Biology subjects

Cournia, Z.

Publications and source records attributed to Cournia, Z..

7 recordsLinked to original sources

bioRxiv2025

Mapping the free energy landscape of K-Ras4B dimerization

KRAS-4B regulates cellular proliferation and differentiation via its GTPase activity, and it is often mutated in human tumors. Deregulation of the MAPK/ERK pathway as a result of K-Ras4B mutations leads to uncontrolled proliferation, with the dimer/multimerization of K-Ras4B on the plasma membrane believed to be the initiating event for subsequent MAPK/ERK signaling. While K-Ras4B proteins are known to cluster on the plasma membrane, whether they associate through well-defined dimerization interfaces remains an open question. Here, we present the dimerization landscape of active, GTP-bound wild-type and G12D mutant K-Ras4B using coarse-grained unbiased and enhanced sampling molecular dynamics simulations. We recover the experimentally-reported K-Ras4B interfaces, and additionally unveil rugged free energy landscapes with many-yet uncharacterized-minima that feature c-Raf-mediated dimerization interfaces. We further explore whether wild-type or G12D K-Ras4B present different dimerization states, revealing that the G12D mutant is more likely to form diverse dimers compared to WT K-Ras4B. Our work presents evidence that K-Ras4B proteins likely interact through multifaceted interfaces that may enable controlled dimerization in different conformations from a single system, efficiently promoting nanoclustering. Although many weak, non-specific interfaces are forming, the most dominant interfaces occur with nanomolar affinity, offering a structural basis for the design of ligands able to modulate K-Ras4B dimers.

biophysics↗

bioRxiv2024

Comparison of Methodologies for Absolute Binding Free Energy Calculations of Ligands to Intrinsically Disordered Proteins

Modulating the function of Intrinsically Disordered Proteins (IDPs) with small molecules is of considerable importance given the crucial roles of IDPs in the patho-physiology of numerous diseases. Reported binding affinities for ligands to diverse IDPs vary broadly and little is known about the detailed molecular mechanisms that underpin ligand efficacy. Molecular simulations of IDP-ligand binding mechanisms can help us understand the mode of action of small molecule inhibitors of IDP function, but it is still unclear how binding energies can be modeled rigorously for such a flexible class of proteins. Here we compare alchemical absolute binding free energy calculation (ABFE) and Markov-State Modelling (MSM) protocols to model the binding of the small molecule 10058-F4 to a disordered peptide extracted from a segment of the oncoprotein c-Myc. The ABFE results produce binding energy estimates that are sensitive to the choice of reference structure. In contrast, the MSM results produce more reproducible binding energy estimates consistent with weak mM binding affinities and transient intermolecular contacts reported in the literature.

biophysics↗

bioRxiv2024

Computational investigation of BMAA and its carbamate adducts as potential GluR2 modulators

Beta-N-methylamino-L-alanine (BMAA) is a potential neurotoxic non-protein amino acid, which can reach the human body through the food chain. When BMAA interacts with bicarbonate in the human body, carbamate adducts are produced, which share high structural similarity with the neurotransmitter glutamate. It is believed that BMAA and its L-carbamate adducts bind in the glutamate binding site of ionotropic glutamate receptor 2 (GluR2). Chronic exposure to BMAA and its adducts could cause neurological illness such as neurodegenerative diseases. However, the mechanism of BMAA action and its carbamate adducts bound to GluR2 has not been yet elucidated. Here, we investigate the binding modes and the affinity of BMAA and its carbamate adducts to GluR2 in comparison to the natural agonist, glutamate, to understand whether these can act as GluR2 agonists. Initially, we perform Molecular Dynamics (MD) simulations of BMAA and its carbamate adducts bound to GluR2 to examine the stability of the ligands in the S1/S2 ligand-binding domain of the receptor. In addition, we perform alchemical free energy calculations to compute the difference in the free energy of binding of the beta-carbamate adduct of BMAA to GluR2 compared to glutamate. Our findings indicate that carbamate adducts of BMAA and glutamate remain stable in the binding site of the GluR2 compared to BMAA. Additionally, alchemical free energy results reveal that glutamate and the beta-carbamate adduct of BMAA have comparable binding affinity in the GluR2. These results provide a rationale that BMAA carbamate adducts may be in fact the modulators of GluR2 and not BMAA itself.

pharmacology and toxicology↗

bioRxiv2022

Evaluation of K-Ras4B dimer interfaces and the role of Raf effectors

K-Ras4B is one the most frequently mutated proteins in cancer, yet mechanistic details of its activation such as its homodimerization on the membrane remain elusive. The structural determinants of K-Ras4B homodimerization have been debated with different conformations being proposed in the literature. Here, we perform microsecond all-atom Molecular Dynamics (MD) simulations on the K-Ras4B monomer in solution, the K-Ras4B monomer on the membrane, and two experimentally-based K-Ras4B dimer models of the 4-5 interface to investigate the stability of these structures bound to GTP on a model cell membrane. We then evaluate the complexes for their propensity to form stable dimers on the plasma membrane in the presence and absence of Raf[RBD-CRD] effectors. We find that Raf[RBD-CRD] effectors enhance dimer stability, suggesting that the presence of effectors is necessary for K-Ras4B dimers stabilization on the cell membrane. Moreover, we observe, for the first time, a dynamic water channel at the K-Ras4B dimer interface, and identify putative allosteric connections in the K-Ras4B dimer interface. To discover novel K-Ras4B interfaces, we perform coarse-grained MD simulations in two dissociated K-Ras4B monomers on the membrane, which reveal that the dominant dimer interface is the 4-5 interface. Finally, a druggability analysis is performed in the different K-Ras4B structures in the monomeric states. Strikingly, all known binding pockets of K-Ras4B are identified only in the structure that is membrane-bound, but not in the solution structure. Based on these results, we propose that modulating the protein-membrane interactions can be an alternative strategy for inhibiting K-Ras4B signaling.

