Researcher: Keskin, Özlem
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Keskin, Özlem
Özkaya, Zehra Özlem Keskin
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Publication Metadata only PPInterface: a comprehensive dataset of 3D protein-protein interface structures(Academic Press, 2024) Department of Computer Engineering;Department of Chemical and Biological Engineering; Abalı, Zeynep; Aydın, Zeynep; Khokkar, Moaaz Ur-Rehman; Gürsoy, Attila; Keskin, Özlem; Graduate School of Sciences and Engineering; College of EngineeringThe PPInterface dataset contains 815,082 interface structures, providing the most comprehensive structural information on protein–protein interfaces. This resource is extracted from over 215,000 three-dimensional protein structures stored in the Protein Data Bank (PDB). The dataset contains a wide range of protein complexes, providing a wealth of information for researchers investigating the structural properties of protein–protein interactions. The accompanying web server has a user-friendly interface that allows for efficient search and download functions. Researchers can access detailed information on protein interface structures, visualize them, and explore a variety of features, increasing the dataset's utility and accessibility.Publication Metadata only Conformational diversity and protein-protein interfaces in drug repurposing in ras signaling pathway(Nature Portfolio, 2024) Department of Computer Engineering;Department of Chemical and Biological Engineering; Sayın, Ahenk Zeynep; Abalı, Zeynep; Şenyüz, Simge; Cankara, Fatma; Gürsoy, Attila; Keskin, Özlem; Graduate School of Sciences and Engineering; College of EngineeringWe focus on drug repurposing in the Ras signaling pathway, considering structural similarities of protein-protein interfaces. The interfaces formed by physically interacting proteins are found from PDB if available and via PRISM (PRotein Interaction by Structural Matching) otherwise. The structural coverage of these interactions has been increased from 21 to 92% using PRISM. Multiple conformations of each protein are used to include protein dynamics and diversity. Next, we find FDA-approved drugs bound to structurally similar protein-protein interfaces. The results suggest that HIV protease inhibitors tipranavir, indinavir, and saquinavir may bind to EGFR and ERBB3/HER3 interface. Tipranavir and indinavir may also bind to EGFR and ERBB2/HER2 interface. Additionally, a drug used in Alzheimer's disease can bind to RAF1 and BRAF interface. Hence, we propose a methodology to find drugs to be potentially used for cancer using a dataset of structurally similar protein-protein interface clusters rather than pockets in a systematic way.Publication Metadata only Shared proteins and pathways of cardiovascular and cognitive diseases: relation to vascular cognitive impairment(Amer Chemical Soc, 2024) Picon-Pages, Pol; Garcia-Elias, Anna; Tajes, Marta; Munoz, Francisco J.; Oliva, Baldomero; Garcia-Ojalvo, Jordi; Barbu, Eduard; Vicente, Raul; Nattel, Stanley; Ois, Angel; Puig-Pijoan, Albert; Department of Chemical and Biological Engineering; Department of Computer Engineering; Zeylan, Melisa Ece; Şenyüz, Simge; Keskin, Özlem; Gürsoy, Attila; Graduate School of Sciences and Engineering; College of EngineeringOne of the primary goals of systems medicine is the detection of putative proteins and pathways involved in disease progression and pathological phenotypes. Vascular cognitive impairment (VCI) is a heterogeneous condition manifesting as cognitive impairment resulting from vascular factors. The precise mechanisms underlying this relationship remain unclear, which poses challenges for experimental research. Here, we applied computational approaches like systems biology to unveil and select relevant proteins and pathways related to VCI by studying the crosstalk between cardiovascular and cognitive diseases. In addition, we specifically included signals related to oxidative stress, a common etiologic factor tightly linked to aging, a major determinant of VCI. Our results show that pathways associated with oxidative stress are quite relevant, as most of the prioritized vascular cognitive genes and proteins were enriched in these pathways. Our analysis provided a short list of proteins that could be contributing to VCI: DOLK, TSC1, ATP1A1, MAPK14, YWHAZ, CREB3, HSPB1, PRDX6, and