De-Xin Kong

Distribution patterns of small-molecule ligands in the protein universe and implications for origin of life and drug discovery

BackgroundExtant life depends greatly on the binding of small molecules (such as ligands) with macromolecules (such as proteins), and one ligand can bind multiple proteins. However, little is known about the global patterns of ligand-protein mapping.ResultsBy examining 2,186 well-defined small-molecule ligands and thousands of protein domains derived from a database of druggable binding sites, we show that a few ligands bind tens of protein domains or folds, whereas most ligands bind only one, which indicates that ligand-protein mapping follows a power law. Through assigning the protein-binding orders (early or late) for bio-ligands, we demonstrate that the preferential attachment principle still holds for the power-law relation between ligands and proteins. We also found that polar molecular surface area, H-bond acceptor counts, H-bond donor counts and partition coefficient are potential factors to discriminate ligands from ordinary molecules and to differentiate super ligands (shared by three or more folds) from others.ConclusionThese findings have significant implications for evolution and drug discovery. First, the chronology of ligand-protein binding can be inferred by the power-law feature of ligand-protein mapping. Some nucleotide-containing ligands, such as ATP, ADP, GDP, NAD, FAD, dihydro-nicotinamide-adenine-dinucleotide phosphate (NDP), nicotinamide-adenine-dinucleotide phosphate (NAP), flavin mononucleotide (FMN) and AMP, are found to be the earliest cofactors bound to proteins, agreeing with the current understanding of evolutionary history. Second, the finding that about 30% of ligands are shared by two or more domains will help with drug discovery, such as in finding new functions from old drugs, developing promiscuous drugs and depending more on natural products.

How Many Traditional Chinese Medicine Components Have Been Recognized by Modern Western Medicine? A Chemoinformatic Analysis and Implications for Finding Multicomponent Drugs

Traditional Chinese medicine (TCM), featured in its combinatorial use of herbs (sometimes animals and minerals are also involved), has been developed in China for more than 4 000 years. Although TCM attracts more and more attention from medicinal practice throughout the world and is considered a promising source of new drugs, [1–7] it is still outside mainstream medicine, because of the conceptual differences between TCM therapy and modern medication. However, it should be pointed out that historically Western medicine also depended on natural products (for over 3 000 years) and synthetic modern drugs only began to blossom approximately 100 years ago. [8, 9] In addition, it is estimated that ~ 50 % of currently used modern Western drugs are derived from natural products. [9–12] Considering the fact that the plant distribution patterns in China and Western countries are rather similar, it is reasonable to infer that there exist certain similarities between TCM components and modern Western drugs and some TCM components may have been recognized by modern Western medicine, although by and large both medical systems evolved independently. To verify this speculation, we employed chemoinformatic methods to make a global structural comparison between the two kinds of drugs. Structurally similar agents in TCM and modern Western medicine In the present analysis, traditional Chinese medicine database (TCMD), [13] which records 10 458 components extracted from 4 636 TCMs (including herbs, animals, and minerals) and the comprehensive medicinal chemistry (CMC) database, [14] which contains 8 659 approved modern drugs (of which 7 988 molecules are represented in Mol2 format), were used as data sources of TCM components and modern Western drugs, respectively. The molecular similarity comparison of TCMD and CMC database was performed by using atom environment descriptors (MOLPRINT 2D). [15] As a result, 908 TCMD–CMC agent pairs were found to be structurally similar (with similarity > 85 %) and 327 agents were revealed as common members of both databases, which indicates that a certain part of TCM components have been recognized by modern Western medicine. As the structurally identical agents are of special interest to our study, they are listed in Table S1 and are analyzed in detail (see below).

Exploring the biologically relevant chemical space for drug discovery.

Both recent studies and our calculation suggest that the physicochemical properties of launched drugs changed continuously over the past decades. Besides shifting of commonly used properties, the average biological relevance (BR) and similarity to natural products (NPs) of launched drugs decreased, reflecting the fact that current drug discovery deviated away from NPs. To change the current situation characterized by high investment but low productivity in drug discovery, efforts should be made to improve the BR of the screening library and hunt drugs more effectively in the biologically relevant chemical space. Additionally, a multiple dimensional molecular descriptor, named the biologically relevant spectrum (BRS) was proposed for quantitative structure-activity relationships (QSAR) study or screening library preparation. Prediction models for 43 biological activity categories were developed with BRS and support vector machine (SVM). In most cases, the overall prediction accuracies were around 95% and the Matthews correlation coefficients (MCC) were over 0.8. Thirty-seven out of 48 drug-activity associations were successfully predicted for drugs that launched from 2006 to 2012, which were not included in the training data set. A web-server named BioRel ( http://ibi.hzau.edu.cn/biorel ) was developed to provide services including BR, BRS calculation, activity class, and pharmacokinetic property prediction.

The impact of oxygen on metabolic evolution: A chemoinformatic investigation

The appearance of planetary oxygen likely transformed the chemical and biochemical makeup of life and probably triggered episodes of organismal diversification. Here we use chemoinformatic methods to explore the impact of the rise of oxygen on metabolic evolution. We undertake a comprehensive comparative analysis of structures, chemical properties and chemical reactions of anaerobic and aerobic metabolites. The results indicate that aerobic metabolism has expanded the structural and chemical space of metabolites considerably, including the appearance of 130 novel molecular scaffolds. The molecular functions of these metabolites are mainly associated with derived aspects of cellular life, such as signal transfer, defense against biotic factors, and protection of organisms from oxidation. Moreover, aerobic metabolites are more hydrophobic and rigid than anaerobic compounds, suggesting they are better fit to modulate membrane functions and to serve as transmembrane signaling factors. Since higher organisms depend largely on sophisticated membrane-enabled functions and intercellular signaling systems, the metabolic developments brought about by oxygen benefit the diversity of cellular makeup and the complexity of cellular organization as well. These findings enhance our understanding of the molecular link between oxygen and evolution. They also show the significance of chemoinformatics in addressing basic biological questions.

