Paranormal believers’ thinking is frequently biased by intuitive beliefs. Lack of inhibition of these tempting beliefs is considered a key element in paranormal believers’ thinking. However, the brain activity related to inhibitory control in paranormal believers is poorly understood. We examined EEG activities at resting state in alpha, beta, and gamma bands with inhibitory control in paranormal believers and skeptics. The present study shows that paranormal belief is related to the reduced power of the alpha, beta, and gamma frequency bands, and reduced inhibitory control. This study may contribute to understanding the differences between believers and skeptics in brain activity related to inhibitory control in paranormal believers. Such beliefs include believing in traditional religions, telekinesis, superstition, witchcraft, spiritualism, magical thinking, extrasensory perception, and precognition2. Irwin3 hypothesizes that paranormal believers suffer from cognitive deficits. Supporting this hypothesis, some studies have shown deficiencies in the cognitive functions of paranormal believers. These deficits may include inhibitory control4, critical thinking5, probability misjudgment6, working memory and inattention blindness7, reasoning skills8, imagination9, cognitive and belief bias12. Human thinking is frequently biased; however, some people, such as paranormal believers, are more prone to biased thinking14. Cognitive and belief biases are mental errors that systematically lead to false tendencies, attitudes, and beliefs, and affect decision-making, reasoning, perception, and cognition15. Willard and Norenzayan14 stated that belief and cognitive biases, as byproducts of brain functions, form the paranormal experience’s biological basis. They suggest that supernatural agents appear from a set of correlated biases. Influenced by these biases, the human mind gravitates toward paranormal beliefs and intuitions. Intuitive beliefs often bias the thinking of paranormal believers16. Considering that several paranormal beliefs are built on statements that fail spectacularly when exposed to analytical consideration, one may anticipate an analytical thinking style to be adversely correlated with these beliefs17. Because the lower paranormal belief was correlated with higher analytical thinking18. However, concerning the reasoning interaction of interpretation inconsistencies, the dual-process theory in reasoning interaction is still under debate21. The main question is whether these two processes  compete to overcome each other, or whether a particular regulatory mechanism exists for these reasoning strategies. The mechanism that may be implicated as the suppressor of the intuitive thinking style is inhibitory control, which reduces the tendency toward paranormal beliefs18.Paranormal beliefs are beliefs, entities, practices, and processes that contradict the basic limiting laws of science22. According to Hood23, a paranormal sense may overwhelm some individuals who cannot adequately inhibit the rising intuitions. Consistent with this idea, poor inhibitory control is associated with teleological biases, and core knowledge confusion tendency17. Some studies have confirmed the inhibitory deficit in paranormal believers. Hood et al.24 showed that paranormal believers committed more errors than skeptics in the Wisconsin Card Sorting Test (WCST). Svedholm and Lindeman17 also showed that higher scores on ontological confusions and paranormal beliefs were correlated with poor inhibitory control in the Stroop task. In addition, Narmashiri et al.25 revealed that paranormal believers showed more errors in No-Go trials than skeptics in the Go/No-Go paradigm.From a psychological perspective, the concept of controlling dominant biases and responses is related to the inhibitory control concept. Inhibitory control leads to the management of inappropriate or undesirable behaviors in humans, and it is considered one of the crucial components of executive functions27. EEG is used in a variety of specific procedures. One popular method is known as resting-state EEG, which records continuing brain activity while the participant is not engaged in any specific cognitive task28. EEG activity during the resting-state, which is reliable over time, and reflects indices of brain activity, has been related to cognitive performance in previous studies31. Thus, evaluating the EEG resting-state activity may increase our knowledge about fundamental brain processes related to cognitive processes in paranormal beliefs. Event-related neural oscillations may be employed to analyze the neural responses through various frequency bands 32. Different cognitive functions are associated with each of these bands36. The alpha band activities are primarily related to cognitive control in the Go/No-Go paradigm37. In addition, several studies have been performed based on resting-state EEG focusing on inhibitory control in alpha, beta, and gamma band activities. For instance, Lee et al.38 stated that a reduction in alpha and beta band activities was associated with poor inhibitory control in the gambling disorder. Bresnahan and Barry39 revealed that ADHD individuals with high impulsivity had a lower activity level in the beta band. In addition, Choi et al.40 reported that reduced beta activity was associated with low inhibitory control in internet addiction. Moreover, there is a relationship between beta band activity, response preparation, and inhibitory control42, as well as cognitive function44. Studies have shown a weaker beta band power in No-Go trials in both non-human primates and healthy and neuropsychiatric human populations49. It is possible that increased inhibitory control results in increased beta band activity, while decreased inhibitory control results in reduced beta band activity51. According to these studies, beta power oscillations may be associated with inhibitory control. On the other hand, gamma power oscillations are associated with diverse cognitive functions from conscious awareness to inhibitory response55. Few studies have shown low gamma band activity in the No-Go trials related to inhibitory control57. Barry et al.58 suggest that ADHD children with high impulsivity have decreased beta and gamma absolute power. Benasich et al.59 showed a relationship between better cognitive functions, such as inhibition control, and an increased frontal gamma band activity in children with ADHD. In addition, low gamma power oscillations in the frontal lobe may indicate poor inhibitory control60.Electroencephalography (EEG) has been used to assess brain activity since more than a century. The EEG records the electrical activity of the brain across the scalp and provides a continuous index of electrocortical rhythms62. However, there is little evidence of the underlying neural changes related to inhibitory control in paranormal beliefs. Nonetheless, Lindeman et al.63 showed that the rIFG area had less activation in paranormal believers based on functional magnetic resonance imaging (fMRI). In contrast, this area had strong activity in skeptics, indicating that less activation in the rIFG may be related to poor inhibitory control in paranormal believers. On the other hand, while a few studies have investigated resting-state EEG in paranormal believers67, the relationship between brain activity and specific cognitive processes, such as inhibitory control, has not yet been investigated, and data regarding the role of frontal lobe activity are lacking. Hence, Fleck et al.68 showed that individuals with high transliminality demonstrated low alpha, beta, and gamma band activities over the left parietal/occipital lobe, the right superior temporal cortex, and the left/right temporal lobe, respectively, compared to individuals with low transliminality. Additionally, Nash et al.69 found that religious believers showed increased dominance of a network related to intuitive processing. In contrast, non-believers showed increased power of a network linked to analytic processing. Furthermore, Kleinert et al.70 found that self-control, behavior related to self-control , and a neural measure of self-control were associated with longer durations of mental processes as identified in resting-state EEG recordings.Neuroimaging studies have linked inhibitory control to the right inferior frontal gyrus (IFG)73. Previous studies in poor inhibitory control have shown reduced alpha, beta, and gamma oscillations in EEG under resting conditions. So far, no study has examined EEG activities during resting-state concerning inhibitory control in paranormal believers, who would be expected to show low levels of inhibitory control. Following the cognitive deficits hypothesis in paranormal believers3, we investigated resting-state EEG oscillatory activity to identify brain activation related to paranormal beliefs and inhibitory control. Since there aren't any EEG resting-state studies related to response inhibitory processes, inhibitory deficit, and reports of frontal lobe dysfunction in paranormal believers75, we predicted that paranormal believers would be characterized by reduced EEG oscillatory activity related to inhibitory control in the whole brain compared to skeptics. Paranormal believers are most likely to show poor inhibitory control compared to skeptics, which, as mentioned, may be related to beta band activity in the brain. Therefore, we hypothesize that paranormal believers are most likely to show poor performance in No-Go trials compared to skeptics. Moreover, we predict that paranormal believers show lower beta band activation across the whole brain. Additionally, frontal lobe is separately analyzed as it is associated with inhibitory control  in the present study.It seems that there is an association between the alpha, beta, and gamma oscillations and inhibitory control in the frontal lobeA total of 20  healthy right-handed (Edinburgh Handedness Inventory) students were selected for the study. We were looking for students who believed in or were skeptical about