Strong and weak hydrogen bonds in drug-DNA complexes: a statistical analysis

A statistical analysis of strong and weak hydrogen bonds in the minor groove of DNA was carried out for a set of 70 drug-DNA complexes. The terms "strong" and "weak" pertain to the inherent strengths and weakness of the donor and acceptor fragments rather than to any energy considerations. The dataset was extracted from the protein data bank (PDB). The analysis was performed with an in-house software, hydrogen bond analysis tool (HBAT). In addition to strong hydrogen bonds such as O-H···O and N-H···O, the ubiquitous presence of weak hydrogen bonds such as C-H···O is implicated in molecular recognition. On an average, there are 1.4 weak hydrogen bonds for every strong hydrogen bond. For both categories of interaction, the N(3) of purine and the O(2) of pyrimidine are favoured acceptors. Donor multifurcation is common with the donors generally present in the drug molecules, and shared by hydrogen bond acceptors in the minor groove. Bifurcation and trifurcation are most commonly observed. The metrics for strong hydrogen bonds are consistent with established trends. The geometries are variable for weak hydrogen bonds. A database of recognition geometries for 26 literature amidinium-based inhibitors of Human African Trypanosomes (HAT) was generated with a docking study using seven inhibitors which occur in published crystal structures included in the list of 70 complexes mentioned above, and 19 inhibitors for which the drug-DNA complex crystal structures are unknown. The virtual geometries so generated correlate well with published activities for these 26 inhibitors, justifying our assumption that strong and weak hydrogen bonds are optimized in the active site

Strong and weak hydrogen bonds in the protein-ligand interface

The characteristics of NH···O, OH···O, and CH···O hydrogen bonds and other weak intermolecular interactions are analyzed in a large and diverse group of 251 protein-ligand complexes using a new computer program that was developed in-house for this purpose. The interactions examined in the present study are those which occur in the active sites, defined here as a sphere of 10 Å radius around the ligand. Notably, NH···O and OH···O bonds tend towards linearity. Multifurcated interactions are especially common, especially multifurcated acceptors, and the average degree of furcation is 2.6 hydrogen bonds per furcated acceptor. A significant aspect of this study is that we have been able to assess the reliability of hydrogen bond geometry as a function of crystallographic resolution. Thresholds of 2.3 and 2.0 Å are established for strong and weak hydrogen bonds, below which hydrogen bond geometries may be safely considered for detailed analysis. Interactions involving water as donor or acceptor, and CH···O bonds with Gly and Tyr as donors are ubiquitous in the active site. A similar trend was observed in an external test set of 233 protein-ligand complexes belonging to the kinase family. Weaker interactions like XH···∏ (X = C, N, O) and those involving halogen atoms as electrophiles or nucleophiles have also been studied. We conclude that the strong and weak hydrogen bonds are ubiquitous in protein-ligand recognition, and that with suitable computational tools very large numbers of strong and weak intermolecular interactions in the ligand-protein interface may be analyzed reliably. Results confirm earlier trends reported previously by us but the extended nature of the present data set mean that the observed trends are more reliable

Gpr17 deficiency in POMC neurons ameliorates the metabolic derangements caused by long-term high-fat diet feeding

BACKGROUND: Proopiomelanocortin (POMC) neurons in the arcuate nucleus of the hypothalamus (ARH) control energy homeostasis by sensing hormonal and nutrient cues and activating secondary melanocortin sensing neurons. We identified the expression of a G protein-coupled receptor, Gpr17, in the ARH and hypothesized that it contributes to the regulatory function of POMC neurons on metabolism. METHODS: In order to test this hypothesis, we generated POMC neuron-specific Gpr17 knockout (PGKO) mice and determined their energy and glucose metabolic phenotypes on normal chow diet (NCD) and high-fat diet (HFD). RESULTS: Adult PGKO mice on NCD displayed comparable body composition and metabolic features measured by indirect calorimetry. By contrast, PGKO mice on HFD demonstrated a sexually dimorphic phenotype with female PGKO mice displaying better metabolic homeostasis. Notably, female PGKO mice gained significantly less body weight and adiposity (p < 0.01), which was associated with increased energy expenditure, locomotor activity, and respiratory quotient, while males did not have an overt change in energy homeostasis. Though PGKO mice of both sexes had comparable glucose and insulin tolerance, detailed analyses of liver gene expression and serum metabolites indicate that PGKO mice could have reduced gluconeogenesis and increased lipid utilization on HFD. To elucidate the central-based mechanism(s) underlying the better-preserved energy and glucose homeostasis in PGKO mice on HFD, we examined the electrophysiological properties of POMC neurons and found Gpr17 deficiency led to increased spontaneous action potentials. Moreover, PGKO mice, especially female knockouts, had increased POMC-derived alpha-melanocyte stimulating hormone and beta-endorphin despite a comparable level of prohormone POMC in their hypothalamic extracts. CONCLUSIONS: Gpr17 deficiency in POMC neurons protects metabolic homeostasis in a sex-dependent manner during dietary and aging challenges, suggesting that Gpr17 could be an effective anti-obesity target in specific populations with poor metabolic control

