Hypercard-based data management tools for molecular biologists.

I have designed a Macintosh data management system for molecular biologists. This system, called DataMinder, can be used to store information about oligonucleotides, nucleic acid or protein sequences, recombinant DNA clones, cells, reagents and protocols. DataMinder is not limited to data storage. A number of utilities for data analysis are provided, including those for the evaluation of oligonucleotides for use as hybridization probes or primers for DNA synthesis, and a variety of sequence editing features. Context-sensitive help is available on-line. DataMinder is simple to use and to customize and allows for sharing of database information across a computer network.     

ACNUC--a portable retrieval system for nucleic acid sequence databases: logical and physical designs and usage

ACNUC is a database structure and retrieval software for use with either the GenBank or EMBL nucleic acid sequence data collections. The nucleotide and textual data furnished by both collections are each restructured into a database that allows sequence retrieval on a multi-criterion basis. The main selection criteria are: species (or higher order taxon), keyword, reference, journal, author, and organelle; all logical combinations of these criteria can be used. Direct access to sequence regions that code for a specific product (protein, tRNA or rRNA) is provided. A versatile extraction procedure copies selected sequences, or fragments of them, from the database to user files suitable to be analysed by user-supplied application programs. A detailed help mechanism is provided to aid the user at any time during the retrieval session. All software has been written in FORTRAN 77 which guarantees a high degree of transportability to minicomputers or mainframes.     

Easy to use and rapid isolation and detection of a viral nucleic acid by using paramagnetic microparticles and carbon nanotubes-based screen-printed electrodes

A method that is easy to use, rapid, with a low cost of detecting viral nucleic acid in a biological sample represents the essential tool in targeted therapy. In this study, we report the use of paramagnetic microparticles covered by streptavidin and modified by an oligonucleotide probe with a specific viral sequence labeled by biotin to detect human immunodeficiency virus (HIV) and influenza virus subtype H5N1. The viral nucleic acids were primarily detected by adsorptive transfer stripping technique coupled with square wave voltammetry using carbon paste, hanging mercury drop or carbon nanotubes-based screen-printed working electrodes. Detection limits were estimated for both sequences down to picograms per 3 μl. To isolate the viral sequences, paramagnetic microparticles covered with biotin-labeled oligonucleotides were used. We calculated the yield of isolation for H5N1 and/or HIV sequences, which was defined as “isolated concentration of viral nucleic acid sequence”/“given viral nucleic acid sequence” × 100. We estimated the yield for both sequences as 59%. Moreover, we studied the influence of human serum, dsDNA and non-complementary sequence of nucleic acids on isolation of viral nucleic acids. We also used carbon nanotubes-based screen-printed electrodes coupled with micro-flow instrument to detect viral nucleic acids. We were able to isolate and detect nanogram amounts of nucleic acids.     

Binding free energy calculations using MMPB/GBSA approaches for PAMAM-G4-drug complexes at neutral,basic and acid pH conditions

Dendrimers are synthetic macromolecules with a highly-branched structure and high concentration of surface groups. Among dendrimers, Poly(amidoamine) (PAMAM) has received substantial attention as a novel drug carrier and delivery system. Depending on the generation and type of terminal groups, dendrimer toxicity could change and include cytotoxicity. Although PAMAM is water soluble, molecular modeling of the dendrimer-drug complex is considered challenging for exploring the conformational mobility of dendrimers and atomic specific interactions during the dendrimer-drug association. However, conventional protocols for predicting binding affinities have been designed for small protein molecules or protein-protein complexes that can be applied to study the dendrimer-drug association. In this work, we performed docking calculations for a set of 94 previously reported compounds on PAMAM of fourth generation (G4-PAMAM) to select six compounds, cromoglicic acid (CRO) − a mast cell stabilizer, Fusidic acid (FUS) − a bacteriostatic antibiotic, and Methotrexate (MTX) − a chemotherapy agent and immune system suppressant, which have the highest affinities for G4-PAMAM, and Lidocaine (LDC) − used to numb tissue in a specific area and for ventricular tachycardia treatment, Metoprolol (MET) − a β₁ receptor blocker, and Pindolol (PIN) − a β blocker, which have the lowest affinities for the G4-PAMAM dendrimer, to perform MD simulations combined with the molecular mechanics generalized/Poisson-Boltzmann surface area MMGBSA/MMPBSA approach to investigate the interactions of generating 4 charge-neutral, charge-basic and charge-acid G4-PAMAM dendrimers. In addition, to validate these theoretical G4-PAMAM-drug complexes, the complexes were experimentally conjugated to determine their stability in aqueous solubility studies immediately and over one year. Our results show that among the different commercial drugs, both charged and neutral PAMAM have the most favorable binding free energies for CRO, MTX, and FUS, which appears to be due to a complex counterbalance of electrostatics and van der Waals interactions. These theoretical and aqueous solubility studies supported the high affinity of methotrexate for the G4-PAMAM-drug due to its carboxyl and aryl moieties that favor its accommodation by noncovalent interactions.     

H-BloX: visualizing alignment block entropies.

