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Mohammadi M, Razmara J, Hadizadeh M, Parvizpour S, Shahir Shamsir M. Peptide vaccine design against glioblastoma by applying immunoinformatics approach. Int Immunopharmacol 2024; 142:113219. [PMID: 39340993 DOI: 10.1016/j.intimp.2024.113219] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2024] [Revised: 09/15/2024] [Accepted: 09/18/2024] [Indexed: 09/30/2024]
Abstract
Brain tumors are considered to be one of the most fatal forms of cancer owing to their highly aggressive attributes, diverse characteristics, and notably low rate of survival. Among these tumors, glioblastoma stands out as the prevalent and perilous variant Despite the present advancements in surgical procedures, pharmacological treatment, and radiation therapy, the overall prognosis remains notably unfavorable, as merely 4.3 % of individuals manage to attain a five-year survival rate; For this reason, it has emerged as a challenge for cancer researchers. Therefore, among several immunotherapy methods, using peptide-based vaccines for cancer treatment is considered promising due to their ability to generate a focused immune response with minimal damage. This study endeavors to devise a multi-epitope vaccine utilizing an immunoinformatics methodology to address the challenge posed by glioblastoma disease. Through this approach, it is anticipated that the duration and expenses associated with vaccine manufacturing can be diminished, while simultaneously enhancing the characteristics of the vaccine. The target gene in this research is ITGA5, which was achieved through TCGA analysis by targeting the PI3K-Akt pathway as a significant association with patient survival. Subsequently, the suitable epitopes of T and B cells were selected through various immunoinformatics tools by analyzing their sequence. Then, nine epitopes were merged with GM-CSF as an adjuvant to enhance immunogenicity. The outcomes encompass molecular docking, molecular dynamics (MD) simulation, simulation of the immune response, prognosis and confirmation of the secondary and tertiary structure, Chemical and physical characteristics, toxicity, as well as antigenicity and allergenicity of the potential vaccine candidate against glioblastoma.
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Parvizpour S, Beyrampour-Basmenj H, Razmara J, Farhadi F, Shamsir MS. Cancer treatment comes to age: from one-size-fits-all to next-generation sequencing (NGS) technologies. BIOIMPACTS : BI 2023; 14:29957. [PMID: 39104623 PMCID: PMC11298019 DOI: 10.34172/bi.2023.29957] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/21/2023] [Revised: 11/08/2023] [Accepted: 11/14/2023] [Indexed: 08/07/2024]
Abstract
Cancer is one of the leading causes of death worldwide and one of the greatest challenges in extending life expectancy. The paradigm of one-size-fits-all medicine has already given way to the stratification of patients by disease subtypes, clinical characteristics, and biomarkers (stratified medicine). The introduction of next-generation sequencing (NGS) in clinical oncology has made it possible to tailor cancer patient therapy to their molecular profiles. NGS is expected to lead the transition to precision medicine (PM), where the right therapeutic approach is chosen for each patient based on their characteristics and mutations. Here, we highlight how the NGS technology facilitates cancer treatment. In this regard, first, precision medicine and NGS technology are reviewed, and then, the NGS revolution in precision medicine is described. In the sequel, the role of NGS in oncology and the existing limitations are discussed. The available databases and bioinformatics tools and online servers used in NGS data analysis are also reviewed. The review ends with concluding remarks.
