structural and chemical engineering towards graphene can enhance the ion removal capacity and rate, and improve the charge efficiency and ion selectivity. In this review, we keep pace with the in-depth studies of CDI technologies and recent progress on graphene-based materials for CDI. Major challenges in the rational assembly of the desired material functionalities in terms of surface area, pore structure, and hydrophilicity are addressed. As electrode materials develop, the ultimate goal is to achieve highly efficient, energy-saving, and environment-friendly CDI.

In this paper, a novel approach is proposed based on the accurate computation of the inaccessible volume and the corresponding surface area which is defined by the locus of points where a ligand molecule can be placed so that it “touches” a protein molecule at a preset minimum interatomic distance without resulting in overlaps between the atoms of the protein and the atoms of the ligand. The proposed approach can be considered an extension of the widely used concept of the solvent accessible surface area (SASA). The SASA is defined as the surface where a solvent molecule can be in contact with the initial one without any overlaps. This excluded volume interaction is evaluated by treating atoms as hard core spheres, with the limitation of the solvent molecule being represented as a single sphere. In the proposed concepts of the molecular accessible surface (MASA) and the molecular inaccessible volume (MIV) we have practically removed this limitation and all atoms, both in the initial and the “inserted” molecules, are represented as hard spheres. In this paper we focus our examples on biological systems, especially on studying protein–ligand systems, since we expect that this will be one of the most promising fields of applications where the MASA and MIV extensions of the SASA will be of practical and immediate use. Therefore, the MASA and MIV are evaluated based on the surface generated by the ligand while it is being rolled over on all the atoms of the protein without penetrating them. Identification of the inaccessible volume of each candidate protein–ligand pair is also provided in the context of this study, along with the boundary surface where the ligand can be placed so as to be in “contact” with the protein. The proposed concepts of the MASA and MIV are expected to significantly enhance the ability to investigate specific protein–drug interactions by explicitly taking into account the polyatomic nature of a ligand. Several trials have been conducted using the analytical method of Dodd and Theodorou leading to accurate volume and surface area measurements of an arbitrary set of fused spheres in systems of various scales.

In this work, we studied the sintering process of two homogeneous polycyclic aromatic hydrocarbon (PAH) clusters with diameters in the range of 3–6 nm using molecular dynamics (MD) simulations. The sintering process was quantified through monitoring the solvent accessible surface area (SASA) and the distance between the center of mass (COM) of the two PAH clusters. The effect of temperature and crosslinking level of PAH clusters on sintering was investigated. The results show that the sintering rate of two PAH clusters at a certain temperature T is largely dependent on the melting point (TMP) of the PAH cluster. When T is higher than TMP, the characteristic sintering time (τs) is around 10 − 2 ns and sintering is not affected by the crosslinking level as the PAH clusters are liquid-like. In contrast, when T is much lower than TMP, the PAH clusters sinter rather slowly with τs > 5 ns, and the sintering process is hindered by the crosslinks between PAH molecules within solid-like PAH clusters due to the enhanced steric effect.

Background Proteases are key drivers in many biological processes, in part due to their specificity towards their substrates. However, depending on the family and molecular function, they can also display substrate promiscuity which can also be essential. Databases compiling specificity matrices derived from experimental assays have provided valuable insights into protease substrate recognition. Despite this, there are still gaps in our knowledge of the structural determinants. Here, we compile a set of protease crystal structures with bound peptide-like ligands to create a protocol for modelling substrates bound to protease structures, and for studying observables associated to the binding recognition. Results As an application, we modelled a subset of protease–peptide complexes for which experimental cleavage data are available to compare with informational entropies obtained from protease–specificity matrices. The modelled complexes were subjected to conformational sampling using the Backrub method in Rosetta, and multiple observables from the simulations were calculated and compared per peptide position. We found that some of the calculated structural observables, such as the relative accessible surface area and the interaction energy, can help characterize a protease’s substrate recognition, giving insights for the potential prediction of novel substrates by combining additional approaches. Conclusion Overall, our approach provides a repository of protease structures with annotated data, and an open source computational protocol to reproduce the modelling and dynamic analysis of the protease–peptide complexes.

