Biology subjects

Ozkan, S. B.

Publications and source records attributed to Ozkan, S. B..

11 recordsLinked to original sources

bioRxiv2026

SMartini: automated small molecule parametrization for Martini 3 force field

We present SMartini, an automated pipeline for deriving Martini 3 coarse-grained force-field parameters for arbitrary small molecules. Starting from a molecular structure or a SMILES string, the pipeline maps the all-atom molecule onto a coarse-grained bead representation and automatically fits both bonded and non-bonded parameters. Bonded parameters are obtained via Boltzmann inversion of atomistic molecular dynamics trajectories; successive rounds of coarse-grained simulation and distribution-matching updates then refine these estimates until the coarse-grained conformational ensemble reproduces the all-atom reference within tolerance. We validate the pipeline on a diverse set of small molecules including drug-like compounds, metabolites, and cofactors. Implemented as a modular sequence of scripts that can be orchestrated on high-performance computing clusters, SMartini makes automated parametrization of large ligand libraries practical and reduces the manual effort required for coarse-grained model development, enabling high-throughput coarse-grained simulations of protein--ligand systems within the Martini 3 ecosystem

biophysics↗

bioRxiv2026

Entanglement-based continuum conformational landscape of proteins

MotivationWith the rapid development of AI methods that predict protein structures from sequence, understanding the structure-function relation increasingly depends on quantitative structural descriptors that are both biologically meaningful and scalable to large datasets. Here, we introduce mathematical topology metrics that quantify the entanglement complexity of a tertiary protein structure while respecting uncrossability constraints. ResultsBy employing only three such metrics across all protein structures in the Protein Data Bank, we represent the proteome structural space in a continuous three-dimensional space. Distances within this space capture structural similarity and correlate with functional similarity. We find that the mathematical entanglement based landscape of protein structural space diversifies with the evolutionary expansion of protein function across species. Moreover, this continuous representation reproduces CATH classifications with high accuracy for major structural classes. These results indicate that these metrics efficiently encode structural features linked to protein function and provide a more informative description than conventional metrics. AvailabilityData used in this study are available in the Protein Data Bank. Details of the machine learning model used can be found in https://github.com/roshitac/CATH_Classification-. ContactBanu.Ozkan@asu.edu, Eleni.Panagiotou@asu.edu Supplementary informationSupplementary data are available at Journal Name online.

molecular biology↗

bioRxiv2025

Long-range coupling regulates stator dynamics in the bacterial flagellar motor

The bacterial flagellar motor generates torque through MotAB stator complexes which couple ion flux to rotation. Stators anchor in the peptidoglycan cell wall and dynamically remodel in response to changes in external conditions such as the mechanical load, yet how stator anchoring is regulated remains unknown. Here, we show that long-range allosteric interactions within the MotB periplasmic domain tune stator binding in Escherichia coli. Using coarse-grained elastic-network modeling and co-evolutionary analyses, we identified residues mechanically coupled to peptidoglycan-interacting loops of MotB. Targeted mutagenesis at these coupled sites produced distinct motility phenotypes in some mutants, exhibiting altered swimming speeds compared to wild-type and characteristic expression-dependent swimming trends, indicating mutation-specific effects on stator dynamics or torque. Single-motor measurements distinguished mutants with altered torque from those with altered stator dynamics. Molecular dynamics simulations revealed that mutations at distal positions reshape loop flexibility in ways that quantitatively correlate with swimming speeds. These results demonstrate that allosteric communication within MotB propagates across length scales to modulate the performance of the entire motor, revealing how local molecular changes can tune large-scale bacterial motion.

