Assessing AMBER force fields for protein folding in an implicit solvent

Highly Efficient Biosynthesis of Rebaudioside M8 through Structure-Guided Engineering of Glycosyltransferase UGT94E13

Given the low-calorie, high-sweetness characteristics of steviol glycosides (SGs), developing SGs with improved taste profiles is a key focus. Rebaudioside M8 (Reb M8), a novel non-natural SG derivative obtained through glycosylation at the C-13 position of rebaudioside D (Reb D) using glycosyltransferase UGT94E13, holds promise for further development due to its enhanced sweetness. However, the low catalytic activity of UGT94E13 hampers further research and commercialization. This study aimed to improve the enzymatic activity of UGT94E13 through semirational design, and a variant UGT94E13-F169G/I185G was obtained with the catalytic activity improved by 13.90 times. A cascade reaction involving UGT94E13-F169G/I185G and sucrose synthase AtSuSy was established to recycle uridine diphosphate glucose, resulting in an efficient preparation of Reb M8 with a yield of 98%. Moreover, according to the analysis of the distances between the substrate Reb D and enzymes as well as between Reb D and the glucose donor through molecular dynamics simulations, it is found that the positive effect of shortening the distance on glycosylation reaction activity accounts for the improved catalytic activity of UGT94E13-F169G/I185G. Therefore, this study addresses the bottleneck in the efficient production of Reb M8 and provides a foundation for its widespread application in the food industry.

Atomic Insight into the Enzymatic Selectivity of Acetyltransferase for Endogenous Polyamines

The N1-Spermidine/spermine acetyltransferase (SSAT) serves as the rate-limiting enzyme in the polyamine metabolism pathway, specifically catalyzing the acetylation of spermidine, spermine, and other specific polyamines. The source of its enzymatic selectivity remains elusive. Here, we used quantum mechanics and molecular mechanics simulations combined with various technologies to explore the enzymatic mechanism of SSAT for endogenous polyamines from an atomic perspective. The static binding and chemical transformation were considered. The binding affinity was identified to be dependent on protonated state of polyamine. The order of the binding affinity for Spm, Spd, and Put is consistent with the experimental results, which is also verified by the dynamic separation of polyamine and SSAT. Hydrogen bond interactions and salt bridges contribute most, and the common hot residues were identified. In addition, the transfer of acetyl and proton between polyamine and AcCoA was discovered to follow a concert mechanism, and thermodynamic properties are responsible for the catalytic efficiency of SSAT. This work may be helpful for development of polyamine derivatives based on catalysis to regulate polyamine metabolism.

Exploring Structural Insights of Aβ42 and α-Synuclein Monomers and Heterodimer: A Comparative Study Using Implicit and Explicit Solvent Simulations

Protein misfolding, aggregation, and fibril formation play a central role in the development of severe neurological disorders, including Alzheimer's and Parkinson's diseases. The structural stability of mature fibrils in these diseases is of great importance, as organisms struggle to effectively eliminate amyloid plaques. To address this issue, it is crucial to investigate the early stages of fibril formation when monomers aggregate into small, toxic, and soluble oligomers. However, these structures are inherently disordered, making them challenging to study through experimental approaches. Recently, it has been shown experimentally that amyloid-β 42 (Aβ42) and α-synuclein (α-Syn) can coassemble. This has motivated us to investigate the interaction between their monomers as a first step toward exploring the possibility of forming heterodimeric complexes. In particular, our study involves the utilization of various Amber and CHARMM force-fields, employing both implicit and explicit solvent models in replica exchange and conventional simulation modes. This comprehensive approach allowed us to assess the strengths and weaknesses of these solvent models and force fields in comparison to experimental and theoretical findings, ensuring the highest level of robustness. Our investigations revealed that Aβ42 and α-Syn monomers can indeed form stable heterodimers, and the resulting heterodimeric model exhibits stronger interactions compared to the Aβ42 dimer. The binding of α-Syn to Aβ42 reduces the propensity of Aβ42 to adopt fibril-prone conformations and induces significant changes in its conformational properties. Notably, in AMBER-FB15 and CHARMM36m force fields with the use of explicit solvent, the presence of Aβ42 significantly increases the β-content of α-Syn, consistent with the experiments showing that Aβ42 triggers α-Syn aggregation. Our analysis clearly shows that although the use of implicit solvent resulted in too large compactness of monomeric α-Syn, structural properties of monomeric Aβ42 and the heterodimer were preserved in explicit-solvent simulations. We anticipate that our study sheds light on the interaction between α-Syn and Aβ42 proteins, thus providing the atom-level model required to assess the initial stage of aggregation mechanisms related to Alzheimer's and Parkinson's diseases.

