The Journal of Physical Chemistry B

Invertebrate vision relies on bistable visual pigments flipping upon photon absorption between rhodopsin and metarhodopsin states. In living butterflies, the UV-VIS absorption spectra of rhodopsin and metarhodopsin, respectively with 11-cis and all-trans isomers of 3-hydroxy-retinal (A3) chromophore, can be conveniently recorded from the eyeshine, the light reflected from the compound eye after passing twice through the light-guiding rhabdoms. * Here, a microscope coupled with a broadband LED source and a microspectrometer was used to record photorelaxations reported in eyeshine reflection spectra. Fitting temporal exponential relaxations to log-reflectance arrays yielded transient and baseline spectra that are analogous to absorbance difference and sum, respectively. Both types of spectra were subjected to singular value decomposition and to fitting of templated visual pigment absorption spectra. * The compound eye of the high brown fritillary Fabriciana adippe was exposed to a series of second-long broadband light pulses, causing photorelaxations with time constants between 40 and 120 ms that led to 80% metarhodopsin in equilibrium. The transient and baseline spectra were fitted with pigment templates, estimating the alpha peak wavelength 547-552 nm for rhodopsin and 496-501 nm for metarhodopsin. The metarhodopsin to rhodopsin alpha peak absorbance ratio 1.25-1.35 is consistent with the isosbestic wavelength at 530 nm. The second isosbestic wavelength indicates that rhodopsin beta (UV) peak absorbs more strongly than metarhodopsin below 405 nm. * Baseline spectra, which were not explicitly analysed in previous studies, enable concatenation of exposures, monitor long-term changes of pigment, and enhance the estimation of beta peak parameters. * The method can be directly used in many butterflies and could be adapted to other insects, particularly fruitflies, facilitating studies of the relation between the visual pigment spectra and the opsin sequences. Spectroscopic results can be complemented with physiologically measured photoreceptor spectral sensitivity datasets and analysed with the same global fitting procedure.

The molten globule (MG) state is an intermediate in the unfolding pathway of proteins, typically triggered by denaturing agents such as urea, extreme pH, high pressure, or heat. The microscopic details of such states are far from understood. Here we study the MG states in protein Hen Egg-White Lysozyme (PDB ID: 1AKI) using microscopic constant pH molecular dynamics (CpHMD) simulations and experiments across a wide pH range. We observe that the titratable residues act as key drivers of conformational fluctuations, promoting the emergence of MG states at extreme pH. These states display partial unfolding, and small global structural changes (< 7% deviation). Hydration around the fluctuating acidic residues shows reduced water density and weakened hydrogen bonding at low pH. At high pH, hydration around acidic residues increases relative to pH = 7, whereas hydration around basic residues decreases. The translational and rotational dynamics of hydration water also exhibit pronounced pH dependence: the translational diffusion coefficient (Dtrans) increases linearly with decrease in pH in acidic medium and increases linearly with increasing pH in the basic regime. The rotational diffusion (Drot) shows similar dependencies on pH except a break at pH {approx} 4 corresponding to acidic residue pKa values. Our results may be useful to identify ligand binding of lysozyme in extreme pH conditions.

Intrinsic tryptophan fluorescence is widely used as a sensitive reporter of protein conformational dynamics, yet the molecular origin of its temperature-dependent modulation remains unclear. Here we investigate the conformational dynamics of Trp134 in bovine serum albumin (BSA) using molecular dynamics (MD) simulations, free-energy calculations based on umbrella sampling and WHAM, quantum mechanical (QM) calculations, and QM/MM approaches. MD simulations show that the global structure of BSA remains stable while temperature induces a gradual population shift from the Ia+ to the Ia- rotamer. The corresponding free-energy landscapes reveal that this shift arises from subtle changes in basin stability and transition barriers along the rotameric coordinate. In contrast, standalone QM calculations on isolated tryptophan predict different energetic trends, highlighting the sensitivity of rotamer stability to electronic-structure treatments and environmental effects. QM/MM calculations partially reconcile these differences by incorporating the protein environment. Together, these results suggest that temperature reshapes the rotamer free-energy landscape of Trp134, leading to population shifts that modulate intrinsic tryptophan fluorescence in proteins.