paranormal beliefs. The participants received gifts for participating in the present study.76. The distribution of paranormal beliefs was strongly skewed, as expected. Those belonging to the upper and lower groups (30%) were included in the analyses, i.e., paranormal believers , and skeptics . Based on previous studies78, we focused on the more extreme groups.Initially, 33 students were selected for this study. The severity of paranormal beliefs was determined using the overall score on the Revised Paranormal Belief ScaleThe participants' mean (SD) paranormal belief scores in the paranormal believer and skeptic groups were 84.80 (17.03) and 35.30 (6.23), respectively. According to the self-report questionnaire, the participants had no history of psychosis, mental illnesses, acute or chronic diseases, neurological or personality problems, alcohol or drug abuse, or epilepsy. This study was conducted following the principles of the Declaration of Helsinki, and approved by the Ethics Committee of The Institute for Cognitive Science Studies. All participants provided written informed consent before enrollment.76. Items are presented as phrases , and respondents evaluate the answers on a seven-point Likert scale according to how strongly they agree with them. The RPBS can give scores that corresponds to the subscales, and the aggregate yields a general estimate of the degree of paranormal belief. The RPBS subscales and the measurement show sufficient validity and reliability79. Internal consistency in previous study was excellent, with Chronbach's α = 0.9280.The current study uses the Revised Paranormal Beliefs Scale (RPBS), which is used widely to assess belief in the paranormal. The RPBS consists of 26 items grouped in seven subscales, i.e., Traditional Religious Beliefs, Psi, Witchcraft, Superstition, Spiritualism, Extraordinary Life Forms, and Precognition. The items are rated on a seven-point Likert scale (from 1 = Strongly Disagree to 7 = Strongly Agree)81. It has been demonstrated that CFQ has adequate validity and reliability, including high internal consistency and test–retest stability, and multidimensional factor structure84.The Cognitive Failures Questionnaire (CFQ) is a self-report questionnaire measuring failures in memory, perception, and motion in daily life. The CFQ consists of 25 questions, and the participants answer the items on a five-point Likert scale . "Do you neglect to listen to people's names while you are meeting them?" is an example of a question. A high score shows a greater propensity for cognitive failure85. On a computer monitor, this task was presented. A fixation stimulus in the monitor's center always appeared before the visual Go and No-Go stimuli. The participants were instructed to press a button as rapidly as possible in response to the green rectangle that appeared in the center, which served as the go stimulus. The participants were asked to withhold their response to the No-Go stimulus (blue rectangle), which appeared in the center. The mean of errors  were calculated based on the task performance. The Go and No-Go stimuli were presented in random  were organized for an in laboratory component. The experiment was carried out by participants at a computer station within an electrically isolated EEG-cabin. They were fitted with a 32-channel EEG  headset after initially providing written informed permission. Although there seems to be a difference between the eyes-open and eyes-close conditions86, there are still inconsistent results87. We used an eyes-open resting-state instead of an eye-closed resting-state, because the EEG recording was conducted in the early morning for all the participants. Participants were instructed to keep their eyes open while the EEG was being recorded to avoid drowsiness artifacts in line with previous studies93. Additionally, the eyes-open resting-state represents a more appropriate baseline for comparing two groups together92. EEG data were collected while participants stared at a blank screen for five minutes. Then, participants completed Go/No-Go task. Eventually, participants completed the manipulation and compliance checks. After receiving a debriefing, the headset was taken off, participants had their hair cleaned, and they were thanked for their participation.There were two stages to this experiment. First, participants completed the questionnaires including the demographic questions, RPBS, and CFQ. Second, participants . Absolute (µV2) power was extracted from the cleaned EEG data in nine frequency bands, including delta (1–4 Hz), theta (4–8 Hz), alpha (8–13 Hz), alpha1 (8–10), alpha2 (11–13), beta (13–30 Hz), beta1(13–21), beta2 (19–30), and gamma (30–40 Hz). Following a previous study75, the activity at 31 sites was divided into four regions, two hemispheres, and eight hemispheres/regions by averaging within each region, hemisphere, and hemisphere/region. The four regions include frontal , temporal , parietal , and occipital . The two hemispheres are the right  and the left . In addition, the eight hemispheres/regions are left frontal , right frontal , left temporal , right temporal , left parietal (CP3 and P3), right parietal (CP4 and P4), left occipital (O1), and right occipital (O2).The participants were seated in a resting state in a recording room. EEG recordings lasted for 5 min with eyes open. EEG recordings and acquisitions were made with a 32-channel MITSAR 202 system . The standard 10–20 montage system was used, including FP1, FPZ, FP2, F7, F3, Fz, F4, F8, FT7, FC3, FCZ, FC4, FT8, T3, C3, CZ, C4, T4, TP7, CP3, CPZ, CP4, TP8, T5, P3, Pz, P4, T6, O1, Oz, and O2 electrodes. As a reference, a single channel with bipolar electrodes was attached to the ears. The location of the ground electrode was between FPz and Fz. The signal sampling was done at a frequency of 250 Hz. The electrode’s impedance was below 5 kΩ, and the EEG signals were band-pass filtered offline from 0.1 to 40 Hz. The WinEEG system’s recordings were transferred to the EEGLAB toolbox  for the standard preprocessing stage. Artifact removal was performed offline using the artifact rejection toolbox of the EEGLAB toolbox. EEG recordings were also visually and manually inspected to eliminate the effects of eye, muscle, movements, and other artifacts in line with previous studies98. FDR correction was not performed in correlation results due to the exploratory nature of this stage. The effect size for the t-test was calculated using Cohen's d. In addition, we used Pearson’s correlations to explore the relationships between resting-state EEG activities and demographic/behavioral variables in paranormal believers and skeptics. A multiple regression analysis was performed to show the effect of frequency bands  as predictors on the measure of the paranormal belief as the criterion. In addition, we used model 4 of the PROCESS macro in SPSS99 to examine whether the effect of paranormal beliefs on inhibitory control  was mediated by frequency bands  in the whole brain (the first mediation model) and frontal lobe (the second mediation model) separately. The statistical significance of the indirect mediation effect on inhibitory control was assessed by bootstrapping (5000 samples) with a 95% confidence interval99. Statistical analyses were performed using IBM SPSS Statistics version 24 , and MATLAB 2021a , and p-values less than 0.05 were considered statistically significant.Comparisons of demographic  and behavioral variables  between the groups  were conducted using the independent two-sample t-test and chi-square tests. EEG absolute power data were analyzed separately for all the bands, the areas, the hemispheres, and the hemispheres/regions using an independent two-sample t-test between two groups  with adjusted p-values using the false discovery rate (FDR) method to limit type I errorAs can be seen in Table 18 = 2.117, p = 0.048, FDR corrected, Cohen's d = 0.997) and beta2 band activities . As shown in Fig. 18 = 2.123, p = 0.048, FDR corrected, Cohen's d = 1.00), beta2 , and gamma-band activities . As shown in Fig. 18 = 2.548, p = 0.020, FDR corrected, Cohen's d = 1.201) and beta2 band activities . The absolute power in the beta1 and beta2 band activities of the paranormal believers was lower than that of the skeptics in the right frontal area.Figure 18 = 2.216, p = 0.040, FDR corrected, Cohen's d = 1.044), and beta2 band activities . The absolute power in the beta1 and beta2 band activities of the paranormal believers was lower than that of the skeptics in the parietal area. In the left parietal area, the independent t-test results showed a significant difference between the groups for the absolute power in the beta1 band activity . The absolute power in the beta1 band activity of the paranormal believers was lower than that of the skeptics in the left parietal area. In the occipital area, the independent t-test results showed a significant difference between the groups for the absolute power in the beta1 , and beta2 band activities . The absolute power in the beta 1 and beta2 band activities of the paranormal believers was lower than that of the skeptics in the occipital area.In the parietal area, the independent t-test results showed a significant difference between the groups for the absolute power in the beta1 . The absolute power in the beta1 band activity of the paranormal believers was lower than that of the skeptics in the right hemisphere. However, results showed no significant difference between the groups for the absolute power in other bands, areas, and hemispheres.In the right hemisphere, the independent t-test results showed a significant difference between the groups for the absolute power in the beta1 band activity , and beta2 band activities   and beta2 power activities . In the left parietal area, there were significant negative correlations between the severity of paranormal beliefs and beta1  and beta2 band activities .In the left temporal area, there were significant negative correlations between the severity of paranormal beliefs and absolute beta2 band