scholarly journals βLact-Pred: A Predictor Developed for Identification of Beta-Lactamases Using Statistical Moments and PseAAC via 5-Step Rule

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Muhammad Adeel Ashraf ◽  
Yaser Daanial Khan ◽  
Bilal Shoaib ◽  
Muhammad Adnan Khan ◽  
Faheem Khan ◽  
...  
Keyword(s):  
Computational Model ◽  
Cross Validation ◽  
Statistical Moments ◽  
Gene Encoding ◽  
Beta Lactamases ◽  
Proposed Model ◽  
The Neural Networks ◽  
Primary Amino ◽  
Tract Infections ◽  
Self Consistency

Beta-lactamase (β-lactamase) produced by different bacteria confers resistance against β-lactam-containing drugs. The gene encoding β-lactamase is plasmid-borne and can easily be transferred from one bacterium to another during conjugation. By such transformations, the recipient also acquires resistance against the drugs of the β-lactam family. β-Lactam antibiotics play a vital significance in clinical treatment of disastrous diseases like soft tissue infections, gonorrhoea, skin infections, urinary tract infections, and bronchitis. Herein, we report a prediction classifier named as βLact-Pred for the identification of β-lactamase proteins. The computational model uses the primary amino acid sequence structure as its input. Various metrics are derived from the primary structure to form a feature vector. Experimentally determined data of positive and negative beta-lactamases are collected and transformed into feature vectors. An operating algorithm based on the artificial neural network is used by integrating the position relative features and sequence statistical moments in PseAAC for training the neural networks. The results for the proposed computational model were validated by employing numerous types of approach, i.e., self-consistency testing, jackknife testing, cross-validation, and independent testing. The overall accuracy of the predictor for self-consistency, jackknife testing, cross-validation, and independent testing presents 99.76%, 96.07%, 94.20%, and 91.65%, respectively, for the proposed model. Stupendous experimental results demonstrated that the proposed predictor “βLact-Pred” has surpassed results from the existing methods.

iTSP-PseAAC: Identify Tumor Suppressor Proteins by Using Fully Connected Neural Network and PseAAC

2021 ◽  
Vol 15 ◽  
Author(s):  
Muhammad Awais ◽  
Waqar Hussain ◽  
Nouman Rasool ◽  
Yaser Daanial Khan
Keyword(s):  
Tumor Suppressor ◽  
Cross Validation ◽  
Control Cell ◽  
Normal Function ◽  
In Vivo Studies ◽  
Tumor Suppressor Proteins ◽  
Proposed Model ◽  
Self Consistency

Background: The uncontrolled growth due to accumulation of genetic and epigenetic changes as a result of loss or reduction in the normal function of Tumor Suppressor Genes (TSGs) and Pro-oncogenes is known as cancer. TSGs control cell division and growth by repairing of DNA mistakes during replication and restrict the unwanted proliferation of a cell or activities, those are the part of tumor production. Objectives: This study aims to propose a novel, accurate, user-friendly model to predict tumor suppressor proteins, which would be freely available to experimental molecular biologists to assist them using in vitro and in vivo studies. Methods: The predictor model has used the input feature vector (IFV) calculated from the physicochemical properties of proteins based on FCNN to compute the accuracy, sensitivity, specificity, and MCC. The proposed model was validated against different exhaustive validation techniques i.e. self-consistency and cross-validation. Results: Using self-consistency, the accuracy is 99%, for cross-validation and independent testing has 99.80% and 100% accuracy respectively. The overall accuracy of the proposed model is 99%, sensitivity value 98% and specificity 99% and F1-score was 0.99. Conclusion: It concludes, the proposed model for prediction of the tumor suppressor proteins can predict the tumor suppressor proteins efficiently, but it still has space for improvements in computational ways as the protein sequences may rapidly increase, day by day.

scholarly journals iSulfoTyr-PseAAC: Identify Tyrosine Sulfation Sites by Incorporating Statistical Moments via Chou’s 5-steps Rule and Pseudo Components

