Revisiting the Ramachandran plot: hard-sphere repulsion, electrostatics, and H-bonding in the alpha-helix

Immunoinformatic based designing of potential immunogenic novel mRNA and peptide-based prophylactic vaccines against H5N1 and H7N9 avian influenza viruses

Influenza viruses are the most common cause of serious respiratory illnesses worldwide and are responsible for a significant number of annual fatalities. Therefore, it is crucial to look for new immunogenic sites that might trigger an effective immune response. In the present study, bioinformatics tools were used to design mRNA and multiepitope-based vaccines against H5N1 and H7N9 subtypes of avian influenza viruses. Several Immunoinformatic tools were employed to extrapolate T and B lymphocyte epitopes of HA and NA proteins of both subtypes. The molecular docking approach was used to dock the selected HTL and CTL epitopes with the corresponding MHC molecules. Eight (8) CTL, four (4) HTL, and Six (6) linear B cell epitopes were chosen for the structural arrangement of mRNA and of peptide-based prophylactic vaccine designs. Different physicochemical characteristics of the selected epitopes fitted with suitable linkers were analyzed. High antigenic, non-toxic, and non-allergenic features of the designed vaccines were noted at a neutral physiological pH. Codon optimization tool was used to check the GC content and CAI value of constructed MEVC-Flu vaccine, which were recorded to be 50.42% and 0.97 respectively. the GC content and CAI value verify the stable expression of vaccine in pET28a + vector. In-silico immunological simulation the MEVC-Flu vaccine construct revealed a high level of immune responses. The molecular dynamics simulation and docking results confirmed the stable interaction of TLR-8 and MEVC-Flu vaccine. Based on these parameters, vaccine constructs can be regarded as an optimistic choice against H5N1 and H7N9 strains of the influenza virus. Further experimental testing of these prophylactic vaccine designs against pathogenic avian influenza strains may clarify their safety and efficacy.Communicated by Ramaswamy H. Sarma.

Riparin II-type benzamides as novel antibiofilm agents against dermatophytes: chemical synthesis, in vitro, ex vivo and in silico evaluation

BACKGROUND

The ability of dermatophytes to develop biofilms in host tissues confers physical and biochemical resistance to antifungal drugs. Therefore, research to find new compounds against dermatophyte biofilm is crucial.

OBJECTIVES

To evaluate the antifungal activity of riparin II (RIP2), nor-riparin II (NOR2) and dinor-riparin II (DINOR2) against Trichophyton rubrum, Microsporum canis and Nannizzia gypsea strains.

METHODS

Initially, we determined the minimum inhibitory concentration (MIC) and minimum fungicidal concentration (MFC) of benzamides. We evaluated the inhibitory effects on the development of dermatophyte biofilms using in vitro and ex vivo models. Finally, we built three-dimensional models of the sulphite pump Ssu1 to investigate the interactions with the benzamides by molecular docking.

RESULTS

RIP2 showed a broad spectrum of activity against T. rubrum, M. canis and N. gypsea, whereas NOR2 and DINOR2 were more selective. Furthermore, the shortening of the carbon chain from RIP2 benzamide to NOR2 and DINOR2 homologs caused a decrease in the MIC values. The benzamides reduced biofilm production and viability in vitro (P < 0.05) at MIC. This result was similar ex vivo in human nail fragments tests, but NOR2 and DINOR2 showed significant results at 2xMIC (P < 0.05). We constructed a model of the Ssu1 protein for each dermatophyte with high similarity. Molecular docking showed that the benzamides obtained higher binding energy values than ciclopirox.

CONCLUSIONS

Our study shows the antibiofilm potential for riparin II-type benzamides as new drugs targeting dermatophytes by inhibiting the Ssu1 protein.

Simulation of oriented NMR spectra: Combining molecular dynamics and chemical shift tensor calculations

Solid state NMR is widely used to study the orientation and other structural features of proteins and peptides in lipid bilayers. Using data obtained by PISEMA (Polarization Inversion Spin Exchange at Magic Angle) experiments, periodic spectral patterns arise from well-aligned α-helical molecules. Significant problems in the interpretation of PISEMA spectra may arise for systems that do not form perfectly defined secondary structures, like α-helices, or the signal pattern is disturbed by molecular motion. Here, we present a new method that combines molecular dynamics simulation with tensorial orientational constraints (MDOC) and chemical shift tensor calculations for the simulation and interpretation of PISEMA-like spectra. The calculations include the spectra arising from non α-helical molecules and molecules with non-uniform intrinsic mobility. In a first step, dipolar or quadrupolar interaction tensors drive molecular rotations and reorientations to obtain the proper mean values as observed in corresponding NMR experiments. In a second step, the coordinate snapshots of the MDOC simulations are geometry optimized with the isotropic 15 N chemical shifts as constraints using Bond Polarization Theory (BPT) to provide reliable 15 N CS tensor data. The averaged dipolar 1 H-15 N couplings and the δzz tensor components can then be combined to simulate PISEMA patterns. We apply this method to the ß-helical peptide gramicidin A (gA) and demonstrate that this method enables the assignment of most PISEMA resonances. In addition, MDOC simulations provide local order parameters for the calculated sites. These local order parameters reveal large differences in backbone mobility between L- and D-amino acids of gA.

Multi-eGO: Model Improvements toward the Study of Complex Self-Assembly Processes

Structure-based models have been instrumental in simulating protein folding and suggesting hypotheses about the mechanisms involved. Nowadays, at least for fast-folding proteins, folding can be simulated in explicit solvent using classical molecular dynamics. However, other self-assembly processes, such as protein aggregation, are still far from being accessible. Recently, we proposed that a hybrid multistate structure-based model, multi-eGO, could help to bridge the gap toward the simulation of out-of-equilibrium, concentration-dependent self-assembly processes. Here, we further improve the model and show how multi-eGO can effectively and accurately learn the conformational ensemble of the amyloid β42 intrinsically disordered peptide, reproduce the well-established folding mechanism of the B1 immunoglobulin-binding domain of streptococcal protein G, and reproduce the aggregation as a function of the concentration of the transthyretin 105-115 amyloidogenic peptide. We envision that by learning from the dynamics of a few minima, multi-eGO can become a platform for simulating processes inaccessible to other simulation techniques.

Disallowed spots in protein structures

Ramachandran (ϕ, ψ) steric map was introduced in 1963 to describe available conformation space for protein structures. Subsequently, residues were observed in high-energy disallowed regions of the map. To unequivocally identify the locations of disallowed conformations of residues, we got 36 noise-free protein structures (resolution ≤1 Å, Rwork/Rfree ≤ 0.10). These stringent criteria were applied to rule out data or model errors or any crystallographic disorders. No disallowed conformation was found in the dataset. Further, we also examined disallowed conformations in a larger dataset (resolution ≤1.5 Å, devoid of any model errors, or disorders). The observed locations of disallowed residues are referred as disallowed spots. These spots include short loops of 3-5 residues, and locations where residues participate in disulfide bonding or intramolecular interactions or inter-molecular interactions with neighboring water, metals or ligands. Conformational sampling revealed that short loops in between secondary structures hardly have any opportunity to relieve from conformational strain. Residues involved in interactions, which provide energetic compensation for high-energy conformational states, were relieved from strain once the causative interaction was removed. The present study aims to identify disallowed spots in the native state of proteins, wherein residues are forced to be trapped in high-energy disallowed conformations. Moreover, it was also observed that pre-Pro, Ser, Asp, trans-Pro, Val, Asn & Gly have higher tendency to occur in disallowed conformation, which could be attributed to factors such as conformational restrictions, residue propensity of secondary structures and compensating sidechain and mainchain interactions, stabilizing turn-mimics.