BackgroundPredicting physical interaction between proteins is one of the greatest challenges in computational biology. There are considerable various protein interactions and a huge number of protein sequences and synthetic peptides with unknown interacting counterparts. Most of co-evolutionary methods discover a combination of physical interplays and functional associations. However, there are only a handful of approaches which specifically infer physical interactions. Hybrid co-evolutionary methods exploit inter-protein residue coevolution to unravel specific physical interacting proteins. In this study, we introduce a hybrid co-evolutionary-based approach to predict physical interplays between pairs of protein families, starting from protein sequences only.ResultsIn the present analysis, pairs of multiple sequence alignments are constructed for each dimer and the covariation between residues in those pairs are calculated by CCMpred (Contacts from Correlated Mutations predicted) and three mutual information based approaches for ten accessible surface area threshold groups. Then, whole residue couplings between proteins of each dimer are unified into a single Frobenius norm value. Norms of residue contact matrices of all dimers in different accessible surface area thresholds are fed into support vector machine as single or multiple feature models. The results of training the classifiers by single features show no apparent different accuracies in distinct methods for different accessible surface area thresholds. Nevertheless, mutual information product and context likelihood of relatedness procedures may roughly have an overall higher and lower performances than other two methods for different accessible surface area cut-offs, respectively. The results also demonstrate that training support vector machine with multiple norm features for several accessible surface area thresholds leads to a considerable improvement of prediction performance. In this context, CCMpred roughly achieves an overall better performance than mutual information based approaches. The best accuracy, sensitivity, specificity, precision and negative predictive value for that method are 0.98, 1, 0.962, 0.96, and 0.962, respectively.ConclusionsIn this paper, by feeding norm values of protein dimers into support vector machines in different accessible surface area thresholds, we demonstrate that even small number of proteins in pairs of multiple alignments could allow one to accurately discriminate between positive and negative dimers.

The hydrophobic effect plays a key role in many chemical and biological processes, including protein folding. Nonetheless, a comprehensive picture of the effect of temperature on hydrophobic hydration and protein denaturation remains elusive. Here, we study the effect of temperature on the hydration of model hydrophobic and amphiphilic solutes, through molecular dynamics, aiming at getting insight on the singular behavior of water, concerning the zero-entropy temperature, TS, and entropy convergence, TS*, also observed for some proteins, upon denaturation. We show that, similar to hydrocarbons, polar amphiphilic solutes exhibit a TS, although strongly dependent on solute-water interactions, opposite to hydrocarbons. Further, the temperature dependence of the hydration entropy, normalized by the solvent accessible surface area, is shown to be nearly solute size independent for hydrophobic but not for amphiphilic solutes, for similar reasons. These results are further discussed in the light of information theory (IT) and the structure of water around hydrophobic groups. The latter shows that the tetrahedral enhancement of some water molecules around hydrophobic groups, associated with the reduction of water defects, leads to the strengthening of the weakest hydrogen bonds, relative to bulk water. In addition, a larger tetrahedrality is found in low density water populations, demonstrating that pure water has encoded structural information, similar to that associated with hydrophobic hydration. The reversal of the hydration entropy dependence on the solute size, above TS*, is also analyzed and shown to be associated with a greater loss of water molecules exhibiting enhanced orientational order, in the coordination sphere of large solutes. Finally, the source of the differences between Kauzmann's "hydrocarbon model" on protein denaturation and hydrophobic hydration is discussed, with relatively large amphiphilic hydrocarbons seemingly displaying a more similar behavior to some globular proteins than aliphatic hydrocarbons.

The effects of metalation process by inorganic compounds containing Au, Pt and Ru on protein structure and on conformation and flexibility of the residues involved in the metal compound binding have been here investigated by analysing 204 structures of protein/metallodrug adducts and the corresponding metal-free forms. The overall structure of the proteins is not significantly affected by the metal label. 162 non-redundant protein residues involved in Au, Pt and Ru coordination have been identified. In the metal-free protein structures these residues often belong to α-helical regions and show low flexibility. They do not necessarily belong to outer layers of the protein structure. In the majority of the adducts, the side chains of these residues adopt a conformation that is similar to that observed in the metal-free protein. The metal coordination reduces their solvent accessible surface area without altering their overall flexibility. These results could be useful for the prediction of residues able to bind Au, Pt and Ru compounds.

