Library enhancement through the wisdom of crowds

We present a novel approach for enhancing the diversity of a chemical library rooted on the theory of the wisdom of crowds. Our approach was motivated by a desire to tap into the collective experience of our global medicinal chemistry community and involved four basic steps: (1) Candidate compounds for acquisition were screened using various structural and property filters in order to eliminate clearly nondrug-like matter. (2) The remaining compounds were clustered together with our in-house collection using a novel fingerprint-based clustering algorithm that emphasizes common substructures and works with millions of molecules. (3) Clusters populated exclusively by external compounds were identified as "diversity holes," and representative members of these clusters were presented to our global medicinal chemistry community, who were asked to specify which ones they liked, disliked, or were indifferent to using a simple point-and-click interface. (4) The resulting votes were used to rank the clusters from most to least desirable, and to prioritize which ones should be targeted for acquisition. Analysis of the voting results reveals interesting voter behaviors and distinct preferences for certain molecular property ranges that are fully consistent with lead-like profiles established through systematic analysis of large historical databases.     

The Asymmetric Hetero‐Diels–Alder Reaction in the Syntheses of Biologically Relevant Compounds

The hetero‐Diels–Alder reaction is one of the most powerful transformations in the chemistry toolbox for the synthesis of aza‐ and oxa‐heterocycles embodying multiple stereogenic centers. However, as compared to other cycloadditions, in particular the dipolar cycloadditions and the Diels–Alder reaction, the hetero‐Diels–Alder reaction has been much less explored and exploited in organic synthesis. Nevertheless, this powerful transformation has opened up efficient and creative routes to biologically relevant small molecules and different natural products which contain six‐membered oxygen or nitrogen ring systems. Recent developments in this field, in particular in the establishment of enantioselectively catalyzed hetero‐Diels–Alder cycloadditions steered by a plethora of different catalysts and the application of the resulting small molecules in chemical biology and medicinal chemistry research, are highlighted in this Minireview.     

The Chemistry of the Cyaphide Ion

We review the known chemistry of the cyaphide ion, (C≡P)⁻. This remarkable diatomic anion has been the subject of study since the late nineteenth century, however its isolation and characterization eluded chemists for almost a hundred years. In this mini-review, we explore the pioneering synthetic experiments that first allowed for its isolation, as well as more recent developments demonstrating that cyaphide transfer is viable in well-established salt-metathesis protocols. The physical properties of the cyaphide ion are also explored in depth, allowing us to compare and contrast the chemistry of this ion with that of its lighter congener cyanide (an archetypal strong field ligand and important organic functional group). Recent studies show that the cyaphide ion has the potential to be used as a versatile chemical regent for the synthesis of novel molecules and materials, hinting at many interesting future avenues of investigation.     

Harnessing the complexity of metabolomic data with chemometrics

Because of the ever‐increasing number of signals that can be measured within a single run by modern platforms in analytical chemistry, life sciences datasets become not only gradually larger but also more intricate in their structures. Challenges related to making use of this wealth of data include extracting relevant elements within massive amounts of signals possibly spread across different tables, reducing dimensionality, summarising dynamic information in a comprehensible way and displaying it for interpretation purposes. Metabolomics constitutes a representative example of fast‐moving research fields taking advantage of recent technological advances to provide extensive sample monitoring. Because of the wide chemical diversity of metabolites, several analytical setups are required to provide a broad coverage of complex samples. The integration and visualisation of multiple highly multivariate datasets constitute key issues for effective analysis leading to valuable biological or chemical knowledge. Additionally, high‐order data structures arise from experimental setups involving time‐resolved measurements. These data are intrinsically multiway, and classical statistical tools cannot be applied without altering their organisation with the risk of information loss. Dedicated modelling algorithms, able to cope with the inherent properties of these metabolomic datasets, are therefore mandatory for harnessing their complexity and provide relevant information. In that perspective, chemometrics has a central role to play. Copyright © 2013 John Wiley & Sons, Ltd.     

