Molecular Scaffold Analysis of Natural Products Databases in the Public Domain

Natural products represent important sources of bioactive compounds in drug discovery efforts. In this work, we compiled five natural products databases available in the public domain and performed a comprehensive chemoinformatic analysis focused on the content and diversity of the scaffolds with an overview of the diversity based on molecular fingerprints. The natural products databases were compared with each other and with a set of molecules obtained from in‐house combinatorial libraries, and with a general screening commercial library. It was found that publicly available natural products databases have different scaffold diversity. In contrast to the common concept that larger libraries have the largest scaffold diversity, the largest natural products collection analyzed in this work was not the most diverse. The general screening library showed, overall, the highest scaffold diversity. However, considering the most frequent scaffolds, the general reference library was the least diverse. In general, natural products databases in the public domain showed low molecule overlap. In addition to benzene and acyclic compounds, flavones, coumarins, and flavanones were identified as the most frequent molecular scaffolds across the different natural products collections. The results of this work have direct implications in the computational and experimental screening of natural product databases for drug discovery.     

药物分子设计的策略：论药效团和骨架迁越

药物分子是由药效团和结构骨架构成的，药效团是由不连续的离散的原子、基团或片断所构成，但需结合在分子骨架上，形成具体的分子。骨架具有连续性，相同的药效团附着在不同的分子骨架上，构成了作用于同一靶标而结构多样的化合物。骨架依据受体的柔性和可塑性形成了“杂乱性”的空间。显示了受体结合部位的杂乱性。杂乱性越大，可容纳的配体分子的结构多样性就越多，意味着结构修饰与变换的余地大，成药的机会多。由苗头化合物演化成先导物，进而优化成候选药物，这由化合物变革成安全、有效、稳定、可控的药物过程就是保持药效团、变换分子骨架、修饰基团和边链的过程。结构骨架的变化可分为3个层次：以电子等排原理变换骨架结构；以优势结构为导向变换骨架结构；以结构一活性演化的方式变换骨架结构，即骨架迁越。骨架迁越的目的是改善分子的物化、药代、稳定性和赋予分子的结构新颖性。该文以实例阐述了骨架变换的方法与技巧。     

A Re‐examination of the MDM2/p53 Interaction Leads to Revised Design Criteria for Novel Inhibitors

The general model of epitope‐type MDM2 inhibitor was developed based on the structural information on the complexes between MDM2 and various low molecular weight ligands found in the PDB database. Application of this model to our in‐house library has led us to a new scaffold capable of interrupting protein–protein interactions. A synthetic library based on this and related scaffolds resulted in new classes of compounds that possess biochemical and cellular activity and good pharmacokinetic properties. We assume that such general approach to PPI inhibitors design may be useful for the development of inhibitors of various PPI types, including Bcl/XL.     

Ensemble docking to difficult targets in early‐stage drug discovery: Methodology and application to fibroblast growth factor 23

Ensemble docking is now commonly used in early‐stage in silico drug discovery and can be used to attack difficult problems such as finding lead compounds which can disrupt protein–protein interactions. We give an example of this methodology here, as applied to fibroblast growth factor 23 (FGF23), a protein hormone that is responsible for regulating phosphate homeostasis. The first small‐molecule antagonists of FGF23 were recently discovered by combining ensemble docking with extensive experimental target validation data (Science Signaling, 9, 2016, ra113). Here, we provide a detailed account of how ensemble‐based high‐throughput virtual screening was used to identify the antagonist compounds discovered in reference (Science Signaling, 9, 2016, ra113). Moreover, we perform further calculations, redocking those antagonist compounds identified in reference (Science Signaling, 9, 2016, ra113) that performed well on drug‐likeness filters, to predict possible binding regions. These predicted binding modes are rescored with the molecular mechanics Poisson–Boltzmann surface area (MM/PBSA) approach to calculate the most likely binding site. Our findings suggest that the antagonist compounds antagonize FGF23 through the disruption of protein–protein interactions between FGF23 and fibroblast growth factor receptor (FGFR).     

