Fusenes and benzenoids with perfect matchings

In this paper, a method to constructively enumerate fusenes and benzenoids with perfect matchings is given. It is based on an algorithm for generating all fusenes and benzenoids and introduces new restrictions into the generation process that avoid the generation of structures without perfect matchings.      

Fast generation of molecular surfaces from 3D data fields with an enhanced “marching cube” algorithm

An improved version of the “marching cubes” algorithm [W. Lorensen and H. Cline, Comp. Graph. 21 , (1987)] for the generation of isosurfaces from 3D data fields is presented and applied to molecular surfaces. The new algorithm avoids inconsistent pattern definitions of the original one, which lead to artificial gaps. The advantage of a logarithmic interpolation procedure, in particular for data fields typically occurring in molecular science, is demonstrated. An example is the generation of molecular surfaces based upon electron density data. © 1993 John Wiley & Sons, Inc.     

Calculations of a list of neighbors in Molecular Dynamics simulations

A new algorithm is proposed for the evaluation of nonbonded interactions in Molecular Dynamics simulations. The algorithm is based on a grid search and on partitioning of the atoms into boxes rather than on calculations of distances. The effort associated with the generation of the box list grows only linearly with the number of atoms. The algorithm is particularly advantageous for solvated systems. Test calculations show significant savings in CPU time and storage compared to commonly used algorithms for systems containing in excess of ca. 600 atoms.     

k‐Nearest neighbors optimization‐based outlier removal

Datasets of molecular compounds often contain outliers, that is, compounds which are different from the rest of the dataset. Outliers, while often interesting may affect data interpretation, model generation, and decisions making, and therefore, should be removed from the dataset prior to modeling efforts. Here, we describe a new method for the iterative identification and removal of outliers based on a k‐nearest neighbors optimization algorithm. We demonstrate for three different datasets that the removal of outliers using the new algorithm provides filtered datasets which are better than those provided by four alternative outlier removal procedures as well as by random compound removal in two important aspects: (1) they better maintain the diversity of the parent datasets; (2) they give rise to quantitative structure activity relationship (QSAR) models with much better prediction statistics. The new algorithm is, therefore, suitable for the pretreatment of datasets prior to QSAR modeling. © 2014 Wiley Periodicals, Inc.     

A self‐assembling neural network for modeling polymers

A central problem in modeling protein and other polymer structures is the generation of self‐avoiding chains which obey a priori distance restraint information which could include a folding potential function. This problem is usually addressed with a lattice model or a torsion space model of the polymer. Exhaustive searches in these spaces are of necessity exponentially complex. A new computer algorithm for modeling polymers and polymeric systems is described. This algorithm is a randomized algorithm based on a self‐assembling or Kohonen neural network. Given a defined chain topology, a defined spatial extent, and a prior probability distribution, it finds a set of coordinates which reproduce these properties. The convergence rate of the algorithm is linear with respect to the number of distance terms included. Modifications to the standard Kohonen algorithm to include a defined spatial metric, and a modified update rule improve the convergence of the standard algorithm and result in a highly efficient algorithm for building polymer models which are self avoiding and consistent with prior probability information and interatomic distance restraints. This revised version was published online in July 2006 with corrections to the Cover Date.     

Simulation of Amorphous Nylon 6 Using SuSi,a Strategy Based on Generation–Relaxation Algorithms

Summary: The ability of SuSi to generate microstructures of polymers with hydrogen bonding interactions has been checked. This is a random procedure recently developed to localize independent minima. Calculations were performed on nylon 6, a large number of equilibrated and relaxed atomistic models, i.e. microstructures without torsional strain and atomic overlaps, being generated. Results indicated that the generation algorithm implemented in SuSi underestimates the amount of amide groups involved in hydrogen bonding interactions. This is an expected result since no specific criterion was introduced in it to facilitate the formation of specific interactions. Several modifications have been introduced in the generation algorithm to overcome this limitation. The changes induced by these modifications in the generated microstructures are discussed.

A new computational strategy denoted SuSi generates atomistic models of hydrogen bond forming polymers with very reliable results.     

Generation of potential energy surfaces in high dimensions and their haptic exploration

A method is proposed for the automated generation of potential energy surfaces in high dimensions. It combines the existing algorithm for the definition of new energy data points, based on the interpolating moving least-squares algorithm with a simulated annealing procedure. This method is then studied in a haptic quantum chemistry environment that requires a fast evaluation of gradients on a potential energy surface with automatic improvement of its accuracy. As an example we investigate the nitrogen binding pathway in the Schrock dinitrogen fixation complex with this set-up.     

