Architecture‐dependent robustness in a class of multiple positive feedback loops

Many types of multiple positive feedbacks with each having potentials to generate bistability exist extensively in natural, raising the question of why a particular architecture is present in a cell. In this study, the authors investigate multiple positive feedback loops across three classes: one‐loop class, two‐loop class and three‐loop class, where each class is composed of double positive feedback loop (DPFL) or double negative feedback loop (DNFL) or both. Through large‐scale sampling and robustness analysis, the authors find that for a given class, the homogeneous DPFL circuit (i.e. the coupled circuit that is composed of only DPFLs) is more robust than all the other circuits in generating bistable behaviour. In addition, stochastic simulation shows that the low stable state is more robust than the high stable state in homogeneous DPFL whereas the high‐stable state is more robust than the low‐stable state in homogeneous DNFL circuits. It was argued that this investigation provides insight into the relationship between robustness and network architecture.Inspec keywords: cellular biophysics, feedback, sampling methods, stochastic processesOther keywords: network architecture, low stable state, stochastic simulation, bistable behaviour, homogeneous DPFL circuit, robustness analysis, large‐scale sampling, DNFL, double negative feedback loop, double positive feedback loop, three‐loop class, two‐loop class, one‐loop class, cell architecture, bistability, multiple positive feedback loops, architecture‐dependent robustness     

Analysis and classification of DNA‐binding sites in single‐stranded and double‐stranded DNA‐binding proteins using protein information

Single‐stranded DNA‐binding proteins (SSBs) and double‐stranded DNA‐binding proteins (DSBs) play different roles in biological processes when they bind to single‐stranded DNA (ssDNA) or double‐stranded DNA (dsDNA). However, the underlying binding mechanisms of SSBs and DSBs have not yet been fully understood. Here, the authors firstly constructed two groups of ssDNA and dsDNA specific binding sites from two non‐redundant sets of SSBs and DSBs. They further analysed the relationship between the two classes of binding sites and a newly proposed set of features (residue charge distribution, secondary structure and spatial shape). To assess and utilise the predictive power of these features, they trained a classification model using support vector machine to make predictions about the ssDNA and the dsDNA binding sites. The author''s analysis and prediction results indicated that the two classes of binding sites can be distinguishable by the three types of features, and the final classifier using all the features achieved satisfactory performance. In conclusion, the proposed features will deepen their understanding of the specificity of proteins which bind to ssDNA or dsDNA.Inspec keywords: biology computing, DNA, molecular biophysics, molecular configurations, pattern classification, proteins, support vector machinesOther keywords: dsDNA binding sites, ssDNA binding sites, support vector machine, classiflcation model, spatial shape, secondary structure, residue charge distribution, binding mechanisms, biological process, protein information, double‐stranded DNA‐binding proteins, single‐stranded DNA‐binding proteins     

Controllable synthesis and characterisation of palladium (II) anticancer complex‐loaded colloidal gelatin nanoparticles as a novel sustained‐release delivery system in cancer therapy

Over the past few years, there have been several attempts to deliver anticancer drugs into the body. It has been shown that compared to other available carriers, colloidal gelatin nanoparticles (CGNPs) have distinct properties due to their exceptional physico‐chemical and biological characteristics. In this study, a novel water‐soluble palladium (II) anticancer complex was first synthesised, and then loaded into CGNPs. The CGNPs were synthesised through a two‐step desolvation method with an average particle size of 378 nm. After confirming the stability of the drug in the nanoparticles, the drug‐loaded CGNPs were tested for in vitro cytotoxicity against human breast cancer cells. The results showed that the average drug encapsulating efficiency and drug loading of CGNPs were 64 and 10 ± 2.1% (w/w), respectively. There was a slight shift to higher values of cumulative release, when the samples were tested in lower pH values. In addition, the in vitro cytotoxicity test indicated that the number of growing cells significantly decreased after 48 h in the presence of different concentrations of drug. The results also demonstrated that the released drug could bind to DNA by a static mechanism at low concentrations (0.57 µM) on the basis of hydrophobic and hydrogen binding interactions.Inspec keywords: cancer, drug delivery systems, drugs, palladium compounds, colloids, gelatin, nanoparticles, nanomedicine, biomedical materials, nanofabrication, nanocomposites, molecular biophysics, molecular configurations, pH, solubility, particle size, cellular biophysics, encapsulation, DNA, hydrophobicity, hydrogen bondsOther keywords: controllable synthesis, sustained‐release delivery system, cancer therapy, palladium (II) anticancer complex‐loaded colloidal gelatin nanoparticles, anticancer drug delivery, physicochemical characteristics, biological characteristics, therapeutic pathways, water‐soluble palladium (II) anticancer complex, two‐step desolvation method, particle size, drug stability, gelatin matrix, drug‐loaded CGNPs, in vitro cytotoxic activity, human breast cancer cells, average drug encapsulating efficiency, pH values, cell growth, drug concentrations, DNA, static mechanism, hydrophobic interaction, hydrogen binding interactions     

