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Integrase strand transfer inhibitors (INSTIs) based antiretroviral therapy (ART) is currently used as first-line regimen to treat HIV infection. Despite its high efficacy and barrier to resistance, ART-associated neuropsychiatric adverse effects remain a major concern. Recent studies have identified a potential interaction between the INSTI, dolutegravir (DTG), and folate transport pathways at the placental barrier. We hypothesized that such interactions could also occur at the two major blood-brain interfaces: blood-cerebrospinal fluid barrier (BCSFB) and blood-brain barrier (BBB). To address this question, we evaluated the effect of two INSTIs, DTG and bictegravir (BTG), on folate transporters and receptor expression at the mouse BCSFB and the BBB in vitro, ex vivo and in vivo. We demonstrated that DTG but not BTG significantly downregulated the mRNA and/or protein expression of folate transporters (RFC/SLC19A1, PCFT/SLC46A1) in human and mouse BBB models in vitro, and mouse brain capillaries ex vivo. Our in vivo study further revealed a significant downregulation in Slc19a1 and Slc46a1 mRNA expression at the BCSFB and the BBB following a 14-day DTG oral treatment in C57BL/6 mice. However, despite the observed downregulatory effect of DTG in folate transporters/receptor at both brain barriers, a 14-day oral treatment of DTG-based ART did not significantly alter the brain folate level in animals. Interestingly, DTG treatment robustly elevated the mRNA and/or protein expression of pro-inflammatory cytokines and chemokines (Cxcl1, Cxcl2, Cxcl3, Il6, Il23, Il12) in primary cultures of mouse brain microvascular endothelial cells (BBB). DTG oral treatment also significantly upregulated proinflammatory cytokines and chemokine (Il6, Il1β, Tnfα, Ccl2) at the BCSFB in mice. We additionally observed a downregulated mRNA expression of drug efflux transporters (Abcc1, Abcc4, and Abcb1a) and tight junction protein (Cldn3) at the CP isolated from mice treated with DTG. Despite the structural similarities, BTG only elicited minor effects on the markers of interest at both the BBB and BCSFB. In summary, our current data demonstrates that DTG but not BTG strongly induced inflammatory responses in a rodent BBB and BCSFB model. Together, these data provide valuable insights into the mechanism of DTG-induced brain toxicity, which may contribute to the pathogenesis of DTG-associated neuropsychiatric adverse effect., (© 2024 The Author(s). The FASEB Journal published by Wiley Periodicals LLC on behalf of Federation of American Societies for Experimental Biology.)

In cardiovascular homeostasis thyroid hormone plays an important role. We planned to study the changes in thyroid hormone profile in acute coronary syndrome patients admitted in the coronary care unit and compare them between two groups: unstable angina/non-ST elevated Myocardial infarction (UA/NSTEMI) and ST elevated Myocardial infarction (STEMI). This study was a hospital based descriptive cross sectional study which was conducted from 01 March 2018 to 01 February 2019 in Coronary Care Unit of Bangladesh Medical College Hospital and laboratory tests were done in Microbiology Department of Bangladesh Medical College, Dhaka, Bangladesh. Eighty three cases of acute coronary syndromes were taken for the study. Troponin-I was measured as cardiac marker, Electrocardiogram, Complete blood count, blood glucose level, Blood urea, serum creatinine, serum electrolytes, Fasting lipid profile, Thyroid profile, Echocardiography 2D were done. Most of the respondents were distributed in age group 46-60 years where 34(64.15%) male and 19(35.85%) female. Out of 83 Acute Coronary Syndrome (ACS) patients, 27(32.53%) hypertensive, 22(26.50%) diabetic and 16(19.27%) were Chronic kidney disease (CKD). Abnormal lipid profile was present in 30(43.47%) patients. Among total 52 male and 31 female 9(17.30%) male and 6(19.35%) female had abnormal thyroid function. We further elaborated abnormal thyroid function tests in STEMI group and UA/Non STEMI group of ACS patients. We found 10 patients in STEMI group and 5 patients in UA/Non STEMI group with abnormal thyroid function 29.41% and 10.20% respectively which was not statistically significant (p=0.025). This study depicts abnormality in thyroid hormone profile in 18.07% patients of ACS. Abnormal thyroid function increases risk of coronary artery disease. TSH level of ACS patients on hospital admission could be helpful to evaluate further prognosis of the disease.

DNA-binding and RNA-binding proteins are essential to an organism's normal life cycle. These proteins have diverse functions in various biological processes. DNA-binding proteins are crucial for DNA replication, transcription, repair, packaging, and gene expression. Likewise, RNA-binding proteins are essential for the post-transcriptional control of RNAs and RNA metabolism. Identifying DNA- and RNA-binding residue is essential for biological research and understanding the pathogenesis of many diseases. However, most DNA-binding and RNA-binding proteins still need to be discovered. This research explored various properties of the protein sequences, such as amino acid composition type, Position-Specific Scoring Matrix (PSSM) values of amino acids, Hidden Markov model (HMM) profiles, physiochemical properties, structural properties, torsion angles, and disorder regions. We utilized a sliding window technique to extract more information from a target residue's neighbors. We proposed an optimized Light Gradient Boosting Machine (LightGBM) method, named DRBpred, to predict DNA-binding and RNA-binding residues from the protein sequence. DRBpred shows an improvement of 112.00 %, 33.33 %, and 6.49 % for the DNA-binding test set compared to the state-of-the-art method. It shows an improvement of 112.50 %, 16.67 %, and 7.46 % for the RNA-binding test set regarding Sensitivity, Mathews Correlation Coefficient (MCC), and AUC metric., Competing Interests: Declaration of competing interest There is no conflict of interest with any of the authors or the suggested reviewers (if any)., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Background: Folic acid supplementation during the periconceptional period reduces the risk of neural tube defects in infants, but concern over chronic folic acid exposure remains. An improved understanding of folate absorption may clarify potential risks. Folate transporters have been characterized in the small intestine, but less so in the colon of healthy, free-living humans. The impact of folic acid fortification or supplementation on regulation of these transporters along the intestinal tract is unknown., Objective: The objective was to characterize expression of folate transporters/receptor (FT/R) and folate hydrolase, glutamate carboxypeptidase II (GCPII), from the terminal ileum and throughout the colon of adults and assess the impact of supplemental folic acid., Methods: In this 16-wk open-labeled randomized clinical trial, adults consumed a low folic acid-containing diet, a folate-free multivitamin, and either a 400 μg folic acid supplement or no folic acid supplement. Dietary intakes and blood were assessed at baseline, 8 wk, and 16 wk (time of colonoscopy). Messenger RNA (mRNA) expression and protein expression of FT/R and GCPII were assessed in the terminal ileum, cecum, and ascending and descending colon., Results: Among 24 randomly assigned subjects, no differences in dietary folate intake or blood folate were observed at baseline. Mean ± SD red blood cell folate at 16 wk was 1765 ± 426 and 911 ± 242 nmol/L in the 400 and 0 μg folic acid group, respectively (P < 0.0001). Reduced folate carrier, proton-coupled folate transporter, and folate-receptor alpha expression were detected in the terminal ileum and colon, as were efflux transporters of breast cancer resistance protein and multidrug resistance protein-3. Other than a higher mRNA expression of FR-alpha and GCPII in the 400 μg supplement group in the ascending colon, no treatment differences were observed (P < 0.02)., Conclusions: Folate transporters are present throughout the terminal ileum and colon; there is little evidence that a low dose of folic acid supplementation affects colonic absorption. This trial was registered at clinicaltrials.gov as NCT03421483., (Copyright © 2023 American Society for Nutrition. Published by Elsevier Inc. All rights reserved.)

Peroxisome proliferator-activated receptors [PPARs; PPARα, PPARβ/δ (also known as PPARδ), and PPARγ] widely recognized for their important role in glucose/lipid homeostasis, have recently received significant attention due to their additional anti-inflammatory and neuroprotective effects. Several newly developed PPAR agonists have shown high selectivity for specific PPAR isoforms in vitro and in vivo, offering the potential to achieve desired therapeutic outcomes while reducing the risk of adverse effects. In this review, we discuss the latest preclinical and clinical studies of the activation of PPARs by synthetic, natural, and isoform-specific (full, partial, and dual) agonists for the treatment of neuroinflammatory diseases, including HIV-associated neurocognitive disorders (HAND), Alzheimer's disease (AD), Parkinson's disease (PD), multiple sclerosis (MS), and cerebral ischemia., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Protein molecules show varying degrees of flexibility throughout their three-dimensional structures. The flexibility is determined by the fluctuations in torsion angles, specifically phi (φ) and psi (ψ), which define the protein backbone. These angle fluctuations are derived from variations in backbone torsion angles observed in different models. By analyzing the fluctuations in Cartesian coordinate space, we can understand the structural flexibility of proteins. Predicting torsion angle fluctuations is valuable for determining protein function and structure when these angles act as constraints. In this study, a machine learning method called TAFPred is developed to predict torsion angle fluctuations using protein sequences directly. The method incorporates various features, such as disorder probability, position-specific scoring matrix profiles, secondary structure probabilities, and more. TAFPred, employing an optimized Light Gradient Boosting Machine Regressor (LightGBM), achieved high accuracy with correlation coefficients of 0.746 and 0.737 and mean absolute errors of 0.114 and 0.123 for the φ and ψ angles, respectively. Compared to the state-of-the-art method, TAFPred demonstrated significant improvements of 10.08% in MAE and 24.83% in PCC for the phi angle and 9.93% in MAE, and 22.37% in PCC for the psi angle.