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Khatir RA, Izadkhah H, Razmara J. Designing a Novel Approach Using a Greedy and Information-Theoretic Clustering-Based Algorithm for Anonymizing Microdata Sets. ENTROPY (BASEL, SWITZERLAND) 2023; 25:1613. [PMID: 38136493 PMCID: PMC10742671 DOI: 10.3390/e25121613] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/19/2023] [Revised: 11/16/2023] [Accepted: 11/22/2023] [Indexed: 12/24/2023]
Abstract
Data anonymization is a technique that safeguards individuals' privacy by modifying attribute values in published data. However, increased modifications enhance privacy but diminish the utility of published data, necessitating a balance between privacy and utility levels. K-Anonymity is a crucial anonymization technique that generates k-anonymous clusters, where the probability of disclosing a record is 1/k. However, k-anonymity fails to protect against attribute disclosure when the diversity of sensitive values within the anonymous cluster is insufficient. Several techniques have been proposed to address this issue, among which t-closeness is considered one of the most robust privacy techniques. In this paper, we propose a novel approach employing a greedy and information-theoretic clustering-based algorithm to achieve strict privacy protection. The proposed anonymization algorithm commences by clustering the data based on both the similarity of quasi-identifier values and the diversity of sensitive attribute values. In the subsequent adjustment phase, the algorithm splits and merges the clusters to ensure that they each possess at least k members and adhere to the t-closeness requirements. Finally, the algorithm replaces the quasi-identifier values of the records in each cluster with the values of the cluster center to attain k-anonymity and t-closeness. Experimental results on three microdata sets from Facebook, Twitter, and Google+ demonstrate the proposed algorithm's ability to preserve the utility of released data by minimizing the modifications of attribute values while satisfying the k-anonymity and t-closeness constraints.
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Amiri R, Razmara J, Parvizpour S, Izadkhah H. A novel efficient drug repurposing framework through drug-disease association data integration using convolutional neural networks. BMC Bioinformatics 2023; 24:442. [PMID: 37993777 PMCID: PMC10664633 DOI: 10.1186/s12859-023-05572-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2023] [Accepted: 11/17/2023] [Indexed: 11/24/2023] Open
Abstract
Drug repurposing is an exciting field of research toward recognizing a new FDA-approved drug target for the treatment of a specific disease. It has received extensive attention regarding the tedious, time-consuming, and highly expensive procedure with a high risk of failure of new drug discovery. Data-driven approaches are an important class of methods that have been introduced for identifying a candidate drug against a target disease. In the present study, a model is proposed illustrating the integration of drug-disease association data for drug repurposing using a deep neural network. The model, so-called IDDI-DNN, primarily constructs similarity matrices for drug-related properties (three matrices), disease-related properties (two matrices), and drug-disease associations (one matrix). Then, these matrices are integrated into a unique matrix through a two-step procedure benefiting from the similarity network fusion method. The model uses a constructed matrix for the prediction of novel and unknown drug-disease associations through a convolutional neural network. The proposed model was evaluated comparatively using two different datasets including the gold standard dataset and DNdataset. Comparing the results of evaluations indicates that IDDI-DNN outperforms other state-of-the-art methods concerning prediction accuracy.
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Parvizpour S, Elengoe A, Alizadeh E, Razmara J, Shamsir MS. In silico targeting breast cancer biomarkers by applying rambutan ( Nephelium lappaceum) phytocompounds. J Biomol Struct Dyn 2023; 41:10037-10050. [PMID: 36451602 DOI: 10.1080/07391102.2022.2152868] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2022] [Accepted: 11/23/2022] [Indexed: 12/03/2022]
Abstract
Worldwide, breast cancer is the leading type of cancer among women. Overexpression of various prognostic indicators, including nuclear receptors, is linked to breast cancer features. To date, no effective drug has been discovered to block the proliferation of breast cancer cells. This study has been designed to discover target-based small molecular-like natural drug candidates that have anti-cancer potential without causing any serious side effects. A comprehensive substrate-based drug design was carried out to discover the potential plant compounds against the target breast cancer biomarkers including phytochemicals screening, active site identification, molecular docking, pharmacokinetic (PK) properties prediction, toxicity prediction, and molecular dynamics (MD) simulation approaches. Twenty plant compounds extracted from the rambutan (Nephelium lappaceum) were obtained from PubChem Database; and screened against the breast cancer biomarkers including estrogen receptor (ER), progesterone receptor (PR), and androgen receptor (AR). The best docking interaction was chosen based on the higher binding affinity. Analyzing the pharmacokinetic properties and toxicity prediction results indicated that the fifteen selected plant compounds have good potency without toxicity and are safe for humans. Four phytochemicals with a higher binding affinity were chosen for each breast cancer biomarker to study their stability in interaction with the target proteins using MD simulation. Among the above compounds, Ellagic acid showed the high binding affinity against all three breast cancer biomarkers.Communicated by Ramaswamy H. Sarma.
