Expediting Combinatorial Data Set Analysis by Combining Human and Algorithmic Analysis.

A challenge in combinatorial materials science remains the efficient analysis of X-ray diffraction (XRD) data and its correlation to functional properties. Rapid identification of phase-regions and proper assignment of corresponding crystal structures is necessary to keep pace with the improved methods for synthesizing and characterizing materials libraries. Therefore, a new modular software called htAx (high-throughput analysis of X-ray and functional properties data) is presented that couples human intelligence tasks used for "ground-truth" phase-region identification with subsequent unbiased verification by an algorithm to efficiently analyze which phases are present in a materials library. Identified phases and phase-regions may then be correlated to functional properties in an expedited manner. For the functionality of htAx to be proven, two previously published XRD benchmark data sets of the materials systems Al-Cr-Fe-O and Ni-Ti-Cu are analyzed by htAx. The analysis of ∼1000 XRD patterns takes less than 1 day with htAx. The proposed method reliably identifies phase-region boundaries and robustly identifies multiphase structures. The method also addresses the problem of identifying regions with previously unpublished crystal structures using a special daisy ternary plot.

Decoding split and pool combinatorial libraries with electron-transfer dissociation tandem mass spectrometry.

Screening of bead-based split and pool combinatorial chemistry libraries is a powerful approach to aid the discovery of new chemical compounds able to interact with, and modulate the activities of, protein targets of interest. Split and pool synthesis provides for large and well diversified chemical libraries, in this case comprised of oligomers generated from a well-defined starting set. At the end of the synthesis, each bead in the library displays many copies of a unique oligomer sequence. Because the sequence of the oligomer is not known at the time of screening, methods for decoding of the sequence of each screening "hit" are essential. Here we describe an electron-transfer dissociation (ETD) based tandem mass spectrometry approach for the decoding of mass-encoded split and pool libraries. We demonstrate that the newly described "chiral oligomers of pentenoic amides (COPAs)" yield non-sequence-specific product ions upon collisional activated dissociation; however, complete sequence information can be obtained with ETD. To aid in the decoding of libraries from MS and MS/MS data, we have incorporated (79)Br/(81)Br isotope "tags" to differentiate N- and C-terminal product ions. In addition, we have created "Hit-Find," a software program that allows users to generate libraries in silico. The user can then search all possible members of the chemical library for those that fall within a user-defined mass error.

State estimation for delayed genetic regulatory networks based on passivity theory.

This paper is concerned with the state estimation problem for delayed genetic regulatory networks (GRNs) based on passivity analysis approach. The main purpose of the problem is to design the estimator to approximate the true concentrations of the mRNA and protein through available measurement outputs. Time-varying delays are explicitly assumed to be non-differentiable and constraint on the derivative of the time-varying delay is less than one can be removed. Based on the Lyapunov-Krasovskii functionals involving triple integral terms, using some integral inequalities and convex combination technique, a delay-dependent passivity criterion is established for GRNs in terms of linear matrix inequalities (LMIs) that can efficiently be solved by any available LMI solvers. Finally, numerical examples and simulation are presented to demonstrate the efficiency of the proposed estimation schemes.

Molecular library synthesis using complex substrates: expanding the framework of triterpenoids.

The remodeling of a natural product core framework by means of diversity-oriented synthesis (DOS) is a valuable approach to access diverse/biologically relevant chemical space and to overcome the limitations of combinatorial-type compounds. Here we provide proof of principle and a thorough conformational analysis for a general strategy whereby the inherent complexity of a starting material is used to define the regio- and stereochemical outcomes of reactions in chemical library construction. This is in contrast to the traditional DOS logic employing reaction development and catalysis to drive library diversity.

A description of large-scale metabolomics studies: increasing value by combining metabolomics with genome-wide SNP genotyping and transcriptional profiling.