Transformable nano-antibiotics for mechanotherapy and immune activation against drug-resistant Gram-negative bacteria

The dearth of antibiotic candidates against Gram-negative bacteria and the rise of antibiotic resistance create a global health concern. The challenge lies in the unique Gram-negative bacterial outer membrane that provides the impermeable barrier for antibiotics and sequesters antigen presentation. We designed a transformable nano-antibiotics (TNA) that can transform from nontoxic nanoparticles to bactericidal nanofibrils with reasonable rigidity (Young's modulus, 21.6 ± 5.9 MPa) after targeting β-barrel assembly machine A (BamA) and lipid polysaccharides (LPSs) of Gram-negative bacteria. After morphological transformation, the TNA can penetrate and damage the bacterial envelope, disrupt electron transport and multiple conserved biosynthetic and metabolic pathways, burst bacterial antigen release from the outer membrane, and subsequently activate the innate and adaptive immunity. TNA kills Gram-negative bacteria in vitro and in vivo with undetectable resistance through multiple bactericidal modes of action. TNA treatment-induced vaccination results in rapid and long-lasting immune responses, protecting against lethal reinfections.

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.

Conformations and Solvation of Synthetic Polymers in Water by Generalized Born Implicit-Solvent Molecular Dynamics Simulations: Stereoisomers of Poly(acrylic acid) and Poly(methacrylic acid)

We present the GB-OBC model as an approach for implicit-solvent MD simulations of a synthetic macromolecule in water. The model is tested and found to be successful in reproducing the chain dimensions and predicting the free energy of solvation of carboxylic acid vinyl polymers. The influence of stereochemistry and the hydrophobic nature of the polymer was investigated as a function of chain length (20 < N < 600) for poly(acrylic acid) (PAA) and poly(methacrylic acid) (PMA). The dimensionless parameters of the GB-OBC model were parameterized to be applicable to PAA and PMA. Scaling relations for chain dimensions obtained using implicit-solvent MD simulations in this study are in good agreement with those from experiments, theory of solvated chains in good solvents, and all-atom MD simulations in explicit water. Results show that ⟨R_g²⟩/NL² is greater for the atactic chain as compared to the isotactic chain, for PAA as well as PMA. ⟨R_g²⟩/NL² values of chains attain constancy in water for N = 200, with the values being greater for PMA. The PMA chain is conformationally more perturbed than the PAA chain, for both isotactic and atactic stereochemistry. The solvation free energy ΔG_hyd of PAA and PMA in water is negative for all chain lengths (N = 20-600) and becomes more favorable with an increase in molecular weight. The ΔG_hyd values for isotactic and atactic chains are identical at lower values of N but differ slightly for N > 300. Irrespective of the hydrophobic nature of the polymer, the atactic chain is thermodynamically more soluble in water as compared to the isotactic chain. The isotactic chain is less hydrophilic as compared to the atactic chain due to the closer proximity of the COOH groups along the backbone. This implicit solvent method is an effective way to accurately simulate the configurational properties and solvation of synthetic polymers in water.

