Displaying publications 1 - 20 of 602 in total

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  1. Abbasi MA, Hassan M, Ur-Rehman A, Siddiqui SZ, Hussain G, Shah SAA, et al.
    Comput Biol Chem, 2018 Dec;77:72-86.
    PMID: 30245349 DOI: 10.1016/j.compbiolchem.2018.09.007
    The heterocyclic compounds have been extensively reported for their bioactivity potential. The current research work reports the synthesis of some new multi-functional derivatives of 2-furoic piperazide (1; 1-(2-furoyl)piperazine). The synthesis was initiated by reacting the starting compound 1 with 3,5-dichloro-2-hydroxybenzenesulfonyl chloride (2) in a basic, polar and protic medium to obtain the parent sulfonamide 3 which was then treated with different electrophiles, 4a-g, in a polar and aprotic medium to acquire the designed molecules, 5a-g. These convergent derivatives were evaluated for their inhibitory potential against α-glucosidase, acetylcholinesterase (AChE) and butyrylcholinesterase (BChE) enzymes. Acarbose was used as a reference standard for α-glucosidase inhibition while eserine for AChE and BChE inhibition. Some of the synthesized compounds were identified as promising inhibitors of these three enzymes and their bioactivity potentials were also supported by molecular docking study. The most active compounds among the synthetic analogues might be helpful in drug discovery and development for the treatment of type 2 diabetes and Alzhiemer's diseases.
    Matched MeSH terms: Computer Simulation
  2. Alkinani MH, Almazroi AA, Jhanjhi NZ, Khan NA
    Sensors (Basel), 2021 Oct 18;21(20).
    PMID: 34696118 DOI: 10.3390/s21206905
    Internet of Things (IoT) and 5G are enabling intelligent transportation systems (ITSs). ITSs promise to improve road safety in smart cities. Therefore, ITSs are gaining earnest devotion in the industry as well as in academics. Due to the rapid increase in population, vehicle numbers are increasing, resulting in a large number of road accidents. The majority of the time, casualties are not appropriately discovered and reported to hospitals and relatives. This lack of rapid care and first aid might result in life loss in a matter of minutes. To address all of these challenges, an intelligent system is necessary. Although several information communication technologies (ICT)-based solutions for accident detection and rescue operations have been proposed, these solutions are not compatible with all vehicles and are also costly. Therefore, we proposed a reporting and accident detection system (RAD) for a smart city that is compatible with any vehicle and less expensive. Our strategy aims to improve the transportation system at a low cost. In this context, we developed an android application that collects data related to sound, gravitational force, pressure, speed, and location of the accident from the smartphone. The value of speed helps to improve the accident detection accuracy. The collected information is further processed for accident identification. Additionally, a navigation system is designed to inform the relatives, police station, and the nearest hospital. The hospital dispatches UAV (i.e., drone with first aid box) and ambulance to the accident spot. The actual dataset from the Road Safety Open Repository is used for results generation through simulation. The proposed scheme shows promising results in terms of accuracy and response time as compared to existing techniques.
    Matched MeSH terms: Computer Simulation
  3. Lim WL, Wibowo A, Desa MI, Haron H
    Comput Intell Neurosci, 2016;2016:5803893.
    PMID: 26819585 DOI: 10.1155/2016/5803893
    The quadratic assignment problem (QAP) is an NP-hard combinatorial optimization problem with a wide variety of applications. Biogeography-based optimization (BBO), a relatively new optimization technique based on the biogeography concept, uses the idea of migration strategy of species to derive algorithm for solving optimization problems. It has been shown that BBO provides performance on a par with other optimization methods. A classical BBO algorithm employs the mutation operator as its diversification strategy. However, this process will often ruin the quality of solutions in QAP. In this paper, we propose a hybrid technique to overcome the weakness of classical BBO algorithm to solve QAP, by replacing the mutation operator with a tabu search procedure. Our experiments using the benchmark instances from QAPLIB show that the proposed hybrid method is able to find good solutions for them within reasonable computational times. Out of 61 benchmark instances tested, the proposed method is able to obtain the best known solutions for 57 of them.
    Matched MeSH terms: Computer Simulation*
  4. Abiri R, Abdul-Hamid H, Sytar O, Abiri R, Bezerra de Almeida E, Sharma SK, et al.
    Molecules, 2021 Jun 24;26(13).
