A computational model for predicting fusion peptide of retroviruses

As a pivotal domain within envelope protein, fusion peptide (FP) plays a crucial role in pathogenicity and therapeutic intervention. Taken into account the limited FP annotations in NCBI database and absence of FP prediction software, it is urgent and desirable to develop a bioinformatics tool to predict new putative FPs (np-FPs) in retroviruses. In this work, a sequence-based FP model was proposed by combining Hidden Markov Method with similarity comparison. The classification accuracies are 91.97% and 92.31% corresponding to 10-fold and leave-one-out cross-validation. After scanning sequences without FP annotations, this model discovered 53,946 np-FPs. The statistical results on FPs or np-FPs reveal that FP is a conserved and hydrophobic domain. The FP software programmed for windows environment is available at https://sourceforge.net/projects/fptool/files/?source=navbar.     

A computational model of the 5-HT3 receptor extracellular domain: search for ligand binding sites

A three-dimensional model of the 5-HT₃ receptor extarcellular domain has been derived on the basis of the nicotinic acetylcholine receptor model recently published by Tsigelny et al. Maximum complementarity between the position and characteristics of mutated residues putatively involved in ligand interaction and the pharmacophoric elements derived by the indirect approach applied on several series of 5-HT₃ ligands have been exploited to gain insights into the ligand binding modalities and to speculate on the mechanistic role of the structural components. The analysis of the three-dimensional model allows one to distinguish among amino acids that exert key roles in ligand interactions, subunit architecture, receptor assembly and receptor dynamics. For some of these, alternative roles with respect to the ones hypothesized by experimentalists are assigned. Different binding modalities for agonists and antagonists are highlighted, and residues which probably play a role in the transduction of binding into a change in conformational state of the receptor are suggested. Received: 27 July 2000 / Accepted: 15 September 2000 / Published online: 21 December 2000     

预测混合煤燃烧性能的数学模型

用热重分析法研究了单种煤的DTG和TG曲线特征，建立了预测混合煤燃烧性能的数学模型。结果表明，各单种煤的DTG曲线呈单峰，峰值温度tmax与其燃料比F的对数呈线性相关关系，tmax=68.86 ln（F）+512.2 （℃）。由组成混合煤的单种煤的燃料比F可推断出混合煤的DTG曲线特征，从而预测混合煤的燃烧性能。如果混合煤的煤质指标满足标准煤的煤质指标要求，则当Fmax/Fmin≤3.20时，混合煤的燃烧性能好；当3.205.71时，混合煤的燃烧性能较差。     

The enhancement of immunosuppressive effects of cyclosporine A on human T-cells using fusogenic liposomes

The aim of this study was to prepare and characterize neutral, positively charged, negatively charged and fusogenic liposomes of different sizes that contain cyclosporine A (CyA) and to evaluate their immunosuppressive activity on human T-cells. Neutral liposomes containing CyA were prepared from dipalmitoylphosphatidylcholine (DPPC) and cholesterol using the solvent evaporation method. To prepare positively charged, negatively charged and fusogenic liposomes containing CyA; stearylamine (SA), dicetylphosphate (DCP) and dioleoylphosphatidylethanolamine (DOPE) were added to the neutral liposome formulation, respectively. To reduce the size of liposomes containing CyA, extrusion through polycarbonate filters (1000, 400 and 100 nm) was used. The liposomes were characterized by their size, zeta potential and encapsulation efficiency. The in vitro immunosuppressive effects of an aqueous solution of CyA and different liposomes containing CyA were determined on human T-cells by the MTT [3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium bromide] assay. The mean diameter of the various multilamellar vesicle (MLV) liposomes containing CyA was between 1.76 and 2.49 μm. The encapsulation efficiency for the different MLV and extruded liposomes containing CyA ranged from 73% to 90%. In vitro immunosuppressive evaluation by T-cell culture showed that fusogenic liposomes have the best inhibitory effects on T-cell proliferation compared to the other liposomes. Reducing the size of the liposomes did not affect the in vitro immunosuppressive activity. The average IC₅₀ for the aqueous solution of CyA and the neutral, positively charged, negatively charged and fusogenic liposomes containing CyA was 4.98 × 10⁻², 7.38, 1.43, 3.84 × 10⁻³ and 7.93 × 10⁻⁵ mM, respectively. The results of this study indicate that fusogenic liposomes have the strongest immunosuppressive activity and could be considered as a suitable delivery system for CyA.     