Cu‐induced assembly of methanobactin‐modified gold nanoparticles and its peroxidase mimic activity

Methanobactin (Mb) is a small copper‐chelating molecule that functions as an agent for copper acquisition, uptake and copper‐containing methane monooxygenase catalysis in methane‐oxidising bacteria. The UV–visible spectral and fluorescence spectral suggested that Mb/Cu coordination complex as a monomer (Mb‐Cu), dimmer (Mb₂ ‐Cu) and tetramer (Mb₄ ‐Cu) could be obtained at different ratios of Mb to Cu (II). The kinetics of the oxidation of hydroquinone with hydrogen peroxide catalysed by the different Mb/Cu coordination complex were investigated. The results suggested that Mb₂ ‐Cu coordination form has highest catalytic capacity. Further, Mb‐modified gold nanoparticles (AuNPs) were obtained by ligand exchange and assembled into two‐ and three‐D nanocluster structure by metal‐organic coordination as driving force. It has been found that AuNPs increased the catalytic activity of Mb₂ ‐Cu on AuNPs. The more significant catalytic activity was exhibited by the nanocluster assembly with multi‐catalytic centres. This may be attributed to the multivalent collaborative characteristics of the catalytic active centres in the nanocluster network assembly. The assembly of Mb‐modified AuNPs can act as excellent nanoenzyme models for imitating peroxidase.Inspec keywords: nanoparticles, catalysis, oxidation, enzymes, microorganisms, nanobiotechnology, gold, organic compounds, reduction (chemical), visible spectra, molecular biophysics, ultraviolet spectra, biochemistry, copper, nanofabrication, fluorescenceOther keywords: Mb‐modified gold nanoparticles, catalytic active centres, Mb‐modified AuNPs, Cu‐induced assembly, methanobactin‐modified gold nanoparticles, peroxidase mimic activity, copper‐chelating molecule, copper‐containing methane monooxygenase catalysis, methane‐oxidising bacteria, fluorescence, Mb/Cu coordination complex, catalytic activity, UV–visible spectra, nanocluster assembly, Cu, Au     

Nano‐biosensor based on reduced graphene oxide and gold nanoparticles,for detection of phenylketonuria‐associated DNA mutation

Phenylketonuria (PKU)‐associated DNA mutation in newborn children can be harmful to his health and early detection is the best way to inhibit consequences. A novel electrochemical nano‐biosensor was developed for PKU detection, based on signal amplification using nanomaterials, e.g. gold nanoparticles (AuNPs) decorated on the reduced graphene oxide sheet on the screen‐printed carbon electrode. The fabrication steps were checked by field emission scanning electron microscope imaging as well as cyclic voltammetry analysis. The specific alkanethiol single‐stranded DNA probes were attached by self‐assembly methodology on the AuNPs surface and Oracet blue was used as an intercalating electrochemical label. The results showed the detection limit of 21.3 fM and the dynamic range of 80–1200 fM. Moreover, the selectivity results represented a great specificity of the nano‐biosensor for its specific target DNA oligo versus other non‐specific sequences. The real sample simulation was performed successfully with almost no difference than a synthetic buffer solution environment.Inspec keywords: biosensors, nanosensors, nanoparticles, graphene compounds, gold, nanomedicine, DNA, molecular biophysics, biomedical equipment, electrochemical sensors, electrochemical electrodes, field emission scanning electron microscopy, voltammetry (chemical analysis), self‐assembly, biochemistryOther keywords: reduced graphene oxide, gold nanoparticles, phenylketonuria‐associated DNA mutation, newborn children, electrochemical nanobiosensor, signal amplification, nanomaterials, reduced graphene oxide sheet, screen‐printed carbon electrode, field emission scanning electron microscopy imaging, cyclic voltammetry, alkanethiol single‐stranded DNA probes, self‐assembly methodology, Oracet blue, intercalating electrochemical label, Au‐CO     

