Structure-based combinatorial library design: methodologies and applications

Rational design of small focused libraries that are biased toward specific therapeutic targets is currently at the forefront of combinatorial library design. Various structure-based design strategies can be implemented in focused library design when the 3D structure of the target is available through X-ray or NMR determination. This review discusses the major methods and programs specifically developed for the purpose of designing combinatorial libraries under the constraint of the binding site of a biological target, with emphasis on their advantages and disadvantages. Examples of the successful application of these methodologies are highlighted, demonstrating their performances within the practical drug discovery process.     

Structure-based design of inhibitors of the rice blast fungal enzyme trihydroxynaphthalene reductase

Rice Blast Disease, caused by the fungus Pyricularia oryzae, is one of the most important diseases of rice. Several enzymes in the melanin biosynthetic pathway have proven to be valuable targets for development of rice blast fungicides. In particular, inhibitors of trihydroxynaphthalene reductase (3HNR), which catalyzes the conversion of trihydroxynaphthalene to vermelone, have yielded commercially useful rice fungicides. The X-ray structure of 3HNR has been published recently, presenting an opportunity to use this information in the de novo design of novel 3HNR inhibitors that may exhibit useful rice blast activity. We used the LeapFrog program to develop a docking model for interaction of ligands with the active site of THNR. The final model gave a good correlation between calculated binding energy and log Ki and was used to design novel ligands and score compounds for synthesis. Using this as a tool, we synthesized inhibitors in the nanomolar range and also developed several inhibitors that did not conform to the properties of the THNR active site. Leapfrog was able to locate a previously unrecognized binding pocket that could accommodate these otherwise anomalous regions of structure.     

Structure-based prediction of MHC-peptide association: algorithm comparison and application to cancer vaccine design

Peptide vaccination for cancer immunotherapy requires identification of peptide epitopes derived from antigenic proteins associated with the tumor. Such peptides can bind to MHC proteins (MHC molecules) on the tumor-cell surface, with the potential to initiate a host immune response against the tumor. Computer prediction of peptide epitopes can be based on known motifs for peptide sequences that bind to a certain MHC molecule, on algorithms using experimental data as a training set, or on structure-based approaches. We have developed an algorithm, which we refer to as PePSSI, for flexible structural prediction of peptide binding to MHC molecules. Here, we have applied this algorithm to identify peptide epitopes (of nine amino acids, the common length) from the sequence of the cancer-testis antigen KU-CT-1, based on the potential of these peptides to bind to the human MHC molecule HLA-A2. We compared the PePSSI predictions with those of other algorithms and found that several peptides predicted to be strong HLA-A2 binders by PePSSI were similarly predicted by another structure-based algorithm, PREDEP. The results show how structure-based prediction can identify potential peptide epitopes without known binding motifs and suggest that side chain orientation in binding peptides may be obtained using PePSSI.     

Structure-based design of inhibitors of NS3 serine protease of hepatitis C virus

We have designed small focused combinatorial library of hexapeptide inhibitors of NS3 serine protease of the hepatitis C virus (HCV) by structure-based molecular design complemented by combinatorial optimisation of the individual residues. Rational residue substitutions were guided by the structure and properties of the binding pockets of the enzyme's active site. The inhibitors were derived from peptides known to inhibit the NS3 serine protease by using unusual amino acids and alpha-ketocysteine or difluoroaminobutyric acid, which are known to bind to the S1 pocket of the catalytic site. Inhibition constants (Ki) of the designed library of inhibitors were predicted from a QSAR model that correlated experimental Ki of known peptidic inhibitors of NS3 with the enthalpies of enzyme-inhibitor interaction computed via molecular mechanics and the solvent effect contribution to the binding affinity derived from the continuum model of solvation. The library of the optimised inhibitors contains promising drug candidates-water-soluble anionic hexapeptides with predicted Ki* in the picomolar range.     

Structure-based drug design to the discovery of new 2-aminothiazole CDK2 inhibitors

N-(5-Bromo-1,3-thiazol-2-yl)butanamide (compound 1) was found active (IC50=808 nM) in a high throughput screening (HTS) for CDK2 inhibitors. By exploiting crystal structures of several complexes between CDK2 and inhibitors and applying structure-based drug design (SBDD), we rapidly discovered a very potent and selective CDK2 inhibitor 4-[(5-isopropyl-1,3-thiazol-2-yl)amino] benzenesulfonamide (compound 4, IC50=20 nM). The syntheses, structure-based analog design, kinases inhibition data and X-ray crystallographic structures of CDK2/inhibitor complexes are reported.     