SARS-CoV-2-mediated interactions with drug metabolizing enzymes and membrane transporters (DMETs) in different tissues, especially lung, the main affected organ may limit the clinical efficacy and safety profile of promising COVID-19 drugs. Herein, we investigated whether SARS-CoV-2 infection could dysregulate the expression of 25 clinically relevant DMETs in Vero E6 cells and postmortem lung tissues from COVID-19 patients. Also, we assessed the role of 2 inflammatory and 4 regulatory proteins in modulating the dysregulation of DMETs in human lung tissues. We showed for the first time that SARS-CoV-2 infection dysregulates CYP3A4 and UGT1A1 at the mRNA level, as well as P-gp and MRP1 at the protein level, in Vero E6 cells and postmortem human lung tissues, respectively. We observed that at the cellular level, DMETs could potentially be dysregulated by SARS-CoV-2-associated inflammatory response and lung injury. We uncovered the pulmonary cellular localization of CYP1A2, CYP2C8, CYP2C9, and CYP2D6, as well as ENT1 and ENT2 in human lung tissues, and observed that the presence of inflammatory cells is the major driving force for the discrepancy in the localization of DMETs between COVID-19 and control human lung tissues. Because alveolar epithelial cells and lymphocytes are both sites of SARS-CoV-2 infection and localization of DMETs, we recommend further investigation of the pulmonary pharmacokinetic profile of current COVID-19 drug dosing regimen to improve clinical outcomes., Competing Interests: CN was a former employee of Gilead Sciences and was involved in the development of remdesivir. CN was employed by OneDrug. MK and MP were employed by Ontario Forensic Pathology Service. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Nwabufo, Hoque, Yip, Khara, Mubareka, Pollanen and Bendayan.)

Motivation: Biological processes are regulated by underlying genes and their interactions that form gene regulatory networks (GRNs). Dysregulation of these GRNs can cause complex diseases such as cancer, Alzheimer's and diabetes. Hence, accurate GRN inference is critical for elucidating gene function, allowing for the faster identification and prioritization of candidate genes for functional investigation. Several statistical and machine learning-based methods have been developed to infer GRNs based on biological and synthetic datasets. Here, we developed a method named AGRN that infers GRNs by employing an ensemble of machine learning algorithms., Results: From the idea that a single method may not perform well on all datasets, we calculate the gene importance scores using three machine learning methods-random forest, extra tree and support vector regressors. We calculate the importance scores from Shapley Additive Explanations, a recently published method to explain machine learning models. We have found that the importance scores from Shapley values perform better than the traditional importance scoring methods based on almost all the benchmark datasets. We have analyzed the performance of AGRN using the datasets from the DREAM4 and DREAM5 challenges for GRN inference. The proposed method, AGRN-an ensemble machine learning method with Shapley values, outperforms the existing methods both in the DREAM4 and DREAM5 datasets. With improved accuracy, we believe that AGRN inferred GRNs would enhance our mechanistic understanding of biological processes in health and disease., Availabilityand Implementation: https://github.com/DuaaAlawad/AGRN., Supplementary Information: Supplementary data are available at Bioinformatics online., (© The Author(s) 2023. Published by Oxford University Press.)

Background: Folates are a family of B9 vitamins that serve as one-carbon donors critical to biosynthetic processes required for the development and function of the central nervous system (CNS) in mammals. Folate transport is mediated by three highly specific systems: (1) folate receptor alpha (FRα; FOLR1/Folr1), (2) the reduced folate-carrier (RFC; SLC19A1/Slc19a1) and (3) the proton-coupled folate transporter (PCFT; SLC46A1/Slc46a1). Folate transport into and out of the CNS occurs at the blood-cerebrospinal fluid barrier (BCSFB), mediated by FRα and PCFT. Impairment of folate transport at the BCSFB results in cerebral folate deficiency in infants characterized by severe neurological deficiencies and seizures. In contrast to the BCSFB, CNS folate transport at other brain barriers and brain parenchymal cells has not been extensively investigated. The aim of this study is to characterize folate transport systems in the murine CNS at several known barriers encompassing the BCSFB, arachnoid barrier (AB), blood-brain barrier (BBB) and parenchymal cells (astrocytes, microglia, neurons)., Methods: Applying immunohistochemistry, localization of folate transport systems (RFC, PCFT, FRα) was examined at CNS barriers and parenchymal sites in wildtype (C57BL6/N) mice. Subcellular localization of the folate transport systems was further assessed in an in vitro model of the mouse AB. Gene and protein expression was analyzed in several in vitro models of brain barriers and parenchyma by qPCR and western blot analysis., Results: RFC, PCFT, and FRα expression was localized within the BCSFB and BBB consistent with previous reports. Only RFC and PCFT expression was detected at the AB. Varied levels of RFC and PCFT expression were detected in neuronal and glial cells., Conclusions: Localization of RFC and PCFT within the AB, described here for the first time, suggest that AB may contribute to folate transport between the peripheral circulation and the CSF. RFC and PCFT expression observed in astrocytes and microglia is consistent with the role that one or both of these transporters may play in delivering folates into cells within brain parenchyma. These studies provide insights into mechanisms of folate transport in the CNS and may enhance our understanding of the critical role folates play in neurodevelopment and in the development of novel treatment strategies for disorders of brain folate deficiency due to impaired transporter function., (© 2022. The Author(s).)

A visible-light organophotoredox-catalyzed sulfurization of alkenes and alkynes with aromatic and heteroaromatic thiols using eco-friendly air (O 2 ) as the sole oxidant has been demonstrated. The established method delivers a novel, benign, and metal-free strategy for the difunctionalization of alkenes and alkynes using organophotoredox catalyst Eosin Y. The selective and controlled synthetic approach shows good substrate generality to afford sulfoxides, β-hydroxysulfoxides, and β-keto sulfides in high yield and excellent regioselectivity.

The study was aimed to assess the psychological aspects and relevant factors of the health-care workers (HCWs) working in COVID 19 pandemic condition in Bangladesh. This online cross-sectional survey was conducted from different tertiary, secondary and primary hospitals in Bangladesh. Eligible 638 HCWs who were directly involved in the caring of confirmed or suspected COVID-19 patients were recruited in this study. The mental health was assessed by the Patient Health Questionnare-9 (PHQ-9), Generalized Anxiety Disorder-7 (GAD-7) and Athens Insomnia Scale (AIS). High frequency of depression 536(84.0%), anxiety 386(60.5%) and insomnia 302(47.3%) was found among the HCWs, which were significantly higher in physicians (p<0.001) than nurses. Moderate to severe depression was significantly higher in female, whereas minimal to mild depression was significant in male HCWs (p=0.014). Symptoms of depression (p<0.001), anxiety (p<0.001) and insomnia (p=0.004) were significantly higher among the HCWs of primary and secondary compared to the tertiary level. The HCWs developed psychological trauma due to family health (45.3%) and contagious disease property (66.6%). After adjusting confounders, multivariable logistic regression analysis showed that physicians and HCWs of secondary hospital had significant symptoms of severe depression (OR=2.95, 95% CI=0.50-17.24; p<0.001), anxiety (OR=2.64, 95% CI=0.80-8.72; p<0.001) and insomnia (OR=2.67, 95% CI=1.23-5.84; p=0.018); whereas female HCWs had more risk of developing symptoms of severe insomnia (OR= 1.84; 95% CI=1.23-2.75; p=0.003). High rate of depression, anxiety and insomnia was found among HCWs working in the COVID-19 pandemic condition in this survey.