System‐based strategies for p53 recovery

The authors have proposed a systems theory‐based novel drug design approach for the p53 pathway. The pathway is taken as a dynamic system represented by ordinary differential equations‐based mathematical model. Using control engineering practices, the system analysis and subsequent controller design is performed for the re‐activation of wild‐type p53. p53 revival is discussed for both modes of operation, i.e. the sustained and oscillatory. To define the problem in control system paradigm, modification in the existing mathematical model is performed to incorporate the effect of Nutlin. Attractor point analysis is carried out to select the suitable domain of attraction. A two‐loop negative feedback control strategy is devised to drag the system trajectories to the attractor point and to regulate cellular concentration of Nutlin, respectively. An integrated framework is constituted to incorporate the pharmacokinetic effects of Nutlin in the cancerous cells. Bifurcation analysis is also performed on the p53 model to see the conditions for p53 oscillation.Inspec keywords: proteins, tumours, cancer, cellular biophysics, molecular biophysics, molecular configurations, biochemistry, differential equations, closed loop systems, bifurcation, biology computingOther keywords: system‐based strategies, p53 recovery, systems theory‐based novel drug design approach, dynamic system, ordinary differential equations‐based mathematical model, control engineering practices, subsequent controller design, wild‐type p53, p53 revival, oscillatory, control system paradigm, mathematical model, Nutlin effect, attractor point analysis, domain‐of‐attraction, two‐loop negative feedback control strategy, cellular concentration, pharmacokinetic effects, cancerous cells, bifurcation analysis, p53 oscillation, anomalous cell     

Inferring non‐synonymous single‐nucleotide polymorphisms‐disease associations via integration of multiple similarity networks

Detecting associations between human genetic variants and their phenotypic effects is a significant problem in understanding genetic bases of human‐inherited diseases. The focus is on a typical type of genetic variants called non‐synonymous single nucleotide polymorphisms (nsSNPs), whose occurrence may potentially alter the structures of proteins, affecting functions of proteins, and thereby causing diseases. Most of the existing methods predict associations between nsSNPs and diseases based on features derived from only protein sequence and/or structure information, and give no information about which specific disease an nsSNP is associated with. To cope with these problems, the identification of nsSNPs that are associated with a specific disease from a set of candidate nsSNPs as a binary classification problem has been formulated. A new approach has been adopted for predicting associations between nsSNPs and diseases based on multiple nsSNP similarity networks and disease phenotype similarity networks. With a series of comprehensive validation experiments, it has been demonstrated that the proposed method is effective in both recovering the nsSNP‐disease associations and inferring suspect disease‐associated nsSNPs for both diseases with known genetic bases and diseases of unknown genetic bases.Inspec keywords: diseases, genetics, polymorphism, proteinsOther keywords: nonsynonymous single‐nucleotide polymorphisms, disease associations, multiple similarity network integration, human genetic variants, phenotypic effects, human‐inherited diseases, nonsynonymous single nucleotide polymorphisms, proteins, protein sequence, structure information, candidate nsSNP, binary classification problem, disease phenotype similarity networks, unknown genetic bases     

Facile synthesis of reduced graphene oxide/trimethyl chlorosilane‐coated cellulose nanofibres aerogel for oil absorption

A hydrophobic and oleophilic trimethyl chlorosilane/reduced graphene oxide‐coated cellulose nanofibres (TMCS/rGO/CNFs) aerogel with a three‐dimensional structure was fabricated through a facile dip‐coating process. The prepared aerogel exhibited several advantageous properties for absorption and expulsion of oils from water surfaces, such as a high specific surface area, low density (6.78 mg/cm³) and good porosity (99.12％). In addition, the TMCS/rGO/CNFs aerogel demonstrated good absorption capacities up to 39 times its own weight over a short time (1.5 min) for a broad range of oils. This research suggests that practical application of TMCS/rGO/CNFs aerogel in the cleanup of an oil spill is feasible.Inspec keywords: graphene, nanofibres, aerogels, absorption, hydrophobicity, dip coating, oil pollution, nanofabricationOther keywords: facile synthesis, reduced graphene oxide‐trimethyl chlorosilane‐coated cellulose nanofibre aerogel, three‐dimensional structure, facile dip‐coating process, oil expulsion, water surfaces, TMCS‐rGO‐CNF aerogel, oil absorption capacities, oil spill cleanup, CO     