Machine learning based implicit solvent model for aqueous-solution alanine dipeptide molecular dynamics simulations

Inspired by the recent work from Noé and coworkers on the development of machine learning based implicit solvent model for the simulation of solvated peptides [Chen et al., J. Chem. Phys., 2021, 155, 084101], here we report another investigation of the possibility of using machine learning (ML) techniques to "derive" an implicit solvent model directly from explicit solvent molecular dynamics (MD) simulations. For alanine dipeptide, a machine learning potential (MLP) based on the DeepPot-SE representation of the molecule was trained to capture its interactions with its average solvent environment configuration (ASEC). The predicted forces on the solute deviated only by an RMSD of 0.4 kcal mol-1 Å-1 from the reference values, and the MLP-based free energy surface differed from that obtained from explicit solvent MD simulations by an RMSD of less than 0.9 kcal mol-1. Our MLP training protocol could also accurately reproduce combined quantum mechanical molecular mechanical (QM/MM) forces on the quantum mechanical (QM) solute in ASEC environment, thus enabling the development of accurate ML-based implicit solvent models for ab initio-QM MD simulations. Such ML-based implicit solvent models for QM calculations are cost-effective in both the training stage, where the use of ASEC reduces the number of data points to be labelled, and the inference stage, where the MLP can be evaluated at a relatively small additional cost on top of the QM calculation of the solute.

New Insights into the Structural and Binding Properties on Aβ Mature Fibrils Due to Histidine Protonation Behaviors

Histidine tautomeric behaviors have been considered origin factors for controlling the structure and aggregation properties of misfolding peptides. Except for tautomeric behaviors, histidine protonation behaviors definitely have the same capacities due to the net charge changes and the various N/N-H orientations on imidazole rings. However, such phenomena are still unknown. In the current study, Aβ mature fibrils substituted with various protonation states were performed by molecular dynamics simulations to investigate the structure and binding properties. Our results show that all kinds of protonation states can increase the ΔG1 stability and decrease ΔG2 and ΔG3 stabilities. A significantly higher averaged β-sheet content was detected in (εεp), (εpp), and (ppp) fibrils in one, two, and three protonation stages, respectively. Impressively, we found that the substituted fibril with specific protonated states can control the N-terminus structural properties. Further analysis confirmed that H6 and H13 are more important than H14 since the H-bond donor and receptor cooperate among C1/C3/C8_H6, C1/C3/C8_H13, and C1/C3/C8_E11. Furthermore, the mechanism of protonation behaviors was discussed. The current study is helpful for understanding the histidine protonation behaviors on one, two, and three protonation stages, which provides new horizons for exploring the origin of protein folding and misfolding.

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 N^δ-H state is defined as δ, likewise, N^ε-H: ε and both N^δ-H and N^ε-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.

Exploiting Sequence-Dependent Rotamer Information in Global Optimization of Proteins

Rotamers, namely amino acid side chain conformations common to many different peptides, can be compiled into libraries. These rotamer libraries are used in protein modeling, where the limited conformational space occupied by amino acid side chains is exploited. Here, we construct a sequence-dependent rotamer library from simulations of all possible tripeptides, which provides rotameric states dependent on adjacent amino acids. We observe significant sensitivity of rotamer populations to sequence and find that the library is successful in locating side chain conformations present in crystal structures. The library is designed for applications with basin-hopping global optimization, where we use it to propose moves in conformational space. The addition of rotamer moves significantly increases the efficiency of protein structure prediction within this framework, and we determine parameters to optimize efficiency.

Probing the effect of NEK7 and cofactor interactions on dynamics of NLRP3 monomer using molecular simulation