Revisiting the Ramachandran plot based on statistical analysis of static and dynamic characteristics of protein structures

Ramachandran plots, which describe protein structures by plotting the dihedral angle pairs of the backbone on a two-dimensional plane, have played an important role in structural biology over the past few decades. However, despite continued discovery of new protein structures to date, the Ramachandran plot is still constructed by only a small number of data points, and further it cannot reflect the steric information of proteins. Here, we investigated the secondary structure of proteins in terms of static and dynamic characteristics. As for static feature, the Ramachandran plot was revisited for the dataset consisting of 9,148 non-redundant high-resolution protein structures released in the protein data bank until April 1, 2022. By calculating amino acid propensities, it was found that the proportion of secondary structures with respect to residue depth is directly related to their hydrophobicity. As for dynamic feature, normal mode analysis (NMA) based on an elastic network model (ENM) was carried out for the dataset using our KOSMOS web server (http://bioengineering.skku.ac.kr/kosmos/). All ENM-based NMA results were stored in the KOSMOS database, allowing researchers to use them in various ways. In this process, it was commonly found that high B-factors appeared at the edge of the alpha helix region, which was elucidated by introducing residue depth. In addition, by investigating the change in dihedral angle, it was possible to quantitatively survey the contribution of structural change of protein on the Ramachandran plot. In conclusion, our statistical analysis of protein characteristics will provide insight into a range of protein structural studies.

Recognition and release of uridine and hCNT3: From multivariate interactions to molecular design

As a vital target for the development of novel anti-cancer drugs, human concentrative nucleoside transporter 3 (hCNT3) has been widely concerned. Nevertheless, the lack of a comprehensive understanding of molecular interactions and motion mechanism has greatly hindered the development of novel inhibitors against hCNT3. In this paper, molecular recognition of hCNT3 with uridine was investigated with molecular docking, conventional molecular dynamics (CMD) simulations and adaptive steered molecular dynamics (ASMD) simulations; and then, the uridine derivatives with possibly highly inhibitory activity were designed. The result of CMD showed that more water-mediated H-bonds and lower binding free energy both explained higher recognition ability and transported efficiency of hCNT3. While during the ASMD simulation, nucleoside transport process involved the significant side-chain flip of residues F321 and Q142, a typical substrate-induced conformational change. By considering electronegativity, atomic radius, functional group and key H-bonds factors, 25 novel uridine derivatives were constructed. Subsequently, the receptor-ligand binding free energy was predicted by solvated interaction energy (SIE) method to determine the inhibitor c8 with the best potential performance. This work not only revealed molecular recognition and release mechanism of uridine with hCNT3, but also designed a series of uridine derivatives to obtain lead compounds with potential high activity.

Identification of Novel Arachidonic Acid 15-Lipoxygenase Inhibitors Based on the Bayesian Classifier Model and Computer-Aided High-Throughput Virtual Screening

Ferroptosis is an iron-dependent lipid peroxidative form of cell death that is distinct from apoptosis and necrosis. ALOX15, also known as arachidonic acid 15-lipoxygenase, promotes ferroptosis by converting intracellular unsaturated lipids into oxidized lipid intermediates and is an important ferroptosis target. In this study, a naive Bayesian machine learning classifier with a structure-based, high-throughput screening approach and a molecular docking program were combined to screen for three compounds with excellent target-binding potential. In the absorption, distribution, metabolism, excretion, and toxicity characterization, three candidate molecules were predicted to exhibit drug-like properties. The subsequent molecular dynamics simulations confirmed their stable binding to the targets. The findings indicated that the compounds exhibited excellent potential ALOX15 inhibitor capacity, thereby providing novel candidates for the treatment of inflammatory ischemia-related diseases caused by ferroptosis.

Local Backbone Geometry Plays a Critical Role in Determining Conformational Preferences of Amino Acid Residues in Proteins

The definition of the structural basis of the conformational preferences of the genetically encoded amino acid residues is an important yet unresolved issue of structural biology. In order to gain insights into this intricate topic, we here determined and compared the amino acid propensity scales for different (φ, ψ) regions of the Ramachandran plot and for different secondary structure elements. These propensities were calculated using the Chou–Fasman approach on a database of non-redundant protein chains retrieved from the Protein Data Bank. Similarities between propensity scales were evaluated by linear regression analyses. One of the most striking and unexpected findings is that distant regions of the Ramachandran plot may exhibit significantly similar propensity scales. On the other hand, contiguous regions of the Ramachandran plot may present anticorrelated propensities. In order to provide an interpretative background to these results, we evaluated the role that the local variability of protein backbone geometry plays in this context. Our analysis indicates that (dis)similarities of propensity scales between different regions of the Ramachandran plot are coupled with (dis)similarities in the local geometry. The concept that similarities of the propensity scales are dictated by the similarity of the NCαC angle and not necessarily by the similarity of the (φ, ψ) conformation may have far-reaching implications in the field.

Exploring Nearest Neighbor Interactions and Their Influence on the Gibbs Energy Landscape of Unfolded Proteins and Peptides

The Flory isolated pair hypothesis (IPH) is one of the corner stones of the random coil model, which is generally invoked to describe the conformational dynamics of unfolded and intrinsically disordered proteins (IDPs). It stipulates, that individual residues sample the entire sterically allowed space of the Ramachandran plot without exhibiting any correlations with the conformational dynamics of its neighbors. However, multiple lines of computational, bioinformatic and experimental evidence suggest that nearest neighbors have a significant influence on the conformational sampling of amino acid residues. This implies that the conformational entropy of unfolded polypeptides and proteins is much less than one would expect based on the Ramachandran plots of individual residues. A further implication is that the Gibbs energies of residues in unfolded proteins or polypeptides are not additive. This review provides an overview of what is currently known and what has yet to be explored regarding nearest neighbor interactions in unfolded proteins.

Plant Source Derived Compound Exhibited In Silico Inhibition of Membrane Glycoprotein In SARS-CoV-2: Paving the Way to Discover a New Class of Compound For Treatment of COVID-19

SARS-CoV-2 is the virus responsible for causing COVID-19 disease in humans, creating the recent pandemic across the world, where lower production of Type I Interferon (IFN-I) is associated with the deadly form of the disease. Membrane protein or SARS-CoV-2 M proteins are known to be the major reason behind the lower production of human IFN-I by suppressing the expression of IFNβ and Interferon Stimulated Genes. In this study, 7,832 compounds from 32 medicinal plants of India possessing traditional knowledge linkage with pneumonia-like disease treatment, were screened against the Homology-Modelled structure of SARS-CoV-2 M protein with the objective of identifying some active phytochemicals as inhibitors. The entire study was carried out using different modules of Schrodinger Suite 2020-3. During the docking of the phytochemicals against the SARS-CoV-2 M protein, a compound, ZIN1722 from Zingiber officinale showed the best binding affinity with the receptor with a Glide Docking Score of −5.752 and Glide gscore of −5.789. In order to study the binding stability, the complex between the SARS-CoV-2 M protein and ZIN1722 was subjected to 50 ns Molecular Dynamics simulation using Desmond module of Schrodinger suite 2020-3, during which the receptor-ligand complex showed substantial stability after 32 ns of MD Simulation. The molecule ZIN1722 also showed promising results during ADME-Tox analysis performed using Swiss ADME and pkCSM. With all the findings of this extensive computational study, the compound ZIN1722 is proposed as a potential inhibitor to the SARS-CoV-2 M protein, which may subsequently prevent the immunosuppression mechanism in the human body during the SARS-CoV-2 virus infection. Further studies based on this work would pave the way towards the identification of an effective therapeutic regime for the treatment and management of SARS-CoV-2 infection in a precise and sustainable manner.