Evaluation of CSF and plasma biomarkers of brain melanocortin activity in response to caloric restriction in humans

The melanocortin neuronal system, which consists of hypothalamic proopiomelanocortin (POMC) and agouti-related protein (AgRP) neurons, is a leptin target that regulates energy balance and metabolism, but studies in humans are limited by a lack of reliable biomarkers to assess brain melanocortin activity. The objective of this study was to measure the POMC prohormone and its processed peptide, β-endorphin (β-EP), in cerebrospinal fluid (CSF) and AgRP in CSF and plasma after calorie restriction to validate their utility as biomarkers of brain melanocortin activity. CSF and plasma were obtained from 10 lean and obese subjects after fasting (40 h) and refeeding (24 h), and from 8 obese subjects before and after 6 wk of dieting (800 kcal/day) to assess changes in neuropeptide and hormone levels. After fasting, plasma leptin decreased to 35%, and AgRP increased to 153% of baseline. During refeeding, AgRP declined as leptin increased; CSF β-EP increased, but POMC did not change. Relative changes in plasma and CSF leptin were blunted in obese subjects. After dieting, plasma and CSF leptin decreased to 46% and 70% of baseline, CSF POMC and β-EP decreased, and plasma AgRP increased. At baseline, AgRP correlated negatively with insulin and homeostasis model assessment (HOMA-IR), and positively with the Matsuda index. Thus, following chronic calorie restriction, POMC and β-EP declined in CSF, whereas acutely, only β-EP changed. Plasma AgRP, however, increased after both acute and chronic calorie restriction. These results support the use of CSF POMC and plasma AgRP as biomarkers of hypothalamic melanocortin activity and provide evidence linking AgRP to insulin sensitivity

RAD9 deficiency enhances radiation induced bystander DNA damage and transcriptomal response

Background Radiation induced bystander effects are an important component of the overall response of cells to irradiation and are associated with human health risks. The mechanism responsible includes intra-cellular and inter-cellular signaling by which the bystander response is propagated. However, details of the signaling mechanism are not well defined. Methods We measured the bystander response of Mrad9 +/+ and Mrad9 −/− mouse embryonic stem cells, as well as human H1299 cells with inherent or RNA interference-mediated reduced RAD9 levels after exposure to 1 Gy α particles, by scoring chromosomal aberrations and micronuclei formation, respectively. In addition, we used microarray gene expression analyses to profile the transcriptome of directly irradiated and bystander H1299 cells. Results We demonstrated that Mrad9 null enhances chromatid aberration frequency induced by radiation in bystander mouse embryonic stem cells. In addition, we found that H1299 cells with reduced RAD9 protein levels showed a higher frequency of radiation induced bystander micronuclei formation, compared with parental cells containing inherent levels of RAD9. The enhanced bystander response in human cells was associated with a unique transcriptomic profile. In unirradiated cells, RAD9 reduction broadly affected stress response pathways at the mRNA level; there was reduction in transcript levels corresponding to genes encoding multiple members of the UVA-MAPK and p38MAPK families, such as STAT1 and PARP1, suggesting that these signaling mechanisms may not function optimally when RAD9 is reduced. Using network analysis, we found that differential activation of the SP1 and NUPR1 transcriptional regulators was predicted in directly irradiated and bystander H1299 cells. Transcription factor prediction analysis also implied that HIF1α (Hypoxia induced factor 1 alpha) activation by protein stabilization in irradiated cells could be a negative predictor of the bystander response, suggesting that local hypoxic stress experienced by cells directly exposed to radiation may influence whether or not they will elicit a bystander response in neighboring cells

Modern microwave methods in solid state inorganic materials chemistry: from fundamentals to manufacturing

No abstract available

Neurodevelopmental disorders in children aged 2-9 years: Population-based burden estimates across five regions in India.