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Omidian H, Razmara J, Parvizpour S, Tabrizchi H, Masoudi-Sobhanzadeh Y, Omidi Y. Tracing drugs from discovery to disposal. Drug Discov Today 2023; 28:103538. [PMID: 36828192 DOI: 10.1016/j.drudis.2023.103538] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Revised: 02/08/2023] [Accepted: 02/14/2023] [Indexed: 02/24/2023]
Abstract
The life cycle of a drug begins with discovery and ends with its disposal. Drug discovery companies, drug manufacturers, regulatory agencies, suppliers, pharmacies, patients, healthcare providers, and many more are involved in this process. Transparency, traceability, automation, and data security are some of the most crucial factors affecting how effectively and safely the transactions are conducted across all parties involved in the cycle. By contrast, scalability, energy consumption, regulation, standards, and complexity hamper the adoption of new technology that is expected to fulfil these requirements. Here, we highlight how blockchain technology can track, accelerate, and boost the efficiency of incredibly complicated operations, such as pharmaceutical development.
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Parvizpour S, Masoudi-Sobhanzadeh Y, Pourseif MM, Barzegari A, Razmara J, Omidi Y. Pharmacoinformatics-based phytochemical screening for anticancer impacts of yellow sweet clover, Melilotus officinalis (Linn.) Pall. Comput Biol Med 2021; 138:104921. [PMID: 34656871 DOI: 10.1016/j.compbiomed.2021.104921] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2021] [Revised: 10/03/2021] [Accepted: 10/05/2021] [Indexed: 11/24/2022]
Abstract
To date, much attention has been paid to phytochemicals because of their diverse pharmacological effects on a variety of diseases such as cancer. In this regard, computer-aided drug design, as a cost- and time-effective approach, is primarily applied to investigate the drug candidates before their further costly in vitro and in vivo experimental evaluations. Accordingly, different signaling pathways and proteins can be targeted using such strategies. As a key protein for the initiation of eukaryotic DNA replication, mini-chromosome maintenance complex component 7 (MCM7) overexpression is related to the initiation and progression of aggressive malignancies. The current study was conducted to identify new potential natural compounds from the yellow sweet clover, Melilotus officinalis (Linn.) Pall, by examining the potential of 40 isolated phytochemicals against MCM7 protein. A structure-based pharmacophore model to the protein active site cavity was generated and followed by virtual screening and molecular docking. Overall, four compounds were selected for further evaluation based on their binding affinities. Our analyses revealed that two novel compounds, namely rosmarinic acid (PubChem CID:5281792) and melilotigenin (PubChem CID:14059499) might be druggable and offer safe usage in human. The stability of these two protein-ligand complex structures was confirmed through molecular dynamics simulation. The findings of this study reveal the potential of these two phytochemicals to serve as anticancer agents, while further pharmacological experiments are required to confirm their effectiveness against human cancers.
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Mirzaei S, Razmara J, Lotfi S. GADP-align: A genetic algorithm and dynamic programming-based method for structural alignment of proteins. BIOIMPACTS 2020; 11:271-279. [PMID: 34631489 PMCID: PMC8494253 DOI: 10.34172/bi.2021.37] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/03/2020] [Revised: 06/10/2020] [Accepted: 06/16/2020] [Indexed: 11/16/2022]
Abstract
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Introduction: Similarity analysis of protein structure is considered as a fundamental step to give insight into the relationships between proteins. The primary step in structural alignment is looking for the optimal correspondence between residues of two structures to optimize the scoring function. An exhaustive search for finding such a correspondence between two structures is intractable.
Methods: In this paper, a hybrid method is proposed, namely GADP-align, for pairwise protein structure alignment. The proposed method looks for an optimal alignment using a hybrid method based on a genetic algorithm and an iterative dynamic programming technique. To this end, the method first creates an initial map of correspondence between secondary structure elements (SSEs) of two proteins. Then, a genetic algorithm combined with an iterative dynamic programming algorithm is employed to optimize the alignment.
