Design and Prioritization of Plates for High-Throughput Screening

A general algorithm for the prioritization and selection of plates for high-throughput screening is presented. The method uses a simulated annealing algorithm to search through the space of plate combinations for the one that maximizes some user-defined objective function. The algorithm is robust and convergent, and permits the simultaneous optimization of multiple design objectives, including molecular diversity, similarity to known actives, predicted activity or binding affinity, and many others. It is shown that the arrangement of compounds among the plates may have important consequences on the ability to design a well-targeted and cost-effective experiment. To that end, two simple and effective schemes for the construction of homogeneous and heterogeneous plates are outlined, using a novel similarity sorting algorithm based on one-dimensional nonlinear mapping.

[1]  David Weininger,et al.  Stigmata: An Algorithm To Determine Structural Commonalities in Diverse Datasets , 1996, J. Chem. Inf. Comput. Sci..

[2]  Dimitris K. Agrafiotis,et al.  A Constant Time Algorithm for Estimating the Diversity of Large Chemical Libraries , 2001, J. Chem. Inf. Comput. Sci..

[3]  Dimitris K. Agrafiotis,et al.  Nonlinear Mapping Networks , 2000, J. Chem. Inf. Comput. Sci..

[4]  Dimitris K. Agrafiotis,et al.  An Efficient Implementation of Distance-Based Diversity Measures Based on k-d Trees , 1999, J. Chem. Inf. Comput. Sci..

[5]  David J. Cummins,et al.  Molecular Diversity in Chemical Databases: Comparison of Medicinal Chemistry Knowledge Bases and Databases of Commercially Available Compounds , 1996, J. Chem. Inf. Comput. Sci..

[6]  Jennifer L. Miller,et al.  Combinatorial Library Design: Maximizing Model-Fitting Compounds within Matrix Synthesis Constraints , 2000, J. Chem. Inf. Comput. Sci..

[7]  A. Good,et al.  New methodology for profiling combinatorial libraries and screening sets: cleaning up the design process with HARPick. , 1997, Journal of medicinal chemistry.

[8]  Edward P. Jaeger,et al.  Application of Genetic Algorithms to Combinatorial Synthesis: A Computational Approach to Lead Identification and Lead Optimization†,∇ , 1996 .

[9]  David Chapman,et al.  The measurement of molecular diversity: A three-dimensional approach , 1996, J. Comput. Aided Mol. Des..

[10]  Darren V. S. Green,et al.  Selecting Combinatorial Libraries to Optimize Diversity and Physical Properties , 1999, J. Chem. Inf. Comput. Sci..

[11]  Robert P. Sheridan,et al.  Using a Genetic Algorithm To Suggest Combinatorial Libraries , 1995, J. Chem. Inf. Comput. Sci..

[12]  Dimitris K. Agrafiotis,et al.  Multidimensional scaling and visualization of large molecular similarity tables , 2001, J. Comput. Chem..

[13]  Dimitris K. Agrafiotis,et al.  Nonlinear mapping of massive data sets by fuzzy clustering and neural networks , 2001, J. Comput. Chem..

[14]  A. N. Jain,et al.  IcePick: a flexible surface-based system for molecular diversity. , 1999, Journal of medicinal chemistry.

[15]  D K Agrafiotis,et al.  Kolmogorov-Smirnov statistic and its application in library design. , 2000, Journal of molecular graphics & modelling.

[16]  Dimitris K. Agrafiotis,et al.  Stochastic Similarity Selections from Large Combinatorial Libraries , 2000, J. Chem. Inf. Comput. Sci..

[17]  Klaus Gubernator,et al.  Optimization of the Biological Activity of Combinatorial Compound Libraries by a Genetic Algorithm , 1995 .

[18]  Stephen D. Pickett,et al.  Diversity Profiling and Design Using 3D Pharmacophores: Pharmacophore-Derived Queries (PDQ) , 1996, J. Chem. Inf. Comput. Sci..

[19]  Dimitris K. Agrafiotis,et al.  Ultrafast Algorithm for Designing Focused Combinational Arrays , 2000, J. Chem. Inf. Comput. Sci..

[20]  Y. Martin,et al.  Designing combinatorial library mixtures using a genetic algorithm. , 1997, Journal of medicinal chemistry.

[21]  K. M. Smith,et al.  Novel software tools for chemical diversity , 1998 .

[22]  Eric J. Martin,et al.  Does Combinatorial Chemistry Obviate Computer-Aided Drug Design?o Reviews in Computational Chemistry , 2007 .

[23]  Dimitris K. Agrafiotis,et al.  Stochastic Algorithms for Maximizing Molecular Diversity , 1997, J. Chem. Inf. Comput. Sci..

[24]  N. Trinajstic,et al.  Information theory, distance matrix, and molecular branching , 1977 .

[25]  Robin Taylor,et al.  Simulation Analysis of Experimental Design Strategies for Screening Random Compounds as Potential New Drugs and Agrochemicals , 1995, J. Chem. Inf. Comput. Sci..

[26]  Robert D Clark,et al.  Neighborhood behavior: a useful concept for validation of "molecular diversity" descriptors. , 1996, Journal of medicinal chemistry.

[27]  Yvonne C. Martin,et al.  The Information Content of 2D and 3D Structural Descriptors Relevant to Ligand-Receptor Binding , 1997, J. Chem. Inf. Comput. Sci..

[28]  Dimitris K. Agrafiotis,et al.  The Measurement of Molecular Diversity , 2000 .

[29]  Dimitris K. Agrafiotis,et al.  The Diversity of Chemical Libraries , 2002 .

[30]  Yvonne C. Martin,et al.  Use of Structure-Activity Data To Compare Structure-Based Clustering Methods and Descriptors for Use in Compound Selection , 1996, J. Chem. Inf. Comput. Sci..

[31]  J. Kruskal.  Nonmetric multidimensional scaling: A numerical method , 1964 .

[32]  Johnz Willett.  Similarity and Clustering in Chemical Information Systems , 1987 .

[33]  Jonathan A. Ellman,et al.  Synthesis and Applications of Small Molecule Libraries. , 1996, Chemical reviews.

[34]  D C Spellmeyer,et al.  Measuring diversity: experimental design of combinatorial libraries for drug discovery. , 1995, Journal of medicinal chemistry.

[35]  Peter Willett,et al.  Similarity Searching and Clustering of Chemical-Structure Databases Using Molecular Property Data , 1994, J. Chem. Inf. Comput. Sci..

[36]  W. Torgerson.  Multidimensional scaling: I. Theory and method , 1952 .

[37]  Dimitris K. Agrafiotis.  On the Use of Information Theory for Assessing Molecular Diversity , 1997, J. Chem. Inf. Comput. Sci..