Biology subjects

Oktay, L.

Publications and source records attributed to Oktay, L..

5 recordsLinked to original sources

bioRxiv2024

Targeting miRNA for Colorectal Cancer: In Silico Identification and Physics-based De Novo Modeling of Oncogenic miR-135b for Small Molecule RNA Therapy

Colorectal cancer is one of the leading causes of cancer deaths worldwide. In the current study, we have identified miR-135b, a microRNA to be differentially expressed in colorectal cancer, through an analysis of the differentially expressed miRNAs from the Gene Expression Omnibus database. Subsequently, the target genes associated with miR-135b were pinpointed, and pathway and functional enrichment analyses were performed to gain a comprehensive understanding of the underlying biological processes involved. A de novo three-dimensional model of its tertiary structure was developed for small-molecule targeting at the Dicer cleavage site. Dicer binds to the terminal loop region of the pre-miRNA and cleaves to generate double stranded miRNA duplex. The miRNA duplex is unwound, one of the strands, guide miRNA, is loaded into the RNA-induced silencing complex (RISC) for miRNA-mRNA target interaction and post-transcriptional gene silencing. Following results from molecular docking simulations initiated with the ChemDiv miRNA-targeted small molecule library ([~]20.000 compounds), top-scoring compounds commercial analogues were then searched within the ZINC library using SwissSimilarity. These analogues were docked to the Dicer cleavage site and their optimized docking scores were obtained. These top-scoring molecules were then subject to all-atom molecular dynamics simulations and post-simulation analyses were conducted to assess the dynamic interactions between the miRNA and the selected hit ligands.

bioinformatics↗

bioRxiv2023

Utilizing Heteroatom Types and Numbers from Extensive Ligand Libraries to Develop Novel hERG Blocker QSAR Models Using Machine Learning-based Classifiers

The human Ether-a-go-go Related Gene (hERG) channel plays a crucial role in membrane repolarization. Any disruptions in its function can lead to severe cardiovascular disorders like long QT syndrome (LQTS), which increases the risk of serious cardiovascular problems such as tachyarrhythmia and sudden cardiac death. Drug-induced LQTS is a significant concern and has resulted in drug withdrawals in the past. The main objective of this research study is to pinpoint crucial heteroatoms present in ligands that initiate interactions leading to effective blocking of the hERG channel. To achieve this aim, ligand-based quantitative structure-activity relationships (QSAR) models were constructed using extensive ligand libraries, considering the heteroatom types and numbers, and their associated hERG channel blockage pIC50 values. Machine learning-assisted QSAR models were developed to analyze the key structural components influencing compound activity. Among various methods, the KPLS method proved to be the most efficient, allowing the construction of models based on eight distinct fingerprints. The study delved into investigating the influence of heteroatoms on the activity of hERG blockers, revealing their significant role. Furthermore, by quantifying the effect of heteroatom types and numbers on ligand activity at the hERG channel, six compound pairs were selected for molecular docking. Subsequent molecular dynamics (MD) simulations and MM/GBSA calculations per residue were performed to comprehensively analyze the interactions of the selected pair compounds.

bioinformatics↗

bioRxiv2023

Dynamic Structure-based Pharmacophore Models for Virtual Screening of Small Molecule Libraries Targeting the YB-1

In drug discovery, ligand-based techniques offer rapid screening, whereas structure-based approaches provide deeper insights but are time-consuming. Hybrid methods like structure-based pharmacophore models combine advantages for accurate screening of large ligand libraries. However, there are substantial limits to build structure-based pharmacophore models. Static models relying on a single co-crystallized structure or docking pose often fall short in capturing the dynamic nature of binding interactions. In this study, we present dynamic structure-based pharmacophore models, aimed at better representing physiological conditions and addressing these challenges. The urgent need for improved cancer treatment has led to the search for new chemotherapeutic strategies. Y box binding protein 1 (YB-1) is a multifunctional protein associated with tumor progression and treatment resistance in various cancers. For the first time in the literature, our study utilizes a known small molecule YB-1 inhibitor (SU056) bound to the active regions of the RNA-binding sites to develop dynamic structure-based pharmacophores. These models were then used in the screening of large ligand libraries.

biophysics↗

bioRxiv2020

The neutralization effect of Montelukast on SARS-CoV-2 is shown by multiscale in silico simulations and combined in vitro studies

Small molecule inhibitors have previously been investigated in different studies as possible therapeutics in the treatment of SARS-CoV-2. In the current drug repurposing study, we identified the leukotriene (D4) receptor antagonist Montelukast as a novel agent that simultaneously targets two important drug targets of SARS-CoV-2. We initially demonstrated the dual inhibition profile of Montelukast through multiscale molecular modeling studies. Next, we characterized its effect on both targets by different in vitro experiments including the Fluorescent Resonance Energy Transfer (FRET)-based main protease enzyme inhibition assay, surface plasmon resonance (SPR) spectroscopy, pseudovirus neutralization on HEK293T / hACE2, and virus neutralization assay using xCELLigence MP real time cell analyzer. Our integrated in silico and in vitro results confirmed the dual potential effect of the Montelukast both on virus entry into the host cell (Spike/ACE2) and on the main protease enzyme inhibition. The virus neutralization assay results showed that while no cytotoxicity of the Montelukast was observed at 12 M concentration, the cell index time 50 (CIT50) value was delayed for 12 hours. Moreover, it was also shown that Favipiravir, a well-known antiviral used in COVID-19 therapy, should be used by 16-fold higher concentrations than Montelukast in order to have the same effect of Montelukast. The rapid use of new small molecules in the pandemic is very important today. Montelukast, whose pharmacokinetic and pharmacodynamic properties are very well characterized and has been widely used in the treatment of asthma since 1998, should urgently be completed in clinical phase studies and if its effect is proven in clinical phase studies, it should be used against COVID-19.

biophysics↗

bioRxiv2020

Near-Physiological-Temperature Serial Femtosecond X-ray Crystallography Reveals Novel Conformations of SARS-CoV-2 Main Protease Active Site for Improved Drug Repurposing

The COVID19 pandemic has resulted in 25+ million reported infections and nearly 850.000 deaths. Research to identify effective therapies for COVID19 includes: i) designing a vaccine as future protection; ii) structure-based drug design; and iii) identifying existing drugs to repurpose them as effective and immediate treatments. To assist in drug repurposing and design, we determined two apo structures of Severe Acute Respiratory Syndrome CoronaVirus-2 main protease at ambienttemperature by Serial Femtosecond X-ray crystallography. We employed detailed molecular simulations of selected known main protease inhibitors with the structures and compared binding modes and energies. The combined structural biology and molecular modeling studies not only reveal the dynamics of small molecules targeting main protease but will also provide invaluable opportunities for drug repurposing and structure-based drug design studies against SARS-CoV-2. One Sentence SummaryRadiation-damage-free high-resolution SARS-CoV-2 main protease SFX structures obtained at near-physiological-temperature offer invaluable information for immediate drug-repurposing studies for the treatment of COVID19.

biophysics↗