A genetic algorithm for the automated generation of small organic molecules: Drug design using an evolutionary algorithm

Rational drug design involves finding solutions to large combinatorial problems for which an exhaustive search is impractical. Genetic algorithms provide a novel tool for the investigation of such problems. These are a class of algorithms that mimic some of the major characteristics of Darwinian evolution. LEA has been designed in order to conceive novel small organic molecules which satisfy quantitative structure-activity relationship based rules (fitness). The fitness consists of a sum of constraints that are range properties. The algorithm takes an initial set of fragments and iteratively improves them by means of crossover and mutation operators that are related to those involved in Darwinian evolution. The basis of the algorithm, its implementation and parameterization, are described together with an application in de novo molecular design of new retinoids. The results may be promising for chemical synthesis and show that this tool may find extensive applications in de novo drug design projects.     

Test of variational transition state theory with multidimensional tunneling contributions against experimental kinetic isotope effects for the CHnD4−n + OH→P (n=0, 4) reactions

 Variational transition state theory including tunneling corrections (as implemented in Polyrate 8.7) and using multilevel energy calculations at the MCCM-CCSD(T)-1sc level for the CH₄ + OH reaction and at the MCCM-CCSD(T)-2m level for the CD₄ + OH process, reproduces very well the experimental rate constants. However, no single methodology was found that reproduces equally well the experimental rate constants for both title reactions. Received: 24 March 2002 / Accepted: 11 April 2002 / Published online: 4 July 2002     

多组分多出口稀土串级萃取静态优化设计研究(I)静态设计算法

研究了多组分、多出口稀土串级萃取体系静态优化设计过程的精确计算方法. 首先推导出串级萃取体系最重要的物料平衡和萃取平衡关系, 其次根据分离要求等条件确定了各出口的相对流量, 利用萃取平衡和物料平衡关系进行静态递推, 并在求解过程中根据物料平衡关系引入了校正参数, 通过对递推结果的迭代校正, 最终得到收敛的计算结果, 解决了静态设计算法的关键问题. 这一方法为多组分多出口稀土串级萃取过程的静态优化设计提供了精确算法.     

A Procedure for Transforming Impedance Spectra for the Determination of Mechanism of Electrochemical Reactions

Transformation of impedance spectra into relaxation time spectra (RTS) is used for determining contributions of individual processes of the oxygen electroreduction reaction (OER) to the polarization resistance of the electrochemical cell. The transformation technique involves the solution of the convolution equation found with the aid of a modified Van Cittert iteration algorithm checked on model impedance spectra. The technique, when used to analyze impedance spectra of electrochemical cells air|Pt|YSZ|YSZ + Pt|air, shows that the conversion of a globular structure of the YSZ + Pt cermet layer to a columnar one is accompanied by a change of peak amplitudes in RTS. The revealed RTS dynamics when heated to 750°C is compared with peculiarities of individual processes in OER.     

1-芳基-2-丙酮的合成研究

以芳香胺为原料, 经重氮化和改进的Meerwein芳基取代反应, 合成了一系列的1-芳基-2-丙酮, 其中1-(3,5-二三氟甲基苯基)-2-丙酮是一个新化合物. 改进后的方法简化了合成步骤, 提高了收率, 可方便地用于在苯环上具有不同取代基的芳基丙酮的合成.     

Comparative analysis of affine scaling algorithms based on simplifying assumptions

We analyze several affine potential reduction algorithms for linear programming based on simplifying assumptions. We show that, under a strong probabilistic assumption regarding the distribution of the data in an iteration, the decrease in the primal potential function will be with high probability, compared to the guaranteed(1). ( 2n is a parameter in the potential function andn is the number of variables.) Under the same assumption, we further show that the objective reduction rate of Dikin's affine scaling algorithm is with high probability, compared to no guaranteed convergence rate.Research supported in part by NSF Grant DDM-8922636.     

Efficient algorithms for solving rank two and rank three bilinear programming problems

Finitely convergent algorithms for solving rank two and three bilinear programming problems are proposed. A rank k bilinear programming problem is a nonconvex quadratic programming problem with the following structure: % MathType!MTEF!2!1!+-% feaafeart1ev1aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn% hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr% 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4baFfea0dXde9vqpa0lb9% cq0dXdb9IqFHe9FjuP0-iq0dXdbba9pe0lb9hs0dXda91qaq-xfr-x% fj-hmeGabaqaciGacaGaaeqabaWaaeaaeaaakeaaieaacaWFTbGaa8% xAaiaa-5gacaWFPbGaa8xBaiaa-LgacaWF6bGaa8xzaiaa-bcacaWF% 7bacbiGaa43yamaaDaaaleaacaGFWaaabaGaa4hDaaaakiaa+Hhaca% GFRaGaa4hzamaaDaaaleaacaGFWaaabaGaa4hDaaaakiaa+LhacaGF% RaWaaabuaeaacaGFJbWaa0baaSqaaiaa+PgaaeaacaGF0baaaOGaam% iEaiabl+y6NjaadsgadaqhaaWcbaGaamOAaaqaaiaadshaaaGccaWG% 5bGaaiiFaaWcbaGaa8NAaiaa-1dacaWFXaaabeqdcqGHris5aOGaa4% hEaiabgIGiolaa+HfacaGFSaGaa4xEaiabgIGiolaa+LfacaWF9bGa% a8hlaaaa!5D2E!\[minimize \{ c_0^t x + d_0^t y + \sum\limits_{j = 1} {c_j^t xd_j^t y|} x \in X,y \in Y\} ,\]where X Rⁿ¹ and Y R ⁿ² are non-empty and bounded polytopes. We show that a variant of parametric simplex algorithm can solve large scale rank two bilinear programming problems efficiently. Also, we show that a cutting-cake algorithm, a more elaborate variant of parametric simplex algorithm can solve medium scale rank three problems.This research was supported in part by Grant-in-Aid for Scientific Research of the Ministry of Education, Science and Culture, Grant No. 63490010.     

Global optimization of univariate Lipschitz functions: II. New algorithms and computational comparison

We consider the following global optimization problems for a Lipschitz functionf implicitly defined on an interval [a, b]. Problem P: find a globally-optimal value off and a corresponding point; Problem Q: find a set of disjoint subintervals of [a, b] containing only points with a globally-optimal value and the union of which contains all globally optimal points. A two-phase algorithm is proposed for Problem P. In phase I, this algorithm obtains rapidly a solution which is often globally-optimal. Moreover, a sufficient condition onf for this to be the case is given. In phase II, the algorithm proves the-optimality of the solution obtained in phase I or finds a sequence of points of increasing value containing one with a globally-optimal value. The new algorithm is empirically compared (on twenty problems from the literature) with a best possible algorithm (for which the optimal value is assumed to be known), with a passive algorithm and with the algorithms of Evtushenko, Galperin, Shen and Zhu, Piyavskii, Timonov and Schoen. For small, the new algorithm requires only a few percent more function evaluations than the best possible one. An extended version of Piyavskii's algorithm is proposed for problem Q. A sufficient condition onf is given for the globally optimal points to be in one-to-one correspondance with the obtained intervals. This result is achieved for all twenty test problems.The research of the authors has been supported by AFOSR grants 0271 and 0066 to Rutgers University. Research of the second author has been also supported by NSERC grant GP0036426, FCAR grant 89EQ4144 and partially by AFOSR grant 0066. We thank Nicole Paradis for her help in drawing the figures.