Absence Of Structural Features Research Articles

Chemical Space Covered by Applicability Domains of Quantitative Structure-Property Relationships and Semiempirical Relationships in Chemical Assessments.

A significant number of chemicals registered in national and regional chemical inventories require assessments of their potential "hazard" concerns posed to humans and ecological receptors. This warrants knowledge of their partitioning and reactivity properties, which are often predicted by quantitative structure-property relationships (QSPRs) and other semiempirical relationships. It is imperative to evaluate the applicability domain (AD) of these tools to ensure their suitability for assessment purpose. Here, we investigate the extent to which the ADs of commonly used QSPRs and semiempirical relationships cover seven partitioning and reactivity properties of a chemical "space" comprising 81,000+ organic chemicals registered in regulatory and academic chemical inventories. Our findings show that around or more than half of the chemicals studied are covered by at least one of the commonly used QSPRs. The investigated QSPRs demonstrate adequate AD coverage for organochlorides and organobromines but limited AD coverage for chemicals containing fluorine and phosphorus. These QSPRs exhibit limited AD coverage for atmospheric reactivity, biodegradation, and octanol-air partitioning, particularly for ionizable organic chemicals compared to nonionizable ones, challenging assessments of environmental persistence, bioaccumulation capability, and long-range transport potential. We also find that a predictive tool's AD coverage of chemicals depends on how the AD is defined, for example, by the distance of a predicted chemical from the centroid of the training chemicals or by the presence or absence of structural features.

LigMate: A Multifeature Integration Algorithm for Ligand-Similarity-Based Virtual Screening.

Ligand-similarity-based virtual screening is one of the most applicable computer-aided drug design techniques. The current methodology relies heavily on several descriptors of molecular features, including atoms (zero-dimensional, 0D), the presence or absence of structural features (one-dimensional, 1D), topological descriptors (two-dimensional, 2D), geometry and volume (three-dimensional, 3D), or stereoelectronic and stereodynamic properties (four-dimensional, 4D). These descriptors have been frequently used in virtual screening; however, they are usually used independently without integration, which may hinder effective and precise virtual screening. In this study, we developed a multifeature integration algorithm named LigMate, which employs a Hungarian algorithm-based matching and a machine learning-based nonlinear combination of various descriptors, including the new relevant descriptors focusing on the maximum common substructures (maximum common substructure score, MCSS), the relative distance of atoms from the ligand mass center (intraligand distance score, ILDS), as well as the ring differences (ring score, RS). In the benchmark tests, LigMate achieved an overall enrichment factor of the first percent (EF1) of 36.14 and an area under the curve (AUC) value of 0.81 on the DUD-E data set, as well as an EF1 of 15.44 and an AUC of 0.69 on the maximum unbiased validation (MUV) data set, outperforming the control methods that are based on single descriptors. Thus, our study provides a new framework for multiple feature integration, which can benefit ligand-similarity-based virtual screening. LigMate is freely available for noncommercial users at http://cao.labshare.cn/ligmate/.

Systemic Loss and Gain of Chromatin Architecture throughout Zebrafish Development

SummaryThe spatial organization of chromosomes is critical in establishing gene expression programs. We generated in situ Hi-C maps throughout zebrafish development to gain insight into higher-order chromatin organization and dynamics. Zebrafish chromosomes segregate in active and inactive chromatin (A/B compartments), which are further organized into topologically associating domains (TADs). Zebrafish A/B compartments and TADs have genomic features similar to those of their mammalian counterparts, including evolutionary conservation and enrichment of CTCF binding sites at TAD borders. At the earliest time point, when there is no zygotic transcription, the genome is highly structured. After zygotic genome activation (ZGA), the genome loses structural features, which are re-established throughout early development. Despite the absence of structural features, we see clustering of super-enhancers in the 3D genome. Our results provide insight into vertebrate genome organization and demonstrate that the developing zebrafish embryo is a powerful model system to study the dynamics of nuclear organization.

Assembly and Expression of Shark Ig Genes.

