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Öğe Binding Activity Classification of Anti-SARS-CoV-2 Molecules using Deep Learning Across Multiple Assays(Galenos Publ House, 2024) Yamasan, Bilge Eren; Korkmaz, SelcukBackground: The coronavirus disease -2019 (COVID-19) pandemic, caused by severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2), has urgently necessitated effective therapeutic solutions, with a focus on rapidly identifying and classifying potential small -molecule drugs. Given traditional methods' labor-intensive and time-consuming nature, deep learning has emerged as an essential tool for efficiently processing and extracting insights from complex biological data. Aims: To utilize deep learning techniques, particularly deep neural networks (DNN) enhanced with the synthetic minority oversampling technique (SMOTE), to enhance the classification of binding activities in anti-SARS-CoV-2 molecules across various bioassays. Methods: We used 11 bioassay datasets covering various SARS-CoV-2 interactions and inhibitory mechanisms. These assays ranged from spike-ACE2 protein -protein interaction to ACE2 enzymatic activity and 3CL enzymatic activity. To address the prevalent class imbalance in these datasets, the SMOTE technique was employed to generate new samples for the minority class. In our model -building approach, we divided the dataset into 80% training and 20% test sets, reserving 10% of the training set for validation. Our approach involved employing a DNN that integrates ReLU and sigmoid activation functions, incorporates batch normalization, and uses Adam optimization. The hyperparameters and architecture of the DNN were optimized through various tests on layers, minibatch sizes, epoch sizes, and learning rates. A 40% dropout rate was incorporated to mitigate overfitting. For model evaluation, we computed performance metrics, such as balanced accuracy (BACC), precision, recall, F1 score, Matthews' correlation coefficient (MCC), and area under the curve (AUC). Results: The performance of the DNN across 11 bioassay test sets revealed varying outcomes, significantly influenced by the ratios of active -to -inactive compounds. Assays, such as AlphaLISA and CoV-PPE, demonstrated robust performance across various metrics, including BACC, precision, recall, and AUC, when configured with more balanced ratios (1:3 and 1:1, respectively). This suggests the effective identification of active compounds in both cases. In contrast, assays with higher imbalance ratios, such as 3CL (1:38) and cytopathic effect (1:15), demonstrated higher recall but lower precision, highlighting challenges in accurately identifying active compounds among numerous inactive compounds. However, even in these challenging settings, the model achieved favorable BACC and recall scores. Overall, the DNN model generally performed well, as indicated by the BACC, MCC, and AUC values, especially when considering the degree of dataset imbalance in each assay. Conclusion: This study demonstrates the significant impact of deep learning, particularly DNN models enhanced with SMOTE, in improving the identification of active compounds in bioassay datasets for COVID-19 drug discovery, outperforming traditional machine learning models. Furthermore, this study highlights the efficacy of advanced computational techniques in addressing high -throughput screening data imbalances.