A kinetic model for predicting biodegradation

Biodegradation plays a key role in the environmental risk assessment of organic chemicals. The need to assess biodegradability of a chemical for regulatory purposes supports the development of a model for predicting the extent of biodegradation at different time frames, in particular the extent of ultimate biodegradation within a ‘10?day window’ criterion as well as estimating biodegradation half-lives. Conceptually this implies expressing the rate of catabolic transformations as a function of time. An attempt to correlate the kinetics of biodegradation with molecular structure of chemicals is presented. A simplified biodegradation kinetic model was formulated by combining the probabilistic approach of the original formulation of the CATABOL model with the assumption of first order kinetics of catabolic transformations. Nonlinear regression analysis was used to fit the model parameters to OECD 301F biodegradation kinetic data for a set of 208 chemicals. The new model allows the prediction of biodegradation multi-pathways, primary and ultimate half-lives and simulation of related kinetic biodegradation parameters such as biological oxygen demand (BOD), carbon dioxide production, and the nature and amount of metabolites as a function of time. The model may also be used for evaluating the OECD ready biodegradability potential of a chemical within the ‘10-day window’ criterion.     

A new method for predicting conduction anesthesia

A new method for predicting conduction anesthesia has been suggested. The method is based on calculation of theP matrix probabilities of interatomic contacts for each molecule of the compounds considered. TheP matrix enables one to evaluate the main tendencies of atoms and atomic groups to interact in biochemical sorption on the nerve fiber surface. The minimum effective concentrations calculated for 25 compounds are in good agreement with the experimental data. The correlation coefficient between the experimental and calculated values is 0.98 when the standard deviation is 0.1 mmol L⁻¹. Translated fromIzvestiya Akademii Nauk. Seriya Khimicheskaya, No. 10, pp. 1781–1784, October, 1997.     

PPM-Dom: A novel method for domain position prediction

Domains are the structural basis of the physiological functions of proteins, and the prediction of which is an advantageous process on the study of protein structure and function. This article proposes a new complete automatic prediction method, PPM-Dom (Domain Position Prediction Method), for predicting the particular positions of domains in a target protein via its atomic coordinate. The presented method integrates complex networks, community division, and fuzzy mean operator (FMO). The whole sequences are divided into potential domain regions by the complex network and community division, and FMO allows the final determination for the domain position. This method will suffice to predict regions that will form a domain structure and those that are unstructured based on completely new atomic coordinate information of the query sequence, and be able to separate different domains in the same query sequence from each other. On evaluating the performance using an independent testing dataset, PPM-Dom reached 91.41% for prediction accuracy, 96.12% for sensitivity and 92.86% for specificity. The tool bag of PPM-Dom is freely available at http://cic.scu.edu.cn/bioinformatics/PPMDom.zip.     

How to make continuum solvation incredibly fast in a few simple steps: A practical guide to the domain decomposition paradigm for the conductor-like screening model

We illustrate the domain decomposition Conductor-like Screening Model (ddCOSMO) implementation and how to couple it with an existing classical or quantum mechanical (QM) code. We review in detail what input needs to be provided to ddCOSMO and how to assemble it, describe how the ddCOSMO equations are solved and how to process the results to assemble the required quantities, such as Fock matrix contributions for the QM case, or forces for the classical one. Throughout the article, we will make explicit references to the ddCOSMO module, which is an open source, Fortran 90 implementation of ddCOSMO that can be downloaded and distributed under the LGPL license.     

A computer simulation — Statistical procedure for predicting complexation equilibrium constants

The complexing properties of macrocyclic ligands have been quantitatively studied by the combined use of molecular mechanics, molecular dynamics, and multiple linear regression. The dependent variables in the regression equations are experimental equilibrium constants for known macrocycle complexes in various solvents. The independent variables are theoretical simulation results on the solvent-free ligand and its complex and additional physically motivated empirical variables to describe solvent and other important effects.The systems studied were: (a) 314 metal ion-macrocycle-solvent (including 3 mixed solvents) combinations; (b) 88 ammonium ion-crown ether-solvent (including 1 mixed solvent) combinations; (c) 24 hydrogen ion-crown ether-H₂O combinations; (d) 26 Na⁺ ion-spherand-CDCl₃ combinations; (e) 78 ammonium ion-spherand-CDCl₃ combinations; and (f) 73 complicated host-guest-solvent (including 1 mixed solvent) combinations.For each system, we report the best regression equation obtained using the AMBER force field. The standard errors in logK range from 1.42 in the largest system to 0.36 in the smallest. Regression equations were determined for several of the systems using the MMP2 force field as well, and the equations are shown to be relatively insensitive to the force field.The predictive ability of the method was tested by predicting logK for 20% of the cases chosen at random using equations derived from the remaining 80%. The errors in the predicted values are shown to be consistent with the statistical assumptions of the model.Regression equations obtained with this method can be used to predict the equilibrium constants for new complexes involving some combination of new, possibly unknown macrocycle, new host and, in certain cases new solvent. No X-ray or other structural data for the macrocycle is needed.     