Completing the genotype-to-phenotype map requires rigorous measurement of the entire multivariate organismal phenotype. However, phenotyping on a large scale is not feasible for many kinds of traits, resulting in missing data that can also cause problems for comparative analyses and the assessment of evolutionary trends across species. Measuring the multivariate performance phenotype is especially logistically challenging, and our ability to predict several performance traits from a given morphology is consequently poor. We developed a machine learning model to accurately estimate multivariate performance data from morphology alone by training it on a dataset containing performance and morphology data from 68 lizard species. Our final, stacked model predicts missing performance data accurately at the level of the individual from simple morphological measures. This model performed exceptionally well, even for performance traits that were missing values for >90% of the sampled individuals. Furthermore, incorporating phylogeny did not improve model fit, indicating that the phenotypic data alone preserved sufficient information to predict the performance based on morphological information. This approach can both significantly increase our understanding of performance evolution and act as a bridge to incorporate performance into future work on phenomics., Competing Interests: The authors have declared that no competing interests exist.

Background: Due to the critical role of folates in neurodevelopment, it is important to understand potential interactions between anti-HIV drugs used during pregnancy, and folate delivery pathways in the placenta. This study investigates the effect of dolutegravir (DTG) exposure on the functional expression of the reduced folate carrier (RFC), proton-coupled folate transporter (PCFT), and folate receptor-α (FRα) in the placenta., Methods: Human placental cell lines, human placental explants, and a pregnant mouse model treated with clinically relevant concentrations of DTG were used. Gene and protein expression were assessed by qPCR, immunoblot and immunohistochemical assays. Folate transport function was measured by applying radioisotope-based transport assays., Findings: In placental cells, clinically relevant DTG exposure for 3h or 6h was associated with a modest but significant reduction in the expression of RFC and PCFT both at the mRNA and protein levels, as well as decreased uptake of RFC and PCFT substrates [ 3 H]-methotrexate and [ 3 H]-folic acid, respectively. In pregnant mice, DTG administration was associated with an increase in both placental RFC and PCFT mRNA expression, accompanied by a decrease in placental FRα mRNA under folate-deficient dietary conditions., Interpretation: These findings demonstrate a potential interaction between DTG and folate transport pathways in the placenta, particularly in vivo, under folate deficient conditions, potentially impacting folate delivery to the foetus in the context of DTG-based ART during pregnancy., Funding: Funded by Ontario HIV Treatment Network, grant #506657; and Eunice Kennedy Shriver National Institute of Child Health & Human Development of the National Institutes of Health, award #R01HD104553., Competing Interests: Declaration of interests LS received personal support for participating in a ViiV organized Think Tank. The authors have no further competing interests related to this study., (Copyright © 2021 The Authors. Published by Elsevier B.V. All rights reserved.)

Motivation: Transposable Elements (TEs) or jumping genes are DNA sequences that have an intrinsic capability to move within a host genome from one genomic location to another. Studies show that the presence of a TE within or adjacent to a functional gene may alter its expression. TEs can also cause an increase in the rate of mutation and can even mediate duplications and large insertions and deletions in the genome, promoting gross genetic rearrangements. The proper classification of identified jumping genes is important for analyzing their genetic and evolutionary effects. An effective classifier, which can explain the role of TEs in germline and somatic evolution more accurately, is needed. In this study, we examine the performance of a variety of machine learning (ML) techniques and propose a robust method, ClassifyTE, for the hierarchical classification of TEs with high accuracy, using a stacking-based ML method., Results: We propose a stacking-based approach for the hierarchical classification of TEs. When trained on three different benchmark datasets, our proposed system achieved 4%, 10.68% and 10.13% average percentage improvement (using the hF measure) compared to several state-of-the-art methods. We developed an end-to-end automated hierarchical classification tool based on the proposed approach, ClassifyTE, to classify TEs up to the super-family level. We further evaluated our method on a new TE library generated by a homology-based classification method and found relatively high concordance at higher taxonomic levels. Thus, ClassifyTE paves the way for a more accurate analysis of the role of TEs., Availability and Implementation: The source code and data are available at https://github.com/manisa/ClassifyTE., Supplementary Information: Supplementary data are available at Bioinformatics online., (© The Author(s) 2021. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

The protein disulfide bond is a covalent bond that forms during post-translational modification by the oxidation of a pair of cysteines. In protein, the disulfide bond is the most frequent covalent link between amino acids after the peptide bond. It plays a significant role in three-dimensional (3D) ab initio protein structure prediction (aiPSP), stabilizing protein conformation, post-translational modification, and protein folding. In aiPSP, the location of disulfide bonds can strongly reduce the conformational space searching by imposing geometrical constraints. Existing experimental techniques for the determination of disulfide bonds are time-consuming and expensive. Thus, developing sequence-based computational methods for disulfide bond prediction becomes indispensable. This study proposed a stacking-based machine learning approach for disulfide bond prediction (diSBPred). Various useful sequence and structure-based features are extracted for effective training, including conservation profile, residue solvent accessibility, torsion angle flexibility, disorder probability, a sequential distance between cysteines, and more. The prediction of disulfide bonds is carried out in two stages: first, individual cysteines are predicted as either bonding or non-bonding; second, the cysteine-pairs are predicted as either bonding or non-bonding by including the results from cysteine bonding prediction as a feature. The examination of the relevance of the features employed in this study and the features utilized in the existing nearest neighbor algorithm (NNA) method shows that the features used in this study improve about 7.39 % in jackknife validation balanced accuracy. Moreover, for individual cysteine bonding prediction and cysteine-pair bonding prediction, diSBPred provides a 10-fold cross-validation balanced accuracy of 82.29 % and 94.20 %, respectively. Altogether, our predictor achieves an improvement of 43.25 % based on balanced accuracy compared to the existing NNA based approach. Thus, diSBPred can be utilized to annotate the cysteine bonding residues of protein sequences whose structures are unknown as well as improve the accuracy of the aiPSP method, which can further aid in experimental studies of the disulfide bond and structure determination., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Objectives: ATP-binding cassette (ABC) drug efflux transporters and drug metabolic enzymes could reduce antiretroviral concentrations in HIV target cells. The testis has been demonstrated to be a sanctuary site, displaying suboptimal antiretroviral concentrations and persistent HIV infection. Therefore, we compared the expression and function of ABC transporters and metabolic enzymes in CD4 and CD8 T cells isolated from human testis and peripheral blood mononuclear cells (PBMCs), and assessed their expression in circulating naive and memory CD4 T-cell phenotypes., Design: Testicular tissue and blood were collected from 15 uninfected donors undergoing gender affirmation surgery. Testicular interstitial cells were isolated by enzymatic digestion, whereas PBMCs were isolated from blood by density gradient centrifugation. The expression and/or function of ABC transporters and metabolic enzymes were examined in blood and testicular T-cell subsets by flow cytometry., Results: ABC transporters (P-gp, BCRP, MRP1) and metabolic enzymes (CYP3A4, UGT1A1) were expressed in testicular and circulating CD4 and CD8 T cells, as well as in circulating naive, central, transitional, and effector memory T-cell phenotypes. MRP1 demonstrated lower frequencies in T cells from testis compared with PBMCs, as well as in circulating naive T cells compared with the memory T-cell phenotypes. Functional activity of P-gp and BCRP was detected in T-cell subsets from testis and PBMCs., Conclusion: Our findings demonstrate for the first time that antiretroviral drug efflux transporters and metabolic enzymes are functionally expressed in T-cell subsets infiltrating the human testis. These transporters and enzymes can reduce antiretroviral intracellular concentrations, potentially contributing to residual HIV replication in the testis, and negatively impact HIV cure strategies.

Folates are important for neurodevelopment and cognitive function. Folate transport across biological membranes is mediated by three major pathways: folate receptor alpha (FRα), proton-coupled folate transporter (PCFT), and reduced folate carrier (RFC). Brain folate transport primarily occurs at the choroid plexus through FRα and PCFT; inactivation of these transport systems results in suboptimal folate levels in the cerebrospinal fluid (CSF) causing childhood neurological disorders. Our group has reported that upregulation of RFC at the blood-brain barrier (BBB) through interactions with specific transcription factors, that is, vitamin D receptor (VDR) could increase brain folate delivery. This study investigates the role of nuclear respiratory factor 1 (NRF-1) in the regulation of RFC at the BBB. Activation of NRF-1/PGC-1α signaling through treatment with its specific ligand, pyrroloquinoline quinone (PQQ), significantly induced RFC expression and transport activity in hCMEC/D3 cells. In contrast, transfection with NRF-1 or PGC-1α targeting siRNA downregulated RFC functional expression in the same cell system. Applying chromatin immunoprecipitation (ChIP) assay, we further demonstrated that PQQ treatment increased NRF-1 binding to putative NRF-1 binding sites within the SLC19A1 promoter, which encodes for RFC. Additionally, in vivo treatment of wild type mice with PQQ-induced RFC expression in isolated mouse brain capillaries. Together, these findings demonstrate that NRF-1/PGC-1α activation by PQQ upregulates RFC functional expression at the BBB and could potentially enhance brain folate uptake., (© 2020 Federation of American Societies for Experimental Biology.)