activity . In addition, in the occipital area, there were significant negative correlations between the severity of paranormal beliefs and beta1  and beta2 band activities . Additionally, in the right hemisphere, we found significant negative correlations between the severity of paranormal beliefs and absolute beta1 , and beta2 band activities . In the left hemisphere, we found significant negative correlations between the severity of paranormal beliefs and beta2 band activities .Additionally, the results of the multiple regression analysis show that the regression coefficient value (R) is 0.70 and the determination coefficient is R2) 0.49. All frequency bands combined could explain 49% of the variance in paranormal beliefs. The amount of relative and effective contribution of the frequency bands (predictors), toward the dependent variable, namely the paranormal beliefs results, is presented in Table  0.49. AlWe also observed relationships between EEG frequency bands and the Go/No-Go task performance Fig. . Error i99 . The results in supplementary Fig Besides, a mediation model with inhibitory control  as a dependent variable, paranormal beliefs as an independent variable, frequency bands  as mediators was constructed for each band separately. The Hayes' PROCESS macro for SPSS was also used to test the mediation model58. Beta band oscillations within the cognitive function occipito-frontal network is modulated by inhibitory control100. The top-down control of behavior has been used to illustrate the connection between cognitive processes and frontal beta oscillations101. Compared to instructed decisions, a study found that free decisions were accompanied by higher frontoparietal beta-band coherence102. Similar to the search and repetition phases of this task, free and instructed decisions demand differing levels of inhibitory control44. The "status quo" maintained by this proposed explanation is consistent with an extended theory of beta oscillations43. These authors suggest that when a task has a "strong endogenous top-down component," such activity should be connected to the active maintenance of a cognitive set in the cognitive domain. Furthermore, it's important to note that, like the majority of neurophysiological research on inhibitory control, our evidence for the relationship between beta power and inhibitory control is correlational. The causal mechanisms underlying these associations can only be shown by direct experimental changes in brain activity that concentrate on beta oscillations.Our main results indicate that paranormal believers show reduced beta power compared to skeptics. Additionally, paranormal believers were more impaired in inhibitory control on the No-Go trials, as compared to the skeptics. As expected, lower absolute beta1 and beta2 power activities during resting-state EEG were shown in paranormal believers. Previous studies have shown that a weaker beta band activity in No-Go trials is associated with poor inhibitory control103, is most likely a key player in schizophrenia psychopathology104. Furthermore, the DA levels in neural networks could affect the temporal dynamics of beta oscillations105. For instance, the subthalamic nucleus's beta-band increased when Parkinson’s patients were given the DA precursor Levodopa106. However, it is still speculative at this date to attribute the beta-band impairments in schizophrenia patients to the dopaminergic system. Future studies using combined EEG and positron emission tomography may look into the relationship between beta-band differences in schizophrenia patients and DA. Additionally, concerning the reduction of the beta power in paranormal believers compared to skeptics in the present study, we can refer to the relationship between paranormal experiences and the DA107, as well as lower activity in the rIFG area63. Moreover, beta band differences during EEG resting-state in the lack of stimulant may indicate dopamine depletion in the rIFG area108, which is related to inhibitory control. Additionally, a study found that less constrained firing rates were caused by enhanced dopaminergic transmission in mesolimbic neurons109, and would generate more internal noise and promote, on the phenomenal level, loosened associations, and paranormal beliefs110.From the view of neurochemistry, dopamine (DA), which is essential for stabilizing brain networks3, it is possible to assume that this cognitive deficit may be associated with differences in brain activity. Several studies showed a relationship between paranormal belief and schizotypy, and other characteristics associated with schizophrenia112. Therefore, studies focusing on paranormal phenomena have reported a reduction in gamma band in individuals with high transliminality68, hallucinations, positive schizophrenia symptoms113, and dysfunction in attention and cognition114. Gamma band activity has been related to a broad range of cognitive processes118. Therefore, widespread gamma power in cognitive functions, such as inhibitory control39, may be linked to the feature binding theory in the brain120. Given that the gamma band activity has decreased in paranormal believers in the frontal lobe compared to skeptics, this can also be attributed to the poor inhibitory control in these individuals. From the cognitive neuroscience perspective, the decrease in gamma band activity may be related to neural dysfunction in the frontal lobe121, reflecting impairment in the synchronous inhibition of pyramidal neurons122, and the GABAergic neurotransmission123. Furthermore, previous studies showed that the frontal lobe is involved in higher-order cognitive functions126. Concerning the frontal lobe dysfunction in paranormal beliefs74, the results of the present study also show that in paranormal believers as compared to skeptics, the absolute power of the beta was significantly reduced in the frontal area. These findings indicate that low gamma activity in the frontal lobe and low beta band activity in the frontal lobe may also be associated with the inhibitory control deficit in paranormal believers.Our results showed that in terms of absolute gamma power, paranormal believers showed lower activation in the frontal lobe compared to skeptics. According to the theory of cognitive deficits in paranormal beliefs127. Through alpha power, this mechanism may be related to the GABAergic inhibitory activity via an inter-neuronal network in the brain128, and an unbalance between the GABAergic system and glutamatergic neurotransmission. Alpha power has been associated with the integrity of the cognitive process129, while it has been found to play a critical role in inhibitory control130. The alpha band differences may be associated with a range of information processing deficits such as inhibitory control131.We also found that paranormal believers showed a low absolute alpha power in the bilateral frontal lobe compared to skeptics. Alpha power reflected a neural inhibitory mechanism involved in the influence of external sensory information at the resting-state EEG49. Perhaps, deficiency in inhibitory control is associated with beta band reduction. Additionally, our results demonstrated that all frequency bands combined could explain 49% of the variance in paranormal beliefs, although the model was not significant. This may be due to the small sample size in the present study. However, there was no previous study on the relationship between paranormal beliefs and EEG oscillatory activity, these findings seem to prompt further investigations into correlations with EEG oscillatory activity in large sample size. Additionally, in mediation model analysis, beta2 frequency band activation in the frontal lobe (but not in the whole brain) mediated the relationship between paranormal belief and inhibitory control. However, there was no significant direct effect of paranormal beliefs on inhibitory control. The lack of significant correlations between paranormal beliefs and inhibitory control through frequency bands could in part be due to the small sample size. It may be revealed with larger populations and further studies are required with a large sample size.Our results indicate that paranormal believers showed more errors in both the Go and No-Go trials compared to skeptics. Still, there was only a significant group difference in No/Go trials in the Go/No-Go task Fig. . It seem133. Therefore, future studies are recommended to control the status of female participants. Finally, according to previous studies based on the greater tendency of women to paranormal beliefs135, and due to the small sample size of men and women in each group, it was impossible to examine their performance separately. Therefore, we suggest that gender differences be explored in future studies.We had several limitations in this study. Firstly, convenient sampling and selection of the sample from university students constituted one of the limitations of the present study. Based on these results, future studies could address associations of higher order frequency band oscillations with phenomena related to paranormal belief, such as schizophrenia. Secondly, the sample size in the present study was small. Thirdly, cognitive failures were assessed with a self-reported scale. Future studies using objective methods to assess cognitive failures level, including cognitive and behavioral function tasks, are needed. Another limitation of this study is that no resting EEG with closed eyes was measured. In addition, concerning the participation of women in this study, some studies have reported that performance in cognitive tasks related to the prefrontal cortex might be affected by the levels of estrogen and progesterone hormonesIn summary, the present study shows that paranormal belief is related to the reduced power of the alpha, beta, and gamma frequency bands, and reduced inhibitory control. This study will provide new insights into the role of differences between believers and skeptics in brain activity in paranormal believers.Supplementary Information.