Hot spot residues at protein–DNA binding interfaces are hugely important for investigating the underlying mechanism of molecular recognition. Currently, there are a few tools available for identifying the hot spot residues in the protein–DNA complexes. In addition, the three-dimensional protein structures are needed in these tools. However, it is well known that the three-dimensional structures are unavailable for most proteins. Considering the limitation, we proposed a method, named SPDH, for predicting hot spot residues only based on protein sequences. Firstly, we obtained 133 features from physicochemical property, conservation, predicted solvent accessible surface area and structure. Then, we systematically assessed these features based on various feature selection methods to obtain the optimal feature subset and compared the models using four classical machine learning algorithms (support vector machine, random forest, logistic regression, and k-nearest neighbor) on the training dataset. We found that the variability of physicochemical property features between wild and mutative types was important on improving the performance of the prediction model. On the independent test set, our method achieved the performance with AUC of 0.760 and sensitivity of 0.808, and outperformed other methods. The data and source code can be downloaded at https://github.com/xialab-ahu/SPDH .

A one‐dimensional nanotubular metal–organic framework (MOF) [Ni(Cu‐H4TPPA)]⋅2 (CH3)2NH2 + (H8TPPA=5,10,15,20‐tetrakis[p‐phenylphosphonic acid] porphyrin) constructed by using the arylphosphonic acid H8TPPA is reported. The structure of this MOF, known as GTUB‐4, was solved by using single‐crystal X‐ray diffraction and its geometric accessible surface area was calculated to be 1102 m2 g−1, making it the phosphonate MOF with the highest reported surface area. Due to the extended conjugation of its porphyrin core, GTUB‐4 possesses narrow indirect and direct bandgaps (1.9 eV and 2.16 eV, respectively) in the semiconductor regime. Thermogravimetric analysis suggests that GTUB‐4 is thermally stable up to 400 °C. Owing to its high surface area, low bandgap, and high thermal stability, GTUB‐4 could find applications as electrodes in supercapacitors., A 1D nanotubular MOF, GTUB‐4, was constructed by using the highly conjugated arylphosphonic acid H8‐TPPA. The structure of this metal–organic framework (MOF) was solved by using single‐crystal X‐ray. GTUB‐4 is characterized by high surface area and, due to the extended conjugation of its porphyrin core, possesses narrow indirect and direct bandgaps in the semiconductor regime. Owing to its high surface area, low band gap, and high thermal stability, GTUB‐4 could find applications as electrode material in supercapacitors.

Background Profilaggrin belongs to the S100 fused-type protein family expressed in keratinocytes and is important for skin barrier integrity. Its N-terminus contains an S100 (“A”) domain and a unique “B” domain with a nuclear localization sequence. Objective To determine whether profilaggrin B domain cooperates with the S100 domain to bind macromolecules. To characterize the biochemical and structural properties of the profilaggrin N-terminal “AB” domain and compare it to other S100 fused-type proteins. Methods We used biochemical (protease protection, light scattering, fluorescence spectroscopy, pull-down assays) and computational techniques (sequence analysis, molecular modeling with crystallographic structures) to examine human profilaggrin and S100 fused-type proteins. Results Comparing profilaggrin S100 crystal structure with models of the other S100 fused-type proteins demonstrated each has a unique chemical composition of solvent accessible surface around the hydrophobic binding pocket. S100 fused-type proteins exhibit higher pocket hydrophobicity than soluble S100 proteins. The inter-EF-hand linker in S100 fused-type proteins contains conserved hydrophobic residues involved in binding substrates. Profilaggrin B domain cooperates with the S100 domain to bind annexin II and keratin intermediate filaments in a calcium-dependent manner using exposed cationic surface. Using molecular modeling we demonstrate profilaggrin B domain likely interacts with annexin II domains I and II. Steric clash analysis shows annexin II N-terminal peptide is favored to bind profilaggrin among S100 fused-type proteins. Conclusion The N-terminal S100 and B domains of profilaggrin cooperate to bind substrate molecules in granular layer keratinocytes to provide epidermal barrier functions.