HIV associated neurocognitive disorders (HAND) are the spectrum of cognitive impairments present in patients infected with human immunodeficiency virus type 1 (HIV-1). The number of patients affected with HAND ranges from 30 to 50% of HIV infected individuals and although the development of combinational antiretroviral therapy (cART) has improved longevity, HAND continues to pose a significant clinical problem as the current standard of care does not alleviate or prevent HAND symptoms. At present, the pathological mechanisms contributing to HAND remain unclear, but evidence suggests that it stems from neuronal injury due to chronic release of neurotoxins, chemokines, viral proteins, and proinflammatory cytokines secreted by HIV-1 activated microglia, macrophages and astrocytes in the central nervous system (CNS). Furthermore, the blood-brain barrier (BBB) not only serves as a route for HIV-1 entry into the brain but also prevents cART therapy from reaching HIV-1 brain reservoirs, and therefore could play an important role in HAND. The goal of this review is to discuss the current data on the epidemiology, pathology and research models of HAND as well as address the potential pharmacological treatment approaches that are being investigated.

Carbohydrate-binding proteins play vital roles in many important biological processes. The study of these protein-carbohydrate interactions, at residue level, is useful in treating many critical diseases. Analyzing the local sequential environments of the binding and non-binding regions to predict the protein-carbohydrate binding sites is one of the challenging problems in molecular and computational biology. Existing experimental methods for identifying protein-carbohydrate binding sites are laborious and expensive. Thus, prediction of such binding sites, directly from sequences, using computational methods, can be useful to fast annotate the binding sites and guide the experimental process. Because the number of carbohydrate-binding residues is significantly lower than the number of non-carbohydrate-binding residues, most of the methods developed for the prediction of protein-carbohydrate binding sites are biased towards over predicting the negative class (or non-carbohydrate-binding). Here, we propose a balanced predictor, called StackCBPred, which utilizes features, extracted from evolution-driven sequence profile, called the position-specific scoring matrix (PSSM) and several predicted structural properties of amino acids to effectively train a Stacking-based machine learning method for the accurate prediction of protein-carbohydrate binding sites (https://bmll.cs.uno.edu/)., (Published by Elsevier Ltd.)

Folates are critical for central nervous system function. Folate transport is mediated by 3 major pathways, reduced folate carrier (RFC), proton-coupled folate transporter (PCFT), and folate receptor alpha (FRα/Folr1), known to be regulated by ligand-activated nuclear receptors. Cerebral folate delivery primarily occurs at the choroid plexus through FRα and PCFT; inactivation of these transport systems can result in very low folate levels in the cerebrospinal fluid causing childhood neurodegenerative disorders. These disorders have devastating effects in young children, and current therapeutic approaches are not sufficiently effective. Our group has previously reported in vitro that functional expression of RFC at the blood-brain barrier (BBB) and its upregulation by the vitamin D nuclear receptor (VDR) could provide an alternative route for brain folate uptake. In this study, we further demonstrated in vivo, using Folr1 knockout (KO) mice, that loss of FRα led to a substantial decrease of folate delivery to the brain and that pretreatment of Folr1 KO mice with the VDR activating ligand, calcitriol (1,25-dihydroxyvitamin D 3 ), resulted in over a 6-fold increase in [ 13 C 5 ]-5-formyltetrahydrofolate ([ 13 C 5 ]-5-formylTHF) concentration in brain tissues, with levels comparable to wild-type animals. Brain-to-plasma concentration ratio of [ 13 C 5 ]-5-formylTHF was also significantly higher in calcitriol-treated Folr1 KO mice (15-fold), indicating a remarkable enhancement in brain folate delivery. These findings demonstrate that augmenting RFC functional expression at the BBB could effectively compensate for the loss of Folr1-mediated folate uptake at the choroid plexus, providing a therapeutic approach for neurometabolic disorders caused by defective brain folate transport., Competing Interests: The authors declare no conflict of interest.

Motivation: Identification of DNA-binding proteins from only sequence information is one of the most challenging problems in the field of genome annotation. DNA-binding proteins play an important role in various biological processes such as DNA replication, repair, transcription and splicing. Existing experimental techniques for identifying DNA-binding proteins are time-consuming and expensive. Thus, prediction of DNA-binding proteins from sequences alone using computational methods can be useful to quickly annotate and guide the experimental process. Most of the methods developed for predicting DNA-binding proteins use the information from the evolutionary profile, called the position-specific scoring matrix (PSSM) profile, alone and the accuracies of such methods have been limited. Here, we propose a method, called StackDPPred, which utilizes features extracted from PSSM and residue specific contact-energy to help train a stacking based machine learning method for the effective prediction of DNA-binding proteins., Results: Based on benchmark sequences of 1063 (518 DNA-binding and 545 non DNA-binding) proteins and using jackknife validation, StackDPPred achieved an ACC of 89.96%, MCC of 0.799 and AUC of 94.50%. This outcome outperforms several state-of-the-art approaches. Furthermore, when tested on recently designed two independent test datasets, StackDPPred outperforms existing approaches consistently. The proposed StackDPPred can be used for effective prediction of DNA-binding proteins from sequence alone., Availability and Implementation: Online server is at http://bmll.cs.uno.edu/add and code-data is at http://cs.uno.edu/∼tamjid/Software/StackDPPred/code&#95;data.zip., Supplementary Information: Supplementary data are available at Bioinformatics online.

Supersecondary structure (SSS) refers to specific geometric arrangements of several secondary structure (SS) elements that are connected by loops. The SSS can provide useful information about the spatial structure and function of a protein. As such, the SSS is a bridge between the secondary structure and tertiary structure. In this chapter, we propose a stacking-based machine learning method for the prediction of two types of SSSs, namely, β-hairpins and β-α-β, from the protein sequence based on comprehensive feature encoding. To encode protein residues, we utilize key features such as solvent accessibility, conservation profile, half surface exposure, torsion angle fluctuation, disorder probabilities, and more. The usefulness of the proposed approach is assessed using a widely used threefold cross-validation technique. The obtained empirical result shows that the proposed approach is useful and prediction can be improved further.

Motivation: Machine learning plays a substantial role in bioscience owing to the explosive growth in sequence data and the challenging application of computational methods. Peptide-recognition domains (PRDs) are critical as they promote coupled-binding with short peptide-motifs of functional importance through transient interactions. It is challenging to build a reliable predictor of peptide-binding residue in proteins with diverse types of PRDs from protein sequence alone. On the other hand, it is vital to cope up with the sequencing speed and to broaden the scope of study., Results: In this paper, we propose a machine-learning-based tool, named PBRpredict, to predict residues in peptide-binding domains from protein sequence alone. To develop a generic predictor, we train the models on peptide-binding residues of diverse types of domains. As inputs to the models, we use a high-dimensional feature set of chemical, structural and evolutionary information extracted from protein sequence. We carefully investigate six different state-of-the-art classification algorithms for this application. Finally, we use the stacked generalization approach to non-linearly combine a set of complementary base-level learners using a meta-level learner which outperformed the winner-takes-all approach. The proposed predictor is found competitive based on statistical evaluation., Availability and Implementation: PBRpredict-Suite software: http://cs.uno.edu/~tamjid/Software/PBRpredict/pbrpredict-suite.zip., Supplementary Information: Supplementary data are available at Bioinformatics online.

Poor antiretroviral drug (ARV) penetration in the testes could be due, in part, to the presence of ATP-binding cassette (ABC) membrane-associated drug efflux transporters such as P-glycoprotein (P-gp), breast cancer resistance protein (BCRP), and multidrug resistance-associated proteins (MRPs) expressed at the blood-testis barrier (BTB). The functional expression of these transporters is known to be regulated by ligand-activated nuclear receptors pregnane X receptor (PXR) and constitutive androstane receptor (CAR) in various tissues. This study aimed to investigate in vitro and ex vivo the role of PXR and CAR in the regulation of ABC transporters at the BTB. Both PXR and CAR proteins were expressed in human testicular tissue and in mouse TM4 Sertoli cells (an in vitro cell line model of the BTB). In addition, we demonstrated an upregulation of P-gp, Bcrp, and Mrp4 mRNA and protein expression, after exposure to PXR or CAR ligands in TM4 cells. Small interfering RNA downregulation of PXR or CAR attenuated the expression of these transporters, suggesting the direct involvement of these nuclear receptors in regulating P-gp, Bcrp, and Mrp4 in this system. In an ex vivo study using freshly isolated mouse seminiferous tubules, we found that exposure to PXR or CAR ligands, including ARVs, significantly increased P-gp expression and function. Together, our data suggest that ABC transporters could be regulated at the BTB during chronic treatment with ARVs that can serve as ligands for PXR and CAR, which could in turn further limit testicular ARV concentrations., (Copyright © 2017 by The American Society for Pharmacology and Experimental Therapeutics.)