Do biologically relevant compounds have more chance to be drugs

To prove the innate advantages of endogenous compounds/fragments for drug discovery and development, a novel index termed biological relevance (BR) is proposed. The results clearly indicate its ability to distinguish between synthetic chemicals, bioactive compounds, drug candidates, and launched drugs. Primarily, the average BR of the databases investigated decreases in the order DNP > CMC > ACD-3D > MDDR. Second, for compounds with the same bioactivity, drugs (CMC) possess higher average BR than their candidates (MDDR). These results suggest that compounds with higher BR have more chance to survive the drug development pipeline. Third, the above conclusion is supported by the fact that compounds in the later development phases possess higher BR than those in the earlier phases. Comparisons were made between BR and other indices, including toxicity, druglikeness, and natural productlikeness.

How does oxygen rise drive evolution? Clues from oxygen-dependent biosynthesis of nuclear receptor ligands

It is well known that oxygen rise greatly facilitated biological evolution. However, the underlying mechanisms remain elusive. Recently, Raymond and Segrè revealed that molecular oxygen allows 1000 more metabolic reactions than can occur in anoxic conditions. From the novel metabolites produced in aerobic metabolism, we serendipitously found that some of the metabolites are signaling molecules that target nuclear receptors. Since nuclear signaling systems are indispensable to superior organisms, we speculated that aerobic metabolism may facilitate biological evolution through promoting the establishment of nuclear signaling systems. This hypothesis is validated by the observation that most (97.5%) nuclear receptor ligands are produced by aerobic metabolism, which is further explained in terms of the chemical criteria (appropriate volume and rather high hydrophobicity) of nuclear receptor ligands that aerobic metabolites are more ready than anaerobic counterparts to satisfy these criteria.

Chemoinformatics Approaches for Traditional Chinese Medicine Research and Case Application in Anticancer Drug Discovery

Traditional Chinese Medicine (TCM), which has been used for thousands of years to treat diseases, provides unique theoretical and practical methodologies for disease control. With the increasing accumulation of TCM data, it is imperative to study and analyze these resources with modern technologies and to elucidate the molecular mechanisms of TCM therapy. However, the philosophy, framework and technique of TCM are quite different from those of Western medicine, which causes complications when attempting to design modern drug treatments based on TCM. To meet this challenge, some basic chemoinformatics techniques, including molecular similarity searching, virtual screening and inverse docking, have been utilized in an attempt to gain a deeper understanding of TCM and to accelerate the TCM-based drug discovery. Recent progress on the use of chemoinformatics in TCM research will be discussed and an example of the preliminary application of chemoinformatics methods in anticancer drug design will be provided.

Chemical basis of metabolic network organization.

Although the metabolic networks of the three domains of life consist of different constituents and metabolic pathways, they exhibit the same scale-free organization. This phenomenon has been hypothetically explained by preferential attachment principle that the new-recruited metabolites attach preferentially to those that are already well connected. However, since metabolites are usually small molecules and metabolic processes are basically chemical reactions, we speculate that the metabolic network organization may have a chemical basis. In this paper, chemoinformatic analyses on metabolic networks of Kyoto Encyclopedia of Genes and Genomes (KEGG), Escherichia coli and Saccharomyces cerevisiae were performed. It was found that there exist qualitative and quantitative correlations between network topology and chemical properties of metabolites. The metabolites with larger degrees of connectivity (hubs) are of relatively stronger polarity. This suggests that metabolic networks are chemically organized to a certain extent, which was further elucidated in terms of high concentrations required by metabolic hubs to drive a variety of reactions. This finding not only provides a chemical explanation to the preferential attachment principle for metabolic network expansion, but also has important implications for metabolic network design and metabolite concentration prediction.

Historical Variation of Structural Novelty in a Natural Product Library

To evaluate the potential of natural products as novel structure suppliers, a historical analysis was performed on the structural novelty of a natural product library, viz., the Chapman & Hall/CRC Dictionary of Natural Products. The results show that although the unexplored natural product universe is still ample, it is more and more difficult to find novel agents from nature, with the discovery probability of novel structures and scaffolds being lower than 50% in the near future, which mainly results from the intrinsic redundancy of natural products and, thus, is unlikely to be reversed merely through technical progresses.

Construction of a genome-scale metabolic network of the plant pathogen Pectobacterium carotovorum provides new strategies for bactericide discovery

We reconstructed the first genome‐scale metabolic network of the plant pathogen Pectobacterium carotovorum subsp. carotovorum PC1 based on its genomic sequence, annotation, and physiological data. Metabolic characteristics were analyzed using flux balance analysis (FBA), and the results were afterwards validated by phenotype microarray (PM) experiments. The reconstructed genome‐scale metabolic model, iPC1209, contains 2235 reactions, 1113 metabolites and 1209 genes. We identified 19 potential bactericide targets through a comprehensive in silico gene‐deletion study. Next, we performed virtual screening to identify candidate inhibitors for an important potential drug target, alkaline phosphatase, and experimentally verified that three lead compounds were able to inhibit both bacterial cell viability and the activity of alkaline phosphatase in vitro. This study illustrates a new strategy for the discovery of agricultural bactericides.