Publications by authors named "Osman Uğur Sezerman"

36 Publications

Identifying and elucidating the roles of Y198N and Y204F mutations in the PAH enzyme through molecular dynamic simulations.

J Biomol Struct Dyn 2021 May 10:1-12. Epub 2021 May 10.

Faculty of Arts and Sciences, Department of Molecular Biology and Genetics, Bogazici University, Istanbul, Turkey.

Phenylketonuria is an autosomal recessive disorder caused by mutations in the phenylalanine hydroxylase gene. In phenylketonuria causes various symptoms including severe mental retardation. PAH gene of a classical Phenylketonuria patient was sequenced, and two novel heterozygous mutations, p.Y198N and p.Y204F, were found. This study aimed to reveal the impacts of these variants on the structural stability of the PAH enzyme. analyses using prediction tools and molecular dynamics simulations were performed. Mutations were introduced to the wild type catalytic monomer and full length tetramer crystal structures. Variant pathogenicity analyses predicted p.Y198N to be damaging, and p.Y204F to be benign by some prediction tools and damaging by others. Simulations suggested p.Y198N mutation cause significant fluctuations in the spatial organization of two catalytic residues in the temperature accelerated MD simulations with the monomer and increased root-mean-square deviations in the tetramer structure. p.Y204F causes noticeable changes in the spatial positioning of T278 suggesting a possible segregation from the catalytic site in temperature accelerated MD simulations with the monomer. This mutation also leads to increased root-mean-square fluctuations in the regulatory domain which may lead to conformational change resulting in inhibition of dimerization and enzyme activation. Our study reports two novel mutations in the PAH gene and gives insight to their effects on the PAH activity. MD simulations did not yield conclusive results that explains the phenotype but gave plausible insight to possible effects which should be investigated further with and studies to assess the roles of these mutations in etiology of PKU. Communicated by Ramaswamy H. Sarma.
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http://dx.doi.org/10.1080/07391102.2021.1921619DOI Listing
May 2021

CogNet: classification of gene expression data based on ranked active-subnetwork-oriented KEGG pathway enrichment analysis.

PeerJ Comput Sci 2021 22;7:e336. Epub 2021 Feb 22.

Department of Biostatistics and Medical Informatics, School of Medicine, Acibadem Mehmet Ali Aydinlar University, Istanbul, Turkey.

Most of the traditional gene selection approaches are borrowed from other fields such as statistics and computer science, However, they do not prioritize biologically relevant genes since the ultimate goal is to determine features that optimize model performance metrics not to build a biologically meaningful model. Therefore, there is an imminent need for new computational tools that integrate the biological knowledge about the data in the process of gene selection and machine learning. Integrative gene selection enables incorporation of biological domain knowledge from external biological resources. In this study, we propose a new computational approach named CogNet that is an integrative gene selection tool that exploits biological knowledge for grouping the genes for the computational modeling tasks of ranking and classification. In CogNet, the pathfindR serves as the biological grouping tool to allow the main algorithm to rank active-subnetwork-oriented KEGG pathway enrichment analysis results to build a biologically relevant model. CogNet provides a list of significant KEGG pathways that can classify the data with a very high accuracy. The list also provides the genes belonging to these pathways that are differentially expressed that are used as features in the classification problem. The list facilitates deep analysis and better interpretability of the role of KEGG pathways in classification of the data thus better establishing the biological relevance of these differentially expressed genes. Even though the main aim of our study is not to improve the accuracy of any existing tool, the performance of the CogNet outperforms a similar approach called maTE while obtaining similar performance compared to other similar tools including SVM-RCE. CogNet was tested on 13 gene expression datasets concerning a variety of diseases.
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http://dx.doi.org/10.7717/peerj-cs.336DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7959595PMC
February 2021

A recursive molecular docking coupled with energy-based pose-rescoring and MD simulations to identify sGC βH-NOX allosteric modulators for cardiovascular dysfunctions.

J Biomol Struct Dyn 2021 Feb 1:1-23. Epub 2021 Feb 1.

Department of Biostatistics and Medical Informatics, Acibadem M. A. A. University, Istanbul, Turkey.

Modulating the activity of human soluble guanylate cyclase (sGC) through allosteric regulation of the βH-NOX domain has been considered as an immediate treatment for cardiovascular disorder (CVDs). Currently available βH-NOX domain-specific agonists including cinaciguat are unable to deal with the conundrum raised due to oxidative stress in the case of CVDs and their associated comorbidities. Therefore, the idea of investigating novel compounds for allosteric regulation of sGC activation has been rekindled to circumvent CVDs. Current study aims to identify novel βH-NOX domain-specific compounds that can selectively turn on sGC functions by modulating the conformational dynamics of the target protein. Through a comprehensive computational drug-discovery approach, we first executed a target-based performance assessment of multiple docking (PLANTS, QVina, LeDock, Vinardo, Smina) scoring functions based on multiple performance metrices. QVina showed the highest capability of selecting true-positive ligands over false positives thus, used to screen 4.8 million ZINC15 compounds against βH-NOX domain. The docked ligands were further probed in terms of contact footprint and pose reassessment through clustering analysis and PLANTS docking, respectively. Subsequently, energy-based AMBER rescoring of top 100 low-energy complexes, per-residue energy decomposition analysis, and ADME-Tox analysis yielded the top three compounds i.e. ZINC000098973660, ZINC001354120371, and ZINC000096022607. The impact of three selected ligands on the internal structural dynamics of the βH-NOX domain was also investigated through molecular dynamics simulations. The study revealed potential electrostatic interactions for better conformational dialogue between βH-NOX domain and allosteric ligands that are critical for the activation of sGC as compared to the reference compound.
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http://dx.doi.org/10.1080/07391102.2021.1877818DOI Listing
February 2021

Intraoperative Neuromonitoring of Blink Reflex During Posterior Fossa Surgeries and its Correlation With Clinical Outcome.

