ThermalProGAN: A sequence-based thermally stable protein generator trained using unpaired data.

MOTIVATION: The synthesis of proteins with novel desired properties is challenging but sought after by the industry and academia. The dominating approach is based on trial-and-error inducing point mutations, assisted by structural information or predictive models built with paired data that are difficult to collect. This study proposes a sequence-based unpaired-sample of novel protein inventor (SUNI) to build ThermalProGAN for generating thermally stable proteins based on sequence information. RESULTS: The ThermalProGAN can strongly mutate the input sequence with a median number of 32 residues. A known normal protein, 1RG0, was used to generate a thermally stable form by mutating 51 residues. After superimposing the two structures, high similarity is shown, indicating that the basic function would be conserved. Eighty four molecular dynamics simulation results of 1RG0 and the COVID-19 vaccine candidates with a total simulation time of 840[Formula: see text]ns indicate that the thermal stability increased. CONCLUSION: This proof of concept demonstrated that transfer of a desired protein property from one set of proteins is feasible. Availability and implementation: The source code of ThermalProGAN can be freely accessed at https://github.com/markliou/ThermalProGAN/ with an MIT license. The website is https://thermalprogan.markliou.tw:433. Supplementary information: Supplementary data are available on Github.

Angiotensin II receptor blocker irbesartan attenuates sleep apnea-induced cardiac apoptosis and enhances cardiac survival and Sirtuin 1 upregulation.

BACKGROUND: The purpose of this study was to investigate whether or not angiotensin II type 1 receptor blocker irbesartan (ARB) with a partial agonist of PPAR-γ could protect against chronic nocturnal intermittent hypoxia (CIH)-induced cardiac Fas/FasL-mediated to mitochondria-mediated apoptosis. METHODS: Sprague-Dawley rats were in a normoxic control group (CON-G), or rats were in a chronic nocturnal intermittent hypoxia group (HP-G, from 3 to 7% oxygen versus 21% oxygen per forty seconds cycle, nocturnally 8 h per day for 1 month), or rats were in a chronic nocturnal intermittent hypoxia group pretreated with ARB (50 mg/kg/day, S.C.) (ARB-HP-G). Echocardiography, H&E staining, TUNEL staining, and Western blotting were measured in the left ventricle. RESULTS: Hypoxia-induced SIRT1 degradation, Fas receptors, FADD, active caspase-8 and caspase-3 (Fas/FasL apoptotic pathway) and Bax, tBid, active caspase-9 and -3 (mitochondrial apoptotic pathway) and TUNEL-positive apoptosis were reduced in ARB-HP-G when compared with HP-G. IGF-I, IGF1 receptor, p-PI3k, p-Akt, Bcl2, and Bcl-XL (IGF1/PI3K/AKT pro-survival pathway) were increased in ARB-HP-G compared to HP-G. CONCLUSIONS: Our findings suggest that the ARB may prevent cardiac Fas/FasL to mitochondrial apoptotic pathways and enhance cardiac IGF1/PI3K/AKT pro-survival pathway in the sleep apnea model associated with JNK de-activation and SIRT1 upregulation. ARB prevents chronic sleep apnea-enhanced cardiac apoptosis via enhancing survival pathways.

Effect of superoxide anion scavenger on rat hearts with chronic intermittent hypoxia.

