Identification of low-frequency modes in protein molecules

Use Chou's 5-Steps Rule With Different Word Embedding Types to Boost Performance of Electron Transport Protein Prediction Model

Living organisms receive necessary energy substances directly from cellular respiration. The completion of electron storage and transportation requires the process of cellular respiration with the aid of electron transport chains. Therefore, the work of deciphering electron transport proteins is inevitably needed. The identification of these proteins with high performance has a prompt dependence on the choice of methods for feature extraction and machine learning algorithm. In this study, protein sequences served as natural language sentences comprising words. The nominated word embedding-based feature sets, hinged on the word embedding modulation and protein motif frequencies, were useful for feature choosing. Five word embedding types and a variety of conjoint features were examined for such feature selection. The support vector machine algorithm consequentially was employed to perform classification. The performance statistics within the 5-fold cross-validation including average accuracy, specificity, sensitivity, as well as MCC rates surpass 0.95. Such metrics in the independent test are 96.82, 97.16, 95.76 percent, and 0.9, respectively. Compared to state-of-the-art predictors, the proposed method can generate more preferable performance above all metrics indicating the effectiveness of the proposed method in determining electron transport proteins. Furthermore, this study reveals insights about the applicability of various word embeddings for understanding surveyed sequences.

Dissipative Particle Dynamics Simulation of Ultrasound Propagation through Liquid Water

Ultrasound is widely used as a noninvasive method in therapeutic and diagnostic applications. These can be further optimized by computational approaches, as they allow for controlled testing and rational optimization of the ultrasound parameters, such as frequency and amplitude. Usually, continuum numerical methods are used to simulate ultrasound propagating through different tissue types. In contrast, ultrasound simulations using particle description are less common, as the implementation is challenging. In this work, a dissipative particle dynamics model is used to perform ultrasound simulations in liquid water. The effects of frequency and thermostat parameters are studied and discussed. We show that frequency and thermostat parameters affect not only the attenuation but also the computed speed of sound. The present study paves the way for development and optimization of a virtual ultrasound machine for large-scale biomolecular simulations.

An Insightful 10-year Recollection Since the Emergence of the 5-steps Rule

OBJECTIVE

One of the most challenging and also the most difficult problems is how to formulate a biological sequence with a vector but considerably keep its sequence order information.

METHODS

To address such a problem, the approach of Pseudo Amino Acid Components or PseAAC has been developed.

RESULTS AND CONCLUSION

It has become increasingly clear via the 10-year recollection that the aforementioned proposal has been indeed very powerful.

Characterization of the relationship between FLI1 and immune infiltrate level in tumour immune microenvironment for breast cancer

Breast cancer is the most common cancer and the leading cause of cancer death among women in the world. Tumour‐infiltrating lymphocytes were defined as the white blood cells left in the vasculature and localized in tumours. Recently, tumour‐infiltrating lymphocytes were found to be associated with good prognosis and response to immunotherapy in tumours. In this study, to examine the influence of FLI1 in immune system in breast cancer, we interrogated the relationship between the FLI1 expression levels with infiltration levels of 28 immune cell types. By splitting the breast cancer samples into high and low expression FLI1 subtypes, we found that the high expression FLI1 subtype was enriched in many immune cell types, and the up‐regulated differentially expressed genes between them were enriched in immune system processes, immune‐related KEGG pathways and biological processes. In addition, many important immune‐related features were found to be positively correlated with the FLI1 expression level. Furthermore, we found that the FLI1 was correlated with the immune‐related genes. Our findings may provide useful help for recognizing the relationship between tumour immune microenvironment and FLI1, and may unravel clinical outcomes and immunotherapy utility for FLI1 in breast cancer.

Surface-Enhanced Raman Spectroscopy Characterization of Breast Cell Phenotypes: Effect of Nanoparticle Geometry

The use of surface-enhanced Raman spectroscopy (SERS) to delineate between the breast epithelial cell lines MCF10A, SK-BR-3, and MDA-MB-231 is explored utilizing varied morphologies of gold nanoparticles. The nanoparticles studied had spherical, star-like, and quasi-fractal (nanocaltrop) morphologies and possessed varying degrees of surface inhomogeneity and complexity. The efficacy of Raman enhancement of these nanoparticles was a function of their size, their surface morphology, and the associated density of "hot spots," as well as their cellular uptake. The spherical and star-like nanoparticles provided strong signal enhancement that allowed for the discernment among the three cell phenotypes based solely on the acquired Raman spectra. The presence of overlapping Raman band spectral regions, as well as unique spectral bands, suggests that the underlying biological differences between these cells can be accessed without the need for tagging the nanoparticles or for specific cell targeting, demonstrating the potential ubiquity of this technique in imaging any cancer. This work provides clear evidence for the potential application of SERS as a tool for mapping cancerous lesions, possibly during surgery and under histopathological analysis.

