Synthesis,stability, and in vitro oral cancer cell toxicity of human serum albumin stabilised gold nanoflowers

Gold nanoflowers (GNFs) prepared by reduction of HAuCl₄ by ascorbic acid were capped with human serum albumin (HSA) by either electrostatic or covalent attachment to prevent their self‐aggregation. Measurement of surface plasmon resonance absorbance changes under different stress conditions showed that GNFs stabilised by covalent attachment of HSA were more stable than those stabilised by electrostatic attachment. Cytotoxicity of the covalently conjugated GNF was also studied in cultured human oral cancer cell lines by measuring the metabolic activity via 3‐(4,5‐dimethylthiazol‐2‐yl)‐2,5‐diphenyltetrazolium bromide assay.Inspec keywords: proteins, molecular biophysics, biomedical materials, reduction (chemical), gold, cellular biophysics, nanofabrication, biochemistry, surface plasmon resonance, cancer, nanomedicine, materials preparation, nanostructured materialsOther keywords: Au, human serum albumin stabilised gold nanoflowers, cytotoxicity, in vitro oral cancer cell toxicity, stress conditions, surface plasmon resonance absorbance, 3‐(4,5‐dimethylthiazol‐2‐yl)‐2,5‐diphenyltetrazolium bromide assay, self‐aggregation, covalent attachment, electrostatic attachment, ascorbic acid, cultured human oral cancer cell lines     

Experimental and theoretical investigation of sensing parameters in carbon nanotube‐based DNA sensor

Nowadays, sensitive biosensors with high selectivity, lower costs and short response time are required for detection of DNA. The most preferred materials in DNA sensor designing are nanomaterials such as carbon and Au nanoparticles, because of their very high surface area and biocompatibility which lead to performance and sensitivity improvements in DNA sensors. Carbon nanomaterials such as carbon nanotubes (CNTs) can be considered as a suitable DNA sensor platform due to their high surface‐to‐volume ratio, favourable electronic properties and fast electron transfer rate. Therefore, in this study, the CNTs which are synthesised by pulsed AC arc discharge method on a high‐density polyethylene substrate are used as conducting channels in a chemiresistor for the electrochemical detection of double stranded DNA. Moreover, the response of the proposed sensor is investigated experimentally and analytically in different temperatures, which confirm good agreement between the presented model and experimental data.Inspec keywords: electrochemical sensors, polymers, arcs (electric), biological techniques, nanosensors, carbon nanotubes, DNAOther keywords: C, chemiresistor, double stranded DNA detection, CNT, electronic properties, surface‐to‐volume ratio, nanoparticles, biosensors, electrochemical detection, high‐density polyethylene substrate, pulsed AC arc discharge method, electron transfer rate, carbon nanomaterials, carbon nanotube‐based DNA sensor     

Size effects of magnetic beads in circulating tumour cells magnetic capture based on streptavidin–biotin complexation

Circulating tumour cells (CTCs) draw significant attention as a promising biomarker for cancer prognosis, status monitoring, and metastasis diagnosis. However, the concentration of CTCs in peripheral blood is usually extremely low, thereby requiring enrichment followed by isolation of CTCs prior to detection. An immunomagnetic separation is a promising tool for CTCs enrichment. In this study, a cost‐effective magnetic separation method, based on streptavidin–biotin complexation, was developed and the effects of magnetic beads’ size in CTCs capture were compared. Magnetic nanobeads which were 25 nm in diameter lead to highest capture efficiency (82.2%) compared with 150 nm magnetic beads and 1 µm microbeads. Based on the streptavidin–biotin system, 25 nm magnetic nanobeads could capture model CTCs over 80% efficiency even at concentrations as low as ∼25 cells/mL that may represent the actual level of CTCs in peripheral blood of cancer patients. Furthermore, the isolated cells remained robust and healthy showing insignificant changes in morphology and behaviour when cultured for 24 h immediately after capture and isolation. The magnetic nanobeads based on streptavidin–biotin complexation showed promise for the easy and efficient capture and isolation of healthy CTCs for further diagnosis and analysis.Inspec keywords: cancer, magnetic separation, nanomedicine, nanomagnetics, proteins, biomagnetism, tumours, cellular biophysics, magnetic particles, molecular biophysics, blood, nanoparticlesOther keywords: streptavidin–biotin complexation, cancer prognosis, peripheral blood, immunomagnetic separation, CTCs capture, streptavidin–biotin system, circulating tumour cells, CTC enrichment, magnetic separation method, magnetic nanobeads, magnetic capture, size 25.0 nm, size 150.0 nm, time 24.0 hour     

