Investigation of Atomic Level Patterns in Protein—Small Ligand Interactions

BACKGROUND: Shape complementarity and non-covalent interactions are believed to drive protein-ligand interaction. To date protein-protein, protein-DNA, and protein-RNA interactions were systematically investigated, which is in contrast to interactions with small ligands. We investigate the role of covalent and non-covalent bonds in protein-small ligand interactions using a comprehensive dataset of 2,320 complexes. METHODOLOGY AND PRINCIPAL FINDINGS: We show that protein-ligand interactions are governed by different forces for different ligand types, i.e., protein-organic compound interactions are governed by hydrogen bonds, van der Waals contacts, and covalent bonds; protein-metal ion interactions are dominated by electrostatic force and coordination bonds; protein-anion interactions are established with electrostatic force, hydrogen bonds, and van der Waals contacts; and protein-inorganic cluster interactions are driven by coordination bonds. We extracted several frequently occurring atomic-level patterns concerning these interactions. For instance, 73% of investigated covalent bonds were summarized with just three patterns in which bonds are formed between thiol of Cys and carbon or sulfur atoms of ligands, and nitrogen of Lys and carbon of ligands. Similar patterns were found for the coordination bonds. Hydrogen bonds occur in 67% of protein-organic compound complexes and 66% of them are formed between NH- group of protein residues and oxygen atom of ligands. We quantify relative abundance of specific interaction types and discuss their characteristic features. The extracted protein-organic compound patterns are shown to complement and improve a geometric approach for prediction of binding sites. CONCLUSIONS AND SIGNIFICANCE: We show that for a given type (group) of ligands and type of the interaction force, majority of protein-ligand interactions are repetitive and could be summarized with several simple atomic-level patterns. We summarize and analyze 10 frequently occurring interaction patterns that cover 56% of all considered complexes and we show a practical application for the patterns that concerns interactions with organic compounds

Membrane-mediated interactions

Interactions mediated by the cell membrane between inclusions, such as membrane proteins or antimicrobial peptides, play important roles in their biological activity. They also constitute a fascinating challenge for physicists, since they test the boundaries of our understanding of self-assembled lipid membranes, which are remarkable examples of two-dimensional complex fluids. Inclusions can couple to various degrees of freedom of the membrane, resulting in different types of interactions. In this chapter, we review the membrane-mediated interactions that arise from direct constraints imposed by inclusions on the shape of the membrane. These effects are generic and do not depend on specific chemical interactions. Hence, they can be studied using coarse-grained soft matter descriptions. We deal with long-range membrane-mediated interactions due to the constraints imposed by inclusions on membrane curvature and on its fluctuations. We also discuss the shorter-range interactions that arise from the constraints on membrane thickness imposed by inclusions presenting a hydrophobic mismatch with the membrane.Comment: 38 pages, 10 figures, pre-submission version. In: Bassereau P., Sens P. (eds) Physics of Biological Membranes. Springer, Cha

Pan-cancer analysis of whole genomes

Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale(1-3). Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4-5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter(4); identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation(5,6); analyses timings and patterns of tumour evolution(7); describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity(8,9); and evaluates a range of more-specialized features of cancer genomes(8,10-18).Peer reviewe

SERUM-LIPIDS, LIPOPROTEINS AND APOLIPOPROTEINS IN UNTREATED ESSENTIAL-HYPERTENSION

WOS: A1993LG99000019PubMed ID: 8345503