Conditional Copper‐Catalyzed Azide–Alkyne Cycloaddition by Catalyst Encapsulation

Supramolecular encapsulation is known to alter chemical properties of guest molecules. We have applied this strategy of molecular encapsulation to temporally control the catalytic activity of a stable copper(I)–carbene catalyst. Encapsulation of the copper(I)–carbene catalyst by the supramolecular host cucurbit[7]uril (CB[7]) resulted in the complete inactivation of a copper‐catalyzed alkyne–azide cycloaddition (CuAAC) reaction. The addition of a chemical signal achieved the near instantaneous activation of the catalyst, by releasing the catalyst from the inhibited CB[7] catalyst complex. To broaden the scope of our on‐demand CuAAC reaction, we demonstrated the protein labeling of vinculin with the copper(I)–carbene catalyst, to inhibit its activity by encapsulation with CB[7] and to initiate labeling at any moment by adding a specific signal molecule. Ultimately, this strategy allows for temporal control over copper‐catalyzed click chemistry, on small molecules as well as protein targets.     

Toward designing drug-like libraries: a novel computational approach for prediction of drug feasibility of compounds

Prediction of the degree of drug-like character in small molecules is of great industrial interest. The major barrier, however, is the lack of a definition for drug-like character. We used the concept of the multilevel chemical compatibility (MLCC) between a compound and a drug library as a measure of the drug-like character of a compound. The rationale is that the local chemical environment of each atom or group of atoms in a compound largely contributes to the stability, toxicity, and metabolism in vivo. A systematic comparison of the local environments within a compound and those within the existing drugs provides a basis for determining whether and how much a compound is drug-like. We applied the MLCC calculations to four test sets: top selling drugs, compounds under biological testing prior to the preclinical test, anticancer drugs, and compounds known to have poor drug-like character. The following conclusions were obtained: (1) A convergent number of unique local structure types were found in the analysis of the library of the existing drugs. It suggests that the current drug library contains about 80% of all the viable types; therefore, discovery of a drug with new local structures is only an event of relatively small probability. (2) The method is highly selective in discerning drug-like compounds: most of the top drugs are predicted to be drug-like, about one-quarter of the biological testing compounds are drug-like, and about one-fifth of the anticancer drugs are drug-like. (3) The method also correctly predicted that none of the known problematic compounds are drug-like. (4) The method is fast enough for computational screening of virtual combinatorial chemistry libraries and databases of available compounds.     

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.     

Controlled Chemical and Drug Delivery via the Internal and External Surfaces of Layered Compounds

Abstract

We demonstrate, and review the very small, but growing body of literature regarding a recently discovered application of layered compounds, which involves the ability of layered materials to sequester and later release molecules of chemical and biological significance. The application relies upon intercalation chemistry; a reversible process whereby atoms, molecules, macromolecules, and polymers may be inserted into the interstices of a layered matrix. We demonstrate that layered materials are able to effectively getter water‐soluble atoms and molecules from aqueous dispersions, and further demonstrate that the absorbed molecules can be later released from the interlayer region to perform a desired chemical function. Work in our laboratory involving the application of layered hybrid materials in photographic media is described in detail and we establish two general release mechanisms whereby intercalated functional chemistry can be first sequestrated and later delivered via a chemical switch to perform a desired function. The process has enormous potential as a general method for the controlled, temporal release of materials of chemical and biological significance.     

Mining a chemical database for fragment co-occurrence: discovery of "chemical clichés"

Nowadays millions of different compounds are known, their structures stored in electronic databases. Analysis of these data could yield valuable insights into the laws of chemistry and the habits of chemists. We have therefore explored the public database of the National Cancer Institute (>250,000 compounds) by pattern searching. We split the molecules of this database into fragments to find out which fragments exist, how frequent they are, and whether the occurrence of one fragment in a molecule is related to the occurrence of another, nonoverlapping fragment. It turns out that some fragments and combinations of fragments are so frequent that they can be called "chemical clichés". We believe that the fragment data can give insight into the chemical space explored so far by synthesis. The lists of fragments and their (co-)occurrences can help create novel chemical compounds by (i) systematically listing the most popular and therefore most easily used substituents and ring systems for synthesizing new compounds, (ii) being an easily accessible repository for rarer fragments suitable for lead compound optimization, and (iii) pointing out some of the yet unexplored parts of chemical space.     

