Independent Molecular Dynamics Simulations Research Articles

Molecular Insights into the Effects of F16L and F19L Substitutions on the Conformation and Aggregation Dynamics of Human Calcitonin.

Human calcitonin (hCT) regulates calcium-phosphorus metabolism, but its amyloid aggregation disrupts physiological activity, increases thyroid carcinoma risk, and hampers its clinical use for bone-related diseases like osteoporosis and Paget's disease. Improving hCT with targeted modifications to mitigate amyloid formation while maintaining its function holds promise as a strategy. Understanding how each residue in hCT's amyloidogenic core affects its structure and aggregation dynamics is crucial for designing effective analogues. Mutants F16L-hCT and F19L-hCT, where Phe residues in the core are replaced with Leu as in nonamyloidogenic salmon calcitonin, showed different aggregation kinetics. However, the molecular effects of these substitutions in hCT are still unclear. Here, we systematically investigated the folding and self-assembly conformational dynamics of hCT, F16L-hCT, and F19L-hCT through multiple long-time scale independent atomistic discrete molecular dynamics (DMD) simulations. Our results indicated that the hCT monomer primarily assumed unstructured conformations with dynamic helices around residues 4-12 and 14-21. During self-assembly, the amyloidogenic core of hCT14-21 converted from dynamic helices to β-sheets. However, substituting F16L did not induce significant conformational changes, as F16L-hCT exhibited characteristics similar to those of wild-type hCT in both monomeric and oligomeric states. In contrast, F19L-hCT exhibited substantially more helices and fewer β-sheets than did hCT, irrespective of their monomers or oligomers. The substitution of F19L significantly enhanced the stability of the helical conformation for hCT14-21, thereby suppressing the helix-to-β-sheet conformational conversion. Overall, our findings elucidate the molecular mechanisms underlying hCT aggregation and the effects of F16L and F19L substitutions on the conformational dynamics of hCT, highlighting the critical role of F19 as an important target in the design of amyloid-resistant hCT analogs for future clinical applications.

Structural and Computational Insights into Dynamics and Intermediate States of Orexin 2 Receptor Signaling.

Orexin 2 receptor (OX2R) is a G protein-coupled receptor (GPCR) whose activation is crucial to regulation of the sleep-wake cycle. Recently, inactive and active state structures were determined from X-ray crystallography and cryo-electron microscopy single particle analysis, and the activation mechanisms have been discussed based on these static data. GPCRs have multiscale intermediate states during activation, and insights into these dynamics and intermediate states may aid the precise control of intracellular signaling by ligands in drug discovery. Molecular dynamics (MD) simulations are used to investigate dynamics induced in response to thermal perturbations, such as structural fluctuations of main and side chains. In this study, we proposed collective motions of the TM domain during activation by performing 30 independent microsecond-scale MD simulations for various OX2R systems and applying relaxation mode analysis. The analysis results suggested that TM3 had a vertical structural movement relative to the membrane surface during activation. In addition, we extracted three characteristic amino acid residues on TM3, i.e., Q1343.32, V1423.40, and R1523.50, which exhibited large conformational fluctuations. We quantitatively evaluated the changes in their equilibrium during activation in relation to the movement of TM3. We also discuss the regulation of ligand binding recognition and intracellular signal selectivity by changes in the equilibrium of Q1343.32 and R1523.50, respectively, according to MD simulations and GPCR database. Additionally, the OX2R-Gi signaling complex is stabilized in the conformation resembling a non-canonical (NC) state, which was previously proposed as an intermediate state during activation of neurotensin 1 receptor. Insights into the dynamics and intermediate states during activation gained from this study may be useful for developing biased agonists for OX2R.

Sampling Real-Time Atomic Dynamics in Metal Nanoparticles by Combining Experiments, Simulations, and Machine Learning.

