Initial Conformation Research Articles

Effect of applied magnetic fields on the morphology of nematic nanobridges in slit pores

In this paper, we report a molecular dynamics study of the effect of the application of magnetic fields on the morphology of nematic nanobridges of 32,000 oblate Gay-Berne particles in slit pores favouring homeotropic anchoring. In absence of magnetic fields, previous studies show that there are different conformations of the nanobridge, depending on the slit pore width D and the wettability of the walls. Under the application of uniform magnetic field cycles, in which the intensity of the field is increased stepwise until a maximum value and then decreased at the same rate, switching between different nanobridge conformations can be observed if the magnetic field is applied in a perpendicular direction to the global nematic director of the nanobridge. However, there are situations in which the initial bridge conformation is recovered after the magnetic field application, indicating that the switching can only be observed if there are different locally stable nanobridge conformations under the same thermodynamic conditions. Moreover, magnetic fields can destabilise the nanobridge, leading to its breakdown into isolated nanodroplets attached to a single wall.

Salt-Induced Hydrophobic C-Terminal Region of α-Synuclein Triggers Its Fibrillation under the Mimic Physiologic Condition.

α-Synuclein (αS) causes Parkinson's disease due to the structural alteration into amyloid fibrils that form after the interaction with synaptic membranes in neurons. To understand the alternation mechanism, the effect of salt (NaCl) on the interaction of αS with synaptic mimic membrane was characterized at the molecular level because salt triggered the amyloid fibril formation. The membrane-bound conformation (or the initial conformation before fibrillation) showed that NaCl decreased the number of helical structures and Tyr residues interacting with the membrane surface compared to when NaCl was absent, implying an increase in solvent-exposed regions. The N-terminal region of αS interacted with the membrane, forming the helical structures regardless of NaCl, while the C-terminal region formed a random structure with weak membrane interaction, but NaCl inhibited the interaction of its hydrophobic area, suggesting that salt promoted amyloid fibril formations by exposing the hydrophobic C-terminal region, which can intermolecularly interact with free αS.

DFT Study on Retigerane-Type Sesterterpenoid Biosynthesis: Initial Conformation of GFPP Regulates Biosynthetic Pathway, Ring-Construction Order and Stereochemistry.

Retigerane-type sesterterpenoids, which feature a unique 5/6/5/5/5 fused pentacyclic structure with an angular-type triquinane moiety, are biosynthesized via successive carbocation-mediated reactions triggered by terpene cyclases. However, the precise biosynthetic pathways/mechanisms, wherein steric inversion of the carbon skeleton occurs at least once, remain elusive. Two plausible reaction pathways have been proposed, which differ in the order of ring cyclization: A → B/C → D/E-ring(s) (Route 1) and A → E → B → C/D-ring(s) (Route 2). Since the reaction intermediates of these complicated domino-type reaction sequences are experimentally inaccessible, we employed comprehensive density functional theory (DFT) calculations to evaluate these routes. The results indicate that retigeranin biosynthesis proceeds via Route 2 involving a multistep carbocation cascade, in which the order of ring cyclization (A → E → B → C/D) is the key to constructing the angular 5/5/5 triquinane structure with the correct stereochemistry at C3. The result also suggests that slight differences in the initial conformation have a significant effect on the order of cyclization and steric inversion. The computed pathway/mechanism also provides a rational basis for the formation of various related terpenes/terpenoids.

K-Means NANI: An Improved Clustering Algorithm for Molecular Dynamics Simulations.

One of the key challenges of k-means clustering is the seed selection or the initial centroid estimation since the clustering result depends heavily on this choice. Alternatives such as k-means++ have mitigated this limitation by estimating the centroids using an empirical probability distribution. However, with high-dimensional and complex data sets such as those obtained from molecular simulation, k-means++ fails to partition the data in an optimal manner. Furthermore, stochastic elements in all flavors of k-means++ will lead to a lack of reproducibility. K-means N-Ary Natural Initiation (NANI) is presented as an alternative to tackle this challenge by using efficient n-ary comparisons to both identify high-density regions in the data and select a diverse set of initial conformations. Centroids generated from NANI are not only representative of the data and different from one another, helping k-means to partition the data accurately, but also deterministic, providing consistent cluster populations across replicates. From peptide and protein folding molecular simulations, NANI was able to create compact and well-separated clusters as well as accurately find the metastable states that agree with the literature. NANI can cluster diverse data sets and be used as a standalone tool or as part of our MDANCE clustering package.