2019 ◽  
Vol 20 (4) ◽  
pp. 306-320 ◽  
Author(s):  
Omar Barukab ◽  
Yaser Daanial Khan ◽  
Sher Afzal Khan ◽  
Kuo-Chen Chou
Keyword(s):  
Amino Acid ◽  
Computational Model ◽  
Amino Acid Sequences ◽  
Site Directed Mutagenesis ◽  
Statistical Moments ◽  
Amino Acid Residues ◽  
Tyrosine Sulfation ◽  
Protein Amino Acid ◽  
Jackknife Test ◽  
Self Consistency

Background: The amino acid residues, in protein, undergo post-translation modification (PTM) during protein synthesis, a process of chemical and physical change in an amino acid that in turn alters behavioral properties of proteins. Tyrosine sulfation is a ubiquitous posttranslational modification which is known to be associated with regulation of various biological functions and pathological processes. Thus its identification is necessary to understand its mechanism. Experimental determination through site-directed mutagenesis and high throughput mass spectrometry is a costly and time taking process, thus, the reliable computational model is required for identification of sulfotyrosine sites. Methodology: In this paper, we present a computational model for the prediction of the sulfotyrosine sites named iSulfoTyr-PseAAC in which feature vectors are constructed using statistical moments of protein amino acid sequences and various position/composition relative features. These features are incorporated into PseAAC. The model is validated by jackknife, cross-validation, self-consistency and independent testing. Results: Accuracy determined through validation was 93.93% for jackknife test, 95.16% for crossvalidation, 94.3% for self-consistency and 94.3% for independent testing. Conclusion: The proposed model has better performance as compared to the existing predictors, however, the accuracy can be improved further, in future, due to increasing number of sulfotyrosine sites in proteins.

Identification of Lysine Carboxylation Sites in Proteins by Integrating Statistical Moments and Position Relative Features via General PseAAC

2020 ◽  
Vol 15 (5) ◽  
pp. 396-407 ◽  
Author(s):  
Saba Amanat ◽  
Adeel Ashraf ◽  
Waqar Hussain ◽  
Nouman Rasool ◽  
Yaser D. Khan
Keyword(s):  
Prediction Model ◽  
Model Validation ◽  
Cross Validation ◽  
Covalent Attachment ◽  
Side Chain ◽  
Consistency Test ◽  
Post Translational Modifications ◽  
Independent Dataset ◽  
Proposed Model ◽  
Self Consistency

Background: Carboxylation is one of the most biologically important post-translational modifications and occurs on lysine, arginine, and glutamine residues of a protein. Among all these three, the covalent attachment of the carboxyl group with the lysine side chain is the most frequent and biologically important type of carboxylation. For studying such biological functions, it is essential to correctly determine the lysine sites sensitive to carboxylation. Objective: Herein, we present a computational model for the prediction of the carboxylysine site which is based on machine learning. Methods: Various position and composition relative features have been incorporated into the Pse- AAC for construction of feature vectors and a neural network is employed as a classifier. The model is validated by jackknife, cross-validation, self-consistency, and independent testing. Results: The results of the self-consistency test elaborated that model has 99.76% Acc, 99.76% Sp, 99.76% Sp, and 0.99 MCC..Using the jackknife method, prediction model validation gave 97.07% Acc, while for 10-fold cross-validation, prediction model validation gave 95.16% Acc. Conclusion: The results of independent dataset testing were 94.3% which illustrated that the proposed model has better performance as compared to the existing model PreLysCar; however, the accuracy can be improved further, in the future, due to the increasing number of carboxylysine sites in proteins.

