Natural products as an inspiration in the diversity-oriented synthesis of bioactive compound libraries

The purpose of diversity-oriented synthesis is to drive the discovery of small molecules with previously unknown biological functions. Natural products necessarily populate biologically relevant chemical space, since they bind both their biosynthetic enzymes and their target macromolecules. Natural product families are, therefore, libraries of pre-validated, functionally diverse structures in which individual compounds selectively modulate unrelated macromolecular targets. This review describes examples of diversity-oriented syntheses which have, to some extent, been inspired by the structures of natural products. Particular emphasis is placed on innovations that allow the synthesis of compound libraries that, like natural products, are skeletally diverse. Mimicking the broad structural features of natural products may allow the discovery of compounds that modulate the functions of macromolecules for which ligands are not known. The ability of innovations in diversity-oriented synthesis to deliver such compounds is critically assessed.     

On the Inhibitability of Natural Products Isolated from Tetradium ruticarpum towards Tyrosine Phosphatase 1B (PTP1B) and α-Glucosidase (3W37): An In Vitro and In Silico Study

Folk experiences suggest natural products in Tetradium ruticarpum can be effective inhibitors towards diabetes-related enzymes. The compounds were experimentally isolated, structurally elucidated, and tested in vitro for their inhibition effects on tyrosine phosphatase 1B (PTP1B) and α-glucosidase (3W37). Density functional theory and molecular docking techniques were utilized as computational methods to predict the stability of the ligands and simulate interaction between the studied inhibitory agents and the targeted proteins. Structural elucidation identifies two natural products: 2-heptyl-1-methylquinolin-4-one (1) and 3-[4-(4-methylhydroxy-2-butenyloxy)-phenyl]-2-propenol (2). In vitro study shows that the compounds (1 and 2) possess high potentiality for the inhibition of PTP1B (IC₅₀ values of 24.3 ± 0.8, and 47.7 ± 1.1 μM) and α-glucosidase (IC₅₀ values of 92.1 ± 0.8, and 167.4 ± 0.4 μM). DS values and the number of interactions obtained from docking simulation highly correlate with the experimental results yielded. Furthermore, in-depth analyses of the structure–activity relationship suggest significant contributions of amino acids Arg254 and Arg676 to the conformational distortion of PTP1B and 3W37 structures overall, thus leading to the deterioration of their enzymatic activity observed in assay-based experiments. This study encourages further investigations either to develop appropriate alternatives for diabetes treatment or to verify the role of amino acids Arg254 and Arg676.     

Quality, not quantity: the role of natural products and chemical proteomics in modern drug discovery

Chemical genetics and reverse chemical genetics parallel classical genetics but target genes at the protein level and have proven useful in recent years for screening combinatorial libraries for compounds of biological interest. However, the performance of combinatorial chemistry in filling pharmaceutical pipelines has been lower than anticipated and the tide may be turning back to Nature in the search for new drug candidates. Even though diversity oriented synthesis is now producing molecules that are natural product-like in terms of size and complexity, these molecules have not evolved to interact with biomolecules. Natural products, on the other hand, have evolved to interact with biomolecules, which is why so many can be found in pharmacopoeias. However, the cellular targets and modes of action of these fascinating compounds are seldom known, hindering the drug development process. This review focuses on the emergence of chemical proteomics and reverse chemical proteomics as tools for the discovery of cellular receptors for natural products, thereby generating protein/ligand pairs that will prove useful in identifying new drug targets and new biologically active small molecule scaffolds. Such a system-wide approach to identifying new drugable targets and their small molecule ligands will help unblock the pharmaceutical product pipelines by speeding the process of target and lead identification.     

Chemical Constituents of Polyalthia nemoralis

Three new natural products, the taraxastane‐type triterpenoid 1 , the azafluorene‐based constituent 2‐hydroxyonychine ( 2 ), and the diterpenoid nemoralisin ( 3 ) were isolated from the EtOH extract of Polyalthia nemoralis, along with five known compounds. The structures of the new compounds were established by in‐depth spectroscopic and mass‐spectrometric analyses, as well as by chemical transformation.     