The non-estrogenic 2,5-disubstituted tetrazole core-bearing bisphenol structures (TbB) are being researched as emerging structural congeners of Bisphenol A, an established industrial endocrine disruptor. However, there is no understanding of TbB’s adverse effects elicited via metabolic activation. Therefore, the current study aimed to investigate the metabolism of TbB ligands, with in silico results serving as a guide for in vitro studies. The Cytochrome P450 enzymes (CYP) inhibitory assay of TbB ligands on the seven human liver CYP isoforms  using human liver microsomes (HLM) revealed TbB ligand 223-3 to have a 50% inhibitory effect on all the CYP isoforms at a 10  Cytochrome P450 enzymes (CYP)-mediated metabolism is crucial in new chemical entity (NCE) research since their metabolic profile may influence many biological processes related to the liver that could potentially damage it. Such detrimental effects of an NCE, either in the clinical stage or after commercial use, could result in their withdrawal from the market due to poor metabolic profile. One such classic example of an industrial chemical banned from food contact applications because of its poor metabolic profile is Bisphenol A (BPA). BPA is an important industrial chemical belonging to the family of diphenyl alkanes and is a ubiquitous critical starting material for various polymers  such as BPA is known to leach into food products, and long-term exposure to it is known to be detrimental to health. It is an established endocrine disruptor and has the potential to induce hepatotoxicity via different mechanisms. Endocrine-mediated health effects such as reproductive toxicity, thyroid disruption, immunotoxicity, neurotoxicity, atopic diseases, and metabolic disorders have been reported as a result of BPA exposure . Such touggested . The t-T−1 day−1 . Yoshiha−1 day−1  showed t−1 day−1 .The common BPA replacements like bisphenol F (BPF), bisphenol AF (BPAF), bisphenol S (BPS), tetramethyl bisphenol F (TMBPF), Bisphenol S (BPS), Bisphenol Z (BPZ), Bisphenol M (BPM), etc., have been found to be exerting an endocrine-disrupting effect. Many of the metabolites formed by the biotransformation of BPA replacements were observed to be hydroxylated metabolites and electrophilic species during bioactivation in HLM and CYP isozymes, thus highlighting the need for their detailed toxicity and safety studies ,10,11. TOur recent research on safer BPA replacements highlighted replacing the BPA’s isopropylidene core with a polar core. As a result, there was a decrease in bisphenol estrogenicity. For example, two of the designed NCEs with bisphenol structures (223-2 and 223-3) bearing tetrazole core (TbB) were potentially non-estrogenic by in vitro studies  14]. It. It14]. Therefore, the goal of the current work was to study the metabolism of three 2,5-disubstituted TbB ligands to get an insight into the potential adverse effects, if any, elicited via metabolic activation. Hence, two objectives were defined to accomplish this goal. The first was to understand the CYP inhibition potential of the 2,5-disubstituted TbB ligands by utilizing various in silico methodologies, such as structure- and ligand-based modeling, identifying the site of metabolism (SOM) and molecular dynamic simulations. The second objective was to perform the in vitro analysis in lieu of animal data to understand the inhibition potencies on various CYP isoforms, their time-dependent inhibition, and metabolic stability in human liver microsome (HLM), and cryopreserved human hepatocytes (CPHH) with an understanding for apparent intrinsic clearance, substrate depletion after incubation and TIdeally, lipophilic compounds are converted into more hydrophilic metabolites in xenobiotic metabolism for enhanced excretion. Thus, an NCE entering humans via the oral route passes through the regions of first-pass metabolism, namely, the intestinal wall, followed by the liver. Since the liver is a detoxifying organ, it helps to eliminate these bio-transformed products through various enzymatic phase I and II pathways. On the contrary, xenobiotics or NCEs can also become adversely metabolized before reaching adequate plasma concentrations or inhibiting the enzymes. CYPs inhibitions lead to decreased elimination, thus causing xenobiotic/NCE-drug interactions and provoking adverse drug reactions. On the other hand, adverse metabolism can lead to the generation of reactive metabolites leading to hepatotoxicity. Therefore, it is imperative to gain insight into NCEs’ (such as TbB ligands of the current study) metabolic stability and CYP inhibition potential. Although there are many complexities in predicting metabolic stability and CYP inhibition, such an understanding can still be best gained computationally by parallel ligand and structure-based design approaches, as mentioned in the following sections.The in silico insight into the molecular metabolism/inhibition of the TbB ligands was enabled by performing molecular docking studies. Ideally, in molecular docking, greater interest lies in optimizing the ligand and residue of the ligand binding pocket such that the ligand is bound tightly to the active site, leading to the desired pharmacological effect. However, in the case of docking to CYP, it is the opposite, wherein the interest is to avoid tight binding to decrease or minimize the binding affinity (BA) such that the enzyme does not become inhibited and undesired drug–drug interaction or toxicity is avoided. Therefore, to understand if the TbB ligands were potential inhibitors or non-inhibitors, they were docked into the active site of seven CYPs, namely, CYP2C9, CYP2B6, CYP2C8, CYP1A2, CYP2D6, CYP3A4, and CYP2C19, since the majority of these CYP represents ∼75% of drug metabolism . The P45CYP2C9 is the major enzyme driving phase I metabolism of xenobiotics, and undesirable drug–drug interaction or toxicity occur due to CYP2C9 inhibition . The “6 CYP2C8 has drawn much attention because of its crucial function in understanding clinically significant drug interactions. CYP2C8 has a relatively larger active site (1438 Å3), allowing it to accommodate larger xenobiotic substances . It has CYP2B6 is a highly polymorphic and inducible enzyme that plays a key role in human drug metabolism . VariatiTo prevent pharmacokinetic interactions and to lessen or eliminate the harmful effects of toxicities mediated by xenobiotic metabolism, knowledge of the CYP1A2 inhibition by any xenobiotic is highly beneficial  ThereforCYP2D6 primarily metabolizes compounds containing basic amines such as aromatic amines and an aromatic planar ring due to acidic residues in the active site. The CYP2D6 is known to metabolize more than 20% of the drugs. Key residues such as Asp 301 and Glu 216 attract ligands to the active site . Around CYP3A4 is a broad specificity oxygenase that metabolizes compounds of diverse structures. Its versatility in oxidizing bulky substrates is due to its considerably larger active site than any other CYP; hence, it is responsible for metabolizing more than 50% of the drugs in the market . TherefoIn the case of CYP2C19 active site , H-bond The molecular docking and HYDE prediction provided insightful information on how avidly the ligands bind to a given P450 enzyme. Molecular docking suggested that in some of the CYP, the atoms of some poses are within the 6 Å of the heme iron; however, to corroborate prediction of the metabolism site (SOM), which is key to understanding the ligand’s metabolic stability or instability, the additional computational tools were utilized such as DFT , the ADMXenoSite Cytochrome P450 Prediction Models predict atoms on a molecule that a specific CYP enzyme could likely oxidize. XenoSite provides visual output wherein a color gradient labels the potential SOMs, referring to the atom in a molecule that is metabolically labile and prone to metabolic reactions. For efficient visualizations of metabolism in a molecule, the major SOM is identified based on the color coding of the probability scale. In the default mode “background,” blue, white, and red colors are used. A zero probability of metabolism is represented by blue, a probability equal to the background probability of observing a SOM at random is represented by white, and a probability of 1.0 is indicated by red. Computational modeling graphical outputs highlighting metabolic reactivity and SOMs for the TbB ligands are displayed as a metabolic landscape in CYP’s are known to catalyze the oxidation of bisphenols, for example, BPA and, in one instance, as reported by Atkinson A. et al. ,28. BPA From the molecular docking studies discussed in the previous section, it is understood that the TbB ligands show two binding motifs wherein, in a certain CYP binding pocket, there is direct interaction with heme iron, and in others, there is interaction with amino acids in the hydrophobic distal pocket without coordinating the heme iron. Since the molecular docking is considered static and to better understand the steadiness and conformation stability of the three TbB ligand-CYP complexes, 50 ns MD simulations were performed. The trajectories of MD simulations were studied to determine the accessibility and binding of the TbB ligand in each of the CYP isoforms.After the completion of MD simulations, the relative binding free energy (BE) of the three TbB ligands was analyzed, as the heatmap shown in The free energy of the binding heat map presented in The free energy of the binding heat map presented in The regulatory bodies and pharmaceutical firms are quite concerned about CYP inhibition. Therefore, medicinal chemists often change the lead structure to decrease CYP inhibition. If left uncorrected, it can cause DDIs, enhanced drug concentration, and, thus, toxicity. Hence, to understand the CYP inhibition, the in vitro metabolism of TbB ligands by human CYP involving most common isoforms such as CYP2C8 (Amodiaquine), CYP2D6 (Dextromethorphan), CYP2C9 (Tolbutamide), CYP2B6 (Bupropion), CYP3A4 (Midazolam), CYP1A2 (Phenacetin) and CYP2C19 (S-Mephenytoin) using their respective probe substrates at single