Even at low temperatures, metal nanoparticles (NPs) possess atomic dynamics that are key for their properties but challenging to elucidate. Recent experimental advances allow obtaining atomic-resolution snapshots of the NPs in realistic regimes, but data acquisition limitations hinder the experimental reconstruction of the atomic dynamics present within them. Molecular simulations have the advantage that these allow directly tracking the motion of atoms over time. However, these typically start from ideal/perfect NP structures and, suffering from sampling limits, provide results that are often dependent on the initial/putative structure and remain purely indicative. Here, by combining state-of-the-art experimental and computational approaches, how it is possible to tackle the limitations of both approaches and resolve the atomistic dynamics present in metal NPs in realistic conditions is demonstrated. Annular dark-field scanning transmission electron microscopy enables the acquisition of ten high-resolution images of an Au NP at intervals of 0.6 s. These are used to reconstruct atomistic 3D models of the real NP used to run ten independent molecular dynamics simulations. Machine learning analyses of the simulation trajectories allow resolving the real-time atomic dynamics present within the NP. This provides a robust combined experimental/computational approach to characterize the structural dynamics of metal NPs in realistic conditions.

Binding Mechanism of Inhibitors to BRD4 and BRD9 Decoded by Multiple Independent Molecular Dynamics Simulations and Deep Learning.

Bromodomain 4 and 9 (BRD4 and BRD9) have been regarded as important targets of drug designs in regard to the treatment of multiple diseases. In our current study, molecular dynamics (MD) simulations, deep learning (DL) and binding free energy calculations are integrated to probe the binding modes of three inhibitors (H1B, JQ1 and TVU) to BRD4 and BRD9. The MD trajectory-based DL successfully identify significant functional function domains, such as BC-loop and ZA-loop. The information from the post-processing analysis of MD simulations indicates that inhibitor binding highly influences the structural flexibility and dynamic behavior of BRD4 and BRD9. The results of the MM-GBSA calculations not only suggest that the binding ability of H1B, JQ1 and TVU to BRD9 are stronger than to BRD4, but they also verify that van der Walls interactions are the primary forces responsible for inhibitor binding. The hot spots of BRD4 and BRD9 revealed by residue-based free energy estimation provide target sites of drug design in regard to BRD4 and BRD9. This work is anticipated to provide useful theoretical aids for the development of selective inhibitors over BRD family members.

Comprehensive Characterization of LAT1 Cholesterol-Binding Sites.

The human L-type amino acid transporter 1 (LAT1; SLC7A5), is an amino acid exchanger protein, primarily found in the blood-brain barrier, placenta, and testis, where it plays a key role in amino acid homeostasis. Cholesterol is an essential lipid that has been highlighted to play a role in regulating the activity of membrane transporters, such as LAT1, yet little is known about the molecular mechanisms driving this phenomenon. Here we perform a comprehensive computational analysis to investigate cholesterol's role in LAT1 structure and function, focusing on four cholesterol-binding sites (CHOL1-4) identified in a recent LAT1-apo inward-open conformation cryo-EM structure. Through a series of independent molecular dynamics (MD) simulations, molecular docking, MM/GBSA free energy calculations, and other analysis tools, we explored the interactions between LAT1 and cholesterol. Our findings suggest that CHOL3 forms the most stable and favorable interactions with LAT1. Principal component analysis (PCA) and center of mass (COM) distance assessments show that CHOL3 binding stabilizes the inward-open state of LAT1 by preserving the spatial arrangement of the hash and bundle domains. Additionally, we propose an alternative cholesterol-binding site for originally assigned CHOL1. Overall, this study improves the understanding of cholesterol's modulatory effect on LAT1 and proposes candidate sites for the discovery of future allosteric ligands with rational design.

Edge Substitution Effects of Histidine Tautomerization Behaviors on the Structural Properties and Aggregation Properties of Aβ(1-42) Mature Fibril.

Histidine behaviors play critical roles in folding and misfolding processes due to the changes in net charge and the various N/N-H orientations on imidazole rings. However, the effect of histidine tautomerization (HIE (Nε-H, ε) and HID (Nδ-H, δ) states) behaviors on the edge chain of Aβ mature fibrils remains inadequately understood, which is critical for finding a strategy to disturb fibril elongation and growth. In the current study, eight independent molecular dynamics simulations were conducted to investigate such impacts on the structural and aggregation properties. Our results from three different binding models revealed that the binding contributions of edge substitution effects are primarily located between chains 1 and 2. Histidine states significantly influence the secondary structure of each domain. Further analysis confirmed that the C1_H6//C1_E11 intrachain interaction is essential in maintaining the internal stability of chain 1, while the C1_H13//C2_H13 and C1_H14//C2_H13 interchain interactions are critical in maintaining the interchain stability of the fibril structure. Our subsequent analysis revealed that the current edge substitution leads to the loss of the C1_H13//C1_E11 intrachain and C1_H13//C2_H14 interchain interactions. The N-terminal regularity was significantly directly influenced by histidine states, particularly by the residue of C1_H13. Our study provides valuable insights into the effect of histidine behaviors on the edge chain of Aβ mature fibril, advancing our understanding of the histidine behavior hypothesis in misfolding diseases.