J Clin Neurophysiol 2020 Sep 28. Epub 2020 Sep 28.

Department of Biostatistics and Bioinformatics, Life Science Institute, Acibadem Mehmet Ali Aydinlar University, Istanbul, Turkey.

Purpose: Blink reflex (BR) under general anesthesia as an intraoperative neuromonitoring method was used to monitor facial nerves in few studies. This study aimed to test the utility of intraoperative BR during cerebellopontine angle and skull base surgeries, assess its prognostic value for facial nerve functions, and compare it with facial corticobulbar motor evoked potentials (CoMEPs).

Methods: Blink reflex and facial CoMEPs were recorded from 40 patients undergoing skull base surgeries. Subdermal needles were placed in the supraorbital notch for stimulation and in the orbicularis oculi muscle for recording the BR. A double train of 20 to 40 V intensity with an intertrain interval of 40 to 60 milliseconds, an interstimulus interval of 2.5 milliseconds, and a stimulus duration of 0.5 milliseconds were applied. Facial nerve functions were assessed with the House-Brackmann grading system in the postoperative day 1 and third-month period and correlated with intraoperative BR and CoMEPs measurements.

Results: Of 40 patients, BR was recordable on the affected side in 32 (80%) and contralateral side in 35 (87.5%) patients. According to our statistical results, BR had a slightly better sensitivity than facial CoMEPs in predicting impairment of facial nerve functions for both postoperative and third-month time points. Blink reflex showed better accuracy for predicting postoperative nerve functions, whereas CoMEPs correlated better in predicting third-month outcome.

Conclusions: We suggest that BR is a valuable intraoperative neuromonitoring method that can be used in addition to facial CoMEPs during skull base surgeries to assess real-time facial nerve integrity and predict prognosis.
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http://dx.doi.org/10.1097/WNP.0000000000000777DOI Listing
September 2020

SARS-CoV-2 isolation and propagation from Turkish COVID-19 patients.

Turk J Biol 2020 21;44(3):192-202. Epub 2020 Jun 21.

Acıbadem Labcell Cellular Therapy Laboratory, İstanbul Turkey.

The novel coronavirus pneumonia, which was named later as coronavirus disease 2019 (COVID-19), is caused by the severe acute respiratory syndrome coronavirus 2, namely SARS-CoV-2. It is a positive-strand RNA virus that is the seventh coronavirus known to infect humans. The COVID-19 outbreak presents enormous challenges for global health behind the pandemic outbreak. The first diagnosed patient in Turkey has been reported by the Republic of Turkey Ministry of Health on March 11, 2020. In May, over 150,000 cases in Turkey, and 5.5 million cases around the world have been declared. Due to the urgent need for a vaccine and antiviral drug, isolation of the virus is crucial. Here, we report 1 of the first isolation and characterization studies of SARS-CoV-2 from nasopharyngeal and oropharyngeal specimens of diagnosed patients in Turkey. This study provides an isolation and replication methodology,and cell culture tropism of the virus that will be available to the research communities.
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http://dx.doi.org/10.3906/biy-2004-113DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7314506PMC
June 2020

Probing the Structural Dynamics of the Catalytic Domain of Human Soluble Guanylate Cyclase.

Sci Rep 2020 06 11;10(1):9488. Epub 2020 Jun 11.

Department of Biology, University of Crete, 70013, Heraklion, Greece.

In the nitric oxide (NO) signaling pathway, human soluble guanylate cyclase (hsGC) synthesizes cyclic guanosine monophosphate (cGMP); responsible for the regulation of cGMP-specific protein kinases (PKGs) and phosphodiesterases (PDEs). The crystal structure of the inactive hsGC cyclase dimer is known, but there is still a lack of information regarding the substrate-specific internal motions that are essential for the catalytic mechanism of the hsGC. In the current study, the hsGC cyclase heterodimer complexed with guanosine triphosphate (GTP) and cGMP was subjected to molecular dynamics simulations, to investigate the conformational dynamics that have functional implications on the catalytic activity of hsGC. Results revealed that in the GTP-bound complex of the hsGC heterodimer, helix 1 of subunit α (α:h1) moves slightly inwards and comes close to helix 4 of subunit β (β:h4). This conformational change brings loop 2 of subunit β (β:L2) closer to helix 2 of subunit α (α:h2). Likewise, loop 2 of subunit α (α:L2) comes closer to helix 2 of subunit β (β:h2). These structural events stabilize and lock GTP within the closed pocket for cyclization. In the cGMP-bound complex, α:L2 detaches from β:h2 and establishes interactions with β:L2, which results in the loss of global structure compactness. Furthermore, with the release of pyrophosphate, the interaction between α:h1 and β:L2 weakens, abolishing the tight packing of the binding pocket. This study discusses the conformational changes induced by the binding of GTP and cGMP to the hsGC catalytic domain, valuable in designing new therapeutic strategies for the treatment of cardiovascular diseases.
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http://dx.doi.org/10.1038/s41598-020-66310-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7289801PMC
June 2020

High-throughput profiling reveals perturbation of endoplasmic reticulum stress-related genes in atherosclerosis induced by high-cholesterol diet and the protective role of vitamin E.

Biofactors 2020 Jul 8;46(4):653-664. Epub 2020 May 8.

Department of Biochemistry, Faculty of Medicine, Marmara University, Istanbul, Turkey.