concentration of 10 The TbB ligands 223-2, 223-3, and 223-10 exhibited an inhibition effect of above 50% on CYP2C9, whereas only 223-3, 223-10 exhibited inhibition on CYP2B6 and CYP2C8. The TbB ligand 223-3 was observed to have an above 50% inhibitory effect on all the CYP isoforms except CYP1A2. Thus, the potential clinical interaction between 223-3 and these CYPs would be significant. The possible reason for such observation could be that the binding site of metabolizing enzymes is generally lipophilic; hence, these enzymes more readily accept lipophilic molecules. Since 223-3 is comparatively more lipophilic than 223-2 and 223-10 , hence mCurrently, an understanding of metabolic stability of the three 2,5-disubstituted TbB ligands is unavailable. Such an understanding using a substrate depletion assay is required to comprehend their toxicological profile. Consequently, investigations using microsomes together with hepatocytes were carried out to obtain more thorough information to understand the different clearance pathways by CYP or non-CYP enzymes. This approach is also very valuable as it allows the investigation of the total cytochrome P450-mediated metabolism of TbB ligands without the need for complete knowledge of the metabolites. Further, it enables understanding the enzyme kinetics since this approach encompasses all the activity of the CYPs and all the biotransformation pathways involved in the metabolism.Microsomal stability was determined for the TbB ligands by monitoring the presence of compound after incubation in CPHH and HLM, as shown in 1/2 .From the plot shown in According to the results, the test compound is extensively depleted in CPHH compared to HLM, thus resulting in significant parent compound depletion. Multiple factors can cause intrinsic clearance by CPHH to differ from HLM . AdditioCYP inhibition evaluation is typically performed by either IC50 at single-point or IC50 Shift or abbreviated assay such as the first-order inactivity rate constant , and considered to be inactive, harmless, and excretable. However, on the contrary, these metabolites can also be formed with higher or equivalent toxicity when compared to the parent ligand. Therefore, to gain such an understanding of metabolite toxicity, 223-2 TbB ligand was shortlisted for metabolite identification (MetID) studies as it was the least prominent CYP inhibitor among the three TbB ligands studied for CYP inhibition, as discussed in earlier sections. The metabolites’ detection and identification were accomplished by utilizing the high-resolution LC-MS/MS (HR LC-MS/MS) technique and the obtained fragmentation pattern was subsequently analyzed to propose putative structures as discussed in the following paragraph. MetID studies was initiated first for the parent 223-2 ligand by HR LC-MS/MS as its fragmentation understanding could act as a guide to potentially identify the metabolites formed after incubation with hepatocytes. Since the 223-2 TbB ligand contain N and O atoms, it could be easily protonated and it was sensitive in positive ionization mode. Consequently, it was studied using the positive fragmentation pattern by ESI-MSTo understand the fragmentation pattern of the parent compound, EPI spectrum was analyzed. Three fragment ions 347.2, 332.0 and 315.0 m/z were considered to propose the possible fragmentation. On closer observation of the ESI-MSown in α .The current study provides insight into the metabolism of 2,5-disubstituted tetrazole core-based bisphenol structures. While the scientific consensus indicates that most bisphenol replacements are EDCs whose metabolites have potential toxicity, the current study highlights no potential adverse effect by metabolic activation of polar TbB ligand 223-2. The present study provides a new approach to rethink the existing paradigm for developing safer BPA replacements utilizing the polar heterocyclic core. First, of its instance, our findings highlight the likelihood of tetrazole core-based bisphenol derivatives as privileged compounds for prospective bisphenol replacement. The current study emphasizes opportunities for introducing other heterocycle-based structural motifs into the bisphenol core, thus providing a newer dimension for developing more unique ligands as potential BPA replacement while posing no risk of deleterious metabolic activation effects.https://www.rcsb.org/, accessed on 21 January 2022 ). Polar hydrogen atoms were added to the protein structure before docking after the water and native ligands were taken out. YASARA molecular modeling software was used to prepare ligands before docking [Molecular docking was carried out using seven crystal structures: CYP2C9 (PDB code: 4NZ2), CYP2C8 (PDB code: 2NNI), 2B6 (PDB code: 3IBD), 1A2 (PDB code: 2HI4), 2D6 (PDB code: 4WNV), 3A4 (PDB code: 4D6Z), and 2C19 (PDB code: 4GQ6) after downloading the same from the RCSB data bank   an implemented scoring function in SeeSAR 12.0 enabled the calculation of the BA post docking . HYDE scThe molecular dynamic simulation of the seven CYP crystal structures was run with YASARA . The setThe three 2,5-disubstituted TbB ligands—223-2, 223-3, and 223-10, were available in-house. They were synthesized by 1,5-dipolar cyclization of arylazoaryldiazomethane as they are not commercially available. The synthesized tetrazole derivatives bearing bisphenol structures were analyzed by high-pressure liquid chromatography (HPLC), high-resolution mass spectrometry (HR-MS spectroscopy),  ligands .Using HLM as the enzyme source, the CYP inhibition potential was employed to assess the inhibitory effect of the TbB ligands on the CYP1A2, 2B6, 2C8, 2C9, 2C19, and 2D6 3A4 isoforms. Phenacetin , tolbutamide , bupropion , mephenytoin , midazolam , amodiaquine , and dextromethorphan  were used as probe substrates. The test substance included TbB ligand  and HLMs , with or without 1.0 mM NADPH. The reaction was started by adding pre-incubated 25 By preincubating a test substance for 5 minutes in phosphate buffer (pH 7.4) at 37 °C in shaking water bath, the stability of the test substance was examined in pooled HLM. After NADPH-generating systems addition, the reaction gets initiated and post incubation for 0, 15, 30, 45, and 60 min, the reaction is terminated with addition of acetonitrile/methanol to the incubation mixture. Supernatant obtained after mixing and centrifuging the sample is analyzed by HPLC-MS/MS. Microsomal protein for final use is at 0.1 mg/mL concentration. Four compounds, namely, propranolol and imipramine, known to be relatively stable, and verapamil and terfenadine, known as readily metabolizing in HLM, were included in each assay. Post HPLC-MS/MS of the samples, data are analyzed by considering test compounds peak area at each time point to time zero. Assuming the reaction to follow first-order kinetics, the slope of the initial linear range of the logarithmic curve of remaining compound (%) vs. time is considered to calculate the half-life. Additionally, the half-life is utilized to calculate the intrinsic clearance (CLint) as shown in the following equation.The test compound stability in a pooled human cryopreserved hepatocytes was tested after thawing, washing, and resuspending the cryopreserved hepatocytes in Krebs–Heinslet buffer (pH 7.3). The onset of reaction happens by the addition of the test compound into cell suspension and incubated for 0, 30, 1, 1.5, and 2 h, respectively, at 37 °C/5% COThe time-dependent inhibition (TDI) potential of test compounds against CYP1A2, 2B6, 2C8, 2C9, 2C19, 2D6, 3A4/5 isoforms were determined using Human liver microsomes. Assay is performed in 96-deep well plate format (n = 1). Positive controls and DMSO as negative control in each assay. To obtain 100 A liquid chromatography–high resolution mass spectrometer (LC-MS/MS 5500 + QTRAP) was utilized for the metabolite’s identification formed during the MetID studies. A gradient elution using the mobile phase A (containing water and 0.1% of formic acid) and mobile phase B (containing acetonitrile and 0.1% of formic acid) was used for separation on Phenomenex, Luna C18, 100 A, 5 This study investigated the in silico and in vitro metabolism of 2,5-disubstituted tetrazole derivatives-based bisphenols (TbB). The CYP inhibition assay results in a single concentration of 10


Soybean oil body (SOB) has potential as a milk fat substitute due to its ideal emulsification, stability and potential biological activity. In this study, SOB was used as a milk fat substitute to prepare ice cream, expecting to reduce the content of saturated fatty acid and improve the quality defects of ice cream products caused by the poor stability of milk fat at low temperatures. This study investigated the effect of SOB as a milk fat substitute (the substitution amount was 10–50%) on ice cream through apparent viscosity, particle size, overrun, melting, texture, sensory and digestive properties. The results show SOB substitution for milk fat significantly increased the apparent viscosity and droplet uniformity and decreased the particle size of the ice cream mixes, indicating that there were lots of intermolecular interactions to improve ice cream stability. In addition, ice cream with 30% to 50% SOB substitution had better melting properties and texture characteristics. The ice cream with 40% SOB substitution had the highest overall acceptability. Furthermore, SOB substitution for milk fat increased unsaturated fatty acid content in ice cream and fatty acid release during digestion, which had potential health benefits for consumers. Therefore, SOB as a milk fat substitute may be an effective way to improve the nutritional value and quality characteristics of dairy products. Ice cream has good flavor and texture as a consumer-friendly frozen dairy product. Ice cream, as an oil-in-water frozen aerated emulsion, contains partially agglomerated fat globules, unfrozen viscous whey, ice crystals and air bubbles . GeneralSoybean oil body (SOB) is lipid-storing organelles in soybean with a particle size in the approximate range of 0.4–2.0 μm . The purIn this study, SOB was served as a milk fat substitute