When analoging is not enough: scaffold discovery in medicinal chemistry

Importance of the field: As an integral part of lead generation and optimization, scaffold discovery has broad implications in drug discovery. Currently available chemical scaffolds might be inadequate to provide drug-like ligands for new targets such as phosphatases and protein–protein interactions and therapeutically useful chemical space needs to be continuously explored. New scaffolds are often desired to overcome major hurdles (e.g., potency plateau, selectivity, pharmacokinetics, etc.) in lead generation and optimization. Timely discovery of proof-of-concept compounds facilitates target validation, diversifies clinical candidates and improves the overall success rate of drug discovery.

Areas covered in this review: This analysis discusses the strategies involved in finding new scaffolds (i.e., fragment-, ligand- and structure-based design) and their applications (e.g., improve potency/selectivity, multiple ligand design, protein–protein interactions, etc.) in drug discovery.

What the reader will gain: The readers will learn the strategies involved in scaffold design and the problems that they solve. They will also gain the understanding of the circumstances suitable for using scaffold design.

Take home message: Scaffold is defined by the authors as a biological target dependent concept. Therapeutically useful scaffolds are limited and the identification of new scaffolds is sometimes required to overcome major optimization hurdles. However, depending on the promiscuity of the binding pocket of the target and the validity of the optimization protocol, finding better scaffolds can be a challenging task. Several strategies in scaffold discovery have emerged or matured owing to recent trends such as pursuit of targets from new proteomic families, lack of validated targets, advances in synthesis and biological assays and adoption of in vitro activity-driven screening paradigms.     

Discovery of highly selective inhibitors of p38alpha

The p38 MAP kinases are a family of serine/threonine protein kinases that play a key role in cellular pathways leading to pro-inflammatory responses. We have developed and implemented a method for rapidly identifying and optimizing potent and selective p38alpha inhibitors, which is amenable to other targets and target classes. A diverse library of druggable, purified and quantitated molecules was assembled and standardized enzymatic assays were performed in a microfluidic format that provided very accurate and precise inhibition data allowing for development of SAR directly from the primary HTS. All compounds were screened against a collection of more than 60 enzymes (kinases, proteases and phosphatases), allowing for removal of promiscuous and non-selective inhibitors very early in the discovery process. Follow-up enzymological studies included measurement of concentration of compound in buffer, yielding accurate determination of K(i) and IC50 values, as well as mechanism of action. In addition, active compounds were screened against less desirable properties such as inhibition of the enzyme activity by aggregation, irreversible binding, and time-dependence. Screening of an 88,634-compound library through the above-described process led to the rapid identification of multiple scaffolds (>5 active compounds per scaffold) of potential drug leads for p38alpha that are highly selective against all other enzymes tested, including the three other p38 isoforms. Potency and selectivity data allowed prioritization of the identified scaffolds for optimization. Herein we present results around our 3-thio-1,2,4-triazole lead series of p38- selective inhibitors, including identification, SAR, synthesis, selectivity profile, enzymatic and cellular data in their progression towards drug candidates.     

Identifying and characterizing promiscuous targets: implications for virtual screening

INTRODUCTION: Ligand-based shape matching approaches have become established as important and popular virtual screening (VS) techniques. However, despite their relative success, the question of how to best choose the initial query compounds and their conformations remains largely unsolved. This issue gains importance when dealing with promiscuous targets, that is, proteins that bind multiple ligand scaffold families in one or more binding site. Conventional shape matching VS approaches assume that there is only one binding mode for a given protein target. This may be true for some targets, but it is certainly not true in all cases. Several recent studies have shown that some protein targets bind to different ligands in different ways. AREAS COVERED: The authors discuss the concept of promiscuity in the context of virtual drug screening, and present and analyze several examples of promiscuous targets. The article also reports on the impact of the query conformation on the performance of shape-based VS and the potential to improve VS performance by using consensus shape clustering techniques. EXPERT OPINION: The notion of polypharmacology is becoming highly relevant in drug discovery. Understanding and exploiting promiscuity present challenges and opportunities for drug discovery endeavors. The examples of promiscuity presented here suggest that promiscuous targets and ligands are much more common than previously assumed, and this should be taken into account in practical VS protocols. Although some progress has been made, there is a need to develop more sophisticated computational techniques and protocols that can identify and characterize promiscuous targets on a genomic scale.     