Raman Signal Enhancement by Quasi-Fractal Geometries of Au Nanoparticles

The synthesis of star-like gold nanoparticles (SGNs) in a temperature-controlled environment allows for temperature modulation and facilitates the growth of highly branched nanoparticles. By increasing the synthesis temperature, the level of branching increases as well. These highly branched features represent a distinctly novel, quasi-fractal nanoparticle morphology, referred to herein as gold nano caltrops (GNC). The increased surface roughness, local curvature and degree of inhomogeneity of GNC lend themselves to generating improved enhancement of the scattering signals in surface-enhanced Raman spectroscopy (SERS) via a mechanism in which the localized surface plasmon sites, or "hot spots," provide the engine for the signal amplification, rather than the more conventional surface plasmon. Here, the synthesis procedure and the surface-enhancing capabilities of GNC are described and discussed.

Mechanistic Insights of Chemicals and Drugs as Risk Factors for Systemic Lupus Erythematosus

Systemic Lupus Erythematosus (SLE) is a chronic and relapsing heterogenous autoimmune disease that primarily affects women of reproductive age. Genetic and environmental risk factors are involved in the pathogenesis of SLE, and susceptibility genes have recently been identified. However, as gene therapy is far from clinical application, further investigation of environmental risk factors could reveal important therapeutic approaches. We systematically explored two groups of environmental risk factors: chemicals (including silica, solvents, pesticides, hydrocarbons, heavy metals, and particulate matter) and drugs (including procainamide, hydralazine, quinidine, Dpenicillamine, isoniazid, and methyldopa). Furthermore, the mechanisms underlying risk factors, such as genetic factors, epigenetic change, and disrupted immune tolerance, were explored. This review identifies novel risk factors and their underlying mechanisms. Practicable measures for the management of these risk factors will benefit SLE patients and provide potential therapeutic strategies.

Carbon Nanotubes' Effect on Mitochondrial Oxygen Flux Dynamics: Polarography Experimental Study and Machine Learning Models using Star Graph Trace Invariants of Raman Spectra

This study presents the impact of carbon nanotubes (CNTs) on mitochondrial oxygen mass flux (J_m) under three experimental conditions. New experimental results and a new methodology are reported for the first time and they are based on CNT Raman spectra star graph transform (spectral moments) and perturbation theory. The experimental measures of J_m showed that no tested CNT family can inhibit the oxygen consumption profiles of mitochondria. The best model for the prediction of J_m for other CNTs was provided by random forest using eight features, obtaining test R-squared (R²) of 0.863 and test root-mean-square error (RMSE) of 0.0461. The results demonstrate the capability of encoding CNT information into spectral moments of the Raman star graphs (SG) transform with a potential applicability as predictive tools in nanotechnology and material risk assessments.

Experimental-Computational Study of Carbon Nanotube Effects on Mitochondrial Respiration: In Silico Nano-QSPR Machine Learning Models Based on New Raman Spectra Transform with Markov-Shannon Entropy Invariants

The study of selective toxicity of carbon nanotubes (CNTs) on mitochondria (CNT-mitotoxicity) is of major interest for future biomedical applications. In the current work, the mitochondrial oxygen consumption (E3) is measured under three experimental conditions by exposure to pristine and oxidized CNTs (hydroxylated and carboxylated). Respiratory functional assays showed that the information on the CNT Raman spectroscopy could be useful to predict structural parameters of mitotoxicity induced by CNTs. The in vitro functional assays show that the mitochondrial oxidative phosphorylation by ATP-synthase (or state V3 of respiration) was not perturbed in isolated rat-liver mitochondria. For the first time a star graph (SG) transform of the CNT Raman spectra is proposed in order to obtain the raw information for a nano-QSPR model. Box-Jenkins and perturbation theory operators are used for the SG Shannon entropies. A modified RRegrs methodology is employed to test four regression methods such as multiple linear regression (LM), partial least squares regression (PLS), neural networks regression (NN), and random forest (RF). RF provides the best models to predict the mitochondrial oxygen consumption in the presence of specific CNTs with R² of 0.998-0.999 and RMSE of 0.0068-0.0133 (training and test subsets). This work is aimed at demonstrating that the SG transform of Raman spectra is useful to encode CNT information, similarly to the SG transform of the blood proteome spectra in cancer or electroencephalograms in epilepsy and also as a prospective chemoinformatics tool for nanorisk assessment. All data files and R object models are available at https://dx.doi.org/10.6084/m9.figshare.3472349 .