biophysics↗

bioRxiv2025

Coarse-Grained RNA Model for the Martini 3 Force Field

In this work we developed a coarse-grained model for RNA that is compatible with the Martini 3 force field. The model is parameterized following the Martini philosophy combining the top-down and bottom-up approaches. The nonbonded interactions in the model are derived from the partitioning of nucleobases between polar and nonpolar solvents, along with calculations of the potential of mean force between bases. For bonded interactions, parameters were refined based on atomistic simulations of double-stranded RNA. Additionally, an elastic network was incorporated to maintain the structural integrity of complex RNA molecules, such as transfer RNA, and other specific RNA configurations. We present the implementation of the Martini 3 RNA model and demonstrate its ability to capture the properties of individual bases, single-stranded RNA, double-stranded RNA, and RNA-protein complexes. Compared to the Martini 2 version, the current model offers several key advantages. It is fully compatible with the updated Martini 3 force field, exhibits greater numerical stability--allowing for the successful simulation of larger RNA-protein complexes, such as ribosomes, using the standard Martini timestep of 20 fs, and it demonstrates improved agreement with all-atom models and experimental data. This new RNA model enables realistic large-scale explicit-solvent molecular dynamics simulations of complex RNA-containing systems. SignificanceThis research introduces a new coarse-grained model for explicit water MD simulations of RNA compatible with Martini 3 software. The model demonstrates improved agreement with both all-atom simulations and experimental data, enabling more accurate and computationally efficient simulations of large RNA-protein complexes. This advancement facilitates the study of RNA and RNA-protein interactions, allowing for the modeling of larger biological complexes and paving the way for more efficient simulations of RNA systems across various fields, including therapeutics, molecular biology, and synthetic biology, where understanding RNA interactions is crucial for developing biomedical applications and advancing fundamental research.

biophysics↗

bioRxiv2023

Some mechanistic underpinnings of molecular adaptations of SARS-COV-2 spike protein by integrating candidate adaptive polymorphisms with protein dynamics

We integrate evolutionary predictions based on the neutral theory of molecular evolution with protein dynamics to generate mechanistic insight into the molecular adaptations of the SARS-COV-2 Spike (S) protein. With this approach, we first identified Candidate Adaptive Polymorphisms (CAPs) of the SARS-CoV-2 Spike protein and assessed the impact of these CAPs through dynamics analysis. Not only have we found that CAPs frequently overlap with well-known functional sites, but also, using several different dynamics-based metrics, we reveal the critical allosteric interplay between SARS-CoV-2 CAPs and the S protein binding sites with the human ACE2 (hACE2) protein. CAPs interact far differently with the hACE2 binding site residues in the open conformation of the S protein compared to the closed form. In particular, the CAP sites control the dynamics of binding residues in the open state, suggesting an allosteric control of hACE2 binding. We also explored the characteristic mutations of different SARS-CoV-2 strains to find dynamic hallmarks and potential effects of future mutations. Our analyses reveal that Delta strain-specific variants have non-additive (i.e., epistatic) interactions with CAP sites, whereas the less pathogenic Omicron strains have mostly additive mutations. Finally, our dynamics-based analysis suggests that the novel mutations observed in the Omicron strain epistatically interact with the CAP sites to help escape antibody binding.

biophysics↗

bioRxiv2023

RNA-induced allosteric coupling drives viral capsid assembly in bacteriophage MS2

Understanding the mechanisms by which single-stranded RNA viruses regulate capsid assembly around their RNA genomes has become increasingly important for the development of both antiviral treatments and drug delivery systems. Here, we investigate the effects of RNA-induced allostery in a single-stranded RNA virus -- Levivirus bacteriophage MS2 -- using the computational methods of the Dynamic Flexibility Index (DFI) and the Dynamic Coupling Index (DCI). We show that asymmetric binding of RNA to a symmetric MS2 coat protein dimer increases the flexibility of the distant FG-loop and induces a conformational change to an asymmetric dimer that is essential for proper capsid formation. We also show that a point mutation W82R in the FG-loop creates an assembly-deficient dimer in which RNA-binding has no significant effect on FG-loop flexibility. Lastly, we show that the highly flexible disordered FG-loop of the RNA bound asymmetric dimer not only becomes the controller of the rigid FG-loop but enhances its dynamic coupling with all the distal positions in the dimer. This strong dynamic coupling allows highly regulated communication and unidirectional signal transduction that drives the formation of the experimentally observed capsid intermediates. Author summaryThe final stage of an RNA virus life cycle is the assembly of a protein shell encapsulating the viral genome prior to release from the host organism. Despite rapid advancements in both experimental and theoretical biology since the mid-20th century, little is still known about the underlying mechanisms of viral capsid assembly. However, understanding the biophysical principles of viral capsid assembly would bring us one step closer to developing new biotechnologies such as antivirals that inhibit this critical stage of the life cycle or artificial capsids for targeted drug/vaccine delivery. Although we limit the present study to one simple RNA virus that infects bacteria, we propose that the physical implications can extend to other RNA viruses including the human coronavirus SARS-CoV-2. We also propose that the allosteric regulation by specific protein-RNA interactions might be a general mechanism exploited by many other ribonucleoprotein complexes, such as CRISPR-Cas9, spliceosome or ribosome.

