Extent of Structural Asymmetry in Homodimeric Proteins: Prevalence and Relevance

Most homodimeric proteins have symmetric structure. Although symmetry is known to confer structural and functional advantage, asymmetric organization is also observed. Using a non-redundant dataset of 223 high-resolution crystal structures of biologically relevant homodimers, we address questions on the prevalence and significance of asymmetry. We used two measures to quantify global and interface asymmetry, and assess the correlation of several molecular and structural parameters with asymmetry. We have identified rare cases (11/223) of biologically relevant homodimers with pronounced global asymmetry. Asymmetry serves as a means to bring about 2∶1 binding between the homodimer and another molecule; it also enables cellular signalling arising from asymmetric macromolecular ligands such as DNA. Analysis of these cases reveals two possible mechanisms by which possible infinite array formation is prevented. In case of homodimers associating via non-topologically equivalent surfaces in their tertiary structures, ligand-dependent mechanisms are used. For stable dimers binding via large surfaces, ligand-dependent structural change regulates polymerisation/depolymerisation; for unstable dimers binding via smaller surfaces that are not evolutionarily well conserved, dimerisation occurs only in the presence of the ligand. In case of homodimers associating via interaction surfaces with parts of the surfaces topologically equivalent in the tertiary structures, steric hindrance serves as the preventive mechanism of infinite array. We also find that homodimers exhibiting grossly symmetric organization rarely exhibit either perfect local symmetry or high local asymmetry. Binding of small ligands at the interface does not cause any significant variation in interface asymmetry. However, identification of biologically relevant interface asymmetry in grossly symmetric homodimers is confounded by the presence of similar small magnitude changes caused due to artefacts of crystallisation. Our study provides new insights regarding accommodation of asymmetry in homodimers

GTM-decon: guided-topic modeling of single-cell transcriptomes enables sub-cell-type and disease-subtype deconvolution of bulk transcriptomes

Abstract Cell-type composition is an important indicator of health. We present Guided Topic Model for deconvolution (GTM-decon) to automatically infer cell-type-specific gene topic distributions from single-cell RNA-seq data for deconvolving bulk transcriptomes. GTM-decon performs competitively on deconvolving simulated and real bulk data compared with the state-of-the-art methods. Moreover, as demonstrated in deconvolving disease transcriptomes, GTM-decon can infer multiple cell-type-specific gene topic distributions per cell type, which captures sub-cell-type variations. GTM-decon can also use phenotype labels from single-cell or bulk data to infer phenotype-specific gene distributions. In a nested-guided design, GTM-decon identified cell-type-specific differentially expressed genes from bulk breast cancer transcriptomes

Additional file 2 of GTM-decon: guided-topic modeling of single-cell transcriptomes enables sub-cell-type and disease-subtype deconvolution of bulk transcriptomes

Additional file 2. Review history

Additional file 1 of GTM-decon: guided-topic modeling of single-cell transcriptomes enables sub-cell-type and disease-subtype deconvolution of bulk transcriptomes

Additional file 1. Supplementary Section S1 (Evaluation on gene selection strategies); S2 (Evaluation on raw count and transformation strategies); S3 (Experimenting hyperparameters $$\alpha_{\mathrm m,\mathrm k}$$ α m , k for cell-type mixture prior); S4 (Experimenting hyperparameter $$\beta$$ β for CTS topics); S5 (Experimenting number of topics per cell type); S6 (Benchmark time and memory usage); S7 (Effect of sparsification on phenotype classification); S8 (Phenotype-CTS topic modeling of single-cell breast cancer transcriptomes for TCGA-BRCA bulk deconvolution); S9 (Effect of cell size on inference of cell-type deconvolution); Table S1-S3; Figure S1-S31

Molecular aspects of asymmetry.

<p>This figure shows the correlation of mathematical asymmetry captured by GloA_Sc with a) Cα-RMSD b) interface area c) normalized B-factors and d) crystal packing. Figures a,b,and c are scatter plots in which the molecular parameter being studied is shown along the X-axis and GloA_Sc along the Y-axis. In b), a subset of the overall graph cotnaining the majority of data is shown for clarity (with the maximum interface area being ∼25000 Ų). Figure d) is a box-plot representation of the absolute difference in GloA_Sc for the pairs of homodimers in each dataset. The horizontal bars present the 5 percentile, 25 percentile, 50 percentile, 75 percentile and 95 percentile values of each distribution and the mean value as ‘+’. Outliers are represented as dots.</p

Homodimers exhibiting ligand-dependent global asymmetry.

<p>This figure shows examples of ligand-dependent asymmetric homodimers. a). Orphan nuclear receptor NR1D1 (GloA_Sc – 15.49; PDB – 1a6y) b). Vitamin D3 receptor (GloA_Sc – 17.47; PDB – 1kb2) c). Heme activator protein (GloA_Sc – 9.08; PDB – 1hwt) d). Stage 0 sporulation protein A (GloA_Sc – 11.79; PDB – 1lq1). One of the chains of the dimer is shown as a green colored cartoon whereas the other chain provides a color-based representation of the conservation of every residue position, calculated using ConSurf <i>(refer Methods)</i>. In the chain colored based on ConSurf scores, highly conserved residues are colored magenta whereas poorly conserved residues are colored cyan and moderately conserved residues are shown in white. Any other ligand(s) bound to the dimer is depicted as orange spheres. Other chains closely interacting in the asymmetric unit are colored yellow.</p

Details of functionally relevant homodimers exhibiting global asymmetry.

<p>Note: The dimeric molecule under consideration is highlighted using italics. For cases of interface asymmetry score 1 = 1, no interface asymmetry score 2 can be calculated. These are indicated as ##.</p

Evolutionary aspects of functionally relevant homodimers exhibiting global asymmetry.

<p>Note: Unless indicated by * all homologous sequences have been gathered from Uniref50 database. If very few homologues are identified then homologues identified from Uniref90 database (indicated by *) are used in the analysis. In a few PDB entries, several molecules are present. The dimeric molecule under consideration is highlighted using italics.</p