BACKGROUND: Neurodevelopmental disorders (NDDs) compromise the development and attainment of full social and economic potential at individual, family, community, and country levels. Paucity of data on NDDs slows down policy and programmatic action in most developing countries despite perceived high burden. METHODS AND FINDINGS: We assessed 3,964 children (with almost equal number of boys and girls distributed in 2-<6 and 6-9 year age categories) identified from five geographically diverse populations in India using cluster sampling technique (probability proportionate to population size). These were from the North-Central, i.e., Palwal (N = 998; all rural, 16.4% non-Hindu, 25.3% from scheduled caste/tribe [SC-ST] [these are considered underserved communities who are eligible for affirmative action]); North, i.e., Kangra (N = 997; 91.6% rural, 3.7% non-Hindu, 25.3% SC-ST); East, i.e., Dhenkanal (N = 981; 89.8% rural, 1.2% non-Hindu, 38.0% SC-ST); South, i.e., Hyderabad (N = 495; all urban, 25.7% non-Hindu, 27.3% SC-ST) and West, i.e., North Goa (N = 493; 68.0% rural, 11.4% non-Hindu, 18.5% SC-ST). All children were assessed for vision impairment (VI), epilepsy (Epi), neuromotor impairments including cerebral palsy (NMI-CP), hearing impairment (HI), speech and language disorders, autism spectrum disorders (ASDs), and intellectual disability (ID). Furthermore, 6-9-year-old children were also assessed for attention deficit hyperactivity disorder (ADHD) and learning disorders (LDs). We standardized sample characteristics as per Census of India 2011 to arrive at district level and all-sites-pooled estimates. Site-specific prevalence of any of seven NDDs in 2-<6 year olds ranged from 2.9% (95% CI 1.6-5.5) to 18.7% (95% CI 14.7-23.6), and for any of nine NDDs in the 6-9-year-old children, from 6.5% (95% CI 4.6-9.1) to 18.5% (95% CI 15.3-22.3). Two or more NDDs were present in 0.4% (95% CI 0.1-1.7) to 4.3% (95% CI 2.2-8.2) in the younger age category and 0.7% (95% CI 0.2-2.0) to 5.3% (95% CI 3.3-8.2) in the older age category. All-site-pooled estimates for NDDs were 9.2% (95% CI 7.5-11.2) and 13.6% (95% CI 11.3-16.2) in children of 2-<6 and 6-9 year age categories, respectively, without significant difference according to gender, rural/urban residence, or religion; almost one-fifth of these children had more than one NDD. The pooled estimates for prevalence increased by up to three percentage points when these were adjusted for national rates of stunting or low birth weight (LBW). HI, ID, speech and language disorders, Epi, and LDs were the common NDDs across sites. Upon risk modelling, noninstitutional delivery, history of perinatal asphyxia, neonatal illness, postnatal neurological/brain infections, stunting, LBW/prematurity, and older age category (6-9 year) were significantly associated with NDDs. The study sample was underrepresentative of stunting and LBW and had a 15.6% refusal. These factors could be contributing to underestimation of the true NDD burden in our population. CONCLUSIONS: The study identifies NDDs in children aged 2-9 years as a significant public health burden for India. HI was higher than and ASD prevalence comparable to the published global literature. Most risk factors of NDDs were modifiable and amenable to public health interventions

A DWT and SVM based method for rolling element bearing fault diagnosis and its comparison with Artificial Neural Networks

A classification technique using Support Vector Machine (SVM) classifier for detection of rolling element bearing fault is presented here.  The SVM was fed from features that were extracted from of vibration signals obtained from experimental setup consisting of rotating driveline that was mounted on rolling element bearings which were run in normal and with artificially faults induced conditions. The time-domain vibration signals were divided into 40 segments and simple features such as peaks in time domain and spectrum along with statistical features such as standard deviation, skewness, kurtosis etc. were extracted. Effectiveness of SVM classifier was compared with the performance of Artificial Neural Network (ANN) classifier and it was found that the performance of SVM classifier is superior to that of ANN. The effect of pre-processing of the vibration signal by Discreet Wavelet Transform (DWT) prior to feature extraction is also studied and it is shown that pre-processing of vibration signal with DWT enhances the effectiveness of both ANN and SVM classifiers. It has been demonstrated from experiment results that performance of SVM classifier is better than ANN in detection of bearing condition and pre-processing the vibration signal with DWT improves the performance of SVM classifier

A Hybrid Genetic Algorithm and Back-Propagation Classifier for Gearbox Fault Diagnosis

An Artificial Neural Network (ANN) classifier trained by a hybrid GA-BP method for diagnosis of gear faults is presented here that can be incorporated in an online fault diagnostic system of vital gearboxes. The distinctive features obtained from vibration signals of a running gearbox; that was operated in normal and with faults induced conditions were used to feed the GA-BP hybrid classifier. Time domain vibration signals were divided in 40segments. From each segment features such as magnitude of peaks in time domain and spectrum along with statistical features such as central moments and standard deviations were extracted to feed the classifier. Based on the experimental results it was shown that the GA-BP hybrid classifier can successfully identify gear condition. It was also shown that the network trained by GA-BP hybrid method performs much better than ANN that is trained by standard BP or GA individually. Further, it was also shown that if prior to extraction of features; the vibration signals are pre-processed by Discrete Wavelet Transform (DWT) then efficacy of the GA-BP hybrid is significantly enhanced