Insight into a molecular interaction force supporting peptide backbones and its implication to protein loops and folding

Although not being classified as the most fundamental protein structural elements like α-helices and β-strands, the loop segment may play considerable roles for protein stability, flexibility, and dynamic activity. Meanwhile, the protein loop is also quite elusive; i.e. its interactions with the other parts of protein as well as its own shape-maintaining forces have still remained as a puzzle or at least not quite clear yet. Here, we report a molecular force, the so-called polar hydrogen-π interaction (Hp-π), which may play an important role in supporting the backbones of protein loops. By conducting the potential energy surface scanning calculations on the quasi π-plane of peptide bond unit, we have observed the following intriguing phenomena: (1) when the polar hydrogen atom of a peptide unit is perpendicularly pointing to the π-plane of other peptide bond units, a remarkable Hp-π interaction occurs; (2) the interaction is distance and orientation dependent, acting in a broad space, and belonging to the 'point-to-plane' one. The molecular force reported here may provide useful interaction concepts and insights into better understanding the loop's unique stability and flexibility feature, as well as the driving force of the protein global folding.

Continuous-Wave Stimulated Raman Scattering (cwSRS) Microscopy

Stimulated Raman scattering (SRS) microscopy is a powerful tool for chemically-sensitive non-invasive optical imaging. However, ultrafast laser sources, which are currently employed, are still expensive and require substantial maintenance to provide temporal overlap and spectral tuning. SRS imaging, which utilizes continuous-wave laser sources, has a major advantage, as it eliminates the cell damage due to exposure to the high-intensity light radiation, while substantially reducing the cost and complexity of the set-up. As a proof-of-principle, we demonstrate microscopic imaging of dimethyl sulfoxide using two independent, commonly used lasers, a diode-pumped, intracavity doubled 532-nm laser and a He-Ne laser operating at 632.8-nm.

Efficient Raman frequency conversion by coherent feedback at low light intensity

We experimentally demonstrate efficient Raman conversion to respective Stokes and anti-Stokes fields in both pulsed and continuous modes with a Rb-87 atomic vapor cell. The conversion efficiency is about 40-50% for the Stokes field and 20-30% for the anti-Stokes field, respectively. This efficient conversion process is realized with coherent feedback of both the Raman pump and the frequency-converted fields (Stokes or anti-Stokes). The experimental setup is simple and can be applied easily to produce light sources with larger frequency shifts using other Raman media with long coherence time. They may have potential applications in nonlinear optics, Raman spectroscopy and precision measurement.

Two birds with one stone? Possible dual-targeting H1N1 inhibitors from traditional Chinese medicine

The H1N1 influenza pandemic of 2009 has claimed over 18,000 lives. During this pandemic, development of drug resistance further complicated efforts to control and treat the widespread illness. This research utilizes traditional Chinese medicine Database@Taiwan (TCM Database@Taiwan) to screen for compounds that simultaneously target H1 and N1 to overcome current difficulties with virus mutations. The top three candidates were de novo derivatives of xylopine and rosmaricine. Bioactivity of the de novo derivatives against N1 were validated by multiple machine learning prediction models. Ability of the de novo compounds to maintain CoMFA/CoMSIA contour and form key interactions implied bioactivity within H1 as well. Addition of a pyridinium fragment was critical to form stable interactions in H1 and N1 as supported by molecular dynamics (MD) simulation. Results from MD, hydrophobic interactions, and torsion angles are consistent and support the findings of docking. Multiple anchors and lack of binding to residues prone to mutation suggest that the TCM de novo derivatives may be resistant to drug resistance and are advantageous over conventional H1N1 treatments such as oseltamivir. These results suggest that the TCM de novo derivatives may be suitable candidates of dual-targeting drugs for influenza.

