Single-molecule theory of enzymatic inhibition

Use of a small molecule microarray screen to identify inhibitors of the catalytic RNA subunit of Methanobrevibacter smithii RNase P

Despite interest in developing therapeutics that leverage binding pockets in structured RNAs-whose dysregulation leads to diseases-such drug discovery efforts are limited. Here, we have used a small molecule microarray (SMM) screen to find inhibitors of a large ribozyme: the Methanobrevibacter smithii RNase P RNA (Msm RPR, ∼300 nt). The ribonucleoprotein form of RNase P, which catalyzes the 5'-maturation of precursor tRNAs, is a suitable drug target as it is essential, structurally diverse across life domains, and present in low copy. From an SMM screen of 7,300 compounds followed by selectivity profiling, we identified 48 hits that bound specifically to the Msm RPR-the catalytic subunit in Msm (archaeal) RNase P. When we tested these hits in precursor-tRNA cleavage assays, we discovered that the drug-like M1, a diaryl-piperidine, inhibits Msm RPR (KI, 17 ± 1 μM) but not a structurally related archaeal RPR, and binds to Msm RPR with a KD(app) of 8 ± 3 μM. Structure-activity relationship analyses performed with synthesized analogs pinpointed groups in M1 that are important for its ability to inhibit Msm RPR. Overall, the SMM method offers prospects for advancing RNA druggability by identifying new privileged scaffolds/chemotypes that bind large, structured RNAs.

Constructing efficient strategies for the process optimization by restart

Optimization of the mean completion time of random processes by restart is a subject of active theoretical research in statistical physics and has long found practical application in computer science. Meanwhile, one of the key issues remains largely unsolved: how to construct a restart strategy for a process whose detailed statistics are unknown to ensure that the expected completion time will reduce? Addressing this query here we propose several constructive criteria for the effectiveness of various protocols of noninstantaneous restart in the mean completion time problem and in the success probability problem. Being expressed in terms of a small number of easily estimated statistical characteristics of the original process (MAD, median completion time, low-order statistical moments of completion time), these criteria allow informed restart decision based on partial information.

Phytochemical Analysis, Biological Activities, and Molecular Docking Studies of Root Extracts from Paeonia Species in Serbia

Without being aware of their chemical composition, many cultures have used herbaceous peony roots for medicinal purposes. Modern phytopreparations intended for use in human therapy require specific knowledge about the chemistry of peony roots and their biological activities. In this study, ethanol-water extracts were prepared by maceration and microwave- and ultrasound-assisted extractions (MAE and UAE, respectively) in order to obtain bioactive molecules from the roots of Paeonia tenuifolia L., Paeonia peregrina Mill., and Paeonia officinalis L. wild growing in Serbia. Chemical characterization; polyphenol and flavonoid content; antioxidant, multianti-enzymatic, and antibacterial activities of extracts; and in vitro gastrointestinal digestion (GID) of hot water extracts were performed. The strongest anti-cholinesterase activity was observed in PT extracts. The highest anti-ABTS (2,2'-azino-bis(3-ethylbenzothiazoline-6-sulphonic acid) radical potential was observed in PP extracts, whereas against DPPH (2,2-diphenyl-1-picrylhydrazyl radicals), the best results were achieved with PO extracts. Regarding antibacterial activity, extracts were strongly potent against Bacillus cereus. A molecular docking simulation was conducted to gather insights into the binding affinity and interactions of polyphenols and other Paeonia-specific molecules in the active sites of tested enzymes. In vitro GID of Paeonia teas showed a different recovery and behavior of the individual bioactives, with an increased recovery of methyl gallate and digallate and a decreased recovery of paeoniflorin and its derivatives. PT (Gulenovci) and PP (Pirot) extracts obtained by UAE and M were more efficient in the majority of the bioactivity assays. This study represents an initial step toward the possible application of Paeonia root extracts in pharmacy, medicine, and food technologies.

Studying allosteric regulation of chemokines and antagonists using a nanoscale hCCR3 receptor sensor

CC chemokine receptor-3 (hCCR3), a G protein-coupled receptor (GPCR) expressed predominantly on eosinophils, is an important drug target. However, it was unclear how chemokine ligands, activators and antagonists recognize hCCR3, and quantitative measurements of hCCR3 inhibition or activation were rare. This study constructed a nanogold receptor sensor using hCCR3 as the molecular recognition element and horseradish peroxidase as the signal amplifier. We quantified the kinetic antagonism between chemokines and hCCR3 before and after adding hCCR3 antagonists. A molecular docking study was carried out to investigate how hCCR3 and its ligands work. The study results indicate chemokines interact with hCCR3 at low concentrations, and reversible hCCR3 inhibitors solely inhibit hCCR3, not CCLs. Moreover, a quantitative evaluation of hCCR3 chemokine activators and their antagonists was carried out using a directed weighted network. This offers a novel approach to quantitatively evaluate chemokine-receptor activation and antagonism together. This research could potentially offer new insights into the mechanisms of action of chemokines and drug screening.