Only very limited information regarding the protective effects of the superoxide anion scavenger on chronic intermittent hypoxia-induced cardiac apoptosis is available. The purpose of this study is to evaluate the effects of the superoxide anion scavenger on cardiac apoptotic and prosurvival pathways in rats with sleep apnea. Forty-two Sprague-Dawley rats were divided into three groups, rats with normoxic exposure (Control, 21% O2, 1 mo), rats with chronic intermittent hypoxia exposure (Hypoxia, 3-7% O2vs. 21% O2per 40 s cycle, 8 h per day, 1 mo), and rats with pretreatment of the superoxide anion scavenger and chronic intermittent hypoxia exposure (Hypoxia-O2 (-)-Scavenger, MnTMPyP pentachloride, 1 mg/kg ip per day; 3-7% O2vs. 21% O2per 40 s cycle, 8 h per day, 1 mo) at 5-6 mo of age. After 1 mo, the protein levels and apoptotic cells of excised hearts from three groups were measured by Western blotting and terminal deoxynucleotide transferase-mediated dUTP nick end labeling (TUNEL) assay. The superoxide anion scavenger decreased hypoxia-induced myocardial architecture abnormalities, left ventricular hypertrophy, and TUNEL-positive apoptosis. The superoxide anion scavenger decreased hypoxia-induced Fas ligand, Fas death receptors, Fas-associated death domain (FADD), activated caspase-8, and activated caspase-3 (Fas-dependent apoptotic pathway) as well as Bad, activated caspase-9 and activated caspase-3 (mitochondria-dependent apoptotic pathway), endonuclease G (EndoG), apoptosis-inducing factor (AIF), and TUNEL-positive apoptosis. The superoxide anion scavenger increased IGF-1, IGF-1R, p-PI3k, p-Akt, p-Bad, Bcl-2, and Bcl-xL (survival pathway). Our findings imply that the superoxide anion scavenger might prevent cardiac Fas-mediated and mitochondrial-mediated apoptosis and enhance the IGF-1-related survival pathway in chronic intermittent hypoxia. The superoxide anion scavenger may prevent chronic sleep apnea-enhanced cardiac apoptotic pathways and enhances cardiac survival pathways.

A hydrophobic spine stabilizes a surface-exposed α-helix according to analysis of the solvent-accessible surface area.

BACKGROUND: Most of hydrophilic and hydrophobic residues are thought to be exposed and buried in proteins, respectively. In contrast to the majority of the existing studies on protein folding characteristics using protein structures, in this study, our aim was to design predictors for estimating relative solvent accessibility (RSA) of amino acid residues to discover protein folding characteristics from sequences. METHODS: The proposed 20 real-value RSA predictors were designed on the basis of the support vector regression method with a set of informative physicochemical properties (PCPs) obtained by means of an optimal feature selection algorithm. Then, molecular dynamics simulations were performed for validating the knowledge discovered by analysis of the selected PCPs. RESULTS: The RSA predictors had the mean absolute error of 14.11% and a correlation coefficient of 0.69, better than the existing predictors. The hydrophilic-residue predictors preferred PCPs of buried amino acid residues to PCPs of exposed ones as prediction features. A hydrophobic spine composed of exposed hydrophobic residues of an α-helix was discovered by analyzing the PCPs of RSA predictors corresponding to hydrophobic residues. For example, the results of a molecular dynamics simulation of wild-type sequences and their mutants showed that proteins 1MOF and 2WRP_H16I (Protein Data Bank IDs), which have a perfectly hydrophobic spine, have more stable structures than 1MOF_I54D and 2WRP do (which do not have a perfectly hydrophobic spine). CONCLUSIONS: We identified informative PCPs to design high-performance RSA predictors and to analyze these PCPs for identification of novel protein folding characteristics. A hydrophobic spine in a protein can help to stabilize exposed α-helices.

SCMBYK: prediction and characterization of bacterial tyrosine-kinases based on propensity scores of dipeptides.

BACKGROUND: Bacterial tyrosine-kinases (BY-kinases), which play an important role in numerous cellular processes, are characterized as a separate class of enzymes and share no structural similarity with their eukaryotic counterparts. However, in silico methods for predicting BY-kinases have not been developed yet. Since these enzymes are involved in key regulatory processes, and are promising targets for anti-bacterial drug design, it is desirable to develop a simple and easily interpretable predictor to gain new insights into bacterial tyrosine phosphorylation. This study proposes a novel SCMBYK method for predicting and characterizing BY-kinases. RESULTS: A dataset consisting of 797 BY-kinases and 783 non-BY-kinases was established to design the SCMBYK predictor, which achieved training and test accuracies of 97.55 and 96.73%, respectively. Furthermore, the leave-one-phylum-out method was used to predict specific bacterial phyla hosts of target sequences, gaining 97.39% average test accuracy. After analyzing SCMBYK-derived propensity scores, four characteristics of BY-kinases were determined: 1) BY-kinases tend to be composed of α-helices; 2) the amino-acid content of extracellular regions of BY-kinases is expected to be dominated by residues such as Val, Ile, Phe and Tyr; 3) BY-kinases structurally resemble nuclear proteins; 4) different domains play different roles in triggering BY-kinase activity. CONCLUSIONS: The SCMBYK predictor is an effective method for identification of possible BY-kinases. Furthermore, it can be used as a part of a novel drug repurposing method, which recognizes putative BY-kinases and matches them to approved drugs. Among other results, our analysis revealed that azathioprine could suppress the virulence of M. tuberculosis, and thus be considered as a potential antibiotic for tuberculosis treatment.