N-MyristoylG-PseAAC: Sequence-based Prediction of N-Myristoyl Glycine Sites in Proteins by Integration of PseAAC and Statistical Moments

2019 ◽  
Vol 16 (3) ◽  
pp. 226-234 ◽  
Author(s):  
Sher Afzal Khan ◽  
Yaser Daanial Khan ◽  
Shakeel Ahmad ◽  
Khalid H. Allehaibi
Keyword(s):  
Adaptive Learning ◽  
Protein Modification ◽  
Cross Validation ◽  
Back Propagation ◽  
Back Propagation Neural Network ◽  
Statistical Moments ◽  
Covalent Attachment ◽  
Related Proteins ◽  
Self Consistency ◽  
Fold Cross Validation

N-Myristoylation, an irreversible protein modification, occurs by the covalent attachment of myristate with the N-terminal glycine of the eukaryotic and viral proteins, and is associated with a variety of pathogens and disease-related proteins. Identification of myristoylation sites through experimental mechanisms can be costly, labour associated and time-consuming. Due to the association of N-myristoylation with various diseases, its timely prediction can help in diagnosing and controlling the associated fatal diseases. Herein, we present a method named N-MyristoylG-PseAAC in which we have incorporated PseAAC with statistical moments for the prediction of N-Myristoyl Glycine (NMG) sites. A benchmark dataset of 893 positive and 1093 negative samples was collected and used in this study. For feature vector, various position and composition relative features along with the statistical moments were calculated. Later on, a back propagation neural network was trained using feature vectors and scaled conjugate gradient descent with adaptive learning was used as an optimizer. Selfconsistency testing and 10-fold cross-validation were performed to evaluate the performance of N-MyristoylG-PseAAC, by using accuracy metrics. For self-consistency testing, 99.80% Acc, 99.78% Sp, 99.81% Sn and 0.99 MCC were observed, whereas, for 10-fold cross validation, 97.18% Acc, 98.54% Sp, 96.07% Sn and 0.94 MCC were observed. Thus, it was found that the proposed predictor can help in predicting the myristoylation sites in an efficient and accurate way.

Where Robot Looks Is Not Where Person Thinks Robot Looks

2017 ◽  
Vol 21 (4) ◽  
pp. 660-666 ◽  
Author(s):  
Yusuke Tamura ◽  
Takafumi Akashi ◽  
Hisashi Osumi ◽  
◽  
Keyword(s):  
Computational Model ◽  
Cross Validation ◽  
The Gaze ◽  
Human Attention ◽  
Proposed Model ◽  
The Relationship

For a robot to smoothly interact with humans, it has to possess the capability to manipulate human attention to a certain degree. In this study, we start with a hypothesis that humans cannot correctly perceive what a robot is looking at. To examine the hypothesis, an experiment, which focuses on the relationship between a robot’s geometrical gaze point and the gaze point perceived by a human, was conducted. The results of the experiment supported the hypothesis. Based on the results, we propose a computational model that calculates where robots are to look in order to guide human’s attention to the desired area. The validity of the proposed model was demonstrated by cross validation.

scholarly journals Antibiotic Resistance of Uropathogens Isolated from Patients Hospitalized in District Hospital in Central Poland in 2020

Antibiotics ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 447
Author(s):  
Barbara Kot ◽  
Agata Grużewska ◽  
Piotr Szweda ◽  
Jolanta Wicha ◽  
Urszula Parulska
Keyword(s):  
Antibiotic Resistance ◽  
Multidrug Resistant ◽  
Diffusion Method ◽  
Disk Diffusion Method ◽  
Beta Lactamases ◽  
E Coli ◽  
Central Poland ◽  
Resistance Patterns ◽  
Extended Spectrum Beta Lactamases ◽  
Tract Infections