Simulation-Guided Conformational Space Exploration to Assess Reactive Conformations of a Ribozyme.

Self-splicing ribozymes are small ribonucleic acid (RNA) enzymes that catalyze their own cleavage through a transphosphoesterification reaction. While this process is involved in some specific steps of viral RNA replication and splicing, it is also of importance in the context of the (putative) first autocatalytic RNA-based systems that could have preceded the emergence of modern life. The uncatalyzed phosphoester bond formation is thermodynamically very unfavorable, and many experimental studies have focused on understanding the molecular features of catalysis in these ribozymes. However, chemical reaction paths are short-lived and not easily characterized by experimental approaches, so molecular simulation approaches appear as an ideal tool to unveil the molecular details of the reaction. Here, we focus on the model hairpin ribozyme. We show that identifying a relevant initial conformation for reactivity studies, which is frequently overlooked in mixed quantum-classical studies that predominantly concentrate on the chemical reaction itself, can be highly challenging. These challenges stem from limitations in both available experimental structures (which are chemically altered to prevent self-cleavage) and the accuracy of force fields, together with the necessity for comprehensive sampling. We show that molecular dynamics simulations, combined with extensive conformational phase space exploration with Hamiltonian replica-exchange simulations, enable us to characterize the relevant conformational basins of the minimal hairpin ribozyme in the ligated state prior to self-cleavage. We find that what is usually considered a canonical reactive conformation with active site geometries and hydrogen-bond patterns that are optimal for the addition-elimination reaction with general acid/general base catalysis is metastable and only marginally populated. The thermodynamically stable conformation appears to be consistent with the expectations of a mechanism that does not require the direct participation of ribozyme residues in the reaction. While these observations may suffer from forcefield inaccuracies, all investigated forcefields lead to the same conclusions upon proper sampling, contrasting with previous investigations on shorter timescales suggesting that at least one reparametrization of the Amber99 forcefield allowed to stabilize aligned active site conformations. Our study demonstrates that identifying the most pertinent reactant state conformation holds equal importance alongside the accurate determination of the thermodynamics and kinetics of the chemical steps of the reaction.

Molecular docking and MD simulation studies of 4-thiazol-N-(pyridin-2-yl)pyrimidin-2-amine derivatives as novel inhibitors targeted to CDK2/4/6