Proteins in solution adsorb to the corona of nanoparticles such as single-walled carbon nanotubes (SWCNTs), but these interactions are difficult to predict and analyze due to ambiguities in the structure of the latter. In this work, we employ ss(GT)15-DNA wrapped SWCNTs, a commonly used fluorescent sensor construct, to examine protein adsorption by quantifying binding dissociation constants and characterizing the corresponding photophysical effects. A library of 20 proteins are used to evaluate adsorption-induced changes in photoluminescence (PL) intensity ({Delta}I/I0) and emission wavelength upon solution phase binding. We find that 15 proteins produce monotonic dose-response behavior well described using a single-site Langmuir model. Alternatively, five proteins exhibited more complex, non-monotonic behavior consistent with a two-step binding model representing protein-protein interactions coupled to adsorption. The study reveals that metalloproteins, which comprised 12 of the 20 proteins in the library, induced greater PL quenching compared with metal-free proteins for this system, with maximum binding-associated quenching ({Delta}I/I0) of 94% for metalloproteins versus 20% for metal-free proteins. For metalloproteins, we introduce a proximity-based quenching framework in which protein size provides a coarse proxy for cofactor-SWCNT separation, offering a mechanistic interpretation of the observed quenching variation across proteins. Together, these results establish the use of metal coordination sites, such as those in metalloproteins, to assist the transduction of certain nanoparticle fluorescent sensors, helping with sensor probe design and interpretation in biological environments.

The repair of photo-induced DNA lesions through nucleotide excision repair machinery is still the source of important questions. It has been observed that the repair rate of the different cyclobutane pyrimidine dimers, i.e. the photoproducts induced by dimerization of two {pi}-stacked pyrimidines (T<>T, T<>C, C<>T, C<>C), depends on the nucleobases involved in the lesion. TT derivatives (T<>T) are removed more slowly than those containing cytosine, especially in 5. Using all-atom molecular dynamics simulations and free-energy calculations, we demonstrate that the variation of the repair rate observed in human skin and in cultured cutaneous cell is associated to the recognition of the four lesions by the DDB2 protein moiety, and more specifically by the differential structural deformation induced on the complementary strand. Indeed, while C<>C and C<>T induce a larger deviation on the groove parameters, T<>T and T<>C, instead, affect DNA structure to a lesser extent. less affected. These effects then hamper differentially the downstream recruitment of the repair complexes. The observed DNA deformation correlates with the experimental repair rate and provides a structural rationale for the different repair rates of CPD by nucleotide excision repair machinery. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=105 SRC="FIGDIR/small/724087v1_ufig1.gif" ALT="Figure 1"> View larger version (43K): org.highwire.dtl.DTLVardef@cf6b6dorg.highwire.dtl.DTLVardef@195e35forg.highwire.dtl.DTLVardef@1829296org.highwire.dtl.DTLVardef@165baba_HPS_FORMAT_FIGEXP M_FIG C_FIG

Protein dynamics are essential to biological function, yet understanding whether deep learning models contain information about these dynamics remains an open question. In this study, we quantitatively investigate the capacity of deep learning structure generation methods to predict protein flexibilities by directly comparing residue-level mean squared fluctuation (MSF) profiles derived from structural ensembles with experimental or simulation-informed flexibility profiles. We assembled four diverse benchmark datasets representing different types of structural information, including 70 NMR ensembles, 43 X-ray crystallographic protein pairs in two distinct conformational states, 82 high-resolution cryo-EM structures, and molecular dynamics simulations of 10 proteins. Utilizing AlphaFold3, AlphaFold2, and RosettaFold to generate multiple structural models, we applied ranksort normalization to place the profiles on a comparable scale and quantified similarity primarily using cosine and Pearson similarities. Our results demonstrate that the flexibility predictions from deep learning-generated models agree well with experimental data, suggesting that fluctuations in these predicted ensembles can serve as effective proxies for protein flexibility. Notably, AlphaFold3 consistently produced the best results across the datasets. We also observed that flexibility prediction accuracy generally improves as the number of models increases up to 15, and our findings remain robust even when terminal residues are excluded from the analysis. To facilitate broader application, we provide three publicly accessible Jupyter Notebooks to calculate MSF from deep learning outputs. Ultimately, this work provides evidence that deep learning structural ensembles can serve as proxies for protein flexibility.