Effect of Histidine Behaviors on Structural Properties of Human Islet Amyloid Peptides

AbstractHistidine behaviors (including tautomeric behaviors and protonation behaviors) have been considered as an origin factor in protein folding and misfolding. However, such effects on human islet amyloid peptide (hIAPP) is still unclear, which are the key points in understanding hIAPP misfolding mechanisms. In current study, to investigate the structural properties of hIAPP peptide with histidine in (δ), (ϵ), and (p) states, three independent replica exchange molecular dynamics simulations were performed. Our results show that β‐sheet structure contents are very low no matter histidine on which state, while high α‐helix contents are obtained in A8‐L16/H18 and G24‐L27/S28 regions. Cluster data suggested that three hIAPP systems are prone to flexible structural features. Further analysis confirmed that the histidine related H‐bonding networks were detected in hIAPP(δ) (N14‐H18) and hIAPP(p) (N14‐H18 and F15‐H18). Moreover, based on overall hIAPP(δ), hIAPP(ϵ), and hIAPP(p) equilibration trajectories, we discovered both sheet and helix structural features in basin of free energy landscape. Our current study contributes to the understanding on conformational changes of hIAPP due to histidine behaviors, which could lead to new insights into histidine behaviors mechanisms.

Evidence of Spontaneous Formation of Two-Dimensional Amorphous Clathrates on Superhydrophilic Surfaces.

Clathrate hydrates reserved in the seabed are often dispersed in the pores of coarse-grained sediments; hence, their formation typically occurs under nanoconfinement. Herein, we show the first molecular dynamics (MD) simulation evidence of the spontaneous formation of two-dimensional (2D) clathrate hydrates on crystal surfaces without conventional nanoconfinement. The kinetic process of 2D clathrate formation is illustrated via simulated single-molecule deposition. 2D amorphous patterns are observed on various superhydrophilic face-centered cubic surfaces. Notably, the formation of 2D amorphous clathrate can occur over a wide range of temperatures, even at room temperature. The strong water-surface interaction, the characteristic properties of guest-gas molecules, and the underlying surface structure dictate the formation of 2D amorphous clathrates. Semiquantitative phase diagrams of 2D clathrates are constructed where representative patterns of 2D clathrates for characteristic gas molecules on prototypical Pd(111) and Pt(111) surfaces are confirmed by independent MD simulations. A tunable pattern of 2D amorphous clathrates is demonstrated by changing the lattice strain of the underlying substrate. Moreover, ab initio MD simulations confirm the stability of 2D amorphous clathrate. The underlining physical mechanism for 2D clathrate formation on superhydrophilic surfaces is elucidated, which offers deeper insight into the crucial role of water-surface interaction.

High-throughput machine learning - Kinetic Monte Carlo framework for diffusion studies in Equiatomic and Non-equiatomic FeNiCrCoCu high-entropy alloys

Sluggish diffusion is postulated as an underlying mechanism for many unique properties in high-entropy alloys (HEAs). However, its existence remains a subject of debate. Due to the challenges of exploring the vast composition space, to date most experimental and computational diffusion studies have been limited to equiatomic HEA compositions. To develop a high-throughput approach to study sluggish diffusion in a wide range of non-equiatomic compositions, this work presents an innovative artificial neural network (ANN) based machine learning model that can predict the vacancy migration barriers for arbitrary local atomic configurations in a model FeNiCrCoCu HEA system. Remarkably, the model utilizes the training data exclusively from the equiatomic HEA while it can accurately predict barriers in non-equiatomic HEAs as well as in the quaternary, ternary, and binary sub-systems. The ANN model is implemented as an on-the-fly barrier calculator for kinetic Monte Carlo (KMC) simulations, achieving diffusivities nearly identical to the independent molecular dynamics (MD) simulations but with far higher efficiency. The high-throughput ANN-KMC method is then used to study the diffusion behavior in 1,500 non-equiatomic HEA compositions. It is found that although the sluggish diffusion is not evident in the equiatomic HEA, it does exist in many non-equiatomic compositions. The compositions, complex potential energy landscapes (PEL), and percolation effect of the fastest diffuser (Cu) in these sluggish compositions are analyzed, which could provide valuable insights for the experimental HEA designs.