Advanced interactional characterization of the inhibitory effect of anthocyanin extract from Hibiscus sabdariffa L. on apple polyphenol oxidase

In this study, a comprehensive approach to advance the inhibitory effect of Hibiscus sabdariffa extract on apple polyphenol oxidase (PPO) was performed. PPO was extracted, purified, and characterized for optimal activity, whereas response surface methodology generated a quadratic polynomial model to fit the experimental results for hibiscus extraction. The optimum conditions allowed to predict a maximum recovery of anthocyanins (256.11 mg delphinidin-3-O-glucoside/g), with a validated value of 272.87 mg delphinidin-3-O-glucoside/g dry weight (DW). The chromatographic methods highlighted the presence of gallic acid (36,812.90 µg/g DW extract), myricetin (141,933.84 µg/g DW extract), caffeic acid (101,394.07 µg/g DW extract), sinapic acid (1157.46 µg/g DW extract), kaempferol (2136.76 µg/g DW extract), and delphinidin 3-O-β-d-glucoside (226,367.08 µg/g DW extract). The inactivation of PPO followed a first-order kinetic model. A temperature-mediated flexible fit between PPO and anthocyanins was suggested, whereas the molecular docking tests indicated that PPO is a good receptor for cafestol, gallic acid, and catechin, involving hydrophobic and hydrogen bond interactions. PRACTICAL APPLICATION: It is well known that enzymatic browning is one of the most important challenges in the industrial minimal processing of selected fruit and vegetable products. Novel inhibitors for polyphenol oxidase are proposed in this study by using an anthocyanin-enriched extract from Hibiscus sabdariffa L. Based on our results, combining the chemical effect of phytochemicals from hibiscus extract with different functional groups with minimal heating could be an interesting approach for the development of a new strategy to inhibit apple polyphenol oxidase.

Mixed and non-competitive enzyme inhibition: underlying mechanisms and mechanistic irrelevance of the formal two-site model

The formal mechanism of linear mixed and non-competitive enzyme inhibition implies the binding of inhibitors to both the active site of the free enzyme in competition with the substrate, and to an allosteric site on the enzyme-substrate complex. However, it is evident from a review of the scientific literature that the two-site mechanism is frequently mistaken as the actual underlying mechanism of mixed inhibition. In this study, we conducted a comprehensive assessment of the mechanistic relevance of this type of inhibition using a statistical approach. By combining a statistical analysis of the inhibition cases documented in the BRENDA database with a theoretical investigation of inhibition models, we conclude that mixed inhibitors exclusively bind to the active site of enzymes. Hence ruling out any implication of allosteric sites and depriving the two-site model of any mechanistic relevance.

Molecular noise-induced activator-inhibitor duality in enzyme inhibition kinetics

Classical theories of enzyme inhibition kinetics predict a monotonic decrease in the mean catalytic activity with the increase in inhibitor concentration. The steady-state result, derived from deterministic mass action kinetics, ignores molecular noise in enzyme-inhibition mechanisms. Here, we present a stochastic generalization of enzyme inhibition kinetics to mesoscopic enzyme concentrations by systematically accounting for molecular noise in competitive and uncompetitive mechanisms of enzyme inhibition. Our work reveals an activator-inhibitor duality as a non-classical effect in the transient regime in which inhibitors tend to enhance enzymatic activity. We introduce statistical measures that quantify this counterintuitive response through the stochastic analog of the Lineweaver-Burk plot that shows a merging of the inhibitor-dependent velocity with the Michaelis-Menten velocity. The statistical measures of mean and temporal fluctuations - fractional enzyme activity and waiting time correlations - show a non-monotonic rise with the increase in inhibitors before subsiding to their baseline value. The inhibitor and substrate dependence of the fractional enzyme activity yields kinetic phase diagrams for non-classical activator-inhibitor duality. Our work links this duality to a molecular memory effect in the transient regime, arising from positive correlations between consecutive product turnover times. The vanishing of memory in the steady state recovers all the classical results.

Inhibitory Potential of Synthetic Amino Acid Derivatives against Digestive Enzymes as Promising Hypoglycemic and Anti-Obesity Agents

Over the last decades, the increased incidence of metabolic disorders, such as type two diabetes and obesity, has motivated researchers to investigate new enzyme inhibitors. In this study, the inhibitory effects of synthetic amino acid derivatives (PPC80, PPC82, PPC84, PPC89, and PPC101) on the activity of digestive enzymes were assessed using in vitro assays. The inhibitory effect was determined by the inhibition percentage and the 50% inhibitory concentration (IC50), and the mechanism of action was investigated using kinetic parameters and Lineweaver-Burk plots. PPC80, PPC82, and PPC84 inhibited pancreatic lipase (IC50 of 167-1023 µM) via competitive or mixed mechanisms. The activity of pancreatic α-amylase was suppressed by PPC80, PPC82, PPC84, PPC89, and PPC101 (IC50 of 162-519 µM), which acted as competitive or mixed inhibitors. Finally, PPC84, PPC89, and PPC101 also showed potent inhibitory effects on α-glucosidase (IC50 of 51-353 µM) as competitive inhibitors. The results suggest that these synthetic amino acid derivatives have inhibitory potential against digestive enzymes and may be used as therapeutic agents to control metabolic disorders.