SCMMTP: identifying and characterizing membrane transport proteins using propensity scores of dipeptides.

BACKGROUND: Identifying putative membrane transport proteins (MTPs) and understanding the transport mechanisms involved remain important challenges for the advancement of structural and functional genomics. However, the transporter characters are mainly acquired from MTP crystal structures which are hard to crystalize. Therefore, it is desirable to develop bioinformatics tools for the effective large-scale analysis of available sequences to identify novel transporters and characterize such transporters. RESULTS: This work proposes a novel method (SCMMTP) based on the scoring card method (SCM) using dipeptide composition to identify and characterize MTPs from an existing dataset containing 900 MTPs and 660 non-MTPs which are separated into a training dataset consisting 1,380 proteins and an independent dataset consisting 180 proteins. The SCMMTP produced estimating propensity scores for amino acids and dipeptides as MTPs. The SCMMTP training and test accuracy levels respectively reached 83.81% and 76.11%. The test accuracy of support vector machine (SVM) using a complicated classification method with a low possibility for biological interpretation and position-specific substitution matrix (PSSM) as a protein feature is 80.56%, thus SCMMTP is comparable to SVM-PSSM. To identify MTPs, SCMMTP is applied to three datasets including: 1) human transmembrane proteins, 2) a photosynthetic protein dataset, and 3) a human protein database. MTPs showing α-helix rich structure is agreed with previous studies. The MTPs used residues with low hydration energy. It is hypothesized that, after filtering substrates, the hydrated water molecules need to be released from the pore regions. CONCLUSIONS: SCMMTP yields estimating propensity scores for amino acids and dipeptides as MTPs, which can be used to identify novel MTPs and characterize transport mechanisms for use in further experiments. AVAILABILITY: http://iclab.life.nctu.edu.tw/iclab_webtools/SCMMTP/.

Attenuation of Magnesium Sulfate on CoCl2-Induced Cell Death by Activating ERK1/2/MAPK and Inhibiting HIF-1α via Mitochondrial Apoptotic Signaling Suppression in a Neuronal Cell Line.

Magnesium sulfate (MgSO4) ameliorates hypoxia/ischemia-induced neuronal apoptosis in a rat model. This study aimed to investigate the mechanisms governing the anti-apoptotic effect of MgSO4 on cobalt chloride (CoCl2)-exposed NB41A3 mouse neuroblastoma cells. MgSO4 increased the viability of NB41A3 cells treated with CoCl2 in a dose-dependent manner. MgSO4 treatment was shown to lead to an increase in the anti-apoptotic Bcl-2 family proteins, with a concomitant decrease in the pro-apoptotic proteins. MgSO4 also attenuated the CoCl2-induced disruption of mitochondrial membrane potential (ΔΨ(m)) and reduced the release of cytochrome c form the mitochondria to the cytosol. Furthermore, exposure to CoCl2 caused activation of the hypoxia-inducible factor 1α (HIF-1α). On the other hand, MgSO4 markedly reduced CoCl2-induced HIF-1α activation and suppressed HIF-1α downstream protein BNIP3. MgSO4 treatment induced ERK1/2 activation and attenuated CoCl2-induced activation of p38 and JNK. Addition of the ERK1/2 inhibitor U0126 significantly reduced the ability of MgSO4 to protect neurons from CoCl2-induced mitochondrial apoptotic events. However, incubation of cultures with the p38 and JNK inhibitors did not significantly affect MgSO4-mediated neuroprotection. MgSO4 appears to suppress CoCl2-induced NB41A3 cell death by activating ERK1/2/ MAPK pathways, which further modulates the role of Bcl-2 family proteins and mitochondria in NB41A3 cells. Our data suggest that MgSO4 may act as a survival factor that preserves mitochondrial integrity and inhibits apoptotic pathways.