Öğe Calcitonin Gene Related Peptide Gene Polymorphism in Migraine Patients(Cambridge Univ Press, 2013) Guldiken, Baburhan; Sipahi, Tammam; Tekinarslan, Remziye; Kabayel, Levent; Ozkan, Hulya; Unlu, Ayhan; Yamasan, Bilge ErenObjective: Calcitonin gene related peptide (CGRP), which has a vasodilator effect, is held responsible for neurogenic inflammation and vasodilatation of the cranial vessels in migraine pathophysiology. In this study, we investigated the association between alpha CGRP gene polymorphism (CALCA T-692C) and migraine. Material and Methods: One hundred and thirty-four female migraineurs and 96 healthy female cases were enrolled in the study. The patient group was further subdivided into migraine with and without aura groups. The CALCA T-692C gene polymorphism was identified using polymerase chain reaction (PCR) technique and restriction fragment length polymorphism (RFLP). Results: The genotype and allele frequencies of CALCA T-692C gene polymorphism did not differ between the migraine and control groups. Between the migraine with and without aura subgroups, there was no difference. No association was seen between the CALCA T-692C gene polymorphisms and migraine attack severity and frequency. Conclusion: Our study did not show any association between CALCA T-692C gene polymorphism and migraine.Öğe The Effect of a High-Protein Diet and Exercise on Cardiac AQP7 and GLUT4 Gene Expression(Springer/Plenum Publishers, 2016) Palabiyik, Orkide; Karaca, Aziz; Tastekin, Ebru; Yamasan, Bilge Eren; Tokuc, Burcu; Sipahi, Tammam; Vardar, Selma ArzuHigh-protein (HP) diets are commonly consumed by athletes despite their potential health hazard, which is postulated to enforce a negative effect on bone and renal health. However, its effects on heart have not been known yet. Aquaporin-7 (AQP7) is an aquaglyceroporin that facilitates glycerol and water transport. Glycerol is an important cardiac energy production substrate, especially during exercise, in conjunction with fatty acids and glucose. Glucose transporter 4 (GLUT4) is an insulin-sensitive glucose transporter in heart. We aimed to investigate the effect of HPD on AQP7 and GLUT4 levels in the rat heart subjected to exercise. Male Sprague-Dawley rats were divided into control (n = 12), exercise (E) training (n = 10), HPD (n = 12), and HPD-E training (n = 9) groups. The HPD groups were fed a 45 % protein-containing diet 5 weeks. The HPD-E and E groups were performed the treadmill exercise during the 5-week study period. Real-time polymerase chain reaction and immunohistochemistry techniques were used to determine the gene expression and localization of AQP7 and GLUT4 in heart tissue. Results of relative gene expression were calculated by the 'Pfaffl' mathematical method using the REST program. Differences in AQP7 and GLUT4 gene expression were expressed as fold change compared to the control group. Heart weight/tibia ratio and ventricular wall thickness were evaluated as markers of cardiac hypertrophy. Further, serum glucose, glycerol, and insulin levels were also measured. AQP7 gene expression was found to be increased in the E (3.47-fold, p < 0.001), HPD (5.59-fold, p < 0.001), and HPD-E (3.87-fold, p < 0.001) groups compared to the control group. AQP7 protein expression was also increased in the HPD and HPD-E groups (p < 0.001). Additionally, cardiac mRNA expression levels of GLUT4 showed a significant increase in the E (2.16-fold, p < 0.003), HPD (7.14-fold, p < 0.001), and HPD-E (3.43-fold, p < 0.001) groups compared to the control group. GLUT4 protein expression was significantly increased in the E, HPD, and HPD-E groups compared to the control group (p = 0.024, p < 0.001, and p < 0.001, respectively). Furthermore, Serum glucose levels were significantly different between groups (p < 0.005). This difference was observed between the HPD groups and normal-protein diet groups (C and E). Serum insulin levels were higher for HPD groups compared with the normal-protein diet groups (p < 0.001), whereas no differences were observed between the exercise and sedentary groups (p = 0.111). Serum glycerol levels were significantly increased in the HPD groups compared with control and E groups (p < 0.05 and p < 0.05, respectively). Consumption of HPD supplementation caused the increased effects on AQP7 and GLUT4 expression in rat heart.