PurposeNowadays, cyclin-dependent kinase 4/6 (CDK4/6) inhibitors have been approved for treating metastatic breast cancer and have achieved inspiring curative effects. But some discoveries have indicated that CDK 4/6 are not the requisite factors in some cell types because CDK2 partly compensates for the inhibition of CDK4/6. Thus, it is urgent to design CDK2/4/6 inhibitors for significantly enhancing their potency. This study aims to explore the mechanism of the binding of CDK2/4/6 kinases and their inhibitors to design novel CDK2/4/6 inhibitors for significantly enhancing their potency in different kinds of cancers.Materials and methodsA series of 72 disparately functionalized 4-substituted N-phenylpyrimidin-2-amine derivatives exhibiting potent inhibitor activities against CDK2, CDK4 and CDK6 were collected to apply to this research. The total set of these derivatives was divided into a training set (54 compounds) and a test set (18 compounds). The derivatives were constructed through the sketch molecule module in SYBYL 6.9 software. A Powell gradient algorithm and Tripos force field were used to calculate the minimal structural energy and the minimized structure was used as the initial conformation for molecular docking. By the means of 3D-QSAR models, partial least squares (PLS) analysis, molecular dynamics (MD) simulations and binding free energy calculations, we can find the relationship between structure and biological activity.ResultsIn this study, we used molecular docking, 3D-QSAR and molecular dynamics simulation methods to comprehensively analyze the interaction and structure–activity relationships of 72 new CDK2/4/6 inhibitors. We used detailed statistical data to reasonably verify the constructed 3D-QSAR models for three receptors (q2 of CDK2 = 0.714, R2pred = 0.764, q2 = 0.815; R2pred of CDK4 = 0.681, q2 = 0.757; R2pred of CDK6 = 0.674). MD simulations and decomposition energy analysis validated the reasonability of the docking results and identified polar interactions as crucial factors that influence the different bioactivities of the studied inhibitors of CDK2/4/6 receptors, especially the electrostatic interactions of Lys33/35/43 and Asp145/158/163. The nonpolar interaction with Ile10/12/19 was also critical for the differing potencies of the CDK2/4/6 inhibitors. We concluded that the following probably enhanced the bioactivity against CDK2/4/6 kinases: (1) electronegative groups at the N1-position and electropositive and moderate-sized groups at ring E; (2) electrogroups featured at R2; (3) carbon atoms at the X-position or ring C replaced by a benzene ring; and (4) an electrogroup as R4.ConclusionPrevious studies, to our knowledge, only utilized a single approach of 3D-QSAR and did not integrate this method with other sophisticated techniques such as molecular dynamics simulations to discover new potential inhibitors of CDK2, CDK4, or CDK6. So we applied the intergenerational technology, such as 3D-QSAR technology, molecular docking simulation techniques, molecular dynamics simulations and MMPBSA19/MMGBSA20-binding free energy calculations to statistically explore the correlations between the structure with biological activities. The constructed 3D-QSAR models of the three receptors were reasonable and confirmed by the excellent statistical data. We hope the results obtained from this work will provide some useful references for the development of novel CDK2/4/6 inhibitors.

Development of Integrated Database for Experiments and Simulations

Researchers collect data and use various methods to organize it. Ensuring the reliability and reproducibility of data is crucial, and collaboration across different research fields is on the rise. However, when there is geographical distance, sharing data becomes a challenging task. Therefore, there is a need for the development of a mechanism for sharing data on the web. We have developed an integrated database to facilitate the sharing and management of research data, particularly focusing on small molecules. The integrated database serves as a platform for centralizing data related to small molecules, including their chemical structures, wet lab experimental data, simulation data, and more. It has been constructed as a web application, offering features such as library management for small molecules, registration and viewing of wet lab experiment results, generation of initial conformations for simulations, and data visualization. This enables researchers to efficiently share their research data and collaborate seamlessly, whether within their research group or via cloud-based access that allows project and team members to connect from anywhere. This integrated database plays a critical role in connecting wet lab experiments and simulations, enabling researchers to cross-reference and analyze experimental data comprehensively. It serves as an essential tool to advance research and foster idea generation.

COSMIC: Molecular Conformation Space Modeling in Internal Coordinates with an Adversarial Framework.

The fast and accurate conformation space modeling is an essential part of computational approaches for solving ligand and structure-based drug discovery problems. Recent state-of-the-art diffusion models for molecular conformation generation show promising distribution coverage and physical plausibility metrics but suffer from a slow sampling procedure. We propose a novel adversarial generative framework, COSMIC, that shows comparable generative performance but provides a time-efficient sampling and training procedure. Given a molecular graph and random noise, the generator produces a conformation in two stages. First, it constructs a conformation in a rotation and translation invariant representation─internal coordinates. In the second step, the model predicts the distances between neighboring atoms and performs a few fast optimization steps to refine the initial conformation. The proposed model considers conformation energy, achieving comparable space coverage, and diversity metrics results.

Unraveling the Nano-Bio Interface Interactions of a Lipase Adsorbed on Gold Nanoparticles under Laser Excitation.