biophysics↗

bioRxiv2021

Dynamic Allostery Highlights the Evolutionary Differences between the CoV-1 and CoV-2 Main Proteases

The SARS-CoV-2 coronavirus has become one of the most immediate and widely-studied systems since its identification and subsequent global outbreak from 2019-2020. In an effort to understand the biophysical changes as a result of mutations, the mechanics of multiple different proteins within the SARS-CoV-2 virus have been studied and compared with SARS-CoV-1. Focusing on the main protease (mPro), we first explored the long range dynamic-relationship, particularly in cross-chain dynamics, using the Dynamic Coupling Index (DCI) to investigate the dynamic coupling between the catalytic site residues and the rest of the protein, both inter and intra chain for the CoV-1 and CoV-2 mPro. We found that there is significant cross-chain coupling between these active sites and distal residues in the CoV-2 mPro but it was missing in CoV-1. The enhanced long distance interactions, particularly between the two chains, suggest subsequently enhanced cooperativity for CoV-2. A further comparative analysis of the dynamic flexibility using the Dynamic Flexibility Index (DFI) between the CoV-1 and CoV-2 mPros shows that the inhibitor binding near active sites induces change in flexibility to a distal region of the protein, opposite in behavior between the two systems; this region becomes more flexible upon inhibitor binding in CoV-1 while it becomes less flexible in the CoV-2 mPro. Upon inspection, we show that, on average, the dynamic flexibility of the sites substituted from CoV-1 to CoV-2 changes significantly less than the average calculated across all residues within the structure, indicating that the differences in behaviors between the two systems is likely the result of allosteric influence, where the new substitutions in COV-2 induce flexibility and dynamical changes elsewhere in the structure. SIGNIFICANCEHere we have conducted a comparative analysis between the SARS-CoV-1 and SARS-CoV-2 mPro systems to shed mechanistic insight on the biophysical changes associated with the mutations between these two enzymes. Our work shows that the CoV-2 mPro system exhibits enhanced cross-chain communication between catalytic site residues and the rest of the structure. Further, both dynamic coupling and dynamic flexibility analyses indicates that, largely, the dynamic changes as evaluated by DCI and DFI occur at sites other than the mutation sites themselves, indicating that the functional differences between these two proteins are a result of dynamic allostery

biophysics↗

bioRxiv2021

Dynamic coupling of residues within proteins as a mechanistic foundation of many enigmatic pathogenic missense variants

Many pathogenic missense mutations are found in protein positions that are neither well-conserved nor belong to any known functional domains. Consequently, we lack any mechanistic underpinning of dysfunction caused by such mutations. We explored the disruption of allosteric dynamic coupling between these positions and the known functional sites as a possible mechanism for such mutations. In this study, we present an analysis of 144 human enzymes containing 591 pathogenic missense variants, in which allosteric dynamic coupling of mutated positions with known active sites provides insights into a primary biophysical mechanism and evidence of their functional importance. We illustrate this mechanism in a case study of {beta}-Glucocerebrosidase (GCase), which contains 94 Gaucher disease-associated missense variants located some distance away from the active site. An analysis of the conformational dynamics of GCase suggests that mutations on these distal sites cause changes in the flexibility of active site residues despite their distance, indicating a dynamic communication network throughout the protein. The disruption of the long-distance dynamic coupling due to the presence of missense mutations may provide a plausible general mechanistic explanation for biological dysfunction and disease. Author SummaryGenetic diseases occur when mutations to a particular gene cause a gain/loss in function of the related protein. Although several methods based on conservation and protein biochemistry exist to predict which genetic mutations may impact function, many disease causing changes remain unexplained by these metrics. In this study, we propose an explanation for these genetic changes may cause disease. In order to function, important regions of a protein must be able to exhibit collective motion. Through computer simulations, we observed that changing even a single amino acid within a protein can change the protein motion. Notably, disease causing genetic changes tend to alter the motion of regions which are critically important to protein function, even the mutations are far from these critical regions. In addition, we examined the degree that two amino acids within a protein may "couple" to one another, meaning the degree to which motion in one amino acid will affect the other. We found that amino acids which are highly coupled to the active site of a protein are more likely to result in disease if mutated, thereby offering a new tool for predicting genetic disease which incorporates internal protein dynamics.