The metabolome, defined as the reflection of metabolic dynamics derived from parameters measured primarily in easily accessible body fluids such as serum, plasma, and urine, can be considered as the omics data pool that is closest to the phenotype because it integrates genetic influences as well as nongenetic factors. Metabolic traits can be related to genetic polymorphisms in genome-wide association studies, enabling the identification of underlying genetic factors, as well as to specific phenotypes, resulting in the identification of metabolome signatures primarily caused by nongenetic factors. Similarly, correlation of metabolome data with transcriptional or/and proteome profiles of blood cells also produces valuable data, by revealing associations between metabolic changes and mRNA and protein levels. In the last years, the progress in correlating genetic variation and metabolome profiles was most impressive. This review will therefore try to summarize the most important of these studies and give an outlook on future developments.

Expanding the medicinally relevant chemical space with compound libraries.

Analysis of marketed drugs and commercial vendor libraries used in high-throughput screening suggests that the medicinally relevant chemical space may be expanded to unexplored regions. Novel regions of the chemical space can be conveniently explored with structurally unique molecules with increased complexity and balanced physicochemical properties. As a case study, we discuss the chemoinformatic profile of natural products in the Traditional Chinese Medicine (TCM) database and a large collection assembled from 30 small-molecule combinatorial libraries with emphasis on assessing molecular complexity. The herein surveyed combinatorial libraries have been successfully used over the past 20 years to identify novel bioactive compounds across different therapeutic areas. Combinatorial libraries and natural products are suitable sources to expand the traditional relevant medicinal chemistry space.

Customisation of the exome data analysis pipeline using a combinatorial approach.

The advent of next generation sequencing (NGS) technologies have revolutionised the way biologists produce, analyse and interpret data. Although NGS platforms provide a cost-effective way to discover genome-wide variants from a single experiment, variants discovered by NGS need follow up validation due to the high error rates associated with various sequencing chemistries. Recently, whole exome sequencing has been proposed as an affordable option compared to whole genome runs but it still requires follow up validation of all the novel exomic variants. Customarily, a consensus approach is used to overcome the systematic errors inherent to the sequencing technology, alignment and post alignment variant detection algorithms. However, the aforementioned approach warrants the use of multiple sequencing chemistry, multiple alignment tools, multiple variant callers which may not be viable in terms of time and money for individual investigators with limited informatics know-how. Biologists often lack the requisite training to deal with the huge amount of data produced by NGS runs and face difficulty in choosing from the list of freely available analytical tools for NGS data analysis. Hence, there is a need to customise the NGS data analysis pipeline to preferentially retain true variants by minimising the incidence of false positives and make the choice of right analytical tools easier. To this end, we have sampled different freely available tools used at the alignment and post alignment stage suggesting the use of the most suitable combination determined by a simple framework of pre-existing metrics to create significant datasets.

Chemoinformatic analysis of combinatorial libraries, drugs, natural products, and molecular libraries small molecule repository.

A multiple criteria approach is presented, that is used to perform a comparative analysis of four recently developed combinatorial libraries to drugs, Molecular Libraries Small Molecule Repository (MLSMR) and natural products. The compound databases were assessed in terms of physicochemical properties, scaffolds, and fingerprints. The approach enables the analysis of property space coverage, degree of overlap between collections, scaffold and structural diversity, and overall structural novelty. The degree of overlap between combinatorial libraries and drugs was assessed using the R-NN curve methodology, which measures the density of chemical space around a query molecule embedded in the chemical space of a target collection. The combinatorial libraries studied in this work exhibit scaffolds that were not observed in the drug, MLSMR, and natural products databases. The fingerprint-based comparisons indicate that these combinatorial libraries are structurally different than current drugs. The R-NN curve methodology revealed that a proportion of molecules in the combinatorial libraries is located within the property space of the drugs. However, the R-NN analysis also showed that there are a significant number of molecules in several combinatorial libraries that are located in sparse regions of the drug space.

Systematic detection of statistically overrepresented DNA motif association rules.