Universal performance bounds of restart

As has long been known to computer scientists, the performance of probabilistic algorithms characterized by relatively large runtime fluctuations can be improved by applying a restart, i.e., episodic interruption of a randomized computational procedure followed by initialization of its new statistically independent realization. A similar effect of restart-induced process acceleration could potentially be possible in the context of enzymatic reactions, where dissociation of the enzyme-substrate intermediate corresponds to restarting the catalytic step of the reaction. To date, a significant number of analytical results have been obtained in physics and computer science regarding the effect of restart on the completion time statistics in various model problems, however, the fundamental limits of restart efficiency remain unknown. Here we derive a range of universal statistical inequalities that offer constraints on the effect that restart could impose on the completion time of a generic stochastic process. The corresponding bounds are expressed via simple statistical metrics of the original process such as harmonic mean h, median value m, and mode M, and, thus, are remarkably practical. We test our analytical predictions with multiple numerical examples, discuss implications arising from them and important avenues of future work.

Epac as a tractable therapeutic target

In 1957, cyclic adenosine monophosphate (cAMP) was identified as the first secondary messenger, and the first signaling cascade discovered was the cAMP-protein kinase A (PKA) pathway. Since then, cAMP has received increasing attention given its multitude of actions. Not long ago, a new cAMP effector named exchange protein directly activated by cAMP (Epac) emerged as a critical mediator of cAMP's actions. Epac mediates a plethora of pathophysiologic processes and contributes to the pathogenesis of several diseases such as cancer, cardiovascular disease, diabetes, lung fibrosis, neurological disorders, and others. These findings strongly underscore the potential of Epac as a tractable therapeutic target. In this context, Epac modulators seem to possess unique characteristics and advantages and hold the promise of providing more efficacious treatments for a wide array of diseases. This paper provides an in-depth dissection and analysis of Epac structure, distribution, subcellular compartmentalization, and signaling mechanisms. We elaborate on how these characteristics can be utilized to design specific, efficient, and safe Epac agonists and antagonists that can be incorporated into future pharmacotherapeutics. In addition, we provide a detailed portfolio for specific Epac modulators highlighting their discovery, advantages, potential concerns, and utilization in the context of clinical disease entities.

Identification and Characterization of a Novel Dual Inhibitor of Indoleamine 2,3-dioxygenase 1 and Tryptophan 2,3-dioxygenase

Kynurenine (Kyn), a metabolite of tryptophan (Trp), is a key regulator of mammal immune responses such as cancer immune tolerance. Indoleamine-2,3-dioxygenase (IDO) and tryptophan-2,3-dioxygenase (TDO) are main enzymes regulating the first and rate-limiting step of the Kyn pathway. To identify new small molecule inhibitors of TDO, we selected A172 glioblastoma cell line constitutively expressed TDO. Characterization of this cell line using kinase inhibitor library resulted in identification of MEK/ERK pathway-dependent TDO expression. After knowing the properties for TDO expression, we further proceeded to screen chemical library for TDO inhibitors. We previously determined that S-benzylisothiourea derivatives are enzymatic inhibitors of indoleamine 2,3-dioxygenase 1 (IDO1) and suggested that the isothiourea moiety could be an important pharmacophore for binding to heme. Based on this premise, we screened an in-house library composed of various isothiourea derivatives and identified a bisisothiourea derivative, PVZB3001, as an inhibitor of TDO. Interestingly, PVZB3001 also inhibited the enzymatic activity of IDO1 in both cell-based and cell-free assays but did not inhibit other heme enzymes. Molecular docking studies suggested the importance of isothiourea moieties at the ortho position of the phenyl ring for the inhibition of catalytic activity. PVZB3001 showed competitive inhibition against TDO, and this was supported by the docking simulation. PVZB3001 recovered natural killer (NK) cell viability and functions by inhibiting Kyn accumulation in conditioned medium of both IDO1- and TDO-expressing cells. Furthermore, oral administration of IDO1-overexpressing tumor-bearing mice with PVZB3001 significantly inhibited tumor growth. Thus, we identified a novel selective dual inhibitor of IDO1 and TDO using the Kyn production assay with a glioblastoma cell line. This inhibitor could be a useful pharmacological tool for modulating the Kyn pathway in a variety of experimental systems.