Do dynamic effects play a significant role in enzymatic catalysis? A theoretical analysis of formate dehydrogenase

A theoretical study of the protein dynamic effects on the hydride transfer between the formate anion and nicotinamide adenine dinucleotide (NAD(+)), catalyzed by formate dehydrogenase (FDH), is presented in this paper. The analysis of free downhill molecular dynamic trajectories, performed in the enzyme and compared with the reaction in aqueous solution, has allowed the study of the dynamic coupling between the reacting fragments and the protein or the solvent water molecules, as well as an estimation of the dynamic effect contribution to the catalytic effect from calculation of the transmission coefficient in the enzyme and in solution. The obtained transmission coefficients for the enzyme and in solution were 0.46±0.04 and 0.20±0.03, respectively. These values represent a contribution to catalysis of 0.5 kcal mol(-1), which, although small, is not negligible keeping in mind the low efficiency of FDH. The analysis of the reactive trajectories also reveals how the relative movements of some amino acids, mainly His332 and Arg284, precede and promote the chemical reaction. In spite of these movements, the time-dependent evolution of the electric field created by the enzyme on the key atoms of the reaction reveals a permanent field, which reduces the work required to reach the transition state, with a concomitant polarization of the cofactor. Finally, application of Grote-Hynes theory has allowed the identification of the modes responsible for the substrate-environment coupling, showing how some protein motions take place simultaneously with the reaction. Thus, the equilibrium approach would provide, in this case, an overestimation of the catalyzed rate constant.

Insights from studying the mutation-induced allostery in the M2 proton channel by molecular dynamics

As an essential component of the viral envelope, M2 proton channel plays a central role in the virus replications and has been a key target for drug design against the influenza A viruses. The adamantadine-based drugs, such as amantadine and rimantadine, were developed for blocking the channel so as to suppress the replication of viruses. However, patients, especially those infected by the H1N1 influenza A viruses, are increasingly suffering from the drug-resistance problem. According to the findings revealed recently by the high-resolution NMR studies, the drug-resistance problem is due to the structural allostery caused by some mutations, such as L26F, V27A and S31N, in the four-helix bundle of the channel. In this study, we are to address this problem from a dynamic point of view by conducting molecular dynamics (MD) simulations on both the open and the closed states of the wild-type (WT) and S31N mutant M2 channels in the presence of rimantadine. It was observed from the MD simulated structures that the mutant channel could still keep open even if binding with rimantadine, but the WT channel could not. This was because the mutation would destabilize the helix bundle and trigger it from a compact packing state to a loose one. It is anticipated that the findings may provide useful insights for in-depth understanding the action mechanism of the M2 channel and developing more-effective drugs against influenza A viruses.

Molecular modeling of BAD complex resided in a mitochondrion integrating glycolysis and apoptosis

BAD (Bcl-2 antagonist of cell death) and GK (glucokinase) reside in a mitochondrial complex together with PKA and PP1 catalytic units (PKAc and PP1c) and WAVE-1 that integrates glycolysis and apoptosis. Our research results reveal that BAD is phosphorylated and inactivated on Ser 75 in a BAD-Bcl-xL complex by PKA (targeted to mitochondria through association with WAVE1), resulting in the dissociation of BAD and its binding to GK. Moreover, GK can interact with PP1c and also distinguish WAVE1. On the other hand, BAD is dephosphorylated and activated on Ser75 by PP1c, leading to the separation of PKAc and its binding to the regulatory (R) subunit of PKA which by the dimerization domain of its R subunit connects with WAVE1 linked with GK of the complex. This may be the reason of the complex existing in liver mitochondria, regardless of phosphorylated and dephosphorylated BAD. Additionally, GK like PKA may also prevent Bcl-xL from rebinding to BAD by phosphorylating BAD at Ser 118. The BAD complex model reveals that BAD and GK play key roles because of BAD as a substrate for the PKA-PP1 pair and by BH3 domain directly interacting with GK. This is helpful for our development and research of the molecular mechanism of BAD integrating glycolysis and apoptosis.

Trends in global warming and evolution of matrix protein 2 family from influenza A virus

The global warming is an important factor affecting the biological evolution, and the influenza is an important disease that threatens humans with possible epidemics or pandemics. In this study, we attempted to analyze the trends in global warming and evolution of matrix protein 2 family from influenza A virus, because this protein is a target of anti-flu drug, and its mutation would have significant effect on the resistance to anti-flu drugs. The evolution of matrix protein 2 of influenza A virus from 1959 to 2008 was defined using the unpredictable portion of amino-acid pair predictability. Then the trend in this evolution was compared with the trend in the global temperature, the temperature in north and south hemispheres, and the temperature in influenza A virus sampling site, and species carrying influenza A virus. The results showed the similar trends in global warming and in evolution of M2 proteins although we could not correlate them at this stage of study. The study suggested the potential impact of global warming on the evolution of proteins from influenza A virus.