to prepare ice cream, expecting to reduce the content of saturated fatty acid and improve the quality defects of ice cream products caused by the poor stability of milk fat at low temperatures. The apparent viscosity, particle size, melting properties, chemical composition, microstructure and digestive properties of ice cream were characterized to explore the consequence of SOB as a milk fat substitute on ice cream quality. While improving the beneficial ingredients and quality of ice cream to further determine the application value of SOB in ice cream, this study provides a theoretical underpinning for expanding the application of SOB in the food industry and also supplies innovative ideas for the development of healthy frozen foods.Soybeans were obtained from the Soybean Institute of Northeast Agricultural University . Skimmed milk powder was purchased from Inner Mongolia Yili Industrial Group Co., Ltd. . Vast cream was purchased from Qingdao Nestle Co., Ltd. .g, 4 °C, 20 min) to collect the precipitation. The precipitation was resuspended in 20% sucrose solution and centrifuged . This step was repeated three times to obtain SOB and sterilized at 100 °C for 20 min.The preparation method of SOB referred to the description of Zhou et al., . Brieflyw/w), granulated sugar , egg yolk , cream  and water were mixed and filtered. Among them, SOB was used to replace cream according to 0% (control group), 10%, 20%, 30%, 40% and 50% of the amount of cream. Then, the above mixture was homogenized , pasteurized  and aged  to obtain the ice cream mixes. Finally, the ice cream mixes were whipped and frozen for 30 min and hardened  to obtain ice cream samples.Skimmed milk powder  and flow behavior index (n).The method for the determination of the steady shear rheological properties of ice cream mixes referred to the description of Jiang et al., and was modified . The stew/v) and measured by laser particle size distribution analyzer . Droplet size measurements were reported as surface average diameter , volume average diameter  and median diameter (D50).The measuring method of average particle diameter referred to the report of Zhao et al., . The ice0 and the mass of the ice cream sample was recorded as W1:The overrun of ice cream was measured according to the method of Pon et al., . Equal vThe determination method of the melting properties referred to the description of Kurt et al., . The iceThe hardness, adhesiveness, springiness and chewiness of ice cream samples were determined by texture analyzer . The specific parameters are as follows: the texture analyzer probe was P/5, the probe diameter was 5 mm, the pre-measurement rate was 8 mm/s, the mid- and post-measurement rate was 2 mm/s, the penetration depth was 15 mm and the trigger force was 20 g.L* value represented the light dark value, a* represented the red green value and b* represented the yellow blue value. The flavor of the ice cream samples was determined by electronic nose.The chemical composition of the ice cream was determined according to AOAC . The conThe observation method of ice cream microstructure referred to the report of Zhou et al., and was modified . The micThe sensory evaluation system is established by using the fuzzy mathematical model. The sensory scoring standard was shown in 1, u2, u3, u4}, where u1, u2, u3 and u4 represented the color, taste, texture and flavor of ice cream, respectively. The sensory evaluation comment set was established V = {v1, v2, v3, v4}, where v1, v2, v3 and v4 represented excellent, good, medium and poor, respectively. The middle score of each grade was selected as the final sensory score, V = {9, 7, 5, 3}.Then, according to the sensory evaluation index, the index set was established. U = {u1, x2, x3, x4}.In addition, 10 professionally trained sensory panelists  performed a weighted analysis on the color, taste, texture and flavor of ice cream samples. The frequency statistics method was adopted to determine the weight of each evaluation index. The weight set was X = {xFurthermore, the fuzzy matrix was established. The 10 sensory panelists scored ice cream samples based on color, taste, texture and flavor. The final votes for each grade  were counted. Fuzzy matrix R was the number of votes at each grade divided by the total number of sensory panelists. Fuzzy relation evaluation set was Y = X × R. Sensory score was T = Y × V.2PO4, 13.6 mmol NaHCO3, 0.15 mmol MgCl2(H2O)6, 0.06 mmol (NH4)2CO3, 0.075 mmol CaCl2(H2O)2 and 50 mg ptyalin  were dissolved in deionized water with constant volume to 500 mL and adjusted pH to 6.8.Preparation of artificial saliva: 15.1 mmol KCl, 3.7 mmol KH2PO4, 25 mmol NaHCO3, 47.2 mmol NaCl, 0.1 mmol MgCl2(H2O)6, 0.5 mmol (NH4)2CO3, 0.075 mmol CaCl2(H2O)2 and 106 U pepsin were dissolved in deionized water with constant volume to 500 mL and adjusted pH to 2.0.Preparation of artificial gastric juice: 6.9 mmol KCl, 0.9 mmol KH2PO4, 85 mmol NaHCO3, 38.4 mmol NaCl, 0.33 mmol MgCl2(H2O)6, 0.3 mmol CaCl2(H2O)2 160 mmol bile salt and 5 × 104 U trypsin were dissolved in deionized water with constant volume to 500 mL and adjusted pH to 7.0.Preparation of artificial intestinal juice: 6.8 mmol KCl, 0.8 mmol KHv/v) and digested for 5 min at 100 rpm/min on a 37 °C incubator shaker. Then, the artificial saliva digesta was mixed with artificial gastric juice  and digested for 60 min at 100 rpm/min on a 37 °C incubator shaker. Finally, the artificial gastric digesta was mixed with artificial intestinal juice  and digested for 120 min at 100 rpm/min on a 37 °C incubator shaker. Finally, the digesta were placed at −80 °C to terminate the reaction and stored. In addition, the artificial saliva, artificial gastric juice and artificial intestinal juice were replaced with equal volumes of deionized water in the control sample (undigested ice cream dilution sample).The digestion model in vitro was constructed according to the method of Ma et al., . Briefly1 (μL), the concentration of NaOH was recorded as C1 (mol/L) and the digest volume was recorded as V2 (mL):The pH-stat method was used to measure the content of the free fatty acids released in simulated intestinal juice digestion  according to the method of Hageman et al., . Changesg and the supernatant was taken. The protein content of each supernatant was then determined using the BCA protein assay kit. The protein content remaining in the digesta was recorded as C1 and the protein content in the control sample (undigested ice cream dilution sample) was recorded as C2. The formula for calculating the protein digestibility was as follows:The determination method of protein digestibility followed the previous report of Li et al., . An amouThe experiment method referred to the description of Nikiforidis et al., and was improved . Brieflyp < 0.05 represented significant difference with Duncan’s test.All results were the mean of three independent replicates and expressed as mean ± standard deviation. One-way analysis of variance (ANOVA) was used with SPSS statistics software . The apparent viscosity is a crucial indicator reflecting the flow behavior and the taste of ice cream. The sample exhibited shear thinning behavior shown in ) and particle size distribution of droplets are effective indicators for evaluating the stability of ice cream mixes and the degree of droplet coalescence and are important for improving the sensory properties of food products  of ice cream increased significantly, which may be due to the binding of anionic mucins in saliva to the positive charges of droplet surface proteins, depleting the interaction between droplets and causing aggregation, resulting in the increase of D  of ice cream digesta increased significantly when digested in simulated gastric juice for 20 min. This result was because the gastric juice was acidic and contained various protein hydrolase, thus the casein micelles and fat globule surface proteins in ice cream samples were denaturation, hydrolyzed and aggregated  of the digesta increased  of the full milk fat ice cream digesta was significantly higher than that of the ice cream with SOB substitution, which may be because the surface protein of milk fat globules was more easily hydrolyzed by pepsin than the surface protein of SOB, thereby destabilizing the ice cream emulsion system, resulting in digesta particle size increase. Furthermore, with the increase of digestion time in gastric and intestinal juice, the flocculated protein was decomposed by protease, resulting in the decrease of D of ice cream digesta  of ice cream digesta with SOB substitution was always smaller than that of full milk fat ice cream digesta and the D of digesta decreased with the increase of SOB substitution amount. This meant that the ice cream with SOB substitution was easier to digest and absorb than full milk fat ice cream.The particle size of ice cream in vitro digestion was shown in f D . In addigregated . Meanwhincreased . In part digesta . Among tThe intestine is the main place for fat digestion and release, which transforms fat into absorption forms through interaction with pancreatic and bile secretions . The freThe protein digestibility of ice cream in vitro digestion was shown in This study provided new insights into ice cream prepared with SOB as a milk fat substitute. SOB substitution for milk fat not only decreased the content of saturated fatty acids in ice cream, but also improved the quality defects of ice cream products caused by the poor stability of milk fat at low temperatures. SOB substitution for 40–50% milk fat could improve the stability of ice cream by increasing the apparent viscosity and decreasing the particle size of the ice cream mixes, which made the ice cream form the desired quality. Therefore, ice cream prepared substitution 40–50% SOB for milk fat had ideal physicochemical properties and potential biological activity. Among them, the ice cream prepared substitution 40% SOB for milk fat had the best sensory acceptability and had the potential for practical application. This study provided a significant theoretical underpinning for the application of SOB in dairy products.