Overlapping functional modules detection in PPI network with pair‐wise constrained non‐negative matrix tri‐factorisation

A large amount of available protein–protein interaction (PPI) data has been generated by high‐throughput experimental techniques. Uncovering functional modules from PPI networks will help us better understand the underlying mechanisms of cellular functions. Numerous computational algorithms have been designed to identify functional modules automatically in the past decades. However, most community detection methods (non‐overlapping or overlapping types) are unsupervised models, which cannot incorporate the well‐known protein complexes as a priori. The authors propose a novel semi‐supervised model named pairwise constrains nonnegative matrix tri‐factorisation (PCNMTF), which takes full advantage of the well‐known protein complexes to find overlapping functional modules based on protein module indicator matrix and module correlation matrix simultaneously from PPI networks. PCNMTF determinately models and learns the mixed module memberships of each protein by considering the correlation among modules simultaneously based on the non‐negative matrix tri‐factorisation. The experiment results on both synthetic and real‐world biological networks demonstrate that PCNMTF gains more precise functional modules than that of state‐of‐the‐art methods.Inspec keywords: proteins, molecular biophysics, cellular biophysics, matrix algebraOther keywords: overlapping functional module detection, PPI network, pair‐wise constrained nonnegative matrix trifactorisation, protein–protein interaction data, cellular functions, protein complexes, real‐world biological networks, synthetic biological networks     

Investigating receptor enzyme activity using time‐scale analysis

At early drug discovery, purified protein‐based assays are often used to characterise compound potency. In the context of dose response, it is often perceived that a time‐independent inhibitor is reversible and a time‐dependent inhibitor is irreversible. The legitimacy of this argument is investigated using a simple kinetics model, where it is revealed by model‐based analytical analysis and numerical studies that dose response of an irreversible inhibitor may appear time‐independent under certain parametric conditions. Hence, the observation of time‐independence cannot be used as sole evidence for identification of inhibitor reversibility. It has also been discussed how the synthesis and degradation of a target receptor affect drug inhibition in an in vitro cell‐based assay setting. These processes may also influence dose response of an irreversible inhibitor in such a way that it appears time‐independent under certain conditions. Furthermore, model‐based steady‐state analysis reveals the complexity nature of the drug–receptor process.Inspec keywords: enzymes, molecular biophysics, drugs, biochemistry, reaction kinetics, cellular biophysicsOther keywords: receptor enzyme activity, time‐scale analysis, drug discovery, purified protein‐based assays, compound potency, dose response, reversible time‐independent inhibitor, irreversible time‐dependent inhibitor, kinetics model, target receptor degradation, drug inhibition, in vitro cell‐based assay setting, model‐based steady‐state analysis, drug‐receptor process     

Gene regulatory network discovery using pairwise Granger causality

Discovery of gene regulatory network from gene expression data can yield a useful insight to drug development. Among the methods applied to time‐series data, Granger causality (GC) has emerged as a powerful tool with several merits. Since gene expression data usually have a much larger number of genes than time points therefore a full model cannot be applied in a straightforward manner, GC is often applied to genes pairwisely. In this study, the authors first investigate with synthetic data how spurious causalities (false discoveries) may arise because of the use of pairwise rather than full‐model GC detection. Furthermore, spurious causalities may also arise if the order of the vector autoregressive model is not high enough. As a remedy, the authors demonstrate that model validation techniques can effectively reduce the number of false discoveries. Then, they apply pairwise GC with model validation to the real human HeLa cell‐cycle dataset. They find that Akaike information criterion is generally most suitable for determining model order, but precaution should be taken for extremely short time series. With the authors proposed implementation, degree distributions and network hubs are obtained and compared with existing results, giving a new observation that the hubs tend to act as sources rather than receivers of interactions.Inspec keywords: biology computing, cancer, causality, cellular biophysics, genetics, genomics, time seriesOther keywords: gene regulatory network discovery, pairwise Granger causality, gene expression data, drug development, time‐series data, synthetic data, spurious causalities, full‐model Granger causality detection, vector autoregressive model, real human HeLa cell‐cycle dataset, Akaike information criterion, degree distributions, network hubs     