Scoring function for DNA-drug docking of anticancer and antiparasitic compounds based on spectral moments of 2D lattice graphs for molecular dynamics trajectories

We introduce here a new class of invariants for MD trajectories based on the spectral moments pi(k)(L) of the Markov matrix associated to lattice network-like (LN) graph representations of Molecular Dynamics (MD) trajectories. The procedure embeds the MD energy profiles on a 2D Cartesian coordinates system using simple heuristic rules. At the same time, we associate the LN with a Markov matrix that describes the probabilities of passing from one state to other in the new 2D space. We construct this type of LNs for 422 MD trajectories obtained in DNA-drug docking experiments of 57 furocoumarins. The combined use of psoralens+ultraviolet light (UVA) radiation is known as PUVA therapy. PUVA is effective in the treatment of skin diseases such as psoriasis and mycosis fungoides. PUVA is also useful to treat human platelet (PTL) concentrates in order to eliminate Leishmania spp. and Trypanosoma cruzi. Both are parasites that cause Leishmaniosis (a dangerous skin and visceral disease) and Chagas disease, respectively; and may circulate in blood products collected from infected donors. We included in this study both lineal (psoralens) and angular (angelicins) furocoumarins. In the study, we grouped the LNs on two sets; set1: DNA-drug complex MD trajectories for active compounds and set2: MD trajectories of non-active compounds or no-optimal MD trajectories of active compounds. We calculated the respective pi(k)(L) values for all these LNs and used them as inputs to train a new classifier that discriminate set1 from set2 cases. In training series the model correctly classifies 79 out of 80 (specificity=98.75%) set1 and 226 out of 238 (Sensitivity=94.96%) set2 trajectories. In independent validation series the model correctly classifies 26 out of 26 (specificity=100%) set1 and 75 out of 78 (sensitivity=96.15%) set2 trajectories. We propose this new model as a scoring function to guide DNA-docking studies in the drug design of new coumarins for anticancer or antiparasitic PUVA therapy.

Elastic energy storage in an unmineralized collagen type I molecular model with explicit solvation and water infiltration

Collagen type I is a structural protein that provides tensile strength to tendons and ligaments. Type I collagen molecules form collagen fibers, which are viscoelastic and can therefore store energy elastically via molecular elongation and dissipate viscous energy through molecular rearrangement and fibrillar slippage. The ability to store elastic energy is important for the resiliency of tendons and ligaments, which must be able to deform and revert to their initial lengths with changes in load. In an earlier paper by one of the present authors, molecular modeling was used to investigate the role of mineralization upon elastic energy storage in collagen type I. Their collagen model showed a similar trend to their experimental data but with an over-estimation of elastic energy storage. Their simulations were conducted in vacuum and employed a distance-dependent dielectric function. In this study, we performed a re-evaluation of Freeman and Silver's model data incorporating the effects of explicit solvation and water infiltration, in order to determine whether the model data could be improved with a more accurate representation of the solvent and osmotic effects. We observed an average decrease in the model's elastic energy storage of 45.1%+/-6.9% in closer proximity to Freeman and Silver's experimental data. This suggests that although the distance-dependent dielectric implicit solvation approach was favored for its increased speed and decreased computational requirements, an explicit representation of water may be necessary to more accurately model solvent interactions in this particular system. In this paper, we discuss the collagen model described by Freeman and Silver, the present model building approach, the application of the present model to that of Freeman and Silver, and additional assumptions and limitations.

Study of peptide fingerprints of parasite proteins and drug-DNA interactions with Markov-Mean-Energy invariants of biopolymer molecular-dynamic lattice networks

Since the advent of Molecular Dynamics (MD) in biopolymers science with the study by Karplus et al. on protein dynamics, MD has become the by foremost well established, computational technique to investigate structure and function of biomolecules and their respective complexes and interactions. The analysis of the MD trajectories (MDTs) remains, however, the greatest challenge and requires a great deal of insight, experience, and effort. Here, we introduce a new class of invariants for MDTs based on the spatial distribution of Mean-Energy values ξk (L) on a 2D Euclidean space representation of the MDTs. The procedure forces one MD trajectory to fold into a 2D Cartesian coordinates system using a step-by-step procedure driven by simple rules. The ξk (L) values are invariants of a Markov matrix (1 Π), which describes the probabilities of transition between two states in the new 2D space; which is associated to a graph representation of MDTs similar to the lattice networks (LNs) of DNA and protein sequences. We also introduce a new algorithm to perform phylogenetic analysis of peptides based on MDTs instead of the sequence of the polypeptide. In a first experiment, we illustrate this algorithm for 35 peptides present on the Peptide Mass Fingerprint (PMF) of a new protein of Leishmania infantum studied in this work. We report, by the first time, 2D Electrophoresis isolation, MALDI TOF Mass Spectroscopy characterization, and MASCOT search results for this PMF. In a second experiment, we construct the LNs for 422 MDTs obtained in DNA-Drug Docking simulations of the interaction of 57 anticancer furocoumarins with a DNA oligonucleotide. We calculated the respective ξk (L) values for all these LNs and used them as inputs to train a new classifier with Accuracy = 85.44% and 84.91% in training and validation respectively. The new model can be used as scoring function to guide DNA-Drug Docking studies in drug design of new coumarins for PUVA therapy. The new phylogenetics analysis algorithms encode information different from sequence similarity and may be used to analyze MDTs obtained in Docking or modeling experiments for any classes of biopolymers. The work opens new perspective on the analysis and applications of MD in polymer sciences.

