考虑相关能效应的过渡态计算方法

提出了一种在X_a方法基础上,同时包含电子相关效应和考虑电子自相互作用的过渡态计算方法.由此计算的一系列原子电离势的结果表明,相关能对电离势的计算结果有很大影响,其数值为—0.41eV～0.94eV.引入相关能效应使计算结果明显趋于合理.此计算模型兼有简便和合理的特点,且能适用于分子体系的计算.     

Prediction of protein subcellular location using hydrophobic patterns of amino acid sequence

The function of eukaryotic protein is closely correlated with its subcellular location. The number of newly found protein sequences entering into data banks is rapidly increasing with the success of human genome project. It is highly desirable to predict a protein subcellular automatically from its amino acid sequence. In this paper, amino acid hydrophobic patterns and average power-spectral density (APSD) are introduced to define pseudo amino acid composition. The covariant-discriminant predictor is used to predict subcellular location. Immune-genetic algorithm (IGA) is used to find the fittest weight factors which are very important in this method. As such, high success rates are obtained by both self-consistency test (86%) and jackknife test (73%). More than 80% predictive accuracy is achieved in independent dataset test. The results demonstrate that the proposed method is practical. And, the method illuminates that the protein subcellular location can be predicted from its surface physio-chemical characteristic of protein folding.     

A new approach towards peptidosulfonamides: synthesis of potential inhibitors of bacterial peptidoglycan biosynthesis enzymes MurD and MurE

Peptidosulfonamides are an emerging group of peptidomimetics with a variety of applications in medicinal chemistry. We present a novel approach to the synthesis of peptidosulfonamides, and apply it to a series of new potential inhibitors of the bacterial peptidoglycan biosynthesis enzymes MurD and MurE. The synthesis was conducted via N-phthalimido β-aminoethanesulfonyl chlorides, which are new building blocks for the synthesis of peptidosulfonamides. In the most crucial step, sulfonic acids or their sodium salts were converted into the corresponding sulfonyl chlorides using an excess of either SOCl₂ or SOCl₂/DMF, and then coupled to the C-protected amino acid. None of the compounds significantly inhibited MurD, however, some inhibited MurE; one had an IC₅₀ below 200 μM, which constitutes a promising starting point for further development. Molecular modelling simulations were performed on two analogues to investigate the absence of inhibitory activity of the sulfonamide compounds on MurD.     

An algorithm for the location of transition states

An algorithm for locating transition states designed for use in the ab initio program package GAUSSIAN 82 is presented. It is capable of locating transition states even if started in the wrong region of the energy surface, and, by incorporating the ideas on hessian mode following due to Cerjan and Miller, can locate transition states for alternative rearrangement/dissociation reactions from the same initial starting point. It can also be used to locate minima.     

A fast annealing evolutionary algorithm for global optimization

By combining the aspect of population in genetic algorithms (GAs) and the simulated annealing algorithm (SAA), a novel algorithm, called fast annealing evolutionary algorithm (FAEA), is proposed. The algorithm is similar to the annealing evolutionary algorithm (AEA), and a very fast annealing technique is adopted for the annealing procedure. By an application of the algorithm to the optimization of test functions and a comparison of the algorithm with other stochastic optimization methods, it is shown that the algorithm is a highly efficient optimization method. It was also applied in optimization of Lennard-Jones clusters and compared with other methods in this study. The results indicate that the algorithm is a good tool for the energy minimization problem.     

Transition-state structures for describing the enzyme-catalyzed mechanisms of rubisco

The carboxylation and oxygenation processes of a model substrate, 3,4-dihydroxy-2-pentanone, have been theoreticaly characterized as a set of steps, mimicking the corresponding reactions of D-ribulose-1,5-bisphosphate catalyzed by rubisco. A theoretical characterization is carried out of transition-state structures and possible molecular intermediates represented as saddle points of index 1 and minimum energy structures, respectively. The quantum chemical characterization, at the HF/3-21G calculation level, of these stationary points is used to rationalize and to discuss both catalyzed sequences. The reported set of these stationary points maps out most experimental aspects of the reaction pathways for the real system. Received: 24 March 1998 / Accepted: 3 September 1998 / Published online: 10 December 1998     

A genetic algorithm for flexible molecular overlay and pharmacophore elucidation

Summary A genetic algorithm (GA) has been developed for the superimposition of sets of flexible molecules. Molecules are represented by a chromosome that encodes angles of rotation about flexible bonds and mappings between hydrogen-bond donor proton, acceptor lone pair and ring centre features in pairs of molecules. The molecule with the smallest number of features in the data set is used as a template, onto which the remaining molecules are fitted with the objective of maximising structural equivalences. The fitness function of the GA is a weighted combination of: (i) the number and the similarity of the features that have been overlaid in this way; (ii) the volume integral of the overlay; and (iii) the van der Waals energy of the molecular conformations defined by the torsion angles encoded in the chromosomes. The algorithm has been applied to a number of pharmacophore elucidation problems, i.e., angiotensin II receptor antagonists, Leu-enkephalin and a hybrid morphine molecule, 5-HT_1D agonists, benzodiazepine receptor ligands, 5-HT₃ antagonists, dopamine D₂ antagonists, dopamine reuptake blockers and FKBP12 ligands. The resulting pharmacophores are generated rapidly and are in good agreement with those derived from alternative means.     