Computer program for finding all possible cycles in graphs

A new approach is presented for identifying all possible cycles in graphs. Input data are the total numbers of vertices and edges, as well as the vertex adjacencies using arbitrary vertex numbering. A homeomorphically reduced graph (HRG) is constructed by ignoring vertices of degree less than three. The algorithm is based on successive generation of possible edge-combinations in the HRG. If a combination yields a cycle, it is either printed or stored and then finally printed in a list of all possible cycles arranged in the order of increasing ring size. A unique numbering of the cycle is used. The computer program is listed and exemplified. Computing times are given.     

目标化合物析分系统中的重要算法

介绍了目标化合物析分系统中所用到的三个重要算法。它们是：最短拓扑距离的求解、析分过程结束的判别以及合成树的构建。分子结构中任意两个原子之间最短拓扑距离的求解是建立在采用队列数据结构的宽度优先搜索算法基础上的,析分过程结束的判别是由在新Morgan算法基础上产生的化合物的唯一编码和B－树两种算法构成,前者是为了将前体与原料库中每个化合物是否同构的复杂问题简化为码之间的比较问题;后者是一种高效文件组织方式,将代表原料库中化合物的唯一编码作为检索键来组织建库,从而实现对原料库的快速查询,合成树采用的是链表存储方式,每一个结点由六个域组成,且在建树和画树的过程中,均用前序遍历。这些算法是实现析分系统的基础,因此它们的正确设计与高效实现就显得尤为重要。     

Pattern-based algorithm for peptide sequencing from tandem high energy collision-induced dissociation mass spectra

A new strategy is reported for extracting complete and partial sequence information from collision-induced dissociation (CID) spectra of peptides, CID spectra are obtained from high energy CID of peptide molecular ions on a four-sector tandem mass spectrometer with an electro-optically coupled microchannel array detector, A peak detection routine reduces the spectrum to a list of peak masses and peak heights, which is then used for sequencing, The sequencing algorithm was designed to use spectral data to generate sequence fits directly rather than to use data to test the fit of series of sequence guesses. The peptide sequencing algorithm uses a pattern based on the polymeric nature of peptides to classify spectral peaks into sets that are related in a sequence-independent manner, It then establishes sequence relationships among these sets, Peak detection from raw data takes 10–20 s, with sequence generation requiring an additional 10–60 s on a Sun 3/60 workstation, The program is written in the C language to run on a Unix platform. The principal advantages of our method are in the speed of analysis and the potential for identifying modified or rare amino acids. The algorithm was designed to permit real-time sequencing but awaits hardware modifications to allow real-time access to CID spectra.     

TGMin: An efficient global minimum searching program for free and surface-supported clusters

In this article, we introduce an efficient global-minimum structural search program named Tsinghua Global Minimum 2 (TGMin-2), which is the successor of the original TGMin algorithm that was developed in our group in 2011. We have introduced a number of new features and improvements into TGMin-2, including a symmetric structure generation algorithm that can produce good initial seeds for small- and medium-size clusters, the duplicated structure identification algorithm, and the improved structure adaption algorithm that was implemented in the original TGMin code. To predict the simulated photoelectron spectrum (PE spectrum) automatically, we also implemented a standalone program named AutoPES (Auto Photoelectron Spectroscopy), which can be used to simulate PE spectra and compare them with experimental results automatically. We have demonstrated that TGMin-2 and AutoPES are powerful tools for studying free and surface-supported molecules, clusters, and nanoclusters. © 2018 Wiley Periodicals, Inc.     

A scalable approach to combinatorial library design for drug discovery

In this paper, we propose an algorithm for the design of lead generation libraries required in combinatorial drug discovery. This algorithm addresses simultaneously the two key criteria of diversity and representativeness of compounds in the resulting library and is computationally efficient when applied to a large class of lead generation design problems. At the same time, additional constraints on experimental resources are also incorporated in the framework presented in this paper. A computationally efficient scalable algorithm is developed, where the ability of the deterministic annealing algorithm to identify clusters is exploited to truncate computations over the entire data set to computations over individual clusters. An analysis of this algorithm quantifies the tradeoff between the error due to truncation and computational effort. Results applied on test data sets corroborate the analysis and show improvement by factors as large as 10 or more, depending on the data sets.     