Formation of atherosclerotic plaques, called atherogenesis, is a complex process affected by genetic and environmental factors. It was proposed that endoplasmic reticulum (ER) stress is an important factor in the pathogenesis of atherosclerosis and that vitamin E affects atherosclerotic plaque formation via its antioxidant properties. Here, we investigated ER stress-related molecular mechanisms in high-cholesterol diet (HCD, 2%)-induced atherosclerosis model and the role of vitamin E supplementation in it, beyond its antioxidant properties. The consequences of HCD and vitamin E supplementation were examined by determining protein levels of ER stress markers in aortic tissues. As vitamin E supplementation acts on several unfolded protein response (UPR) factors, it decreased ER stress induced by HCD. To elucidate the associated pathways, gene expression profiling was performed, revealing differentially expressed genes enriched in ER stress-related pathways such as the proteasome and the apoptosis pathways. We further assessed the proteasomal activity impaired by HCD in the aorta and showed that vitamin E reversed it to that of control animals. Overall, the study characterized the effects of HCD and vitamin E on ER stress-related gene expression, revealing the role of proteolytic systems during atherogenesis.
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http://dx.doi.org/10.1002/biof.1635DOI Listing
July 2020

Understanding thermal and organic solvent stability of thermoalkalophilic lipases: insights from computational predictions and experiments.

J Mol Model 2020 May 8;26(6):122. Epub 2020 May 8.

Department of Biostatistics and Medical Informatics, School of Medicine, Acibadem Mehmet Ali Aydınlar University, Atasehir, Istanbul, Turkey.

Bacillus thermocatenulatus lipase (BTL2), a member of the isolated lipase family known as thermoalkalophilic lipases, carries potential for industrial applications owing to its ability to catalyze versatile reactions under extreme conditions. This study investigates the molecular effects of distinct solvents on the stability of BTL2 at different temperatures, aiming to contribute to lipase use in industrial applications. Initially, molecular dynamic (MD) simulations were carried out to address for the molecular impacts of distinct solvents on the structural stability of BTL2 at different temperatures. Two lipase conformations representing the active and inactive forms were simulated in 5 solvents including water, ethanol, methanol, cyclohexane, and toluene. Low temperature simulations showed that polar solvents led to enhanced lid fluctuations compared with non-polar solvents reflecting a more dynamic equilibrium between active and inactive lipase conformations in polar solvents including water, while the overall structure of the lipase in both forms became more rigid in non-polar solvents than they were in polar solvent. Notably, the native lipase fold was maintained in non-polar solvents even at high temperatures, indicating an enhancement of lipase's thermostability in non-polar organic solvents. Next, we conducted experiments for which BTL2 was expressed in a heterologous host and purified to homogeneity, and its thermostability in different solvents was assessed. Parallel to the computational findings, experimental results suggested that non-polar organic solvents contributed to BTL2's thermostability at concentrations as high as 70% (v/v). Altogether, this study provides beneficial insights to the lipase use under extreme conditions. Graphical Abstract.
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http://dx.doi.org/10.1007/s00894-020-04396-3DOI Listing
May 2020

A comprehensive study on identifying the structural and functional SNPs of human neuronal membrane glycoprotein M6A (GPM6A).

J Biomol Struct Dyn 2021 May 20;39(8):2693-2701. Epub 2020 Apr 20.

Department of Biostatistics and Medical Informatics, Acibadem University, Istanbul, Turkey.

Glycoprotein M6A, a stress related gene, plays an important role in synapse and filopodia formation. Filopodia formation is vital for development, immunity, angiogenesis, wound healing and metastasis. In this study, structural and functional analysis of high-risk SNPs associated with Glycoprotein M6-A were evaluated using six different bioinformatics tools. Results classified T210I, T134I, Y153H, I215T, F156L, T160I, I226T, R247W, R178C, W159R, N157S and P151L as deleterious mutants that are crucial for the structure and function of the protein causing malfunction of M6-a and ultimately leads to disease development. The three-dimensional structure of wild-type M6-a and mutant M6-a were also predicted. Furthermore, the effects of high risk substitutions were also analyzed with interaction with valproic acid. Based on structural models obtained, the binding pocket of ligand bound glycoprotein M6-A structure showed few core interacting residues which are different in the mutant models. Among all substitutions, F156L showed complete loss of binding pocket when interacting with valproic acid as compared to the wild type model. Up to the best of our knowledge this is the first comprehensive study where GPM6A mutations were analyzed. The mechanism of action of GPM6A is still not fully defined which limits the understanding of functional details encoding M6-A. Our results may help enlighten some molecular aspects underlying glycoprotein M6-A. Communicated by Ramaswamy H. Sarma.
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http://dx.doi.org/10.1080/07391102.2020.1751712DOI Listing
May 2021

Adaptive phenotypic modulations lead to therapy resistance in chronic myeloid leukemia cells.

PLoS One 2020 27;15(2):e0229104. Epub 2020 Feb 27.

Department of Medical Biology, Faculty of Medicine, Dokuz Eylul University, Izmir, Turkey.

Tyrosine kinase inhibitor (TKI) resistance is a major problem in chronic myeloid leukemia (CML). We generated a TKI-resistant K562 sub-population, K562-IR, under selective imatinib-mesylate pressure. K562-IR cells are CD34-/CD38-, BCR-Abl-independent, proliferate slowly, highly adherent and form intact tumor spheroids. Loss of CD45 and other hematopoietic markers reveal these cells have diverged from their hematopoietic origin. CD34 negativity, high expression of E-cadherin and CD44; decreased levels of CD45 and β-catenin do not fully confer with the leukemic stem cell (LSC) phenotype. Expression analyses reveal that K562-IR cells differentially express tissue/organ development and differentiation genes. Our data suggest that the observed phenotypic shift is an adaptive process rendering cells under TKI stress to become oncogene independent. Cells develop transcriptional instability in search for a gene expression framework suitable for new environmental stresses, resulting in an adaptive phenotypic shift in which some cells partially display LSC-like properties. With leukemic/cancer stem cell targeted therapies underway, the difference between treating an entity and a spectrum of dynamic cellular states will have conclusive effects on the outcome.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0229104PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7046262PMC
May 2020

pathfindR: An R Package for Comprehensive Identification of Enriched Pathways in Omics Data Through Active Subnetworks.

Front Genet 2019 25;10:858. Epub 2019 Sep 25.

Department of Biostatistics and Medical Informatics, School of Medicine, Acibadem Mehmet Ali Aydinlar University, Istanbul, Turkey.