Surface functionalization of inorganic quantum dot nanoparticles is of great interest in the application of these materials toward a wide range of biological applications where membrane interactions are critical. The use of amphiphilic lipids to functionalize the surfaces of quantum dots represents a promising alternative to produce water-soluble and membrane-active materials with facile tuning of the quantum dots surface properties. Here, we demonstrate an experimental approach that yields lipid-coated quantum dots with highly tunable surface charge by controlling the concentration of cationic lipids during preparation. Through fluorescence-activated cell sorting assays, we show that these cationic lipid-coated quantum dots can enhance membrane interactions and increase membrane labeling density in live HEK293 cells. We further employed coarse-grained molecular dynamics simulations to model the lipid self-assembly process using an implicit solvent force field and subsequently model the adsorption of lipid-coated quantum dots to model membranes. Our simulations show that we can control the effective surface charge of lipid-coated quantum dots and influence the strength of adsorption to oppositely charged lipid membranes, a process that is mediated by the release of counterions at the quantum dot-membrane interface. This work supports the future development of biocompatible and water-soluble inorganic nanoparticles with highly tunable surfaces, and provides mechanistic insight into how different lipids can influence nanoparticle-membrane interactions at a molecular scale.

Orthoflavivirus, such as West Nile Virus (WNV), dengue virus (DENV) and ZIKA virus (ZIKV), are globally distributed pathogens that pose substantial threats to human health. Currently, there are still no effective antiviral drugs for WNV or ZIKV. Despite the availability of two licensed DENV vaccines, their use remains limited due to potential risks, highlighting an urgent need for antiviral drug development. The highly conserved orthoflavivirus protease NS2B/NS3 is required for viral replication, making it a promising anti-flavivirus target. A major challenge, however, is the highly charged active site of this enzyme, which requires charged chemical matters with low bioavailability. An alternative and more attractive strategy is to target potential allosteric sites or folding intermediate states of the protease. In this work, we employ the topology-based coarse-grained G[o] modeling to explore the coupled binding and folding pathways of WNV NS2B/NS3 protease and study the effects of the widely used experimental construct with a G4SG4 linker between NS2B and NS3 on stability and folding. Our results provide a holistic conformational landscape of the protease binding and folding, including several key intermediate states. We find that the presence of the G4SG4 linker alters the folding pathways and destabilizes the NS2B C-terminus. The latter is consistent with experimental observations that the G4SG4 linked protease has lower activity and adopts an open state without the substrate in crystal structures. Together, these findings provide for the first time a complete picture of the binding and folding of the NS2B/NS3 protease and identify important folding intermediate states that could be targeted for allosteric antiviral drug development. TOC Figure O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=157 SRC="FIGDIR/small/722635v1_ufig1.gif" ALT="Figure 1"> View larger version (40K): org.highwire.dtl.DTLVardef@163c356org.highwire.dtl.DTLVardef@ad7b35org.highwire.dtl.DTLVardef@173ed8aorg.highwire.dtl.DTLVardef@1f026bf_HPS_FORMAT_FIGEXP M_FIG C_FIG