A genetic algorithm for structure-based de novo design

Genetic algorithms have properties which make them attractive in de novo drug design. Like other de novo design programs, genetic algorithms require a method to reduce the enormous search space of possible compounds. Most often this is done using information from known ligands. We have developed the ADAPT program, a genetic algorithm which uses molecular interactions evaluated with docking calculations as a fitness function to reduce the search space. ADAPT does not require information about known ligands. The program takes an initial set of compounds and iteratively builds new compounds based on the fitness scores of the previous set of compounds. We describe the particulars of the ADAPT algorithm and its application to three well-studied target systems. We also show that the strategies of enhanced local sampling and re-introducing diversity to the compound population during the design cycle provide better results than conventional genetic algorithm protocols.     

A simple protocol for the probability weights of the simulated tempering algorithm: applications to first-order phase transitions

The simulated tempering (ST) is an important method to deal with systems whose phase spaces are hard to sample ergodically. However, it uses accepting probabilities weights, which often demand involving and time consuming calculations. Here it is shown that such weights are quite accurately obtained from the largest eigenvalue of the transfer matrix--a quantity straightforward to compute from direct Monte Carlo simulations--thus simplifying the algorithm implementation. As tests, different systems are considered, namely, Ising, Blume-Capel, Blume-Emery-Griffiths, and Bell-Lavis liquid water models. In particular, we address first-order phase transition at low temperatures, a regime notoriously difficulty to simulate because the large free-energy barriers. The good results found (when compared with other well established approaches) suggest that the ST can be a valuable tool to address strong first-order phase transitions, a possibility still not well explored in the literature.     

FWAVina: A novel optimization algorithm for protein-ligand docking based on the fireworks algorithm

Protein-ligand docking is an essential process that has accelerated drug discovery. How to accurately and effectively optimize the predominant position and orientation of ligands in the binding pocket of a target protein is a major challenge. This paper proposed a novel ligand binding pose search method called FWAVina based on the fireworks algorithm, which combined the fireworks algorithm with the efficient Broyden-Fletcher-Goldfarb-Shannon local search method adopted in AutoDock Vina to address the pose search problem in docking. The FWA was used as a global optimizer to rapidly search promising poses, and the Broyden-Fletcher-Goldfarb-Shannon method was incorporated into FWAVina to perform an exact local search. FWAVina was developed and tested on the PDBbind and DUD-E datasets. The docking performance of FWAVina was compared with the original Vina program. The results showed that FWAVina achieves a remarkable execution time reduction of more than 50 % than Vina without compromising the prediction accuracies in the docking and virtual screening experiments. In addition, the increase in the number of ligand rotatable bonds has almost no effect on the efficiency of FWAVina. The higher accuracy, faster convergence and improved stability make the FWAVina method a better choice of docking tool for computer-aided drug design. The source code is available at https://github.com/eddyblue/FWAVina/.     

A new uniform mapping algorithm for sample selection

A new algorithm for sample selection in the field of experimental design is presented. This method was designed for a multivariate data set of samples where the variables' levels are pre‐determined by the system instead of being determined by the practitioner and especially appropriate for non‐symmetrical multivariable space. Symmetrical experimental designs are not applicable in either of the cases. Anyway, this method is also applicable to symmetrical designs. Several tests have been made for symmetrical and non‐symmetrical cases and also about an already treated real case, comparing the new algorithm with others previously known in literature. Its performance has been checked considering several evaluation quality criteria like D‐optimal, A‐optimal, G‐optimal and models error prediction. Copyright © 2008 John Wiley & Sons, Ltd.     

A fast genetic algorithm for RNA secondary structure analysis

A fast genetic algorithm GArna for mass calculations of RNA secondary structures through the Internet is proposed. The algorithm GArna was used to study the effects of nucleotide composition on characteristics of the secondary structure of random RNA sequences. A contextual characteristics for evaluation of the stability was proposed and the application of standard statistical tests for heterogeneous RNA samplings was justified. The structure-contextual characteristics by which the 5"-untranslated regions of high- and low-expression genes of dicot plants and mammals differ were found, and the results were interpreted in terms of secondary structure influence on translation initiation and on the general scheme of expression regulation. The application of the results obtained for the development of computer methods for RNA structural genomics, in particular, for RNA search in genome sequences, is discussed.     