Pathway analysis is often the first choice for studying the mechanisms underlying a phenotype. However, conventional methods for pathway analysis do not take into account complex protein-protein interaction information, resulting in incomplete conclusions. Previously, numerous approaches that utilize protein-protein interaction information to enhance pathway analysis yielded superior results compared to conventional methods. Hereby, we present pathfindR, another approach exploiting protein-protein interaction information and the first R package for active-subnetwork-oriented pathway enrichment analyses for class comparison omics experiments. Using the list of genes obtained from an omics experiment comparing two groups of samples, pathfindR identifies active subnetworks in a protein-protein interaction network. It then performs pathway enrichment analyses on these identified subnetworks. To further reduce the complexity, it provides functionality for clustering the resulting pathways. Moreover, through a scoring function, the overall activity of each pathway in each sample can be estimated. We illustrate the capabilities of our pathway analysis method on three gene expression datasets and compare our results with those obtained from three popular pathway analysis tools. The results demonstrate that literature-supported disease-related pathways ranked higher in our approach compared to the others. Moreover, pathfindR identified additional pathways relevant to the conditions that were not identified by other tools, including pathways named after the conditions.
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http://dx.doi.org/10.3389/fgene.2019.00858DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6773876PMC
September 2019

Identification of epilepsy related pathways using genome-wide DNA methylation measures: A trio-based approach.

PLoS One 2019 8;14(2):e0211917. Epub 2019 Feb 8.

Aziz Sancar Institute of Experimental Medicine, Department of Genetics, Istanbul University, Istanbul, Turkey.

Genetic generalized epilepsies (GGE) are genetically determined, as their name implies and they are clinically characterized by generalized seizures involving both sides of the brain in the absence of detectable brain lesions or other known causes. GGEs are yet complex and are influenced by many different genetic and environmental factors. Methylation specific epigenetic marks are one of the players of the complex epileptogenesis scenario leading to GGE. In this study, we have set out to perform genome-wide methylation profiling to analyze GGE trios each consisting of an affected parent-offspring couple along with an unaffected parent. We have developed a novel scoring scheme within trios to categorize each locus analyzed as hypo or hypermethylated. This stringent approach classified differentially methylated genes in each trio and helped us to produce trio specific and pooled gene lists with inherited and aberrant methylation levels. In order to analyze the methylation differences from a boarder perspective, we performed enrichment analysis with these lists using the PANOGA software. This collective effort has led us to detect pathways associated with the GGE phenotype, including the neurotrophin signaling pathway. We have demonstrated a trio based approach to genome-wide DNA methylation analysis that identified individual and possibly minor changes in methylation marks that could be involved in epileptogenesis leading to GGE.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0211917PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6368378PMC
November 2019

Comparison of Dendritic Cell Activation by Virus-Based Vaccine Delivery Vectors Emphasizes the Transcriptional Downregulation of the Oxidative Phosphorylation Pathway.

Hum Gene Ther 2019 04 25;30(4):429-445. Epub 2019 Jan 25.

1 Molecular Virology Laboratory, Hellenic Pasteur Institute, Athens, Greece.

Antigen delivery platforms based on engineered viruses or virus-like particles are currently developed as vaccines against infectious diseases. As the interaction of vaccines with dendritic cells (DCs) shapes the immunological response, we compared the interaction of a range of virus-based vectors and virus-like particles with DCs in a murine model of systemic administration and transcriptome analyses of splenic DCs. The transcriptome profiles of DCs separated the vaccine vectors into two distinct groups characterized by high- and low-magnitude differential gene expression, which strongly correlated with (1) the surface expression of costimulatory molecules CD40, CD83, and CD86 on DCs, and (2) antigen-specific T-cell responses. Pathway analysis using PANOGA (Pathway and Network-Oriented GWAS Analysis) revealed that the JAK/STAT pathway was significantly activated by both groups of vaccines. In contrast, the oxidative phosphorylation pathway was significantly downregulated only by the high-magnitude DC-stimulating vectors. A gene signature including exclusively chemokine-, cytokine-, and receptor-related genes revealed a vector-specific pattern. Overall, this in vivo DC stimulation model demonstrated a strong relationship between the levels of induced DC maturation and the intensity of T-cell-specific immune responses with a distinct cytokine/chemokine profile, metabolic shifting, and cell surface expression of maturation markers. It could represent an important tool for vaccine design.
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http://dx.doi.org/10.1089/hum.2018.161DOI Listing
April 2019

Computational drug repurposing to predict approved and novel drug-disease associations.

J Mol Graph Model 2018 10 14;85:91-96. Epub 2018 Aug 14.

Acibadem University, Istanbul, Turkey. Electronic address:

The Drug often binds to more than one targets defined as polypharmacology, one application of which is drug repurposing also referred as drug repositioning or therapeutic switching. The traditional drug discovery and development is a high-priced and tedious process, thus making drug repurposing a popular alternate strategy. We proposed an integrative method based on similarity scheme that predicts approved and novel Drug targets with new disease associations. We combined PPI, biological pathways, binding site structural similarities and disease-disease similarity measures. The results showed 94% Accuracy with 0.93 Recall and 0.94 Precision measure in predicting the approved and novel targets surpassing the existing methods. All these parameters help in elucidating the unknown associations between drug and diseases for finding the new uses for old drugs.
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http://dx.doi.org/10.1016/j.jmgm.2018.08.005DOI Listing
October 2018

Investigating the structural properties of the active conformation BTL2 of a lipase from Geobacillus thermocatenulatus in toluene using molecular dynamic simulations and engineering BTL2 via in-silico mutation.

J Mol Model 2018 Aug 10;24(9):229. Epub 2018 Aug 10.

Department of Biostatistics and Medical Informatics, School of Medicine, Acibadem Mehmet Ali Aydınlar University, Atasehir, Istanbul, Turkey.

