Biology subjects

ATILGAN, C.

Publications and source records attributed to ATILGAN, C..

9 recordsLinked to original sources

bioRxiv2026

Temporal Hydrogen-Bond Network Analysis Reveals Substrate-Directed Connectivity in Dihydrofolate Reductase

Hydrogen-bond networks are central to protein function, but most network analyses rely on static representations that neglect how interactions evolve in time. Here, we introduce a framework that combines instantaneous and temporal graph analysis of hydrogen-bond networks derived from molecular dynamics trajectories to quantify ligand-directed hydrogen-bond connectivity. We apply the method to E. coli dihydrofolate reductase (DHFR) and its L28R mutant, computing shortest hydrogen-bond paths from all residues to the substrate dihydrofolate (DHF). The instantaneous analysis reveals that DHF-directed connectivity is organized through a sparse set of preferred routes, with D27 and T113 acting as prominent hubs in the wild-type enzyme. Temporal analysis highlights residues that preferentially support time-ordered DHF-directed connectivity. Comparison with L28R shows that the mutation preserves the main substrate-contacting architecture and the overall communication scaffold but redistributes pathway usage, persistence, and temporal convergence. The network-derived hotspots partially overlap with independent coevolution signals, most strongly in the K109-I115 region, while overlap with cryptic-site predictors is more limited. This pattern indicates that the hydrogen-bond network captures evolutionarily supported communication regions in DHFR that are not fully recovered by static structural approaches. The framework is broadly applicable to ligand-binding proteins and provides a route to identify persistent, delayed, and mutation-sensitive signaling pathways directly from time-ordered simulation data.

biophysics↗

bioRxiv2025

A thermodynamic cycle to predict the competitive inhibition outcomes of an evolving enzyme

Understanding competitive inhibition at the molecular level is essential for unraveling the dynamics of enzyme-inhibitor interactions and predicting the evolutionary outcomes of resistance mutations. In this study, we present a framework linking competitive inhibition to alchemical free energy perturbation (FEP) calculations, focusing on E. coli dihydrofolate reductase (DHFR) and its inhibition by trimethoprim (TMP). Using thermodynamic cycles, we relate experimentally measured binding constants (Ki and Km) to free energy differences associated with wild-type and mutant forms of DHFR with a mean error of 0.9 kcal/mol, providing insights into the molecular underpinnings of TMP resistance. Our findings highlight the importance of local conformational dynamics in competitive inhibition. Mutations in DHFR affect substrate and inhibitor binding affinities differently, influencing the fitness landscape under selective pressure from TMP. Our FEP simulations reveal that resistance mutations stabilize inhibitor-bound or substrate-bound states through specific structural and/or dynamical effects. The interplay of these effects showcases significant epistasis in certain cases. The ability to separately assess substrate and inhibitor binding provides valuable insights, allowing for a more precise interpretation of mutation effects and epistatic interactions. Furthermore, we identify key challenges in FEP simulations, including convergence issues arising from charge-changing mutations and long-range allosteric effects. By integrating computational and experimental data, we provide an effective approach for predicting the functional impact of resistance mutations and their contributions to evolutionary fitness landscapes. These insights pave the way for constructing robust mutational scanning protocols and designing more effective therapeutic strategies against resistant bacterial strains.

biophysics↗

bioRxiv2025

Multiply Perturbed Response to Disclose Allosteric Control of Conformational Change: Application to Fluorescent Biosensor Design

Proteins exhibit remarkable conformational flexibility, enabling precise functional regulation through allostery. A key application of allostery is in the design of protein-based sensors, which detect environmental changes--such as ligand binding or post-translational modifications--and convert these cues into measurable signals (e.g., fluorescence). Here, we investigate a series of ligand-binding proteins that serve as sensing domains in direct-response fluorescent biosensors, wherein ligand binding enhances fluorescence output. We employ a multiple force application approach which we term Multiply Perturbed Response (MPR) to identify "hot spot" residues that drive the conformational transition from an apo (inactive/OFF) to a holo (active/ON) state. We first present two efficient computational approaches to determine residues and forces that maximize the overlap of the observed conformational change. We then determine the overlap maximizer residues for up to five force insertion locations, and we compare them with actual insertion sites used in existing biosensors. This work enhances the utility of linear response theory-based methods in uncovering multiple functionally significant regions that trigger a known conformational change. The approach might prove useful not only in the design of biosensors, or in locating allosteric sites, but may also find applications in offering physics-based collective variables in mapping conformational transition pathways of proteins.