Pore-Scale Heterogeneities Improve the Degradation of a Self-Inhibiting Substrate: Insights from Reactive Transport Modeling

In situ bioremediation is a common remediation strategy for many groundwater contaminants. It was traditionally believed that (in the absence of mixing-limitations) a better in situ bioremediation is obtained in a more homogeneous medium where the even distribution of both substrate and bacteria facilitates the access of a larger portion of the bacterial community to a higher amount of substrate. Such conclusions were driven with the typical assumption of disregarding substrate inhibitory effects on the metabolic activity of enzymes at high concentration levels. To investigate the influence of pore matrix heterogeneities on substrate inhibition, we use a numerical approach to solve reactive transport processes in the presence of pore-scale heterogeneities. To this end, a rigorous reactive pore network model is developed and used to model the reactive transport of a self-inhibiting substrate under both transient and steady-state conditions through media with various, spatially correlated, pore-size distributions. For the first time, we explore on the basis of a pore-scale model approach the link between pore-size heterogeneities and substrate inhibition. Our results show that for a self-inhibiting substrate, (1) pore-scale heterogeneities can consistently promote degradation rates at toxic levels, (2) the effect reverses when the concentrations fall to levels essential for microbial growth, and (3) an engineered combination of homogeneous and heterogeneous media can increase the overall efficiency of bioremediation.

Anomalous transport tuned through stochastic resetting in the rugged energy landscape of a chaotic system with roughness

Stochastic resetting causes kinetic phase transitions, whereas its underlying physical mechanism remains to be elucidated. We here investigate the anomalous transport of a particle moving in a chaotic system with a stochastic resetting and a rough potential and focus on how the stochastic resetting, roughness, and nonequilibrium noise affect the transports of the particle. We uncover the physical mechanism for stochastic resetting resulting in the anomalous transport in a nonlinear chaotic system: The particle is reset to a new basin of attraction which may be different from the initial basin of attraction from the view of dynamics. From the view of the energy landscape, the particle is reset to a new energy state of the energy landscape which may be different from the initial energy state. This resetting can lead to a kinetic phase transition between no transport and a finite net transport or between negative mobility and positive mobility. The roughness and noise also lead to the transition. Based on the mechanism, the transport of the particle can be tuned by these parameters. For example, the combination of the stochastic resetting, roughness, and noise can enhance the transport and tune negative mobility, the enhanced stability of the system, and the resonant-like activity. We analyze these results through variances (e.g., mean-squared velocity, etc.) and correlation functions (i.e., velocity autocorrelation function, position-velocity correlation function, etc.). Our results can be extensively applied in the biology, physics, and chemistry, even social system.

First passage in the presence of stochastic resetting and a potential barrier

Diffusion and first passage in the presence of stochastic resetting and potential bias have been of recent interest. We study a few models, systematically progressing in their complexity, to understand the usefulness of resetting. In the parameter space of the models, there are multiple continuous and discontinuous transitions where the advantage of resetting vanishes. We show these results analytically exactly for a tent potential, and numerically accurately for a quartic potential relevant to a magnetic system at low temperatures. We find that the spatial asymmetry of the potential across the barrier, and the number of absorbing boundaries, play a crucial role in determining the type of transition.

Chemical Modification of Phage-Displayed Helix-Loop-Helix Peptides to Construct Kinase-Focused Libraries

Conformationally constrained peptides hold promise as molecular tools in chemical biology and as a new modality in drug discovery. The construction and screening of a target-focused library could be a promising approach for the generation of de novo ligands or inhibitors against target proteins. Here, we have prepared a protein kinase-focused library by chemically modifying helix-loop-helix (HLH) peptides displayed on phage and subsequently tethered to adenosine. The library was screened against aurora kinase A (AurA). The selected HLH peptide Bip-3 retained the α-helical structure and bound to AurA with a KD value of 13.7 μM. Bip-3 and the adenosine-tethered peptide Bip-3-Adc provided IC50 values of 103 μM and 7.7 μM, respectively, suggesting that Bip-3-Adc bivalently inhibited AurA. In addition, the selectivity of Bip-3-Adc to several protein kinases was tested, and was highest against AurA. These results demonstrate that chemical modification can enable the construction of a kinase-focused library of phage-displayed HLH peptides.