Natural Products as Probes of Cellular Function: Studies of Immunophilins

One of the great mysteries of cell biology remains the mechanism of information transfer, or signaling, through the cytoplasm of the cell. Natural products that inhibit this process offer a unique window into fundamental aspects of cytoplasmic signal transduction, the means by which extracellular molecules influence intracellular events. Thus, natural products chemistry, including organic synthesis, conformational analysis, and methods of structure elucidation, is a powerful tool in the study of cell function. This article traces our understanding of a group of natural products from the finding that they inhibit cytoplasmic signaling to their current recognition as mediators of the interaction between widely distributed protein targets. The emphasis of the discussion is primarily structural. The interactions between the natural-product ligands and their protein receptors are analyzed at a molecular level in order to shed light on the molecular mechanisms of the biological functions of these compounds. In the process we hope to illustrate the power of chemical analysis as applied to biological systems. Through chemistry we can understand the molecular basis of biological phenomena.     

Steroids from the underground parts of Trillium kamtschaticum

Two 18-norspirostanol glycosides and an 18-norspirostanol, which were new compounds as natural products, have been isolated from the underground parts of Trillium kamtschaticum PALL. along with eight known steroidal glycosides. Their chemical structures were determined on the basis of spectroscopic data.     

Systematic analysis of enzyme-catalyzed reaction patterns and prediction of microbial biodegradation pathways

The roles of chemical compounds in biological systems are now systematically analyzed by high-throughput experimental technologies. To automate the processing and interpretation of large-scale data it is necessary to develop bioinformatics methods to extract information from the chemical structures of these small molecules by considering the interactions and reactions involving proteins and other biological macromolecules. Here we focus on metabolic compounds and present a knowledge-based approach for understanding reactivity and metabolic fate in enzyme-catalyzed reactions in a given organism or group. We first constructed the KEGG RPAIR database containing chemical structure alignments and structure transformation patterns, called RDM patterns, for 7091 reactant pairs (substrate-product pairs) in 5734 known enzyme-catalyzed reactions. A total of 2205 RDM patterns were then categorized based on the KEGG PATHWAY database. The majority of RDM patterns were uniquely or preferentially found in specific classes of pathways, although some RDM patterns, such as those involving phosphorylation, were ubiquitous. The xenobiotics biodegradation pathways contained the most distinct RDM patterns, and we developed a scheme for predicting bacterial biodegradation pathways given chemical structures of, for example, environmental compounds.     

Voronoi binding site models

A frequently occurring problem in drug design and enzymology is that the binding constants for several compounds to the same site are known, but the geometry and energetic interactions of the site are not. This paper presents in detail a novel approach to the problem which accurately but compactly represents the allowed conformation space of each ligand, accurately depicts their three-dimensional structures, and realistically allows each ligand to adopt the conformation and positioning in the site which is most favorable energetically. The investigator supplies only the ligand structures and observed binding free energies, along with a proposed site geometry. With no further assumptions about how the ligands bind and what parts of the ligands are important in determining the binding, the algorithm fits the observed binding energies without leaving outliers, predicts exactly how each of the given ligands binds in the site, and predicts the strength and mode of binding of new compounds, regardless of chemical similarity to the original set of ligands. The method is illustrated by devising a simple site that accounts for the binding of five polychlorinated biphenyls to thyroxine binding prealbumin. This model then predicts the binding energies correctly for an additional six biphenyls, and fails on one compound.     

New Scabimycins A-C Isolated from Streptomyces acidiscabies (Lu19992)

Peptide natural products displaying a wide range of biological activities have become important drug candidates over the years. Microorganisms have been a powerful source of such bioactive peptides, and Streptomyces have yielded many novel natural products thus far. In an effort to uncover such new, meaningful compounds, the metabolome of Streptomyces acidiscabies was analyzed thoroughly. Three new compounds, scabimycins A–C (1–3), were discovered, and their chemical structures were elucidated by NMR spectroscopy. The relative and absolute configurations were determined using ROESY NMR experiments and advanced Marfey’s method.     

Stereochemical determination of tetrahydropyran-substituted xanthones from fungus Chaetomium murorum

Chaetoxanthone D (1), a new tetrahydropyran-substituted xanthone originated from polyketide pathway, together with the four known natural products chaetoxanthone C (2), alternariol methyl ether (3), alternariol (4) and 2,5-dimethyl-7-hydroxychromone (5) was isolated from a strain of Chaetomium murorum. The structures of these compounds were elucidated based on extensive spectroscopic analyses. The absolute configurations of 1 and 2 were determined by using quantum chemical electronic circular dichroism (ECD) calculations.     