The NLRP3 inflammasome is a cytoplasmic complex that regulates the activation of inflammatory cytokines and, given its implication in a range of diseases, is an important therapeutic target. The cofactor ATP and the centrosomal kinase NEK7 are important for NLRP3 activation. Here we have constructed and simulated computational models of full‐length monomeric NLRP3 to shed light on the importance of NEK7 and cofactor interactions for its conformation and dynamics in aqueous solution. We find that molecular dynamics simulation reproduces well the features of the recently published cryo‐EM structure of the ADP‐bound NLRP3–NEK7 complex; on the removal of NEK7, the NLRP3 molecule adopts a more compact closed form during simulations. Replacement of ADP by ATP promotes a rearrangement of hydrogen‐bonding interactions, domain interfaces, and a degree of opening of the NLRP3 conformation. We also examine the dynamics of an acidic loop of the LRR domain of NLRP3, which samples in a region observed in the NEK7‐bound cryo‐EM structure but not in an oligomeric form of inactive NLRP3. During the molecular dynamics simulations of NLRP3, we find some plasticity in its topology that suggests access routes for ATP to the cofactor pocket not immediately evident from the existing NEK7‐bound cryo‐EM structure. These computed dynamical trajectories of NLRP3 provide insight into coordinates of deformation that may be key for cofactor binding and inflammasome activation.

Evaluating the accuracy of the AMBER protein force fields in modeling dihydrofolate reductase structures: misbalance in the conformational arrangements of the flexible loop domains

Protein flexible loop regions were once thought to be simple linkers between other more functional secondary structural elements. However, as it becomes clearer that these loop domains are critical players in a plethora of biological processes, accurate conformational sampling of 3D loop structures is vital to the advancement of drug design techniques and the overall growth of knowledge surrounding molecular systems. While experimental techniques provide a wealth of structural information, the resolution of flexible loop domains is sometimes low or entirely absent due to their complex and dynamic nature. This highlights an opportunity for de novo structure prediction using in silico methods with molecular dynamics (MDs). This study evaluates some of the AMBER protein force field's (ffs) ability to accurately model dihydrofolate reductase (DHFR) conformations, a protein complex characterized by specific arrangements and interactions of multiple flexible loops whose conformations are determined by the presence or absence of bound ligands and cofactors. Although the AMBER ffs, including ff19SB, studied well model most protein structures with rich secondary structure, results obtained here suggest the inability to significantly sample the expected DHFR loop-loop conformations - of the six distinct protein-ligand systems simulated, a majority lacked consistent stabilization of experimentally derived metrics definitive the three enzyme conformations. Although under-sampling and the chosen ff parameter combinations could be the cause, given past successes with these MD approaches for many protein systems, this suggests a potential misbalance in available ff parameters required to accurately predict the structure of multiple flexible loop regions present in proteins.Communicated by Ramaswamy H. Sarma.

Combination of multiple methods and views for recognition, transportation, and structure-guided modification of lysine-specific demethylase phenylcyclopropylamine inhibitor

Lysine-Specific Demethylase 1 (LSD1) is a typical histone-specific demethylase, which plays an important role in protein methylation modification. It is a member of the amine oxidase family (MAO) that specifically removes methyl groups from monomethylated H3K4, dimethylated H3K4 and H3K9 sites associated with tumorigenesis. Phenylcyclopropylamine derivatives are a class of specific LSD1 inhibitors, drawing attention due to their high efficiency. Here, extensive molecular dynamics (MD) simulations are combined with a three-dimensional quantitative structure-activity relationship (3D-QSAR) in order to design a new phenylcyclopropylamine inhibitor from multiple perspectives. In a ligand-oriented point of view, a 3D-QSAR model with comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA) can be built based on the 55 phenylcyclopropylamine compounds targeting LSD1 obtained experimentally. The aromatic and piperazine rings are identified as the potential key groups regulating the activity of the compounds. In an interaction-oriented view, the representative compound is defined with the highest inhibitory efficiency. The binding and delivery mechanism and conformational dependence of activity, including channel and dynamic properties, are studied using RAMD and umbrella sampling technologies. The direct hydrogen bond and conjugated interactions are identified as a major driving force in this procedure. The dominant region of the phenylcyclopropylamine influences the free energy and detects the key residues in recognition and delivery. On the basis of both the ligand and interaction, a series of new inhibitor structures were designed, and two of them showed better efficiency. In order to select the inhibitor with a longer residence time, a comparison is conducted between the designed inhibitors and the experimentally obtained inhibitor from the perspective of static binding and dynamic delivery properties. This work creates new guidance for the phenylcyclopropylamine inhibitor design of LDS1 by combining the ligand and receptor, considering both static and dynamic properties. This scheme could be applied in other inhibitor design systems.

