Random Network Behaviour of Protein Structures

Geometric and structural constraints greatly restrict the selection of folds adapted by protein backbones, and yet, folded proteins show an astounding diversity in functionality. For structure to have any bearing on function, it is thus imperative that, apart from the protein backbone, other tunable degrees of freedom be accountable. Here, we focus on side-chain interactions, which non-covalently link amino acids in folded proteins to form a network structure. At a coarse-grained level, we show that the network conforms remarkably well to realizations of random graphs and displays associated percolation behavior. Thus, within the rigid framework of the protein backbone that restricts the structure space, the side-chain interactions exhibit an element of randomness, which account for the functional flexibility and diversity shown by proteins. However, at a finer level, the network exhibits deviations from these random graphs which, as we demonstrate for a few specific examples, reflect the intrinsic uniqueness in the structure and stability, and perhaps specificity in the functioning of biological proteins.Comment: Expanded version available in Molecular BioSystem

Child Under-weight and Agricultural Productivity in India: Implications for Public Provisioning and Women’s Agency

This study is part of the ongoing research program on Leveraging Agriculture for Nutrition in South Asia (LANSA) funded by UK Aid from the Department for International Development, UK. The authors are consultants or regular staff of M.S. Swaminathan Research Foundation, India, one of the six partner institutions of LANSA.A recent global hunger index indicated a 12 percent decline in child underweight rates. This study attempts an empirical explanation of the factors that influence child underweight rates at the district level. Agricultural land productivity, share of women educated above the secondary level and participating in work, maternal, and child health seem to contribute to the reduction in child underweight. However government health and water supply facilities turn out to be ineffective

Human Tyrosine Hydroxylase Natural Allelic Variation: Influence on Autonomic Function and Hypertension

The catecholamine biosynthetic pathway consists of several enzymatic steps in series, beginning with the amino acids phenylalanine and tyrosine, and eventuating in the catecholamines norepinephrine (noradrenaline) and epinephrine (adrenaline). Since the enzyme tyrosine hydroxylase (TH; tyrosine 3-mono-oxygenase; EC 1.14.16.2; chromosome 11p15.5) is generally considered to be rate-limiting in this pathway, probed as to whether common genetic variation at the TH gene occurred, and whether such variants contributed to inter-individual alterations in autonomic function, either biochemical or physiological. We began with sequencing a tetranucleotide (TCAT) repeat in the first intron, and found that the two most common versions, (TCAT)6 and (TCAT)10i, predicted heritable autonomic traits in twin pairs. We then conducted systematic polymorphism discovery across the ~8 kbp locus, and discovered numerous variants, principally non-coding. The proximal promoter block contained four common variants, and its haplotypes and SNPs (especially C-824T, rs10770141) predicted catecholamine secretion, environmental stress-induced BP increments, and hypertension. Finally, we found that two of the common promoter variants, C-824T (rs10770141) and A-581G (rs10770140), were functional in that they differentially affected transcriptional activity of the isolated promoter, disrupted recognition motifs for specific transcription factor binding, altered the promoter responses to the co-transfected (exogenous) factors, and bound the endogenous factors in the chromatin fraction of the nucleus. We concluded that common variation in the proximal TH promoter is functional, giving rise to changes in autonomic function and consequently cardiovascular risk

Oncogenic KRAS engages an RSK1/NF1 pathway to inhibit wild-type RAS signaling in pancreatic cancer.

Pancreatic ductal adenocarcinoma (PDAC) is a lethal malignancy with limited treatment options. Although activating mutations of the KRAS GTPase are the predominant dependency present in >90% of PDAC patients, targeting KRAS mutants directly has been challenging in PDAC. Similarly, strategies targeting known KRAS downstream effectors have had limited clinical success due to feedback mechanisms, alternate pathways, and dose-limiting toxicities in normal tissues. Therefore, identifying additional functionally relevant KRAS interactions in PDAC may allow for a better understanding of feedback mechanisms and unveil potential therapeutic targets. Here, we used proximity labeling to identify protein interactors of active KRAS in PDAC cells. We expressed fusions of wild-type (WT) (BirA-KRAS4B), mutant (BirA-KRAS4BG12D), and nontransforming cytosolic double mutant (BirA-KRAS4BG12D/C185S) KRAS with the BirA biotin ligase in murine PDAC cells. Mass spectrometry analysis revealed that RSK1 selectively interacts with membrane-bound KRASG12D, and we demonstrate that this interaction requires NF1 and SPRED2. We find that membrane RSK1 mediates negative feedback on WT RAS signaling and impedes the proliferation of pancreatic cancer cells upon the ablation of mutant KRAS. Our findings link NF1 to the membrane-localized functions of RSK1 and highlight a role for WT RAS signaling in promoting adaptive resistance to mutant KRAS-specific inhibitors in PDAC