Sharks are modern descendants of the earliest vertebrates possessing Ig superfamily receptor-based adaptive immunity. They respond to immunogen with Abs that, upon boosting, appear more rapidly and show affinity maturation. Specific Abs and immunological memory imply that Ab diversification and clonal selection exist in cartilaginous fish. Shark Ag receptors are generated through V(D)J recombination, and because it is a mechanism known to generate autoreactive receptors, this implies that shark lymphocytes undergo selection. In the mouse, the ∼2.8-Mb IgH and IgL loci require long-range, differential activation of component parts for V(D)J recombination, allelic exclusion, and receptor editing. These processes, including class switching, evolved with and appear inseparable from the complex locus organization. In contrast, shark Igs are encoded by 100-200 autonomously rearranging miniloci. This review describes how the shark primary Ab repertoire is generated in the absence of structural features considered essential in mammalian Ig gene assembly and expression.

Contrasting expression of membrane metalloproteinases, MT1-MMP and MT3-MMP, suggests distinct functions in skeletal development

Membrane-type 1 matrix metalloproteinase (MT1-MMP) is the most ubiquitous and widely studied of the membrane-type metalloproteinases (MT-MMPs). It was thus surprising to find no published data on chicken MT1-MMP. We report here the characterization of the chicken gene. Its low sequence identity with the MT1-MMP genes of other species, high GC content, and divergent catalytic domain explains the absence of data and our difficulties in characterizing the gene. The absence of structural features in the chicken gene that have been suggested to be critical for the activation of MMP-2 by MT1-MMP; for the effect of MT1-MMP on cell migration and for the recycling of MT1-MMP suggest these features are either not essential or that MT1-MMP does not perform these functions in chickens. Comparison of the expression of chicken MT1-MMP with MT3-MMP and with MMP-2 and MMP-13 has confirmed the previously recognized co-expression of MT1-MMP with MMP-2 and MMP-13 in fibrous and vascular tissues, particularly those surrounding the developing long bones in other species. By contrast, MT3-MMP expression differs markedly from that of MT1-MMP and of both MMP-2 and MMP-13. MT3-MMP is expressed by chondrocytes of the developing articular surface. Similar expression patterns of this group of MT-MMPs and MMPs have been observed in mouse embryos and suggest distinct and specific functions for MT1-MMP and MT3-MMP in skeletal development.

A Modification of the Jaccard–Tanimoto Similarity Index for Diverse Selection of Chemical Compounds Using Binary Strings

Determination of molecular similarity plays an important role in analyzing large compound databases in chemical and pharmaceutical research. When molecules are described by binary vectors with bits corresponding to the presence or absence of structural features, the Tanimoto association coefficient is the most commonly used measure of similarity or chemical distance between two compounds. However, when used to select compounds for an optimal spread design, the Tanimoto coefficient produces an intrinsic bias toward smaller compounds. We have developed a new association coefficient that overcomes this bias. This article gives details of the new coefficient and contrasts the two coefficients for selecting diverse sets of compounds from a large collection. When the Tanimoto coefficient is modified as suggested to select a diverse set in the National Cancer Institute and Registry of Toxic Effects of Chemical Substances databases, the average number of features among the selected compounds increases by more than 50%.

Structural requirements for the induction of the SOS repair in bacteria by nitrated polycyclic aromatic hydrocarbons and related chemicals

The CASE (computer-automated structure evaluation) methodology was used to investigate the structural basis of the SOS-inducing activity of 56 nitrated polycyclic aromatic hydrocarbons (nitroarenes, nPAH) and the unsubstituted parent PAH molecules. Based upon the presence and/or absence of structural features, CASE identified 5 activating (biophores) and 4 inactivating (biophobes) fragments responsible for the SOS-inducing activity. Based upon these fragments, CASE correctly calculated the genotoxicity of 94.6% of the molecules in the training set (sensitivity = 0.85, specifity = 1.0). Disregarding the questionable experimental results of the unexpected very weak direct-acting activity of the unsubstituted benzo[ a]pyrene, dibenzo[ a, h]anthracene and 7,12-dimethylbenz[ a]anthracene, the concordance of the prediction was 100%, i.e., sensitivity = 1.0, specifity = 1.0. Additionally, the quantitative analysis of the SOS-inducing potency showed a good correlation between the experimental and predicted results. The present analyses indicate an identity in the structural determinants responsible for SOS induction in E. coli PQ37 (SOS chromotest) and mutagenicity in Salmonella typhimurium.