Phosphorylation ofEscherichia coliCheY protein transduces chemoreceptor stimulation to a highly cooperative flagellar motor response. CheY binds to the N-terminal peptide of the FliM motor protein (FliMN). Constitutively active D13K-Y106W CheY has been an important tool for motor physiology. The crystal structures of CheY and CheY.FliMNwith and without D13K-Y106W have shown FliMNbound CheY contains features of both active and inactive states. We used molecular dynamics (MD) simulations to characterize the CheY conformational landscape accessed by FliMNand D13K-Y106W. Mutual information measures identified the central features of the long-range CheY allosteric network between D13K at the D57 phosphorylation site and Y/W106 at the FliMNinterface; namely the closure of the α4-β4 hinge and inward rotation of Y/W106 with W58. We used hydroxy-radical foot-printing with mass spectroscopy (XFMS) to track the solvent accessibility of these and other sidechains. The solution XFMS oxidation rate correlated with the solvent-accessible area of the crystal structures. The protection of allosteric relay sidechains reported by XFMS confirmed the intermediate conformation of the native CheY.FliMNcomplex, 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/W106 sidechain burial correlated with increased FliMNaffinity. Activation entrained CheY fold stabilization to FliMNaffinity. The CheY network could be partitioned into four dynamically coordinated community sectors. Residue substitutions mapped to sectors around D57 or the FliMNinterface according to phenotype. FliMNincreased sector size and interactions. These sectors fused between the substituted K13K-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.Statement of SignificanceCheY affinity for FliMN, its binding target at the flagellar motor, is increased by phosphorylation to switch rotation sense. Atomistic simulations based on CheY and CheY.FliMNcrystal structures with and without the phospho-mimetic double substitution (D13K-Y106W) showed CheY compaction is entrained to increased FliMNaffinity. Burial of exposed aromatic sidechains drove compaction, as validated by tracking sidechain solvent accessibility with hydroxyl-radical foot-printing. The substitutions were localized at the phosphorylation pocket (D13K) and FliMNinterface (Y106W). Mutual information measures revealed these locations were allosterically coupled by a specialized conduit when the conformational landscape of FliMN-tethered CheY was modified by the substitutions. Novel surfaces stabilized by the conduit may bind additional motor sites, essential for the high cooperativity of the flagellar switch.

Tetracycline is one of the most commonly used antibiotics in a wide range of antibacterial drugs. Self-association of drugs (e.g. antibiotics) causes problems, such as increasing toxicity and reducing penetration of drugs through cell membranes. In this study, the self-association process of tetracycline was investigated experimentally and theoretically in aqueous, ethanol, and salt solutions. Spectroscopy studies showed that the self-association process occurred in salt solution at lower concentrations of tetracycline in comparison with the other two solutions. However, the presence of ethanol led to a delay in the self-association process. The self-association constants of tetracycline were obtained by using experimental values. Moreover, the analysis of the number of clusters and solvent accessible surface area were carried out by molecular dynamics (MD) simulations. The MD results clarified that the tetracycline self-association process happened earlier in salt solution compared to the others through forming the larger clusters by the hydrophobic interactions, whereas the presence of ethanol caused a reduction in the self-association process and the cluster populations through weakening the hydrophobic interactions. Furthermore, the type of the involved interactions in the formation of the tetracycline clusters was investigated by RDG analysis. The obtained results revealed that van der Waals interactions possessed a fundamental influence on the formation of tetracycline clusters.