Investigating the Effects of the POPC-POPG Lipid Bilayer Composition on PAP248-286 Binding Using CG Molecular Dynamics Simulations.

PAP248-286 is a fusogenic peptide derived from prostatic acid phosphatase, commonly found in human semen, and is known to mediate HIV fusion with cell membranes. In this study, we performed 120 independent coarse-grained molecular dynamics simulations to investigate the spontaneous binding of PAP248-286 monomers, considering both charged and neutral histidine (His) residues, to membrane bilayers composed of different lipid compositions: 100% POPC, 70% POPC-30% POPG, and 50% POPC-50% POPG. Our simulations revealed that PAP248-286 displayed spontaneous binding to the membrane, with increased binding observed in the presence of anionic lipid POPG. Specifically, in systems containing 30% and 50% POPG lipids, monomer residues, particularly in the systems containing charged histidine (His) residues, exhibited prolonged binding with the membrane. Furthermore, our simulations indicated that PAP248-286 adopted a parallel orientation with the membrane, exposing its positively charged residues to the lipid bilayer. Interestingly, systems containing charged His residues showed a higher lipid occupancy around the peptide. These findings are consistent with previous experimental data, suggesting that PAP248-286 binding is enhanced in membranes with charged His residues, resembling the conditions found in the acidic vaginal pH environment. The results of our study provide further insights into the molecular mechanisms underlying the membrane binding of PAP248-286, contributing to our understanding of its potential role in HIV fusion and infection.

Binding Mechanism of Inhibitors to Heat Shock Protein 90 Investigated by Multiple Independent Molecular Dynamics Simulations and Prediction of Binding Free Energy.

The heat shock protein (HSP90) has been an import target of drug design in the treatment of human disease. An exploration of the conformational changes in HSP90 can provide useful information for the development of efficient inhibitors targeting HSP90. In this work, multiple independent all-atom molecular dynamics (AAMD) simulations followed by calculations of the molecular mechanics generalized Born surface area (MM-GBSA) were performed to explore the binding mechanism of three inhibitors (W8Y, W8V, and W8S) to HSP90. The dynamics analyses verified that the presence of inhibitors impacts the structural flexibility, correlated movements, and dynamics behavior of HSP90. The results of the MM-GBSA calculations suggest that the selection of GB models and empirical parameters has important influences on the predicted results and verify that van der Waals interactions are the main forces that determine inhibitor-HSP90 binding. The contributions of separate residues to the inhibitor-HSP90 binding process indicate that hydrogen-bonding interactions (HBIs) and hydrophobic interactions play important roles in HSP90-inhibitor identifications. Moreover, residues L34, N37, D40, A41, D79, I82, G83, M84, F124, and T171 are recognized as hot spots of inhibitor-HSP90 binding and provide significant target sites of for the design of drugs related to HSP90. This study aims to contribute to the development of efficient inhibitors that target HSP90 by providing an energy-based and theoretical foundation.

Dissecting the Self-assembly Dynamics of Imperfect Repeats in α-Synuclein.