Folates are essential for brain development and function. Folate transport in mammalian tissues is mediated by three major folate transport systems, i.e., reduced folate carrier (RFC), proton-coupled folate transporter (PCFT), and folate receptor alpha (FRα), known to be regulated by ligand-activated nuclear receptors, such as vitamin D receptor (VDR). Folate uptake at the choroid plexus, which requires the actions of both FRα and PCFT, is critical to cerebral folate delivery. Inactivating FRα or PCFT mutations cause severe cerebral folate deficiency resulting in early childhood neurodegeneration. The objective of this study was to investigate the role of RFC in folate uptake at the level of the blood-brain barrier (BBB) and its potential regulation by VDR. We detected robust expression of RFC in different in vitro BBB model systems, particularly in immortalized cultures of human cerebral microvascular endothelial cells (hCMEC/D3) and isolated mouse brain capillaries. [ 3 H]-methotrexate uptake by hCMEC/D3 cells at pH 7.4 was inhibited by PT523 and pemetrexed, antifolates with high affinity for RFC. We also showed that activation of VDR through calcitriol (1,25-dihydroxyvitamin D 3 ) exposure up-regulates RFC mRNA and protein expression as well as function in hCMEC/D3 cells and isolated mouse brain capillaries. We further demonstrated that RFC expression could be down-regulated by VDR-targeting siRNA, further confirming the role of VDR in the direct regulation of this folate transporter. Together, these data suggest that augmenting RFC functional expression could constitute a novel strategy for enhancing brain folate delivery for the treatment of neurometabolic disorders caused by loss of FRα or PCFT function.

Background: Despite the use of combination antiretroviral therapy for the treatment of HIV-1 infection, cognitive impairments remain prevalent due to persistent viral replication and associated brain inflammation. Primary cellular targets of HIV-1 in the brain are macrophages, microglia, and to a certain extent astrocytes which in response to infection release inflammatory markers, viral proteins [i.e., glycoprotein 120 (gp120)] and exhibit impaired glutamate uptake. Peroxisome proliferator-activated receptors (PPARs) are members of the nuclear receptor superfamily of ligand-activated transcription factors. Compelling evidence suggests that PPARγ exerts anti-inflammatory properties in neurological disorders. The goal of this study was to examine the role of PPARγ in the context of HIV-1 ADA gp120-induced inflammation in vitro, in primary cultures of rat astrocytes and microglia, and in vivo, in a rodent model of HIV-1 ADA gp120-associated brain inflammation., Methods: Primary mixed cultures of rat astrocytes and microglia were treated with PPARγ agonists (rosiglitazone or pioglitazone) and exposed to HIV-1 ADA gp120. Inflammatory cytokines and indicator of oxidative stress response (TNFα, IL-1β, iNOS) were measured using qPCR, and glutamate transporter (GLT-1) was quantified by immunoblotting. In vivo, rats were administered an intracerebroventricular injection of HIV-1 ADA gp120 and an intraperitoneal injection of PPARγ agonist (rosiglitazone) or co-administration with PPARγ antagonist (GW9662). qPCR and immunoblotting analyses were applied to measure inflammatory markers, GLT-1 and PPARγ., Results: In primary mixed cultures of rat astrocytes and microglia, HIV-1 ADA gp120 exposure resulted in a significant elevation of inflammatory markers and a decrease in GLT-1 expression which were significantly attenuated with rosiglitazone or pioglitazone treatment. Similarly, in vivo, treatment with rosiglitazone reversed the gp120-mediated inflammatory response and downregulation of GLT-1. Furthermore, we demonstrated that the anti-inflammatory effects of PPARγ agonist rosiglitazone were mediated through inhibition of NF-κB., Conclusion: Our data demonstrate that gp120 can induce an inflammatory response and decrease expression of GLT-1 in the brain in vitro and in vivo. We have also successfully shown that these effects can be reversed by treatment with PPARγ agonists, rosiglitazone or pioglitazone. Together our data suggest that targeting PPARγ signaling may provide an option for preventing/treating HIV-associated brain inflammation.

A set of features computed from the primary amino acid sequence of proteins, is crucial in the process of inducing a machine learning model that is capable of accurately predicting three-dimensional protein structures. Solutions for existing protein structure prediction problems are in need of features that can capture the complexity of molecular level interactions. With a view to this, we propose a novel approach to estimate position specific estimated energy (PSEE) of a residue using contact energy and predicted relative solvent accessibility (RSA). Furthermore, we demonstrate PSEE can be reasonably estimated based on sequence information alone. PSEE is useful in identifying the structured as well as unstructured or, intrinsically disordered region of a protein by computing favorable and unfavorable energy respectively, characterized by appropriate threshold. The most intriguing finding, verified empirically, is the indication that the PSEE feature can effectively classify disorder versus ordered residues and can segregate different secondary structure type residues by computing the constituent energies. PSEE values for each amino acid strongly correlate with the hydrophobicity value of the corresponding amino acid. Further, PSEE can be used to detect the existence of critical binding regions that essentially undergo disorder-to-order transitions to perform crucial biological functions. Towards an application of disorder prediction using the PSEE feature, we have rigorously tested and found that a support vector machine model informed by a set of features including PSEE consistently outperforms a model with an identical set of features with PSEE removed. In addition, the new disorder predictor, DisPredict2, shows competitive performance in predicting protein disorder when compared with six existing disordered protein predictors., Competing Interests: The authors have declared that no competing interests exist.

Objectives: The testes are a potential viral sanctuary site for HIV-1 infection. Our study aims to provide insight into the expression and localization of key drug transporters and metabolic enzymes relevant to ART in this tissue compartment., Methods: We characterized gene and protein expression of 12 representative drug transporters and two metabolic enzymes in testicular tissue samples obtained from uninfected (n = 8) and virally suppressed HIV-1-infected subjects on ART (n = 5) and quantified antiretroviral drug concentrations in plasma and testicular tissues using LC/MS/MS from HIV-1-infected subjects., Results: Our data demonstrate that key ABC drug transporters (permeability glycoprotein, multidrug-resistance protein 1, 2 and 4, and breast cancer resistance protein), solute carrier transporters (organic anion transporting polypeptides 1B1 and 2B1, organic anion transporter 1, concentrative nucleoside transporter 1, equilibrative nucleoside transporter 2) and cytochrome P450 metabolic enzymes (CYP3A4 and CYP2D6) previously shown to interact with many commonly used antiretroviral drugs are expressed at the mRNA and protein level in the testes of both subject groups and localize primarily at the blood-testis barrier, with no significant differences between the two groups. Furthermore, we observed that PIs known to be substrates for ATP-binding cassette membrane transporters, displayed variable testicular tissue penetration, with darunavir concentrations falling below therapeutic values. In contrast, the NRTIs emtricitabine, lamivudine and tenofovir displayed favourable tissue penetration, reaching concentrations comparable to plasma levels. We also demonstrated that nuclear receptors, peroxisome proliferator-activated receptors α and γ exhibited higher gene expression in the testicular tissue compared with pregnane X receptor and constitutive androstane receptor, suggesting a potential regulatory pathway governing drug transporter and metabolic enzyme expression in this tissue compartment., Conclusions: Our data suggest the testes are a complex pharmacological compartment that can restrict the distribution of certain antiretroviral drugs and potentially contribute to HIV-1 persistence., (© The Author 2016. Published by Oxford University Press on behalf of the British Society for Antimicrobial Chemotherapy. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.)

The success of solving the protein folding and structure prediction problems in molecular and structural biology relies on an accurate energy function. With the rapid advancement in the computational biology and bioinformatics fields, there is a growing need of solving unknown fold and structure faster and thus an accurate energy function is indispensable. To address this need, we develop a new potential function, namely 3DIGARS3.0, which is a linearly weighted combination of 3DIGARS, mined accessible surface area (ASA) and ubiquitously computed Phi (uPhi) and Psi (uPsi) energies - optimized by a Genetic Algorithm (GA). We use a dataset of 4332 protein-structures to generate uPhi and uPsi based score libraries to be used within the core 3DIGARS method. The optimized weight of each component is obtained by applying Genetic Algorithm based optimization on three challenging decoy sets. The improved 3DIGARS3.0 outperformed state-of-the-art methods significantly based on a set of independent test datasets., (Published by Elsevier Ltd.)