The discovery or development of thermoalkalophilic lipases that show high levels of catalytic activity in organic solvents would have important industrial ramifications. However, this goal is yet to be achieved because organic solvents induce structural changes in lipases that suppress their catalytic abilities. A deep understanding of these structural changes to lipases in the presence of organic solvents is required before strategies can be devised to stop them from occurring. In this work, we investigated the effects of an organic reaction medium, toluene, on the structure of the Bacillus thermocatenulatus lipase BTL2 using MD simulation. The main aims were to identify the regions of the protein that are particularly sensitive to the presence of an organic solvent, and how the presence of a hydrophobic medium affects the overall stability of the enzyme. Upon analyzing how the behavior of the enzyme differed in aqueous and hydrophobic media, it was found that many significant zones of the protein suffer in the presence of an organic solvent, which increases the rigidity of the system. This was readily apparent when we investigated important noncovalent interactions (salt bridges) and probed how distances between the atoms of the catalytic triad Ser114, Asp318, and His359 change in the presence of toluene. Moreover, the high tendency for the system to destabilize in toluene was explained by the results of FoldX calculations. Calculations showed that the addition of a small amount of water to the hydrophobic reaction environment should restore the required flexibility of BTL2. The insights gained from the analysis of our simulations allowed us to propose a modification of BTL2, the G116P mutation, that should result in the structural behavior of BTL2 in organic solvent being closer to that of BTL2 in water.
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http://dx.doi.org/10.1007/s00894-018-3753-1DOI Listing
August 2018

Thermostability of the PYL-PP2C Heterodimer Is Dependent on Magnesium: In Silico Insights into the Link between Heat Stress Response and Magnesium Deficiency in Plants.

J Chem Inf Model 2018 03 21;58(3):661-672. Epub 2018 Feb 21.

Department of Biostatistics and Medical Informatics, School of Medicine , Acibadem Mehmet Ali Aydinlar University , Atasehir , 34752 , Istanbul Turkey.

Magnesium deficiency increases the susceptibility of plants toward heat stress. The correlation between magnesium levels and stress response has been studied at the physiological level; albeit, the molecular explanation to this relationship remains elusive. Among diverse pathways implicated in the heat stress, the abscisic acid (ABA) signal modulates the heat stress response by magnesium dependent phosphatases (PP2Cs). Exclusively, sequestration of PP2Cs by ABA receptors (PYLs) in the heterodimer form activates the stress response through ABA responsive transcription factors. In this study, the molecular interplay between magnesium levels and ABA related heat stress response was investigated. Molecular dynamics simulations have been applied to two different PYL-PP2C heterodimer systems representing normal and magnesium deficient conditions. The heterodimer conformation and stability were delineated at high temperatures mimicking heat stress. Results showed that the thermostability of the heat stress response heterodimer was significantly dependent on the magnesium. Furthermore, a conserved aromatic cluster at the dimer interface acted synergistically with the metal to confer thermostability to the heterodimer structure. These structural insights into one of the possible links between magnesium levels and stress highlight the importance of metal micronutrients for tuning the stability of the stress-related proteins and optimizing tolerance.
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http://dx.doi.org/10.1021/acs.jcim.7b00655DOI Listing
March 2018

Enhancing Reuse of Data and Biological Material in Medical Research: From FAIR to FAIR-Health.

Biopreserv Biobank 2018 Apr 23;16(2):97-105. Epub 2018 Jan 23.

1 BBMRI-ERIC , Graz, Austria .

The known challenge of underutilization of data and biological material from biorepositories as potential resources for medical research has been the focus of discussion for over a decade. Recently developed guidelines for improved data availability and reusability-entitled FAIR Principles (Findability, Accessibility, Interoperability, and Reusability)-are likely to address only parts of the problem. In this article, we argue that biological material and data should be viewed as a unified resource. This approach would facilitate access to complete provenance information, which is a prerequisite for reproducibility and meaningful integration of the data. A unified view also allows for optimization of long-term storage strategies, as demonstrated in the case of biobanks. We propose an extension of the FAIR Principles to include the following additional components: (1) quality aspects related to research reproducibility and meaningful reuse of the data, (2) incentives to stimulate effective enrichment of data sets and biological material collections and its reuse on all levels, and (3) privacy-respecting approaches for working with the human material and data. These FAIR-Health principles should then be applied to both the biological material and data. We also propose the development of common guidelines for cloud architectures, due to the unprecedented growth of volume and breadth of medical data generation, as well as the associated need to process the data efficiently.
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http://dx.doi.org/10.1089/bio.2017.0110DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5906729PMC
April 2018

ZK DrugResist 2.0: A TextMiner to extract semantic relations of drug resistance from PubMed.

J Biomed Inform 2017 05 4;69:93-98. Epub 2017 Apr 4.

Department of Biostatistics and Medical Informatics, Acıbadem University, Istanbul, Turkey. Electronic address:

Extracting useful knowledge from an unstructured textual data is a challenging task for biologists, since biomedical literature is growing exponentially on a daily basis. Building an automated method for such tasks is gaining much attention of researchers. ZK DrugResist is an online tool that automatically extracts mutations and expression changes associated with drug resistance from PubMed. In this study we have extended our tool to include semantic relations extracted from biomedical text covering drug resistance and established a server including both of these features. Our system was tested for three relations, Resistance (R), Intermediate (I) and Susceptible (S) by applying hybrid feature set. From the last few decades the focus has changed to hybrid approaches as it provides better results. In our case this approach combines rule-based methods with machine learning techniques. The results showed 97.67% accuracy with 96% precision, recall and F-measure. The results have outperformed the previously existing relation extraction systems thus can facilitate computational analysis of drug resistance against complex diseases and further can be implemented on other areas of biomedicine.
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http://dx.doi.org/10.1016/j.jbi.2017.04.002DOI Listing
May 2017

Computational approaches for design and redesign of metal-binding sites on proteins.

Biosci Rep 2017 04 27;37(2). Epub 2017 Mar 27.