The Root Extract of Gentiana macrophylla Pall. Alleviates Cardiac Apoptosis in Lupus Prone Mice.

The roots of the perennial herb Gentiana macrophylla Pall. (GM) are known as Qinjiao, which has been used for centuries to treat systemic lupus erythematosus (SLE). However, little is known about the effects of GM on cholesterol-aggravated cardiac abnormalities in SLE, and the mechanisms thereof. This study investigates whether GM exhibits anti-apoptotic effects, focusing on the left ventricle (LV) of NZB/W F1 mice fed with high-cholesterol diet. The morphology and apoptotic status of ventricular tissues were determined by microscopy and Terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL) assay. Levels of apoptotic biomarkers were determined by immunoblotting. The results thus obtained revealed that GM significantly reduced the cholesterol-aggravated apoptosis of LV in NZB/W F1 mice by suppressing both intrinsic and extrinsic apoptotic pathways. Additionally, GM significantly increased the cardiac insulin-like growth factors (IGF)-1 survival signaling and anti-apoptotic proteins in LV tissues. Accordingly, GM is considered to be beneficial in alleviating cholesterol-aggravated cardiac damage in SLE, and therefore constitute an alternative treatment for SLE patients with cardiac abnormalities.

SCMPSP: Prediction and characterization of photosynthetic proteins based on a scoring card method.

BACKGROUND: Photosynthetic proteins (PSPs) greatly differ in their structure and function as they are involved in numerous subprocesses that take place inside an organelle called a chloroplast. Few studies predict PSPs from sequences due to their high variety of sequences and structues. This work aims to predict and characterize PSPs by establishing the datasets of PSP and non-PSP sequences and developing prediction methods. RESULTS: A novel bioinformatics method of predicting and characterizing PSPs based on scoring card method (SCMPSP) was used. First, a dataset consisting of 649 PSPs was established by using a Gene Ontology term GO:0015979 and 649 non-PSPs from the SwissProt database with sequence identity <= 25%.- Several prediction methods are presented based on support vector machine (SVM), decision tree J48, Bayes, BLAST, and SCM. The SVM method using dipeptide features-performed well and yielded - a test accuracy of 72.31%. The SCMPSP method uses the estimated propensity scores of 400 dipeptides - as PSPs and has a test accuracy of 71.54%, which is comparable to that of the SVM method. The derived propensity scores of 20 amino acids were further used to identify informative physicochemical properties for characterizing PSPs. The analytical results reveal the following four characteristics of PSPs: 1) PSPs favour hydrophobic side chain amino acids; 2) PSPs are composed of the amino acids prone to form helices in membrane environments; 3) PSPs have low interaction with water; and 4) PSPs prefer to be composed of the amino acids of electron-reactive side chains. CONCLUSIONS: The SCMPSP method not only estimates the propensity of a sequence to be PSPs, it also discovers characteristics that further improve understanding of PSPs. The SCMPSP source code and the datasets used in this study are available at http://iclab.life.nctu.edu.tw/SCMPSP/.

SCMHBP: prediction and analysis of heme binding proteins using propensity scores of dipeptides.