molecular biology↗

bioRxiv2021

Predicting protein-membrane interfaces of peripheral membrane proteins using ensemble machine learning

Abnormal protein-membrane attachment is involved in deregulated cellular pathways and in disease. Therefore, the possibility to modulate protein-membrane interactions represents a new promising therapeutic strategy for peripheral membrane proteins that have been considered so far undruggable. A major obstacle in this drug design strategy is that the membrane binding domains of peripheral membrane proteins are usually not known. The development of fast and efficient algorithms predicting the protein-membrane interface would shed light into the accessibility of membrane-protein interfaces by drug-like molecules. Herein, we describe an ensemble machine learning methodology and algorithm for predicting membrane-penetrating amino acids. We utilize available experimental data in the literature for training 21 machine learning classifiers and a voting classifier. Evaluation of the ensemble classifier accuracy produced a macro-averaged F1 score = 0.92 and an MCC = 0.84 for predicting correctly membrane-penetrating amino acids on unknown proteins of an independent test set. The python code for predicting protein-membrane interfaces of peripheral membrane proteins is available at https://github.com/zoecournia/DREAMM.

bioinformatics↗

bioRxiv2019

The SAMPL6 SAMPLing challenge: Assessing the reliability and efficiency of binding free energy calculations

Approaches for computing small molecule binding free energies based on molecular simulations are now regularly being employed by academic and industry practitioners to study receptor-ligand systems and prioritize the synthesis of small molecules for ligand design. Given the variety of methods and implementations available, it is natural to ask how the convergence rates and final predictions of these methods compare. In this study, we describe the concept and results for the SAMPL6 SAMPLing challenge, the first challenge from the SAMPL series focusing on the assessment of convergence properties and reproducibility of binding free energy methodologies. We provided parameter files, partial charges, and multiple initial geometries for two octa-acid (OA) and one cucurbit[8]uril (CB8) host-guest systems. Participants submitted binding free energy predictions as a function of the number of force and energy evaluations for seven different alchemical and physical-pathway (i.e., potential of mean force and weighted ensemble of trajectories) methodologies implemented with the GROMACS, AMBER, NAMD, or OpenMM simulation engines. To rank the methods, we developed an efficiency statistic based on bias and variance of the free energy estimates. For the two small OA binders, the free energy estimates computed with alchemical and potential of mean force approaches show relatively similar variance and bias as a function of the number of energy/force evaluations, with the attach-pull-release (APR), GROMACS expanded ensemble, and NAMD double decoupling submissions obtaining the greatest efficiency. The differences between the methods increase when analyzing the CB8-quinine system, where both the guest size and correlation times for system dynamics are greater. For this system, nonequilibrium switching (GROMACS/NS-DS/SB) obtained the overall highest efficiency. Surprisingly, the results suggest that specifying force field parameters and partial charges is insufficient to generally ensure reproducibility, and we observe differences between seemingly converged predictions ranging approximately from 0.3 to 1.0 kcal/mol, even with almost identical simulations parameters and system setup (e.g., Lennard-Jones cutoff, ionic composition). Further work will be required to completely identify the exact source of these discrepancies. Among the conclusions emerging from the data, we found that Hamiltonian replica exchange--while displaying very small variance--can be affected by a slowly-decaying bias that depends on the initial population of the replicas, that bidirectional estimators are significantly more efficient than unidirectional estimators for nonequilibrium free energy calculations for systems considered, and that the Berendsen barostat introduces non-negligible artifacts in expanded ensemble simulations.

biophysics↗

bioRxiv2018

Effect of 5-trans isomer of arachidonic acid on model liposomal membranes studied by a combined simulation and experimental approach

Unsaturated fatty acids are found in humans predominantly in the cis configuration. Fatty acids in the trans configuration are primarily the result of human processing (trans fats), but can also be formed endogenously by radical stress. The cis-trans isomerization of fatty acids by free radicals could be connected to several pathologies. Trans fats have been linked to an increased risk of coronary artery disease; however, the reasons for the resulting pathogenesis remain unclear. Here, we investigate the effect of a mono trans isomer of arachidonic acid (C20:4-5trans,8cis,11cis,14cis) produced by free radicals in physiological concentration on a model erythrocyte membrane using a combined experimental and theoretical approach. Molecular Dynamics (MD) simulations of two model lipid bilayers containing arachidonic acid and its 5-trans isomer in 3% mol. were carried out for this purpose. The 5-trans isomer formation in the phospholipids was catalyzed by HOCH2CH2S* radicals, generated from the corresponding thiol by {gamma}-irradiation, in multilamellar vesicles (MLVs) of SAPC. Large unilamellar vesicles were made by the extrusion method (LUVET) as a biomimetic model for cis-trans isomerization. Atomic Force Microscopy and Dynamic Light Scattering were used to measure the average size, morphology, and the z-potential of the liposomes. Both results from MD simulations and experiments are in agreement and indicate that the two model membranes display different physicochemical properties in that the bilayers containing the trans fatty acids were more ordered and more rigid than those containing solely the cis arachidonic acid. Correspondingly, the average size of the liposomes containing trans isomers was smaller than the ones without.

biophysics↗