The aim of this study was to determine antibiotic resistance patterns and the prevalence of uropathogenes causing urinary tract infections (UTIs) in patients hospitalized in January–June 2020 in central Poland. Antimicrobial susceptibility testing was performed using the disk-diffusion method. Escherichia coli (52.2%), Klebsiella pneumoniae (13.7%), Enterococcus faecalis (9.3%), E. faecium (6.2%), and Proteus mirabilis (4,3%) were most commonly isolated from urine samples. E. coli was significantly more frequent in women (58.6%) (p = 0.0089) and in the age group 0–18, while K. pneumoniae was more frequent in men (24.4%) (p = 0.0119) and in individuals aged 40–60 and >60. Gram-negative species showed resistance to ampicillin. K. pneumoniae were resistant to amoxicillin plus clavulanic acid (75.0%), piperacillin plus tazobactam (76.2%), cefotaxime (76.2%), cefuroxime (81.0%), ciprofloxacin (81.0%), and trimethoprim plus sulphamethoxazole (81.0%). Carbapenems were effective against all E. coli and P. mirabilis. Some K. pneumoniae (13.6%) produced metallo-β-lactamases (MBLs). E. coli (22.6%), K. pneumoniae (81.8%), and all E. faecium were multidrug-resistant (MDR). Some E. coli (26.2%), K. pneumoniae (63.6%), and P. mirabilis (14.3%) isolates produced extended-spectrum beta-lactamases (ESBL). Vancomycin-resistant E. faecium was also found. This study showed that the possibilities of UTIs therapy using available antibiotics become limited due to the increasing number of antibiotic-resistant uropathogens.

scholarly journals A Fatty Acid Synthase Gene in Cochliobolus carbonum Required for Production of HC-Toxin, Cyclo(d-Prolyl-l-Alanyl- d-Alanyl- l-2-Amino-9,10-Epoxi-8-Oxodecanoyl)

1997 ◽  
Vol 10 (2) ◽  
pp. 207-214 ◽  
Author(s):  
Joong-Hoon Ahn ◽  
Jonathan D. Walton
Keyword(s):  
Fatty Acid ◽  
Fatty Acid Synthase ◽  
Cyclic Peptide ◽  
Decanoic Acid ◽  
Toxin Production ◽  
Gene Encoding ◽  
Cochliobolus Carbonum ◽  
Primary Amino ◽  
Hc Toxin

The fungal maize pathogen Cochliobolus carbonum produces a phytotoxic and cytostatic cyclic peptide, HC-toxin, of structure cyclo(D-prolyl-L-alanyl-D-alanyl-L-Aeo), in which Aeo stands for 2-amino-9,10-epoxi-8-oxodecanoic acid. Here we report the isolation of a gene, TOXC, that is present only in HC-toxin-producing (Tox2+) fungal strains. TOXC is present in most Tox2+ strains in three functional copies, all of which are on the same chromosome as the gene encoding HC-toxin synthetase. When all copies of TOXC are mutated by targeted gene disruption, the fungus grows and sporulates normally in vitro but no longer makes HC-toxin and is not pathogenic, indicating that TOXC has a specific role in HC-toxin production and hence virulence. The TOXC mRNA is 6.5 kb and the predicted product has 2,080 amino acids and a molecular weight of 233,000. The primary amino acid sequence is highly similar (45 to 47% identity) to the β subunit of fatty acid synthase from several lower eukaryotes, and contains, in the same order as in other β subunits, domains predicted to encode acetyl transferase, enoyl reductase, dehydratase, and malonyl-palmityl transferase. The most plausible function of TOXC is to contribute to the synthesis of the decanoic acid backbone of Aeo.

scholarly journals Phenotypic detection of Carbapenamase among Klebsiella pneumoniae isolated from clinical samples using modified Hodged test

2020 ◽  
Vol 13 (3) ◽  
pp. 135-140
Author(s):  
HauwaYakubu ◽  
Mahmud Yerima Iliyasu ◽  
Asma’u Salisu ◽  
Abdulmumin Ibrahim Sulaiman ◽  
Fatima Tahir ◽  
...  
Keyword(s):  
Klebsiella Pneumoniae ◽  
Susceptibility Testing ◽  
University Teaching ◽  
Diffusion Method ◽  
Clinical Samples ◽  
Beta Lactam ◽  
Beta Lactamases ◽  
Beta Lactam Antibiotics ◽  
Microbiological Techniques ◽  
Tract Infections