The complex nature and structure of biomolecules and nanoparticles and their interactions make it challenging to achieve a deeper understanding of the dynamics at the nano-bio interface of enzymes and plasmonic nanoparticles subjected to light excitation. In this study, circular dichroism (CD) and Raman spectroscopic experiments and molecular dynamics (MD) simulations were used to investigate the potential changes at the nano-bio interface upon plasmonic excitation. Our data showed that photothermal and thermal heating induced distinct changes in the secondary structure of a model nanobioconjugate composed of lipase fromCandida antarcticafraction B (CALB) and gold nanoparticles (AuNPs). The use of a green laser led to a substantial decrease in the α-helix content of the lipase from 66% to 13% and an increase in the β-sheet content from 5% to 31% compared to the initial conformation of the nanobioconjugate. In contrast, the differences under similar thermal heating conditions were only 55% and 11%, respectively. This study revealed important differences related to the enzyme secondary structure, enzyme-nanoparticle interactions, and the stability of the enzyme catalytic triad (Ser105-Asp187-His224), influenced by the instantaneous local temperature increase generated from photothermal heating compared to the slower rate of thermal heating of the bulk. These results provide valuable insights into the interactions between biomolecules and plasmonic nanoparticles induced by photothermal heating, advancing plasmonic biocatalysis and related fields.

Multi-targeted therapeutic potential of stigmasterol from the Euphorbia ammak plant in treating lung and breast cancer

Cancer is the most prevalent disease globally, which presents a significant challenge to the healthcare industry, with breast and lung cancer being predominant malignancies. This study used RNA-seq data from the TCGA database to identify potential biomarkers for lung and breast cancer. Tumor Necrosis Factor (TNFAIP8) and Sulfite Oxidase (SUOX) showed significant expression variation and were selected for further study using structure-based drug discovery (SBDD). Compounds derived from the Euphorbia ammak plant were selected for in-silico study with both TNFAIP8 and SUOX. Stigmasterol had the greatest binding scores (normalized scores of −8.53 kcal/mol and −9.69 kcal/mol) with both proteins, indicating strong stability in their binding pockets throughout the molecular dynamics’ simulation. Although Stigmasterol first changed its initial conformation (RMSD = 0.5 nm with the starting conformation) in SUOX, it eventually reached a stable conformation (RMSD of 1.5 nm). The compound on TNFAIP8 showed a persistent shape (RMSD of 0.35 nm), indicating strong protein stability. The binding free energy of the complex was calculated using the MM/GBSA technique; TNFAIP8 had a ΔGTOTAL of −24.98 kcal/mol, with TYR160 being the most significant residue, contributing −2.52 kcal/mol. On the other hand, the SUOX complex had a binding free energy of −16.87 kcal/mol, with LEU151 being the primary contributor (-1.17 kcal/mol). Analysis of the complexes' free energy landscape unveiled several states with minimum free energy, indicating robust interactions between the protein and ligand. In its conclusion, this work emphasises the favourable ability of Stigmasterol to bind with prospective targets for lung and breast cancer, indicating the need for more experimental study.

Modulating surface functional groups in carbon dots for enhanced inhibition of β‐amyloid aggregation

AbstractGaining a profound understanding of carbon dots (CDs) structure and their potential to inhibit β‐amyloid (Aβ) aggregation holds significant importance in the quest for Alzheimer's disease (AD) prevention and treatment. Herein, CDs with varying structures were synthesized by adjusting the molar ratio of citric acid (CA) and ethylenediamine (EDA). Transmission electron microscopy (TEM) was used to characterize their size and morphology. Fourier transform infrared spectroscopy (FTIR) and X‐ray photoelectron spectroscopy (XPS) were applied to study their structure. Optical properties were analyzed through Ultraviolet (UV) spectroscopy absorption and fluorescence spectroscopy. The inhibitory effect of CDs on Aβ1–42 aggregation was explored using circular dichroism and atomic force microscopy (AFM). The results highlighted the substantial influence of the CA to EDA molar ratio on the surface structure of CDs, subsequently impacting their optical properties and efficacy in inhibiting Aβ1–42 aggregation. With increasing EDA content, CDs exhibited a rise in the number of amino functional groups while experiencing a reduction in carboxyl groups. CDs possessing more amino functional groups effectively induced alterations in the initial conformation of Aβ1–42, leading to a significant inhibition of Aβ1–42 aggregation.

