Computational methods in protein structure prediction

This review presents the advances in protein structure prediction from the computational methods perspective. The approaches are classified into four major categories: comparative modeling, fold recognition, first principles methods that employ database information, and first principles methods without database information. Important advances along with current limitations and challenges are presented.     

Computational studies of H5N1 influenza virus resistance to oseltamivir

Influenza A (H5N1) virus is one of the world's greatest pandemic threats. Neuraminidase (NA) inhibitors, oseltamivir and zanamivir, prevent the spread of influenza, but drug‐resistant viruses have reduced their effectiveness. Resistance depends on the binding properties of NA‐drug complexes. Key residue mutations within the active site of NA glycoproteins diminish binding, thereby resulting in drug resistance. We performed molecular simulations and calculations to characterize the mechanisms of H5N1 influenza virus resistance to oseltamivir and predict potential drug‐resistant mutations. We examined two resistant NA mutations, H274Y and N294S, and one non‐drug‐resistant mutation, E119G. Six‐nanosecond unrestrained molecular dynamic simulations with explicit solvent were performed using NA‐oseltamivir complexes containing either NA wild‐type H5N1 virus or a variant. MM_PBSA techniques were then used to rank the binding free energies of these complexes. Detailed analyses indicated that conformational change of E276 in the Pocket 1 region of NA is a key source of drug resistance in the H274Y mutant but not in the N294S mutant.     

Transmission of the Subthalamic Nucleus Oscillatory Activity to the Cortex: A Computational Approach

Parkinsonian tremor is most likely due to oscillatory neuronal activities of central oscillators such as the subthalamic nucleus (STN)-external segment of the globus pallidus (GPe) pacemaker within the basal ganglia (BG). Activity from the central oscillator is proposed to be transmitted via transcortical pathways to the periphery. A computational model of the BG is proposed for simulating the transmission of the STN oscillatory activity to the cortex, based closely on known anatomy and physiology of the BG. According to the results of the simulation, for transmission of the STN oscillatory activity to the cortex, the STN oscillatory activity has to be transmitted simultaneously to the thalamus via STN-internal segment of the globus pallidus (GPi)-thalamus and STN-GPe-GPi-thalamus pathways. This transmission is controlled by the various factors such as the phase between the STN and GPe oscillatory activities, the STN oscillatory activity frequency, the low-threshold calcium spike bursts of the thalamus and the GPi spontaneous activity.     

Computational strategies for protein conformational ensemble detection

Protein function is constrained by the three-dimensional structure but is delineated by its dynamics. This framework must satisfy specificity of function along with adaptability to changing environments and evolvability under external constraints. The accessibility of the available regions of the energy landscape for a set of conditions and shifts in the populations upon their modulation have effects propagating across scales, from biomolecular interactions, to organisms, to populations. Developing the ability to detect and juggle protein conformations supplemented by a physics-based understanding has implications for not only in vivo problems but also for resistance impeding drug discovery and bionano-sensor design.     

Conformational preferences in diglycosyl disulfides: NMR and molecular modeling studies

The conformations of several β1→β1′ diglycosyl disulfides were investigated by NMR and computational methods. Experimental data, such as NOEs, proton–proton and proton–carbon-13 coupling constants, measured for solutions in DMSO, are in good agreement with values obtained by MD simulations in explicit DMSO. The disulfide torsion angles (C1–S–S–C1′) preferentially sample values close to either +90° or −90° (+g or −g) and appear as the main metric that determines the conformational behavior of these glycomimetics. There is more conformational freedom around the C1–S and C1′–S′ bonds (Φ and Ω torsions, respectively) and population cluster analysis allowed to identify up to four allowed conformational regions for each of the +g or −g forms. Population analysis of the hydroxylic group rotamers, based on proton–proton and proton–carbon-13 couplings as well as on calculated hydrogen bonding statistics, did not reveal any significant intramolecular hydrogen bonds in DMSO solution.     