Structure-based virtual screening of natural products as potential stearoyl-coenzyme a desaturase 1 (SCD1) inhibitors

Stearyl coenzyme A desaturase enzyme 1 (SCD1) is a key enzyme that catalyzes the conversion of saturated fatty acids (SFA) into monounsaturated fatty acids (MUFA) and plays a vital role in lipid metabolism of tumor cells. SCD1 is overexpressed in a variety of malignant tumors, and its related inhibitors showed significant anti-tumor activity in vitro and in vivo experiments, which is a new target for tumor therapy. The focus of this study is to identify novel SCD1 inhibitors from natural products through computer simulations. First, 176,602 compounds from natural product databases were virtually screened. By molecular dynamics (MD) simulations, the ligand-protein interactions of 5 compounds with high docking manifestation were analyzed accurately. Then, MM-GBSA and MM-PBMA methods were used to verify the results. Finally, ADMET prediction was performed for the 5 compounds. As a result, two natural products with potential inhibition towards SCD1 were identified, which had the excellent docking manifestation, binding mode within SCD1 pocket and stability during molecular dynamics simulation. This study provides a meaningful model for the development and optimization of new inhibitors and anti-tumor drugs targeting SCD1.     

Analysis of HIV wild-type and mutant structures via in silico docking against diverse ligand libraries

The FightAIDS@Home distributed computing project uses AutoDock for an initial virtual screen of HIV protease structures against a broad range of 1771 ligands including both known protease inhibitors and a diverse library of other ligands. The volume of results allows novel large-scale analyses of binding energy "profiles" for HIV structures. Beyond identifying potential lead compounds, these characterizations provide methods for choosing representative wild-type and mutant protein structures from the larger set. From the binding energy profiles of the PDB structures, a principal component analysis based analysis identifies seven "spanning" proteases. A complementary analysis finds that the wild-type protease structure 2BPZ best captures the central tendency of the protease set. Using a comparison of known protease inhibitors against the diverse ligand set yields an AutoDock binding energy "significance" threshold of -7.0 kcal/mol between significant, strongly binding ligands and other weak/nonspecific binding energies. This threshold captures nearly 98% of known inhibitor interactions while rejecting more than 95% of suspected noninhibitor interactions. These methods should be of general use in virtual screening projects and will be used to improve further FightAIDS@Home experiments.     

An efficient in silico screening method based on the protein-compound affinity matrix and its application to the design of a focused library for cytochrome P450 (CYP) ligands

A new method has been developed to design a focused library based on available active compounds using protein-compound docking simulations. This method was applied to the design of a focused library for cytochrome P450 (CYP) ligands, not only to distinguish CYP ligands from other compounds but also to identify the putative ligands for a particular CYP. Principal component analysis (PCA) was applied to the protein-compound affinity matrix, which was obtained by thorough docking calculations between a large set of protein pockets and chemical compounds. Each compound was depicted as a point in the PCA space. Compounds that were close to the known active compounds were selected as candidate hit compounds. A machine-learning technique optimized the docking scores of the protein-compound affinity matrix to maximize the database enrichment of the known active compounds, providing an optimized focused library.     

Stalis: A Computational Method for Template-Based Ab Initio Ligand Design

Proteins interact with small molecules through specific molecular recognition, which is central to essential biological functions in living systems. Therefore, understanding such interactions is crucial for basic sciences and drug discovery. Here, we present S tructure t emplate-based a b initio li gand design s olution (Stalis), a knowledge-based approach that uses structure templates from the Protein Data Bank libraries of whole ligands and their fragments and generates a set of molecules (virtual ligands) whose structures represent the pocket shape and chemical features of a given target binding site. Our benchmark performance evaluation shows that ligand structure-based virtual screening using virtual ligands from Stalis outperforms a receptor structure-based virtual screening using AutoDock Vina, demonstrating reliable overall screening performance applicable to computational high-throughput screening. However, virtual ligands from Stalis are worse in recognizing active compounds at the small fraction of a rank-ordered list of screened library compounds than crystal ligands, due to the low resolution of the virtual ligand structures. In conclusion, Stalis can facilitate drug discovery research by designing virtual ligands that can be used for fast ligand structure-based virtual screening. Moreover, Stalis provides actual three-dimensional ligand structures that likely bind to a target protein, enabling to gain structural insight into potential ligands. Stalis can be an efficient computational platform for high-throughput ligand design for fundamental biological study and drug discovery research at the proteomic level. © 2019 Wiley Periodicals, Inc.     