SENSAAS-Flex: a joint optimization approach for aligning 3D shapes and exploring the molecular conformation space.

Popular shape-based alignment methods handle molecular flexibility by utilizing conformational ensembles to select the most fitted conformer. However, the initial conformer library generation step is computationally intensive and limiting to the overall alignment process. In this work, we describe a method to perform flexible alignment of two molecular shapes by optimizing the 3D conformation. SENSAAS-Flex, an add-on to the SENSAAS tool, is able to proceed from a limited set of initial conformers through an iterative process where additional conformational optimizations are made at the substructure level and constrained by the target shape. In self- and cross-alignment experiments, SENSAAS-Flex is able to reproduce the crystal structure geometry of ligands of the AstraZeneca Molecule Overlay Test set and PDBbind refined dataset. Our study shows that the point-based representation of molecular surfaces is appropriate in terms of shape constraint to sample the conformational space and perform flexible molecular alignments. The documentation and source code are available at https://chemoinfo.ipmc.cnrs.fr/Sensaas-flex/sensaas-flex-main.tar.gz.

Exploring binding affinity of 1-n-Alkyl-3-methylimidazolium chloride with iron porphyrin and electron uptake ability of the ionic liquid-FeP complex

Interaction of ionic liquids with iron porphyrin (FeP) arises in a number of application of ionic liquids such as dye-sensitized solar cells, batteries, and conversion of CO2 to value-added products, etc. Furthermore, ionic liquid-FeP interactions are thought to be responsible for ionic liquid biodegradation and catalytic breakdown of ionic liquids. Despite the importance of ionic liquid-FeP interactions, there is a lack of information on what conformations ionic liquids adopt when presented to FeP and how thermodynamics of subsequent electron transfer reaction is affected. To begin to answer these questions, electronic structure calculations are performed to assess how the binding propensity of the homologous series of 1-n-alkyl-3-methylimidazolium [Cnmim]Cl (n = 2, 4, 6, 8, 10) to FeP is affected as the alkyl chain length and the initial conformation of the cation presented to FeP are varied. The conceptual density functional theory framework is then invoked to compute the electrophilicity index of the ionic liquid-FeP complex to glean insight into the ability of the complex to acquire an electron. Calculations suggest two equally likely conformations of ionic liquids with similar Gibbs free energy change; however, the enthalpic and entropic contributions differ based on the conformation adopted by ionic liquids which in turn affects the propensity of the subsequent electron transfer process. The importance of results is discussed in terms of experimentally observed alkyl chain length-dependent biodegradability of ionic liquids.

Intrinsic conformational preference in the monomeric protein governs amyloid polymorphism.

The inherent stochasticity associated with the hierarchical self-assembly of either native-like or partially-unfolded protein monomers leads to the formation of transient, morphologically-diverse prefibrillar species resulting in structurally-distinct polymorphic protein aggregates. High-resolution structural characterization of mature aggregates has revealed heterogeneous supramolecular packing of protofibrils within amyloid polymorphs. However, little is known about whether initial monomeric protein conformers engender polymorphism at the onset of aggregation. Here, we show that intrinsic conformational preference in aggregation-competent monomeric ovalbumin, an archetypal serpin, dictates fibrillar polymorphism by modulating aggregation pathways. Using fluorescence, FT-IR, and vibrational Raman spectroscopy coupled with dynamic light scattering and electron microscopy, we demonstrate that conformationally-diverse amyloidogenic monomers, formed via an interplay of electrostatic and hydrophobic interactions before the commencement of aggregation, play a crucial role in promoting amyloid polymorphism. Moreover, the monomeric conformational fingerprints, accrued at the onset of aggregation, persist and propagate during the formation of polymorphic amyloids. Our results delineate essential conformational characteristics of the monomeric protein preceding aggregation, which will have broad implications in the mechanistic understanding of amyloid strain diversity observed in disease-related proteins.

Multiscale Molecular Dynamics Simulations of the Homodimer Accessory Protein ORF7b of SARS-CoV-2.