QSAR for RNases and theoretic-experimental study of molecular diversity on peptide mass fingerprints of a new Leishmania infantum protein

The toxicity and low success of current treatments for Leishmaniosis determines the search of new peptide drugs and/or molecular targets in Leishmania pathogen species (L. infantum and L. major). For example, Ribonucleases (RNases) are enzymes relevant to several biologic processes; then, theoretical and experimental study of the molecular diversity of Peptide Mass Fingerprints (PMFs) of RNases is useful for drug design. This study introduces a methodology that combines QSAR models, 2D-Electrophoresis (2D-E), MALDI-TOF Mass Spectroscopy (MS), BLAST alignment, and Molecular Dynamics (MD) to explore PMFs of RNases. We illustrate this approach by investigating for the first time the PMFs of a new protein of L. infantum. Here we report and compare new versus old predictive models for RNases based on Topological Indices (TIs) of Markov Pseudo-Folding Lattices. These group of indices called Pseudo-folding Lattice 2D-TIs include: Spectral moments pi ( k )(x,y), Mean Electrostatic potentials xi ( k )(x,y), and Entropy measures theta ( k )(x,y). The accuracy of the models (training/cross-validation) was as follows: xi ( k )(x,y)-model (96.0%/91.7%)>pi ( k )(x,y)-model (84.7/83.3) > theta ( k )(x,y)-model (66.0/66.7). We also carried out a 2D-E analysis of biological samples of L. infantum promastigotes focusing on a 2D-E gel spot of one unknown protein with M<20, 100 and pI <7. MASCOT search identified 20 proteins with Mowse score >30, but not one >52 (threshold value), the higher value of 42 was for a probable DNA-directed RNA polymerase. However, we determined experimentally the sequence of more than 140 peptides. We used QSAR models to predict RNase scores for these peptides and BLAST alignment to confirm some results. We also calculated 3D-folding TIs based on MD experiments and compared 2D versus 3D-TIs on molecular phylogenetic analysis of the molecular diversity of these peptides. This combined strategy may be of interest in drug development or target identification.

Molecular dynamics studies on the interactions of PTP1B with inhibitors: from the first phosphate-binding site to the second one

Protein tyrosine phosphatases 1B (PTP1B) is a major negative regulator of both insulin and leptin signaling pathways. In view of this, it becomes an important target for drug development against cancers, diabetes and obesity. The aim of the current study is to use the long time-scale molecular dynamics (MD) simulations to investigate the structural and dynamic factors that cause its inhibition by INTA and INTB, the two most potent and highly selective PTP1B inhibitors known so far. In order to investigate the mode of collective motions that is vitally important to the biological function, the covariance matrix of C(alpha) atoms was introduced for performing the dynamic analysis of the inhibition systems. It has been observed that the conformational and dynamic features of WPD-Loop, R-Loop and S-Loop play a key role in providing a smooth entrance for the inhibitors moving into the binding pocket as well as a favorable microenvironment to stabilize them. Furthermore, the hydrogen bonding networks formed around the active site with INTA and INTB may be the main reason of why the inhibition of PTP1B by the two ligands is so potent and selective. All these findings might provide useful insights for developing novel and effective drugs to treat cancer, diabetes and obesity.

Computational studies of the binding mechanism of calmodulin with chrysin

Calmodulin (CaM) plays a crucial role in metabolism and physiology of eukaryotes by regulating biological activities. Multiple lines of evidences indicate that the phosphorylated flavonoids possess relatively stronger affinities for proteins by forming non-covalent complexes with them, and that the cellular functions are often triggered by this kind of interactions. Chrysin is one of the phosphorylated flavonoids that exist ubiquitously in plants and have remarkably beneficial pharmacological effects. In this study, the molecular docking tools were utilized to investigate the interactions of CaM with chrysin. Two different favorable binding modes have been observed. To complement the results obtained by the molecular docking study, an in-depth investigation into the binding modes was conducted with the molecular dynamics (MD) simulation to explore the binding profile and energy landscape. Based on the results thus obtained, a clear definition of the binding pocket for each of the two binding modes has been revealed. These findings may shed light upon the binding interactions of CaM with chrysin, providing a solid molecular basis for subset analysis of its pharmacological benefits.