Computational alanine scanning with linear scaling semiempirical quantum mechanical methods

Alanine scanning is a powerful experimental tool for understanding the key interactions in protein–protein interfaces. Linear scaling semiempirical quantum mechanical calculations are now sufficiently fast and robust to allow meaningful calculations on large systems such as proteins, RNA and DNA. In particular, they have proven useful in understanding protein–ligand interactions. Here we ask the question: can these linear scaling quantum mechanical methods developed for protein–ligand scoring be useful for computational alanine scanning? To answer this question, we assembled 15 protein–protein complexes with available crystal structures and sufficient alanine scanning data. In all, the data set contains ΔΔGs for 400 single point alanine mutations of these 15 complexes. We show that with only one adjusted parameter the quantum mechanics‐based methods outperform both buried accessible surface area and a potential of mean force and compare favorably to a variety of published empirical methods. Finally, we closely examined the outliers in the data set and discuss some of the challenges that arise from this examination. Proteins 2010. © 2010 Wiley‐Liss, Inc.     

Molecular dynamics and free energy analysis of neuraminidase-ligand interactions

We report molecular dynamics calculations of neuraminidase in complex with an inhibitor, 4-amino-2-deoxy-2,3-didehydro-N-acetylneuraminic acid (N-DANA), with subsequent free energy analysis of binding by using a combined molecular mechanics/continuum solvent model approach. A dynamical model of the complex containing an ionized Glu119 amino acid residue is found to be consistent with experimental data. Computational analysis indicates a major van der Waals component to the inhibitor-neuraminidase binding free energy. Based on the N-DANA/neuraminidase molecular dynamics trajectory, a perturbation methodology was used to predict the binding affinity of related neuraminidase inhibitors by using a force field/Poisson-Boltzmann potential. This approach, incorporating conformational search/local minimization schemes with distance-dependent dielectric or generalized Born solvent models, correctly identifies the most potent neuraminidase inhibitor. Mutation of the key ligand four-substituent to a hydrogen atom indicates no favorable binding free energy contribution of a hydroxyl group; conversely, cationic substituents form favorable electrostatic interactions with neuraminidase. Prospects for further development of the method as an analysis and rational design tool are discussed.     

Computational methods and evaluation of RNA stabilization reagents for genome-wide expression studies

Gene expression studies require high quality messenger RNA (mRNA) in addition to other factors such as efficient primers and labeling reagents. To prevent RNA degradation and to improve the quality of gene array expression data, several commercial reagents have become available. We examined a conventional hot-phenol lysis method and RNA stabilization reagents, and generated comparative gene expression profiles from Escherichia coli cells grown on minimal medium. Our data indicate that certain RNA stabilization reagents induce stress responses and proper caution must be exercised during their use. We observed that the laboratory reagent (phenol/EtOH, 5:95, v/v) worked efficiently in isolating high quality mRNA and reproducibility was such that reliable gene expression profiles were generated. To assist in the analysis of gene expression data, we wrote a number of macros that use the most recent gene annotation and process data in accordance with gene function. Scripts were also written to examine the occurrence of artifacts, based on GC content, length of the individual open reading frame (ORF), its distribution on plus and minus DNA strands, and the distance from the replication origin.     

Bayesian methods in bioinformatics and computational systems biology

Bayesian methods are valuable, inter alia, whenever there is a need to extract information from data that are uncertain or subject to any kind of error or noise (including measurement error and experimental error, as well as noise or random variation intrinsic to the process of interest). Bayesian methods offer a number of advantages over more conventional statistical techniques that make them particularly appropriate for complex data. It is therefore no surprise that Bayesian methods are becoming more widely used in the fields of genetics, genomics, bioinformatics and computational systems biology, where making sense of complex noisy data is the norm. This review provides an introduction to the growing literature in this area, with particular emphasis on recent developments in Bayesian bioinformatics relevant to computational systems biology.     