Curcumin-functionalized gold nanoclusters are promising platforms for catalysis and drug delivery, yet the molecular determinants of their stability, morphology, and solvent response remain unclear. Here, microsecond all-atom molecular dynamics simulations are employed to investigate a 2 nm gold nanoparticle noncovalently coated with different curcumin forms, including neutral enol and trans-keto tautomers, the deprotonated enolate, and their mixtures in water-ethanol and water-methanol solvents. Layer-resolved analyses of radius of gyration, density profiles, and surface coverage reveal that neutral enol and trans forms generate compact assemblies with near-complete surface coverage, whereas enolate-rich systems adopt more expanded conformations with solvent-exposed molecules. Mixed systems preserve these intrinsic packing characteristics while improving overall coverage. Solvent substitution from ethanol to methanol reduces {pi}-{pi} stacking, strengthens Au-curcumin interactions, and increases surface coverage, yielding more compact nanostructures. Free energy and potential of mean force calculations indicate that deprotonated curcumin most effectively screens Au-Au interactions and stabilizes dispersed nanoparticles, while neutral tautomers provide moderate stabilization. Curcumin also enhances the loading of anticancer drug doxorubicin (DOX) onto Au nanoparticles, improving biocompatibility. Enolate(An)-containing systems produce extended structures with weaker membrane interactions, whereas neutral curcumin complexes form compact, positively charged assemblies that strongly bind to negatively charged cancer cell membranes. These findings clarify how tautomeric state and solvent environment cooperatively govern interfacial organization and colloidal stability, establish design guidelines for curcumin-based gold nanocarriers in catalysis, sensing, and drug delivery applications.

In mammalian cells, lipid monolayers support the integrity of lipid droplets (LDs), organelles that function as storage for neutral lipids. Liver-targeting illnesses such as liver cancer interrupt normal LD metabolism and prompt changes in the chemical content of these organelles, which can have effects on structural and organizational behavior of the lipids. In LDs, liver cancer induces concentric crystalline phases of cholesteryl esters (CEs) and triglycerides near the NL-monolayer interface, which become more pronounced as CE concentration increases. Yet, there is little known about how this phenomenon may link to persistence of undigested LDs in liver cancer patients. To shed light on this, all-atom molecular dynamics simulations were used to model LD micropipette aspiration experiments and gain insight into the effect of CE concentration on partitioning, structural, and mechanical properties of LDs. We successfully model micropipette aspiration by application of constant surface tension laterally, which stretches lipid bilayers and monolayers as the magnitude increased. The results show increased phospholipid packing due to insertion of CE fatty tails into the monolayer. Increasing CE concentration induces a non-linear change in surface packing defects on the LDs, notable rigidification, and stiffness. Taken together, these insights improve our understanding of the physical properties at the LD monolayer-core interface during liver cancer progression.

The plasma membrane is a laterally heterogeneous environment in which lipid organization plays a central role in regulating protein function. In model systems, this heterogeneity is often described in terms of coexisting liquid-ordered (Lo) and liquid-disordered (Ld) phases, commonly associated with the lipid raft concept. Despite extensive experimental and computational efforts, the molecular determinants governing protein partitioning between these domains remain poorly understood, largely due to the limited number of systems studied. Here, we address this challenge using a high-throughput computational approach, systematically analyzing the partitioning behavior of almost 5,000 helical transmembrane peptides in phase-separating lipid membranes. Across all simulations, we find that none of the peptides exhibit a clear preference for the Lo phase, while the vast majority partition into the Ld phase. This observation is consistent with experimental results in simplified membrane systems and suggests that commonly used ternary lipid mixtures may not fully capture the physicochemical environment governing protein sorting in biological membranes. In addition, we identify a subset of peptides that preferentially localize at the Lo/Ld interface. These interfacial peptides display distinct sequence characteristics, indicating that boundary localization is governed by specific combinations of residue composition and spatial arrangement rather than a single dominant feature. Overall, our results reveal that transmembrane helix partitioning in model membranes is dominated by a preference for disordered environments, with interfacial localization emerging as a distinct and potentially functional behavior.

Stimulated emission depletion (STED) microscopy is a super-resolution fluorescence imaging technique that achieves high spatial and temporal resolution by exploiting stimulated emission to induce fluorescence depletion (FD) and is expected to have substantial utility for imaging applications using fluorescent proteins. However, the compatibility of fluorescent proteins with STED microscopy systems has been understood primarily through empirical observations, and there is no established methodology for the rational selection of fluorescent proteins for STED microscopy. In this study, we systematically evaluated the compatibility of commonly used fluorescent proteins with STED microscopy systems by measuring FD properties using transient absorption spectroscopy and fluorescence dip spectroscopy, both of which are classified as two-color spectroscopy (TCS). Fluorescent proteins identified as compatible with the STED microscopy system based on the TCS measurements were employed for three-dimensional STED imaging of cellular samples expressing each protein. In all samples, three-dimensional spatial resolution was improved relative to confocal laser microscopy, with particularly marked improvements in z-axis resolution. These findings demonstrate that measurements of FD properties via TCS provide a robust approach for evaluating the compatibility of fluorescent proteins with the STED microscopy system and for selecting suitable fluorescent proteins for STED imaging.

