Illuminating elite patches of chemical space.
Ontology highlight
ABSTRACT:
SUBMITTER: Verhellen J
PROVIDER: S-EPMC8162856 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:Accurately quantifying the variation of urban green space is the prerequisite for fully understanding its ecosystem services. However, knowledge about the spatiotemporal dynamics of urban green space is still insufficient due to multiple challenges that remain in mapping green spaces within heterogeneous urban environments. This paper uses the city of Hangzhou to demonstrate an analysis methodology that integrates sub-pixel mapping technology and landscape analysis to fully investigate the spatiotemporal pattern and variation of hierarchical urban green space patches. Firstly, multiple endmember spectral mixture analysis was applied to time series Landsat data to derive green space coverage at the sub-pixel level. Landscape metric analysis was then employed to characterize the variation pattern of urban green space patches. Results indicate that Hangzhou has experienced a significant loss of urban greenness, producing a more fragmented and isolated vegetation landscape. Additionally, a remarkable amelioration of urban greenness occurred in the city core from 2002 to 2013, characterized by the significant increase of small-sized green space patches. The green space network has been formed as a consequence of new urban greening strategies in Hangzhou. These strategies have greatly fragmented the built-up areas and enriched the diversity of the urban landscape. Gradient analysis further revealed a distinct pattern of urban green space landscape variation in the process of urbanization. By integrating both sub-pixel mapping technology and landscape analysis, our approach revealed the subtle variation of urban green space patches which are otherwise easy to overlook. Findings from this study will help us to refine our understanding of the evolution of heterogeneous urban environments.
| S-EPMC5492285 | biostudies-other
Project description:The protein cereblon serves as a substrate receptor of a ubiquitin ligase complex that can be tuned toward different target proteins by cereblon-binding agents. This approach to targeted protein degradation is exploited in different clinical settings and has sparked the development of a growing number of thalidomide derivatives. Here, we probe the chemical space of cereblon binding beyond such derivatives and work out a simple set of chemical requirements, delineating the metaclass of cereblon effectors. We report co-crystal structures for a diverse set of compounds, including commonly used pharmaceuticals, but also find that already minimalistic cereblon-binding moieties might exert teratogenic effects in zebrafish. Our results may guide the design of a post-thalidomide generation of therapeutic cereblon effectors and provide a framework for the circumvention of unintended cereblon binding by negative design for future pharmaceuticals.
| S-EPMC6644994 | biostudies-literature
Project description:Characterizing how representations of moral violations are organized, cognitively and neurally, is central to understanding how people conceive and judge them. Past work has identified brain regions that represent morally relevant features and distinguish moral domains, but has not yet advanced a broader account of where and on what basis neural representations of moral violations are organized. With searchlight representational similarity analysis, we investigate where category membership drives similarity in neural patterns during moral judgment of violations from two key moral domains: Harm and Purity. Representations converge across domains in a network of regions resembling the mentalizing network. However, Harm and Purity violation representations respectively converge in different regions: precuneus (PC) and left inferior frontal gyrus (LIFG). Examining substructure within moral domains, Harm violations converge in PC regardless of subdomain (physical harms, psychological harms), while Purity subdomains (pathogen-related violations, sex-related violations) converge in distinct sets of regions - mirroring a dissociation observed in principal-component analysis of behavioral data. Further, we find initial evidence for representation of morally relevant features within these two domain-encoding regions. The present analyses offer a case study for understanding how organization within the complex conceptual space of moral violations is reflected in the organization of neural patterns across the cortex.
| S-EPMC5671354 | biostudies-literature
Project description:Understanding luciferase enzymology and the structure of compounds that modulate luciferase activity can be used to improve the design of luminescence-based assays. This review provides an overview of these popular reporters with an emphasis on the commonly used firefly luciferase from Photinus pyralis (FLuc). Large-scale chemical profile studies have identified a variety of scaffolds that inhibit FLuc. In some cell-based assays, these inhibitors can act in a counterintuitive way, leading to a gain in luminescent signal. Although formerly attributed to transcriptional activation, intracellular stabilization of FLuc is the primary mechanism underlying this observation. FLuc inhibition and stabilization can be complex, as illustrated by the compound PTC124, which is converted by FLuc in the presence of ATP to a high affinity multisubstrate adduct inhibitor, PTC124-AMP. The potential influence these findings can have on drug discovery efforts is provided here.
| S-EPMC2925662 | biostudies-literature
Project description:We introduce SAR-by-Space, a concept to drastically accelerate structure-activity relationship (SAR) elucidation by synthesizing neighboring compounds that originate from vast chemical spaces. The space navigation is accomplished within minutes on affordable standard computer hardware using a tree-based molecule descriptor and dynamic programming. Maximizing the synthetic accessibility of the results from the computer is achieved by applying a careful selection of building blocks in combination with suitably chosen reactions; a decade of in-house quality control shows that this is a crucial part in the process. The REAL Space is the largest chemical space of commercially available compounds, counting 11 billion molecules as of today. It was used to mine actives against bromodomain 4 (BRD4). Before synthesis, compounds were docked into the binding site using a scoring function, which incorporates intrinsic desolvation terms, thus avoiding time-consuming simulations. Five micromolecular hits have been identified and verified within less than six weeks, including the measurement of IC50 values. We conclude that this procedure is a substantial time-saver, accelerating both ligand- and structure-based approaches in hit generation and lead optimization stages.
