Recent Changes in the Scaffold Diversity of Organic Chemistry As Seen in the CAS Registry

Discovery of Trypanosoma brucei inhibitors enabled by a unified synthesis of diverse sulfonyl fluorides

Sets of electrophilic probes are generally prepared using a narrow toolkit of robust reactions, which tends to limit both their structural and functional diversity. A unified synthesis of skeletally-diverse sulfonyl fluorides was developed that relied upon photoredox-catalysed dehydrogenative couplings between hetaryl sulfonyl fluorides and hydrogen donor building blocks. A set of 32 diverse probes was prepared, and then screened against Trypanosoma brucei. Four of the probes were found to have sub-micromolar anti-trypanosomal activity. A chemical proteomic approach, harnessing an alkynylated analogue and broad-spectrum fluorophosphonate tools, provided insights into the observed anti-trypanosomal activity, which likely stems from covalent modification of multiple protein targets. It is envisaged that the unified diversity-oriented approach may enable the discovery of electrophilic probes that have value in the elucidation of biological and biomedical mechanisms.

Spaces of mathematical chemistry

In an effort to expand the domain of mathematical chemistry and inspire research beyond the realms of graph theory and quantum chemistry, we explore five mathematical chemistry spaces and their interconnectedness. These spaces comprise the chemical space, which encompasses substances and reactions; the space of reaction conditions, spanning the physical and chemical aspects involved in chemical reactions; the space of reaction grammars, which encapsulates the rules for creating and breaking chemical bonds; the space of substance properties, covering all documented measurements regarding substances; and the space of substance representations, composed of the various ontologies for characterising substances.

Food Chemicals and Epigenetic Targets: An Epi Food Chemical Database

There is increasing awareness of epigenetics's importance in understanding disease etiologies and developing novel therapeutics. An increasing number of publications in the past few years reflect the renewed interest in epigenetic processes and their relationship with food chemicals. However, there needs to be a recent study that accounts for the most recent advances in the area by associating the chemical structures of food and natural product components with their biological activity. Here, we analyze the status of food chemicals and their intersection with natural products in epigenetic research. Using chemoinformatics tools, we compared quantitatively the chemical contents, structural diversity, and coverage in the chemical space of food chemicals with reported epigenetic activity. As part of this work, we built and curated a compound database of food and natural product chemicals annotated with structural information, an epigenetic target activity profile, and the main source of the food chemical or natural product, among other relevant features. The compounds are cross-linked with identifiers from other major public databases such as FooDB and the collection of open natural products, COCONUT. The compound database, the "Epi Food Chemical Database", is accessible in HTML and CSV formats at https://github.com/DIFACQUIM/Epi_food_Chemical_Database.

IMPPAT 2.0: An Enhanced and Expanded Phytochemical Atlas of Indian Medicinal Plants

Compilation, curation, digitization, and exploration of the phytochemical space of Indian medicinal plants can expedite ongoing efforts toward natural product and traditional knowledge based drug discovery. To this end, we present IMPPAT 2.0, an enhanced and expanded database compiling manually curated information on 4010 Indian medicinal plants, 17,967 phytochemicals, and 1095 therapeutic uses. Notably, IMPPAT 2.0 compiles associations at the level of plant parts and provides a FAIR-compliant nonredundant in silico stereo-aware library of 17,967 phytochemicals from Indian medicinal plants. The phytochemical library has been annotated with several useful properties to enable easier exploration of the chemical space. We have also filtered a subset of 1335 drug-like phytochemicals of which majority have no similarity to existing approved drugs. Using cheminformatics, we have characterized the molecular complexity and molecular scaffold based structural diversity of the phytochemical space of Indian medicinal plants and performed a comparative analysis with other chemical libraries. Altogether, IMPPAT 2.0 is a manually curated extensive phytochemical atlas of Indian medicinal plants that is accessible at https://cb.imsc.res.in/imppat/.