Results: The GADP-align algorithm was employed to align 10 ‘difficult to align’ protein pairs in order to evaluate its performance. The experimental study shows that the proposed hybrid method produces highly accurate alignments in comparison with the methods using exactly the dynamic programming technique. Furthermore, the proposed method prevents the local optimal traps caused by the unsuitable initial guess of the corresponding residues.
Conclusion: The findings of this paper demonstrate that employing the genetic algorithm along with the dynamic programming technique yields highly accurate alignments between a protein pair by exploring the global alignment and avoiding trapping in local alignments.
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Parvizpour S, Pourseif MM, Razmara J, Rafi MA, Omidi Y. Epitope-based vaccine design: a comprehensive overview of bioinformatics approaches. Drug Discov Today 2020; 25:1034-1042. [DOI: 10.1016/j.drudis.2020.03.006] [Citation(s) in RCA: 46] [Impact Index Per Article: 9.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2019] [Revised: 01/12/2020] [Accepted: 03/06/2020] [Indexed: 12/26/2022]
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Parvizpour S, Jomah AF, Razmara J. Structural and Functional Analysis of Mutated Human Pyrin B30.2 Domain. CURR PROTEOMICS 2020. [DOI: 10.2174/1570164616666190628165835] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Abstract
Background:
Familial Mediterranean Fever (FMF) is a prototypical hereditary
autoinflammatory disease affecting principally Mediterranean populations and characterized by
recurrent frequent fever and inflammation. The disease is essentially caused by inherited mutations in
the MEFV gene which encodes pyrin protein. The reported mutations are mostly located on the B30.2
domain in the C-terminal end of the protein.
Objective:
The present study reports a structural comparison of the five most common mutated
structures including M694V, V726A, M694I, R761H, and M680I. The aim of this study was to
determine the structural and functional disorders caused by the mutations in the human pyrin protein.
Results:
The comparison revealed that all mutations make overall changes in the structure of the
domain. Further, the effects of these mutations on structural and molecular behavior of the B30.2
domain were compared with the native structure using MD simulation by GROMACS software. The
results revealed that all the studied mutants have a destabilizing effect on the protein structure.
Additionally, analyzing the projection of the motions of the proteins in phase space demonstrates high
rigidity of the mutated structures in comparison with the native protein.
Conclusion:
The results of simulations elucidate how the mutations affect the physiological
functioning of the pyrin B30.2 domain and cause the occurrence of the FMF disease.
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Parvizpour S, Razmara J, Shamsir MS. Temperature adaptation analysis of a psychrophilic mannanase through structural, functional and molecular dynamics simulation. MOLECULAR SIMULATION 2018. [DOI: 10.1080/08927022.2018.1492721] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/28/2022]
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Parvizpour S, Razmara J, Pourseif MM, Omidi Y. In silico design of a triple-negative breast cancer vaccine by targeting cancer testis antigens. ACTA ACUST UNITED AC 2018; 9:45-56. [PMID: 30788259 PMCID: PMC6378095 DOI: 10.15171/bi.2019.06] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2018] [Revised: 04/10/2018] [Accepted: 04/14/2018] [Indexed: 12/14/2022]
Abstract
Introduction: Triple-negative breast cancer (TNBC) is an important subtype of breast cancer, which occurs in the absence of estrogen, progesterone and HER-2 receptors. According to the recent studies, TNBC may be a cancer testis antigen (CTA)-positive tumor, indicating that the CTA-based cancer vaccine can be a treatment option for the patients bearing such tumors. Of these antigens (Ags), the MAGE-A family and NY-ESO-1 as the most immunogenic CTAs are the potentially relevant targets for the development of an immunotherapeutic way of the breast cancer treatment. Methods: In the present study, immunoinformatics approach was used to design a multi-epitope peptide vaccine to combat the TNBC. The vaccine peptide was constructed by the fusion of three crucial components, including the CD8+ cytotoxic T lymphocytes (CTLs) epitopes, helper epitopes and adjuvant. The epitopes were predicted from the MAGE-A and NY-ESO-1 Ags. In addition, the granulocyte-macrophage-colony-stimulating factor (GM-CSF) was used as an adjuvant to promote the CD4+ T cells towards the T-helper for more strong induction of CTL responses. The components were conjugated by proper linkers. Results: The vaccine peptide was examined for different physiochemical characteristics to confirm the safety and immunogenic behavior. Furthermore, the 3D-structure of the vaccine peptide was predicted based on the homology modeling approach using the MODELLER v9.17 program. The vaccine structure was also subjected to the molecular dynamics simulation study for structure refinement. The results verified the immunogenicity and safety profile of the constructed vaccine as well as its capability for stimulating both the cellular and humoral immune responses. Conclusion: Based on our in-silico analyses, the proposed vaccine may be considered for the immunotherapy of TNBC.