Thermostable and organic solvent-tolerant acid pectinase from Aspergillus terreus FP6: purification, characterization and evaluation of its phytopigment extraction potential

The present study discusses the purification, characterization and application of pectinase from Aspergillus terreus FP6 in fruit pigment extraction. By the four-step purification involving precipitation, dialysis, ion-exchange chromatography, gel filtration chromatography, a 20.85-fold purification of the enzyme to homogeneity was achieved. The apparent molecular mass of the pectinase was 47 kDa, as found by sodium dodecyl sulphate-polyacrylamide gel electrophoresis. The optimum activity of the enzyme was recorded at pH 6.0 and 50 °C. The enzyme retained 80.3% and 79.1% residual activity, respectively at pH 6.0 and 50 °C for 90 min. The pectinase was best functional in the presence of toluene and retained its activity for 30 min. Cu²⁺ and Co²⁺ acted as enzyme activators, while Ca²⁺, β-mercaptoethanol, dimethyl sulfoxide and ethylenediaminetetraacetic acid proved to be the inhibitors. The K _m and V _max values of the pectinase with pectin as substrate were 0.002 mM and 27.39 U/mL, respectively thus indicating the high enzyme affinity towards the substrate. After 30-min treatment of the grape skin with the partially purified enzyme, microscopic observation revealed that a short time of the enzymatic treatment resulted in substantial loss of pigment and shrinkage of the grape skin cells thereby highlighting the high efficiency of the pectinase. The current study implies that the A. terreus FP6 pectinase may be applied as a bio-agent in the food and beverage industries and has the potential to replace harmful solvents by promoting a greener approach to extract plant pigments.

The Kinetic and Analytical Aspects of Enzyme Competitive Inhibition: Sensing of Tyrosinase Inhibitors

An amperometric biosensor based on tyrosinase, immobilized onto a carbon black paste electrode using glutaraldehyde and BSA was constructed to detect competitive inhibitors. Three inhibitors were used in this study: benzoic acid, sodium azide, and kojic acid, and the obtained values for fifty percent of inhibition (IC50) were 119 µM, 1480 µM, and 30 µM, respectively. The type of inhibition can also be determined from the curve of the degree of inhibition by considering the shift of the inhibition curves. Amperometric experiments were performed with a biosensor polarized at the potential -0.15 V vs. Ag/AgCl and using 0.1 M phosphate buffer (pH 6.8) as an electrolyte. Under optimized conditions, the proposed biosensor showed a linear amperometric response toward catechol detection from 0.5 µM to 38 µM with a detection limit of 0.35 µM (S/N = 3), and its sensitivity was 66.5 mA M-1 cm-2. Moreover, the biosensor exhibited a good storage stability. Conversely, a novel graphical plot for the determination of reversible competitive inhibition was represented for free tyrosinase. The graph consisted of plotting the half-time reaction (t1/2) as a function of the inhibitor concentration at various substrate concentrations. This innovative method relevance was demonstrated in the case of kojic acid using a colorimetric bioassay relying on tyrosinase inhibition. The results showed that the t1/2 provides an extended linear range of tyrosinase inhibitors.

Immobilized Crosslinked Pectinase Preparation on Porous ZSM-5 Zeolites as Reusable Biocatalysts for Ultra-Efficient Hydrolysis of β-Glycosidic Bonds

In this study, we immobilized pectinase preparation on porous zeolite ZSM-5 as an enzyme carrier. We realized this immobilized enzyme catalyst, pectinase preparation@ZSM-5, via a simple combined strategy involving the van der Waals adsorption of pectinase preparation followed by crosslinking of the adsorbed pectinase preparation with glutaraldehyde over ZSM-5. Conformal pectinase preparation coverage of various ZSM-5 supports was achieved for the as-prepared pectinase preparation@ZSM-5. The porous pectinase preparation@ZSM-5 catalyst exhibited ultra-efficient biocatalytic activity for hydrolyzing the β-glycosidic bonds in the model substrate 4-nitrophenyl β-D-glucopyranoside, with a broad operating temperature range, high thermal stability, and excellent reusability. The relative activity of pectinase preparation@ZSM-5 at a high temperature (70 °C) was nine times higher than that of free pectinase preparation. Using thermal inactivation kinetic analysis based on the Arrhenius law, pectinase preparation@ZSM-5 showed higher activation energy for denaturation (315 kJ mol⁻¹) and a longer half-life (62 min⁻¹) than free pectinase preparation. Moreover, a Michaelis–Menten enzyme kinetic analysis indicated a higher maximal reaction velocity for pectinase preparation@ZSM-5 (0.22 µmol mg⁻¹ min⁻¹). This enhanced reactivity was attributed to the microstructure of the immobilized pectinase preparation@ZSM-5, which offered a heterogeneous reaction system that decreased the substrate–pectinase preparation binding affinity and modulated the kinetic characteristics of the enzyme. Additionally, pectinase preparation@ZSM-5 showed the best ethanol tolerance among all the reported pectinase preparation-immobilized catalysts, and an activity 247% higher than that of free pectinase preparation at a 10% (v/v) ethanol concentration was measured. Furthermore, pectinase preparation@ZSM-5 exhibited potential for practical engineering applications, promoting the hydrolysis of β-glycosidic bonds in baicalin to convert it into baicalein. This was achieved with a 98% conversion rate, i.e., 320% higher than that of the free enzyme.