    PMID: 34202844 DOI: 10.3390/molecules26133868
    The COVID-19 pandemic, as well as the more general global increase in viral diseases, has led researchers to look to the plant kingdom as a potential source for antiviral compounds. Since ancient times, herbal medicines have been extensively applied in the treatment and prevention of various infectious diseases in different traditional systems. The purpose of this review is to highlight the potential antiviral activity of plant compounds as effective and reliable agents against viral infections, especially by viruses from the coronavirus group. Various antiviral mechanisms shown by crude plant extracts and plant-derived bioactive compounds are discussed. The understanding of the action mechanisms of complex plant extract and isolated plant-derived compounds will help pave the way towards the combat of this life-threatening disease. Further, molecular docking studies, in silico analyses of extracted compounds, and future prospects are included. The in vitro production of antiviral chemical compounds from plants using molecular pharming is also considered. Notably, hairy root cultures represent a promising and sustainable way to obtain a range of biologically active compounds that may be applied in the development of novel antiviral agents.
    Matched MeSH terms: Computer Simulation
  5. Hasan MZ, Kamil AA, Mustafa A, Baten MA
    PLoS One, 2012;7(8):e42215.
    PMID: 22900009 DOI: 10.1371/journal.pone.0042215
    Banking system plays an important role in the economic development of any country. Domestic banks, which are the main components of the banking system, have to be efficient; otherwise, they may create obstacle in the process of development in any economy. This study examines the technical efficiency of the Malaysian domestic banks listed in the Kuala Lumpur Stock Exchange (KLSE) market over the period 2005-2010. A parametric approach, Stochastic Frontier Approach (SFA), is used in this analysis. The findings show that Malaysian domestic banks have exhibited an average overall efficiency of 94 percent, implying that sample banks have wasted an average of 6 percent of their inputs. Among the banks, RHBCAP is found to be highly efficient with a score of 0.986 and PBBANK is noted to have the lowest efficiency with a score of 0.918. The results also show that the level of efficiency has increased during the period of study, and that the technical efficiency effect has fluctuated considerably over time.
    Matched MeSH terms: Computer Simulation
  6. Seuk-Yen Phoong, Mohd Tahir Ismail
    Sains Malaysiana, 2015;44:1033-1039.
    Over the years, maximum likelihood estimation and Bayesian method became popular statistical tools in which applied to fit finite mixture model. These trends begin with the advent of computer technology during the last decades. Moreover, the asymptotic properties for both statistical methods also act as one of the main reasons that boost the popularity of the methods. The difference between these two approaches is that the parameters for maximum likelihood estimation are fixed, but unknown meanwhile the parameters for Bayesian method act as random variables with known prior distributions. In the present paper, both the maximum likelihood estimation and Bayesian method are applied to investigate the relationship between exchange rate and the rubber price for Malaysia, Thailand, Philippines and Indonesia. In order to identify the most plausible method between Bayesian method and maximum likelihood estimation of time series data, Akaike Information Criterion and Bayesian Information Criterion are adopted in this paper. The result depicts that the Bayesian method performs better than maximum likelihood estimation on financial data.
    Matched MeSH terms: Computer Simulation
  7. Tang JR, Mat Isa NA, Ch'ng ES
    PLoS One, 2015;10(11):e0142830.
    PMID: 26560331 DOI: 10.1371/journal.pone.0142830
    Despite the effectiveness of Pap-smear test in reducing the mortality rate due to cervical cancer, the criteria of the reporting standard of the Pap-smear test are mostly qualitative in nature. This study addresses the issue on how to define the criteria in a more quantitative and definite term. A negative Pap-smear test result, i.e. negative for intraepithelial lesion or malignancy (NILM), is qualitatively defined to have evenly distributed, finely granular chromatin in the nuclei of cervical squamous cells. To quantify this chromatin pattern, this study employed Fuzzy C-Means clustering as the segmentation technique, enabling different degrees of chromatin segmentation to be performed on sample images of non-neoplastic squamous cells. From the simulation results, a model representing the chromatin distribution of non-neoplastic cervical squamous cell is constructed with the following quantitative characteristics: at the best representative sensitivity level 4 based on statistical analysis and human experts' feedbacks, a nucleus of non-neoplastic squamous cell has an average of 67 chromatins with a total area of 10.827 μm2; the average distance between the nearest chromatin pair is 0.508 μm and the average eccentricity of the chromatin is 0.47.