The roles of cysteines in the heme domain of human soluble guanylate cyclase

Soluble guanylate cyclase(sGC) is a critical heme-containing enzyme involved in NO signaling.The dimerization of sGC subunits is necessary for its bioactivity and its mechanism is a striking and an indistinct issue.The roles of heme domain cysteines of the sGC on the dimerization and heme binding were investigated herein.The site-directed mutations of three conserved cysteines(C78A,C122A and C174S) were studied systematically and the three mutants were characterized by gel filtration analysis,UV-vis spectroscopy and heme transfer examination.Cys78 was involved in heme binding but not referred to the dimerization,while Cys174 was demonstrated to be involved in the homodimerization.These results provide new insights into the cysteine-related dimerization regulation of sGC.     

Toward a computational tool predicting the stereochemical outcome of asymmetric reactions: development of the molecular mechanics-based program ACE and application to asymmetric epoxidation reactions

The development and application of ACE, a program that predicts the stereochemical outcome of asymmetric reactions is presented. As major implementations, ACE includes a genetic algorithm to carry out an efficient global conformational search combined with a conjugate gradient minimization routine for local optimization and a corner flap algorithm to search ring conformations. Further improvements have been made that enable ACE to generate Boltzmann populations of conformations, to investigate highly asynchronous reactions, to compute fluctuating partial atomic charges and solvation energy and to automatically construct reactants and products from libraries of catalysts and substrates. Validation on previously investigated reactions (asymmetric Diels Alder cycloadditions and organocatalyzed aldol reactions) followed by application to a number of alkene epoxidation reactions and a comparative study of DFT-derived and ACE-derived predictions demonstrate the accuracy and usefulness of ACE in the context of asymmetric catalyst design.     

Reaction pathways for model II–VI precursors: A computational study

A computational study of the reactions of model II–VI precursors, MH₂ (M=Zn, Cd, Hg) and H₂E (E=O, S, Se, Te), is reported. The present computations yield several results of relevance to OMVPE of II–VI materials from MR₂/ER precursors. Adduct formation is feasible at low temperatures, in line with recent experiments, but not at higher temperatures common in II–VI OMVPE. Calculations suggest that adducts are most likely to form after elimination has resulted in replacement of hydride with hydroxide ligands (in our model) or alkyl with alkoxide ligands (in larger models). The overall reaction MH₂+2 H₂E→M(EH)₂ is generally more favorable, kinetically and thermodynamically, for lighter metals and heavier elements. On the basis of calculated thermodynamic and kinetic quantities, we conclude that the preferred pathway from reactants (MH₂+2 H₂E), except for M=Hg and E=Te, to an M(EH)₂ intermediate is by way of a 1:2 adduct (or a similar portion of the potential energy surface in the absence of a bound adduct) followed by two successive H₂ eliminations, in preference to the alternative in which adduct formation and H₂ elimination occur in succession. ©1999 John Wiley & Sons, Inc. Int J Quant Chem 71: 47–56, 1999     

A simple model for predicting the course of photochemical reactions

The possibility of building and using a simplified model with constant (time-invariant) reaction probabilities for rapid simulation of photochemical processes with the required reliability of the prediction has been shown. A relation between the probabilities of transformations and fundamental molecular characteristics (optical transition probabilities and quantum beat frequencies referring to a nonradiative reaction transition) that can be quantitatively determined with a good degree of certainty has been revealed. For monomolecular isomerization reactions as an example, the attainable level of the accuracy of prediction by the simple model has been estimated, which has been shown to be ～10% in most cases. It is important that the prediction of the order of magnitude of the key characteristics of photochemical processes, such as quantum yield and the reaction rate, is definitely correct as is required in most applications of photochemistry.     