Allosteric and transport modulation of human concentrative nucleoside transporter 3 at the atomic scale

Nucleosides are important precursors of nucleotide synthesis in cells, and nucleoside transporters play an important role in many physiological processes by mediating transmembrane transport and absorption. During nucleoside transport, such proteins undergo a significant conformational transition between the outward- and inward-facing states, which leads to alternating access of the substrate-binding site to either side of the membrane. In this work, a variety of molecular simulation methods have been applied to comparatively investigate the motion modes of human concentrative nucleoside transporter 3 (hCNT3) in three states, as well as global and local cavity conformational changes; and finally, a possible elevator-like transport mechanism consistent with experimental data was proposed. The results of the Gaussian network model (GNM) and anisotropic network model (ANM) show that hCNT3 as a whole tends to contract inwards and shift towards a membrane inside, exhibiting an allosteric process that is more energetically favorable than the rigid conversion. To reveal the complete allosteric process of hCNT3 in detail, a series of intermediate conformations were obtained by an adaptive anisotropic network model (aANM). One of the simulated intermediate states is similar to that of a crystal structure, which indicates that the allosteric process is reliable; the state with lower energy is slightly inclined to the inward-facing structure rather than the expected intermediate crystal structure. The final HOLE analysis showed that except for the outward-facing state, the transport channels were gradually enlarged, which was conductive to the directional transport of nucleosides. Our work provides a theoretical basis for the multistep elevator-like transportation mechanism of nucleosides, which helps to further understand the dynamic recognition between nucleoside substrates and hCNT3 as well as the design of nucleoside anticancer drugs.

Tripeptide loop closure: a detailed study of reconstructions based on Ramachandran distributions

Tripeptide loop closure (TLC) is a standard procedure to reconstruct protein backbone conformations, by solving a zero dimensional polynomial system yielding up to 16 solutions. In this work, we first show that multiprecision is required in a TLC solver to guarantee the existence and the accuracy of solutions. We then compare solutions yielded by the TLC solver against tripeptides from the Protein Data Bank. We show that these solutions are geometrically diverse (up to 3å RMSD with respect to the data), and sound in terms of potential energy. Finally, we compare Ramachandran distributions of data and reconstructions for the three amino acids. The distribution of reconstructions in the second angular space (φ2 , ψ2) stands out, with a rather uniform distribution leaving a central void. We anticipate that these insights, coupled to our robust implementation in the (https://sbl.inria.fr/doc/Tripeptide_loop_closure-user-manual.html), will help understanding the properties of TLC reconstructions, with potential applications to the generation of conformations of flexible loops in particular. This article is protected by copyright. All rights reserved.

Molecular Docking Study of Antibiotics, Anti-Inflammatory Drugs and [Eu(TTA)3⋅AMX] Complex as COVID-19 Biomarker through Interaction of Its Main Protease (Mpro)

Coronavirus Acute Respiratory Syndrome (SARS-CoV-2) is a very recent viral infection and has generated one of the world’s biggest problems of all time. There is no scientific evidence and clinical trials to indicate that possible therapies have shown results in suspected or confirmed patients other than the use of immunizations. Given the above, some substances are being studied to be applied to contain their spread and further damage. This work aims to perform an in silico study of amoxicillin, widely known as an antibiotic and used to prevent bacterial infections and a possible biomarker made from a complex with Europium (Eu). It was shown to have the ability to interact with the COVID-19 protein in Mpro protease as ligands. The study was conducted using the AutoDock Vina with Lamarckian genetic model algorithm (GA) combined with the estimation of grid-based energy in rigid and flexible conformation. Compared to affinity energy, amoxicillin presented [Formula: see text][Formula: see text]kcal/mol, which was better than its co-crystallized ligand in the study. The Europium complex, where its synthesis was also demonstrated in this work, presented energy of [Formula: see text][Formula: see text]kcal/mol with hydrogen bonds and possible color change when UV light was applied. For the choice of the best poses in the simulation, the neural network parameter, NNScore2, was used. It can be affirmed that this study is still introductory but promising both in the treatment and identification of the virus.

Compounds Identified from Marine Mangrove Plant (Avicennia alba) as Potential Antiviral Drug Candidates Against WDSV, an In-Silico Approach

Walleye dermal sarcoma virus (WDSV) is a type of retrovirus, which affects most of the adult walleye fishes during the spawning time. The virus causes multiple epithelial tumors on the fish’s skin and fins that are liable for more than 50% of the mortality rate of fish around the world. Till now, no effective antiviral drug or vaccine candidates have been developed that can block the progression of the disease caused by the pathogen. It was found that the 582-amino-acid (aa) residues long internal structural gag polyprotein of the virus plays an important role in virus budding and virion maturation outside of the cell. Inhibition of the protein can block the budding and virion maturation process and can be developed as an antiviral drug candidate against the virus. Therefore, the study aimed to identify potential natural antiviral drug candidates from the tropical mangrove marine plant Avicennia alba, which will be able to block the budding and virion maturation process by inhibiting the activity of the gag protein of the virus. Initially, a homology modeling approach was applied to identify the 3D structure, followed by refinement and validation of the protein. The refined protein structures were then utilized for molecular docking simulation. Eleven phytochemical compounds have been isolated from the marine plant and docked against the virus gag polyprotein. Three compounds, namely Friedlein (CID244297), Phytosterols (CID12303662), and 1-Triacontanol (CID68972) have been selected based on their docking score −8.5 kcal/mol, −8.0 kcal/mol and −7.9 kcal/mol, respectively, and were evaluated through ADME (Absorption, Distribution, Metabolism and Excretion), and toxicity properties. Finally, molecular dynamics (MD) simulation was applied to confirm the binding stability of the protein-ligands complex structure. The ADME and toxicity analysis reveal the efficacy and non-toxic properties of the compounds, where MD simulation confirmed the binding stability of the selected three compounds with the targeted protein. This computational study revealed the virtuous value of the selected three compounds against the targeted gag polyprotein and will be effective and promising antiviral candidates against the pathogen in a significant and worthwhile manner. Although in vitro and in vivo study is required for further evaluation of the compounds against the targeted protein.

Determination of amino acids that favour the αL region using Ramachandran propensity plots. Implications for α-sheet as the possible amyloid intermediate

In amyloid diseases an insoluble amyloid fibril forms via a soluble oligomeric intermediate. It is this intermediate that mediates toxicity and it has been suggested, somewhat controversially, that it has the α-sheet structure. Nests and α-strands are similar peptide motifs in that alternate residues lie in the α_R and γ_L regions of the Ramachandran plot for nests, or α_R and α_L regions for α-strands. In nests a concavity is formed by the main chain NH atoms whereas in α-strands the main chain is almost straight. Using "Ramachandran propensity plots" to focus on the α_L/γ_L region, it is shown that glycine favours γ_L (82% of amino acids are glycine), but disfavours α_L (3% are glycine). Most charged and polar amino acids favour α_L with asparagine having by far the highest propensity. Thus, glycine favours nests but, contrary to common expectation, should not favour α-sheet. By contrast most charged or polar amino acids should favour α-sheet by their propensity for the α_L conformation, which is more discriminating amongst amino acids than the α_R conformation. Thus, these results suggest the composition of sequences that favour α-sheet formation and point towards effective prediction of α-sheet from sequence.