    Matched MeSH terms: Computer Simulation
  8. Mollah MM, Jamal R, Mokhtar NM, Harun R, Mollah MN
    PLoS One, 2015;10(9):e0138810.
    PMID: 26413858 DOI: 10.1371/journal.pone.0138810
    Identifying genes that are differentially expressed (DE) between two or more conditions with multiple patterns of expression is one of the primary objectives of gene expression data analysis. Several statistical approaches, including one-way analysis of variance (ANOVA), are used to identify DE genes. However, most of these methods provide misleading results for two or more conditions with multiple patterns of expression in the presence of outlying genes. In this paper, an attempt is made to develop a hybrid one-way ANOVA approach that unifies the robustness and efficiency of estimation using the minimum β-divergence method to overcome some problems that arise in the existing robust methods for both small- and large-sample cases with multiple patterns of expression.
    Matched MeSH terms: Computer Simulation
  9. Wang S, Liu Q, Liu Y, Jia H, Abualigah L, Zheng R, et al.
    Comput Intell Neurosci, 2021;2021:6379469.
    PMID: 34531910 DOI: 10.1155/2021/6379469
    Based on Salp Swarm Algorithm (SSA) and Slime Mould Algorithm (SMA), a novel hybrid optimization algorithm, named Hybrid Slime Mould Salp Swarm Algorithm (HSMSSA), is proposed to solve constrained engineering problems. SSA can obtain good results in solving some optimization problems. However, it is easy to suffer from local minima and lower density of population. SMA specializes in global exploration and good robustness, but its convergence rate is too slow to find satisfactory solutions efficiently. Thus, in this paper, considering the characteristics and advantages of both the above optimization algorithms, SMA is integrated into the leader position updating equations of SSA, which can share helpful information so that the proposed algorithm can utilize these two algorithms' advantages to enhance global optimization performance. Furthermore, Levy flight is utilized to enhance the exploration ability. It is worth noting that a novel strategy called mutation opposition-based learning is proposed to enhance the performance of the hybrid optimization algorithm on premature convergence avoidance, balance between exploration and exploitation phases, and finding satisfactory global optimum. To evaluate the efficiency of the proposed algorithm, HSMSSA is applied to 23 different benchmark functions of the unimodal and multimodal types. Additionally, five classical constrained engineering problems are utilized to evaluate the proposed technique's practicable abilities. The simulation results show that the HSMSSA method is more competitive and presents more engineering effectiveness for real-world constrained problems than SMA, SSA, and other comparative algorithms. In the end, we also provide some potential areas for future studies such as feature selection and multilevel threshold image segmentation.
    Matched MeSH terms: Computer Simulation
  10. Masuyama N, Loo CK, Wermter S
    Int J Neural Syst, 2019 Jun;29(5):1850052.
    PMID: 30764724 DOI: 10.1142/S0129065718500521
    This paper attempts to solve the typical problems of self-organizing growing network models, i.e. (a) an influence of the order of input data on the self-organizing ability, (b) an instability to high-dimensional data and an excessive sensitivity to noise, and (c) an expensive computational cost by integrating Kernel Bayes Rule (KBR) and Correntropy-Induced Metric (CIM) into Adaptive Resonance Theory (ART) framework. KBR performs a covariance-free Bayesian computation which is able to maintain a fast and stable computation. CIM is a generalized similarity measurement which can maintain a high-noise reduction ability even in a high-dimensional space. In addition, a Growing Neural Gas (GNG)-based topology construction process is integrated into the ART framework to enhance its self-organizing ability. The simulation experiments with synthetic and real-world datasets show that the proposed model has an outstanding stable self-organizing ability for various test environments.
    Matched MeSH terms: Computer Simulation*
  11. Islam MT, Mahmud MZ, Islam MT, Kibria S, Samsuzzaman M
    Sci Rep, 2019 10 29;9(1):15491.