Scaffold and Structural Diversity of the Secondary Metabolite Space of Medicinal Fungi

Medicinal fungi, including mushrooms, have well-documented therapeutic uses. In this study, we perform a cheminformatics-based investigation of the scaffold and structural diversity of the secondary metabolite space of medicinal fungi and, moreover, perform a detailed comparison with approved drugs, other natural product libraries, and semi-synthetic libraries. We find that the secondary metabolite space of medicinal fungi has similar or higher scaffold diversity in comparison to other natural product libraries analyzed here. Notably, 94% of the scaffolds in the secondary metabolite space of medicinal fungi are not present in the approved drugs. Further, we find that the secondary metabolites, on the one hand, are structurally far from the approved drugs, while, on the other hand, they are close in terms of molecular properties to the approved drugs. Lastly, chemical space visualization using dimensionality reduction methods showed that the secondary metabolite space has minimal overlap with the approved drug space. In a nutshell, our results underscore that the secondary metabolite space of medicinal fungi is a valuable resource for identifying potential lead molecules for natural product-based drug discovery.

Molecular Framework Analysis of the Generated Database GDB-13s

The generated databases (GDBs) list billions of possible molecules from systematic enumeration following simple rules of chemical stability and synthetic feasibility. To assess the originality of GDB molecules, we compared their Bemis and Murcko molecular frameworks (MFs) with those in public databases. MFs result from molecules by converting all atoms to carbons, all bonds to single bonds, and removing terminal atoms iteratively until none remain. We compared GDB-13s (99,394,177 molecules up to 13 atoms containing simplified functional groups, 22,130 MFs) with ZINC (885,905,524 screening compounds, 1,016,597 MFs), PubChem50 (100,852,694 molecules up to 50 atoms, 1,530,189 MFs), and COCONUT (401,624 natural products, 42,734 MFs). While MFs in public databases mostly contained linker bonds and six-membered rings, GDB-13s MFs had diverse ring sizes and ring systems without linker bonds. Most GDB-13s MFs were exclusive to this database, and many were relatively simple, representing attractive targets for synthetic chemistry aiming at innovative molecules.

Statistics of the Popularity of Chemical Compounds in Relation to the Non-Target Analysis

The idea of popularity/abundance of chemical compounds is widely used in non-target chemical analysis involving environmental studies. To have a clear quantitative basis for this idea, frequency distributions of chemical compounds over indicators of their popularity/abundance are obtained and discussed. Popularity indicators are the number of information sources, the number of chemical vendors, counts of data records, and other variables assessed from two large databases, namely ChemSpider and PubChem. Distributions are approximated by power functions, special cases of Zipf distributions, which are characteristic of the results of human/social activity. Relatively small group of the most popular compounds has been denoted, conventionally accounting for a few percent (several million) of compounds. These compounds are most often explored in scientific research and are practically used. Accordingly, popular compounds have been taken into account as first analyte candidates for identification in non-target analysis.

Pharmacometabonomics: data processing and statistical analysis

Individual variations in drug efficacy, side effects and adverse drug reactions are still challenging that cannot be ignored in drug research and development. The aim of pharmacometabonomics is to better understand the pharmacokinetic properties of drugs and monitor the drug effects on specific metabolic pathways. Here, we systematically reviewed the recent technological advances in pharmacometabonomics for better understanding the pathophysiological mechanisms of diseases as well as the metabolic effects of drugs on bodies. First, the advantages and disadvantages of all mainstream analytical techniques were compared. Second, many data processing strategies including filtering, missing value imputation, quality control-based correction, transformation, normalization together with the methods implemented in each step were discussed. Third, various feature selection and feature extraction algorithms commonly applied in pharmacometabonomics were described. Finally, the databases that facilitate current pharmacometabonomics were collected and discussed. All in all, this review provided guidance for researchers engaged in pharmacometabonomics and metabolomics, and it would promote the wide application of metabolomics in drug research and personalized medicine.

Remote C(sp3)–H functionalization via catalytic cyclometallation: beyond five-membered ring metallacycle intermediates

Despite impressive recent momentum gained in C(sp3)–H activation, achieving high regioselectivity in molecules containing different C–H bonds with similar high energy without abusing tailored substitution remains as one of the biggest challenges.