The pathological aggregation of α-synuclein (αS) into amyloid fibrils is the hallmark of Parkinson's disease (PD). The self-assembly and membrane interactions of αS are mainly governed by the seven imperfect 11-residue repeats of the XKTKEGVXXXX motif around residues 1-95. However, the particular role of each repeat in αS fibrillization remains unclear. To answer this question, we studied the aggregation dynamics of each repeat with up to 10 peptides in silico by conducting multiple independent micro-second atomistic discrete molecular dynamics simulations. Our simulations revealed that only repeats R3 and R6 readily self-assembled into β-sheet-rich oligomers, while the other repeats remained as unstructured monomers with weak self-assembly and β-sheet propensities. The self-assembly process of R3 featured frequent conformational changes with β-sheet formation mainly in the non-conserved hydrophobic tail, whereas R6 spontaneously self-assembled into extended and stable cross-β structures. These results of seven repeats are consistent with their structures and organization in recently solved αS fibrils. As the primary amyloidogenic core, R6 was buried inside the central cross-β core of all αS fibrils, attracting the hydrophobic tails of adjacent R4, R5, and R7 repeats forming β-sheets around R6 in the core. Further away from R6 in the sequence but with a moderate amyloid aggregation propensity, the R3 tail could serve as a secondary amyloidogenic core and form independent β-sheets in the fibril. Overall, our results demonstrate the critical role of R3 and R6 repeats in αS amyloid aggregation and suggest their potential as targets for the peptide-based and small-molecule amyloid inhibitors.

Effects of Coulomb and vdW modifiers on hydrogen-bonds, energy and structural properties of peptide nanomembranes: A study by Molecular Dynamics simulations

In this study, four independent Molecular Dynamics simulations were conducted to evaluate how the calculation method of Coulomb and van der Waals (vdW) interactions (Cut-off or Particle-Mesh-Ewald - PME), and their modifiers: None, Potential-Shift (PS) or Potential-Shift-Verlet (PSV) affect the energetic and structural properties of A6H peptide nanomembranes. The results indicate that the use of cut-off as a basic method for calculating interactions may result in a more pronounced interaction, significantly affecting important characteristics of peptide nanomaterials, especially when compared with results obtained with PME/PSV. Hydrogen bond lifetime, a key feature of peptide nanomaterials, is strongly affected by the modifier used, resulting in a significant impact on self-assembled structures with a highly aligned peptide β-sheet structure.

Intermediate-aided allostery mechanism for α-glucosidase by Xanthene-11v as an inhibitor using residue interaction network analysis

Exploring allosteric inhibition and the discovery of new inhibitor binding sites are important studies in protein regulation mechanisms and drug discovery. Structural and network-based analyses of trajectories resulting from molecular dynamics (MD) simulations have been developed to discover protein dynamics, landscape, functions, and allosteric regions. Here, an experimentally suggested non-competitive inhibitor, xanthene-11v, was considered to explore its allosteric inhibition mechanism in α-glucosidase MAL12. Comparative structural and network analyses were applied to eight 250 ns independent MD simulations, four of which were performed in the free state and four of which were performed in ligand-bound forms. Projected two-dimensional free energy landscapes (FEL) were constructed from the probabilistic distribution of conformations along the first two principal components. The post-simulation analyses of the coordinates, side-chain torsion angles, non-covalent interaction networks, network communities, and their centralities were performed on α-glucosidase conformations and the intermediate sub-states. Important communities of residues have been found that connect the allosteric site to the active site. Some of these residues like Thr307, Arg312, TYR344, ILE345, Phe357, Asp406, Val407, Asp408, and Leu436 are the key messengers in the transition pathway between allosteric and active sites. Evaluating the probability distribution of distances between gate residues including Val407 in one community and Phe158, and Pro65 in another community depicted the closure of this gate due to the inhibitor binding. Six macro states of protein were deduced from the topology of FEL and analysis of conformational preference of free and ligand-bound systems to these macro states shows a combination of lock-and-key, conformational selection, and induced fit mechanisms are effective in ligand binding. All these results reveal structural states, allosteric mechanisms, and key players in the inhibition pathway of α-glucosidase by xanthene-11v.

Insights Into The Effects of Amino Acid Substitutions on The Stability of Reteplase Structure: A Molecular Dynamics Simulation Study.