Soliton/exciton transport in proteins

The study of electron/proton transport in alpha-helix sections of proteins have illustrated the existence of soliton-like mechanisms. Recently, Ciblis and Cosic extended investigation to the existence of possible like soliton-type mechanisms in other parts of the protein. They used Quantum Hamiltonian analysis to investigate. In this paper, we investigate the same problem but we use Classical Hamiltonian analysis in our investigation.

The vibrational normal modes of beta-barrels in an IgG antibody molecule

Based on the quasi-continuity model, and using the method of group theory, we studied the normal vibrations of the VL- and the CHL-beta-barrels in an IgG molecule. We put emphasis on the Raman- and the infrared-active normal modes. The Raman modes we obtained include both the breathing motion mode (or the dominant low-frequency mode) which corresponds to the maximum peak in the Raman spectrum, and the normal modes that correspond to the lower peaks. Our calculated vibration frequencies are found to be in good agreement with the experimental results observed by Painter et al. (Biopolymers 20 (1981) 243). The method and work presented in this paper may improve Chou's quasi-continuity theory in calculating the vibrational modes of a beta-barrel protein.

Energy-optimized structure of antifreeze protein and its binding mechanism

A combination of Monte Carlo simulated annealing and energy minimization was utilized to determine the conformation of the antifreeze protein from the fish winter flounder. It was found from the energy-optimized structure that the hydroxyl groups of its four threonine residues, i.e. Thr2, Thr13, Thr24, Thr35, are aligned on almost the same line parallel to the helix axis and separated successively by 16.1, 16.0 and 16.2 A, respectively, very close to the 16.6 A repeat spacing along [0112] in ice. Based on such a space match, a zipper-like model is proposed to elucidate the binding mechanism of the antifreeze protein to ice crystals. According to the current model, the antifreeze protein may bind to an ice nucleation structure in a zipper-like fashion through hydrogen bonding of the hydroxyl groups of these four Thr residues to the oxygen atoms along the [0112] direction in ice lattice, subsequently stopping or retarding the growth of ice pyramidal planes so as to depress the freeze point. The calculated results and the binding mechanism thus derived accord with recent experimental observations. The mechanistic implications derived from such a special antifreeze molecule might be generally applied to elucidate the structure-function relationship of other antifreeze proteins with the following two common features: (1) recurrence of a Thr residue (or any other polar amino acid residue whose side-chain can form a hydrogen bond with water) in an 11-amino-acid period along the sequence concerned; and (2) a high percentage of Ala residue component therein. Further experiments are suggested to test the ice binding model.

Biophysical aspects of neutron scattering from vibrational modes of proteins

This review describes a major portion of the published work on neutron scattering experiments aimed at measuring large scale motions in proteins. The importance of these motions for enzyme function and oxygen transport is indicated. The theory applicable to each type of neuron scattering measurement is given and results are discussed with a view to biological relevance. New experiments are suggested and a comparison of neutron scattering data is made with results from other techniques such as raman scattering, infrared absorption, photolysis and molecular dynamics simulations.

Protein dynamics: comparison of simulations with inelastic neutron scattering experiments

To deepen our understanding of the principles determining the folding and functioning of globular proteins the determination of their three-dimensional structures must be supplemented with the characterization of their internal motions. Although dynamical events in proteins occur on time-scale ranging from femtoseconds to at least seconds, the physical properties of globular proteins are such that picosecond (ps) time-scale motions make a particularly important contribution to the internal fluctuations of the atoms from their mean positions.

Quasi-continuum models of twist-like and accordion-like low-frequency motions in DNA

Formulae for calculating low-frequency twist-like and accordion-like modes of DNA molecules have been derived using a quasi-continuum model. The formulae can be employed in essentially all (viz. A, B, C, D, E, and Z) forms of DNA. Calculated results indicate that the experimentally observed low-frequency modes at 22 cm-1 for the A-form octanucleotide (d[CCCCGGGG]) and at 18 cm-1 for the B-form dodecanucleotide (d[CGCAA ATTTGCG]) may result from accordion-like motions, while those observed at 12 cm-1 and 15 cm-1 may result from combinations of twist-like oscillations excited in the intact segments of B- and A-DNA's, respectively. Frequency shifts in the low-frequency modes observed when DNA molecules undergo conformational changes among different forms are also discussed in terms of the current model.