Photosystem I (PSI) with its associated light-harvesting system is the most important generator of reducing power in photosynthesis. The PSI core complex is highly conserved, whereas peripheral subunits as well as light-harvesting proteins (LHCI) reveal a dynamic plasticity. Moreover, in green alga, PSI–LHCI complexes are found as monomers, dimers, and state transition complexes, where two LHCII trimers are associated. Herein, we show light-dependent phosphorylation of PSI subunits PsaG and PsaH as well as Lhca6. Potential consequences of the dynamic phosphorylation of PsaG and PsaH are structurally analyzed and discussed in regard to the formation of the monomeric, dimeric, and LHCII-associated PSI–LHCI complexes. Light-induced primary charge separation occurs between the primary electron donor (P700) and acceptor (A0). The reduced A0 donates an electron to iron–sulfur cluster FX via phylloquinone (A1). These redox components as well as most antenna pigments are located on a heterodimer of the two homologous subunits encoded by the chloroplast psaA and psaB genes. Reduced FX forwards an electron to iron–sulfur cluster FA and subsequently to the other iron–sulfur cluster FB that reduces ferredoxin (FDX) as the terminal electron acceptor of PSI. FDX in turn reduces the FDX-NADP-reductase (FNR), leading to the formation of NADPH. The core of PSI further harbors approximately 100 Chls [Arabidopsis thaliana, an additional Lhca1-a4 dimer was found to be bound on the PsaL side [The core of photosystem I (PSI) is highly conserved from cyanobacteria to vascular plants . The lig100 Chls , which s100 Chls . For exa100 Chls . On the 100 Chls , while P100 Chls . NotablysaL side , suggestChlamydomonas reinhardtii [A. thaliana [C. reinhardtii [C. reinhardtii contains two LHCII trimers (termed as LHCII-1 and LHCII-2) [Binding of LHCII to PSI is a common incidence in most organisms of the green lineage and driven by a process called state transitions . State tnhardtii  or STN7 thaliana . High-rethaliana  and C. rnhardtii   . The LHCLHCII-2) . LhcbM5 LHCII-2) . MoreoveLHCII-2) . These tC. reinhardtii where two copies of Lhca9 tethered two monomeric PSI in a head-to-head fashion, forming a large oligomeric protein complex  be envisioned? Possible key players in the remodeling regulation are likely PsaH and Lhca2. PsaH is an 11-kDa transmembrane protein that is imported into chloroplasts and peripherally associates with the PSI reaction center on the opposite side to the LHCI belt . PsaH knphically . Moreovephically . A recendetected . All thereported . The prethaliana  may indithaliana ,36. Thusnhardtii  or acetythaliana . In C. rtor side . It is pe mutant , which porylated . In the nd Lhca9 ,40. Notand Lhca9 . This inIn the current manuscript, we revisited PsaH and PsaG phosphorylation and reveal that in three independent WT strains, phosphorylation is significantly up-regulated for both proteins. The impact of PsaH and PsaG protein phosphorylation on structure and function of PSI is discussed.C. reinhardtii strains CC-124, CC-125, and CC-4375 IFT46::YFP [−2 s−1 under a 16 h light/8 h dark cycle. One day before the experiment, cells were diluted to 3 µg Chl/ml. Normal light (NL) samples were taken 3 h after the onset of light (NL) and centrifuged for 5 min at 2500× g to pellet the cells. The remaining cultures were diluted to 3 µg Chl/ml and transferred to continuous high light . HL samples were taken after 24 h as described above. The experiment included four replicates per strain and light condition.T46::YFP  were groT46::YFP  on a shag for 10 min to pellet cell debris. Protein concentration in the supernatant was determined by BCA assay . A lysate volume corresponding to 100 µg of protein was tryptically digested according to a modified FASP (Filter-aided sample preparation) protocol [g at room temperature. SDS removal and alkylation of cysteines was achieved by addition of 200 µl of 100 mM Tris-HCl/8 M urea/10 mM TCEP/40 mM chloroacetamide, followed by centrifugation as described above. The detergent removal and alkylation step were repeated three times. Subsequently, samples were washed four times with 200 µl of 100 mM ammonium hydrogencarbonate. Then, trypsin  was added to the filters at a protein-to-enzyme ratio of 50:1. Digestion was carried out overnight at 37°C. Peptides were harvested by centrifugation and trifluoroacetic acid (TFA) was added to a final concentration of 0.5%.To disrupt the cells and extract proteins, lysis buffer (100 mM Tris-HCl (pH 8.5)/1 mM benzamidine/1 mM PMSF/10 mM sodium fluoride/1 mM sodium orthovanadate/10 mM sodium pyrophosphate/10 mM β-glycerophosphate/2% (w/v) SDS) was added to the cell pellets and samples were incubated for 15 min at 65°C in a Thermomixer at 1000 rpm, followed by centrifugation at 20000× protocol . Brieflyg. Membranes were washed twice with 200 µl of 0.1% TFA before peptides were eluted in 100 µl of 60% (v/v) acetonitrile/0.1% TFA. Eluates were briefly mixed and each sample was split into two aliquots: a sample volume corresponding to 10 µg of peptides was used directly for characterization of the proteome (‘nonenriched’), whereas the remaining 90 µg was subjected to phosphopeptide enrichment prior to LC-MS/MS analysis (‘enriched’).Peptides were desalted using C18 membranes (7 mm diameter), cut from Empore C18 extraction membranes (Sigma) using a stencil, and inserted into MobiCol spin columns, sandwiched between two frits . The columns were conditioned and equilibrated using 80% (v/v) acetonitrile/0.1% TFA and 0.1% TFA, respectively. Then, the samples were loaded on the columns followed by centrifugation for 2–5 min at 1000× 2 . TiO2 (1 mg per sample) was activated once with acetonitrile and equilibrated three times with loading buffer  acetonitrile/5% (v/v) TFA/1 M glycolic acid). Then, LB was added to obtain 10% (w/v) TiO2 slurry. Peptide samples were resuspended in 50 µl of LB, then added to 10 µl of TiO2 slurry and the mixture was incubated for 1 h at room temperature at 1200 rpm in a Thermomixer (Eppendorf). Afterward, the slurry was transferred to in-house made C18 STAGE tips . Buffer volume was 80 µl throughout. The buffer was removed and the TiO2 beads were washed twice each with LB and 1% (v/v) acetonitrile/0.1% (v/v) TFA (W1). Nonphosphorylated peptides that bound to the C18 plug were removed by two washes with 80% (v/v) acetonitrile/0.1% (v/v) TFA (W2). Weakly and moderately strongly bound phosphopeptides were eluted from the TiO2 and onto the C18 material by six successive washes with 0.4 M NaH2PO4/1% (v/v) acetonitrile/0.1% TFA. Phosphopeptides were washed once with W1 and subsequently eluted with 60% (v/v) acetonitrile/0.1% (v/v) TFA (fraction 1). Strongly bound phosphopeptides were eluted with 5% ammonia (fraction 2). Phosphopeptides that had detached from TiO2 by the ammonia treatment and bound to the C18 plug despite the high pH were washed once with W1, followed by elution with 60% (v/v) acetonitrile/0.1% (v/v) TFA (fraction 3). All fractions were dried by vacuum centrifugation and stored at –80°C until further use.Phosphopeptides were enriched by metal oxide affinity chromatography (MOAC) using TiO8, Sigma ). The foDried peptide samples were reconstituted in 5 µl of 2% (v/v) acetonitrile/0.05% (v/v) TFA in LC/MS grade water. Samples were analyzed on an LC-MS/MS system consisting of an Ultimate 3000 NanoLC (Thermo Fisher Scientific) coupled via a Nanospray Flex ion source (Thermo Fisher Scientific) to a Q Exactive Plus mass spectrometer (Thermo Fisher Scientific). Peptides were concentrated on a trap column  for 3 min using 4% (v/v) acetonitrile/0.05% (v/v) in