High-Throughput Screening for Colloidal Stability of Peptide Formulations Using Dynamic and Static Light Scattering

Selection of an appropriate formulation to stabilize therapeutic proteins against aggregation is one of the most challenging tasks in early-stage drug product development. The amount of aggregates is more difficult to quantify in the case of peptides due to their small molecular size. Here, we investigated the suitability of diffusion self-interaction parameters (k_D) and osmotic second virial coefficients (B₂₂) for high-throughput (HT) screening of peptide formulations regarding their aggregation risk. These parameters were compared to the effect of thermal stress on colloidal stability. The formulation matrix comprised six buffering systems at two selected pH values, four tonicity agents, and a common preservative. The results revealed that electrostatic interactions are the main driver to control colloidal stability. Preferred formulations consisted of acetate and succinate buffer at pH 4.5 combined with glycerol or mannitol and optional m-cresol. k_D proved to be a suitable surrogate for B₂₂ as an indicator of high colloidal stability in the case of peptides as was previously described for globular proteins and antibodies. Formulation assessment solely based on k_D obtained by HT methods offers important insights into the optimization of colloidal stability during the early development of peptide-based liquid formulations and can be performed with a limited amount of peptide (∼360 mg).

Designing a novel mRNA vaccine against SARS-CoV-2: An immunoinformatics approach

SARS-CoV-2 is the deadly virus behind COVID-19, the disease that went on to ravage the world and caused the biggest pandemic 21st century has witnessed so far. On the face of ongoing death and destruction, the urgent need for the discovery of a vaccine against the virus is paramount. This study resorted to the emerging discipline of immunoinformatics in order to design a multi-epitope mRNA vaccine against the spike glycoprotein of SARS-CoV-2. Various immunoinformatics tools were utilized to predict T and B lymphocyte epitopes. The epitopes were channeled through a filtering pipeline comprised of antigenicity, toxicity, allergenicity, and cytokine inducibility evaluation with the goal of selecting epitopes capable of generating both T and B cell-mediated immune responses. Molecular docking simulation between the epitopes and their corresponding MHC molecules was carried out. 13 epitopes, a highly immunogenic adjuvant, elements for proper sub-cellular trafficking, a secretion booster, and appropriate linkers were combined for constructing the vaccine. The vaccine was found to be antigenic, almost neutral at physiological pH, non-toxic, non-allergenic, capable of generating a robust immune response and had a decent worldwide population coverage. Based on these parameters, this design can be considered a promising choice for a vaccine against SARS-CoV-2.

Helix-Coil Transition at a Glycine Following a Nascent α-Helix: A Synergetic Guidance Mechanism for Helix Growth

A detailed understanding of forces guiding the rapid folding of a polypeptide from an apparently random coil state to an ordered α-helical structure following the rate-limiting preorganization of the initial three residue backbones into helical conformation is imperative to comprehending and regulating protein folding and for the rational design of biological mimetics. However, several details of this process are still unknown. First, although the helix-coil transition was proposed to originate at the residue level (J. Chem. Phys. 1959, 31, 526-535; J. Chem. Phys. 1961, 34, 1963-1974), all helix-folding studies have only established it between time-averaged bulk states of a long-lived helix and several transiently populated random coils, along the whole helix model sequence. Second, the predominant thermodynamic forces driving either this two-state transition or the faster helix growth following helix nucleation are still unclear. Third, the conformational space of the random coil state is not well-defined unlike its corresponding α-helix. Here we investigate the restrictions placed on the conformational space of a Gly residue backbone, as a result of it immediately succeeding a nascent α-helical turn. Analyses of the temperature-dependent 1D-, 2D-NMR, FT-IR, and CD spectra and GROMACS MD simulation trajectory of a Gly residue backbone following a model α-helical turn, which is artificially rigidified by a covalent hydrogen bond surrogate, reveal that: (i) the α-helical turn guides the ϕ torsion of the Gly exclusively into either a predominantly populated entropically favored α-helical (α-ϕ) state or a scarcely populated random coil (RC-ϕ) state; (ii) the α-ϕ state of Gly in turn favors the stability of the preceding α-helical turn, while the RC-ϕ state disrupts it, revealing an entropy-driven synergetic guidance for helix growth in the residue following helix nucleation. The applicability of a current synergetic guidance mechanism to explain rapid helix growth in folded and unfolded states of proteins and helical peptides is discussed.

Computational investigation on the effects of pharmaceutical polymers on the structure and dynamics of interleukin2 in heat stress

Application of proteinous drugs can be associated with difficulties during both in storage/transportation and in the body when they are used. However, using pharmaceutical carbohydrates that are widely employed in drug delivery systems, besides the drug can be protected, these systems leading to gradually release the drug over time, or deliver it to the target cell. Using a combination of molecular modeling and simulation techniques, in this study the effects of five carbohydrate polymers of Chitosan, Alginate, Cyclodextrin, Hyaluronic acid and Pectin on structure and dynamics of interleukin2 protein at 298 K and 343 K, are investigated. Data achieved using molecular modeling methods showed that when the temperature rises, the protein stability decreases. Among different polymers, Chitosan and Cyclodextrin have shown to be able to protect protein against the negative effects of high temperatures in comparison with other polymers which suggests that the use of Cyclodextrin biopolymer for the preparation of pharmaceutical formulations of interleukin2 can be the best possible choice among other polymers investigated in this research.Communicated by Ramaswamy H. Sarma.

Secondary structure analysis of peptides with relevance to iron-sulfur cluster nesting

Peptides coordinated to iron-sulfur clusters, referred to as maquettes, represent a synthetic strategy for constructing biomimetic models of iron-sulfur metalloproteins. These maquettes have been successfully employed as building blocks of engineered heme-containing proteins with electron-transfer functionality; however, they have yet to be explored in reactivity studies. The concept of iron-sulfur nesting in peptides is a leading hypothesis in Origins-of-Life research as a plausible path to bridge the discontinuity between prebiotic chemical transformations and extant enzyme catalysis. Based on past biomimetic and biochemical research, we put forward a mechanism of maquette reconstitution that guides our development of computational tools and methodologies. In this study, we examined a key feature of the first stage of maquette formation, which is the secondary structure of aqueous peptide models using molecular dynamics simulations based on the AMBER99SB empirical force field. We compared and contrasted S…S distances, [2Fe-2S] and [4Fe-4S] nests, and peptide conformations via Ramachandran plots for dissolved Cys and Gly amino acids, the CGGCGGC 7-mer, and the GGCGGGCGGCGGW 16-mer peptide. Analytical tools were developed for following the evolution of secondary structural features related to [Fe-S] cluster nesting along 100 ns trajectories. Simulations demonstrated the omnipresence of peptide nests for preformed [2Fe-2S] clusters; however, [4Fe-4S] cluster nests were observed only for the 16-mer peptide with lifetimes of a few nanoseconds. The origin of the [4Fe-4S] nest and its stability was linked to a "kinked-ribbon" peptide conformation. Our computational approach lays the foundation for transitioning into subsequent stages of maquette reconstitution, those being the formation of iron ion/iron-sulfur coordinated peptides. © 2018 Wiley Periodicals, Inc.

