Biology subjects

Erol, I.

Publications and source records attributed to Erol, I..

4 recordsLinked to original sources

bioRxiv2025

Targeting Ubiquitin-Specific Protease 7 (USP7): A Pharmacophore-Guided Drug Repurposing and Physics-Based Molecular Simulations Study

Ubiquitin-Specific Protease 7 (USP7) has emerged as a critical therapeutic target in cancer due to its regulatory roles of tumor suppressors, oncoproteins, and epigenetic modifiers. In this study, we present a comprehensive drug repurposing strategy to identify potential USP7 inhibitors from a curated library of 6,654 FDA-approved and investigational small molecules. Using structure-based pharmacophore models derived from USP7-inhibitor crystal structures, we conducted virtual screening to select candidates with favorable pharmacophoric alignment. The top 100 hits were subjected to short 10 ns molecular dynamics (MD) simulations and MM/GBSA binding energy calculations, narrowing down to 36 promising ligands. These were further evaluated through longer (100 ns) MD simulations, binding energy refinement, ligand clustering based on molecular fingerprints, and cancer-specific activity predictions using a binary QSAR model. Twelve compounds demonstrated favorable binding profiles, structural diversity, and high predicted anticancer activity, such as xantifibrate, etofylline clofibrate, and carafiban. This multi-tiered hybrid virtual screening pipeline highlights the potential of drug repurposing for the rapid identification of USP7 inhibitors, offering a cost-effective path toward novel anticancer therapeutics.

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↗

bioRxiv2021

Receptor-wide Determinants of G Protein Coupling Selectivity in Aminergic GPCRs

G protein-coupled receptors (GPCRs) induce signal transduction pathways through coupling to four main subtypes of G proteins (Gs, Gi, Gq, G12/13), selectively. However, G protein selective activation mechanisms and residual determinants in GPCRs have remained obscure. Herein, we performed an extensive phylogenetic analysis and identified specifically conserved residues for the receptors having similar coupling profiles in each aminergic receptor. By integrating our methodology of differential evolutionary conservation of G protein-specific amino acids with structural analyses, we identified selective activation networks for Gs, Gi1, Go, and Gq. To validate that these networks could determine coupling selectivity we further analyzed Gs specific activation network and associated it with the larger TM6 tilt which is a signature of Gs-coupled receptors. Through molecular dynamics simulations, we showed that previously uncharacterized Glycine at position 7x41 plays an important role in both receptor activation and Gs coupling selectivity by inducing a larger TM6 movement. Finally, we gathered our results into a comprehensive model of G protein selectivity called "sequential switches of activation" describing three main molecular switches controlling GPCR activation: ligand binding, G protein selective activation mechanisms and G protein contact.

evolutionary biology↗

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↗