Resetting transition is governed by an interplay between thermal and potential energy

A dynamical process that takes a random time to complete, e.g., a chemical reaction, may either be accelerated or hindered due to resetting. Tuning system parameters, such as temperature, viscosity, or concentration, can invert the effect of resetting on the mean completion time of the process, which leads to a resetting transition. Although the resetting transition has been recently studied for diffusion in a handful of model potentials, it is yet unknown whether the results follow any universality in terms of well-defined physical parameters. To bridge this gap, we propose a general framework that reveals that the resetting transition is governed by an interplay between the thermal and potential energy. This result is illustrated for different classes of potentials that are used to model a wide variety of stochastic processes with numerous applications.

Combination of network and molecule structure accurately predicts competitive inhibitory interactions

Mining of metabolite-protein interaction networks facilitates the identification of design principles underlying the regulation of different cellular processes. However, identification and characterization of the regulatory role that metabolites play in interactions with proteins on a genome-scale level remains a pressing task. Based on availability of high-quality metabolite-protein interaction networks and genome-scale metabolic networks, here we propose a supervised machine learning approach, called CIRI that determines whether or not a metabolite is involved in a competitive inhibitory regulatory interaction with an enzyme. First, we show that CIRI outperforms the naive approach based on a structural similarity threshold for a putative competitive inhibitor and the substrates of a metabolic reaction. We also validate the performance of CIRI on several unseen data sets and databases of metabolite-protein interactions not used in the training, and demonstrate that the classifier can be effectively used to predict competitive inhibitory interactions. Finally, we show that CIRI can be employed to refine predictions about metabolite-protein interactions from a recently proposed PROMIS approach that employs metabolomics and proteomics profiles from size exclusion chromatography in E. coli to predict metabolite-protein interactions. Altogether, CIRI fills a gap in cataloguing metabolite-protein interactions and can be used in directing future machine learning efforts to categorize the regulatory type of these interactions.

Modulating catalytic activity of human topoisomerase II α enzyme by fluorescent gold nanoclusters

Precise monitoring of the enzyme activity by a suitable modulator is one of the very fundamental aspects of drug designing that provides the opportunity to overcome the challenges of several diseases. Herein, inhibition of human Topoisomerase IIα enzyme which serves as a potential target site for several anti-cancer drugs is demonstrated by using ultra-small size gold nanoclusters (Au NCs) with the dimension comparable with size of the active site of the enzyme. Molecular dynamics simulation results demonstrate that the Au NCs strongly interact with the human Topo IIα enzyme at its active site or allosteric site depending on forms of enzyme. Additionally, binding energy and interaction profile provides the molecular basis of understanding of interactions of ultra-small size Au NCs and human Topo IIα enzyme. Enthalpy change (ΔH) and binding constant (K) are measured based on a sequential binding model of the Au NCs with the enzyme as demonstrated by the ITC study. Moreover, the in-vitro inhibition study of the catalytic activity of the enzyme and gel electrophoresis indicates that the ultra-small size Au NCs may be used as a potent inhibitor of human Topo IIα enzyme.

Explicit Treatment of Non-Michaelis-Menten and Atypical Kinetics in Early Drug Discovery*

Biological systems are highly regulated. They are also highly resistant to sudden perturbations enabling them to maintain the dynamic equilibrium essential to sustain life. This robustness is conferred by regulatory mechanisms that influence the activity of enzymes/proteins within their cellular context to adapt to changing environmental conditions. However, the initial rules governing the study of enzyme kinetics were mostly tested and implemented for cytosolic enzyme systems that were easy to isolate and/or recombinantly express. Moreover, these enzymes lacked complex regulatory modalities. Now, with academic labs and pharmaceutical companies turning their attention to more-complex systems (for instance, multiprotein complexes, oligomeric assemblies, membrane proteins and post-translationally modified proteins), the initial axioms defined by Michaelis-Menten (MM) kinetics are rendered inadequate, and the development of a new kind of kinetic analysis to study these systems is required. This review strives to present an overview of enzyme kinetic mechanisms that are atypical and, oftentimes, do not conform to the classical MM kinetics. Further, it presents initial ideas on the design and analysis of experiments in early drug-discovery for such systems, to enable effective screening and characterisation of small-molecule inhibitors with desirable physiological outcomes.

Sensitivity analysis of the reaction occurrence and recurrence times in steady-state biochemical networks

Continuous-time stationary Markov jump processes among discrete sites are encountered in disparate biochemical ambits. Sites and connecting dynamical events form a 'network' in which the sites are the available system's states, and the events are site-to-site transitions, or even neutral processes in which the system does not change site but the event is however detectable. Examples include conformational transitions in single biomolecules, stochastic chemical kinetics in the space of the molecules copy numbers, and even macroscopic steady-state reactive mixtures if one adopts the viewpoint of a tagged molecule (or even of a molecular moiety) whose state may change when it is involved in a chemical reaction. Among the variety of dynamical descriptors, here we focus on the first occurrence times (starting from a given site) and on the recurrence times of an event of interest. We develop the sensitivity analysis for the lowest moments of the statistical distribution of such times with respect to the rate constants of the network. In particular, simple expressions and inequalities allow us to establish a direct relationship between selective variation of rate constants and effect on average times and variances. As illustrative cases we treat the substrate inhibition in enzymatic catalysis in which a tagged enzyme molecule jumps between three states, and the basic two-site model of stochastic gene expression in which the single gene switches between active and inactive forms.