Water-Mediated Electronic Structure of Oligopeptides Probed by Their UV Circular Dichroism, Absorption Spectra, and Time-Dependent DFT Calculations

We investigate the UV absorption spectra of a series of cationic GxG peptides (where x denotes a guest residue) in aqueous solution and find that only a subset of these spectra show a strong dependence with temperature. To explore whether or not this observation reflects conformational dependencies, we carry out time-dependent density functional calculations for the polyproline II (pPII) and β-strand conformations in implicit and explicit water. We find that the calculated CD spectra for pPII can qualitatively account for the experimental spectra irrespective of the water model. The β-strand UV-CD spectra, however, require the explicit consideration of water. Contrary to conventional wisdom, we find that both the NV₁ and NV₂ band are the envelopes of contributions from multiple transitions that involve more than just the HOMOs and LUMOs of the peptide groups. A natural transition orbital analysis reveals that some of the transitions have a charge-transfer character. The overall manifold of transitions depends on the peptide's backbone conformation, peptide hydration, and side chain of the guest residue. Our results reveal that peptide groups, side chains, and hydration shells must be considered as an entity for a physically valid characterization of UV absorbance and circular dichroism.

Investigation of backbone dynamics and local geometry of bio-molecules using calculated NMR chemical shifts and anisotropies

Prerequisite for chemical shift (CS) and CS tensor calculations are highly refined structures defining the molecular surroundings of the nuclei under study. Here, we present geometry optimizations with ¹³C and ¹⁵N CS constraints for large bio-molecules like peptides and proteins. The method discussed here provides both, refined structures and chemical shift tensors. Furthermore, since the experimental resonances of aligned systems are related to CS tensors, they strongly depend on the orientation and motion of molecules, their fragments, functional groups and moieties. For efficient CS calculations we apply a semi-empirical approach-the bond polarization theory (BPT). The BPT relies on linear bond polarization parameters and we present a new set of parameters based on ab initio second-order Møller-Plesset perturbation theory calculations. The new parametrization extends the applicability of the BPT approach to a wide range of organic molecules and bio-polymers. Here, the method has been applied to the protein ubiquitin and the membrane-active peptide gramicidin A (dimer) in oriented bilayers. The calculated ¹³C and ¹⁵N CS values of best-refined structures published until now gave a large scatter with respect to the experiment. It will be shown that BPT CS optimizations can reduce these errors to values near the experimental uncertainty. In combination with molecular dynamics with orientational constraints it is possible to study motional dynamics and BPT calculations can provide residual chemical shift anisotropies.

Natural selection based on coordination chemistry: computational assessment of [4Fe-4S]-maquettes with non-coded amino acids

Cysteine is the only coded amino acid in biology that contains a thiol functional group. Deprotonated thiolate is essential for anchoring iron-sulfur ([Fe-S]) clusters, as prosthetic groups to the protein matrix. [Fe-S] metalloproteins and metalloenzymes are involved in biological electron transfer, radical chemistry, small molecule activation and signalling. These are key metabolic and regulatory processes that would likely have been present in the earliest organisms. In the context of emergence of life theories, the selection and evolution of the cysteine-specific R-CH₂-SH side chain is a fascinating question to confront. We undertook a computational [4Fe-4S]-maquette modelling approach to evaluate how side chain length can influence [Fe-S] cluster binding and stability in short 7-mer and long 16-mer peptides, which contained either thioglycine, cysteine or homocysteine. Force field-based molecular dynamics simulations for [4Fe-4S] cluster nest formation were supplemented with density functional theory calculations of a ligand-exchange reaction between a preassembled cluster and the peptide. Secondary structure analysis revealed that peptides with cysteine are found with greater frequency nested to bind preformed [4Fe-4S] clusters. Additionally, the presence of the single methylene group in cysteine ligands mitigates the steric bulk, maintains the H-bonding and dipole network, and provides covalent Fe-S(thiolate) bonds that together create the optimal electronic and geometric structural conditions for [4Fe-4S] cluster binding compared to thioglycine or homocysteine ligands. Our theoretical work forms an experimentally testable hypothesis of the natural selection of cysteine through coordination chemistry.

Delineation of a new structural motif involving NHN γ-turn

Macromolecules are characterized by distinctive arrangement of hydrogen bonds. Different patterns of hydrogen bonds give rise to distinct and stable structural motifs. An analysis of 4114 non-redundant protein chains reveals the existence of a three-residue, (i - 1) to (i + 1), structural motif, having two hydrogen-bonded five-membered pseudo rings (the first, an NH···OC involving the first residue, and the second being NH∙∙∙N involving the last two residues), separated by a peptide bond. There could be an additional hydrogen bond between the side-chain at (i-1) and the main-chain NH of (i + 1). The average backbone torsion angles of -76(±21)° and - 12(±17)° at i creates a tight turn in the polypeptide chain, akin to a γ-turn. Indeed, a search of three-residue fragments with restriction on the terminal C^α ···C^α distance and the existence of the two pseudo rings on either side revealed the presence 14 846 cases of a variant, termed NHN γ-turn, distinct from the NHO γ-turn (2032 cases) that has traditionally been characterized by the presence of NHO hydrogen bond linking the terminal main-chain atoms. As in the latter, the newly identified γ-turns are also of two types-classical and inverse, occurring in the ratio of 1:6. The propensities of residues to occur in these turns and their secondary structural features have been enumerated. An understanding of these turns would be useful for structure prediction and loop modeling, and may serve as models to represent some of the unfolded state or disordered region in proteins.

The characterization of Thermotoga maritima Arginine Binding Protein variants demonstrates that minimal local strains have an important impact on protein stability

The Ramachandran plot is a versatile and valuable tool that provides fundamental information for protein structure determination, prediction, and validation. The structural/thermodynamic effects produced by forcing a residue to adopt a conformation predicted to be forbidden were here explored using Thermotoga maritima Arginine Binding Protein (TmArgBP) as model. Specifically, we mutated TmArgBP Gly52 that assumes a conformation believed to be strictly disallowed for non-Gly residues. Surprisingly, the crystallographic characterization of Gly52Ala TmArgBP indicates that the structural context forces the residue to adopt a non-canonical conformation never observed in any of the high-medium resolution PDB structures. Interestingly, the inspection of this high resolution structure demonstrates that only minor alterations occur. Nevertheless, experiments indicate that Gly52 replacements in TmArgBP produce destabilizations comparable to those observed upon protein truncation or dissection in domains. Notably, we show that force-fields commonly used in computational biology do not reproduce this non-canonical state. Using TmArgBP as model system we here demonstrate that the structural context may force residues to adopt conformations believed to be strictly forbidden and that barely detectable alterations produce major destabilizations. Present findings highlight the role of subtle strains in governing protein stability. A full understanding of these phenomena is essential for an exhaustive comprehension of the factors regulating protein structures.

Amyloidogenic model peptides as catalysts for stereoselective aldol reactions

Different polymorphic forms of peptide assemblies influence the stereoselectivity of aldol reactions in water medium.