All-atom simulations of RNA using molecular dynamics have the promise of modeling conformational preferences, folding thermodynamics, conformational change kinetics, and binding affinities of small molecule therapeutics. These simulations rely on a force field, a set of equations and parameters that model the potential energy as a function of conformation using classical mechanics. One popular force field for RNA is Amber OL3, with the most recent iteration derived in 1999 and with subsequent updates to backbone dihedral parameters. The Amber force field, while frequently used, is known to have limitations; for example, it does not properly stabilize native structures against alternative structures. Here, we provide a new approach to fitting the non-bonded parameters for the force field, specifically atom-centered point charges for electrostatics and the Lennard-Jones parameters. The parameters are fit to quantum mechanics (QM) interaction energies calculated with symmetry-adapted perturbation theory (SAPT), including embedded point charges to represent the electrostatic field from solvent and adjacent nucleotides. In this pilot study with a limited set of fitting data, we use the Amber ff99 equations and atom types unchanged. With the revised parameters, we observe improvement in the stability of native structures relative to alternative structures. Native tetraloop conformations, which unfold with the Amber OL3 force field, are stable on the microsecond timescale with our new force field parameters. We also see improvement in the conformational preferences of tetramers. Crucially, A-form helices are still well-modeled, but we observe additional flexibility in an internal loop that is not consistent with NMR data. Overall, we provide evidence that this new approach to fitting RNA force field parameters to SAPT interaction energies with native-structure context represented as embedded point charges is promising. It offers a flexible solution for revising the equations in future work or for extension to other molecules that interact with RNA, such as proteins and small molecules. We call this new set of force field parameters Amber RNA.ROC26.

Mycobacterium tuberculosis fatty acid synthase I (Mtb FAS-I) is a multifunctional hexameric complex essential for fatty acid (FA) synthesis. The need of a hexameric structure for activity of the complex in Mtb remains elusive. Here, we model a conformation of the functionally active complex with acyl carrier protein (ACP) at ketoacyl synthase (KS). Our model reveals a crucial cross-dome dependence in the mechanism of FA synthesis at the condensation step. Using molecular dynamics simulation, we identify key ACP and KS residues that mantain persistent interactions. ACPs phosphopantetheine (PPT) arm adopts several conformations while accessing KSs catalytic pocket, including two distinct conformations that correlate with volumes of ACP and KS pockets. A PHE residue, reported as a gatekeeper of the KS pocket in other species, also shows open and closed orientations in our simulation. Our results provide crucial insights that are essential for a mechanistic undersanding of the Mtb FAS-I complex.

Significant cellular processes, including protein sorting, signal transduction, and pathogen entry, amongst others, are associated with membrane microdomains, also known as lipid rafts. Lipid rafts, due to their unique biophysical properties compared to their surrounding environment, which stem from their distinct lipid and protein profiles, have garnered interest in methods and techniques that tune their coexisting liquid-ordered/liquid-disordered state, aiming to disrupt or destabilize them. Since cholesterol stabilizes the membrane domain, cholesterol-depleting compounds like cyclodextrin can be used to destabilize and disrupt the membrane rafts. Overall, given the membrane rafts importance in biological processes, it is crucial to understand the biophysical factors that influence its stability. In this study, we present a new method for disrupting and dissolving lipid rafts in a model system of phase-separated supported lipid bilayer (SLB) patches composed of DOPC, DPPC, and cholesterol. Using fluorescence microscopy to monitor the liquid ordered (Lo) and liquid disordered (Ld) phases of the SLB patches, we observed that adding DOPC liposomes causes a transformation of the co-existing Ld and Lo phases into a single-phase bilayer. On the other hand, adding liposomes that match the lipid content of the phase-separated SLB patch increase the areas of the existing Ld and Lo phases. This work also offers a new method for redistributing raft-localized molecules, confirmed by tracking the redistribution of cholera toxin bound to GM1 after domain dissolution with DOPC liposomes. The work describes an alternative method for dynamically altering membrane composition and dissolving domains via liposome addition, rather than lipid depletion or exchange.