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Parvizpour S, Razmara J, Omidi Y. Breast cancer vaccination comes to age: impacts of bioinformatics. ACTA ACUST UNITED AC 2018; 8:223-235. [PMID: 30211082 PMCID: PMC6128970 DOI: 10.15171/bi.2018.25] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2018] [Revised: 04/02/2018] [Accepted: 04/03/2018] [Indexed: 01/01/2023]
Abstract
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Introduction: Breast cancer, as one of the major causes of cancer death among women, is the central focus of this study. The recent advances in the development and application of computational tools and bioinformatics in the field of immunotherapy of malignancies such as breast cancer have emerged the new dominion of immunoinformatics, and therefore, next generation of immunomedicines .
Methods: Having reviewed the most recent works on the applications of computational tools, we provide comprehensive insights into the breast cancer incidence and its leading causes as well as immunotherapy approaches and the future trends. Furthermore, we discuss the impacts of bioinformatics on different stages of vaccine design for the breast cancer, which can be used to produce much more efficient vaccines through a rationalized time- and cost-effective in silico approaches prior to conducting costly experiments.
Results: The tools can be significantly used for designing the immune system-modulating drugs and vaccines based on in silico approaches prior to in vitro and in vivo experimental evaluations. Application of immunoinformatics in the cancer immunotherapy has shown its success in the pre-clinical models. This success returns back to the impacts of several powerful computational approaches developed during the last decade.
Conclusion: Despite the invention of a number of vaccines for the cancer immunotherapy, more computational and clinical trials are required to design much more efficient vaccines against various malignancies, including breast cancer.
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Morshedian A, Razmara J, Lotfi S. A novel approach for protein structure prediction based on an estimation of distribution algorithm. Soft comput 2018. [DOI: 10.1007/s00500-018-3130-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
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Sadat Mohajer F, Parvizpour S, Razmara J, Shahir Shamsir M. The two mutations of actin-myosin interface and their effect on the dynamics, structures, and functions of skeletal muscle actin. J Biomol Struct Dyn 2018; 37:372-382. [PMID: 29338614 DOI: 10.1080/07391102.2018.1427630] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Congenital myopathy is a broad category of muscular diseases with symptoms appearing at the time of birth. One type of congenital myopathy is Congenital Fiber Type Disproportion (CFTD), a severely debilitating disease. The G48D and G48C mutations in the D-loop and the actin-myosin interface are the two causes of CFTD. These mutations have been shown to significantly affect the structure and function of muscle fibers. To the author's knowledge, the effects of these mutations have not yet been studied. In this work, the power stroke structure of the head domain of myosin and the wild and mutated types of actin were modeled. Then, a MD simulation was run for the modeled structures to study the effects of these mutations on the structure, function, and molecular dynamics of actin. The wild and mutated actins docked with myosin showed differences in hydrogen bonding patterns, free binding energies, and hydrogen bond occupation frequencies. The G48D and G48C mutations significantly impacted the conformation of D-loops because of their larger size compared to Glycine and their ability to interfere with the polarity or hydrophobicity of this neutralized and hydrophobic loop. Therefore, the mutated loops were unable to fit properly into the hydrophobic groove of the adjacent G-actin. The abnormal structure of D-loops seems to result in the abnormal assembly of F-actins, giving rise to the symptoms of CFTD. It was also noted that G48C and G48D did not form hydrogen bonds with myosin in the residue 48 location. Nevertheless, in this case, muscles are unable to contract properly due to muscle atrophy.