Chiral Ramachandran Plots II: General Trends and Protein Chirality Spectra

The degree of chirality of protein backbone residues is used to enrich the Ramachandran plot (RP) and create three-dimensional chiral RPs with much more structural information. Detailed comparative analysis of the four classical RPs (general, glycine, proline, and pre-proline) is provided, including statistical analysis of quantitative chirality distributions in the maps and in the secondary structures. Our results show that points with outlier chirality levels represent special transitional points in the folded protein such as α-helix kinks, twists of β-strands, and transition points between secondary structures. A protein chirality spectrum in which the degree of chirality of each residue is plotted against the sequence number explores these special points. More than 65000 residues extracted from 200 high-quality proteins are used for this study, which shows that quantitative chirality is a general and useful structural parameter for protein conformational studies.

Gene Cloning, Expression, and Antifungal Activities of Permatin from Naked Oat (Avena nuda)

Thaumatin-like proteins (TLPs) are the products of a large, highly complex gene family involved in host defense. TLPs also belong to the pathogenesis-related family 5 (PR-5) of plant defense proteins. Most TLPs exhibit potential antifungal activities, and their accumulation in the plant is related to many physiological processes. In this study, a gene encoding TLP named permatin with an open reading frame of 678 bp encoding a protein of 225 amino acids with a calculated molecular mass of 23.5 kDa was cloned from naked oat leaves. Phylogenetic analysis revealed that permatin shares high homology with a number of other TLPs among diverse taxa. Model of structure by homology modeling showed that permatin consists of an acidic cleft region consistent with most TLPs. Recombinant NusA-permatin was overexpressed in Escherichia coli strain BL21 and purified by Heparin column combined with Sephacryl S-200 column. The protein exhibited antifungal activity to Fusarium oxysporum (half maximal inhibitory concentration, IC₅₀ = 21.42 μM). Morphological observation showed that NusA-permatin can induce mycelium deformation of F. oxysporum, the cell membrane is blurred, and the diaphragm is not obvious. NusA-permatin also causes membrane permeabilization and reactive oxygen species accumulation in the mycelium of F. oxysporum. Permatin may play an important role in the disease resistance responses of plants against pathogen attacks through its antifungal activity.

The Relation between α-Helical Conformation and Amyloidogenicity

Amyloid fibrils are stable aggregates of misfolded proteins and polypeptides that are insoluble and resistant to protease activity. Abnormal formation of amyloid fibrils in vivo may lead to neurodegenerative disorders and other systemic amyloidosis, such as Alzheimer's, Parkinson's, and atherosclerosis. Because of their clinical importance, amyloids are under intense scientific research. It is believed that short polypeptide segments within proteins are responsible for the transformation of correctly folded proteins into parts of larger amyloid fibrils and that this transition is modulated by environmental factors, such as pH, salt concentration, interaction with the cell membrane, and interaction with metal ions. Most studies on amyloids focus on the amyloidogenic sequences. The focus of this study is on the structure of the amyloidogenic α-helical segments because the α-helical secondary structure has been recognized to be a key player in different stages of the amyloidogenesis process. We have previously shown that the α-helical conformation may be expressed by two parameters (θ and ρ) that form orthogonal coordinates based on the Ramachandran dihedrals (φ and ψ) and provide an illuminating interpretation of the α-helical conformation. By performing statistical analysis on α-helical conformations found in the Protein Data Bank, an apparent relation between α-helical conformation, as expressed by θ and ρ, and amyloidogenicity is revealed. Remarkably, random amino acid sequences, whose helical structures were obtained from the most probable dihedral angles, revealed the same dependency of amyloidogenicity, suggesting the importance of α-helical structure as opposed to sequence.

Order, Disorder, and Temperature-Driven Compaction in a Designed Elastin Protein

Artificial minielastin constructs have been designed that replicate the structure and function of natural elastins in a simpler context, allowing the NMR observation of structure and dynamics of elastin-like proteins with complete residue-specific resolution. We find that the alanine-rich cross-linking domains of elastin have a partially helical structure, but only when capped by proline-rich hydrophobic domains. We also find that the hydrophobic domains, composed of prominent 6-residue repeats VPGVGG and APGVGV found in natural elastins, appear random coil by both NMR chemical shift analysis and circular dichroism. However, these elastin hydrophobic domains exhibit structural bias for a dynamically disordered conformation that is neither helical nor β sheet with a degree of nonrandom structural bias which is dependent on residue type and position in the sequence. Another nonrandom-coil aspect of hydrophobic domain structure lies in the fact that, in contrast to other intrinsically disordered proteins, these hydrophobic domains retain a relatively condensed conformation whether attached to cross-linking domains or not. Importantly, these domains and the proteins containing them constrict with increasing temperature by up to 30% in volume without becoming more ordered. This property is often observed in nonbiological polymers and suggests that temperature-driven constriction is a new type of protein structural change that is linked to elastin's biological functions of coacervation-driven assembly and elastic recoil.

Everyone Is a Protagonist: Residue Conformational Preferences in High-Resolution Protein Structures

In many structural bioinformatics problems, there is a broad range of unanswered questions about protein dynamics and amino acid properties. Proteins are not strictly static objects, but rather populate ensembles of conformations. One way to understand these particularities is to analyze the information available in experimental databases. The Ramachandran plot, despite being more than half a century old, remains an utterly useful tool in the study of protein conformation. Based on its assumptions, we inspected a large data set (11,130 protein structures, amounting to 5,255,768 residues) and discriminated the conformational preferences of each residue type regarding their secondary structure participation. These data were studied for phi [Formula: see text], psi [Formula: see text], and side chain chi [Formula: see text] angles, being presented in non-Ramachandranian plots. In the largest analysis of protein conformation made so far, we propose an original plot to depict conformational preferences in relation to different secondary structure elements. Despite confirming previous observations, our results strongly support a unique character for each residue type, whereas also reinforcing the observation that side chains have a major contribution to secondary structure and, by consequence, on protein conformation. This information can be further used in the development of more robust methods and computational strategies for structural bioinformatics problems.

Unfavorable regions in the ramachandran plot: Is it really steric hindrance? The interacting quantum atoms perspective

Accurate description of the intrinsic preferences of amino acids is important to consider when developing a biomolecular force field. In this study, we use a modern energy partitioning approach called Interacting Quantum Atoms to inspect the cause of the φ and ψ torsional preferences of three dipeptides (Gly, Val, and Ile). Repeating energy trends at each of the molecular, functional group, and atomic levels are observed across both (1) the three amino acids and (2) the φ/ψ scans in Ramachandran plots. At the molecular level, it is surprisingly electrostatic destabilization that causes the high-energy regions in the Ramachandran plot, not molecular steric hindrance (related to the intra-atomic energy). At the functional group and atomic levels, the importance of key peptide atoms (Oi-1 , Ci , Ni , Ni+1 ) and some sidechain hydrogen atoms (Hγ ) are identified as responsible for the destabilization seen in the energetically disfavored Ramachandran regions. Consistently, the Oi-1 atoms are particularly important for the explanation of dipeptide intrinsic behavior, where electrostatic and steric destabilization unusually complement one another. The findings suggest that, at least for these dipeptides, it is the peptide group atoms that dominate the intrinsic behavior, more so than the sidechain atoms. © 2017 The Authors. Journal of Computational Chemistry Published by Wiley Periodicals, Inc.