Nanotechnologies have changed this world in various aspects including the oral medicine. It has been demonstrated that silver (Ag) nanomaterials can exhibit strong inhibition and killing effect on oral bacteria. Furthermore, the Ag nanomaterials have superb antimicrobial activity and nonacute toxic effects on human cells. Previously, the impact of Ag on oral bacteria was demonstrated by experiments. In this work, we applied molecular dynamics (MD) simulations to investigate the influence of Ag nanomaterials on oral bacteria. Firstly, by comparing change of molecular structure of staphylococcal protein A (SPA) with and without Ag, we found that Ag nanomaterials have strong effect on evolution of protein secondary structure of SPA. Secondly, it was observed that Ag has negligible effect on Solvent Accessible Surface Area (SASA) of SPA indicating that the Ag only changed its microstructure. Finally, it was found that the average amount of hydrogen bond in SPA was reduced in the presence of Ag which was origin of antimicrobial activity of Ag. It is believed that the growing interest in dental medicine with nanomaterials would lead molecular dynamics simulations to be an effective method for studying inhibition and killing pathological process of nanomaterials on oral bacteria.

Background:There is a large inter-individual variation in cytochrome P450 2C19 (CYP2C19) activity. The variability can be caused by the genetic polymorphism of CYP2C19 gene. This study aimed to investigate the molecular and kinetics basis for activity changes in three alleles including CYP2C19*23, CYP2C19*24 and CYP2C19*25found in the Chinese population.Methods:The three variants expressed by bacteria were investigated using substrate (omeprazole and 3- cyano-7-ethoxycoumarin[CEC]) and inhibitor (ketoconazole, fluoxetine, sertraline and loratadine) probes in enzyme assays along with molecular docking.Results:All alleles exhibited very low enzyme activity and affinity towards omeprazole and CEC (6.1% or less in intrinsic clearance). The inhibition studies with the four inhibitors, however, suggested that mutations in different variants have a tendency to cause enhanced binding (reduced IC50 values). The enhanced binding could partially be explained by the lower polar solvent accessible surface area of the inhibitors relative to the substrates. Molecular docking indicated that G91R, R335Q and F448L, the unique mutations in the alleles, have caused slight alteration in the substrate access channel morphology and a more compact active site cavity hence affecting ligand access and binding. It is likely that these structural alterations in CYP2C19 proteins have caused ligand-specific alteration in catalytic and inhibitory specificities as observed in the in vitro assays.Conclusion:This study indicates that CYP2C19 variant selectivity for ligands was not solely governed by mutation-induced modifications in the active site architecture, but the intrinsic properties of the probe compounds also played a vital role.

Prostate-specific antigen (PSA) is a high molecular weight glycoprotein that is used as a marker for the diagnosis of prostate cancer and is therefore important in the medical field. In this study, a novel sandwich type immunoassay was designed based on encapsulation of biotinylated antibody into KCC-1-npr-NH2. KCC-1-npr-NH2 stabilized the stability of the primary antibody. So, encapsulated Ab1 was immobilized on the surface of glassy carbon electrode. Field emission scanning electron microscope (FE-SEM) was employed to monitor the sensor fabrication. The engineered immunosensor was used for the detection of PSA using differential pulse voltammetry (DPVs) and square wave voltammetry (SWVs) techniques. The proposed interface lead to enhancement of accessible surface area for immobilizing a high amount of anti-PSA antibody, increasing electrical conductivity, boosting stability, catalytic properties and biocompatibility. The intensity of electrochemical signals is also increased by the use of AuNPs functionalized with CysA used in secondary antibody (HRP conjugated PSA) structure. Under optimal conditions, the designed immuno-assay provide a good analytical performance for quantifying the PSA marker in the linear range of 1 to 60 μg/l.

Wide-line 1 H NMR measurements were extended and all results were interpreted in a thermodynamics-based new approach on aqueous solutions of thymosin-β4 (Tβ4 ), stabilin cytoplasmic domain (CTD), and their 1 : 1 complex. Energy distributions of potential barriers controlling the motion of protein-bound water molecules were determined. Heterogeneous and homogeneous regions were found in the protein-water interface. The measure of heterogeneity of this interface gives quantitative value for the portion of disordered parts in the protein. Ordered structural elements were found extending up to ∼20 % of the individual whole proteins. About 40 % of the binding sites of free Tβ4 get involved in bonds holding the complex together. The complex has the most heterogeneous solvent accessible surface (SAS) in terms of protein-water interactions. The complex is more disordered than Tβ4 or stabilin CTD. The greater SAS area of the complex is interpreted as a clear sign of its open structure.