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Razmara J, Zaboli MH, Hassankhani H. Elderly fall risk prediction based on a physiological profile approach using artificial neural networks. Health Informatics J 2016; 24:410-418. [PMID: 28050920 DOI: 10.1177/1460458216677841] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Falls play a critical role in older people's life as it is an important source of morbidity and mortality in elders. In this article, elders fall risk is predicted based on a physiological profile approach using a multilayer neural network with back-propagation learning algorithm. The personal physiological profile of 200 elders was collected through a questionnaire and used as the experimental data for learning and testing the neural network. The profile contains a series of simple factors putting elders at risk for falls such as vision abilities, muscle forces, and some other daily activities and grouped into two sets: psychological factors and public factors. The experimental data were investigated to select factors with high impact using principal component analysis. The experimental results show an accuracy of ≈90 percent and ≈87.5 percent for fall prediction among the psychological and public factors, respectively. Furthermore, combining these two datasets yield an accuracy of ≈91 percent that is better than the accuracy of single datasets. The proposed method suggests a set of valid and reliable measurements that can be employed in a range of health care systems and physical therapy to distinguish people who are at risk for falls.
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Parvizpour S, Razmara J, Shamsir MS, Illias RM, Abdul Murad AM. The role of alternative salt bridges in cold adaptation of a novel psychrophilic laminarinase. J Biomol Struct Dyn 2016; 35:1685-1692. [PMID: 27206405 DOI: 10.1080/07391102.2016.1191043] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
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Mohajer FS, Parvizpour S, Razmara J, Khoshkhooy Yazdi M, Shamsir MS. Structural, functional and molecular dynamics analysis of the native and mutated actin to study its effect on congenital myopathy. J Biomol Struct Dyn 2016; 35:1608-1614. [PMID: 27448459 DOI: 10.1080/07391102.2016.1190299] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
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Razmara J, Deris SB, Parvizpour S. A context evaluation approach for structural comparison of proteins using cross entropy over n-gram modelling. Comput Biol Med 2013; 43:1614-21. [DOI: 10.1016/j.compbiomed.2013.07.022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2012] [Revised: 07/16/2013] [Accepted: 07/18/2013] [Indexed: 11/25/2022]
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Razmara J, Deris SB, Illias RBM, Parvizpour S. Artificial signal peptide prediction by a hidden markov model to improve protein secretion via Lactococcus lactis bacteria. Bioinformation 2013; 9:345-8. [PMID: 23750078 PMCID: PMC3669786 DOI: 10.6026/97320630009345] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2013] [Accepted: 04/05/2013] [Indexed: 11/23/2022] Open
Abstract
A hidden Markov model (HMM) has been utilized to predict and generate artificial secretory signal peptide sequences. The strength of signal peptides of proteins from different subcellular locations via Lactococcus lactis bacteria correlated with their HMM bit scores in the model. The results show that the HMM bit score +12 are determined as the threshold for discriminating secreteory signal sequences from the others. The model is used to generate artificial signal peptides with different bit scores for secretory proteins. The signal peptide with the maximum bit score strongly directs proteins secretion.