HierS: hierarchical scaffold clustering using topological chemical graphs

An exhaustive ring-based algorithm, HierS, has been developed in order to provide an intuitive approach to compound clustering for analyzing high-throughput screening results. The recursive algorithm rapidly identifies all possible ring-delimited substructures within a set of compounds. Molecules are grouped by shared ring substructures (scaffolds) so that common scaffolds obtain higher membership. Once all of the scaffolds for a set of compounds are identified, the hierarchical structural relationships between the scaffold structures are established. The complex network of hierarchical relationships is then utilized to navigate compounds in a structurally directed fashion. When the scaffold hierarchy is traversed, over-represented structural features can be rapidly identified so that excess compounds that contain them can be removed without significantly impacting the structural diversity landscape of the compound set. Furthermore, the removed compounds can provide the opportunity to follow-up on active compounds that had previously been discarded because of practical limitations on follow-up capacity. A Web-based interface has been developed that incorporates this algorithm in order to allow for an interactive analysis. In addition, biological data are coupled to scaffolds by the inclusion of activity histograms, which indicate how the compounds in each scaffold class performed in previous high-throughput screening campaigns.     

When analoging is not enough: scaffold discovery in medicinal chemistry

Importance of the field: As an integral part of lead generation and optimization, scaffold discovery has broad implications in drug discovery. Currently available chemical scaffolds might be inadequate to provide drug-like ligands for new targets such as phosphatases and protein-protein interactions and therapeutically useful chemical space needs to be continuously explored. New scaffolds are often desired to overcome major hurdles (e.g., potency plateau, selectivity, pharmacokinetics, etc.) in lead generation and optimization. Timely discovery of proof-of-concept compounds facilitates target validation, diversifies clinical candidates and improves the overall success rate of drug discovery. Areas covered in this review: This analysis discusses the strategies involved in finding new scaffolds (i.e., fragment-, ligand- and structure-based design) and their applications (e.g., improve potency/selectivity, multiple ligand design, protein-protein interactions, etc.) in drug discovery. What the reader will gain: The readers will learn the strategies involved in scaffold design and the problems that they solve. They will also gain the understanding of the circumstances suitable for using scaffold design. Take home message: Scaffold is defined by the authors as a biological target dependent concept. Therapeutically useful scaffolds are limited and the identification of new scaffolds is sometimes required to overcome major optimization hurdles. However, depending on the promiscuity of the binding pocket of the target and the validity of the optimization protocol, finding better scaffolds can be a challenging task. Several strategies in scaffold discovery have emerged or matured owing to recent trends such as pursuit of targets from new proteomic families, lack of validated targets, advances in synthesis and biological assays and adoption of in vitro activity-driven screening paradigms.     

Ring systems in mutagenicity databases

The distribution of ring systems in public mutagenicity databases is analyzed. An automated enumeration of substructures permits determination of the occurrence of different scaffolds in data sets. The counts are used to perform population analysis via proportions and odds ratios of mutagenic compounds. Pairwise calculations of odds ratios between scaffolds allow comparison of ring systems for isostere replacement studies. These findings are presented in tables that readily show which scaffold is likely to occur in mutagenic compounds. Also, rings identified in public domain mutagenicity data sets are compared to rings in drugs data sets; unfortunately, public mutagenicity data sets do not reflect the types of scaffolds in drugs and those typically used in medicinal chemistry. The findings bring into question the utility of predictive models that were derived from public domain data sets. The automated ring identification and statistical approaches used here can be applied to other pharmacological properties to yield information about chemical scaffolds.     

Targeted Kinase Selectivity from Kinase Profiling Data

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Classification of scaffold-hopping approaches

The general goal of drug discovery is to identify novel compounds that are active against a preselected biological target with acceptable pharmacological properties defined by marketed drugs. Scaffold hopping has been widely applied by medicinal chemists to discover equipotent compounds with novel backbones that have improved properties. In this article we classify scaffold hopping into four major categories, namely heterocycle replacements, ring opening or closure, peptidomimetics and topology-based hopping. We review the structural diversity of original and final scaffolds with respect to each category. We discuss the advantages and limitations of small, medium and large-step scaffold hopping. Finally, we summarize software that is frequently used to facilitate different kinds of scaffold-hopping methods.     