Öğe Investigation of Angiotensinogen M235T and T174M Gene Polymorphisms in Coronary Artery Disease(Erciyes Univ Sch Medicine, 2021) Yamasan, Bilge Eren; Gulyasar, Tevfik; Sipahi, Tammam; Sivri, Nasir; Palabiyik, OrkideObjective: Coronary artery disease (CAD) is a multifactorial disorder and is caused by both environmental and genetic factors. As the alterations in angiotensinogen (AGT) gene lead to changes in angiotensin II and plasma levels of AGT, variants of this gene may play a role in CAD pathogenesis. This study aimed to investigate the relationship between CAD and polymorphisms of AGT gene at M235T and T174M regions. Moreover, the associations of potential risk factors with these gene regions and CAD were investigated. Materials and Methods: In total, the study enrolled 214 cases with CAD and 200 controls. Polymerase chain reaction (PCR) and restriction fragment length polymorphism (RFLP) were used to detect polymorphisms at M235T and T174M. PCR products were electrophoresed on 2% agarose gel, with ethidium bromide, and were then examined under ultraviolet light. Subsequently, RFLP was used to detect gene polymorphisms. A multiple binary logistic regression model was used to investigate the association of risk factors with both CAD and AGT variants. Results: The number of TT polymorphisms at M235T were significantly higher in the case group than in control group. However, there were no significant differences between cases and controls regarding T174M gene polymorphisms. The presence of hypertension, low high-density lipoprotein level, alcohol consumption, and family history were associated with CAD. Conclusion: TT polymorphisms at the M235T region in AGT can be an influential factor in the development of CAD.Öğe Koroner arter hastaliğinda anjiyotensinojen M235T ve T174M gen polimorfizimlerinin araştirilmasi(Trakya Üniversitesi Sağlık Bilimleri Enstitüsü, 2013) Yamasan, Bilge Eren; Gülyaşar, TevfikKoroner Arter Hastalığı (KAH), multifaktöriyel bir hastalık olup hem çevresel hem de genetik faktörler etyolojisinde önemli bir rol oynamaktadır. Bu nedenle, KAH'ın patogenezine katkıda bulunan aday genleri çalışmak, KAH'ın etyolojisinin anlaşılmasına yardımcı olabilir. Anjiyotensinojen (AGT)'deki değişiklikler, güçlü bir damar daraltıcı etkiye sahip olan anjiyotensin-II ve plazmadaki AGT seviyelerinin değişimine sebep olduğundan, bu genin varyantlarının da KAH'ın patogenezinde rol oynayabileceği düşünülmektedir. Bu çalışmada, KAH tanısı alan hastalarda AGT geninin M235T ve T174M gen bölgelerindeki polimorfizimlerin KAH ile ilişkisinin araştırılması ve KAH'a yol açtığı düşünülen olası risk faktörlerinin belirlenmesi amaçlanmıştır. Çalışmaya, yaşları ve cinsiyetleri eşleşen 214 KAH hastası ve 200 kontrol alındı. M235T ve T174M gen polimorfizimlerini belirlemek için Polimeraz Zincir Reaksiyonu (PZR) ve Restriksiyon Fragment Uzunluk Polimorfizmi (RFLP) yöntemleri uygulandı. PZR ürünleri %2'lik agaroz jelde yürütülüp, etidyum bromür (EtBr) ile boyanarak ultraviyole (UV) ışık altında incelendi ve daha sonra RFLP yöntemi ile gen polimorfizimleri tespit edildi. Ki-kare testi kullanılarak gen polimorfizimleri ile KAH arasındaki ilişki araştırıldı ve çoklu lojistik regresyon kullanılarak KAH için risk faktörleri belirlendi. M235T için genotip dağılımları arasında TT polimorfizmi, hastalarda kontrollere göre anlamlı derecede yüksek bulundu (p<0.05). T174M için ise genotip dağılımları arasında anlamlı bir farklılık gözlenmedi (p>0.05). Hipertansiyon varlığı (OR=2.523, %95GA: 1.441-4.418, p<0.05), düşük HDL seviyesi (OR=0.975, %95GA: 0.952-0.999, p<0.05), alkol kullanımı (OR=2.498, %95GA: 1.093-5.172, p<0.05) ve aile öyküsü (OR=2.357, %95GA: 1.077-5.155, p<0.05) KAH ile ilişkili risk faktörleri olarak bulundu. Bu sonuca göre, AGT'nin M235T gen bölgesindeki TT polimorfizmi KAH gelişiminde etkili bir faktör olabilir.Anahtar kelimeler: Koroner Arter Hastalığı, Anjiyotensinojen, M235T, T174M, Polimorfizm