Carbapenemases are microbial enzymes that confer resistance to virtually all available beta-lactam antibiotics and the most frequent carbapenemases are the Klebsiella pneumoniae Carbapenamase (KPC). Detection of carbapenemases is a significant infection control strategy as the enzymes are often associated with extensive antimicrobial resistance, therapeutic failures and mortality associated with infectious diseases. A total of 400 clinical samples were collected from different groups of patients in Abubakar Tafawa Balewa University Teaching Hospital, Bauchi, Nigeria and 118 K. pneumoniae were isolated using standard microbiological techniques. The isolates were subjected to antibiotic susceptibility testing by Kirby-Bauer disc diffusion method, then screened for Carbapenamase production using modified Hodge test. The results indicated that the isolates were resistant to Ampicillin (61.9%), Ceftriaxone (50.8%) and Ceftazidime (50.8%), then Ciprofloxacin (54.2%), but predominantly sensitive to Imipenem (66.9%), Eterpenem (60.2%) and Meropenem (65.3%). It was found that 38 (32.2%) of the isolates phenotypically shows the presence of Carbapenamase, with highest frequency of (40.7%) among patients, mainly adult females with cases of Urinary Tract Infections (UTIs) and the least from wound (11.8%).This study revealed that the isolates produced other beta-lactamases than KPC or variants of Carbapenamase that cannot be detected by modified Hodge test, thus shows low resistance to carbapenems. Therefore further studies is needed to genotypically confirm the presence of KPC in these isolates.

scholarly journals Prevalence Of Extended Spectrum Beta-Lactamases (ESBLs)-Producing Escherichia Coli Isolated From UTI Patients Attending some Selected Hospitals In Minna, Nigeria

2021 ◽  
Vol 37 (2) ◽  
pp. 56-73
Author(s):  
F Iseghohi ◽  
J.C Igwe ◽  
M Galadima ◽  
A.F Kuta ◽  
A.M Abdullahi ◽  
...  
Keyword(s):  
Escherichia Coli ◽  
Multidrug Resistance ◽  
Urine Samples ◽  
Antibiotics Resistance ◽  
Healthy Individuals ◽  
Beta Lactamases ◽  
E Coli ◽  
Extended Spectrum ◽  
Extended Spectrum Beta Lactamases ◽  
Tract Infections

Globally, urinary tract infections are one of the most common infections in need of urgent clinical attention. The prevalence of extended spectrum beta-lactamases (ESBL)- producing Escherichia coli isolated from urine samples of some UTI patients and s of apparently healthy individuals in Minna, Nigeria, is investigated. Standard microbiological techniques were used to conduct this study. A total of 170 catch midstream urine samples submitted to the Medical Microbiology Laboratories of 4 different hospitals (and samples from healthy individuals) were randomly collected for 5 months and examined for microbial growths. Female patients (65.9%) submitted more urine samples for UTI test than their male counterpart (34.1%). The age ranges of 21 -30 (26.5%) and 31 - 40 (25.3%) had the highest percentages of infection rate while those within the ages 1- 10 (3.5%) and ≥ 71 (2.3%) were the least infected. This study observed a prevalence of 23.5% of E. coli in Minna metropolis and a significant number (30%) of healthy individuals (HI) was observed to harbor the E. coli in their urine. The isolates were highly susceptible to Gentamicin (65%), Ofloxacin (65%), Tetracycline (62.5%), Cotrimoxazole (62.5%), and Streptomycin (57.5%). Mildly susceptible to Pefloxacin (37.5%), Chloramphenicol (37.5%), and Ciprofloxacin (35%). There were significant resistance to most of the beta-lactames tested [Cefuroxime (80%), Amoxicillin (42.5%), Augmentin (40), Cefotaxime (20%) and Ceftaxidime (7.5%)]. Two of the isolates were resistant to all the 13 antibiotics tested; 70% (28) of the isolates had multiple antibiotics resistance index (MARI) ≥0.3. Multidrug resistance was expressed in 37.5% of the isolates tested. The study showed a vast resistant pool in the environment. Only 25% of the E. coli isolated from the urine samples produced beta-lactamases phenotypically, most of which expressed resistance to more than 5 of the antibiotics tested and had MARI of ≥ 0.5. Further evaluation showed that 25% (10/40) of the E. coli isolated from the UTI patients in Minna, Nigeria, were ESBL- producers and could harbor one or two of the genes. TEM gene was expressed in 70% (7) of the isolates that produced ESBL phenotypically, 60% 6) harbored CTXM gene, 20% (2) had the OXA gene while none of the bacteria harbored the SHV gene. The study established a 5.9% ESBL prevalence among the E. coli isolated from UTI in the environment studied. This study established that E. coli is one of the prevalent bacteri urea majorly isolated from UTI patients in Minna. The prevalent E. coli are multidrug resistant and could harbor more than one ESBL gene . keywords: Escherichia coli, Minna, UTI, ESBL, Multidrug resistance