Signal amplification strategy using gold/N ‐trimethyl chitosan/iron oxide magnetic composite nanoparticles as a tracer tag for high‐sensitive electrochemical detection

This study presents a novel signal amplification method for high‐sensitive electrochemical immunosensing. Gold (Au)/N ‐trimethyl chitosan (TMC)/iron oxide (Fe₃ O₄) (shell/shell/core) nanocomposite was used as a tracing tag to label antibody. The tag was shown to be capable of amplifying the recognition signal by high‐density assembly of Au nanoparticles (NPs) on TMC/Fe₃ O₄ particles. The remarkable conductivity of AuNPs provides a feasible pathway for electron transfer. The method was found to be simple, reliable and capable of high‐sensitive detection of human serum albumin as a model, down to 0.2 pg/ml in the range of 0.25–1000 pg/ml. Findings of the present study would create new opportunities for sensitive and rapid detection of various analytes.Inspec keywords: gold, filled polymers, conducting polymers, iron compounds, magnetic particles, nanoparticles, nanocomposites, nanosensors, electrochemical sensors, proteins, molecular biophysics, biomagnetism, biosensorsOther keywords: signal amplification strategy, gold‐N‐trimethyl chitosan‐iron oxide magnetic composite nanoparticles, tracer tag, high‐sensitive electrochemical detection, high‐sensitive electrochemical immunosensing, antibody, high‐density assembly, AuNP conductivity, electron transfer, human serum albumin, FeO‐Au     

Polymeric pH nanosensor with extended measurement range bearing octaarginine as cell penetrating peptide

A synthetic peptide octaarginine which mimics human immunodeficiency virus‐1, Tat protein is used as cell penetrating moiety for new pH nanosensors which demonstrate enhanced cellular uptake and expanded measurement range from pH 3.9 to pH 7.3 by simultaneously incorporating two complemental pH‐sensitive fluorophores in a same nanoparticle. The authors believe that this triple fluorescent pH sensor provides a new tool to pH measurements that can have application in cellular uptake mechanism study and new nanomedicine design.Inspec keywords: polymers, chemical sensors, nanosensors, biomembrane transport, microorganisms, proteins, biomimetics, biosensors, molecular configurations, biochemistry, molecular biophysics, nanoparticles, nanomedicine, nanocomposites, dyes, optical sensors, spectrochemical analysis, nanofabrication, biomedical measurementOther keywords: polymeric pH nanosensor, extended measurement range, octaarginine, cell penetrating peptide, synthetic peptide, human immunodeficiency virus‐1 Tat protein mimicking, cell penetrating moiety, complemental pH‐sensitive fluorophore incorporation, nanoparticle, triple fluorescent pH sensor, pH measurement, cellular uptake mechanism study, nanomedicine design     

Modelling epigenetic regulation of gene expression in 12 human cell types reveals combinatorial patterns of cell‐type‐specific genes

The maintenance of the diverse cell types in a multicellular organism is one of the fundamental mysteries of biology. Modelling the dynamic regulatory relationships between the histone modifications and the gene expression across the diverse cell types is essential for the authors to understand the mechanisms of the epigenetic regulation. Here, the authors thoroughly assessed the histone modification enrichment profiles at the promoters and constructed quantitative models between the histone modification abundances and the gene expression in 12 human cell types. The author''s results showed that the histone modifications at the promoters exhibited remarkably cell‐type‐dependent variability in the cell‐type‐specific (CTS) genes. They demonstrated that the variable profiles of the modifications are highly predictive for the dynamic changes of the gene expression across all the cell types. Their findings revealed the close relationship between the combinatorial patterns of the histone modifications and the CTS gene expression. They anticipate that the findings and the methods they used in this study could provide useful information for the future studies of the regulatory roles of the histone modifications in the CTS genes.Inspec keywords: cellular biophysics, genetics, genomics, physiological models, proteinsOther keywords: CTS gene expression, variable profiles, cell‐type‐dependent variability, histone modification abundances, constructed quantitative models, promoters, histone modification enrichment profiles, dynamic regulatory relationship modelling, biology, multicellular organism, cell‐type‐specific genes, combinatorial patterns, human cell types, epigenetic regulation modelling     