H-BloX is a web-based JavaScript application that allows the calculation and visualization of Shannon information content or relative entropy (Kullback-Leibler 'distance') within sequence alignment blocks. The application was designed for use in both teaching and research. Amino acid, nucleic acid sequences, or any other type of aligned chemical structures may serve as the input. Various interpretations of the meaning of 'entropy' or 'information content' are possible, including treatment as a chemical diversity measure or the degree of feature conservation. For analysis of numerical data by H-BloX, values must be converted to a user-defined character alphabet before computation of entropy or information content. H-BloX was successfully applied to feature identification in Escherichia coli signal peptides and their cleavage sites. Characteristics known features became visible, e.g., the hydrophobic core region and the well-known '-3,-1' cleavage site pattern. Based on the H-BloX analysis, the hydrophobic core is centered at amino acid residue position 13, counting from the N-terminal end of the protein precursor sequence. This result was obtained by using a built-in feature of H-BloX that enables conversion of amino acid sequences to a different alphabet that is based on hydrophobicity assignments. H-BloX can be accessed online or downloaded as HTML/JavaScript at http://bopwww.biologie.uni-freiburg.de/~bioinfo/HBloX/html/index.html.     

PRONUC: a software package for the analysis of protein and nucleic acid sequences

PRONUC is a menu-driven software package from which a molecular biologist may gain access to a variety of tools for the analysis of protein and nucleic acid sequences. Features include various algorithms for sequence comparisons, secondary structure prediction, sequence manipulation (translation complementation etc.) and finding restriction enzyme cut-sites. The sequences under study can be retrieved from several databases of published sequences or a users sequence(s) can be entered by means of a sequence editor or retrieved from a database constructed by the user. PRONUC comes with a comprehensive manual and on-line help which reflects several years of user feedback and is available for Digital VAX computer systems running the VMS or micro-VMS operating system.     

A novel method for alignment of two nucleic acid sequences using ant colony optimization and genetic algorithms

We describe a new method for pairwise nucleic acid sequence alignment that can also be used for pattern searching and tandem repeat searching within a nucleic acid sequence. The method is broadly a hybrid algorithm employing ant colony optimization (ACO) and the simple genetic algorithm. The method first employs ACO to obtain a set of alignments, which are then further processed by an elitist genetic algorithm, which employs primitive selection and a novel multipoint crossover-mutation operator to generate accurate alignments. The resulting alignments show a fair amount of accuracy for smaller and medium size sequences. Furthermore, this algorithm can be used rather quickly and efficiently for aligning shorter sequences and also for pattern searching in both nucleic acid and amino acid sequences. Furthermore, it can be used as an effective local alignment method or as a global alignment tool. On improvement of accuracy, this method can be extended for use towards multiple sequence alignment.     

MMTSB Tool Set: enhanced sampling and multiscale modeling methods for applications in structural biology

We describe the Multiscale Modeling Tools for Structural Biology (MMTSB) Tool Set (https://mmtsb.scripps.edu/software/mmtsbToolSet.html), which is a novel set of utilities and programming libraries that provide new enhanced sampling and multiscale modeling techniques for the simulation of proteins and nucleic acids. The tool set interfaces with the existing molecular modeling packages CHARMM and Amber for classical all-atom simulations, and with MONSSTER for lattice-based low-resolution conformational sampling. In addition, it adds new functionality for the integration and translation between both levels of detail. The replica exchange method is implemented to allow enhanced sampling of both the all-atom and low-resolution models. The tool set aims at applications in structural biology that involve protein or nucleic acid structure prediction, refinement, and/or extended conformational sampling. With structure prediction applications in mind, the tool set also implements a facility that allows the control and application of modeling tasks on a large set of conformations in what we have termed ensemble computing. Ensemble computing encompasses loosely coupled, parallel computation on high-end parallel computers, clustered computational grids and desktop grid environments. This paper describes the design and implementation of the MMTSB Tool Set and illustrates its utility with three typical examples--scoring of a set of predicted protein conformations in order to identify the most native-like structures, ab initio folding of peptides in implicit solvent with the replica exchange method, and the prediction of a missing fragment in a larger protein structure.     

Design of an interface peptide as new inhibitor of human glucose-6-phosphate dehydrogenase

Glucose-6-phosphate dehydrogenase (G6PDH) is an essential enzyme involved in the first reaction of the oxidative branch of the pentose phosphate pathway (PPP). Recently, G6PDH was suggested as a novel target protein for cancer therapy as one of the final products of the PPP, ribose-5-phosphate, is necessary for nucleic acid synthesis and tumor progression. After analyzing the protein–protein interface of the crystal structure of human G6PDH by means of molecular dynamics simulations, we designed six interface peptides based on the natural sequence of the protein. The three most promising peptides, as predicted by binding free energy calculations, were synthesized and one of them was confirmed as a novel inhibitor of human G6PDH in experimental assays. Together, the active peptide found and its suggested binding mode proposes a new strategy for inhibiting this enzyme and should aid the further design of novel, potent and non-peptidic G6PDH inhibitors.     