Department of Statistics and Medical Informatics, School of Medicine, Acibadem University, Istanbul, Turkey

Metal ions play pivotal roles in protein structure, function and stability. The functional and structural diversity of proteins in nature expanded with the incorporation of metal ions or clusters in proteins. Approximately one-third of these proteins in the databases contain metal ions. Many biological and chemical processes in nature involve metal ion-binding proteins, aka metalloproteins. Many cellular reactions that underpin life require metalloproteins. Most of the remarkable, complex chemical transformations are catalysed by metalloenzymes. Realization of the importance of metal-binding sites in a variety of cellular events led to the advancement of various computational methods for their prediction and characterization. Furthermore, as structural and functional knowledgebase about metalloproteins is expanding with advances in computational and experimental fields, the focus of the research is now shifting towards design and redesign of metalloproteins to extend nature's own diversity beyond its limits. In this review, we will focus on the computational toolbox for prediction of metal ion-binding sites, metalloprotein design and redesign. We will also give examples of tailor-made artificial metalloproteins designed with the computational toolbox.
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http://dx.doi.org/10.1042/BSR20160179DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5482196PMC
April 2017

Ligand binding pocket of a novel Allatostatin receptor type C of stick insect, Carausius morosus.

Sci Rep 2017 01 24;7:41266. Epub 2017 Jan 24.

Boğaziçi University Department of Molecular Biology and Genetics, Istanbul, 34342, Turkey.

Allatostatins (AST) are neuropeptides with variable function ranging from regulation of developmental processes to the feeding behavior in insects. They exert their effects by binding to cognate GPCRs, called Allatostatin receptors (AlstR), which emerge as promising targets for pesticide design. However, AlstRs are rarely studied. This study is the first reported structural study on AlstR-AST interaction. In this work, the first C type AlstR from the stick insect Carausius morosus (CamAlstR-C) was identified and its interaction with type C AST peptide was shown to be physically consistent with the experimental results. The proposed structure of CamAlstR-C revealed a conserved motif within the third extracellular loop, which, together with the N-terminus is essential for ligand binding. In this work, computational studies were combined with molecular and nano-scale approaches in order to introduce an unknown GPCR-ligand system. Consequently, the data obtained provided a reliable target region for future agonist/inverse agonist studies on AlstRs.
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http://dx.doi.org/10.1038/srep41266DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5259779PMC
January 2017

Prediction of HIV Drug Resistance by Combining Sequence and Structural Properties.

IEEE/ACM Trans Comput Biol Bioinform 2018 May-Jun;15(3):966-973. Epub 2016 Dec 13.

Drug resistance is a major obstacle faced by therapist in treating HIV infected patients. The reason behind these phenomena is either protein mutation or the changes in gene expression level that induces resistance to drug treatments. These mutations affect the drug binding activity, hence resulting in failure of treatment. Therefore, it is necessary to conduct resistance testing in order to carry out HIV effective therapy. This study combines both sequence and structural features for predicting HIV resistance by applying SVM and Random Forests classifiers. The model was tested on the mutants of HIV-1 protease and reverse transcriptase. Taken together the features we have used in our method, total contact energies among multiple mutations have a strong impact in predicting resistance as they are crucial in understanding the interactions of HIV mutants. The combination of sequence-structure features offers high accuracy with support vector machines as compared to Random Forests classifier. Both single and acquisition of multiple mutations are important in predicting HIV resistance to certain drug treatments. We have discovered the practicality of these features; hence, these can be used in the future to predict resistance for other complex diseases.
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http://dx.doi.org/10.1109/TCBB.2016.2638821DOI Listing
May 2019

RACK1 Is an Interaction Partner of ATG5 and a Novel Regulator of Autophagy.

J Biol Chem 2016 08 20;291(32):16753-65. Epub 2016 Jun 20.

From the Molecular Biology, Genetics and Bioengineering Program, Sabanci University, Orhanli-Tuzla, 34956 Istanbul, Turkey,

Autophagy is biological mechanism allowing recycling of long-lived proteins, abnormal protein aggregates, and damaged organelles under cellular stress conditions. Following sequestration in double- or multimembrane autophagic vesicles, the cargo is delivered to lysosomes for degradation. ATG5 is a key component of an E3-like ATG12-ATG5-ATG16 protein complex that catalyzes conjugation of the MAP1LC3 protein to lipids, thus controlling autophagic vesicle formation and expansion. Accumulating data indicate that ATG5 is a convergence point for autophagy regulation. Here, we describe the scaffold protein RACK1 (receptor activated C-kinase 1, GNB2L1) as a novel ATG5 interactor and an autophagy protein. Using several independent techniques, we showed that RACK1 interacted with ATG5. Importantly, classical autophagy inducers (starvation or mammalian target of rapamycin blockage) stimulated RACK1-ATG5 interaction. Knockdown of RACK1 or prevention of its binding to ATG5 using mutagenesis blocked autophagy activation. Therefore, the scaffold protein RACK1 is a new ATG5-interacting protein and an important and novel component of the autophagy pathways.
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http://dx.doi.org/10.1074/jbc.M115.708081DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4974388PMC
August 2016

Design and characterizations of two novel cellulases through single-gene shuffling of Cel12A (EG3) gene from Trichoderma reseei.

Protein Eng Des Sel 2016 06 28;29(6):219-229. Epub 2016 Apr 28.

Department of Biostatistics and Medical Informatics, School of Medicine, Acibadem University, Atasehir, Istanbul, Turkey.