Protein folding, misfolding and aggregation: The importance of two-electron stabilizing interactions

Proteins associated with neurodegenerative diseases are highly pleiomorphic and may adopt an all-α-helical fold in one environment, assemble into all-β-sheet or collapse into a coil in another, and rapidly polymerize in yet another one via divergent aggregation pathways that yield broad diversity of aggregates’ morphology. A thorough understanding of this behaviour may be necessary to develop a treatment for Alzheimer’s and related disorders. Unfortunately, our present comprehension of folding and misfolding is limited for want of a physicochemical theory of protein secondary and tertiary structure. Here we demonstrate that electronic configuration and hyperconjugation of the peptide amide bonds ought to be taken into account to advance such a theory. To capture the effect of polarization of peptide linkages on conformational and H-bonding propensity of the polypeptide backbone, we introduce a function of shielding tensors of the C^α atoms. Carrying no information about side chain-side chain interactions, this function nonetheless identifies basic features of the secondary and tertiary structure, establishes sequence correlates of the metamorphic and pH-driven equilibria, relates binding affinities and folding rate constants to secondary structure preferences, and manifests common patterns of backbone density distribution in amyloidogenic regions of Alzheimer’s amyloid β and tau, Parkinson’s α-synuclein and prions. Based on those findings, a split-intein like mechanism of molecular recognition is proposed to underlie dimerization of Aβ, tau, αS and PrP^C, and divergent pathways for subsequent association of dimers are outlined; a related mechanism is proposed to underlie formation of PrP^Sc fibrils. The model does account for: (i) structural features of paranuclei, off-pathway oligomers, non-fibrillar aggregates and fibrils; (ii) effects of incubation conditions, point mutations, isoform lengths, small-molecule assembly modulators and chirality of solid-liquid interface on the rate and morphology of aggregation; (iii) fibril-surface catalysis of secondary nucleation; and (iv) self-propagation of infectious strains of mammalian prions.

Mass & secondary structure propensity of amino acids explain their mutability and evolutionary replacements

Why is an amino acid replacement in a protein accepted during evolution? The answer given by bioinformatics relies on the frequency of change of each amino acid by another one and the propensity of each to remain unchanged. We propose that these replacement rules are recoverable from the secondary structural trends of amino acids. A distance measure between high-resolution Ramachandran distributions reveals that structurally similar residues coincide with those found in substitution matrices such as BLOSUM: Asn ↔ Asp, Phe ↔ Tyr, Lys ↔ Arg, Gln ↔ Glu, Ile ↔ Val, Met → Leu; with Ala, Cys, His, Gly, Ser, Pro, and Thr, as structurally idiosyncratic residues. We also found a high average correlation (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\overline{R}$$\end{document}R¯ = 0.85) between thirty amino acid mutability scales and the mutational inertia (I_X), which measures the energetic cost weighted by the number of observations at the most probable amino acid conformation. These results indicate that amino acid substitutions follow two optimally-efficient principles: (a) amino acids interchangeability privileges their secondary structural similarity, and (b) the amino acid mutability depends directly on its biosynthetic energy cost, and inversely with its frequency. These two principles are the underlying rules governing the observed amino acid substitutions.

The Rosetta All-Atom Energy Function for Macromolecular Modeling and Design

Over the past decade, the Rosetta biomolecular modeling suite has informed diverse biological questions and engineering challenges ranging from interpretation of low-resolution structural data to design of nanomaterials, protein therapeutics, and vaccines. Central to Rosetta's success is the energy function: a model parametrized from small-molecule and X-ray crystal structure data used to approximate the energy associated with each biomolecule conformation. This paper describes the mathematical models and physical concepts that underlie the latest Rosetta energy function, called the Rosetta Energy Function 2015 (REF15). Applying these concepts, we explain how to use Rosetta energies to identify and analyze the features of biomolecular models. Finally, we discuss the latest advances in the energy function that extend its capabilities from soluble proteins to also include membrane proteins, peptides containing noncanonical amino acids, small molecules, carbohydrates, nucleic acids, and other macromolecules.

An exhaustive survey of regular peptide conformations using a new metric for backbone handedness (h)

The Ramachandran plot is important to structural biology as it describes a peptide backbone in the context of its dominant degrees of freedom—the backbone dihedral angles φ and ψ (Ramachandran, Ramakrishnan & Sasisekharan, 1963). Since its introduction, the Ramachandran plot has been a crucial tool to characterize protein backbone features. However, the conformation or twist of a backbone as a function of φ and ψ has not been completely described for both cis and trans backbones. Additionally, little intuitive understanding is available about a peptide’s conformation simply from knowing the φ and ψ values of a peptide (e.g., is the regular peptide defined by φ = ψ =  − 100°  left-handed or right-handed?). This report provides a new metric for backbone handedness (h) based on interpreting a peptide backbone as a helix with axial displacement d and angular displacement θ, both of which are derived from a peptide backbone’s internal coordinates, especially dihedral angles φ, ψ and ω. In particular, h equals sin(θ)d∕|d|, with range [−1, 1] and negative (or positive) values indicating left(or right)-handedness. The metric h is used to characterize the handedness of every region of the Ramachandran plot for both cis (ω = 0°) and trans (ω = 180°) backbones, which provides the first exhaustive survey of twist handedness in Ramachandran (φ, ψ) space. These maps fill in the ‘dead space’ within the Ramachandran plot, which are regions that are not commonly accessed by structured proteins, but which may be accessible to intrinsically disordered proteins, short peptide fragments, and protein mimics such as peptoids. Finally, building on the work of (Zacharias & Knapp, 2013), this report presents a new plot based on d and θ that serves as a universal and intuitive alternative to the Ramachandran plot. The universality arises from the fact that the co-inhabitants of such a plot include every possible peptide backbone including cis and trans backbones. The intuitiveness arises from the fact that d and θ provide, at a glance, numerous aspects of the backbone including compactness, handedness, and planarity.

A closer look into the α-helix basin

α-Helices are the most abundant structures found within proteins and play an important role in the determination of the global structure of proteins and their function. Representation of α-helical structures with the common (φ, ψ) dihedrals, as in Ramachandran maps, does not provide informative details regarding the helical structure apart for the abstract geometric meaning of the dihedrals. We present an alternative coordinate system that describes helical conformations in terms of residues per turn (ρ) and angle (ϑ) between backbone carbonyls relative to the helix direction through an approximate linear transformation between the two coordinates system (φ, ψ and ρ, ϑ). In this way, valuable information on the helical structure becomes directly available. Analysis of α-helical conformations acquired from the Protein Data Bank (PDB) demonstrates that a conformational energy function of the α-helix backbone can be harmonically approximated on the (ρ, ϑ) space, which is not applicable to the (φ, ψ) space due to the diagonal distribution of the conformations. The observed trends of helical conformations obtained from the PDB are captured by four conceptual simulations that theoretically examine the effects of residue bulkiness, external electric field, and externally applied mechanical forces. Flory’s isolated pair hypothesis is shown to be partially correct for α-helical conformations.

Conformational analysis of short polar side-chain amino-acids through umbrella sampling and DFT calculations

Molecular and quantum mechanics calculations were carried out in a series of tripeptides (GXG, where X = D, N and C) as models of the unfolded states of proteins. The selected central amino acids, especially aspartic acid (D) and asparagine (N) are known to present significant average conformations in partially allowed areas of the Ramachandran plot, which have been suggested to be important in unfolded protein regions. In this report, we present the calculation of the propensity values through an umbrella sampling procedure in combination with the calculation of the NMR J-coupling constants obtained by a DFT model. The experimental NMR observations can be reasonably explained in terms of a conformational distribution where PP_II and β basins sum up propensities above 0.9. The conformational analysis of the side chain dihedral angle (χ₁), along with the computation of ³J(H^αH^β), revealed a preference for the g _- and g ₊ rotamers. These may be connected with the presence of intermolecular H-bonding and carbonyl-carbonyl interactions sampled in the PP_II and β basins. Taking into account all those results, it can be established that these residues show a similar behavior to other amino acids in short peptides regarding backbone φ,ψ dihedral angle distribution, in agreement with some experimental analysis of capped dipeptides.