LMNA. Moreover, our experimental results suggest a high implication of glycative stress, generating oxidative processes and post-translational protein modifications through advanced glycation end-products (AGEs). We propose that these products interact with their specific receptors (RAGE) and Notch signaling to contribute to the etiology of VCI.Publication Metadata only ProInterVal: validation of protein-protein interfaces through learned interface representations(Amer Chemical Soc, 2024) Department of Chemical and Biological Engineering; Department of Computer Engineering; Övek, Damla; Keskin, Özlem; Gürsoy, Attila; Koç Üniversitesi İş Bankası Yapay Zeka Uygulama ve Araştırma Merkezi (KUIS AI)/ Koç University İş Bank Artificial Intelligence Center (KUIS AI); Graduate School of Sciences and Engineering; College of EngineeringProteins are vital components of the biological world and serve a multitude of functions. They interact with other molecules through their interfaces and participate in crucial cellular processes. Disruption of these interactions can have negative effects on organisms, highlighting the importance of studying protein-protein interfaces for developing targeted therapies for diseases. Therefore, the development of a reliable method for investigating protein-protein interactions is of paramount importance. In this work, we present an approach for validating protein-protein interfaces using learned interface representations. The approach involves using a graph-based contrastive autoencoder architecture and a transformer to learn representations of protein-protein interaction interfaces from unlabeled data and then validating them through learned representations with a graph neural network. Our method achieves an accuracy of 0.91 for the test set, outperforming existing GNN-based methods. We demonstrate the effectiveness of our approach on a benchmark data set and show that it provides a promising solution for validating protein-protein interfaces.Publication Open Access DiPPI: a curated data set for drug-like molecules in protein-protein interfaces(Amer Chemical Soc, 2024) Department of Computer Engineering;Department of Chemical and Biological Engineering; Cankara, Fatma; Şenyüz, Simge; Sayın, Ahenk Zeynep; Gürsoy, Attila; Keskin, Özlem; Graduate School of Sciences and Engineering; College of EngineeringProteins interact through their interfaces, and dysfunction of protein-protein interactions (PPIs) has been associated with various diseases. Therefore, investigating the properties of the drug-modulated PPIs and interface-targeting drugs is critical. Here, we present a curated large data set for drug-like molecules in protein interfaces. We further introduce DiPPI (Drugs in Protein-Protein Interfaces), a two-module web site to facilitate the search for such molecules and their properties by exploiting our data set in drug repurposing studies. In the interface module of the web site, we present several properties, of interfaces, such as amino acid properties, hotspots, evolutionary conservation of drug-binding amino acids, and post-translational modifications of these residues. On the drug-like molecule side, we list drug-like small molecules and FDA-approved drugs from various databases and highlight those that bind to the interfaces. We further clustered the drugs based on their molecular fingerprints to confine the search for an alternative drug to a smaller space. Drug properties, including Lipinski's rules and various molecular descriptors, are also calculated and made available on the web site to guide the selection of drug molecules. Our data set contains 534,203 interfaces for 98,632 protein structures, of which 55,135 are detected to bind to a drug-like molecule. 