Bovine serum albumin with gallic acid: Molecular modeling and physicochemical profiling

Introduction. Gallic acid is a biologically active natural compound with strong antioxidant properties. Gallic acid is highly soluble and stable. It is known to increase the thermal stability of protein. However, its bioavailability is low, but interaction with proteins can solve this problem. Bovine serum albumin can bind various ligands, including polyphenols. The resulting complex of gallic acid and bovine serum albumin can become a promising functional food additive. Study objects and methods. This research featured in silico molecular modeling of gallic acid and bovine serum albumin using the HyperChem program. The methods of infrared spectrometry, potentiometry, and sodium dodecyl-sulfate polyacrylamide gel electrophoresis (SDS-PAGE) made it possible to describe the physicochemical profile of the complex. Results and discussion. The molecular modeling confirmed that hydrophobic interactions were responsible for the chemical bond between gallic acid and bovine serum albumin. The SDS-PAGE test showed that the protein molecule remained intact. The reducing properties of the complex grew as the concentration of gallic acid increased. At 100 mg/L of gallic acid, the reducing properties were 7.8 ± 1.3 mg/L equivalent of gallic acid. At 200 and 300 mg/L, the values reached 15.90 ± 2.65 and 23.30 ± 5.05 mg/L, respectively. The IR spectrometry revealed a significant difference between the samples with different concentrations of gallic acid. Conclusion. The research managed to predict the properties of the complex of bovine serum albumin and gallic acid during its formation. The resulting complex had the highest reducing properties at 0.69 g of bovine serum albumin and 300 mg of gallic acid. The obtained parameters can be used in the food industry to develop new food additives.

Forcefield evaluation and accelerated molecular dynamics simulation of Zn(II) binding to N-terminus of amyloid-β

We report conventional and accelerated molecular dynamics simulation of Zn(II) bound to the N-terminus of amyloid-β. By comparison against NMR data for the experimentally determined binding mode, we find that certain combinations of forcefield and solvent model perform acceptably in describing the size, shape and secondary structure, and that there is no appreciable difference between implicit and explicit solvent models. We therefore used the combination of ff14SB forcefield and GBSA solvent model to compare the result of different binding modes of Zn(II) to the same peptide, using accelerated MD to enhance sampling and comparing the free peptide simulated in the same way. We show that Zn(II) imparts significant rigidity to the peptide, disrupts the secondary structure and pattern of salt bridges seen in the free peptide, and induces closer contact between residues. Free energy surfaces in 1 or 2 dimensions further highlight the effect of metal coordination on peptide's spatial extent. We also provide evidence that accelerated MD provides improved sampling over conventional MD by visiting as many or more configurations in much shorter simulation times.

Conformational Transitions of Amyloid-β: A Langevin and Generalized Langevin Dynamics Simulation Study

The dynamics of conformational transitions of the disordered protein, amyloid-β, is studied via Langevin and generalized Langevin dynamics simulations. The transmission coefficient for the unfold-misfold transition of amyloid-β is calculated from multiple independent trajectories that originate at the transition state with different initial velocities and are directly correlated to Kramers and Grote-Hynes theories. For lower values of the frictional coefficient, a well-defined rate constant is obtained, whereas, for higher values, the transmission coefficient decays with time, indicating a breakdown of the Kramers and Grote-Hynes theories and the emergence of a dynamic disorder, which demonstrates the presence of multiple local minima in the misfolding potential energy surface. The calculated free energy profile describes a two-state transition of amyloid-β in the energy landscape. The transition path time distribution computed from these simulations is compared with the related experimental and theoretical results for the unfold-misfold transition of amyloid-β. The high free energy barrier for this transition confirms the misfolding of amyloid-β. These findings offer an insight into the dynamics of the unfold-misfold transition of this protein.