Laser‐induced heating for in situ DNA replication and detection in microchannels

This study proposes a method for in situ local deoxyribonucleic acid (DNA) replication and detection in a long DNA strand through laser‐induced heating and strong avidin–biotin binding. To achieve the target DNA replication, dielectrophoresis was generated to stretch and immobilise DNA strands on both ends of the electrode. Subsequently, local DNA sequences were replicated using thermal cycles generated by laser‐induced heating. Replicated double‐stranded DNA products were captured in situ on a solid surface and detected using the fluorescence intensity of quantum dots (Qdots). The results revealed that after six laser‐induced thermal cycles, the replicated local DNA sequence could be detected by analysing the difference between Qdot fluorescent intensity before and after replication. The proposed method is expected to improve the efficiency of biosample gene sequence analysis.Inspec keywords: DNA, molecular biophysics, fluorescence, electrophoresis, biochemistry, molecular configurations, quantum dots, laser beam applications, biothermicsOther keywords: laser‐induced heating, long DNA strand, target DNA replication, DNA strands, local DNA sequences, thermal cycles, replicated double‐stranded DNA products, replicated local DNA sequence, in situ DNA replication, in situ local deoxyribonucleic acid replication, strong avidin‐biotin binding, biosample gene sequence analysis, Qdot fluorescent intensity, laser‐induced thermal cycles     

Analysis of healthy and tumour DNA methylation distributions in kidney‐renal‐clear‐cell‐carcinoma using Kullback–Leibler and Jensen–Shannon distance measures

DNA methylation is an epigenetic phenomenon in which methyl groups get bonded to the cytosines of the DNA molecule altering the expression of the associated genes. Cancer is linked with hypo or hyper‐methylation of specific genes as well as global changes in DNA methylation. In this study, the authors study the probability density function distribution of DNA methylation in various significant genes and across the genome in healthy and tumour samples. They propose a unique ‘average healthy methylation distribution’ based on the methylation values of several healthy samples. They then obtain the Kullback–Leibler and Jensen–Shannon distances between methylation distributions of the healthy and tumour samples and the average healthy methylation distribution. The distance measures of the healthy and tumour samples from the average healthy methylation distribution are compared and the differences in the distances are analysed as possible parameters for cancer. A classifier trained on these values was found to provide high values of sensitivity and specificity. They consider this to be a computationally efficient approach to predict tumour samples based on DNA methylation data. This technique can also be improvised to consider other differentially methylated genes significant in cancer or other epigenetic diseases.Inspec keywords: cancer, tumours, DNA, genetics, molecular biophysicsOther keywords: tumour DNA methylation distributions, kidney‐renal‐clear‐cell‐carcinoma, Kullback–Leibler distance measure, Jensen–Shannon distance measure, epigenetic phenomenon, methyl groups, cytosines, hyper‐methylation, probability density function distribution, average healthy methylation distribution     

Positive selection on D‐lactate dehydrogenases of Lactobacillus delbrueckii subspecies bulgaricus

Lactobacillus delbrueckii has been widely used for yogurt fermentation. It has genes encoding both D‐ and L‐type lactate dehydrogenases (LDHs) that catalyse the production of L(+) or D(−) stereoisomer of lactic acid. D‐lactic acid is the primary lactate product by L. delbrueckii, yet it cannot be metabolised by human intestine. Since it has been domesticated for long time, an interesting question arises regarding to whether the selection pressure has affected the evolution of both L‐LDH and D‐LDH genes in the genome. To answer this question, in this study the authors first investigated the evolution of these two genes by constructing phylogenetic trees. They found that D‐LDH‐based phylogenetic tree could better represent the phylogenetic relationship in the acidophilus complex than L‐LDH‐based tree. They next investigated the evolutions of LDH genes of L. delbrueckii at amino acid level, and found that D‐LDH gene in L. delbrueckii is positively selected, possibly a consequence of long‐term domestication. They further identified four amino acids that are under positive selection. One of them, V261, is located at the centre of three catalytic active sites, indicating likely functional effects on the enzyme activity. The selection from the domestication process thus provides direction for future engineering of D‐LDH.Inspec keywords: enzymes, biochemistry, molecular biophysics, microorganisms, genetics, evolution (biological), molecular configurations, isomerism, food products, biological techniques, fermentationOther keywords: Lactobacillus delbrueckii, D‐lactate dehydrogenases, yogurt fermentation, Streptococcus thermophilus, lactic acid stereoisomer, phylogenetic trees, acidophilus complex, amino acids, enzyme activity, three‐dimensional structure, L‐LDH genes, D‐LDH genes     