二烷氧基喹唑啉类PDGFR抑制剂的定量构效关系及分子设计

用量子化学密度泛函、分子力学及统计方法,对二烷氧基喹唑啉衍生物进行定量构效关系(QSAR)研究.由计算所得的化合物分子的几何结构、电子结构参数和分子性质为广义描述符(变量),通过逐步回归分析,筛选出主要因素,建立QSAR方程.结果表明化合物的偶极距(μ),A环C1和C3原子的净电荷(QC1和QC3)以及取代基R7的立体参数(MR7)是影响化合物抑制活性的主要因素.方程的拟合相关系数(r2)和交叉验证系数(q2)分别为0.874和0.8093,表明方程具有良好的预测能力,可用于预测未知化合物的活性.基于此QSAR方程,设计了4个具有较高抑制活性的新的化合物并有待实验的验证.     

Analytical derivatives technology for structural shape design

The ability to perform and evaluate the effect of shape changes on the stress and modal responses of components is an important ingredient in the “design” of aircraft engine components. The classical design of experiments (DOE)-based approach that is motivated from statistics (for physical experiments) is one of the possible approaches for the evaluation of the component response with respect to design parameters [Myers, Montgomery. Response surface methodology, process and product optimization using design of experiments. John Wiley and Sons, NY (1995)]. As the underlying physical model used for the component response is deterministic and understood through a computer simulation model, one needs to re-think the use of the classical DOE techniques for this class of problems. In this paper, we explore an alternate sensitivity-analysis-based technique where a deterministic parametric response is constructed using exact derivatives of the complex finite-element (FE)-based computer models to design parameters. The method is based on a discrete sensitivity analysis formulation using semi-automatic differentiation (Griewank, SIAM (2000), ADIFOR, Automatic Differentiation of FORTRAN codes ) to compute the Taylor series or its Pade equivalent for finite-element-based responses. Shape design or optimization in the context of finite element modeling is challenging because the evaluation of the response for different shape requires the need for a meshing consistent with the new geometry. This paper examines the differences in the nature and performance (accuracy and efficiency) of the analytical derivatives approach against other existing approaches with validation on several benchmark structural applications. The use of analytical derivatives for parametric analysis is demonstrated to have accuracy benefits on certain classes of shape applications.     

Approximation and derivatives of probabilities of survival in structural analysis and design

Yield stresses, allowable stresses, moment capacities (plastic moments), external loadings, manufacturing errors, etc., are not fixed quantities in practice, but must be modelled as random variables with a certain joint probability distribution. In reliability-oriented structural optimization the violation of the random behavioural constraints are evaluated by means of the corresponding probabilityp _s of survival. Hence, the approximative computation ofp _s and its sensitivities is of utmost importance. After the consideration of lower bounds ofp _s based on a selection of certain redundants in the vector of internal forces/bending moments, and the consideration of upper bounds ofp _s based on an optimizational representation of the yield or safety constraints by a pair of dual linear programs, a conical representation ofp _s is introduced based on a coneY _o of admissible pairs of external loads/strength increaments. Approximations ofp _s can be constructed then by replacing the (finitely generated) coneY _o by more simple ones, e.g. spherical or ellipsoidal cones. For the direct numerical computation of sensitivities ofp _s and its bounds or approximations by using e.g. sampling methods or asymptotic expansion techniques based on Laplace integral representation of multiple integrals, exact differentiation formulae — of arbitrary order — forp _s and its bounds or approximations with respect to deterministic input or design variables are obtained by applying the transformation method/stochastic completion techniques; the derivatives ofp _s are represented again by certain expectations or multiple integrals.     

一种基于结构的本体分解方法

RDF三元组构成的图模型是本体表示方法的一种,主体和客体对应图中的结点,谓词对应图中的边.本文首先通过查询获取本体的三元组表示,生成对应的图;然后对图做预处理,为不同种类的边设定不同的重要度值;使用社会网理论计算结点之间的依赖度,通过依赖图的分解达到本体分解的目的.本方法修正了基于结构的类层次分解算法,使得本体分解更加合理.     