Sampling of the conformational landscape of small proteins with Monte Carlo methods

Computer simulation provides an increasingly realistic picture of large-scale conformational change of proteins, but investigations remain fundamentally constrained by the femtosecond timestep of molecular dynamics simulations. For this reason, many biologically interesting questions cannot be addressed using accessible state-of-the-art computational resources. Here, we report the development of an all-atom Monte Carlo approach that permits the modelling of the large-scale conformational change of proteins using standard off-the-shelf computational hardware and standard all-atom force fields. We demonstrate extensive thermodynamic characterization of the folding process of the α-helical Trp-cage, the Villin headpiece and the β-sheet WW-domain. We fully characterize the free energy landscape, transition states, energy barriers between different states, and the per-residue stability of individual amino acids over a wide temperature range. We demonstrate that a state-of-the-art intramolecular force field can be combined with an implicit solvent model to obtain a high quality of the folded structures and also discuss limitations that still remain.

Molecular Dynamics Revealing a Detour-Forward Release Mechanism of Tacrine: Implication for the Specific Binding Characteristics in Butyrylcholinesterase

Butyrylcholinesterase (BChE) is a non-specific enzyme with clinical pharmacological and toxicological significance, which was a renewed interest as therapeutic target in Alzheimer's disease (AD) nowadays. Here, all-atom molecular dynamics simulations of butyrylcholinesterase with tacrine complex were designed to characterize inhibitor binding modes, strengths, and the hydrogen-bond dependent non-covalent release mechanism. Four possible release channels were identified, and the most favorable channel was determined by random acceleration molecular dynamics molecular dynamics (RAMD MD) simulations. The thermodynamic and dynamic properties as well as the corresponding Detour-forward delivery mechanism were determined according to the classical molecular dynamics (MD) simulations accompanied with umbrella sampling. The free energy barrier of the tacrine release process for the most beneficial pathway is about 10.95 kcal/mol, which is related to the non-covalent interactions from the surrounding residues, revealing the specific binding characteristics in the active site. The residues including Asp70, Ser79, Trp82, Gly116, Thr120, Tyr332, and His438 were identified to play major roles in the stabilization of tacrine in the pocket of BChE, where hydrogen bonding and π-π interactions are significant factors. Tyr332 and Asp70, which act as gate keepers, play crucial roles in the substrate delivery. The present results provide a basic understanding for the ligand transport mechanism depending on the BChE enzymatic environment, which is useful for the design of BChE inhibitors in the future.

Structural characterization of a dimeric complex between the short cytoplasmic domain of CEACAM1 and the pseudo tetramer of S100A10-Annexin A2 using NMR and molecular dynamics

AIIt, a heterotetramer of S100A10 (P11) and Annexin A2, plays a key role in calcium dependent, membrane associations with a variety of proteins. We previously showed that AIIt interacts with the short cytoplasmic domain (12 amino acids) of CEACAM1 (CEACAM1-SF). Since the cytoplasmic domains of CEACAM1 help regulate the formation of cis- or trans-dimers at the cell membrane, we investigated the possible role of their association with AIIt in this process. Using NMR and molecular dynamics, we show that AIIt and its pseudoheterodimer interacts with two molecules of short cytoplasmic domain isoform peptides, and that interaction depends on the binding motif 454-Phe-Gly-Lys-Thr-457 where Phe-454 binds in a hydrophobic pocket of AIIt, the null mutation Phe454Ala reduces binding by 2.5 fold, and the pseudophosphorylation mutant Thr457Glu reduces binding by three fold. Since these two residues in CEACAM1-SF were also found to play a role in the binding of calmodulin and G-actin at the membrane, we hypothesize a sequential set of three interactions are responsible for regulation of cis- to trans-dimerization of CEACAM1. The hydrophobic binding pocket in AIIt corresponds to a previously identified binding pocket for a peptide found in SMARCA3 and AHNAK, suggesting a conserved functional motif in AIIt allowing multiple proteins to reversibly interact with integral membrane proteins in a calcium dependent manner.