DNA motifs, or cis-elements, are short nucleotide sequence patterns recognized by various transcription factors (TFs). In promoters, these TFs bind in a complex combinatorial manner in order to regulate the expression of a downstream gene. The combinatorial space is frequently large and difficult to manage since vertebrates have thousands of transcription factors and more than 20,000 genes. We introduce a computer program called CAYCE (Combinatorial AnalYsis of Cis-Elements) that systematically detects statistically overrepresented DNA motif association rules independent of Microarray information. CAYCE is an adaptation of the apriori algorithm traditionally used for association rule mining, but offers three significant advancements. (1) It analyzes multiple occurrences of an item, corresponding to multiple TF binding sites, (2) It compares results with a biologically relevant background, and (3), it provides p-values for straightforward statistical interpretation. CAYCE can be easily applied to any item-set data where the investigator is also interested in multiple occurrences of a single item, and/or overrepresentation of association rules compared with a background. Applying CAYCE to human promoters in 1% of the human genome, we discover that motif clusters containing five repetitions of SP1 are the most statistically significant.

Virtual hydrocarbon and combinatorial databases for use with CAVEAT.

Three new virtual databases have been developed for use with the bond-orientation-based database searching program CAVEAT. These consist of a database of trisubstituted monocyclic hydrocarbons having ethyl, vinyl, and phenyl substituents; a database of unsubstituted bicyclic hydrocarbons; and a database of core structures from established combinatorial synthetic methods having hydrogen, ethyl, vinyl, and phenyl substituents at the readily varied positions. Each collection of molecules was subjected to a batch conformational search, minimization, and conversion to a vector database for use with CAVEAT.

Extremal problems for topological indices in combinatorial chemistry.

Topological indices of molecular graphs are related to several physicochemical characteristics; recently, the inverse problem for some of these indices has been studied, and it has some applications in the design of combinatorial libraries for drug discovery. It is thus very natural to study also extremal problems for these indices, i.e., finding graphs having minimal or maximal index. In this paper, these questions will be discussed for three different indices, namely the sigma-index, the c-index and the Z-index, with emphasis on the sigma-index.

Scaffold hopping and optimization towards libraries of glycogen synthase kinase-3 inhibitors.

Using a virtual screening strategy based on a methodology derived from the CATS molecular descriptor, a novel compound class with inhibitory activity against the GSK-3 enzyme was identified through scaffold hopping. These compounds were readily synthesized, either by solid-phase or solution-phase chemistry. Compounds with inhibitory activity below 1 microM were identified.

Selecting the right compounds for screening: does Lipinski's Rule of 5 for pharmaceuticals apply to agrochemicals?

Large numbers of compounds are now available through combinatorial chemistry and from compound vendors to screen for lead-level agrochemical activity. The likelihood that compounds with whole-organism activity will be discovered can be increased if compounds with physicochemical parameters consistent with transport to the target site are selected for screening. Certain ranges of simple parameters (molecular mass, log P, hydrogen-bond donors and acceptors, rotatable bonds) have been correlated with oral bioavailability of drugs. The distribution of these parameters for commercial insecticides and post-emergence herbicides was examined and ranges consistent with whole-organism activity are proposed for the two classes of agrochemical. The most significant difference identified between drugs and these two classes of agrochemicals was the lower numbers of hydrogen-bond donors allowed in the latter cases. The frequency with which certain functional groups occur in drugs and agrochemicals was also compared.

A combinatorial partitioning method to identify multilocus genotypic partitions that predict quantitative trait variation.