An algorithm for the location of branching points on reaction paths

A branching point is a point on a reaction path leading from reactants to products (via a transition state) at which it is energetically favorable for the system to break symmetry. Such a point can be defined in terms of normal modes along the reaction path and corresponds to zero curvature (a zero Hessian eigenvalue) along a symmetry-breaking mode. An effective method for the location of such points is presented and realized in an efficient, practical algorithm designed for use in the ab initio program package Gaussian 82.     

分子在ITQ-3分子筛窄孔道内扩散的过渡态理论模型

建立了一个基于过渡态理论的分子在ITQ-3窄孔道方向扩散的模型. 该模型中, 由于分子从空腔中的一个吸附位越过势垒到相邻的另一个空腔中的吸附位需要克服很大的势垒能, 因而分子在势垒处可以简化处理为只存在排斥势, 可得到扩散系数依赖温度和Lennard-Jones作用参数的解析关系. 用分子动力学方法对CF₄在ITQ-3上扩散进行了模拟并验证了解析关系的合理性. 分子动力学模拟计算得到的扩散活化能、势垒能和吸附位势能与实际值相吻合. 模拟结果也显示了扩散系数依赖于附载量, 表现为先增大后减小的变化模式. 扩散活化能的计算证实了这一变化机理, 即当附载量增加时, 由于处于空腔中的分子彼此抬高了势能, 降低了扩散活化能, 使得扩散系数随附载量的增加而增大, 之后由于堵塞效应, 扩散系数随附载量的增加而逐步减小.     

A clustering algorithm based on two distance functions for MEC model

Haplotype reconstruction, based on aligned single nucleotide polymorphism (SNP) fragments, is to infer a pair of haplotypes from localized polymorphism data gathered through short genome fragment assembly. This paper first presents two distance functions, which are used to measure the difference degree and similarity degree between SNP fragments. Based on the two distance functions, a clustering algorithm is proposed in order to solve MEC model. The algorithm involves two sections. One is to determine the initial haplotype pair, the other concerns with inferring true haplotype pair by re-clustering. The comparison results prove that our algorithm utilizing two distance functions is effective and feasible.     

A surface hopping algorithm for nonadiabatic minimum energy path calculations

The article introduces a robust algorithm for the computation of minimum energy paths transiting along regions of near‐to or degeneracy of adiabatic states. The method facilitates studies of excited state reactivity involving weakly avoided crossings and conical intersections. Based on the analysis of the change in the multiconfigurational wave function the algorithm takes the decision whether the optimization should continue following the same electronic state or switch to a different state. This algorithm helps to overcome convergence difficulties near degeneracies. The implementation in the MOLCAS quantum chemistry package is discussed. To demonstrate the utility of the proposed procedure four examples of application are provided: thymine, asulam, 1,2‐dioxetane, and a three‐double‐bond model of the 11‐cis‐retinal protonated Schiff base. © 2015 Wiley Periodicals, Inc.     

A novel conformation optimization model and algorithm for structure-based drug design

In this paper, we present a multi-scale optimization model and an entropy-based genetic algorithm for molecular docking. In this model, we introduce to the refined docking design a concept of residue groups based on induced-fit and adopt a combination of conformations in different scales. A new iteration scheme, in conjunction with multi-population evolution strategy, entropy-based searching technique with narrowing down space and the quasi-exact penalty function, is developed to address the optimization problem for molecular docking. A new docking program that accounts for protein flexibility has also been developed. The docking results indicate that the method can be efficiently employed in structure-based drug design.     

Simple algorithm for isothermal-isobaric molecular dynamics

We review principles of non-Hamiltonian statistical mechanics and present a new set of equations and integration algorithm for isothermal-isobaric dynamics. The chief advantage of the present scheme is that it is somewhat simpler than previous methods. We perform numerical simulations to test the accuracy of the algorithm and compare its stability to that of a "gold standard," a symplectic integrator for Hamiltonian dynamics of the same system. The stability of the isothermal-isobaric algorithm is comparable to the stability of the symplectic integrator.     

A box-counting-based algorithm for computing Shannon entropy in molecular dynamics simulations

A box-counting-based algorithm (SEBC) has been developed for the numerical computation of the Shannon entropy from samples of continuous functions. Its performance was tested by applying it to several samples of known continuous distribution functions. The results obtained with SEBC reproduced those obtained by analytical or numerical integration. SEBC was also employed for computing the Shannon entropies of the steric energy, Sh(E(S)), of several amino acids from their in vacuo NVE molecular dynamics simulations using the AMBER-4 force field. The results obtained correlate linearly with the experimental standard thermodynamic entropies of these compounds. This work points to the possibility of introducing straightforward and reliable calculations of thermodynamic entropies from empirical linear relationships with Sh(E(S)) obtained from MD simulations.     

基于Arrhenius定理的化学动力学数值计算法

基于Arrhenius定理建立了一种新的化学动力学数值模拟方法.将其与化学动力学过程契合,能较好地体现化学动力学过程.将该方法对简单一级反应、平行反应和复杂的综合反应进行模拟计算,模拟结果与准确解相对误差小于0.5%.