Using the generalized Born surface area model to fold proteins yields more effective sampling while qualitatively preserving the folding landscape

Protein folding is a long-standing problem and has been widely investigated using molecular dynamics simulations with both explicit and implicit solvents. However, to what extent the folding mechanisms observed in two water models agree remains an open question. In this study, ab initio folding simulations of ten proteins with different topologies are performed in two combinations of force fields and water models (ff14SB+TIP3P and ff14SBonlysc+GB-Neck2). Interestingly, the latter combination not only folds more proteins but also provides a better balance of different secondary structures than the former in the same number of integration time steps. More importantly, the folding pathways found in the two types of simulations are conserved and they may only differ in their weights. Our results suggest that simulations with an implicit solvent may also be suitable for the investigation of the mechanism of protein folding.

Peptide science: A "rule model" for new generations of peptidomimetics

Peptides have been heavily investigated for their biocompatible and bioactive properties. Though a wide array of functionalities can be introduced by varying the amino acid sequence or by structural constraints, properties such as proteolytic stability, catalytic activity, and phase behavior in solution are difficult or impossible to impart upon naturally occurring α-L-peptides. To this end, sequence-controlled peptidomimetics exhibit new folds, morphologies, and chemical modifications that create new structures and functions. The study of these new classes of polymers, especially α-peptoids, has been highly influenced by the analysis, computational, and design techniques developed for peptides. This review examines techniques to determine primary, secondary, and tertiary structure of peptides, and how they have been adapted to investigate peptoid structure. Computational models developed for peptides have been modified to predict the morphologies of peptoids and have increased in accuracy in recent years. The combination of in vitro and in silico techniques have led to secondary and tertiary structure design principles that mirror those for peptides. We then examine several important developments in peptoid applications inspired by peptides such as pharmaceuticals, catalysis, and protein-binding. A brief survey of alternative backbone structures and research investigating these peptidomimetics shows how the advancement of peptide and peptoid science has influenced the growth of numerous fields of study. As peptide, peptoid, and other peptidomimetic studies continue to advance, we will expect to see higher throughput structural analyses, greater computational accuracy and functionality, and wider application space that can improve human health, solve environmental challenges, and meet industrial needs. STATEMENT OF SIGNIFICANCE: Many historical, chemical, and functional relations draw a thread connecting peptides to their recent cognates, the "peptidomimetics". This review presents a comprehensive survey of this field by highlighting the width and relevance of these familial connections. In the first section, we examine the experimental and computational techniques originally developed for peptides and their morphing into a broader analytical and predictive toolbox. The second section presents an excursus of the structures and properties of prominent peptidomimetics, and how the expansion of the chemical and structural diversity has returned new exciting properties. The third section presents an overview of technological applications and new families of peptidomimetics. As the field grows, new compounds emerge with clear potential in medicine and advanced manufacturing.

A novel folding pathway of the villin headpiece subdomain HP35

The villin headpiece subdomain (HP35) is a fast-folding protein with 35 residues and its folding pathways have been extensively studied experimentally and theoretically but remain controversial. While experiments showed that HP35 might have multiple folding pathways, most theoretical studies only found one major pathway, although a few theoretical studies revealed two. Here we report our results of molecular dynamics simulations of HP35 folding by using the newest AMBER ff14SB force field and show that HP35 has a novel folding pathway in addition to the two pathways shown previously. We also study the mechanism of determining the folding pathways and found that the dynamics of Helix2 may play a special role in the folding of HP35. Our results may be helpful to understand the folding mechanism of HP35 further.