7,8-dichloro-1-oxo-β-carbolines as a versatile scaffold for the development of potent and selective kinase inhibitors with unusual binding modes

Development of both potent and selective kinase inhibitors is a challenging task in modern drug discovery. The innate promiscuity of kinase inhibitors largely results from ATP-mimetic binding to the kinase hinge region. We present a novel class of substituted 7,8-dichloro-1-oxo-β-carbolines based on the distinct structural features of the alkaloid bauerine C whose kinase inhibitory activity does not rely on canonical ATP-mimetic hinge interactions. Intriguingly, cocrystal structures revealed an unexpected inverted binding mode and the presence of halogen bonds with kinase backbone residues. The compounds exhibit excellent selectivity over a comprehensive panel of human protein kinases while inhibiting selected kinases such as the oncogenic PIM1 at low nanomolar concentrations. Together, our biochemical and structural data suggest that this scaffold may serve as a valuable template for the design and development of specific inhibitors of various kinases including the PIM family of kinases, CLKs, DAPK3 (ZIPK), BMP2K (BIKE), and others.     

How Promiscuous Are Pharmaceutically Relevant Compounds? A Data-Driven Assessment

Given the increasing notion of target promiscuity of bioactive compounds and polypharmacological drug behavior, a detailed analysis of publicly available compound activity data from medicinal chemistry sources was carried out to determine and quantify the degree of promiscuity of active compounds across all known human target families. The results are surprising. Approximately 62% of currently available compounds with high-confidence activity data are only annotated with a single biological target, whereas 36% are known to act against multiple targets within the same family (i.e., closely related targets). However, only ～2% of bioactive compounds are promiscuous across different target families. Thus, despite general data sparseness, these findings indicate that highly promiscuous bioactive compounds only rarely occur. Because pharmaceutically relevant active compounds represent the pool from which drug candidates emerge, one might extrapolate from these results and conclude that there is a low statistical probability to obtain drugs that act against multiple targets belonging to distinct families.     

SHAFTS: a hybrid approach for 3D molecular similarity calculation. 2. Prospective case study in the discovery of diverse p90 ribosomal S6 protein kinase 2 inhibitors to suppress cell migration

We described a prospective application of ligand-based virtual screening program SHAFTS to discover novel inhibitors for p90 ribosomal S6 protein kinase 2 (RSK2). Taking the putative 3D conformations of two weakly binding RSK2 NTKD inhibitors as query templates, SHAFTS was used to perform 3D similarity based virtual screening because of a lack of crystal structure of RSK2 protein, thus leading to the identification of several novel scaffolds that would have been missed by conventional 2D fingerprint methods. The most potent hit compounds show low micromolar inhibitory activities against RSK2. In particular, one of the hit compounds exhibits potent antimigration activity against the MDA-MB-231 tumor cell. The results exemplified SHAFTS' application in active enrichment and scaffold hopping, which is of general interest for lead identification in drug discovery endeavors and also provides novel scaffolds that lay the foundation for uncovering new RSK2 regulatory mechanisms.     

Pyrimidine-2,4,6-trione derivatives and their inhibition of mutant SOD1-dependent protein aggregation. Toward a treatment for amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease characterized by the progressive loss of motor neurons, leading to muscle weakness, paralysis, and death, most often from respiratory failure. The only FDA-approved drug for the treatment of ALS, riluzole, only extends the median survival in patients by 2-3 months. There is an urgent need for novel therapeutic strategies for this devastating disease. Using a high-throughput screening assay targeting an ALS cultured cell model (PC12-G93A-YFP cell line), we previously identified three chemotypes that were neuroprotective. We present a further detailed analysis of one promising scaffold from that group, pyrimidine-2,4,6-triones (PYTs), characterizing a number of PYT analogues using SAR and ADME. The PYT compounds show good potency, superior ADME data, low toxicity, brain penetration, and excellent oral bioavailability. Compounds from this series show 100% efficacy in the protection assay with a good correlation in activity between the protection and protein aggregation assays. The modifications of the PYT scaffold presented here suggest that this chemical structure may be a novel drug candidate scaffold for use in clinical trials in ALS.