biophysics↗

bioRxiv2024

High throughput mutational scanning of a protein via alchemistry on a high-performance computing resource

Antibiotic resistance presents a significant challenge to public health, as bacteria can develop resistance to antibiotics through random mutations during their life cycles, making the drugs ineffective. Understanding how these mutations contribute to drug resistance at the molecular level is crucial for designing new treatment approaches. Recent advancements in molecular biology tools have made it possible to conduct comprehensive analyses of protein mutations. Computational methods for assessing molecular fitness, such as binding energies, are not as precise as experimental techniques like deep mutational scanning. Although full atomistic alchemical free energy calculations offer the necessary precision, they are seldom used to assess high throughput data as they require significantly more computational resources. We generated a computational library using deep mutational scanning for dihydrofolate reductase (DHFR), a protein commonly studied in antibiotic resistance research. Due to resource limitations, we analyzed 33 out of 159 positions, identifying 16 single amino acid replacements. Calculations were conducted for DHFR in its drug-free state and in the presence of two different inhibitors. We demonstrate the feasibility of such calculations, made possible due to the enhancements in computational resources and their optimized use.

biophysics↗

bioRxiv2024

Ranking Single Fluorescent Protein Based Calcium Biosensor Performance by Molecular Dynamics Simulations

Genetically Encoded Fluorescent Biosensors (GEFBs) have become indispensable tools for visualizing biological processes in vivo. A typical GEFB is composed of a sensory domain (SD) which undergoes a conformational change upon ligand binding and a genetically fused fluorescent protein (FP). Ligand binding in the SD allosterically modulates the chromophore environment and changes its spectral properties. Single fluorescent (FP)-based biosensors, a subclass of GEFBs, offer a simple experimental setup; they are easy to produce in living cells, structurally stable and simple due to their single-wavelength operation. However, they pose a significant challenge for structure optimization, especially concerning the length and residue content of linkers between the FP and SD which affect how well the chromophore responds to conformational change in the SD. In this work, we use classical all-atom molecular dynamics simulations to analyze the dynamic properties of a series of calmodulin-based calcium biosensors, all with different FP-SD interaction interfaces and varying degrees of calcium binding dependent fluorescence change. Our results indicate that biosensor performance can be predicted based on distribution of water molecules around the chromophore and shifts in hydrogen bond occupancies between the ligand-bound and ligand-free sensor structures.

biophysics↗

bioRxiv2024

Deciphering GB1's Single Mutational Landscape: Insights from MuMi Analysis

Mutational changes that affect the binding of the C2 fragment of Streptococcal protein G (GB1) to the Fc domain of human IgG (IgG-Fc) have been extensively studied using deep mutational scanning (DMS), and the binding affinity of all single mutations has been measured experimentally in the literature. To investigate the underlying molecular basis, we perform in-silico mutational scanning for all possible single mutations, along with 2-{micro}s-long molecular dynamics (WT-MD) of the wild-type (WT) GB1 in both unbound and IgG-Fc bound forms. We compute the hydrogen bonds between GB1 and IgG-Fc in WT-MD to identify the dominant hydrogen bonds for binding, which we then assess in conformations produced by Mutation and Minimization (MuMi) to explain the fitness landscape of GB1 and IgG-Fc binding. Furthermore, we analyze MuMi and WT-MD to investigate the dynamics of binding, focusing on the relative solvent accessibility (RSA) of residues and the probability of residues being located at the binding interface. With these analyses, we explain the interactions between GB1 and IgG-Fc and display the structural features of binding. Our findings pave the way for improved predictive accuracy in protein stability and interaction studies, which are crucial for advancements in drug design and synthetic biology.

biophysics↗

bioRxiv2024

Elucidating TolC Protein Dynamics: Structural Shifts Facilitate Efflux Mediated β-lactam Resistance