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     

Mechanism study of silver nanoparticle production using Neurospora intermedia

Elucidation of the molecular mechanism of silver nanoparticle (AgNP) synthesis is necessary to control nanoparticle size, shape, and monodispersity. In this study, the mechanism of AgNP formation by Neurospora intermedia was investigated. The higher production rate of AgNP formation using a culture supernatant heat‐treated at 100° and 121°C relative to that with an un‐treated culture supernatant indicated that the native form of the molecular species is not essential. The effect of the protein molecular weight (MW) on the nanoparticle size distribution and average size was studied by means of ultraviolet–visible spectroscopy and dynamic light scattering. Using un‐treated and concentrated cell‐free filtrate passed through 10 and 20 kDa cut‐off filters led to the production of AgNPs with average sizes of 25, 30, and 34 nm, respectively. Also, using the permeate fraction of cell‐free filtrate passed through a 100 kDa cut‐off filter led to the formation of the smallest nanoparticles with the narrowest size distribution (average size of 16 nm and polydispersity index of 0.18). Sodium dodecyl sulphate polyacrylamide gel electrophoresis analysis of the fungal extracellular proteins showed two notable bands with the MWs of 15 and 23 kDa that are involved in the reduction and stabilisation of the nanoparticles, respectively.Inspec keywords: silver, nanoparticles, nanofabrication, proteins, molecular weight, ultraviolet spectra, visible spectra, cellular biophysics, electrophoresis, molecular biophysicsOther keywords: Neurospora intermedia, molecular mechanism, silver nanoparticle synthesis, nanoparticle shape, nanoparticle monodispersity, AgNP formation, untreated culture supernatant, molecular species, protein molecular weight, MW, nanoparticle size distribution, ultraviolet‐visible spectroscopy, dynamic light scattering, untreated cell‐free filtrate, concentrated cell‐free filtrate, cut‐off filters, permeate fraction, polydispersity index, Sodium dodecyl sulphate polyacrylamide gel electrophoresis analysis, fungal extracellular proteins, nanoparticle reduction, nanoparticle stabilisation, temperature 100 degC, temperature 121 degC, size 25 nm, size 30 nm, size 34 nm, size 16 nm, Ag     

Optical detection of CA 15.3 breast cancer antigen using CdS quantum dot

The present study focus on optical sensing of breast cancer antigen 15.3 (CA 15.3) using cadmium sulphide quantum dot (CdS‐QD) in saline and serum samples spiked with antigen. The surface of CdS‐QD was modified by cysteamine capping followed by tagging of CA 15.3 antibody. The samples were characterised using UV‐visible absorption spectroscopy (UV‐VIS Spectroscopy), Fourier transform infrared spectroscopy (FTIR), high‐resolution transmission electron microscopy (HRTEM) attached with energy‐dispersive X‐ray spectroscopy, phase contrast inverted epi‐fluorescence microscopy and photoluminescence (PL) spectrophotometry (EDS). The CdS‐QD showed a mean diameter of 3.02 ± 0.6 nm. The complex formed after antigen‐antibody interaction resulted in distinguishable optical and fluorescence intensity with respect to varying concentration of antigen. The PL study revealed that CA 15.3 antibody labelled CdS QD can detect CA 15.3 tumour marker even at very low concentration of 0.002 KU/L with a constant response time of 15 min. This study clearly indicates that detection of CA 15.3 at low concentration is possible using surface modified CdS QD in serum samples and can find immense applications in biosensor development for detection of breast cancer marker similar to various automated detection kits available in market.Inspec keywords: semiconductor quantum dots, cadmium compounds, II‐VI semiconductors, wide band gap semiconductors, cancer, tumours, optical sensors, biosensors, biomedical equipment, visible spectra, ultraviolet spectra, Fourier transform infrared spectra, transmission electron microscopy, X‐ray chemical analysis, fluorescence, optical microscopy, photoluminescence, proteins, molecular biophysics, nanosensors, nanomedicine, nanoparticlesOther keywords: optical detection, CA 15.3 breast cancer antigen, optical sensing, cadmium sulphide quantum dot, saline samples, serum samples, cysteamine capping, CA 15.3 antibody, UV‐visible absorption spectroscopy, Fourier transform infrared spectroscopy, high‐resolution transmission electron microscopy, energy dispersive X‐ray spectroscopy, phase contrast inverted epifluorescence microscopy, photoluminescence spectrophotometry, antigen‐antibody interaction, fluorescence intensity, optical intensity, CA 15.3 tumour marker, surface modified CdS QD, biosensor development, time 15 min, CdS     