    PMID: 31664056 DOI: 10.1038/s41598-019-51620-z
    Globally, breast cancer is a major reason for female mortality. Due to the limitations of current clinical imaging, the researchers are encouraged to explore alternative and complementary tools to available techniques to detect the breast tumor in an earlier stage. This article outlines a new, portable, and low-cost microwave imaging (MWI) system using an iterative enhancing technique for breast imaging. A compact side slotted tapered slot antenna is designed for microwave imaging. The radiating fins of tapered slot antenna are modified by etching nine rectangular side slots. The irregular slots on the radiating fins enhance the electrical length as well as produce strong directive radiation due to the suppression of induced surface currents that radiate vertically at the outer edges of the radiating arms with end-fire direction. It has remarkable effects on efficiency and gain. With the addition of slots, the side-lobe levels are reduced, the gain of the main-lobe is increased and corrects the squint effects simultaneously, thus improving the characteristics of the radiation. For experimental validation, a heterogeneous breast phantom was developed that contains dielectric properties identical to real breast tissues with the inclusion of tumors. An alternative PC controlled and microcontroller-based mechanical MWI system is designed and developed to collect the antenna scattering signal. The radiated backscattered signals from the targeted area of the human body are analyzed to reveal the changes in dielectric properties in tissues. The dielectric constants of tumorous cells are higher than that of normal tissues due to their higher water content. The remarkable deviation of the scattered field is processed by using newly proposed Iteratively Corrected Delay and Sum (IC-DAS) algorithm and the reconstruction of the image of the phantom interior is done. The developed UWB (Ultra-Wideband) antenna based MWI has been able to perform the detection of tumorous cells in breast phantom that can pave the way to saving lives.
    Matched MeSH terms: Computer Simulation
  12. Islam MT, Islam MM, Samsuzzaman M, Faruque MR, Misran N
    Sensors (Basel), 2015 May 20;15(5):11601-27.
    PMID: 26007721 DOI: 10.3390/s150511601
    This paper presents a negative index metamaterial incorporated UWB antenna with an integration of complementary SRR (split-ring resonator) and CLS (capacitive loaded strip) unit cells for microwave imaging sensor applications. This metamaterial UWB antenna sensor consists of four unit cells along one axis, where each unit cell incorporates a complementary SRR and CLS pair. This integration enables a design layout that allows both a negative value of permittivity and a negative value of permeability simultaneous, resulting in a durable negative index to enhance the antenna sensor performance for microwave imaging sensor applications. The proposed MTM antenna sensor was designed and fabricated on an FR4 substrate having a thickness of 1.6 mm and a dielectric constant of 4.6. The electrical dimensions of this antenna sensor are 0.20 λ × 0.29 λ at a lower frequency of 3.1 GHz. This antenna sensor achieves a 131.5% bandwidth (VSWR < 2) covering the frequency bands from 3.1 GHz to more than 15 GHz with a maximum gain of 6.57 dBi. High fidelity factor and gain, smooth surface-current distribution and nearly omni-directional radiation patterns with low cross-polarization confirm that the proposed negative index UWB antenna is a promising entrant in the field of microwave imaging sensors.
    Matched MeSH terms: Computer Simulation
  13. Hasan MM, Faruque MRI, Islam SS, Islam MT
    Materials (Basel), 2016 Oct 13;9(10).
    PMID: 28773951 DOI: 10.3390/ma9100830
    The aim of this paper is to introduce a compact double-negative (DNG) metamaterial that exhibits a negative refractive index (NRI) bandwidth of more than 3.6 GHz considering the frequency from 2 to 14 GHz. In this framework, two arms of the designed unit cell are split in a way that forms a Modified-Z-shape structure of the FR-4 substrate material. The finite integration technique (FIT)-based Computer Simulation Technology (CST) Microwave Studio is applied for computation, and the experimental setup for measuring the performance is performed inside two waveguide ports. Therefore, the measured data complies well with the simulated data of the unit cell at 0-degree and 90-degree rotation angles. The designed unit cell shows a negative refractive index from 3.482 to 7.096 GHz (bandwidth of 3.61 GHz), 7.876 to 10.047 GHz (bandwidth of 2.171 GHz), and 11.594 to 14 GHz (bandwidth of 2.406 GHz) in the microwave spectra. The design also exhibits almost the same wide negative refractive index bandwidth in the major region of the C-band and X-band if it is rotated 90 degrees. However, the novelty of the proposed structure lies in its effective medium ratio of more than 4, wide bandwidth, and compact size.
    Matched MeSH terms: Computer Simulation
  14. Aalsalem MY, Khan WZ, Saad NM, Hossain MS, Atiquzzaman M, Khan MK
    PLoS One, 2016;11(7):e0158072.