Recent advances in genome research have accelerated the process of locating candidate genes and the variable sites within them and have simplified the task of genotype measurement. The development of statistical and computational strategies to utilize information on hundreds -- soon thousands -- of variable loci to investigate the relationships between genome variation and phenotypic variation has not kept pace, particularly for quantitative traits that do not follow simple Mendelian patterns of inheritance. We present here the combinatorial partitioning method (CPM) that examines multiple genes, each containing multiple variable loci, to identify partitions of multilocus genotypes that predict interindividual variation in quantitative trait levels. We illustrate this method with an application to plasma triglyceride levels collected on 188 males, ages 20--60 yr, ascertained without regard to health status, from Rochester, Minnesota. Genotype information included measurements at 18 diallelic loci in six coronary heart disease--candidate susceptibility gene regions: APOA1--C3--A4, APOB, APOE, LDLR, LPL, and PON1. To illustrate the CPM, we evaluated all possible partitions of two-locus genotypes into two to nine partitions (approximately 10(6) evaluations). We found that many combinations of loci are involved in sets of genotypic partitions that predict triglyceride variability and that the most predictive sets show nonadditivity. These results suggest that traditional methods of building multilocus models that rely on statistically significant marginal, single-locus effects, may fail to identify combinations of loci that best predict trait variability. The CPM offers a strategy for exploring the high-dimensional genotype state space so as to predict the quantitative trait variation in the population at large that does not require the conditioning of the analysis on a prespecified genetic model.

Prediction of drug transport processes using simple parameters and PLS statistics. The use of ACD/logP and ACD/ChemSketch descriptors.

A method of modelling and predicting biopharmaceutical properties using simple theoretically computed molecular descriptors and multivariate statistics has been investigated for several data sets related to solubility, IAM chromatography, permeability across Caco-2 cell monolayers, human intestinal perfusion, brain-blood partitioning, and P-glycoprotein ATPase activity. The molecular descriptors (e.g. molar refractivity, molar volume, index of refraction, surface tension and density) and logP were computed with ACD/ChemSketch and ACD/logP, respectively. Good statistical models were derived that permit simple computational prediction of biopharmaceutical properties. All final models derived had R(2) values ranging from 0.73 to 0.95 and Q(2) values ranging from 0.69 to 0.86. The RMSEP values for the external test sets ranged from 0.24 to 0.85 (log scale).

Oriented substituent pharmacophore PRopErtY space (OSPPREYS): a substituent-based calculation that describes combinatorial library products better than the corresponding product-based calculation.

Initial combinatorial library designs were based on 2D substituent properties. Subsequently, two important extensions were introduced to improve the approach: use of pharmacophores to introduce 3D information, and performing calculations on the enumerated library products rather than just on the substituents. Unfortunately, practical compromises due to the large number of possible products, the large number of conformations per product, and the explicit dependence on the scaffold limit the application of these extensions in five important ways: (1) to small virtual libraries, (2) to only 3- or 4-point pharmacophores, (3) to inadequate conformational sampling, (4) to simplistic diversity measures, and (5) to requiring a complete new calculation for every new library. The 3D oriented substituent pharmacophores have been developed to overcome these limitations. These add two additional points and corresponding distances to each substituent pharmacophore. This adds little additional computation beyond a normal 3D pharmacophore calculation on the substituents, but recaptures most of the orienting information lost in breaking up the enumerated products into fragments. Two main approximations are still implicitly required: the combinatorial conformer assumption and the template alignment assumption. In turn, however, they are designed to account not just for the 3- and 4-point pharmacophores, but for pharmacophores with up to 9 points in enumerated products with three sites of diversity. Perhaps more importantly, pharmacophore calculations are shown to be very sensitive to conformational sampling. The small number of substituents, plus the small number of rotatable bonds per substituent, permits very thorough conformational sampling. For a rigid scaffold with three diversity sites of 1,000 candidate substituents each, the number of molecules to analyze is reduced by a factor of 10(6), and the number of conformations per molecule is reduced by another 10(4). In addition, the modest number of pairwise substituent similarities permits the creation of a Euclidean property space by MDS. This allows for sophisticated experimental design methods that require coordinates, rather than just the counting of the number of set bits in a library union fingerprint. Finally, oriented substituent calculations are scaffold independent and transferable. They can be stored in a database and need not be repeated for every new library. Thus, there are some approximations in the correspondence between oriented substituent pharmacophore similarities and enumerated product pharmacophore similarities. However, these errors are minor compared to the five advantages that the new method enables: large virtual library sizes, thorough conformational sampling, accounting for 1- to 9-point pharmacophores, creation of a Euclidean property space, and a reusable database of precomputed substituent values.