Modelling the role of catastrophe,crossover and katanin‐mediated severing in the self‐organisation of plant cortical microtubules

Plant cortical microtubules can form ordered arrays through interactions among themselves. When an incident microtubule collides with a barrier microtubule it may entrain if below a certain angle. Else it undergoes collision induced catastrophe (CIC) or crosses over the barrier microtubule. It has been proposed that katanin is necessary to create order by severing these crossover sites. The authors present a three‐state computational model using Arabidopsis thaliana data to show how spontaneous catastrophe, the probability of CIC versus crossover, and katanin‐mediated severing at the crossover sites affect microtubule ordering. The results of the systematic simulations show that (1), the microtubule order is more sensitive to the catastrophe rate than the rescue rate; (2), at 21°C, peak order is observed at 0.3 CIC and order decreases as CIC increases; and (3) at 0.2 CIC, katanin severing acting uniformly at all crossover sites is able to create order within a biologically reasonable time frame, but at lower CICs this becomes unrealistically fast. This would imply that at lower CIC levels preferential crossover site targeting and severing activity regulators would be required for katanin to bring about order.Inspec keywords: cellular biophysics, botany, proteins, molecular biophysicsOther keywords: barrier microtubule crossover, katanin‐mediated severing, self‐organisation, plant cortical microtubules, collision induced catastrophe, three‐state computational model, Arabidopsis thaliana data, microtubule ordering     

Silk‐based microcarriers: current developments and future perspectives

Cell‐seeded microcarriers (MCs) are currently one of the most promising topics in biotechnology. These systems are supportive structures for cell growth and expansion that allow efficient nutrient and gas transfer between the media and the attached cells. Silk proteins have been increasingly used for this purpose in the past few years due to their biocompatibility, biodegradability and non‐toxicity. To date, several silk fibroin spherical MCs in combination with alginate, gelatin and calcium phosphates have been reported with very interesting outcomes. In addition, other silk‐based three‐dimensional structures such as microparticles with chitosan and collagen, as well as organoids, have been increasingly studied. In this study, the physicochemical and biological properties of these biomaterials, as well as the recent methodologies for their processing and for cell culture, are discussed. The potential biomedical applications are also addressed. In addition, an analysis of the future perspectives is presented, where the potential of innovative silk‐based MCs processing technologies is highlighted.Inspec keywords: biodegradable materials, proteins, calcium compounds, gelatin, biomedical materials, cellular biophysics, molecular biophysicsOther keywords: supportive structures, cell growth, gas transfer, attached cells, silk proteins, biodegradability, nontoxicity, silk fibroin spherical MCs, gelatin, calcium phosphates, silk‐based three‐dimensional structures, chitosan, collagen, physicochemical properties, biological properties, cell culture, silk‐based microcarriers, cell‐seeded microcarriers, biotechnology, efficient nutrient transfer, biocompatibility, alginate, biomedical applications     

Multi‐scale approach for simulating time‐delay biochemical reaction systems

This study presents a multi‐scale approach for simulating time‐delay biochemical reaction systems when there are wide ranges of molecular numbers. The authors construct a new efficient approach based on partitioning into slow and fast subsets in conjunction with predictor–corrector methods. This multi‐scale approach is shown to be much more efficient than existing methods such as the delay stochastic simulation algorithm and the modified next reaction method. Numerical testing on several important problems in systems biology confirms the accuracy and computational efficiency of this approach.Inspec keywords: biochemistry, delays, biological techniques, predictor‐corrector methodsOther keywords: multiscale approach, time‐delay biochemical reaction systems, predictor–corrector methods, delay stochastic simulation algorithm, modified next reaction method, numerical testing, systems biology, method accuracy, computational efficiency     

In silico discovery of significant pathways in colorectal cancer metastasis using a two‐stage optimisation approach