2214 drug-like molecules are deposited on our web site, among which 335 are FDA-approved. DiPPI provides users with an easy-to-follow scheme for drug repurposing studies through its well-curated and clustered interface and drug data and is freely available at http://interactome.ku.edu.tr:8501.Publication Metadata only Attenuation of Type IV pili activity by natural products(Taylor & Francis Inc, 2024) Yalkut, Kerem; Hassine, Soumaya Ben Ali; Kula, Ceyda; Ozcan, Aslihan; Avci, Fatma Gizem; Akbulut, Berna Sariyar; Ozbek, Pemra; Department of Chemical and Biological Engineering; Department of Chemical and Biological Engineering; Başaran, Esra; Keskin, Özlem; Graduate School of Sciences and Engineering; College of EngineeringThe virulence factor Type IV pili (T4P) are surface appendages used by the opportunistic pathogen Pseudomonas aeruginosa for twitching motility and adhesion in the environment and during infection. Additionally, the use of these appendages by P. aeruginosa for biofilm formation increases its virulence and drug resistance. Therefore, attenuation of the activity of T4P would be desirable to control P. aeruginosa infections. Here, a computational approach has been pursued to screen natural products that can be used for this purpose. PilB, the elongation ATPase of the T4P machinery in P. aeruginosa, has been selected as the target subunit and virtual screening of FDA-approved drugs has been conducted. Screening identified two natural compounds, ergoloid and irinotecan, as potential candidates for inhibiting this T4P-associated ATPase in P. aeruginosa. These candidate compounds underwent further rigorous evaluation through molecular dynamics (MD) simulations and then through in vitro twitching motility and biofilm inhibition assays. Notably, ergoloid emerged as a particularly promising candidate for weakening the T4P activity by inhibiting the elongation ATPases associated with T4P. This repurposing study paves the way for the timely discovery of antivirulence drugs as an alternative to classical antibiotic treatments to help combat infections caused by P. aeruginosa and related pathogens.Publication Open Access Dysbiosis in pregnant mice induced by transfer of human vaginal microbiota followed by reversal of pathological changes in the uterus and placenta via progesterone treatment(BMC, 2024) Department of Computer Engineering;Department of Chemical and Biological Engineering; Kuyucu, Gülin Özcan; Talay, Zeynep Gülce; Paerhati, Erxiati; Eren, Özgür Can; Coşkun, Nilhan; Şahin, Deniz; Alnajjar, Iman; Albayrak, Özgür; Gürsoy, Attila; Keskin, Özlem; Çelik, Ebru; Can, Füsun; Koç Üniversitesi İş Bankası Enfeksiyon Hastalıkları Uygulama ve Araştırma Merkezi (EHAM) / Koç University İşbank Center for Infectious Diseases (KU-IS CID); Koç University Research Center for Translational Medicine (KUTTAM) / Koç Üniversitesi Translasyonel Tıp Araştırma Merkezi (KUTTAM); Graduate School of Health Sciences; College of Engineering; School of Medicine; Koç University HospitalObjective The vaginal microbiota dysbiosis induces inflammation in the uterus that triggers tissue damage and is associated with preterm birth. Progesterone is used to prevent labor in pregnant women at risk of preterm birth. However, the mechanism of action of progesterone still needs to be clarified. We aimed to show the immunomodulatory effect of progesterone on the inflammation of uterine tissue triggered by dysbiotic vaginal microbiota in a pregnant mouse model.Methods Healthy (n = 6) and dysbiotic (n = 7) vaginal microbiota samples isolated from pregnant women were transferred to control (n = 10) and dysbiotic (n = 14) pregnant mouse groups. The dysbiotic microbiota transferred group was treated with 1 mg progesterone (n = 7). Flow cytometry and immunohistochemistry analyses were used to evaluate inflammatory processes. Vaginal microbiota samples were analyzed by 16 S rRNA sequencing.Results Vaginal exposure to dysbiotic microbiota resulted in macrophage accumulation in the uterus and cellular damage in the placenta. Even though TNF and IL-6 elevations were not significant after dysbiotic microbiota transplantation, progesterone treatment decreased TNF and IL-6 expressions from 49.085 to 31.274% (p = 0.0313) and 29.279-21.216% (p = 0.0167), respectively. Besides, the macrophage density in the uterus was reduced, and less cellular damage in the placenta was observed.Conclusion Analyzing the vaginal microbiota before or during pregnancy may support the decision for initiation of progesterone therapy. Our results also guide the development of new strategies for preventing preterm birth.Publication Metadata only The vaginal microbiome composition during pregnancy in a region compromising different ethnic origins(Springer Heidelberg, 2024) Department of Computer Engineering;Department of Chemical and Biological Engineering; Kuyucu, Gülin Özcan; Vatansever, Cansel; Paerhati, Erxiati; Turğal, Mert; Gürsoy, Tuğba; Çekiç, Sebile Güler; Ünal, Ceren; Özek, Murat