biophysics↗

bioRxiv2020

Design of novel CV-N variants: Modulation of binding dynamics through distal mutations

We develop integrated coevolution and dynamic coupling (ICDC) approach to identify, mutate, and assess distal sites to modulate function. We validate the approach first by analyzing the existing mutational fitness data of TEM-1 {beta}-lactamase and show that allosteric positions co-evolved and dynamically coupled with the active site significantly modulate function. We further apply ICDC approach to identify positions and their mutations that can modulate binding affinity in a lectin, Cyanovirin-N (CV-N), that selectively binds to dimannose, and predict binding energies of its variants through Adaptive BP-Dock. Computational and experimental analyses reveal that binding enhancing mutants identified by ICDC impact the dynamics of the binding pocket, and show that rigidification of the binding residues compensates for the entropic cost of binding. This work suggests a general mechanism by which distal mutations modulate function through dynamic allostery and provides a blueprint to identify candidates for mutagenesis in order to optimize protein function.

biophysics↗

bioRxiv2020

Substitutions at Non-Conserved Rheostat Positions Modulate Function by Re-Wiring Long-Range, Dynamic Interactions

Amino acid substitutions at nonconserved protein positions can have non-canonical and “long-distance” outcomes on protein function. Such outcomes might arise from changes in the internal protein communication network, which is often accompanied by changes in structural flexibility. To test this, we calculated flexibilities (“DFI”) and dynamic coupling (“DCI”) for positions in the linker region of the lactose repressor protein (“LacI”). This region contains nonconserved positions for which substitutions alter DNA binding affinity. We first chose to study eleven substitutions at position 52. In computations, substitutions showed long-range effects on flexibilities of DNA binding positions, and the degree of flexibility change correlated with experimentally-measured changes in DNA binding. Substitutions also altered dynamic coupling to DNA binding positions in a manner that captured other experimentally-determined functional changes. Next, we broadened calculations to consider the dynamic coupling between 17 linker positions and the DNA binding domain. Experimentally, these linker positions exhibited a wide range of substitution outcomes: Four conserved positions tolerated almost no substitutions (“toggle”), ten nonconserved positions showed progressive changes from a range of substitutions (“rheostat”), and three nonconserved positions tolerated almost all substitutions (“neutral”). In computations with wild-type LacI, the dynamic couplings between the DNA binding domain and these linker positions showed varied degrees of asymmetry that correlated with the observed toggle/rheostat/neutral substitution outcomes. Thus, we propose that long-range and non-canonical substitutions outcomes at nonconserved positions arise from re-wiring long-range communication among functionally-important positions. Such calculations might enable predictions for substitution outcomes at a range of nonconserved positions.Competing Interest StatementThe authors have declared no competing interest.View Full Text

biophysics↗

bioRxiv2018

Ancient Thioredoxins Evolved to Modern Day Stability-Function Requirement by Altering Native State Ensemble

Thioredoxins (Thrxs) - small globular proteins that reduce other proteins - are ubiquitous in all forms of life, from archaea to mammals. Although ancestral Thioredoxins share sequential and structural similarity with the modern day (extant) homologs, they exhibit significantly different functional activity and stability. We investigate this puzzle by comparative studies of their (ancient and modern day Thrxs) native state ensemble, as quantified by the Dynamic Flexibility Index (DFI), a metric for the relative resilience of an amino acid to perturbations in the rest of the protein. Clustering proteins using DFI profiles strongly resembles an alternate classification scheme based on their activity and stability. The DFI profiles of the extant proteins are substantially different around the 3, 4 helices and catalytic regions. Likewise, allosteric coupling of the active site with the rest of the protein is different between ancient and extant Thrxs, possibly explaining the decreased catalytic activity at low pH with evolution. At a global level, we note that the population of low flexibility (called hinges) and high flexibility sites increases with evolution. The heterogeneity (quantified by the variance) in DFI distribution increases with the decrease in the melting temperature typically associated with the evolution of ancient proteins to their modern-day counterparts.

biophysics↗