BACKGROUND: Heme binding proteins (HBPs) are metalloproteins that contain a heme ligand (an iron-porphyrin complex) as the prosthetic group. Several computational methods have been proposed to predict heme binding residues and thereby to understand the interactions between heme and its host proteins. However, few in silico methods for identifying HBPs have been proposed. RESULTS: This work proposes a scoring card method (SCM) based method (named SCMHBP) for predicting and analyzing HBPs from sequences. A balanced dataset of 747 HBPs (selected using a Gene Ontology term GO:0020037) and 747 non-HBPs (selected from 91,414 putative non-HBPs) with an identity of 25% was firstly established. Consequently, a set of scores that quantified the propensity of amino acids and dipeptides to be HBPs is estimated using SCM to maximize the predictive accuracy of SCMHBP. Finally, the informative physicochemical properties of 20 amino acids are identified by utilizing the estimated propensity scores to be used to categorize HBPs. The training and mean test accuracies of SCMHBP applied to three independent test datasets are 85.90% and 71.57%, respectively. SCMHBP performs well relative to comparison with such methods as support vector machine (SVM), decision tree J48, and Bayes classifiers. The putative non-HBPs with high sequence propensity scores are potential HBPs, which can be further validated by experimental confirmation. The propensity scores of individual amino acids and dipeptides are examined to elucidate the interactions between heme and its host proteins. The following characteristics of HBPs are derived from the propensity scores: 1) aromatic side chains are important to the effectiveness of specific HBP functions; 2) a hydrophobic environment is important in the interaction between heme and binding sites; and 3) the whole HBP has low flexibility whereas the heme binding residues are relatively flexible. CONCLUSIONS: SCMHBP yields knowledge that improves our understanding of HBPs rather than merely improves the prediction accuracy in predicting HBPs.

Increased risk of major depression in the three years following a femoral neck fracture--a national population-based follow-up study.

Femoral neck fracture is common in the elderly, and its impact has increased in aging societies. Comorbidities, poor levels of activity and pain may contribute to the development of depression, but these factors have not been well addressed. This study aims to investigate the frequency and risk of major depression after a femoral neck fracture using a nationwide population-based study. The Taiwan Longitudinal Health Insurance Database was used in this study. A total of 4,547 patients who were hospitalized for femoral neck fracture within 2003 to 2007 were recruited as a study group; 13,641 matched non-fracture participants were enrolled as a comparison group. Each patient was prospectively followed for 3 years to monitor the occurrence of major depression. Cox proportional-hazards models were used to compute the risk of major depression between members of the study and comparison group after adjusting for residence and socio-demographic characteristics. The most common physical comorbidities that were present after the fracture were also analyzed. The incidences of major depression were 1.2% (n = 55) and 0.7% (n = 95) in the study and comparison groups, respectively. The stratified Cox proportional analysis showed a covariate-adjusted hazard ratio of major depression among patients with femoral neck fracture that was 1.82 times greater (95% CI, 1.30-2.53) than that of the comparison group. Most major depressive episodes (34.5%) presented within the first 200 days following the fracture. In conclusion, patients with a femoral neck fracture are at an increased risk of subsequent major depression. Most importantly, major depressive episodes mainly occurred within the first 200 days following the fracture.

Predicting and analyzing DNA-binding domains using a systematic approach to identifying a set of informative physicochemical and biochemical properties.

BACKGROUND: Existing methods of predicting DNA-binding proteins used valuable features of physicochemical properties to design support vector machine (SVM) based classifiers. Generally, selection of physicochemical properties and determination of their corresponding feature vectors rely mainly on known properties of binding mechanism and experience of designers. However, there exists a troublesome problem for designers that some different physicochemical properties have similar vectors of representing 20 amino acids and some closely related physicochemical properties have dissimilar vectors. RESULTS: This study proposes a systematic approach (named Auto-IDPCPs) to automatically identify a set of physicochemical and biochemical properties in the AAindex database to design SVM-based classifiers for predicting and analyzing DNA-binding domains/proteins. Auto-IDPCPs consists of 1) clustering 531 amino acid indices in AAindex into 20 clusters using a fuzzy c-means algorithm, 2) utilizing an efficient genetic algorithm based optimization method IBCGA to select an informative feature set of size m to represent sequences, and 3) analyzing the selected features to identify related physicochemical properties which may affect the binding mechanism of DNA-binding domains/proteins. The proposed Auto-IDPCPs identified m = 22 features of properties belonging to five clusters for predicting DNA-binding domains with a five-fold cross-validation accuracy of 87.12%, which is promising compared with the accuracy of 86.62% of the existing method PSSM-400. For predicting DNA-binding sequences, the accuracy of 75.50% was obtained using m = 28 features, where PSSM-400 has an accuracy of 74.22%. Auto-IDPCPs and PSSM-400 have accuracies of 80.73% and 82.81%, respectively, applied to an independent test data set of DNA-binding domains. Some typical physicochemical properties discovered are hydrophobicity, secondary structure, charge, solvent accessibility, polarity, flexibility, normalized Van Der Waals volume, pK (pK-C, pK-N, pK-COOH and pK-a(RCOOH)), etc. CONCLUSIONS: The proposed approach Auto-IDPCPs would help designers to investigate informative physicochemical and biochemical properties by considering both prediction accuracy and analysis of binding mechanism simultaneously. The approach Auto-IDPCPs can be also applicable to predict and analyze other protein functions from sequences.