Low-frequency collective motion in biomacromolecules and its biological functions

The occurrence of low-frequency motion in biomacromolecules, which had long been speculated upon with a great deal of skepticism, is now a clearly established phenomenon and has been convincingly demonstrated. The next stage in the process of its elucidation appropriately concerns the determination of its origin, the development of a feasible and effective model for the calculations involved and, more importantly, the extending of investigations on its biological roles in order to gain insights into the various interesting mechanisms underlying the dynamic processes occurring in biomacromolecules. Confronted with such a task, this review has been written with the aim of stimulating further, through a systematic and comprehensive description, developments to open up this exciting frontier of molecular biology, especially from the viewpoint of biological functions.

Origin of low-frequency motions in biological macromolecules. A view of recent progress in the quasi-continuity model

The recent progress in the quasi-continuity model and its applications in studying the low-frequency internal motions of biological macromolecules have been surveyed. Emphasis is placed on revealing the origin of this kind of internal collective motion, which involves many atoms and has significant biological functions. In light of such a line, the low-frequency motions in alpha-helix structure, beta-structure (including beta-sheet and beta-barrel), and DNA double-helix structure, the three most fundamental component elements in biological macromolecules, are discussed, and the corresponding physical pictures described. It turns out that the low-frequency motion in biological macromolecules originates from their two common intrinsic characteristics, i.e., they possess a series of weak bonds, such as hydrogen bonds and salt bridges, and a substantial mass distributed over the region containing those weak bonds.

Low-frequency motions in protein molecules. Beta-sheet and beta-barrel

Low-frequency internal motions in protein molecules play a key role in biological functions. Based on previous work with alpha-helical structure, the quasi-continuum model is extended to the beta-structure, another fundamental element in protein molecules. In terms of the equations derived here, one can easily calculate the low-frequency wave number of a beta-sheet in an accordionlike motion, and the low-frequency wave number of a beta-barrel in a breathing motion. The calculated results for immunoglobulin G and concanavalin A agree well with the observations. These findings further verify that the observed low-frequency motion (or the so-called dominant low-frequency mode) in a protein molecule is essentially governed by the collective fluctuations of its weak bonds, especially hydrogen bonds, and the internal displacement of the massive atoms therein, as described by the quasi-continuum model.

The biological functions of low-frequency vibrations (phonons) 5. A phenomenological theory

Low-frequency internal motions of a biomacromolecule are thought to possess significant biological function from the dynamic point of view. In this paper, a general phenomenological theory is established by which it is clearly verified that low-frequency resonance plays a central role in the energy transmission required during the cooperative interaction between subunits in a protein oligomer. According to the present theory, it is found that the energy transmission between a pair of diagonal subunits in a protein oligomer with a polygon arrangement is the most efficient, so as to in a sense further predict that after a ligand is bound to a subunit by random collision, its diagonal subunit in the same protein oligomer will possess the greatest probability of binding with the next ligand. Furthermore, based on the concept of the 'resonance-controlled trigger' derived from the phenomenological theory, it is feasible to estimate the lower time limit of allosteric transition from one subunit to the other. Such a time limit depends on the dominant low-frequency mode of each subunit, the ratio of the coupling force constant to the corresponding inherent force constant, as well as the geometrical arrangement of subunits in a protein oligomer. So far none of the allosteric transitions observed in proteins has exceeded the time limit as defined here, indicating a logical consistency between our theory and the experiments.

The biological functions of low-frequency vibrations (phonons). 4. Resonance effects and allosteric transition

Based on the internal structure of oligoprotein as well as the basic physical characteristics+ of vibrations, it is deduced that the low-frequency vibrations possess some exceptional functions in transmitting biological information at the molecular level. In particular, according to the viewpoint of energy exchange and intramolecular displacement, it is demonstrated that the low-frequency resonance plays a very significant role during the dynamic process of allosterism of an oligomeric protein molecule. Furthermore, the cooperative reaction between hemoglobins and ligands is taken as an example, through which it is seen that some observed phenomena, whose dynamic principle has thus far been unclear, can be explicitly interpreted in terms of the concept of low-frequency resonance.

Low-frequency vibrations of DNA molecules

A model for calculating the low-frequency modes in DNA molecules is presented. The present model is associated with the 'breathing' of a DNA molecule as well as its complementary hydrogen bonds. The calculated results show excellent agreement with the observed low-frequency wavenumber (30 cm-1). Consequently, such an internal motion as reflected in the proposed model might be the origin of the observed low-frequency vibration in DNA molecules. This is helpful for investigating the relevant biological functions, which so far have been discussed by many scientists.