Reteplase (recombinant plasminogen activator, r-PA) is a recombinant protein designed to imitate the endogenous tissue plasminogen activator and catalyze the plasmin production. It is known that the application of reteplase is limited by the complex production processes and protein's stability challenges. Computational redesign of proteins has gained momentum in recent years, particularly as a powerful tool for improving protein stability and consequently its production efficiency. Hence, in the current study, we implemented computational approaches to improve r-PA conformational stability, which fairly correlates with protein's resistance to proteolysis. The current study was developed in order to evaluate the effect of amino acid substitutions on the stability of reteplase structure using molecular dynamic simulations and computational predictions. Several web servers designed for mutation analysis were utilized to select appropriate mutations. Additionally, the experimentally reported mutation, R103S, converting wild type r-PA into non-cleavable form, was also employed. Firstly, mutant collection, consisting of 15 structures, was constructed based on the combinations of four designated mutations. Then, 3D structures were generated using MODELLER. Finally, 17 independent 20-ns molecular dynamics (MD) simulations were conducted and different analysis were performed like root-mean-square deviation (RMSD), root-mean-square fluctuations (RMSF), secondary structure analysis, number of hydrogen bonds, principal components analysis (PCA), eigenvector projection, and density analysis. Predicted mutations successfully compensated the more flexible conformation caused by R103S substitution, so, improved conformational stability was analyzed from MD simulations. In particular, R103S/A286I/G322I indicated the best results and remarkably enhanced the protein stability. The conformational stability conferred by these mutations will probably lead to more protection of r-PA in protease-rich environments in various recombinant systems and potentially enhance its production and expression level.

Concentration Effect, Structural Properties, and Driving Force on Aβ28 Dimerization with and without Zn2+ Cooperation: Learning from Replica Exchange Sampling.

Zn2+ is a very important factor in promoting the formation of amyloid beta (Aβ) aggregates and amyloid plaques. The Zn2+ -bound Aβ species generate amorphous or low molecular-weight oligomers. However, it is a lack of studies to approach the starting structural features (dimerization) in Aβ nucleation processes with and without Zn2+ , which is the key point in understanding Zn2+ -induced nucleation mechanisms. To better understand the effect of concentration, structural properties, and the driving force, 14 independent replica exchange molecular dynamics simulations were performed in Aβ28 dimerization with and without Zn2+ (zAβ28 ) cooperation. Our scanning results show that the aggregation propensity is easier in Aβ28 -Aβ28 and Aβ28 -zAβ28 systems than zAβ28 -zAβ28 system. In binding property, the Aβ28 -Aβ28 model (-61.5 kcal mol-1 ) is stronger than zAβ28 -zAβ28 (-26.6 kcal mol-1 ) and Aβ28 -zAβ28 (-7.24 kcal mol-1 ) models. Further analysis confirmed that H13 and H14 residues play specific roles in the three systems. The key point is the orientation of N atom of the imidazole ring in histidine residues. Furthermore, we discovered different driving forces for each system. Our current study contributes to the understanding of how the Aβ28 dimer interacts with Zn2+ , which could lead to new insights into Zn2+ -induced nucleation mechanisms.

Decoding the Identification Mechanism of an SAM-III Riboswitch on Ligands through Multiple Independent Gaussian-Accelerated Molecular Dynamics Simulations.

S-Adenosyl-l-methionine (SAM)-responsive riboswitches play a central role in the regulation of bacterial gene expression at the level of transcription attenuation or translation inhibition. In this study, multiple independent Gaussian-accelerated molecular dynamics simulations were performed to decipher the identification mechanisms of SAM-III (SMK) on ligands SAM, SAH, and EEM. The results reveal that ligand binding highly affects the structural flexibility, internal dynamics, and conformational changes of SAM-III. The dynamic analysis shows that helices P3 and P4 as well as two junctions J23 and J24 of SAM-III are highly susceptible to ligand binding. Analyses of free energy landscapes suggest that ligand binding induces different free energy profiles of SAM-III, which leads to the difference in identification sites of SAM-III on ligands. The information on ligand-nucleotide interactions not only uncovers that the π-π, cation-π, and hydrogen bonding interactions drive identification of SAM-III on the three ligands but also reveals that different electrostatic properties of SAM, SAH, and EEM alter the active sites of SAM-III. Meanwhile, the results also verify that the adenine group of SAM, SAH, and EEM is well recognized by conserved nucleotides G7, A29, U37, A38, and G48. We expect that this study can provide useful information for understanding the applications of SAM-III in chemical, synthetic RNA biology, and biomedical fields.