Synthetic Approaches to Star‐Shaped Molecules with 1,3,5‐Trisubstituted Aromatic Cores

Herein, we summarize the synthetic approaches that have been developed for the synthesis of star‐shaped molecules. Typically, to design such highly functionalized molecules, simple building blocks are first assembled through trimerization reactions, starting from commercially available starting materials. Then, these building blocks are synthetically manipulated to generate extended star‐shaped molecules. We also discuss the syntheses of star‐shaped molecules that contain 2,4,6‐trisubstituted 1,3,5‐triazine or 1,3,5‐trisubstituted benzene rings as a central core and diverse substituted styrene, phenyl, and fluorene derivatives at their periphery, which endows these molecules with extended conjugation. A variety of metal‐catalyzed reactions, such as Suzuki, Buchwald–Hartwig, Sonogashira, Heck, and Negishi cross‐coupling reactions, as well as metathesis, have been employed to functionalize a range of star‐shaped molecules. The methods described herein will be helpful for designing a wide range of intricate compounds that are highly valuable in the fields of supramolecular chemistry and materials science. Owing to space limitations, we will not cover all of the publications on this topic. Instead, we will focus on examples that were reported by our research group and other relevant recent literature. Apart from the trimerization sequence, this Minireview has been structured based on the key reactions that were used to prepare the star‐shaped molecules and other higher analogues. Finally, some examples that do not fit into this classification are discussed.     

Symmetrizer: Algorithmic determination of point groups in nearly symmetric molecules

Symmetry is an extremely useful and powerful tool in computational chemistry, both for predicting the properties of molecules and for simplifying calculations. Although methods for determining the point groups of perfectly symmetric molecules are well‐known, finding the closest point group for a “nearly” symmetric molecule is far less studied, although it presents many useful applications. For this reason, we introduce Symmetrizer, an algorithm designed to determine a molecule's symmetry elements and closest matching point groups based on a user‐adjustable tolerance, and then to symmetrize that molecule to a given point group geometry. In contrast to conventional methods, Symmetrizer takes a bottom‐up approach to symmetry detection by locating all possible symmetry elements and uses this set to deduce the most probable point groups. We explain this approach in detail, and assess the flexibility, robustness, and efficiency of the algorithm with respect to various input parameters on several test molecules. We also demonstrate an application of Symmetrizer by interfacing it with the WebMO web‐based interface to computational chemistry packages as a showcase of its ease of integration. © 2012 Wiley Periodicals, Inc.     

An evaluation of experimental design in QSAR modelling utilizing the k‐medoid clustering

A reliable selection of a representative subset of chemical compounds has been reported to be crucial for numerous tasks in computational chemistry and chemoinformatics. We investigated the usability of an approach on the basis of the k‐medoid algorithm for this task and in particular for experimental design and the split between training and validation set. We therefore compared the performance of models derived from such a selection to that of models derived using several other approaches, such as space‐filling design and D‐optimal design. We validated the performance on four datasets with different endpoints, representing toxicity, physicochemical properties and others. Compared with the models derived from the compounds selected by the other examined approaches, those derived with the k‐medoid selection show a high reliability for experimental design, as their performance was constantly among the best for all examined datasets. Of all the models derived with all examined approaches, those derived with the k‐medoid approach were the only ones that showed a significantly improved performance compared with a random selection, for all datasets, the whole examined range of selected compounds and for each dimensionality of the search space. Copyright © 2012 John Wiley & Sons, Ltd.     

The Enzymology of Organic Transformations: A Survey of Name Reactions in Biological Systems

Chemical reactions that are named in honor of their true, or at least perceived, discoverers are known as “name reactions”. This Review is a collection of biological representatives of named chemical reactions. Emphasis is placed on reaction types and catalytic mechanisms that showcase both the chemical diversity in natural product biosynthesis as well as the parallels with synthetic organic chemistry. An attempt has been made, whenever possible, to describe the enzymatic mechanisms of catalysis within the context of their synthetic counterparts and to discuss the mechanistic hypotheses for those reactions that are currently active areas of investigation. This Review has been categorized by reaction type, for example condensation, nucleophilic addition, reduction and oxidation, substitution, carboxylation, radical‐mediated, and rearrangements, which are subdivided by name reactions.     