Aykut; Gürsoy, Attila; Keskin, Özlem; Can, Füsun; Çelik, Ebru; Koç Üniversitesi İş Bankası Enfeksiyon Hastalıkları Uygulama ve Araştırma Merkezi (EHAM) / Koç University İşbank Center for Infectious Diseases (KU-IS CID); Graduate School of Health Sciences; Graduate School of Sciences and Engineering; School of Medicine; College of Engineering; Koç University HospitalBackgroundThe vaginal microbiota plays a significant role in pregnancy outcomes and newborn health. Indeed, the composition and diversity of the vaginal microbiota can vary among different ethnic groups. Our study aimed to investigate the composition of the vaginal microbiome throughout the three trimesters of pregnancy and to identify any potential variations or patterns in the Turkish population compromising mixed ethnicities.MethodWe conducted a longitudinal study to characterize the vaginal microbiota of pregnant women. The study included a total of 25 participants, and the samples were collected at each trimester: 11-13 weeks, 20-24 weeks and 28-34 weeks gestation.ResultsLactobacillus species were consistently found to be dominant in the vaginal microbiota throughout all trimesters of pregnancy. Among Lactobacillus species, L. crispatus had the highest abundance in all trimesters (40.6%, 40.8% and 44.4%, respectively). L. iners was the second most prevalent species (28.5%, 31% and 25.04, respectively). Our findings reveal that the dominant composition of the vaginal microbiota aligns with the CST-type I, commonly observed in the European population.ConclusionsThis suggests that there are shared mechanisms influencing the microbial communities in the vagina, which are likely influenced by factors such as genetics, lifestyle, and cultural behaviors rather than ethnicity alone. The complex interplay of these factors contributes to the establishment and maintenance of the vaginal microbiota during pregnancy. Understanding the underlying mechanisms and their impact on vaginal health across diverse populations is essential for improving pregnancy outcomes.The study was approved by the Koc University Ethical Committee (no:2019.093.IRB2.030) and registered at the clinical trials.ConclusionsThis suggests that there are shared mechanisms influencing the microbial communities in the vagina, which are likely influenced by factors such as genetics, lifestyle, and cultural behaviors rather than ethnicity alone. The complex interplay of these factors contributes to the establishment and maintenance of the vaginal microbiota during pregnancy. Understanding the underlying mechanisms and their impact on vaginal health across diverse populations is essential for improving pregnancy outcomes.The study was approved by the Koc University Ethical Committee (no:2019.093.IRB2.030) and registered at the clinical trials.Publication Metadata only A new dataset of non-redundant protein/protein interfaces(Biophysical Society, 2003) Tsai, CJ; Wolfson, H; Nussinov, R; Department of Chemical and Biological Engineering; Department of Chemical and Biological Engineering; Keskin, Özlem; Faculty Member; College of Engineering; 26605Publication Metadata only How similar are protein folding and protein binding nuclei? Examination of vibrational motions of energy hot spots and conserved residues(Cell Press, 2005) Haliloğlu, Türkan; Ma, Buyong; Nussinov, Ruth; Department of Chemical and Biological Engineering; Department of Chemical and Biological Engineering; Keskin, Özlem; Faculty Member; College of Engineering; 26605The underlying physico-chemical principles of the interactions between domains in protein folding are similar to those between protein molecules in binding. Here we show that conserved residues and experimental hot spots at intermolecular binding interfaces overlap residues that vibrate with high frequencies. Similarly, conserved residues and hot spots are found in protein cores and are also observed to vibrate with high frequencies. In both cases, these residues contribute significantly to the stability. Hence, these observations validate the proposition that binding and folding are similar processes. In both packing plays a critical role, rationalizing the residue conservation and the experimental alanine scanning hot spots. We further show that high-frequency vibrating residues distinguish between protein binding sites and the remainder of the protein surface.