Computational Estimation of Microsecond to Second Atomistic Folding Times

Despite the development of massively parallel computing hardware including inexpensive graphics processing units (GPUs), it has remained infeasible to simulate the folding of atomistic proteins at room temperature using conventional molecular dynamics (MD) beyond the microsecond scale. Here, we report the folding of atomistic, implicitly solvated protein systems with folding times τ ranging from ∼10 μs to ∼100 ms using the weighted ensemble (WE) strategy in combination with GPU computing. Starting from an initial structure or set of structures, WE organizes an ensemble of GPU-accelerated MD trajectory segments via intermittent pruning and replication events to generate statistically unbiased estimates of rate constants for rare events such as folding; no biasing forces are used. Although the variance among atomistic WE folding runs is significant, multiple independent runs are used to reduce and quantify statistical uncertainty. Folding times are estimated directly from WE probability flux and from history-augmented Markov analysis of the WE data. Three systems were examined: NTL9 at low solvent viscosity (yielding τf = 0.8-9 μs), NTL9 at water-like viscosity (τf = 0.2-2 ms), and Protein G at low viscosity (τf = 3-200 ms). In all cases, the folding time, uncertainty, and ensemble properties could be estimated from WE simulation; for Protein G, this characterization required significantly less overall computing than would be required to observe a single folding event with conventional MD simulations. Our results suggest that the use and calibration of force fields and solvent models for precise estimation of kinetic quantities is becoming feasible.

Rotamer Dynamics: Analysis of Rotamers in Molecular Dynamics Simulations of Proteins

Given by χ torsional angles, rotamers describe the side-chain conformations of amino acid residues in a protein based on the rotational isomers (hence the word rotamer). Constructed rotamer libraries, based on either protein crystal structures or dynamics studies, are the tools for classifying rotamers (torsional angles) in a way that reflect their frequency in nature. Rotamer libraries are routinely used in structure modeling and evaluation. In this perspective article, we would like to encourage researchers to apply rotamer analyses beyond their traditional use. Molecular dynamics (MD) of proteins highlight the in silico behavior of molecules in solution and thus can identify favorable side-chain conformations. In this article, we used simple computational tools to study rotamer dynamics (RD) in MD simulations. First, we isolated each frame in the MD trajectories in separate Protein Data Bank files via the cpptraj module in AMBER. Then, we extracted torsional angles via the Bio3D module in R language. The classification of torsional angles was also done in R according to the penultimate rotamer library. RD analysis is useful for various applications such as protein folding, study of rotamer-rotamer relationship in protein-protein interaction, real-time correlation between secondary structures and rotamers, study of flexibility of side chains in binding site for molecular docking preparations, use of RD as guide in functional analysis and study of structural changes caused by mutations, providing parameters for improving coarse-grained MD accuracy and speed, and many others. Major challenges facing RD to emerge as a new scientific field involve the validation of results via easy, inexpensive wet-lab methods. This realm is yet to be explored.

Ligand binding effects on the activation of the EGFR extracellular domain

The epidermal growth factor receptor (EGFR) is one of the most common target proteins in anti-cancer therapy. The binding of the EGF ligand to the EGFR extracellular domain (EGFR-ECD) promotes its inactive-to-active conformational transition (activation) but the relevant detailed mechanism remains elusive still. Here, the structural characterization and energetics of the EGFR-ECD conformational transition with and without the binding of the EGF are quantitatively explored using an innovative enhanced sampling MD simulation method. Intriguingly, the EGF offers hydrophobic interactions (e.g., EGF residues of Tyr44 and Leu47) and electrostatic interactions (e.g., the EGF residues of Glu5, Asp11, Asp17, and Arg41) to play a dominant role in dragging domain III to close the ligand binding domain gap. Subsequently, the correlation between domains III and II is enhanced through salt-bridges among Glu376, Arg403, and Arg405 from domain III and Glu293, Glu295, and Arg300 from domain II. Finally, the structural bending of domain II is regulated to facilitate the disengagement of domain II from domain IV. In this regard, the functional conformational transition of EGFR-ECD is a consequence of the cooperative motion of protein domains driven by the EGF ligand binding. The present study shows a detailed scenario of the EGF induced activation of EGFR-ECD and provides valuable information for drug discovery targeting the EGFR.

Nonnative contact effects in protein folding

The folding simulations of three ββα-motifs and β-barrel structured proteins (NTL9, NuG2b, and CspA) were performed to determine the important roles of native and nonnative contacts in protein folding.