Experimental Realization of Diffusion with Stochastic Resetting

Stochastic resetting is prevalent in natural and man-made systems, giving rise to a long series of nonequilibrium phenomena. Diffusion with stochastic resetting serves as a paradigmatic model to study these phenomena, but the lack of a well-controlled platform by which this process can be studied experimentally has been a major impediment to research in the field. Here, we report the experimental realization of colloidal particle diffusion and resetting via holographic optical tweezers. We provide the first experimental corroboration of central theoretical results and go on to measure the energetic cost of resetting in steady-state and first-passage scenarios. In both cases, we show that this cost cannot be made arbitrarily small because of fundamental constraints on realistic resetting protocols. The methods developed herein open the door to future experimental study of resetting phenomena beyond diffusion.

Anillin: The First Proofreading-like Scaffold?

Scaffolds are fundamental to many cellular signaling pathways. In this essay, a novel class of scaffolds are proposed, whose action bears striking resemblance to kinetic proofreading. Commonly, scaffold proteins are thought to work as tethers, bringing different components of a pathway together to improve the likelihood of their interaction. However, recent studies show that the cytoskeletal scaffold, anillin, supports contractile signaling by a novel, non-tethering mechanism that controls the membrane dissociation kinetics of RhoA. More generally, such proof-reading-like scaffolds are distinguished from tethers by a rare type of cooperativity, manifest as a super-linear relationship between scaffold concentration and signaling efficiency. The evidence for this hypothesis is reviewed, its conceptual ramifications are considered, and research questions for the future are discussed.

Resetting processes with noninstantaneous return

We consider a random two-phase process which we call a reset-return one. The particle starts its motion at the origin. The first, displacement, phase corresponds to a stochastic motion of a particle and is finished at a resetting event. The second, return, phase corresponds to the particle's motion toward the origin from the position it attained at the end of the displacement phase. This motion toward the origin takes place according to a given equation of motion. The whole process is a renewal one. We provide general expressions for the stationary probability density function of the particle's position and for the mean hitting time in one dimension. We perform explicit analysis for the Brownian motion during the displacement phase and three different types of the return motion: return at a constant speed, return at a constant acceleration with zero initial speed, and return under the action of a harmonic force. We assume that the waiting times for resetting events follow an exponential distribution or that resetting takes place after a fixed waiting period. For the first two types of return motion and the exponential resetting, the stationary probability density function of the particle's position is invariant under return speed (acceleration), while no such invariance is found for deterministic resetting, and for exponential resetting with return under the action of the harmonic force. We discuss necessary conditions for such invariance of the stationary PDF of the positions with respect to the properties of the return process, and we demonstrate some additional examples when this invariance does or does not take place.

Order Through Disorder: The Characteristic Variability of Systems

Randomness characterizes many processes in nature, and therefore its importance cannot be overstated. In the present study, we investigate examples of randomness found in various fields, to underlie its fundamental processes. The fields we address include physics, chemistry, biology (biological systems from genes to whole organs), medicine, and environmental science. Through the chosen examples, we explore the seemingly paradoxical nature of life and demonstrate that randomness is preferred under specific conditions. Furthermore, under certain conditions, promoting or making use of variability-associated parameters may be necessary for improving the function of processes and systems.

Time-dependent density of diffusion with stochastic resetting is invariant to return speed

The canonical Evans-Majumdar model for diffusion with stochastic resetting to the origin assumes that resetting takes zero time: upon resetting the diffusing particle is teleported back to the origin to start its motion anew. However, in reality getting from one place to another takes a finite amount of time which must be accounted for as diffusion with resetting already serves as a model for a myriad of processes in physics and beyond. Here we consider a situation where upon resetting the diffusing particle returns to the origin at a finite (rather than infinite) speed. This creates a coupling between the particle's random position at the moment of resetting and its return time, and further gives rise to a nontrivial cross-talk between two separate phases of motion: the diffusive phase and the return phase. We show that each of these phases relaxes to the steady state in a unique manner; and while this could have also rendered the total relaxation dynamics extremely nontrivial, our analysis surprisingly reveals otherwise. Indeed, the time-dependent distribution describing the particle's position in our model is completely invariant to the speed of return. Thus, whether returns are slow or fast, we always recover the result originally obtained for diffusion with instantaneous returns to the origin.