A new multiscale modeling method for simulating the loss processes in polymer solar cell nanodevices

The photoelectric power conversion efficiency of polymer solar cells is till now, compared to conventional inorganic solar cells, still relatively low with maximum values ranging from 7% to 8%. This essentially relates to the existence of exciton and charge carrier loss phenomena, reducing the performance of polymer solar cells significantly. In this paper we introduce a new computer simulation technique, which permits to explore the causes of the occurrence of such phenomena at the nanoscale and to design new photovoltaic materials with optimized opto-electronic properties. Our approach consists in coupling a mesoscopic field-theoretic method with a suitable dynamic Monte Carlo algorithm, to model the elementary photovoltaic processes. Using this algorithm, we investigate the influence of structural characteristics and different device conditions on the exciton generation and charge transport efficiencies in case of a novel nanostructured polymer blend. More specifically, we find that the disjunction of continuous percolation paths leads to the creation of dead ends, resulting in charge carrier losses through charge recombination. Moreover, we observe that defects are characterized by a low exciton dissociation efficiency due to a high charge accumulation, counteracting the charge generation process. From these observations, we conclude that both the charge carrier loss and the exciton loss phenomena lead to a dramatic decrease in the internal quantum efficiency. Finally, by analyzing the photovoltaic behavior of the nanostructures under different circuit conditions, we demonstrate that charge injection significantly determines the impact of the defects on the solar cell performance.     

A fast exchange algorithm for designing focused libraries in lead optimization

Combinatorial chemistry is widely used in drug discovery. Once a lead compound has been identified, a series of R-groups and reagents can be selected and combined to generate new potential drugs. The combinatorial nature of this problem leads to chemical libraries containing usually a very large number of virtual compounds, far too large to permit their chemical synthesis. Therefore, one often wants to select a subset of "good" reagents for each R-group of reagents and synthesize all their possible combinations. In this research, one encounters some difficulties. First, the selection of reagents has to be done such that the compounds of the resulting sublibrary simultaneously optimize a series of chemical properties. For each compound, a desirability index, a concept proposed by Harrington,(20) is used to summarize those properties in one fitness value. Then a loss function is used as objective criteria to globally quantify the quality of a sublibrary. Second, there are a huge number of possible sublibraries, and the solutions space has to be explored as fast as possible. The WEALD algorithm proposed in this paper starts with a random solution and iterates by applying exchanges, a simple method proposed by Fedorov(13) and often used in the generation of optimal designs. Those exchanges are guided by a weighting of the reagents adapted recursively as the solutions space is explored. The algorithm is applied on a real database and reveals to converge rapidly. It is compared to results given by two other algorithms presented in the combinatorial chemistry literature: the Ultrafast algorithm of D. Agrafiotis and V. Lobanov and the Piccolo algorithm of W. Zheng et al.     

Search for new red phosphors using genetic algorithm-assisted combinatorial chemistry

A genetic algorithm was employed in association with high-throughput synthesis and characterization in an attempt to search for red phosphors with high photoluminescent intensity. A tetravalent manganese-doped alkali earth germanium oxide system, with an emission color close to a desirable deep red, was screened with the assistance of a genetic algorithm to pinpoint the phosphor exhibiting the highest photoluminescence. As the genetic algorithm was in progress, the PL intensity increased and maximized in the fourth generation. The highest and the average PL intensity of the fourth generation improved by 23 and 120%, respectively, compared with that of the first generation.     

Automated protein structure determination from NMR spectra

Fully automated structure determination of proteins in solution (FLYA) yields, without human intervention, three-dimensional protein structures starting from a set of multidimensional NMR spectra. Integrating existing and new software, automated peak picking over all spectra is followed by peak list filtering, the generation of an ensemble of initial chemical shift assignments, the determination of consensus chemical shift assignments for all (1)H, (13)C, and (15)N nuclei, the assignment of NOESY cross-peaks, the generation of distance restraints, and the calculation of the three-dimensional structure by torsion angle dynamics. The resulting, preliminary structure serves as additional input to the second stage of the procedure, in which a new ensemble of chemical shift assignments and a refined structure are calculated. The three-dimensional structures of three 12-16 kDa proteins computed with the FLYA algorithm coincided closely with the conventionally determined structures. Deviations were below 0.95 A for the backbone atom positions, excluding the flexible chain termini. 96-97% of all backbone and side-chain chemical shifts in the structured regions were assigned to the correct residues. The purely computational FLYA method is suitable for substituting all manual spectra analysis and thus overcomes a main efficiency limitation of the NMR method for protein structure determination.