真核生物基因启动子的计算机预测及其软件资源

真核生物基因启动子一直是现代分子生物学的研究热点。随着近年来生物技术和计算机技术的高速发展,应用生物信息学技术对真核生物启动子的计算机预测及相关软件开发取得了较大进展。文章将主要对真核生物启动子Ⅱ的预测研究进展和软件资源作一简单介绍。     

Heteronuclear coupling constants of hydroxyl protons in a water solution of oligosaccharides: trehalose and sucrose

Relatively few details are known about the conformational preferences of hydroxyl groups in carbohydrates in water solution, though these would be informative about solvation and H-bonding. We show that highly concentrated solutions of sucrose and trehalose exhibit surprisingly well-resolved ¹H NMR spectra in a deuterium oxide–water solvent mixture at subzero temperatures. Measurement conditions are suitable to extract nearly all homonuclear and, for the first time, heteronuclear coupling constants of OH groups of carbohydrates in their natural abundance. For ^2,3J_HO,C coupling constants new, powerful variants of HETLOC and HECADE techniques were applied. The present data do not support the presence of persistent H-bonds in these two cryogenic disaccharides.     

MALDI–MS Profiling to Address Honey Bee Health Status under Bacterial Challenge through Computational Modeling

Honey bees play a critical role in the maintenance of plant biodiversity and sustainability of food webs. In the past few decades, bees have been subjected to biotic and abiotic threats causing various colony disorders. Therefore, monitoring solutions to help beekeepers to improve bee health are necessary. Matrix‐assisted laser desorption ionization–mass spectrometry (MALDI–MS) profiling has emerged within this decade as a powerful tool to identify in routine micro‐organisms and is currently used in real‐time clinical diagnosis. MALDI BeeTyping is developed to monitor significant hemolymph molecular changes in honey bees upon infection with a series of entomopathogenic Gram‐positive and ‐negative bacteria. A Serratia marcescens strain isolated from one naturally infected honey bee collected from the field is also considered. A series of hemolymph molecular mass fingerprints is individually recorded and to the authors' knowledge, the first computational model harboring a predictive score of 97.92% and made of nine molecular signatures that discriminate and classify the honey bees’ systemic response to the bacteria is built. Hence, the model is challenged by classifying a training set of hemolymphs and an overall recognition of 91.93% is obtained. Through this work, a novel, time and cost saving high‐throughput strategy that addresses honey bee health on an individual scale is introduced.     

影响因子:计算方法、用途及局限性

美国科技信息研究所 （Institute for ScientificInformation,ISI）的期刊引证报告（Journal CitationReports,JCR）近年来已逐渐成为国内评价期刊及其刊载文章质量的主要量化指标。但是各人对它的应用价值有不同的看法。     

Comparative studies on the interactions of dihydroartemisinin and artemisinin with bovine serum albumin using spectroscopic methods

The interactions of dihydroartemisinin (DHA) and artemisinin (ART) with bovine serum albumin (BSA) have been investigated using fluorescence, UV/vis absorption and Fourier transform infrared (FTIR) spectra under simulated physiological conditions. The binding characteristics of DHA/ART and BSA were determined by fluorescence emission and resonance light scattering (RLS) spectra. The quenching mechanism between BSA and DHA/ART is static. The binding constants and binding sites of DHA/ART–BSA systems were calculated at different temperatures (293, 298, 304 and 310 K). According to Förster non‐radiative energy transfer theory, the binding distance of BSA to DHA/ART was calculated to be 1.54/1.65 nm. The effect of DHA/ART on the secondary structure of BSA was analyzed using UV/vis absorption, FTIR, synchronous fluorescence and 3D fluorescence spectra. In addition, the effects of common ions on the binding constants of BSA–DHA and BSA–ART systems were also discussed. Copyright © 2014 John Wiley & Sons, Ltd.     

Computational neuroscience in China

The ultimate goal of Computational Neuroscience(CNS) is to use and develop mathematical models and approaches to elucidate brain functions.CNS is a young and highly multidisciplinary field.It heavily interacts with experimental neuroscience and such other research areas as artificial intelligence,robotics,computer vision,information science and machine learning.This paper reviews the history of CNS in China,its current status and the prospects for its future development.Examples of CNS research in China are...