Structural Approach to Assessing the Innovativeness of New Drugs Finds Accelerating Rate of Innovation

Measuring innovation in the pharmaceutical industry is challenging. Counts of new molecular entities (NMEs) approved by the Food and Drug Administration (FDA) are commonly used, but this measure only gauges quantity not innovativeness. A new indicator of innovation for small molecule and peptide drugs based on structural novelty is proposed and used to analyze recent trends in pharmaceutical innovation. We show pharmaceutical innovation has significantly increased over the last several decades despite recent concerns over an innovation crisis and find Pioneers (a NME whose shape and scaffold were not used in any previously FDA-approved drugs) are significantly more likely to be the source of promising new therapies. Analysis of the underlying source of structural innovation indicates that scaffolds first reported in the CAS REGISTRY five or less years prior to their Investigational New Drug application (IND) or on scaffolds populated with 50 or less other compounds at the time of IND tend to be the main source of Pioneers. Our analysis also shows a widening structural innovation gap between large pharmaceutical companies (Big Pharma) and the rest of the ecosystem even though the number of Big Pharma originated Pioneers has increased.

Evaluation of 3-Dimensionality in Approved and Experimental Drug Space

The 3-dimensional (3D) structure of therapeutics and other bioactive molecules is an important factor in determining the strength and selectivity of their protein-ligand interactions. Previous efforts have considered the strain introduced and tolerated through conformational changes induced upon protein binding. Herein, we present an analysis of 3-dimentionality for energy-minimized structures from the DrugBank and ligands bound to proteins identified in the Protein Data Bank (PDB). This analysis reveals that the majority of molecules found in both the DrugBank and the PDB tend toward linearity and planarity, with few molecules having highly 3D conformations. Decidedly 3D geometries have been historically difficult to achieve, likely due to the synthetic challenge of making 3D organic molecules, and other considerations, such as adherence to the 'rule-of-five'. This has resulted in the dominance of planar and/or linear topologies of the molecules described here. Strategies to address the generally flat nature of these data sets are explored, including the use of 3D organic fragments and inorganic scaffolds as a means of accessing privileged 3D space. This work highlights the potential utility of libraries with greater 3D topological diversity so that the importance of molecular shape to biological behavior can be more fully understood in drug discovery campaigns.

Opening up connectivity between documents, structures and bioactivity

Bioscientists reading papers or patents strive to discern the key relationships reported within a document "D" where a bioactivity "A" with a quantitative result "R" (e.g., an IC50) is reported for chemical structure "C" that modulates (e.g., inhibits) a protein target "P". A useful shorthand for this connectivity thus becomes DARCP. The problem at the core of this article is that the community has spent millions effectively burying these relationships in PDFs over many decades but must now spend millions more trying to get them back out. The key imperative for this is to increase the flow into structured open databases. The positive impacts will include expanded data mining opportunities for drug discovery and chemical biology. Over the last decade commercial sources have manually extracted DARCP from ≈300,000 documents encompassing ≈7 million compounds interacting with ≈10,000 targets. Over a similar time, the Guide to Pharmacology, BindingDB and ChEMBL have carried out analogues DARCP extractions. Although their expert-curated numbers are lower (i.e., ≈2 million compounds against ≈3700 human proteins), these open sources have the great advantage of being merged within PubChem. Parallel efforts have focused on the extraction of document-to-compound (D-C-only) connectivity. In the absence of molecular mechanism of action (mmoa) annotation, this is of less value but can be automatically extracted. This has been significantly accomplished for patents, (e.g., by IBM, SureChEMBL and WIPO) for over 30 million compounds in PubChem. These have recently been joined by 1.4 million D-C submissions from three major chemistry publishers. In addition, both the European and US PubMed Central portals now add chemistry look-ups from abstracts and full-text papers. However, the fully automated extraction of DARCLP has not yet been achieved. This stands in contrast to the ability of biocurators to discern these relationships in minutes. Unfortunately, no journals have yet instigated a flow of author-specified DARCP directly into open databases. Progress may come from trends such as open science, open access (OA), findable, accessible, interoperable and reusable (FAIR), resource description framework (RDF) and WikiData. However, we will need to await the technical applicability in respect to DARCP capture to see if this opens up connectivity.