This study investigated the effects of HIV-1 infection and antiretroviral therapy (ART) on the expression of intestinal drug efflux transporters, i.e., P-glycoprotein (Pgp), multidrug resistance-associated proteins (MRPs), and breast cancer resistance protein (BCRP), and metabolic enzymes, such as cytochrome P450s (CYPs), in the human upper intestinal tract. Intestinal biopsy specimens were obtained from HIV-negative healthy volunteers, ART-naive HIV-positive (HIV(+)) subjects, and HIV(+) subjects receiving ART (10 in each group). Intestinal tissue expression of drug transporters and metabolic enzymes was examined by microarray, real-time quantitative reverse transcription-PCR (qPCR), and immunohistochemistry analyses. Microarray analysis demonstrated significantly lower expression of CYP3A4 and ABCC2/MRP2 in the HIV(+) ART-naive group than in uninfected subjects. qPCR analysis confirmed significantly lower expression of ABCC2/MRP2 in ART-naive subjects than in the control group, while CYP3A4 and ABCG2/BCRP showed a trend toward decreased expression. Protein expression of MRP2 and BCRP was also significantly lower in the HIV(+) naive group than in the control group and was partially restored to baseline levels in HIV(+) subjects receiving ART. In contrast, gene and protein expression of ABCB1/Pgp was significantly increased in HIV(+) subjects on ART relative to HIV(+) ART-naive subjects. These data demonstrate that the expression of drug-metabolizing enzymes and efflux transporters is significantly altered in therapy-naive HIV(+) subjects and in those receiving ART. Since CYP3A4, Pgp, MRPs, and BCRP metabolize or transport many antiretroviral drugs, their altered expression with HIV infection may negatively impact drug pharmacokinetics in HIV(+) subjects. This has clinical implications when using data from healthy volunteers to guide ART., (Copyright © 2016, American Society for Microbiology. All Rights Reserved.)

Protein structure prediction is considered as one of the most challenging and computationally intractable combinatorial problem. Thus, the efficient modeling of convoluted search space, the clever use of energy functions, and more importantly, the use of effective sampling algorithms become crucial to address this problem. For protein structure modeling, an off-lattice model provides limited scopes to exercise and evaluate the algorithmic developments due to its astronomically large set of data-points. In contrast, an on-lattice model widens the scopes and permits studying the relatively larger proteins because of its finite set of data-points. In this work, we took the full advantage of an on-lattice model by using a face-centered-cube lattice that has the highest packing density with the maximum degree of freedom. We proposed a graded energy-strategically mixes the Miyazawa-Jernigan (MJ) energy with the hydrophobic-polar (HP) energy-based genetic algorithm (GA) for conformational search. In our application, we introduced a 2 × 2 HP energy guided macro-mutation operator within the GA to explore the best possible local changes exhaustively. Conversely, the 20 × 20 MJ energy model-the ultimate objective function of our GA that needs to be minimized-considers the impacts amongst the 20 different amino acids and allow searching the globally acceptable conformations. On a set of benchmark proteins, our proposed approach outperformed state-of-the-art approaches in terms of the free energy levels and the root-mean-square deviations., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

Breast cancer resistance protein (Bcrp/Abcg2) localized at the blood-brain barrier (BBB) limits permeability into the brain of many xenobiotics, including pharmacological agents. Peroxisome proliferator-activated receptor α (Pparα), a ligand-activated transcription factor, primarily involved in lipid metabolism, has been shown to regulate the functional expression of Bcrp in human cerebral microvascular endothelial cells (hCMEC/D3). The aim of this study was to investigate ex vivo and in vivo, the regulation of Bcrp by Pparα in an intact BBB. Ex vivo quantitative real-time PCR and immunoblot analyses showed significant up-regulation of Abcg2/Bcrp mRNA and protein levels in CD-1 mouse brain capillaries incubated with clofibrate, a Pparα ligand. Fluorescence-based transport assays in CD-1 and C57BL/6 brain capillaries showed that exposure to clofibrate significantly increased Bcrp transport activity. This increase was not observed in capillaries isolated from Pparα knockout mice. In vivo, we found: i) significant Bcrp protein up-regulation in clofibrate-dosed CD-1 and C57BL/6 capillary lysates, but no effect in Pparα knockout capillary lysates, and ii) significantly increased Bcrp transport activity in capillaries isolated from clofibrate-treated mice. These results demonstrate an increase in Bcrp functional expression by Pparα in brain capillaries, and suggest that Pparα is another nuclear receptor that can contribute to the regulation of membrane efflux transporters and drug permeability at the BBB. We propose the involvement of the following pathways in clofibrate-mediated induction of the drug transporter Abcg2/Bcrp mRNA, protein expression and function by the nuclear receptor Pparα, in mouse brain capillary endothelial cells. Upon activation with clofibrate (Pparα, ligand), Pparα complex translocates from the cytoplasm into the nucleus and further recruits coactivators and transcription machinery which induce the transcription of Abcg2 gene and ultimately results in upregulation of Bcrp protein expression and function. These findings have significant implications since Bcrp is known to play an important role at the BBB in preventing the permeability of several xenobiotics and drugs into the brain., (© 2015 International Society for Neurochemistry.)

Intrinsically disordered proteins or, regions perform important biological functions through their dynamic conformations during binding. Thus accurate identification of these disordered regions have significant implications in proper annotation of function, induced fold prediction and drug design to combat critical diseases. We introduce DisPredict, a disorder predictor that employs a single support vector machine with RBF kernel and novel features for reliable characterization of protein structure. DisPredict yields effective performance. In addition to 10-fold cross validation, training and testing of DisPredict was conducted with independent test datasets. The results were consistent with both the training and test error minimal. The use of multiple data sources, makes the predictor generic. The datasets used in developing the model include disordered regions of various length which are categorized as short and long having different compositions, different types of disorder, ranging from fully to partially disordered regions as well as completely ordered regions. Through comparison with other state of the art approaches and case studies, DisPredict is found to be a useful tool with competitive performance. DisPredict is available at https://github.com/tamjidul/DisPredict&#95;v1.0.

An accurate prediction of real value accessible surface area (ASA) from protein sequence alone has wide application in the field of bioinformatics and computational biology. ASA has been helpful in understanding the 3-dimensional structure and function of a protein, acting as high impact feature in secondary structure prediction, disorder prediction, binding region identification and fold recognition applications. To enhance and support broad applications of ASA, we have made an attempt to improve the prediction accuracy of absolute accessible surface area by developing a new predictor paradigm, namely REGAd(3)p, for real value prediction through classical Exact Regression with Regularization and polynomial kernel of degree 3 which was further optimized using Genetic Algorithm. ASA assisting effective energy function, motivated us to enhance the accuracy of predicted ASA for better energy function application. Our ASA prediction paradigm was trained and tested using a new benchmark dataset, proposed in this work, consisting of 1001 and 298 protein chains, respectively. We achieved maximum Pearson Correlation Coefficient (PCC) of 0.76 and 1.45% improved PCC when compared with existing top performing predictor, SPINE-X, in ASA prediction on independent test set. Furthermore, we modeled the error between actual and predicted ASA in terms of energy and combined this energy linearly with the energy function 3DIGARS which resulted in an effective energy function, namely 3DIGARS2.0, outperforming all the state-of-the-art energy functions. Based on Rosetta and Tasser decoy-sets 3DIGARS2.0 resulted 80.78%, 73.77%, 141.24%, 16.52%, and 32.32% improvement over DFIRE, RWplus, dDFIRE, GOAP and 3DIGARS respectively., (Published by Elsevier Ltd.)

The objectives of this study were to investigate raltegravir transport across several blood-tissue barrier models and the potential interactions with drug efflux transporters. Raltegravir uptake, accumulation, and permeability were evaluated in vitro in (i) P-glycoprotein (P-gp), breast cancer resistance protein (BCRP), multidrug resistance-associated protein 1 (MRP1), or MRP4-overexpressing MDA-MDR1 (P-gp), HEK-ABCG2, HeLa-MRP1, or HEK-MRP4 cells, respectively; (ii) cell culture systems of the human blood-brain (hCMEC/D3), mouse blood-testicular (TM4), and human blood-intestinal (Caco-2) barriers; and (iii) rat jejunum and ileum segments using an in situ single-pass intestinal perfusion model. [(3)H]Raltegravir accumulation by MDA-MDR1 (P-gp) and HEK-ABCG2-overexpressing cells was significantly enhanced in the presence of PSC833 {6-[(2S,4R,6E)-4-methyl-2-(methylamino)-3-oxo-6-octenoic acid]-7-L-valine-cyclosporine}, a P-gp inhibitor, or Ko143 [(3S,6S,12aS)-1,2,3,4,6,7,12,12a-octahydro-9-methoxy-6-(2-methylpropyl)-1,4-dioxopyrazino[1',2':1,6]pyrido[3,4-b]indole-3-propanoic acid 1,1-dimethylethyl ester], a BCRP inhibitor, suggesting the inhibition of a P-gp- or BCRP-mediated efflux process, respectively. Furthermore, [(3)H]raltegravir accumulation by human cerebral microvessel endothelial hCMEC/D3 and mouse Sertoli TM4 cells was significantly increased by PSC833 and Ko143. In human intestinal Caco-2 cells grown on Transwell filters, PSC833, but not Ko143, significantly decreased the [(3)H]raltegravir efflux ratios. In rat intestinal segments, [(3)H]raltegravir in situ permeability was significantly enhanced by the concurrent administration of PSC833 and Ko143. In contrast, in the transporter inhibition assays, raltegravir (10 to 500 μM) did not increase the accumulation of substrate for P-gp (rhodamine-6G), BCRP ([(3)H]mitoxantrone), or MRP1 [2',7'-bis(2-carboxyethyl)-5(6)-carboxyfluorescein (BCECF)] by MDA-MDR1 (P-gp)-, HEK-ABCG2-, or HeLa-MRP1-overexpressing cells, respectively. Our data suggest that raltegravir is a substrate but not an inhibitor of the drug efflux transporters P-gp and BCRP. These transporters might play a role in the restriction of raltegravir permeability across the blood-brain, blood-testicular, and blood-intestinal barriers, potentially contributing to its low tissue concentrations and/or low oral bioavailability observed in the clinic setting., (Copyright © 2015, American Society for Microbiology. All Rights Reserved.)