Positive mental health in schizophrenia and healthy comparison groups: relationships with overall health and biomarkers

ObjectivePositive psychological factors (PPFs) have been reported to have a significant impact on health in the general population. However, little is known about the relationship of these factors with mental and physical health in schizophrenia.MethodOne hundred and thirty-five outpatients with schizophrenia and 127 healthy comparison subjects (HCs), aged 26-65 years, were evaluated with scales of resilience, optimism, happiness, and perceived stress. Measures of mental and physical health were also obtained. Regression analyses examined associations of a PPF composite with health variables.ResultsRelative to the HCs, the schizophrenia group had lower levels of PPFs. However, there was considerable heterogeneity, with over one-third of schizophrenia participants having values within the 'normative' range. The PPF composite was positively related to mental and physical health variables and with biomarkers of inflammation and insulin resistance. The relationship between PPFs and mental health was particularly strong for individuals with schizophrenia.ConclusionA sizable minority of adults with chronic schizophrenia have levels of resilience, optimism, happiness, and perceived stress similar to HCs. Psychosocial interventions to enhance PPFs should be tested in patients with serious mental illnesses, with the goal of improving their mental health (beyond controlling symptoms of psychosis) and their physical health

The Role of Oligomerization and Cooperative Regulation in Protein Function: The Case of Tryptophan Synthase

The oligomerization/co-localization of protein complexes and their cooperative regulation in protein function is a key feature in many biological systems. The synergistic regulation in different subunits often enhances the functional properties of the multi-enzyme complex. The present study used molecular dynamics and Brownian dynamics simulations to study the effects of allostery, oligomerization and intermediate channeling on enhancing the protein function of tryptophan synthase (TRPS). TRPS uses a set of α/β–dimeric units to catalyze the last two steps of L-tryptophan biosynthesis, and the rate is remarkably slower in the isolated monomers. Our work shows that without their binding partner, the isolated monomers are stable and more rigid. The substrates can form fairly stable interactions with the protein in both forms when the protein reaches the final ligand–bound conformations. Our simulations also revealed that the α/β–dimeric unit stabilizes the substrate–protein conformation in the ligand binding process, which lowers the conformation transition barrier and helps the protein conformations shift from an open/inactive form to a closed/active form. Brownian dynamics simulations with a coarse-grained model illustrate how protein conformations affect substrate channeling. The results highlight the complex roles of protein oligomerization and the fine balance between rigidity and dynamics in protein function

Barriers to formal healthcare utilisation among poor older people under the livelihood empowerment against poverty programme in the Atwima Nwabiagya District of Ghana

Abstract: Background: Even though there is a growing literature on barriers to formal healthcare use among older people, little is known from the perspective of vulnerable older people in Ghana. Involving poor older people under the Livelihood Empowerment Against Poverty (LEAP) programme, this study explores barriers to formal healthcare use in the Atwima Nwabiagya District of Ghana. Methods: Interviews and focus group discussions were conducted with 30 poor older people, 15 caregivers and 15 formal healthcare providers in the Atwima Nwabiagya District of Ghana. Data were analysed using the thematic analytical framework, and presented based on an a posteriori inductive reduction approach. Results: Four main barriers to formal healthcare use were identified: physical accessibility barriers (poor transport system and poor architecture of facilities), economic barriers (low income coupled with high charges, and non-comprehensive nature of the National Health Insurance Scheme [NHIS]), social barriers (communication/language difficulties and poor family support) and unfriendly nature of healthcare environment barriers (poor attitude of healthcare providers). Conclusions: Considering these barriers, removing them would require concerted efforts and substantial financial investment by stakeholders. We argue that improvement in rural transport services, implementation of free healthcare for poor older people, strengthening of family support systems, recruitment of language translators at the health facilities and establishment of attitudinal change programmes would lessen barriers to formal healthcare use among poor older people. This study has implications for health equity and health policy framework in Ghana