The SARS-CoV-2 ORF7b protein has drawn attention for its potential role in viral pathogenesis, but its structural details and lateral membrane associations remain elusive. In this study, we conducted multiscale molecular dynamics simulations to provide detailed molecular insights of the protein's dimerization, which is crucial for unraveling its structural model of protein-protein interface important to regulating cellular immune response. To gain a deeper understanding of homodimer configurations, we employed a machine learning algorithm for structural-based clustering. Clusters were categorized into three distinct groups for both parallel and antiparallel orientations, highlighting the influence of the initial monomer conformation on dimer configurations. Analysis of hydrogen bonding and π-π and π-cation stacking interactions within clusters revealed variations in interactions between clusters. In parallel dimers, weak stacking interactions in the transmembrane (TM) region were observed. In contrast, antiparallel dimers exhibited strong hydrogen bonding and stacking interactions contributing to tight dimeric packing, both within and outside the TM domain. Overall, our study provides a comprehensive view of the structural dynamics of ORF7b homodimerization in both parallel and antiparallel orientations. These findings shed light on the molecular interactions involved in ORF7b dimerization, which are crucial for understanding its potential roles in SARS-CoV-2 pathogenesis. This knowledge could inform future research and therapeutic strategies targeting this viral protein.

Accelerating Kinetics with Time-Reversal Path Sampling.

In comparison to numerous enhanced sampling methods for equilibrium thermodynamics, accelerating simulations for kinetics and nonequilibrium statistics are relatively rare and less effective. Here, we derive a time-reversal path sampling (tRPS) method based on time reversibility to accelerate simulations for determining the transition rates between free-energy basins. It converts the difficult uphill path sampling into an easy downhill problem. This method is easy to implement, i.e., forward and backward shooting simulations with opposite initial velocities are conducted from random initial conformations within a transition-state region until they reach the basin minima, which are then assembled to give the distribution of transition paths efficiently. The effects of tRPS are demonstrated using a comparison with direct simulations of protein folding and unfolding, where tRPS is shown to give results consistent with direct simulations and increase the efficiency by up to five orders of magnitude. This approach is generally applicable to stochastic processes with microscopic reversibility, regardless of whether the variables are continuous or discrete.

In silico approach reveals N-(5-phenoxythiophen-2-yl)-2-(arylthio)acetamides as promising selective SIRT2 inhibitors: the case of structural optimization of virtual screening-derived hits

Epigenetic modifications play an essential role in tumor suppression and promotion. Among the diverse range of epigenetic regulators, SIRT2, a member of NAD+-dependent protein deacetylates, has emerged as a crucial regulator of cellular processes, including cell cycle progression, DNA repair, and metabolism, impacting tumor growth and survival. In the present work, a series of N-(5-phenoxythiophen-2-yl)-2-(arylthio)acetamide derivatives were identified following a structural optimization of previously reported virtual screening hits, accompanied by enhanced SIRT2 inhibitory potency. Among the compounds, ST44 and ST45 selectively inhibited SIRT2 with IC50 values of 6.50 and 7.24 μM, respectively. The predicted binding modes of the two compounds revealed the success of the optimization run. Moreover, ST44 displayed antiproliferative effects on the MCF-7 human breast cancer cell line. Further, the contribution of SIRT2 inhibition in this effect of ST44 was supported by western blotting, affording an increased α-tubulin acetylation. Furthermore, molecular dynamics (MD) simulations and binding free energy calculations using molecular mechanics/generalized born surface area (MM-GBSA) method evaluated the accuracy of predicted binding poses and ligand affinities. The results revealed that ST44 exhibited a remarkable level of stability, with minimal deviations from its initial docking conformation. These findings represented a significant improvement over the virtual screening hits and may contribute substantially to our knowledge for further selective SIRT2 drug discovery. Communicated by Ramaswamy H. Sarma

Scaffold Matcher: A CMA-ES based algorithm for identifying hotspot aligned peptidomimetic scaffolds.