Accurate and reliable modelling of protein–protein interaction networks for complex diseases such as colorectal cancer can help better understand mechanism of diseases and potentially discover new drugs. Different machine learning methods such as empirical mode decomposition combined with least square support vector machine, and discrete Fourier transform have been widely utilised as a classifier and for automatic discovery of biomarkers for the diagnosis of the disease. The existing methods are, however, less efficient as they tend to ignore interaction with the classifier. In this study, the authors propose a two‐stage optimisation approach to effectively select biomarkers and discover interactions among them. At the first stage, particle swarm optimisation (PSO) and differential evolution (DE) are used to optimise parameters of support vector machine recursive feature elimination algorithm, and dynamic Bayesian network is then used to predict temporal relationship between biomarkers across two time points. Results show that 18 and 25 biomarkers selected by PSO and DE‐based approach, respectively, yields the same accuracy of 97.3% and F1‐score of 97.7 and 97.6%, respectively. The stratified analysis reveals that Alpha‐2‐HS‐glycoprotein was a dominant hub gene with multiple interactions to other genes including Fibrinogen alpha chain, which is also a potential biomarker for colorectal cancer.Inspec keywords: cancer, proteins, particle swarm optimisation, evolutionary computation, support vector machines, recursive functions, Bayes methods, genetics, molecular biophysics, medical computingOther keywords: colorectal cancer metastasis, two‐stage optimisation approach, protein–protein interaction networks, biomarkers, particle swarm optimisation, differential evolution, support vector machine recursive feature elimination, dynamic Bayesian network, stratified analysis, Alpha‐2‐HS‐glycoprotein, hub gene, Fibrinogen alpha chain     

Fabrication challenges and perspectives on the use of carbon‐electrode dielectrophoresis in sample preparation

The focus of this review is to assess the current status of three‐dimensional (3D) carbon‐electrode dielectrophoresis (carbonDEP) and identify the challenges currently preventing it from its use in high‐throughput applications such as sample preparation for diagnostics. The use of 3D electrodes over more traditional planar ones is emphasised here as a way to increase the throughput of DEP devices. Glass‐like carbon electrodes are derived through the carbonisation of photoresist structures made using photolithography. These biocompatible carbon electrodes are not ideal electrical conductors but are more electrochemically stable than noble metals such as gold and platinum. They are also significantly less expensive than common electrode materials, both in terms of material cost and fabrication process. CarbonDEP has been demonstrated for the manipulation of microorganisms and biomolecules. This review is divided in three main sections: (i) carbonDEP fabrication process; (ii) applications using 3D carbonDEP; and (iii) challenges and perspectives on the use of carbonDEP for high‐throughput applications.Inspec keywords: electrophoresis, electrochemical electrodes, photoresists, electrochemistry, microorganisms, biological specimen preparationOther keywords: sample preparation, three‐dimensional carbon‐electrode dielectrophoresis, high‐throughput applications, diagnostics, 3D electrodes, DEP devices, glass‐like carbon electrodes, carbonisation, photoresist structures, photolithography, biocompatible carbon electrodes, electrochemical stability, electrode materials, material cost, fabrication process, microorganisms, biomolecules, carbonDEP fabrication, C     

Two‐dimensional polynomial type canonical relaxation oscillator model for p53 dynamics

p53 network, which is responsible for DNA damage response of cells, exhibits three distinct qualitative behaviours; low state, oscillation and high state, which are associated with normal cell cycle progression, cell cycle arrest and apoptosis, respectively. The experimental studies demonstrate that these dynamics of p53 are due to the ATM and Wip1 interaction. This paper proposes a simple two‐dimensional canonical relaxation oscillator model based on the identified topological structure of ATM and Wip1 interaction underlying these qualitative behaviours of p53 network. The model includes only polynomial terms that have the interpretability of known ATM and Wip1 interaction. The introduced model is useful for understanding relaxation oscillations in gene regulatory networks. Through mathematical analysis, we investigate the roles of ATM and Wip1 in forming of these three essential behaviours, and show that ATM and Wip1 constitute the core mechanism of p53 dynamics. In agreement with biological findings, we show that Wip1 degradation term is a highly sensitive parameter, possibly related to mutations. By perturbing the corresponding parameters, our model characterizes some mutations such as ATM deficiency and Wip1 overexpression. Finally, we provide intervention strategies considering our observation that Wip1 seems to be an important target to conduct therapies for these mutations.Inspec keywords: enzymes, molecular biophysics, molecular configurations, genetics, cellular biophysicsOther keywords: two‐dimensional polynomial type canonical relaxation oscillator model, p53 dynamics, p53 network, gene regulatory network, DNA damage response, normal cell cycle progression, cell cycle arrest, cell apoptosis, ATM interaction, Wip1 interaction, ataxia‐telangiectasia mutated interaction, wild‐type p53‐induced phosphatase 1 interaction, topological structure, mathematical analysis