Recent Advances in EPAC-Targeted Therapies: A Biophysical Perspective

The universal second messenger cAMP regulates diverse intracellular processes by interacting with ubiquitously expressed proteins, such as Protein Kinase A (PKA) and the Exchange Protein directly Activated by cAMP (EPAC). EPAC is implicated in multiple pathologies, thus several EPAC-specific inhibitors have been identified in recent years. However, the mechanisms and molecular interactions underlying the EPAC inhibition elicited by such compounds are still poorly understood. Additionally, being hydrophobic low molecular weight species, EPAC-specific inhibitors are prone to forming colloidal aggregates, which result in non-specific aggregation-based inhibition (ABI) in aqueous systems. Here, we review from a biophysical perspective the molecular basis of the specific and non-specific interactions of two EPAC antagonists-CE3F4R, a non-competitive inhibitor, and ESI-09, a competitive inhibitor of EPAC. Additionally, we discuss the value of common ABI attenuators (e.g., TX and HSA) to reduce false positives at the expense of introducing false negatives when screening aggregation-prone compounds. We hope this review provides the EPAC community effective criteria to evaluate similar compounds, aiding in the optimization of existing drug leads, and informing the development of the next generation of EPAC-specific inhibitors.

Scaled Brownian motion with renewal resetting

We investigate an intermittent stochastic process in which the diffusive motion with time-dependent diffusion coefficient D(t)∼t^{α-1} with α>0 (scaled Brownian motion) is stochastically reset to its initial position, and starts anew. In the present work we discuss the situation in which the memory on the value of the diffusion coefficient at a resetting time is erased, so that the whole process is a fully renewal one. The situation when the resetting of the coordinate does not affect the diffusion coefficient's time dependence is considered in the other work of this series [A. S. Bodrova et al., Phys. Rev. E 100, 012119 (2019)10.1103/PhysRevE.100.012119]. We show that the properties of the probability densities in such processes (erasing or retaining the memory on the diffusion coefficient) are vastly different. In addition we discuss the first-passage properties of the scaled Brownian motion with renewal resetting and consider the dependence of the efficiency of search on the parameters of the process.

Random search with resetting as a strategy for optimal pollination

The problem of pollination is unique among a wide scope of search problems, since it requires optimization of benefits for both the searcher (pollinator) and its targets (plants). To address this challenge, we propose a pollination model which is based on a framework of first passage under stochastic restart. We derive equations for the search time and number of visited plants as functions of the distribution of nectar in the plant population and of the probability that a pollinator will leave the plant after examining a flower, thus effectively restarting the search. We demonstrate that nectar variation in plants serves as a driving force for pollination and establish conditions required for optimal pollination, which provides an efficient pollinator search strategy and the maximum number of plants visited by the pollinator.

First passage under stochastic resetting in an interval

We consider a Brownian particle diffusing in a one-dimensional interval with absorbing end points. We study the ramifications when such motion is interrupted and restarted from the same initial configuration. We provide a comprehensive study of the first-passage properties of this trapping phenomena. We compute the mean first-passage time and derive the criterion on which restart always expedites the underlying completion. We show how this set-up is a manifestation of a success-failure problem. We obtain the success and failure rates and relate them with the splitting probabilities, namely the probability that the particle will eventually be trapped on either of the boundaries without hitting the other one. Numerical studies are presented to support our analytic results.

First passage of a particle in a potential under stochastic resetting: A vanishing transition of optimal resetting rate

First passage in a stochastic process may be influenced by the presence of an external confining potential, as well as "stochastic resetting" in which the process is repeatedly reset back to its initial position. Here, we study the interplay between these two strategies, for a diffusing particle in a one-dimensional trapping potential V(x), being randomly reset at a constant rate r. Stochastic resetting has been of great interest as it is known to provide an "optimal rate" (r_{*}) at which the mean first passage time is a minimum. On the other hand, an attractive potential also assists in the first capture process. Interestingly, we find that for a sufficiently strong external potential, the advantageous optimal resetting rate vanishes (i.e., r_{*}→0). We derive a condition for this optimal resetting rate vanishing transition, which is continuous. We study this problem for various functional forms of V(x), some analytically, and the rest numerically. We find that the optimal rate r_{*} vanishes with a deviation from the critical strength of the potential as a power law with an exponent β which appears to be universal.

First Passage under Restart with Branching

First passage under restart with branching is proposed as a generalization of first passage under restart. Strong motivation to study this generalization comes from the observation that restart with branching can expedite the completion of processes that cannot be expedited with simple restart; yet a sharp and quantitative formulation of this statement is still lacking. We develop a comprehensive theory of first passage under restart with branching. This reveals that two widely applied measures of statistical dispersion-the coefficient of variation and the Gini index-come together to determine how restart with branching affects the mean completion time of an arbitrary stochastic process. The universality of this result is demonstrated and its connection to extreme value theory is also pointed out and explored.