Diversity‐Oriented Approach for Chemical Biology

Synthetic molecules that modulate and probe biological events are critical tools in chemical biology. Utilizing combinatorial and diversity‐oriented synthetic strategies, access to large numbers of small molecules is becoming more and more feasible, and research groups in this field can take advantage of the power of chemical diversity. Since the majority of early studies were focused on the discovery of compounds that perturb protein functions, diversity‐based approaches are often considered as therapeutic lead discovery tactics. However, the diversity‐oriented approach can also be applied to advance distinct aims, such as target protein identification, or the development of imaging probes and sensors. This review provides a personal perspective of the chemical‐diversity‐based approach and how this principle can be adapted to various chemical biology studies.     

A planning strategy for diversity-oriented synthesis

In contrast to target-oriented synthesis (TOS) and medicinal or combinatorial chemistry, which aim to access precise or dense regions of chemistry space, diversity-oriented synthesis (DOS) populates chemical space broadly with small-molecules having diverse structures. The goals of DOS include the development of pathways leading to the efficient (three- to five-step) synthesis of collections of small molecules having skeletal and stereochemical diversity with defined coordinates in chemical space. Ideally, these pathways also yield compounds having the potential to attach appendages site- and stereoselectively to a variety of attachment sites during a post-screening, maturation stage. The diverse skeletons and stereochemistries ensure that the appendages can be positioned in multiple orientations about the surface of the molecules. TOS as well as medicinal and combinatorial chemistries have been advanced by the development of retrosynthetic analysis. Although the distinct goals of DOS do not permit the application of retrosynthetic concepts and thinking, these foundations are being built on, by using parallel logic, to develop a complementary procedure known as forward-synthetic analysis. This analysis facilitates synthetic planning, communication, and teaching in this evolving discipline.     

Congestion game scheduling for virtual drug screening optimization

In virtual drug screening, the chemical diversity of hits is an important factor, along with their predicted activity. Moreover, interim results are of interest for directing the further research, and their diversity is also desirable. In this paper, we consider a problem of obtaining a diverse set of virtual screening hits in a short time. To this end, we propose a mathematical model of task scheduling for virtual drug screening in high-performance computational systems as a congestion game between computational nodes to find the equilibrium solutions for best balancing the number of interim hits with their chemical diversity. The model considers the heterogeneous environment with workload uncertainty, processing time uncertainty, and limited knowledge about the input dataset structure. We perform computational experiments and evaluate the performance of the developed approach considering organic molecules database GDB-9. The used set of molecules is rich enough to demonstrate the feasibility and practicability of proposed solutions. We compare the algorithm with two known heuristics used in practice and observe that game-based scheduling outperforms them by the hit discovery rate and chemical diversity at earlier steps. Based on these results, we use a social utility metric for assessing the efficiency of our equilibrium solutions and show that they reach greatest values.     

The artemisia L. Genus: a review of bioactive essential oils

Numerous members of the Anthemideae tribe are important as cut flowers and ornamental crops, as well as being medicinal and aromatic plants, many of which produce essential oils used in folk and modern medicine and in the cosmetics and pharmaceutical industry. Essential oils generally have a broad spectrum of bioactivity, owing to the presence of several active ingredients that work through various modes of action. Due to their mode of extraction, mostly by distillation from aromatic plants, they contain a variety of volatile molecules such as terpenes, phenol-derived aromatic and aliphatic components. The large genus Artemisia L., from the tribe Anthemideae, comprises important medicinal plants which are currently the subject of phytochemical attention due to their biological and chemical diversity. Artemisia species, widespread throughout the world, are one of the most popular plants in Chinese traditional preparations and are frequently used for the treatment of diseases such as malaria, hepatitis, cancer, inflammation and infections by fungi, bacteria and viruses. Extensive studies of the chemical components of Artemisia have led to the identification of many compounds as well as essentials oils. This review summarizes some of the main reports on the chemistry and anti-infective activities of Artemisia. Li. essential oils from the data in the recent literature (2000-2011).