Membrane association is governed by the thermodynamics of amino acid partitioning between water and the lipid bilayer. Here, we quantified amino acid side-chain insertion energetics in a 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC) bilayer using unbiased molecular dynamics simulations. Equilibrium depth distributions of 28 analogs, including multiple protonation states, were converted into potentials of mean force (PMFs) by Boltzmann inversion. The resulting PMFs reproduced the main features of bilayer partitioning. Hydrophobic analogs favored the bilayer core, aromatic analogs were stabilized in interfacial regions, and polar or charged analogs remained unfavorable in the hydrophobic interior. A diglycine analog representing the peptide backbone behaved similarly to uncharged polar residues. Depth-dependent pKa profiles and orientational analyses further showed how protonation equilibria and aromatic-ring alignment influence insertion energetics. Agreement with experimental hydrophobicity scales supports the robustness of the approach. These results provide an efficient and internally consistent framework for characterizing bilayer insertion energetics and establish a reference for future studies in more complex lipid environments. O_FIG O_LINKSMALLFIG WIDTH=198 HEIGHT=200 SRC="FIGDIR/small/723583v1_ufig1.gif" ALT="Figure 1"> View larger version (79K): org.highwire.dtl.DTLVardef@127b12org.highwire.dtl.DTLVardef@14de924org.highwire.dtl.DTLVardef@53b27org.highwire.dtl.DTLVardef@16e8ee4_HPS_FORMAT_FIGEXP M_FIG C_FIG SIGNIFICANCEMembrane-associated proteins represent a large fraction of the proteome and include many major drug targets, yet quantitative understanding of their interactions with lipid bilayers remains limited. Here, we present an unbiased molecular dynamics framework for systematically determining amino acid side-chain insertion free energies in a model bilayer. By deriving potentials of mean force directly from equilibrium depth distributions, this approach enables internally consistent comparisons across residue classes and protonation states without biasing restraints. The resulting free-energy profiles reproduce established hydrophobicity trends and show how protonation equilibria and aromatic-ring orientation modulate bilayer partitioning. This scalable strategy provides a quantitative reference for residue-level membrane thermodynamics and establishes a foundation for extending insertion energetics to more diverse lipid compositions and more complex membrane-associated systems.

Building on a complex between a tubulin protofilament (PF) and a fragment of the Tau protein containing residues 169 to 367, we investigate the dynamics of the disordered elements of the system, namely the tubulin C-terminal tails (CTTs) and the Tau protein, using classical all-atom molecular dynamics simulations. Our results show that CTTs adopt a hook-like dynamic pattern on the bare PF while remaining highly mobile. The binding of Tau on the PF surface alters the dynamics of the I-CTTs in a sequence-dependent manner. While the repeat domains of Tau are mostly maintained on the PF by weak and strong binding patches with the tubulin cores, the Proline-Rich Region (PRR) relies on the wrapping phenomenon of I-CTTs to fuzzily stabilize its interaction with the PF. Our study thus provides a deep dive into the dynamic interplay between the Tau protein and the CTTs of microtubules, the latter being characterized extensively using a variety of disorder-adapted metrics. TOC Graphic O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=111 SRC="FIGDIR/small/721901v1_ufig1.gif" ALT="Figure 1"> View larger version (25K): org.highwire.dtl.DTLVardef@b3f985org.highwire.dtl.DTLVardef@1c2bf70org.highwire.dtl.DTLVardef@a66b95org.highwire.dtl.DTLVardef@1e138e0_HPS_FORMAT_FIGEXP M_FIG C_FIG