scholarly journals Plasmid Derived AmpC Genotypes among the Multidrug Resistant Enterobacteriaceae Strains Isolated from Urine Samples in Southern India

2021 ◽  
Author(s):  
P Ronni Mol ◽  
Ganesan Shanthi ◽  
Khalid Bindayna
Keyword(s):  
Clinical Laboratory ◽  
Multidrug Resistant ◽  
Cross Sectional Study ◽  
Urine Samples ◽  
Pcr Analysis ◽  
Genotype Distribution ◽  
Cross Sectional ◽  
Beta Lactamases ◽  
Hospital Infection Control ◽  
Tract Infections

Introduction: The most common pathogens causing Urinary Tract Infections (UTI) in community and hospital settings are Enterobacteriaceae. Antibiotic resistance is a major problem worldwide because of an increase in the use of antibiotics. Production of Extended Spectrum Beta-Lactamases (ESBLs) and AmpC beta-lactamases is the most common cause of resistance among Enterobacteriaceae (AmpC). Initially, AmpC β-lactamases received less attention globally, but now it has become a rising problem. Detection of AmpC β-lactamases expressing microbes is a requirement for addressing surveillance, for problems of hospital infection control, and for choosing optimal antimicrobial therapy. Aim: To study the genotype distribution of plasmid mediated AmpC β-lactamase produced in Enterobacteriaceaestrains isolated from urine samples. Materials and Methods: A cross-sectional study based on clinical laboratory surveillance was conducted from July 2019 to February 2020. Sixty Enterobacteriaceae isolates were identified by standard biochemical reactions. AmpC screening were done by cefoxitin disk diffusion and confirmed by an inhibitor-based assay using boronic acid. The presence of six plasmid mediated AmpC genes was determined by multiplex Polymerase Chain Reaction (PCR). Statistical Package for the Social Science (SPSS) version 20.0 was used to obtain descriptive data. Results: Among 60 Enterobacteriaceae isolates, 23 (38.3%) were cefoxitin-resistant isolates which contain Escherichia colistrain (n=17) while the remaining samples consist ofKlebsiella pneumoniae (n=5) and Proteus mirabilis strains (n=1). AmpC β-lactamase production was phenotypically confirmed in 12(20%) isolates and genotypically confirmed by PCR analysis in 16(26.6%) of all the urine isolates. In the present study, 3(13%), 2 (8.6%) of cefoxitin resistant isolates harboured the DHA, EBC gene and 1(4.3%) each harboured FOX and CIT gene, and 9(39.1%) harboured a combination of the genes. Conclusion: The present study suggested the predominant existence of plasmid mediated AmpC producers in Multi-Drug Resistant (MDR) Escherichia coli and Klebsiella pneumoniae. We suggest continuous surveillance is important to effectively control the spread of these strains and for optimal clinical outcome.

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