Background: Neuroinflammation is a common immune response associated with brain human immunodeficiency virus-1 (HIV-1) infection. Identifying therapeutic compounds that exhibit better brain permeability and can target signaling pathways involved in inflammation may benefit treatment of HIV-associated neurological complications. The objective of this study was to implement an in vivo model of brain inflammation by intracerebroventricular administration of the HIV-1 viral coat protein gp120 in rats and to examine anti-inflammatory properties of HIV adjuvant therapies such as minocycline, chloroquine and simvastatin., Methods: Male Wistar rats were administered a single dose of gp120ADA (500 ng) daily for seven consecutive days, intracerebroventricularly, with or without prior intraperitoneal administration of minocycline, chloroquine or simvastatin. Maraviroc, a CCR5 antagonist, was administered intracerebroventricularly prior to gp120 administration for seven days as control. Real-time qPCR was used to assess gene expression of inflammatory markers in the frontal cortex, hippocampus and striatum. Interleukin-1β (IL-1β) and tumor necrosis factor-α (TNF-α) secretion in cerebrospinal fluid (CSF) was measured applying ELISA. Protein expression of mitogen-activated protein kinases (MAPKs) (extracellular signal-related kinase 1/2 (ERK1/2), c-Jun N-terminal kinases (JNKs) and P38 kinases (P38Ks)) was detected using immunoblot analysis. Student's t-test and ANOVA were applied to determine statistical significance., Results: In gp120ADA-injected rats, mRNA transcripts of interleukin-1β (IL-1β) and inducible nitric oxide synthase (iNOS) were significantly elevated in the frontal cortex, striatum and hippocampus compared to saline or heat-inactivated gp120-injected controls. In CSF, a significant increase in TNF-α and IL-1β was detected. Maraviroc reduced upregulation of these markers suggesting that the interaction of R5-tropic gp120 to CCR5 chemokine receptor is critical for induction of an inflammatory response. Minocycline, chloroquine or simvastatin attenuated upregulation of IL-1β and iNOS transcripts in different brain regions. In CSF, minocycline suppressed TNF-α and IL-1β secretion, whereas chloroquine attenuated IL-1β secretion. In gp120-injected animals, activation of ERK1/2 and JNKs was observed in the hippocampus and ERK1/2 activation was significantly reduced by the anti-inflammatory agents., Conclusions: Our data demonstrate that anti-inflammatory compounds can completely or partially reverse gp120-associated brain inflammation through an interaction with MAPK signaling pathways and suggest their potential role in contributing towards the prevention and treatment of HIV-associated neurological complications.

P-glycoprotein (P-gp, product of Mdr1a and Mdr1b genes), multidrug resistance associated proteins (Mrps), and breast cancer resistance protein (Bcrp), all members of the ATP-binding cassette (ABC) membrane-associated drug transporters superfamily, can significantly restrict the entry of antiretroviral drugs (ARVs) into organs which exhibit a barrier function such as the central nervous system (CNS) and the male genital tract (MGT). In vitro, HIV-1 viral proteins such as glycoprotein-120 (gp120) and transcriptional transactivator (tat) have been shown to alter the expression of these transporters and ARVs permeability. The objective of this study was to compare mRNA expression of these transporters, in vivo, in several tissues obtained from HIV-1 transgenic rats (Tg-rat) (8 and 24 weeks) with those of age-matched wild-type rats. At 24 weeks, significant changes in several drug transporter mRNA expressions were observed, in particular, in brain, kidney, liver and testes. These findings suggest that HIV-1 viral proteins can alter the expression of ABC drug transporters, in vivo, in the context of HIV-1 and further regulate ARVs permeability in several organs including the CNS and MGT, two sites which have been reported to display very low ARVs permeability in the clinic., (Copyright © 2014 Elsevier Inc. All rights reserved.)

Protein structure prediction is computationally a very challenging problem. A large number of existing search algorithms attempt to solve the problem by exploring possible structures and finding the one with the minimum free energy. However, these algorithms perform poorly on large sized proteins due to an astronomically wide search space. In this paper, we present a multipoint spiral search framework that uses parallel processing techniques to expedite exploration by starting from different points. In our approach, a set of random initial solutions are generated and distributed to different threads. We allow each thread to run for a predefined period of time. The improved solutions are stored threadwise. When the threads finish, the solutions are merged together and the duplicates are removed. A selected distinct set of solutions are then split to different threads again. In our ab initio protein structure prediction method, we use the three-dimensional face-centred-cubic lattice for structure-backbone mapping. We use both the low resolution hydrophobic-polar energy model and the high-resolution 20 × 20 energy model for search guiding. The experimental results show that our new parallel framework significantly improves the results obtained by the state-of-the-art single-point search approaches for both energy models on three-dimensional face-centred-cubic lattice. We also experimentally show the effectiveness of mixing energy models within parallel threads.

Three-dimensional (3D) in vitro cell based assays for Prostate Cancer (PCa) research are rapidly becoming the preferred alternative to that of conventional 2D monolayer cultures. 3D assays more precisely mimic the microenvironment found in vivo, and thus are ideally suited to evaluate compounds and their suitability for progression in the drug discovery pipeline. To achieve the desired high throughput needed for most screening programs, automated quantification of 3D cultures is required. Towards this end, this paper reports on the development of a prototype analysis module for an automated high-content-analysis (HCA) system, which allows for accurate and fast investigation of in vitro 3D cell culture models for PCa. The Java based program, which we have named PCaAnalyser, uses novel algorithms that allow accurate and rapid quantitation of protein expression in 3D cell culture. As currently configured, the PCaAnalyser can quantify a range of biological parameters including: nuclei-count, nuclei-spheroid membership prediction, various function based classification of peripheral and non-peripheral areas to measure expression of biomarkers and protein constituents known to be associated with PCa progression, as well as defining segregate cellular-objects effectively for a range of signal-to-noise ratios. In addition, PCaAnalyser architecture is highly flexible, operating as a single independent analysis, as well as in batch mode; essential for High-Throughput-Screening (HTS). Utilising the PCaAnalyser, accurate and rapid analysis in an automated high throughput manner is provided, and reproducible analysis of the distribution and intensity of well-established markers associated with PCa progression in a range of metastatic PCa cell-lines (DU145 and PC3) in a 3D model demonstrated.

The use of antiretroviral therapy (ART) as pre-exposure prophylaxis (PrEP) has gained global attention as a promising HIV prevention strategy in men who have sex with men. Permeability of these agents in the rectal mucosa may be partially regulated by interactions with drug efflux transporters, P-glycoprotein (P-gp), multidrug resistance-associated proteins (MRPs) and/or breast cancer resistance protein (BCRP). The objective of this work was to investigate the expression of drug efflux transporters in recto-sigmoid colon tissues of HIV-infected and uninfected men, and evaluate the association of ART and/or HIV infection with drug transporter expression. MDR1/P-gp, MRPs (1-4) and BCRP mRNA and protein expression were detected in sigmoid colon biopsies of HIV-uninfected individuals. Biopsies from HIV-infected, ART-naïve participants revealed a significant downregulation of P-gp and MRP2 protein levels compared to HIV-uninfected individuals. Biopsies from HIV-infected ART-treated patients showed 1.9-fold higher P-gp protein expression and 1.5-fold higher MRP2 protein expression compared to the ones obtained from the HIV-infected ART-naïve patients. This is a first report demonstrating that HIV infection or ART could alter expression of drug efflux transporters in gut mucosa which in turn could affect the permeability of PrEP antiretroviral agents across this barrier, a highly vulnerable site of HIV transmission., (© The Author(s) 2013.)