基于树结构的数据库设计方案及应用

在需求不明确的情况下,用传统的数据库设计方法组织数据比较困难,数据层次性较差,且无法设计出一个通用的库,造成设计周期长、代码不易重用等问题,针对该问题提出一种新的基于树的数据库设计方法,该方法简单、直观、易于数据的组织,提高数据库设计的灵活性和通用性,在水库移民补偿金信息管理系统中得到较好的应用。     

Structure-based analysis of Bacilli and plasmid dihydrofolate reductase evolution

Dihydrofolate reductase (DHFR), a key enzyme in tetrahydrofolate-mediated biosynthetic pathways, has a structural motif known to be highly conserved over a wide range of organisms. Given its critical role in purine and amino acid synthesis, DHFR is a well established therapeutic target for treating a wide range of prokaryotic and eukaryotic infections as well as certain types of cancer. Here we present a structural-based computer analysis of bacterial (Bacilli) and plasmid DHFR evolution. We generated a structure-based sequence alignment using 7 wild-type DHFR x-ray crystal structures obtained from the RCSB Protein Data Bank and 350 chromosomal and plasmid homology models we generated from sequences obtained from the NCBI Protein Database. We used these alignments to compare active site and non-active site conservation in terms of amino acid residues, secondary structure and amino acid residue class. With respect to amino acid sequences and residue classes, active-site positions in both plasmid and chromosomal DHFR are significantly more conserved than non-active site positions. Secondary structure conservation was similar for active site and non-active site positions. Plasmid-encoded DHFR proteins have greater degree of sequence and residue class conservation, particularly in sequence positions associated with a network of concerted protein motions, than chromosomal-encoded DHFR proteins. These structure-based were used to build DHFR specific phylogenetic trees from which evidence for horizontal gene transfer was identified.     

Outline字体结构式压缩算法及其实现

针对CJK Outline字体在存储量上存在的不足,本文提出一种结构式压缩算法。算法对CJK字体进行集合变换,得到笔划集合元素;并利用聚类算法得到模板笔划;对相似数据进行统一存储与调用。同时,本文还提出了一种基于笔划段的笔划抽取算法,从图论角度实现了集合变换。结果显示,算法取得了较好的效果,而且适用于多种字体。     

Use of structural dynamic and fatigue sensitivity derivatives in an automotive design optimization

Direct accounting for durability rarely finds its way into multidisciplinary optimization. Though reduction of loads by some means can certainly have a beneficial influence on the fatigue performance of a structure, changes in load levels are not a direct measure of the influence of design changes on fatigue performance. In this paper, a previously described method for calculating design sensitivities of a fatigue performance index is used in a simple optimization of suspension damping and stiffness on a simple truck model. The dynamic loading is a conceptual representation of the industrial practice of road testing and simulation. Results demonstrate the feasibility of using a direct measure of fatigue performance in formal structural optimization.     

Topological derivatives applied to fluid flow channel design optimization problems

Topology optimization methods application for viscous flow problems is currently an active area of research. A general approach to deal with shape and topology optimization design is based on the topological derivative. This relatively new concept represents the first term of the asymptotic expansion of a given shape functional with respect to the small parameter which measures the size of singular domain perturbations, such as holes and inclusions. In previous topological derivative-based formulations for viscous fluid flow problems, the topology is obtained by nucleating and removing holes in the fluid domain which creates numerical difficulties to deal with the boundary conditions for these holes. Thus, we propose a topological derivative formulation for fluid flow channel design based on the concept of traditional topology optimization formulations in which solid or fluid material is distributed at each point of the domain to optimize the cost function subjected to some constraints. By using this idea, the problem of dealing with the hole boundary conditions during the optimization process is solved because the asymptotic expansion is performed with respect to the nucleation of inclusions – which mimic solid or fluid phases – instead of inserting or removing holes in the fluid domain, which allows for working in a fixed computational domain. To evaluate the formulation, an optimization problem which consists in minimizing the energy dissipation in fluid flow channels is implemented. Results from considering Stokes and Navier-Stokes are presented and compared, as well as two- (2D) and three-dimensional (3D) designs. The topologies can be obtained in a few iterations with well defined boundaries.     