Structural properties of Aβ (1–40) peptide in protonation stage of one, two, and three: New insights from the histidine protonation behaviors

Structural properties and aggregation tendency can be significantly influenced by histidine behaviors (histidine on Nδ-H state is defined as δ, likewise, Nε-H: ε and both Nδ-H and Nε-H: p). In current study, we investigated structural properties of Aβ(1–40) peptide during protonation evolution stage of one, two, and three by total 19 independent replica exchange molecular dynamics simulations using implicit solvent. Our results show that any kind of protonated state will promote β-sheet structure formation in comparison with deprotonated (εεε). With increase in number of protonation, the lowest β-sheet content increased. The highest averaged β-sheet structure content was detected in (δpδ) (46.0 %), (εpp) (36.8 %), and (ppp) (16.0 %) in each protonation stage. With three β-strand structures, (δpδ) shows more stable features and high hydrophobic properties. Further analysis confirmed that H13 and H14 are more important than H6. Specifically, H13 and H14 have a synergistic effect for structural formations by controlling H-bond networks in H13(p) with V39/V40 and H14(p/δ) with G37/G38. Finally, the Pearson correlation coefficient results confirmed that experimental result (ref. 44) is corresponding to our (εpp) system. Our current study will be conducive to understanding the effects of the histidine behaviors, it provides new insights for exploration protein folding and misfolding processes.

Prediction of Aptamer-Small-Molecule Interactions Using Metastable States from Multiple Independent Molecular Dynamics Simulations.

Understanding aptamer-ligand interactions is necessary to rationally design aptamer-based systems. Commonly used in silico tools have proven to be accurate to predict RNA and DNA oligonucleotide tertiary structures. However, given the complexity of nucleic acids, the most thermodynamically stable conformation is not necessarily the one with the highest affinity for a specific ligand. Because many metastable states may coexist, it remains challenging to predict binding sites through molecular docking simulations using available computational pipelines. In this study, we used independent simulations to broaden the conformational diversity sampled from DNA initial models of distinct stability and assessed the binding affinity of selected metastable representative structures. In our results, utilizing multiple metastable conformations for molecular docking analysis helped identify structures favorable for ligand binding and accurately predict the binding sites. Our workflow was able to correctly identify the binding sites of the characterized adenosine monophosphate and l-argininamide aptamers. Additionally, we demonstrated that our pipeline can be used to aid the design of competition assays that are conducive to aptasensing strategies using an uncharacterized aflatoxin B1 aptamer. We foresee that this approach may help rationally design effective and truncated aptamer sequences interacting with protein biomarkers or small molecules of interest for drug design and sensor applications.

Rational design of thermophilic CYP119 for progesterone hydroxylation by in silico mutagenesis and docking screening

Steroid-based chemicals can affect the metabolism, immune functions, and development of sexual characteristics. Because of these effects, steroid derivatives are widely used in the pharmaceutical industry. Progesterone is a steroid-based hormone that mainly controls the ovulation period of women but is also a precursor molecule for the synthesis of important hormones like testosterone and cortisone. Cytochrome P450 (CYP) enzymes are important for the production of hydroxyprogesterones in the industry since they can catalyze regio- and enantioselective hydroxylation reactions. Although human CYP enzymes can catalyze hydroxyprogesterone synthesis with high selectivity, these enzymes are membrane bound, which limits their application for industrial production. CYP119 is a soluble and thermophilic enzyme from the archaea Sulfolobus acidocaldarius. Even though the native substrate of the enzyme is not known, CYP119 can catalyze styrene epoxidation, lauric acid hydroxylation, and Amplex®Red peroxidation. In this work, an in silico mutagenesis approach was used to design CYP119 mutants with high progesterone affinity. Energy scores of progesterone docking simulations were used for the design and elimination of single, double, and triple mutants of CYP119. Among designed 674 mutants, five of them match the criteria for progesterone hydroxylation. The most common mutation of these five mutants, L69G mutant was analyzed using independent molecular dynamics (MD) simulations in comparison with the wild-type (WT) enzyme. L69G CYP119, was expressed and isolated from Escherichia coli; it showed 800-fold higher affinity for progesterone compared to WT CYP119. L69G CYP119 also catalyzed progesterone hydroxylation. The novel designed enzyme L69G CYP119 is a potential versatile biocatalyst for progesterone hydroxylation that is expected to be stable under industrial production conditions.