    PMID: 27409082 DOI: 10.1371/journal.pone.0158072
    Wireless Sensor Networks (WSNs) are vulnerable to Node Replication attacks or Clone attacks. Among all the existing clone detection protocols in WSNs, RAWL shows the most promising results by employing Simple Random Walk (SRW). More recently, RAND outperforms RAWL by incorporating Network Division with SRW. Both RAND and RAWL have used SRW for random selection of witness nodes which is problematic because of frequently revisiting the previously passed nodes that leads to longer delays, high expenditures of energy with lower probability that witness nodes intersect. To circumvent this problem, we propose to employ a new kind of constrained random walk, namely Single Stage Memory Random Walk and present a distributed technique called SSRWND (Single Stage Memory Random Walk with Network Division). In SSRWND, single stage memory random walk is combined with network division aiming to decrease the communication and memory costs while keeping the detection probability higher. Through intensive simulations it is verified that SSRWND guarantees higher witness node security with moderate communication and memory overheads. SSRWND is expedient for security oriented application fields of WSNs like military and medical.
    Matched MeSH terms: Computer Simulation
  15. Hossain MI, Faruque MRI, Islam MT, Ullah MH
    Materials (Basel), 2014 Dec 25;8(1):57-71.
    PMID: 28787924 DOI: 10.3390/ma8010057
    A new design and analysis of a wide-band double-negative metamaterial, considering a frequency range of 0.5 to 7 GHz, is presented in this paper. Four different unit cells with varying design parameters are analyzed to evaluate the effects of the unit-cell size on the resonance frequencies of the metamaterial. Moreover, open and interconnected 2 × 2 array structures of unit cells are analyzed. The finite-difference time-domain (FDTD) method, based on the Computer Simulation Technology (CST) Microwave Studio, is utilized in the majority of this investigation. The experimental portion of the study was performed in a semi-anechoic chamber. Good agreement is observed between the simulated and measured S parameters of the developed unit cell and array. The designed unit cell exhibits negative permittivity and permeability simultaneously at S-band (2.95 GHz to 4.00 GHz) microwave frequencies. In addition, the designed unit cell can also operate as a double-negative medium throughout the C band (4.00 GHz to 4.95 GHz and 5.00 GHz to 5.57 GHz). At a number of other frequencies, it exhibits a single negative value. The two array configurations cause a slight shift in the resonance frequencies of the metamaterial and hence lead to a slight shift of the single- and double-negative frequency ranges of the metamaterial.
    Matched MeSH terms: Computer Simulation
  16. Daud NH, Leow TC, Oslan SN, Salleh AB
    Mol Biotechnol, 2019 Mar 27.
    PMID: 30919327 DOI: 10.1007/s12033-019-00169-3
    The application of native enzymes may not be economical owing to the stability factor. A smaller protein molecule may be less susceptible to external stresses. Haloalkane dehalogenases (HLDs) that act on toxic haloalkanes may be incorporated as bioreceptors to detect haloalkane contaminants. Therefore, this study aims to develop mini proteins of HLD as an alternative bioreceptor which was able to withstand extreme conditions. Initially, the mini proteins were designed through computer modeling. Based on the results, five designed mini proteins were deemed to be viable stable mini proteins. They were then validated through experimental study. The smallest mini protein (model 5) was chosen for subsequent analysis as it was expressed in soluble form. No dehalogenase activity was detected, thus the specific binding interaction of between 1,3-dibromopropane with mini protein was investigated using isothermal titration calorimetry. Higher binding affinity between 1,3-dibromopropane and mini protein was obtained than the native. Thermal stability study with circular dichroism had proven that the mini protein possessed two times higher Tm value at 83.73 °C than the native at 43.97 °C. In conclusion, a stable mini protein was successfully designed and may be used as bioreceptors in the haloalkane sensor that is suitable for industrial application.
    Matched MeSH terms: Computer Simulation
  17. Tang PW, Chua PS, Chong SK, Mohamad MS, Choon YW, Deris S, et al.
    Recent Pat Biotechnol, 2015;9(3):176-97.
    PMID: 27185502
    BACKGROUND: Predicting the effects of genetic modification is difficult due to the complexity of metabolic net- works. Various gene knockout strategies have been utilised to deactivate specific genes in order to determine the effects of these genes on the function of microbes. Deactivation of genes can lead to deletion of certain proteins and functions. Through these strategies, the associated function of a deleted gene can be identified from the metabolic networks.

    METHODS: The main aim of this paper is to review the available techniques in gene knockout strategies for microbial cells. The review is done in terms of their methodology, recent applications in microbial cells. In addition, the advantages and disadvantages of the techniques are compared and discuss and the related patents are also listed as well.