| S-EPMC6749418 | biostudies-literature
Project description:Modularly assembled combinatorial libraries are often used to identify ligands that bind to and modulate the function of a protein or a nucleic acid. Much of the data from screening these compounds, however, is not efficiently utilized to define structure-activity relationships (SAR). If SAR data are accurately constructed, it can enable the design of more potent binders. Herein, we describe a computer program called Privileged Chemical Space Predictor (PCSP) that statistically determines SAR from high-throughput screening (HTS) data and then identifies features in small molecules that predispose them for binding a target. Features are scored for statistical significance and can be utilized to design improved second generation compounds or more target-focused libraries. The program's utility is demonstrated through analysis of a modularly assembled peptoid library that previously was screened for binding to and inhibiting a group I intron RNA from the fungal pathogen Candida albicans.
| S-EPMC2825671 | biostudies-literature
Project description:We describe a new library generation method, Machine-based Identification of Molecules Inside Characterized Space (MIMICS), that generates sets of molecules inspired by a text-based input. MIMICS-generated libraries were found to preserve distributions of properties while simultaneously increasing structural diversity. Newly identified MIMICS-generated compounds were found to be bioactive as inhibitors of specific components of the unfolded protein response (UPR) and the VEGFR2 pathway in cell-based assays, thus confirming the applicability of this methodology toward drug design applications. Wider application of MIMICS could facilitate the efficient utilization of chemical space.
| S-EPMC5802964 | biostudies-literature
Project description:Just as complex electronic circuits are built from simple Boolean gates, diverse biological functions, including signal transduction, differentiation, and stress response, frequently use biochemical switches as a functional module. A relatively small number of such switches have been described in the literature, and these exhibit considerable diversity in chemical topology. We asked if biochemical switches are indeed rare and if there are common chemical motifs and family relationships among such switches. We performed a systematic exploration of chemical reaction space by generating all possible stoichiometrically valid chemical configurations up to 3 molecules and 6 reactions and up to 4 molecules and 3 reactions. We used Monte Carlo sampling of parameter space for each such configuration to generate specific models and checked each model for switching properties. We found nearly 4,500 reaction topologies, or about 10% of our tested configurations, that demonstrate switching behavior. Commonly accepted topological features such as feedback were poor predictors of bistability, and we identified new reaction motifs that were likely to be found in switches. Furthermore, the discovered switches were related in that most of the larger configurations were derived from smaller ones by addition of one or more reactions. To explore even larger configurations, we developed two tools: the "bistabilizer," which converts almost-bistable systems into bistable ones, and frequent motif mining, which helps rank untested configurations. Both of these tools increased the coverage of our library of bistable systems. Thus, our systematic exploration of chemical reaction space has produced a valuable resource for investigating the key signaling motif of bistability.
| S-EPMC2440819 | biostudies-literature
Project description:Pharmit (http://pharmit.csb.pitt.edu) provides an online, interactive environment for the virtual screening of large compound databases using pharmacophores, molecular shape and energy minimization. Users can import, create and edit virtual screening queries in an interactive browser-based interface. Queries are specified in terms of a pharmacophore, a spatial arrangement of the essential features of an interaction, and molecular shape. Search results can be further ranked and filtered using energy minimization. In addition to a number of pre-built databases of popular compound libraries, users may submit their own compound libraries for screening. Pharmit uses state-of-the-art sub-linear algorithms to provide interactive screening of millions of compounds. Queries typically take a few seconds to a few minutes depending on their complexity. This allows users to iteratively refine their search during a single session. The easy access to large chemical datasets provided by Pharmit simplifies and accelerates structure-based drug design. Pharmit is available under a dual BSD/GPL open-source license.
| S-EPMC4987880 | biostudies-literature
Project description:Unraveling the relation between the chemical structure of small druglike compounds and their rate of passive permeation across lipid membranes is of fundamental importance for pharmaceutical applications. The elucidation of a comprehensive structure-permeability relationship expressed in terms of a few molecular descriptors is unfortunately hampered by the overwhelming number of possible compounds. In this work, we reduce a priori the size and diversity of chemical space to solve an analogous-but smoothed out-structure-property relationship problem. This is achieved by relying on a physics-based coarse-grained model that reduces the size of chemical space, enabling a comprehensive exploration of this space with greatly reduced computational cost. We perform high-throughput coarse-grained (HTCG) simulations to derive a permeability surface in terms of two simple molecular descriptors-bulk partitioning free energy and pK a. The surface is constructed by exhaustively simulating all coarse-grained compounds that are representative of small organic molecules (ranging from 30 to 160 Da) in a high-throughput scheme. We provide results for acidic, basic, and zwitterionic compounds. Connecting back to the atomic resolution, the HTCG predictions for more than 500?000 compounds allow us to establish a clear connection between specific chemical groups and the resulting permeability coefficient, enabling for the first time an inverse design procedure. Our results have profound implications for drug synthesis: the predominance of commonly employed chemical moieties narrows down the range of permeabilities.
| S-EPMC6396385 | biostudies-literature