The design of protein interaction inhibitors is a promising approach to address aberrant protein interactions that cause disease. One strategy in designing inhibitors is to use peptidomimetic scaffolds that mimic the natural interaction interface. A central challenge in using peptidomimetics as protein interaction inhibitors, however, is determining how best the molecular scaffold aligns to the residues of the interface it is attempting to mimic. Here we present the Scaffold Matcher algorithm that aligns a given molecular scaffold onto hotspot residues from a protein interaction interface. To optimize the degrees of freedom of the molecular scaffold we implement the covariance matrix adaptation evolution strategy (CMA-ES), a state-of-the-art derivative-free optimization algorithm in Rosetta. To evaluate the performance of the CMA-ES, we used 26 peptides from the FlexPepDock Benchmark and compared with three other algorithms in Rosetta, specifically, Rosetta's default minimizer, a Monte Carlo protocol of small backbone perturbations, and a Genetic algorithm. We test the algorithms' performance on their ability to align a molecular scaffold to a series of hotspot residues (i.e., constraints) along native peptides. Of the 4 methods, CMA-ES was able to find the lowest energy conformation for all 26 benchmark peptides. Additionally, as a proof of concept, we apply the Scaffold Match algorithm with CMA-ES to align a peptidomimetic oligooxopiperazine scaffold to the hotspot residues of the substrate of the main protease of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Our implementation of CMA-ES into Rosetta allows for an alternative optimization method to be used on macromolecular modeling problems with rough energy landscapes. Finally, our Scaffold Matcher algorithm allows for the identification of initial conformations of interaction inhibitors that can be further designed and optimized as high-affinity reagents.

Molecular docking and dynamic simulation studies of isoflavones inhibiting Lox-2 activity for reducing beany flavor in soybean seeds

Low-lipoxygenase soybean cultivars are highly desirable because lower lipoxygenase content in soybean seeds leads to better quality soybean-based products and oils that are free from off-flavor or beany flavor. The expression of the Lox-2 gene is mainly responsible for this flavor. Over the years, natural antioxidants have been tested biochemically to inhibit Lox-2 activity, but in-silico studies are still lacking. To investigate the structural basis of inhibition, site-specific docking, as well as molecular dynamics (MD) simulations, were performed. Molecular docking analysis revealed that daidzein and genistein could be effective Lox2 receptor inhibitors. Furthermore, docked complexes were subjected to 100 ns MD simulation studies to analyze the structural conformations and stability of the complex. The analysis demonstrated that daidzein formed a more stable complex with the Lox-2 receptor and showed a higher H-bond propensity with the Asp775 residue. We discovered that the initial conformation of Lox2-daidzein complex changed to a more stable conformation at the beginning of the MD simulation and remained stable until the end with minor fluctuations. Furthermore, our analysis suggested that daidzein acts as a potential Lox-2 inhibitor and is a better candidate compared to genistein, which could be used to solve the beany flavor problem in soybean. Communicated by Ramaswamy H. Sarma

Linking folding dynamics and function of SAM/SAH riboswitches at the single molecule level.

Riboswitches are regulatory elements found in bacterial mRNAs that control downstream gene expression through ligand-induced conformational changes. Here, we used single-molecule FRET to map the conformational landscape of the translational SAM/SAH riboswitch and probe how co-transcriptional ligand-induced conformational changes affect its translation regulation function. Riboswitch folding is highly heterogeneous, suggesting a rugged conformational landscape that allows for sampling of the ligand-bound conformation even in the absence of ligand. The addition of ligand shifts the landscape, favoring the ligand-bound conformation. Mutation studies identified a key structural element, the pseudoknot helix, that is crucial for determining ligand-free conformations and their ligand responsiveness. We also investigated ribosomal binding site accessibility under two scenarios: pre-folding and co-transcriptional folding. The regulatory function of the SAM/SAH riboswitch involves kinetically favoring ligand binding, but co-transcriptional folding reduces this preference with a less compact initial conformation that exposes the Shine-Dalgarno sequence and takes min to redistribute to more compact conformations of the pre-folded riboswitch. Such slow equilibration decreases the effective ligand affinity. Overall, our study provides a deeper understanding of the complex folding process and how the riboswitch adapts its folding pattern in response to ligand, modulates ribosome accessibilityand the role of co-transcriptional folding in these processes.