    RESULTS: Traditionally, gene knockout is done through wet lab (in vivo) techniques, which were conducted through laboratory experiments. However, these techniques are costly and time consuming. Hence, various dry lab (in silico) techniques, where are conducted using computational approaches, have been developed to surmount these problem.

    CONCLUSION: The development of numerous techniques for gene knockout in microbial cells has brought many advancements in the study of gene functions. Based on the literatures, we found that the gene knockout strategies currently used are sensibly implemented with regard to their benefits.

    Matched MeSH terms: Computer Simulation
  18. Adnan AI, Hanapi ZM, Othman M, Zukarnain ZA
    PLoS One, 2017;12(1):e0170273.
    PMID: 28121992 DOI: 10.1371/journal.pone.0170273
    Due to the lack of dependency for routing initiation and an inadequate allocated sextant on responding messages, the secure geographic routing protocols for Wireless Sensor Networks (WSNs) have attracted considerable attention. However, the existing protocols are more likely to drop packets when legitimate nodes fail to respond to the routing initiation messages while attackers in the allocated sextant manage to respond. Furthermore, these protocols are designed with inefficient collection window and inadequate verification criteria which may lead to a high number of attacker selections. To prevent the failure to find an appropriate relay node and undesirable packet retransmission, this paper presents Secure Region-Based Geographic Routing Protocol (SRBGR) to increase the probability of selecting the appropriate relay node. By extending the allocated sextant and applying different message contention priorities more legitimate nodes can be admitted in the routing process. Moreover, the paper also proposed the bound collection window for a sufficient collection time and verification cost for both attacker identification and isolation. Extensive simulation experiments have been performed to evaluate the performance of the proposed protocol in comparison with other existing protocols. The results demonstrate that SRBGR increases network performance in terms of the packet delivery ratio and isolates attacks such as Sybil and Black hole.
    Matched MeSH terms: Computer Simulation
  19. Yazdani S, Yusof R, Karimian A, Riazi AH, Bennamoun M
    Comput Math Methods Med, 2015;2015:829893.
    PMID: 26089978 DOI: 10.1155/2015/829893
    Brain MRI segmentation is an important issue for discovering the brain structure and diagnosis of subtle anatomical changes in different brain diseases. However, due to several artifacts brain tissue segmentation remains a challenging task. The aim of this paper is to improve the automatic segmentation of brain into gray matter, white matter, and cerebrospinal fluid in magnetic resonance images (MRI). We proposed an automatic hybrid image segmentation method that integrates the modified statistical expectation-maximization (EM) method and the spatial information combined with support vector machine (SVM). The combined method has more accurate results than what can be achieved with its individual techniques that is demonstrated through experiments on both real data and simulated images. Experiments are carried out on both synthetic and real MRI. The results of proposed technique are evaluated against manual segmentation results and other methods based on real T1-weighted scans from Internet Brain Segmentation Repository (IBSR) and simulated images from BrainWeb. The Kappa index is calculated to assess the performance of the proposed framework relative to the ground truth and expert segmentations. The results demonstrate that the proposed combined method has satisfactory results on both simulated MRI and real brain datasets.
    Matched MeSH terms: Computer Simulation
  20. Mohamad SB, Ong AL, Khairuddin RF, Ripen AM
    In Silico Biol. (Gedrukt), 2010;10(3):145-53.
    PMID: 22430288 DOI: 10.3233/ISB-2010-0423
    Laccases are industrially attractive enzymes and their applications have expanded to the field of bioremediation. The challenge of today's biotechnology in enzymatic studies is to design enzymes that not only have a higher activity but are also more stable and could fit well with the condition requirements. Laccases are known to oxidize non-natural substrates like polycyclic aromatic hydrocarbons (PAHs). We suppose by increasing the hydrophobicity of laccase, it would increase the chance of the enzyme to meet the hydrophobic substrates in a contamination site, therefore increasing the bioremediation efficacy of PAHs from environment. In this attempt, the applications of evolutionary trace (ET), molecular surface accessibility and hydrophobicity analysis on laccase sequences and laccase's crystal structure (1KYA) are described for optimal design of an enzyme with higher hydrophobicity. Our analysis revealed that Q23A, Q45I, N141A, Q237V, N262L, N301V, N331A, Q360L and Q482A could be promising exchanges to be tested in mutagenesis experiments.
    Matched MeSH terms: Computer Simulation
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