Efflux-mediated {beta}-lactam resistance represents a significant public health challenge, limiting the efficacy of various {beta}-lactam antibiotics against numerous clinically relevant pathogenic bacteria. Structural and functional analyses have revealed that the efflux protein TolC in several Gram-negative bacteria serves as a conduit for antibiotics, bacteriocins, and phages, affecting bacterial susceptibility and virulence. In this study, we conducted a comprehensive examination of the efflux of {beta}-lactam drugs mediated by TolC, employing extensive experimental and computational analyses. Our computational investigations into the molecular dynamics of drug-free TolC revealed critical unidirectional movements of the trimeric TolC and identified residues significantly involved in TolC opening. To corroborate these findings, we performed a whole-gene-saturation mutagenesis assay, systematically mutating each residue of TolC to 19 other amino acids and measuring the fitness effects of these mutations under {beta}-lactam-induced selection. The {beta}-lactams oxacillin, piperacillin, and carbenicillin were selected for this study because they are effluxed by the AcrAB-TolC complex with varying efficiencies. This approach clarified the similarities and differences in the efflux processes of the three {beta}-lactam antibiotics through the trimeric TolC. Further analysis of TolCs efflux mechanism for these {beta}-lactam antibiotics via steered molecular dynamics simulations revealed the existence of general and drug-specific mechanisms employed by TolC. We identified key positions at the periplasmic entry of TolC whose altered dynamics influence long-range efflux motions as allosteric modulators. Our findings provide valuable insights into the structural dynamics of TolC, establishing a foundation for understanding the key mechanisms behind multidrug resistance and principles for designing new antibiotics and antibiotic derivatives capable of circumventing the bacterial efflux mechanism.

biophysics↗

bioRxiv2023

Allosteric Modulation of Fluorescence Revealed by Hydrogen Bond Dynamics in a Genetically Encoded Maltose Biosensor

Genetically encoded fluorescent biosensors (GEFBs) proved to be reliable tracers for many metabolites and cellular processes. In the simplest case, a fluorescent protein (FP) is genetically fused to a sensing protein which undergoes a conformational change upon ligand binding. This drives a rearrangement in the chromophore environment and changes the spectral properties of the FP. Structural determinants of successful biosensors are revealed only in hindsight when the crystal structures of both ligand-bound and ligand-free forms are available. This makes the development of new biosensors for desired analytes a long trial-and-error process. In the current study, we conducted {micro}s-long all atom molecular dynamics (MD) simulations of a maltose biosensor in both the apo (dark) and holo (bright) forms. We performed detailed hydrogen bond occupancy analyses to shed light on the mechanism of ligand induced conformational change in the sensor protein and its allosteric effect on the chromophore environment. We find that two strong indicators for distinguishing bright and dark states of biosensors are due to substantial changes in hydrogen bond dynamics in the system and solvent accessibility of the chromophore.

bioengineering↗

bioRxiv2020

N-terminus of the third PDZ Domain of PSD-95 Orchestrates Allosteric Communication for Selective Ligand Binding

PDZ domains constitute common models to study single domain allostery without significant structural changes. The third PDZ domain of PSD-95 (PDZ3) is known to have selective structural features that confer unique modulatory roles to this unit. In this model system two residues, H372 directly connected to the binding site and G330 holding an off-binding-site position, were designated to assess the effect of mutations on binding selectivity. It has been observed that the H372A and G330T/H372A mutations change ligand preferences from class I (T/S amino acid at position -2 of the ligand) to class II (hydrophobic amino acid at the same position). Alternatively, the G330T single mutation leads to the recognition of both ligand classes. We have performed a series of molecular dynamics (MD) simulations for wild-type, H372A, G330T single mutants and a double mutant of PDZ3 in the absence and presence of both types of ligands. With the combination of free energy difference calculations and a detailed analysis of MD trajectories, class switching and class bridging behavior of PDZ3 mutants, as well as their effects on ligand selection and binding affinities are explained. We show that the dynamics of the charged N-terminus plays a fundamental role in determining the binding preferences in PDZ3 by altering the electrostatic energy. These findings are corroborated by simulations on N-termini truncated versions of these systems. The dynamical allostery orchestrated by the N-terminus offers a fresh perspective to the study of communication pathways in proteins.

biophysics↗