On design derivatives for optimization with a critical point constraint

Design optimization of geometrically nonlinear structures with a critical point constraint is considered. A staggered scheme is applied to the optimization problem and the reduced optimization problem is solved at the critical point. Derivatives of the objective function and constraints are defined consistently with the algorithmic steps of the staggered scheme.It is noticed that different schemes require different design derivatives of the objective function and constraints. It is stressed that a distinction must be made between the derivative of displacements at the critical load and the derivative of critical displacements. For the sake of simplicity a nonlinear two-bar truss structure is used to show that their properties are quite different; while the first one grows to infinity when approaching the critical point and thus does not exist, the other exists at the critical point and is equal to zero.Subsequently, two methods of computing the design derivative of critical loads are analysed, and it is demonstrated, for the truss example, that both methods yield correct results. Then, two optimization problems, i.e. the minimum volume problem and the maximum critical load problem, are formulated. Both problems are solved for the two-bar truss, and yield results that compare favourably with those obtained analytically. The solution scheme is shown to be insensitive to initial errors in the determination of the critical point.     

On design derivatives for optimization with a critical point constraint

Design optimization of geometrically nonlinear structures with a critical point constraint is considered. A staggered scheme is applied to the optimization problem and the reduced optimization problem is solved at the critical point. Derivatives of the objective function and constraints are defined consistently with the algorithmic steps of the staggered scheme. It is noticed that different schemes require different design derivatives of the objective function and constraints. It is stressed that a distinction must be made between the derivative of displacements at the critical load and the derivative of critical displacements. For the sake of simplicity a nonlinear two-bar truss structure is used to show that their properties are quite different; while the first one grows to infinity when approaching the critical point and thus does not exist, the other exists at the critical point and is equal to zero. Subsequently, two methods of computing the design derivative of critical loads are analysed, and it is demonstrated, for the truss example, that both methods yield correct results. Then, two optimization problems, i.e. the minimum volume problem and the maximum critical load problem, are formulated. Both problems are solved for the two-bar truss, and yield results that compare favourably with those obtained analytically. The solution scheme is shown to be insensitive to initial errors in the determination of the critical point.     

Structure-based graph distance measures of high degree of precision

In recent years, evaluating graph distance has become more and more important in a variety of real applications and many graph distance measures have been proposed. Among all of those measures, structure-based graph distance measures have become the research focus due to their independence of the definition of cost functions. However, existing structure-based graph distance measures have low degree of precision because only node and edge information of graphs are employed in these measures. To improve the precision of graph distance measures, we define substructure abundance vector (SAV) to capture more substructure information of a graph. Furthermore, based on SAV, we propose unified graph distance measures which are generalization of the existing structure-based graph distance measures. In general, the unified graph distance measures can evaluate graph distance in much finer grain. We also show that unified graph distance measures based on occurrence mapping and some of their variants are metrics. Finally, we apply the unified graph distance metric and its variants to the population evolution analysis and construct distance graphs of marker networks in three populations, which reflect the single nucleotide polymorphism (SNP) linkage disequilibrium (LD) differences among these populations.     

基于黑板结构的足球机器人智能调度方案设计

通过分析足球机器人决策子系统中智能调度以及机器人死锁问题。结合足球机器人自身的特点,提出一种基于黑板一知识源结构的足球机器人智能调度方案。该方案通过对黑板、知识源、控制机制的设计,能解决足球机器人中智能调度以及死锁问题,增强机器人的整体配合。     

Structure-based dynamic characteristics of planar linkages including platform-type robots

A comparative study of kinematic chains and their inversions at the conceptual stage of design is expected to help the designer in selecting the best possible chain and inversion for the specified task. To accomplish this, the designer should be able to read the characteristics of the chains based on their topology. It is only necessary to associate logically certain characteristics, weaknesses, and strengths of a chain to perform a task with the structure of the chain and then generalize. Based on this belief, work has been reported earlier to assess the ability of a chain to reveal some of the characteristics, such as structural error, performance, static, and kinematic behavior. In this study, an effort was made to model a chain as a system of dynamically equivalent lumped masses, interconnected, and then, through energy considerations, show that the distance between ground link and joint masses can be taken as the criterion to compare the chains from the viewpoint of balancing and their expected dynamic behavior. The concepts developed are applied to planar in-parallel robots, which are gaining in importance. © 1997 John Wiley & Sons, Inc.     

基于多层分布式结构的TFCM系统的设计与实现

分析了销售管理的业务模型和多层分布式体系结构,提出了同方销售管理系统TFCM的功能模型和多层分布式结构模型,采用组件技术进行了设计与实现,并针对若干问题提出了优化方法。