Comparison of the effects of three kinds of IgYs, (normal,nanoliposomal and nanoparticle conjugated), which are produced against the small domains of DR5 protein on cancer cells

Cancer treatment with several kinds of drugs, especially targets the apoptotic pathways nowadays. TNF‐related apoptosis‐inducing ligand (TRAIL) as one of the important members of death receptors, significantly trigger induction of apoptosis in cancer cells. Three conserved domains of Death receptor (DR5) protein extracellular domain, which are fortified cysteine, were chosen and chemically synthesised. Hens were immunised with nano‐liposomal peptides, and as a result the purified Immunoglobulin (IgYs) remarkably killed the cancerous MCF7 cells. The flow cytometric assay, confirmed the apoptotic death. Among several kinds of carriers that were used in this research, the nano‐liposomal and nanoparticle conjugated, both were acceptable choices for drug delivery. Furthermore, the IgY against DR5''s small peptides with such carriers successfully reached the target and significantly killed the cancer cells via apoptosis.Inspec keywords: proteins, cancer, cellular biophysics, nanoparticles, nanomedicine, drug delivery systems, molecular biophysics, purification, biochemistryOther keywords: nanoparticle, cancer cells, cancer treatment, apoptotic pathways, DR5 protein extracellular domain, fortified cysteine, nanoliposomal peptides, purified IgY, cancerous MCF7 cells, flow cytometric assay, apoptotic death, drug delivery     

Overcoming the blood–brain barrier in neurodegenerative disorders and brain tumours

Drug delivery is one of the major challenges in the treatment of central nervous system disorders. The brain needs to be protected from harmful agents, which are done by the capillary network, the so‐called blood–brain barrier (BBB). This protective guard also prevents the delivery of therapeutic agents to the brain and limits the effectiveness of treatment. For this reason, various strategies have been explored by scientists for overcoming the BBB from disruption of the BBB to targeted delivery of nanoparticles (NPs) and cells and immunotherapy. In this review, different promising brain drug delivery strategies including disruption of tight junctions in the BBB, enhanced transcellular transport by peptide‐based delivery, local delivery strategies, NP delivery, and cell‐based delivery have been fully discussed.Inspec keywords: drugs, tumours, neurophysiology, blood, biochemistry, brain, drug delivery systems, nanoparticles, biomedical materials, molecular biophysics, cellular biophysics, nanomedicine, diseases, proteins, reviewsOther keywords: blood–brain barrier, neurodegenerative disorders, central nervous system disorders, BBB, therapeutic agents, targeted delivery, peptide‐based delivery, local delivery strategies, NP delivery, cell‐based delivery, brain drug delivery strategies, brain tumours, nanoparticles, immunotherapy, review     

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     

Identify asthma genes across three phases based on protein–protein interaction network

Asthma is a common inflammatory disease that is generally caused by genetic mutations or environmental factors. Recently, the emerging of omics data provides an alternative way to understand asthma. In this study, the authors present a new framework to detect asthma disease genes based on protein–protein interaction network (PPIN) and gene expression. Specifically, they construct PPINs for different stages of asthma, and detect those interactions occurred in the specific stages. By investigating the proteins in these stage‐specific interactions, they find they are more likely related to asthma, and the functional enrichment analysis indicate that the pathways enriched in the differential interactions are related to the progress of asthma. Moreover, some proteins in the differential interactions have been previously reported to be related to asthma in the literature, implying the usefulness of the proposed approach.Inspec keywords: genomics, proteins, molecular biophysics, lung, pneumodynamics, diseases, genetics, molecule‐molecule reactions, molecule‐molecule collisionsOther keywords: asthma gene identification, three‐phase gene identification, protein–protein interaction network, common inflammatory disease, genetic mutation‐caused disease, environmental factors, asthma‐associated omics data, asthma disease gene detection, PPIN construction, asthma gene expression, asthma stages, stage‐specific interaction proteins, asthma stage‐specific interactions, asthma‐related interactions, functional enrichment analysis, asthma progress‐related differential interactions, differential interaction proteins     

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