In silico fragment-based drug design using a PASS approach

Fragment-based drug design integrates different methods to create novel ligands using fragment libraries focused on particular biological activities. Experimental approaches to the preparation of fragment libraries have some drawbacks caused by the need for target crystallization (X-ray and nuclear magnetic resonance) and careful immobilization (surface plasmon resonance). Molecular modelling (docking) requires accurate data on protein-ligand interactions, which are difficult to obtain for some proteins. The main drawbacks of QSAR application are associated with the need to collect large homogeneous datasets of chemical structures with experimentally determined self-consistent quantitative values (potency). We propose a ligand-based approach to the selection of fragments with positive contribution to biological activity, developed on the basis of the PASS algorithm. The robustness of the PASS algorithm for heterogeneous datasets has been shown earlier. PASS estimates qualitative (yes/no) prediction of biological activity spectra for over 4000 biological activities and, therefore, provides the basis for the preparation of a fragment library corresponding to multiple criteria. The algorithm for fragment selection has been validated using the fractions of intermolecular interactions calculated for known inhibitors of nine enzymes extracted from the Protein Data Bank database. The statistical significance of differences between fractions of intermolecular interactions corresponds, for several enzymes, to the estimated positive and negative contribution of fragments in enzyme inhibition.     

SARS-CoV protease inhibitors design using virtual screening method from natural products libraries

Two natural products databases, the marine natural products database (MNPD) and the traditional Chinese medicines database (TCMD), were used to find novel structures of potent SARS-CoV protease inhibitors through virtual screening. Before the procedure, the databases were filtered by Lipinski's ROF and Xu's extension rules. The results were analyzed by statistic methods to eliminate the bias in target-based database screening toward higher molecular weight compounds for enhancing the hit rate. Eighteen lead compounds were recommended by the screening procedure. They were useful for experimental scientists in prioritizing drug candidates and studying the interaction mechanism. The binding mechanism was also analyzed between the best screening compound and the SARS protein.     

Cascade reactions leading to the mechanism of action of vinaxanthone and xanthofulvin,natural products that drive nerve repair

The natural products vinaxanthone and xanthofulvin promote regeneration in animal models of spinal cord injury and corneal transplant. However, inhibition of the initially described biological target of these compounds, semaphorin 3A, does not fully account for the recovery demonstrated in vivo following administration of the natural products. Through chemical synthesis substantial quantities of both natural products have been accessed with early reaction development paving the way for synthesizing both compounds. The success of a model system, first disclosed herein, translated to the syntheses of both natural products. Following from this we also report for the first time the discovery of a new target of the natural products, the succinate receptor 1 (SUCNR1). Both natural products function as positive allosteric modulators of SUCNR1. As the first known allosteric modulators of SUCNR1, the compounds represent powerful new tools to understand the pharmacology of SUCNR1 and its control of growth and cellular defense.     

Mimicking/Extracting Structure and Functions of Natural Products: Synthetic Approaches that Address Unexplored Needs in Chemical Biology

Natural products are often attractive and challenging targets for synthetic chemists, and many have interesting biological activities. However, synthetic chemists need to be more than simply suppliers of compounds to biologists. Therefore, we have been seeking ways to actively apply organic synthetic methods to chemical biology studies of natural products and their activities. In this personal review, I would like to introduce our work on the development of new biologically active compounds inspired by, or extracted from, the structures of natural products, focusing on enhancement of functional activity and specificity and overcoming various drawbacks of the parent natural products.     

同位素标记及未标记的1-脱氧-D-木酮糖-5-磷酸和2-甲基-D-赤藓糖醇-4-磷酸的合成方法

萜类化合物构成了最大的一个天然产物家族,结构复杂多变,且有许多重要的生理活性.2-甲基-D-赤藓糖醇4-磷酸(MEP)途径是近年来发现并建立的一条萜类化合物的生物合成途径,其中所涉及到的酶均可作为靶标来进行新抗菌素的筛选.综述了以化学合成及酶催化合成方法制备MEP途径中关键中间体1-脱氧-D-木酮糖5-磷酸和2-甲基-D-赤藓糖醇4-磷酸的进展,并着重介绍了同位素标记的这两个化合物的制备方法.