分子信标研究进展

分子信标是一种新型核酸探针,它在核酸检测中具有高特异性、高选择性和高灵敏度,取得了广泛的应用.该文主要介绍了分子信标的原理,一些新型的分子信标的结构及其优缺点和潜在的应用前景,并对分子信标的应用领域做了一个简单的介绍.     

基于CGR的蛋白质相似性比较

从蛋白质结构特性出发,利用结构字母表和CGR游走技术将蛋白质三维结构信息转换到二维坐标空间中。通过分析所得图像找出蛋白质分子的主体结构,获得各结构点在CGR图中的坐标,利用Hausdorff距离判定要比较的蛋白质对象相似性。该方法实现了蛋白质相似性比较的结构-序列模式转变,利用Hausdorff距离比较两点集间相似性的优势,为蛋白质相似性比较提供了一种简便有效的方法。     

Classification neural networks for rapid sequence annotation and automated database organization

A neural network classification method has been developed as an alternative approach to the search/organization problem of large molecular databases. Two artificial neural systems have been implemented on a Cray for rapid protein/nucleic acid classification of unknown sequences. The system employs a n-gram hashing function for sequence encoding and modular back-propagation networks for classification. The protein system, which classifies proteins into PIR (Protein Identification Resource) superfamilies, has achieved 82–100% sensitivity at a speed that is about an order of magnitude faster than other search methods. The pilot nucleic acid system showed a 91–97% classification accuracy. The software tool could be used as a filter program to reduce the database search time and help organize the molecular sequence databases. The tool is generally applicable to any databases that are organized according to family relationships.     

元胞自动机图的蛋白质二级结构类型预测

蛋白质结构预测是后基因组时代的一项重要任务,蛋白质二级结构预测是蛋白质结构预测的关键步骤。利用氨基酸数字编码模型生成蛋白质序列的元胞自动机图（Cellular Automata Image,CAI）,提出了一种基于灰度共生矩阵（Gray Level Co-occurrence Matrix,GLCM）提取纹理图像特征的方法。用扩大的协方差算法进行预测,仿真结果显示有较好的分类效果,Jackknife检验的预测成功率达到94.61％。     

Computational prediction of nucleic acid secondary structure: Methods,applications, and challenges

RNA molecules are crucial in different levels of cellular function, ranging from translation and regulating genes to coding for proteins. Additionally, nucleic acids (RNA and DNA molecules) are designed for novel applications in biotechnology. Understanding the structure of a molecule is important in inferring its function, and computational methods for structure prediction have captured the interest of many researchers.Some functions of RNA molecules in cells, such as gene regulation, result from the binding of one RNA molecule to another, so-called target RNA molecule. This has led to recent interest in prediction of the secondary structure formed from interacting molecules. In this paper, we provide a brief overview of methods, applications, and challenges in computational prediction of nucleic acid secondary structure, both for single strands and for interacting strands.     

A knowledge-based experimental design system for nucleic acid engineering

Presented in this paper is a knowledge-based experimental design system that incorporates the domain expertise used in nucleic acid engineering, thus automating the processing of error-prone, laborious low-level work, and many decision-making steps, and guiding the biologist toward a workable plan. This allows the biologist to work at a higher abstraction level, concentrating on more fundamental, difficult and challenging problems directly related to protein structure - function relationships. Cassette-based site-directed mutagenesis and synthetic gene designs are used as examples to illustrate the utility of the knowledge-based system approach to experimental design.     

A review of algorithms for molecular sequence comparison

Computers have recently become an essential component of research in molecular biology. Most computer analyses of nucleic acid and protein sequences depend on comparisons between sequences. These comparisons, depending on their purpose, may differ not only in the kinds of comparisons that are done, but also in the way the results of the comparison are used by molecular biologists or by other computer programs. This paper reviews algorithms currently in use to solve comparison problems in molecular biology. Each algorithm is explained in detail and discussed in terms of the molecular biology problems it is most suited to solve.     

The GenBank nucleic acid sequence database

The GenBank nucleic acid sequence database is a computer-based collection of all published DNA and RNA sequences; it contains over five million bases in close to six thousand sequence entries drawn from four thousand five hundred published articles. Each sequence is accompanied by relevant biological annotation. The database is available either on magnetic tape, on floppy diskettes, on-line or in hardcopy form. We discuss the structure of the database, the extent of the data and the implications of the database for research on nucleic acids.     

基于混合SVM方法的蛋白质二级结构预测算法

预测蛋白质二级结构,是当今生物信息学中一个难以解决的问题。由于预测蛋白质二级结构的精度在蛋白 质结构研究中起到非常重要的作用,因此在基于KDTICM理论基础上,提出一种基于混合SVM方法的蛋白质二级 结构预测算法。该算法有效地利用蛋白质的物化属性和PSI-SEARCH生成的位置特异性打分矩阵作为双层SVM的 输入,从而大大地提高了蛋白质二级结构预测的精度。实验比较分析表明,新算法的预测精度和普适性明显优于目前 其他典型的预测方法。