Natural compounds are evolutionary selected and prevalidated by Nature, displaying a unique chemical diversity and a corresponding diversity of biological activities. These features make them highly interesting for studies of chemical biology, and in the pharmaceutical industry for development of new leads. Of utmost importance, for the discovery of new biologically active compounds, is the identification and charting of the corresponding biologically relevant chemical space. The primary key to this is the coverage of the natural products' chemical space. Here we introduce ChemGPS-NP, a new tool tuned for handling the chemical diversity encountered in natural products research, in contrast to previous tools focused on the much more restricted drug-like chemical space. The aim is to provide a framework for making compound classification and comparison more efficient and stringent, to identify volumes of chemical space related to particular biological activities, and to track changes in chemical properties due to, for example, evolutionary traits and modifications in biosynthesis. Physical-chemical properties not directly discernible from structural data can be discovered, making selection more efficient and increasing the probability of hit generation when screening natural compounds and analogues.
"This step is essential because of the well-recognized disparity between commercial fragment libraries and natural products—commercial fragments have a structural makeup that is largely biased toward readily available small, flat, heterocyclic molecules, whereas natural products have a prevalence of stereogenic centers and even include reactive functional groups.[3b, 10] In the first step of the method, a set of known ligands of both the protein of interest (where available) as well as other related proteins is compiled. Subsequently, a fragment library is assembled that samples the substructural chemical space present in the ligands and is hence expected to increase fragment hit rates. "
[Show abstract][Hide abstract] ABSTRACT: We present a novel fragment-based approach that tackles some of the challenges for chemical biology of predicting protein function. The general approach, which we have termed biofragments, comprises two key stages. First, a biologically relevant fragment library (biofragment library) can be designed and constructed from known sets of substrate-like ligands for a protein class of interest. Second, the library can be screened for binding to a novel putative ligand-binding protein from the same or similar class, and the characterization of hits provides insight into the basis of ligand recognition, selectivity, and function at the substrate level. As a proof-of-concept, we applied the biofragments approach to the functionally uncharacterized Mycobacterium tuberculosis (Mtb) cytochrome P450 isoform, CYP126. This led to the development of a tailored CYP biofragment library with notable 3D characteristics and a significantly higher screening hit rate (14 %) than standard drug-like fragment libraries screened previously against Mtb CYP121 and 125 (4 % and 1 %, respectively). Biofragment hits were identified that make both substrate-like type-I and inhibitor-like type-II interactions with CYP126. A chemical-fingerprint-based substrate model was built from the hits and used to search a virtual TB metabolome, which led to the discovery that CYP126 has a strong preference for the recognition of aromatics and substrate-like type-I binding of chlorophenol moieties within the active site near the heme. Future catalytic analyses will be focused on assessing CYP126 for potential substrate oxidative dehalogenation.
"Is it not time to, at least for a while, study those already well-defined chemical structures? Furthermore, the selection of organisms for collection and further studies could in much higher degree be based on prediction models, for example, combining phylogeny with bioinformatic data (Larsson et al., 2007). Also important for a sustainable use of natural products is the increased knowledge emerging about the real producer of specific secondary metabolites found in plants and animals. "
"Natural products have been hitherto a very successful source of new drugs, with slightly more than a third of “small compounds” launched as “new chemical entities” for the past 30 years belonging to this group . At the same time it has been shown that natural products occupy a different and larger chemical space than synthetic drugs [13, 14, 15], and that they have a higher probability to pass through the pharmaceutical industry drug developmental pipeline . This is today usually discussed within the concept of natural products being prevalidated for activity [14, 15, 17, 18, 19, 20, 21]. "
[Show abstract][Hide abstract] ABSTRACT: The subject of chemosystematics has provided insight to both botanical classification and drug development.
However, degrees of subjectivity in botanical classifications and limited understanding of the evolution of chemical characters
and their biosynthetic pathways has often hampered such studies. In this review an approach of taking phylogenetic
classification into account in evaluating colchicine and related phenethylisoquinoline alkaloids from the family Colchicaceae
will be applied. Following on the trends of utilizing evolutionary reasoning in inferring mechanisms in eg. drug resistance
in cancer and infections, this will exemplify how thinking about evolution can influence selection of plant material
in drug lead discovery, and how knowledge about phylogenetic relationships may be used to evaluate predicted biosynthetic
Current topics in medicinal chemistry 12/2013; 14(2). DOI:10.2174/1568026613666131216110417 · 3.40 Impact Factor
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