Designing peptide sequences that remain stable and selective across heterogeneous environments remains a central challenge in biomolecular modeling. Here we introduce an interpretable, physics-based Hamiltonian for environment-conditioned design of -helical peptide sequences. The model integrates helix propensities, pairwise interactions, electrostatics, anisotropic solvent exposure, and interfacial geometry into a unified energy function. To enable comparison across sequence lengths and environments, all contributions are rescaled and expressed as Z-scores relative to random sequence ensembles, yielding a normalized design landscape with balanced physical terms. This formulation defines a structured optimization problem that can be explored using exact, heuristic, and hybrid quantum- classical approaches without modification of the underlying model. The Hamiltonian recovers polar and apolar limits, discriminates experimentally characterized water-soluble and transmembrane -helical peptide sequences, and captures the preferential stabilization of membrane-active sequences at anionic interfaces over non-functional controls. It further enables multi-objective and selective design, generating candidate sequences with tunable environmental specificity.

HIV-1 buds from infected cells as immature virion particles with a scattered envelope glycoprotein (Env) distribution on their envelope. It then undergoes maturation, during which the viral protease cleaves the Gag polyprotein at multiple sites, leading to structural reorganization of the viral particle and lateral redistribution of Env proteins, ultimately rendering the virion infectious. However, the underlying mechanism of maturation-induced Env reorganization remains elusive. In this study, we combine microsecond-long all-atom (AA), bottom-up coarse-grained (CG) molecular dynamics simulations, and diffusion model-based backmapping to investigate the structural organization and key interactions of Env in viral membranes. AA simulations of fully glycosylated Env embedded in HIV-1 mimetic asymmetric bilayers were first performed to characterize its conformational dynamics and Env-lipid interactions. We then developed a bottom-up CG model of glycosylated Env from that AA data and simulated the mature HIV-1 virion envelope containing multiple Env proteins. The CG simulations predict that Env proteins form clusters through interactions mediated by the cytoplasmic tail domain (CTD) and adopt diverse tilted conformations within these clusters. These CG simulations were then backmapped to AA resolution and further AA simulations were carried out to identify, in detail, the specific interacting residues in the Env clusters. Additionally, analysis of epitope accessibility shows that broadly neutralizing antibodies (bnAbs) targeting the V1/V2 and V3 loops may efficiently interact with Env clusters on the mature virion surface. Together, these results provide a molecular mechanism for Env oligomerization during viral maturation and offer new insights into the accessibility of bnAb epitopes on Env clusters.

Ligand binding to intrinsically disordered proteins resists description in terms of conventional binding pockets, yet it can be analysed as a dynamic process in which ligands move across transient surface interaction sites. Here we characterise a pathway-based representation in which ligand binding is described as a sequence of transitions between residue-defined microstates, enabling ligand-specific effects to be distinguished from intrinsic properties of the peptide conformational ensemble. Using all-atom molecular dynamics simulations of A{beta}42 and the C-terminal region of -synuclein in complex with chemically diverse small molecules, we construct transition matrices that encode ligand movement across the peptide surface and use Markov state models to identify dominant binding pathways and relative binding propensities. Pairwise enrichment-factor and AUC analyses reveal strong conservation of the highest-ranked pathways across chemically diverse ligands, with enrichment factors of 15-45 for the top-ranked states and AUC values typically [&ge;]0.75, well above random expectation. These dominant pathways are also preserved across changes in pH and temperature, whereas a urea control, included as a non-specific binder, shows reduced enrichment, indicating that ligands primarily modulate pathway weights rather than define the underlying network topology. Ensemble docking across chemically diverse libraries further supports the presence of recurrent ligand-accessible hotspots within the peptide conformational ensemble. Building on this framework, we apply a prospective screening pipeline to A{beta}42, combining MSM-derived hotspots with sequence-based Ligand-Transformer scoring and Gnina docking across 1.66 million compounds, to nominate 19 candidates for prospective experimental evaluation. Together, these results indicate that disordered protein sequences give rise to conformational ensembles that exhibit characteristic binding pathways for small molecules.