Development of an ecotoxicity QSAR model for the KAshinhou Tool for Ecotoxicity (KATE) system,March 2009 version

The KAshinhou Tool for Ecotoxicity (KATE) system, including ecotoxicity quantitative structure–activity relationship (QSAR) models, was developed by the Japanese National Institute for Environmental Studies (NIES) using the database of aquatic toxicity results gathered by the Japanese Ministry of the Environment and the US EPA fathead minnow database. In this system chemicals can be entered according to their one-dimensional structures and classified by substructure. The QSAR equations for predicting the toxicity of a chemical compound assume a linear correlation between its log P value and its aquatic toxicity. KATE uses a structural domain called C-judgement, defined by the substructures of specified functional groups in the QSAR models. Internal validation by the leave-one-out method confirms that the QSAR equations, with r ² > 0.7, RMSE ≤ 0.5, and n > 5, give acceptable q ² values. Such external validation indicates that a group of chemicals with an in-domain of KATE C-judgements exhibits a lower root mean square error (RMSE). These findings demonstrate that the KATE system has the potential to enable chemicals to be categorised as potential hazards.     

A computational model for non-conserved mature miRNAs from the rice genome

Several computational approaches employ the high complementarity of plant miRNAs to target mRNAs as a filter to recognize miRNA. Numerous non-conserved miRNAs are known with more recent evolutionary origin as a result of target gene duplication events. We present here a computational model with knowledge inputs from reported non-conserved mature miRNAs of Oryza sativa (rice). Sequence- and structure-based approaches were used to retrieve miRNA features based on rice Argonaute protein and develop a multiple linear regression (MLR) model (r² = 0.996, q²_cv = 0.989) which scored mature miRNAs as predicted by the MaturePred program. The model was validated by scoring test set (q² = 0.990) and computationally predicted mature miRNAs as external test set (q²_test = 0.895). This strategy successfully enhanced the confidence of retrieving most probable non-conserved miRNAs from the rice genome. We anticipate that this computational model would recognize unknown non-conserved miRNA candidates and nurture the current mechanistic understanding of miRNA sorting to unveil the role of non-conserved miRNAs in gene silencing.     

A program for automatically predicting supramolecular aggregates and its application to urea and porphin

Not only the molecular structure but also the presence or absence of aggregates determines many properties of organic materials. Theoretical investigation of such aggregates requires the prediction of a suitable set of diverse structures. Here, we present the open‐source program EnergyScan for the unbiased prediction of geometrically diverse sets of small aggregates. Its bottom‐up approach is complementary to existing ones by performing a detailed scan of an aggregate's potential energy surface, from which diverse local energy minima are selected. We crossvalidate this approach by predicting both literature‐known and heretofore unreported geometries of the urea dimer. We also predict a diverse set of dimers of the less intensely studied case of porphin, which we investigate further using quantum chemistry. For several dimers, we find strong deviations from a reference absorption spectrum, which we explain using computed transition densities. This proof of principle clearly shows that EnergyScan successfully predicts aggregates exhibiting large structural and spectral diversity. © 2018 Wiley Periodicals, Inc.     

A computational model of the nicotinic acetylcholine binding site

We have derived a model of the nicotinic acetylcholine binding site. This was accomplished by using three known agonists (acetylcholine, nicotine and epibatidine) as templates around which polypeptide side chains, found to be part of the receptor cavity from published molecular biology studies, are allowed to flow freely in molecular dynamics simulations and mold themselves around these templates. The resulting supramolecular complex should thus be a complement, both in terms of steric effects as well as electronic effects, to the agonists and it should be a good estimation of the true receptor cavity structure. The shapes of those minireceptor cavities equilibrated rapidly on the simulation time scale and their structural congruence is very high, implying that a satisfactory model of the nicotinic acetylcholine binding site has been achieved. The computational methodology was internally tested against two rigid and specific antagonists (dihydro--erytroidine and erysoidine), that are expected to give rise to a somewhat differently shaped binding site compared to that derived from the agonists. Using these antagonists as templates there were structural reorganizations of the initial receptor cavities leading to distinctly different cavities compared to agonists. This indicates that adequate times and temperatures were used in our computational protocols to achieve equilibrium structures for the agonists. Overall, both minireceptor geometries for agonists and antagonists are similar with the exception of one amino acid (ARG209).