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Razmara J, Deris S, Parvizpour S. TS-AMIR: a topology string alignment method for intensive rapid protein structure comparison. Algorithms Mol Biol 2012; 7:4. [PMID: 22336468 PMCID: PMC3298807 DOI: 10.1186/1748-7188-7-4] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2011] [Accepted: 02/15/2012] [Indexed: 02/02/2023] Open
Abstract
Background In structural biology, similarity analysis of protein structure is a crucial step in studying the relationship between proteins. Despite the considerable number of techniques that have been explored within the past two decades, the development of new alternative methods is still an active research area due to the need for high performance tools. Results In this paper, we present TS-AMIR, a Topology String Alignment Method for Intensive Rapid comparison of protein structures. The proposed method works in two stages: In the first stage, the method generates a topology string based on the geometric details of secondary structure elements, and then, utilizes an n-gram modelling technique over entropy concept to capture similarities in these strings. This initial correspondence map between secondary structure elements is submitted to the second stage in order to obtain the alignment at the residue level. Applying the Kabsch method, a heuristic step-by-step algorithm is adopted in the second stage to align the residues, resulting in an optimal rotation matrix and minimized RMSD. The performance of the method was assessed in different information retrieval tests and the results were compared with those of CE and TM-align, representing two geometrical tools, and YAKUSA, 3D-BLAST and SARST as three representatives of linear encoding schemes. It is shown that the method obtains a high running speed similar to that of the linear encoding schemes. In addition, the method runs about 800 and 7200 times faster than TM-align and CE respectively, while maintaining a competitive accuracy with TM-align and CE. Conclusions The experimental results demonstrate that linear encoding techniques are capable of reaching the same high degree of accuracy as that achieved by geometrical methods, while generally running hundreds of times faster than conventional programs.
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Razmara J, Deris S, Parvizpour S. A rapid protein structure alignment algorithm based on a text modeling technique. Bioinformation 2011; 6:344-7. [PMID: 21814392 PMCID: PMC3143397 DOI: 10.6026/97320630006344] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2011] [Accepted: 05/09/2011] [Indexed: 11/23/2022] Open
Abstract
Structural alignment of proteins is widely used in various fields of structural biology. In order to further improve the quality of alignment, we describe an algorithm for structural alignment based on text modelling techniques. The technique firstly superimposes secondary structure elements of two proteins and then, models the 3D-structure of the protein in a sequence of alphabets. These sequences are utilized by a step-by-step sequence alignment procedure to align two protein structures. A benchmark test was organized on a set of 200 non-homologous proteins to evaluate the program and compare it to state of the art programs, e.g. CE, SAL, TM-align and 3D-BLAST. On average, the results of all-against-all structure comparison by the program have a competitive accuracy with CE and TM-align where the algorithm has a high running speed like 3D-BLAST.
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Hauser H, Roob JM, El Shabrawy A, Hohl MA, Razmara J, Holzer H, Mischinger HJ. Continuous Ambulatory Peritoneal Dialysis – Surgical Technique, Early and Late Complications. Eur Surg 2003. [DOI: 10.1007/s10353-003-0035-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
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Hauser H, Mischinger HJ, Beham A, Berger A, Cerwenka H, Razmara J, Fruhwirth H, Werkgartner G. Cystic retroperitoneal lymphangiomas in adults. EUROPEAN JOURNAL OF SURGICAL ONCOLOGY 1997; 23:322-6. [PMID: 9315061 DOI: 10.1016/s0748-7983(97)90777-0] [Citation(s) in RCA: 43] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
Lymphangioma (LA) is a rare benign tumour of the lymphatic tissue, most common in the neck and head, and clinically manifests itself mostly in childhood. Within this group, intra-abdominal and retroperitonal LA are the rarest tumours, especially when occurring in adults. We report four LAs localized in the retroperitoneum of patients aged between 28 and 72 years. One of these tumours infiltrated the transverse mesocolon and greater omentum, others were situated in the left retroperitoneum and retroperitoneally at the duodeno-jejunal flexure, and in the retrosplenal and retropancreatic area. Diagnosis was made by light microscopy supported by immunohistochemistry. In three cases the tumour could be removed by radical surgery and none of these patients had a recurrence (median follow-up time: 4 years). The tumour could not be removed completely from one patient with pre-operative chylascos. Six months after diagnosis of LA this patient died of cardiopulmonary failure due to progressive tumour chylascos. Isolation and ligation of the cystic LA's peduncle as well as ligation of lymph channels can prevent recurrences and chylascos.
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