LC/MS grade water at a flow rate of 10 µl/min. The trap column was operated in back-flush mode, allowing the transfer of peptides on a reversed-phase column  for chromatographic separation. The buffers used were 0.1% (v/v) formic acid in ultrapure water (A) and 0.1% (v/v) formic acid/80% (v/v) acetonitrile in ultrapure water (B). The gradient was programmed as follows: 5% B to 36% over 160 min, 36% to 99% B over 10 min, and 99% B for 20 min. Flow rate was 300 nl/min. The mass spectrometer was operated in data-dependent acquisition mode (‘Top12’), alternating between one MS1 full scan and up to 12 MS2 scans. Full scans were acquired with the following settings: AGC target 3e6, MS1 resolution 70000, maximum injection time 50 ms, scan range: 300–1400 m/z. Settings for MS were: AGC target 5e4, resolution 17500, MS2 maximum injection time 80 ms (200 ms for enriched samples), intensity threshold 1e4, normalized collision energy 27 (HCD)).MS raw data obtained from nonenriched and enriched samples were searched separately with MaxQuant  againsthttp://proteomecentral.proteomexchange.org) via the PRIDE partner repository [Protein LFQ intensity and phosphorylation site intensity data were preprocessed in Perseus : Intenspository  with theChlamydomonas PSI dimer (PDB ID: 7ZQD), PSI-10Lhca (PDB IDs: 6JO5 and 6IJO), and PSI–LHCI–LHCII (PDB ID: 7DZ7).Structural models were generated using PyMOL , UCSF Chimera , ChimerC. reinhardtii grown under NL and HL conditions. Here, our main focus was on PSI phosphorylation. To analyze photosynthetic protein phosphorylation, the algae were cultivated photo-autotrophically in TP medium under a diurnal light regime (16 h light/8 h dark) in NL (60 µmol photons m−2 s−1) for 1 week and then shifted to continuous HL (500 µmol photons m−2 s−1). Samples were taken right before and 24 h after the transfer. After tryptic digestion, peptide samples were split: one aliquot was analyzed directly by LC-MS/MS to obtain information about changes in protein abundances, while another aliquot underwent phosphopeptide enrichment for subsequent phosphoproteomic analysis. To identify differences in protein abundances and phosphorylation that were independent of a genetic background, three C. reinhardtii strains were used in the experiment  and quantitative proteomics data of all strains were combined. In total, 12001 phosphorylation sites from 3337 proteins were identified. After filtering, 2403 quantified phosphorylation sites remained. Differential expression analysis using Limma [We were interested in light-dependent regulatory processes that may affect protein–protein interactions within the photosynthetic protein complexes and therefore compared the phosphoproteomes of ng Limma  (implemeng Limma ) revealeng Limma ,57 and a6f subunit PETO changed in abundance similarly to PSI subunits. The amounts of PETO T161 and S187 residues, which also correspond to a STT7-dependent phosphorylation [Phosphorylation of PSI subunits PsaG  and PsaH (S50) increased from 1.7 to 5.7-fold in response to HL , PSI–LHCI–LHCII , and PSI dimer (PDB ID: 7ZQD), respectively. The PsaG and PsaH subunits are highlighted in different representations. It is of note that the PsaH subunit is present in the state transition complex, while the PsaG is present in all of these structures. Contrastingly, the PsaH has also been observed in PSI–LHCI supercomplex (PDB ID: 6IJO) [The potential impact of increased phosphorylation of PsaG  and PsaH (S50) was further analyzed on a structural level. D: 6IJO) ; howeverSuperposition of PsaL subunits from PSI dimer and PSI–LHCI–LHCII shows a clear tilting of R158 in PsaL subunit of PSI–LHCI–LHCII toward the pS50 in PsaH, thereby implying that this phosphorylation probably aids in stabilizing PsaH subunit in PSI A. Compar6JO5); 143–156 in PSI dimer) in PsaL near the pS50 of PsaH and pT27 of LhcbM1 during state transitions (7DZ7 and 7D0J) but found distorted in the monomeric and dimeric PSI structures. Surprisingly, this loop of PsaL contains the key residues involved in stabilizing the PsaH as well as state transition complexes, such as residues K149 and R154. Though unresolved in the monomeric PSI structures, residue R158 has recently been resolved in the PSI dimer structure (PDB ID: 7ZQD), but it rather points away from pS50 of PsaH, as elaborated above. C. reinhardtii indicate that a stable PSI–LHCI–LHCII complex can exist without phosphorylation of S50. Yet again, there is also a possibility that PsaH S50 could get phosphorylated later when a state II complex has already been formed, thereby further contributing toward the stability of PsaH under this transition. Another possible reason for the phosphorylation of PsaH S50 and stabilization of nearby loop in PsaL could be attributed to the prevention of PSI dimerization under HL, as the structural alignment between PSI–LHCI–LHCII and PSI dimer complexes reveal that they are mutually exclusive, as dimer formation would clash with the physical features of the state transition complex [Moreover, structural alignments indicate the stabilization of a loop .Phosphoproteomic analysis identified the phosphorylation of four residues, namely pS65, pT66, pT71, and pT72, in the loop of PsaG located on the stromal side of PSI. Interestingly, this loop (residues 63–85), together with a short helix  residue of PsaG in the state transition complex, which are 6.4 Å apart from each other. However, the shortest distance between these two residues is 10.9 Å in the PSI dimer. Furthermore, superposition of PsaG from PSI dimer and the state transition complex reveals a change in conformation in some residues near the Lhca1 pole. Such a change is dramatic for the PsaG F63 and D64 , subsequently giving rise to additional interactions with the PsaB subunit in state transition complex. Pi–Alkyl interactions, for instance, could be observed for F63 of PsaG with R301 and A304 of PsaB  which, on the other side, are not evident in the PSI dimer. Interestingly, this is the region where the phosphorylated residues (pS65 and pT66) also occur. It is well-known that phosphorylation has the ability to modify the structural conformation of a protein ,63. TherC. reinhardtii is induced by HL [C. reinhardtii [C. reinhardtii, phosphorylation of PsaH is STT7 independent [Arabidopsis, where closely packed PSI dimers were more abundant in the dark state [C. reinhardtii [Previously, it has been shown that state transition in ed by HL . PsaG phnhardtii , thus inependent  but alsoependent . Due to ependent . In thisependent  and/or aependent . Likewisependent  under HLrk state . In thisnhardtii . Thus, dC. reinhardtii reveal dynamic phosphorylation in response to different light conditions. Structural analysis indicates that the phosphorylation of PsaH subunit at position S50 seems to be important for its stabilization to the PSI, ultimately facilitating the state transition complexes. On the other hand, phosphorylation of PsaG subunit appears to be important for the formation of both PSI dimer and state transition complexes due to stabilization of PsaG and Lhca9 to the PSI. Moreover, besides phosphorylation, stabilization of loops in PsaG and PsaL subunits appear to further aid these processes as they harbor several key residues engaged in either direct interaction with the phosphorylated residues or providing additional interacting partners for the stabilization of subunits necessary for the dimerization of PSI as well as formation of the state transition complexes in green algae.Conclusively, the PsaG and PsaH subunits of PSI in Click here for additional data file.Click here for additional data file.