Metabolome Based Reaction Graphs of M. tuberculosis and M. leprae: A Comparative Network Analysis

BACKGROUND: Several types of networks, such as transcriptional, metabolic or protein-protein interaction networks of various organisms have been constructed, that have provided a variety of insights into metabolism and regulation. Here, we seek to exploit the reaction-based networks of three organisms for comparative genomics. We use concepts from spectral graph theory to systematically determine how differences in basic metabolism of organisms are reflected at the systems level and in the overall topological structures of their metabolic networks. METHODOLOGY/PRINCIPAL FINDINGS: Metabolome-based reaction networks of Mycobacterium tuberculosis, Mycobacterium leprae and Escherichia coli have been constructed based on the KEGG LIGAND database, followed by graph spectral analysis of the network to identify hubs as well as the sub-clustering of reactions. The shortest and alternate paths in the reaction networks have also been examined. Sub-cluster profiling demonstrates that reactions of the mycolic acid pathway in mycobacteria form a tightly connected sub-cluster. Identification of hubs reveals reactions involving glutamate to be central to mycobacterial metabolism, and pyruvate to be at the centre of the E. coli metabolome. The analysis of shortest paths between reactions has revealed several paths that are shorter than well established pathways. CONCLUSIONS: We conclude that severe downsizing of the leprae genome has not significantly altered the global structure of its reaction network but has reduced the total number of alternate paths between its reactions while keeping the shortest paths between them intact. The hubs in the mycobacterial networks that are absent in the human metabolome can be explored as potential drug targets. This work demonstrates the usefulness of constructing metabolome based networks of organisms and the feasibility of their analyses through graph spectral methods. The insights obtained from such studies provide a broad overview of the similarities and differences between organisms, taking comparative genomics studies to a higher dimension

False positive reduction in protein-protein interaction predictions using gene ontology annotations

<p>Abstract</p> <p>Background</p> <p>Many crucial cellular operations such as metabolism, signalling, and regulations are based on protein-protein interactions. However, the lack of robust protein-protein interaction information is a challenge. One reason for the lack of solid protein-protein interaction information is poor agreement between experimental findings and computational sets that, in turn, comes from huge false positive predictions in computational approaches. Reduction of false positive predictions and enhancing true positive fraction of computationally predicted protein-protein interaction datasets based on highly confident experimental results has not been adequately investigated.</p> <p>Results</p> <p>Gene Ontology (GO) annotations were used to reduce false positive protein-protein interactions (PPI) pairs resulting from computational predictions. Using experimentally obtained PPI pairs as a training dataset, eight top-ranking keywords were extracted from GO molecular function annotations. The sensitivity of these keywords is 64.21% in the yeast experimental dataset and 80.83% in the worm experimental dataset. The specificities, a measure of recovery power, of these keywords applied to four predicted PPI datasets for each studied organisms, are 48.32% and 46.49% (by average of four datasets) in yeast and worm, respectively. Based on eight top-ranking keywords and co-localization of interacting proteins a set of two knowledge rules were deduced and applied to remove false positive protein pairs. The '<it>strength</it>', a measure of improvement provided by the rules was defined based on the signal-to-noise ratio and implemented to measure the applicability of knowledge rules applying to the predicted PPI datasets. Depending on the employed PPI-predicting methods, the <it>strength </it>varies between two and ten-fold of randomly removing protein pairs from the datasets.</p> <p>Conclusion</p> <p>Gene Ontology annotations along with the deduced knowledge rules could be implemented to partially remove false predicted PPI pairs. Removal of false positives from predicted datasets increases the true positive fractions of the datasets and improves the robustness of predicted pairs as compared to random protein pairing, and eventually results in better overlap with experimental results.</p