Cellulases have great potential to be widely used for industrial applications. In general, naturally occurring cellulases are not optimized and limited to meet the industrial needs. These limitations lead to demand for novel cellulases with enhanced enzymatic properties. Here, we describe the enzymatic and structural properties of two novel enzymes, EG3_S1 and EG3_S2, obtained through the single-gene shuffling approach of Cel12A(EG3) gene from Trichoderma reseei EG3_S1 and EG3_S2 shuffled enzymes display 59 and 75% identity in protein sequence with respect to native, respectively. Toward 4-MUC, the minimum activity of EG3_S1 was reported as 5.9-fold decrease in native at 35°C, whereas the maximum activity of EG3_S2 was reported as 15.4-fold increase in native activity at 40°C. Also, the diminished enzyme activity of EG3_S1 was reported within range of 0.6- to 0.8-fold of native and within range of 0.5- to 0.7-fold of native toward CMC and Na-CMC, respectively. For EG3_S2 enzyme, the improved enzymatic activities within range of 1.1- to 1.4-fold of native and within range of 1.1- to 1.6-fold of native were reported toward CMC and Na-CMC, respectively. Moreover, we have reported 6.5-fold increase in the kcat/Km ratio of EG3_S2 with respect to native and suggested EG3_S2 enzyme as more efficient catalysis for hydrolysis reactions than its native counterpart.
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http://dx.doi.org/10.1093/protein/gzw011DOI Listing
June 2016

Prediction of neddylation sites from protein sequences and sequence-derived properties.

BMC Bioinformatics 2015 9;16 Suppl 18:S9. Epub 2015 Dec 9.

Background: Neddylation is a reversible post-translational modification that plays a vital role in maintaining cellular machinery. It is shown to affect localization, binding partners and structure of target proteins. Disruption of protein neddylation was observed in various diseases such as Alzheimer's and cancer. Therefore, understanding the neddylation mechanism and determining neddylation targets possibly bears a huge importance in further understanding the cellular processes. This study is the first attempt to predict neddylated sites from protein sequences by using several sequence and sequence-based structural features.

Results: We have developed a neddylation site prediction method using a support vector machine based on various sequence properties, position-specific scoring matrices, and disorder. Using 21 amino acid long lysine-centred windows, our model was able to predict neddylation sites successfully, with an average 5-fold stratified cross validation performance of 0.91, 0.91, 0.75, 0.44, 0.95 for accuracy, specificity, sensitivity, Matthew's correlation coefficient and area under curve, respectively. Independent test set results validated the robustness of reported new method. Additionally, we observed that neddylation sites are commonly flexible and there is a significant positively charged amino acid presence in neddylation sites.

Conclusions: In this study, a neddylation site prediction method was developed for the first time in literature. Common characteristics of neddylation sites and their discriminative properties were explored for further in silico studies on neddylation. Lastly, up-to-date neddylation dataset was provided for researchers working on post-translational modifications in the accompanying supplementary material of this article.
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http://dx.doi.org/10.1186/1471-2105-16-S18-S9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4682398PMC
July 2016

A novel analysis strategy for integrating methylation and expression data reveals core pathways for thyroid cancer aetiology.

BMC Genomics 2015 9;16 Suppl 12:S7. Epub 2015 Dec 9.

Background: Recently, a wide range of diseases have been associated with changes in DNA methylation levels, which play a vital role in gene expression regulation. With ongoing developments in technology, attempts to understand disease mechanism have benefited greatly from epigenetics and transcriptomics studies. In this work, we have used expression and methylation data of thyroid carcinoma as a case study and explored how to optimally incorporate expression and methylation information into the disease study when both data are available. Moreover, we have also investigated whether there are important post-translational modifiers which could drive critical insights on thyroid cancer genetics.

Results: In this study, we have conducted a threshold analysis for varying methylation levels to identify whether setting a methylation level threshold increases the performance of functional enrichment. Moreover, in order to decide on best-performing analysis strategy, we have performed data integration analysis including comparison of 10 different analysis strategies. As a result, combining methylation with expression and using genes with more than 15% methylation change led to optimal detection rate of thyroid-cancer associated pathways in top 20 functional enrichment results. Furthermore, pooling the data from different experiments increased analysis confidence by improving the data range. Consequently, we have identified 207 transcription factors and 245 post-translational modifiers with more than 15% methylation change which may be important in understanding underlying mechanisms of thyroid cancer.

Conclusion: While only expression or only methylation information would not reveal both primary and secondary mechanisms involved in disease state, combining expression and methylation led to a better detection of thyroid cancer-related genes and pathways that are found in the recent literature. Moreover, focusing on genes that have certain level of methylation change improved the functional enrichment results, revealing the core pathways involved in disease development such as; endocytosis, apoptosis, glutamatergic synapse, MAPK, ErbB, TGF-beta and Toll-like receptor pathways. Overall, in addition to novel analysis framework, our study reveals important thyroid-cancer related mechanisms, secondary molecular alterations and contributes to better knowledge of thyroid cancer aetiology.
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http://dx.doi.org/10.1186/1471-2164-16-S12-S7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4682414PMC
October 2016

Probing the roles of two tryptophans surrounding the unique zinc coordination site in lipase family I.5.

Proteins 2016 Jan 9;84(1):129-42. Epub 2015 Dec 9.

Department of Biostatistics and Medical Informatics, School of Medicine, Acibadem University, Atasehir, Istanbul, 34742, Turkey.

A unique zinc domain found in all of the identified members of the lipase family I.5 is surrounded by two conserved tryptophans (W61 and W212). In this study, we investigated the role of these hydrophobic residues in thermostability and thermoactivity of the lipase from Bacillus thermocatenulatus (BTL2) taken as the representative of the family. Circular dichroism spectroscopy revealed that the secondary structure of BTL2 is conserved by the tryptophan mutations (W61A, W212A, and W61A/W212A), and that W61 is located in a more rigid and less solvent exposed region than is W212. Thermal denaturation and optimal activity analyses pointed out that zinc induces thermostability and thermoactivity of BTL2, in which both tryptophans W61 and W212 play contributing roles. Molecular explanations describing the roles of these tryptophans were pursued by X-ray crystallography of the open form of the W61A mutant and molecular dynamics simulations which highlighted a critical function for W212 in zinc binding to the coordination site. This study reflects the potential use of hydrophobic amino acids in vicinity of metal coordination sites in lipase biocatalysts design.
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http://dx.doi.org/10.1002/prot.24961DOI Listing
January 2016

Assessment of global and gene-specific DNA methylation in rat liver and kidney in response to non-genotoxic carcinogen exposure.