Increased expression of glucose transporter 3 in gerbil brains following magnesium sulfate treatment and focal cerebral ischemic injury.

Glucose is the primary energy substrate for neurons. Glucose transporter 3 (Glut3) localizes at the neuronal cellular membrane, which transports glucose from the extracelluar space into neurons. Ischemia results in an increased energy demand that is associated with profound changes in brain energy metabolism. Magnesium sulfate (MgSO(4)) ameliorates ischemia-induced neuronal death in the rat and gerbil model. We investigated the effects of MgSO(4) administration on the expression of Glut3 in cortex and hippocampus of gerbils during ischemia. The focal cerebral ischemia was produced by unilateral occlusion of the right common carotid artery and right middle cerebral artery. Following ischemia, Glut3 expression increased significantly versus non-ischemic (contra-lateral) cortex and hippocampus. MgSO(4) treatment significantly increased the level of Glut3 expression in the non-ischemic and ischemic cortex and hippocampus. We found that the MgSO(4)-induced increase in Glut3 expression was not reversed by administration of U0126, a MEK kinase inhibitor. These results suggest that other factors may function to modulate the MgSO(4)-induced Glut3 response. In all, our data showed that MgSO(4) increases the expression of Glut3 in the cortex and hippocampus of gerbil brains both in non-ischemia and ischemia status. However, the MEK signaling pathway might not be involved in MgSO(4)-induced Glut3 expression following focal ischemia.

Role of ERK signaling in the neuroprotective efficacy of magnesium sulfate treatment during focal cerebral ischemia in the gerbil cortex.

Magnesium sulfate (MgSO4) ameliorates focal ischemia-induced neuronal death in the rat and gerbil models. However, the molecular mechanisms for this neuroprotection are not known. Focal cerebral ischemia was produced by unilateral occlusion of the right common carotid artery and the right middle cerebral artery (CCAO + MCAO) for 30 min or 60 min. Treatment with MgSO4 significantly increased the level of mitogen-activated protein kinase/extra-cellular signal-regulated kinase kinase 1/2 (MEK1/2), extra-cellular signal-regulated kinase 1/2 (ERK1/2), cyclic-AMP response element binding protein (CREB) phosphorylation and the anti-apoptotic protein Bcl-2 both in the non-ischemic (contralateral) and ischemic (ipsilateral) cortex. However, these effects were reversed by administration of U0126, a MEK kinase inhibitor. In the ipsilateral cortex, a significant increase in the level of the proapoptotic proteins Bax, Bad, BNIP3 and activated caspase 3 were detected at the end of focal ischemia compared to the non-ischemic cortex. Treatment of MgSO4 prevented these ischemia-induced activations of the death cascade. Collectively, these data indicate that the ERK-CREB-Bcl-2 signaling pathway might be involved in MgSO4-induced neuroprotection following focal ischemia. Moreover, MgSO4 treatment also resulted in a reduction in pro-apoptotic proteins. These results enhance our understanding on the role of MgSO4 in treating cerebral ischemia.