ATP-binding cassette membrane-associated drug efflux transporters and solute carrier influx transporters, expressed at the blood-brain barrier, blood-cerebrospinal fluid barrier, and in brain parenchyma, are important determinants of drug disposition in the central nervous system. Targeting the regulatory pathways that govern the expression of these transporters could provide novel approaches to selectively alter drug permeability into the brain. Nuclear receptors are ligand-activated transcription factors which regulate the gene expression of several metabolic enzymes and drug efflux/influx transporters. Although efforts have primarily been focused on investigating these regulatory pathways in peripheral organs (i.e., liver and intestine), recent findings demonstrate their significance in the brain. This review addresses the role of nuclear receptors in the regulation of drug transporter functional expression in the brain. An in-depth understanding of these pathways could guide the development of novel pharmacotherapy with either enhanced efficacy in the central nervous system or minimal associated neurotoxicity., (Copyright © 2013 Elsevier Ltd. All rights reserved.)

Purpose: To investigate the role of membrane-associated drug transporters in regulating the intestinal absorption of the HIV-1 protease inhibitor, atazanavir, and assess the potential contribution of these transporters in clinical interactions of atazanavir with other protease inhibitors and tenofovir disoproxil fumarate (TDF)., Methods: Intestinal permeability of atazanavir was investigated in vitro, using the Caco-2 cell line system grown on Transwell inserts, and in situ, by single-pass perfusion of rat intestinal segments, jejunum and ileum, in the absence or presence of standard transporter inhibitors or antiretroviral drugs., Results: Atazanavir accumulation by Caco-2 cells was susceptible to inhibition by P-glycoprotein and organic anion transporting polypeptide (OATP) family inhibitors and several antiretroviral drugs (protease inhibitors, TDF). The secretory flux of atazanavir (basolateral-to-apical Papp) was 11.7-fold higher than its absorptive flux. This efflux ratio was reduced to 1.5-1.7 in the presence of P-glycoprotein inhibitors or ritonavir. P-glycoprotein inhibition also resulted in 1.5-2.5-fold increase in atazanavir absorption in situ. Co-administration of TDF, however, reduced atazanavir intestinal permeability by 13-49%, similar to the effect observed clinically., Conclusions: Drug transporters such as P-glycoprotein and OATPs regulate intestinal permeability of atazanavir and may contribute to its poor oral bioavailability and drug-drug interactions with other protease inhibitors and TDF.

Background: Protein structure prediction is an important but unsolved problem in biological science. Predicted structures vary much with energy functions and structure-mapping spaces. In our simplified ab initio protein structure prediction methods, we use hydrophobic-polar (HP) energy model for structure evaluation, and 3-dimensional face-centred-cubic lattice for structure mapping. For HP energy model, developing a compact hydrophobic-core (H-core) is essential for the progress of the search. The H-core helps find a stable structure with the lowest possible free energy., Results: In order to build H-cores, we present a new Spiral Search algorithm based on tabu-guided local search. Our algorithm uses a novel H-core directed guidance heuristic that squeezes the structure around a dynamic hydrophobic-core centre. We applied random walks to break premature H-cores and thus to avoid early convergence. We also used a novel relay-restart technique to handle stagnation., Conclusions: We have tested our algorithms on a set of benchmark protein sequences. The experimental results show that our spiral search algorithm outperforms the state-of-the-art local search algorithms for simplified protein structure prediction. We also experimentally show the effectiveness of the relay-restart.

Protein structure prediction (PSP) is computationally a very challenging problem. The challenge largely comes from the fact that the energy function that needs to be minimised in order to obtain the native structure of a given protein is not clearly known. A high resolution 20 × 20 energy model could better capture the behaviour of the actual energy function than a low resolution energy model such as hydrophobic polar. However, the fine grained details of the high resolution interaction energy matrix are often not very informative for guiding the search. In contrast, a low resolution energy model could effectively bias the search towards certain promising directions. In this paper, we develop a genetic algorithm that mainly uses a high resolution energy model for protein structure evaluation but uses a low resolution HP energy model in focussing the search towards exploring structures that have hydrophobic cores. We experimentally show that this mixing of energy models leads to significant lower energy structures compared to the state-of-the-art results.

Breast cancer resistance protein (BCRP/ABCG2), an ATP-binding cassette (ABC) membrane-associated drug efflux transporter, is known to localize at the blood-brain barrier (BBB) and can significantly restrict xenobiotic permeability in the brain. The objective of this study is to investigate the regulation of BCRP functional expression by peroxisome proliferator-activated receptor alpha (PPARα), a ligand-activated transcription factor primarily involved in lipid metabolism, in a cerebral microvascular endothelial cell culture system (hCMEC/D3), representative of human BBB. We demonstrate that PPARα-selective ligands (i.e., clofibrate, GW7647) significantly induce BCRP mRNA and protein expression in a time- and concentration-dependent manner, whereas pharmacological inhibitors (i.e., MK886, GW6471) prevent this induction. Using [(3)H]mitoxantrone, an established BCRP substrate, we observe a significant reduction in its cellular accumulation by monolayer cells treated with clofibrate, suggesting increased BCRP efflux activity. In addition, we show a significant decrease in BCRP protein expression and function when PPARα is down-regulated by small interfering RNA. Applying chromatin immunoprecipitation and quantitative real-time polymerase chain reaction, we observe that clofibrate treatment increases PPARα binding to the peroxisome proliferator response element within the ABCG2 gene promoter. This study provides the first evidence of direct BCRP regulation by PPARα in a human in vitro BBB model and suggests new targeting strategies for either improving drug brain bioavailability or increasing neuroprotection.

In mammalian systems, pregnane X receptor (PXR) and constitutive androstane receptor (CAR) have been recognized as xenobiotic-sensors which can up-regulate the functional expression of drug transporters, such as P-glycoprotein (P-gp). In the brain, an increase in P-gp expression can further limit drug permeability across the blood-brain barrier (BBB) and potentially reduce CNS pharmacotherapy efficacy. At present, the involvement of human PXR (hPXR) and CAR (hCAR) in the regulation of P-gp expression at the human BBB is unknown. In this study, we investigate the role of hPXR and hCAR in the regulation of P-gp expression using a human cerebral microvessel endothelial cell culture system. We demonstrate that activation of hPXR and hCAR by their respective ligands leads to P-gp induction at both mRNA and protein levels, while pharmacological inhibitors of hPXR and hCAR prevent ligand-mediated P-gp induction. Ligand-induced nuclear translocation of hPXR is observed, although such effect could not be demonstrated for hCAR. Furthermore, down-regulation of hPXR and hCAR proteins using small-interfering RNA decreased P-gp expression. Our findings provide first evidence for P-gp regulation by hPXR and hCAR at the human BBB and suggest insights on how to achieve selective P-gp regulation at this site., (© 2011 The Authors. Journal of Neurochemistry © 2011 International Society for Neurochemistry.)

This paper presents the impact of twins and the measures for their removal from the population of genetic algorithm (GA) when applied to effective conformational searching. It is conclusively shown that a twin removal strategy for a GA provides considerably enhanced performance when investigating solutions to complex ab initio protein structure prediction (PSP) problems in low-resolution model. Without twin removal, GA crossover and mutation operations can become ineffectual as generations lose their ability to produce significant differences, which can lead to the solution stalling. The paper relaxes the definition of chromosomal twins in the removal strategy to not only encompass identical, but also highly correlated chromosomes within the GA population, with empirical results consistently exhibiting significant improvements solving PSP problems.

Multidrug resistance protein 4 (MRP4/ABCC4), a member of the ATP-binding cassette protein superfamily, confers resistance to nucleoside and nucleotide analogs as well as camptothecin derivatives. MRP4 also mediates the efflux of certain cyclic nucleotides, eicosanoids, conjugated steroids, and uric acid. Depending on the cell type, MRP4 may localize to either apical or basolateral membranes in polarized cells. The adaptor protein NHERF1 has previously been implicated in MRP4 internalization in non-polarized cells. We have now found that NHERF1 levels are very low in polarized MDCKI cells which express MRP4 on basolateral membranes relative to polarized LLC-PK1 cells which express MRP4 on apical membranes. Furthermore, ectopic expression of FLAG-tagged NHERF1 in MDCKI cells and in MDCKI cells stably expressing eGFP-tagged MRP4 causes endogenous MRP4 and eGFP-MRP4, respectively, to traffic to the apical membranes. These data establish NHERF1 as a major determinant of MRP4 trafficking to apical membranes of mammalian kidney cells.