Toxicol Appl Pharmacol 2015 Dec 30;289(2):203-12. Epub 2015 Sep 30.

Department of Toxicology, University of Würzburg, Würzburg, Germany.

Altered expression of tumor suppressor genes and oncogenes, which is regulated in part at the level of DNA methylation, is an important event involved in non-genotoxic carcinogenesis. This may serve as a marker for early detection of non-genotoxic carcinogens. Therefore, we evaluated the effects of non-genotoxic hepatocarcinogens, 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), hexachlorobenzene (HCB), methapyrilene (MPY) and male rat kidney carcinogens, d-limonene, p-dichlorobenzene (DCB), chloroform and ochratoxin A (OTA) on global and CpG island promoter methylation in their respective target tissues in rats. No significant dose-related effects on global DNA hypomethylation were observed in tissues of rats compared to vehicle controls using LC-MS/MS in response to short-term non-genotoxic carcinogen exposure. Initial experiments investigating gene-specific methylation using methylation-specific PCR and bisulfite sequencing, revealed partial methylation of p16 in the liver of rats treated with HCB and TCDD. However, no treatment related effects on the methylation status of Cx32, e-cadherin, VHL, c-myc, Igfbp2, and p15 were observed. We therefore applied genome-wide DNA methylation analysis using methylated DNA immunoprecipitation combined with microarrays to identify alterations in gene-specific methylation. Under the conditions of our study, some genes were differentially methylated in response to MPY and TCDD, whereas d-limonene, DCB and chloroform did not induce any methylation changes. 90-day OTA treatment revealed enrichment of several categories of genes important in protein kinase activity and mTOR cell signaling process which are related to OTA nephrocarcinogenicity.
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http://dx.doi.org/10.1016/j.taap.2015.09.023DOI Listing
December 2015

Molecular diversity of LysM carbohydrate-binding motifs in fungi.

Curr Genet 2015 May 15;61(2):103-13. Epub 2015 Jan 15.

Faculty of Natural Sciences and Engineering, Biological Sciences and Bioengineering, Sabanci University, Tuzla, 34956, Istanbul, Turkey.

LysM motifs are carbohydrate-binding modules found in prokaryotes and eukaryotes. They bind to N-acetylglucosamine-containing carbohydrates, such as chitin, chitio-oligosaccharides and peptidoglycan. In this review, we summarize the features of the protein architecture of LysM-containing proteins in fungi and discuss their so far known biochemical properties, transcriptional profiles and biological functions. Further, based on data from evolutionary analyses and consensus pattern profiling of fungal LysM motifs, we show that they can be classified into a fungal-specific group and a fungal/bacterial group. This facilitates the classification and selection of further LysM proteins for detailed analyses and will contribute to widening our understanding of the functional spectrum of this protein family in fungi. Fungal LysM motifs are predominantly found in subgroup C chitinases and in LysM effector proteins, which are secreted proteins with LysM motifs but no catalytic domains. In enzymes, LysM motifs mediate the attachment to insoluble carbon sources. In plants, receptors containing LysM motifs are responsible for the perception of chitin-oligosaccharides and are involved in beneficial symbiotic interactions between plants and bacteria or fungi, as well as plant defence responses. In plant pathogenic fungi, LysM effector proteins have already been shown to have important functions in the dampening of host defence responses as well as protective functions of fungal hyphae against chitinases. However, the large number and diversity of proteins with LysM motifs that are being unravelled in fungal genome sequencing projects suggest that the functional repertoire of LysM effector proteins in fungi is only partially discovered so far.
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http://dx.doi.org/10.1007/s00294-014-0471-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4392113PMC
May 2015

Reply to Stoimenis et al.

Eur J Hum Genet 2015 Oct 14;23(10):1280. Epub 2015 Jan 14.

Department of Biological Sciences and Bioengineering, Faculty of Engineering and Natural Sciences, Sabanci University, Istanbul, Turkey.

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http://dx.doi.org/10.1038/ejhg.2014.288DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4592084PMC
October 2015

Predicting sumoylation sites using support vector machines based on various sequence features, conformational flexibility and disorder.

BMC Genomics 2014 8;15 Suppl 9:S18. Epub 2014 Dec 8.

Background: Sumoylation, which is a reversible and dynamic post-translational modification, is one of the vital processes in a cell. Before a protein matures to perform its function, sumoylation may alter its localization, interactions, and possibly structural conformation. Abberations in protein sumoylation has been linked with a variety of disorders and developmental anomalies. Experimental approaches to identification of sumoylation sites may not be effective due to the dynamic nature of sumoylation, laborsome experiments and their cost. Therefore, computational approaches may guide experimental identification of sumoylation sites and provide insights for further understanding sumoylation mechanism.

Results: In this paper, the effectiveness of using various sequence properties in predicting sumoylation sites was investigated with statistical analyses and machine learning approach employing support vector machines. These sequence properties were derived from windows of size 7 including position-specific amino acid composition, hydrophobicity, estimated sub-window volumes, predicted disorder, and conformational flexibility. 5-fold cross-validation results on experimentally identified sumoylation sites revealed that our method successfully predicts sumoylation sites with a Matthew's correlation coefficient, sensitivity, specificity, and accuracy equal to 0.66, 73%, 98%, and 97%, respectively. Additionally, we have showed that our method compares favorably to the existing prediction methods and basic regular expressions scanner.

Conclusions: By using support vector machines, a new, robust method for sumoylation site prediction was introduced. Besides, the possible effects of predicted conformational flexibility and disorder on sumoylation site recognition were explored computationally for the first time to our knowledge as an additional parameter that could aid in sumoylation site prediction.
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http://dx.doi.org/10.1186/1471-2164-15-S9-S18DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4290605PMC
August 2015