Insights into Unfolded Proteins from the Intrinsic ϕ/ψ Propensities of the AAXAA Host-Guest Series

Various host-guest peptide series are used by experimentalists as reference conformational states. One such use is as a baseline for random-coil NMR chemical shifts. Comparison to this random-coil baseline, through secondary chemical shifts, is used to infer protein secondary structure. The use of these random-coil data sets rests on the perception that the reference chemical shifts arise from states where there is little or no conformational bias. However, there is growing evidence that the conformational composition of natively and nonnatively unfolded proteins fail to approach anything that can be construed as random coil. Here, we use molecular dynamics simulations of an alanine-based host-guest peptide series (AAXAA) as a model of unfolded and denatured states to examine the intrinsic propensities of the amino acids. We produced ensembles that are in good agreement with the experimental NMR chemical shifts and confirm that the sampling of the 20 natural amino acids in this peptide series is be far from random. Preferences toward certain regions of conformational space were both present and dependent upon the environment when compared under conditions typically used to denature proteins, i.e., thermal and chemical denaturation. Moreover, the simulations allowed us to examine the conformational makeup of the underlying ensembles giving rise to the ensemble-averaged chemical shifts. We present these data as an intrinsic backbone propensity library that forms part of our Structural Library of Intrinsic Residue Propensities to inform model building, to aid in interpretation of experiment, and for structure prediction of natively and nonnatively unfolded states.

Evolution of a Protein Interaction Domain Family by Tuning Conformational Flexibility

Conformational flexibility allows proteins to adopt multiple functionally important conformations but can also lead to nonfunctional structures. We analyzed the dynamic behavior of the enzyme guanylate kinase as it evolved into the GK protein interaction domain (GK_PID) to investigate the role of flexibility in the evolution of new protein functions. We found that the ancestral enzyme is very flexible, allowing it to adopt open conformations that can bind nucleotide and closed ones that enable catalysis of phosphotransfer from ATP to GMP. Historical mutations that converted the GK from an enzyme to a protein interaction domain dramatically reduce flexibility, predominantly by inhibiting rotations of the protein backbone that are coupled to the global closing motion. Removing flexibility prevents adoption of conformations that cannot fit the protein partner in the binding site. Our results highlight the importance of mutations that optimize protein conformational flexibility with function during evolution.

A novel secondary structure based on fused five-membered rings motif

An analysis of protein structures indicates the existence of a novel, fused five-membered rings motif, comprising of two residues (i and i + 1), stabilized by interresidue N_i+1–H∙∙∙N_i and intraresidue N_i+1–H∙∙∙O=C_i+1 hydrogen bonds. Fused-rings geometry is the common thread running through many commonly occurring motifs, such as β-turn, β-bulge, Asx-turn, Ser/Thr-turn, Schellman motif, and points to its structural robustness. A location close to the beginning of a β-strand is rather common for the motif. Devoid of side chain, Gly seems to be a key player in this motif, occurring at i, for which the backbone torsion angles cluster at ~(−90°, −10°) and (70°, 20°). The fused-rings structures, distant from each other in sequence, can hydrogen bond with each other, and the two segments aligned to each other in a parallel fashion, give rise to a novel secondary structure, topi, which is quite common in proteins, distinct from two major secondary structures, α-helix and β-sheet. Majority of the peptide segments making topi are identified as aggregation-prone and the residues tend to be conserved among homologous proteins.

Removal of the Side Chain at the Active-Site Serine by a Glycine Substitution Increases the Stability of a Wide Range of Serine β-Lactamases by Relieving Steric Strain

Serine β-lactamases are bacterial enzymes that hydrolyze β-lactam antibiotics. They utilize an active-site serine residue as a nucleophile, forming an acyl-enzyme intermediate during hydrolysis. In this study, thermal denaturation experiments as well as X-ray crystallography were performed to test the effect of substitution of the catalytic serine with glycine on protein stability in serine β-lactamases. Six different enzymes comprising representatives from each of the three classes of serine β-lactamases were examined, including TEM-1, CTX-M-14, and KPC-2 of class A, P99 of class C, and OXA-48 and OXA-163 of class D. For each enzyme, the wild type and a serine-to-glycine mutant were evaluated for stability. The glycine mutants all exhibited enhanced thermostability compared to that of the wild type. In contrast, alanine substitutions of the catalytic serine in TEM-1, OXA-48, and OXA-163 did not alter stability, suggesting removal of the Cβ atom is key to the stability increase associated with the glycine mutants. The X-ray crystal structures of P99 S64G, OXA-48 S70G and S70A, and OXA-163 S70G suggest that removal of the side chain of the catalytic serine releases steric strain to improve enzyme stability. Additionally, analysis of the torsion angles at the nucleophile position indicates that the glycine mutants exhibit improved distance and angular parameters of the intrahelical hydrogen bond network compared to those of the wild-type enzymes, which is also consistent with increased stability. The increased stability of the mutants indicates that the enzyme pays a price in stability for the presence of a side chain at the catalytic serine position but that the cost is necessary in that removal of the serine drastically impairs function. These findings support the stability-function hypothesis, which states that active-site residues are optimized for substrate binding and catalysis but that the requirements for catalysis are often not consistent with the requirements for optimal stability.

Structure-Activity Relationship Studies of N- and C-Terminally Modified Secretin Analogs for the Human Secretin Receptor

The pleiotropic role of human secretin (hSCT) validates its potential use as a therapeutic agent. Nevertheless, the structure of secretin in complex with its receptor is necessary to develop a suitable therapeutic agent. Therefore, in an effort to design a three-dimensional virtual homology model and identify a peptide agonist and/or antagonist for the human secretin receptor (hSR), the significance of the primary sequence of secretin peptides in allosteric binding and activation was elucidated using virtual docking, FRET competitive binding and assessment of the cAMP response. Secretin analogs containing various N- or C-terminal modifications were prepared based on previous findings of the role of these domains in receptor binding and activation. These analogs exhibited very low or no binding affinity in a virtual model, and were found to neither exhibit in vitro binding nor agonistic or antagonistic properties. A parallel analysis of the analogs in the virtual model and in vitro studies revealed instability of these peptide analogs to bind and activate the receptor.

General trends of dihedral conformational transitions in a globular protein

Dihedral conformational transitions are analyzed systematically in a model globular protein, cytochrome P450cam, to examine their structural and chemical dependences through combined conventional molecular dynamics (cMD), accelerated molecular dynamics (aMD) and adaptive biasing force (ABF) simulations. The aMD simulations are performed at two acceleration levels, using dihedral and dual boost, respectively. In comparison with cMD, aMD samples protein dihedral transitions approximately two times faster on average using dihedral boost, and ∼ 3.5 times faster using dual boost. In the protein backbone, significantly higher dihedral transition rates are observed in the bend, coil, and turn flexible regions, followed by the β bridge and β sheet, and then the helices. Moreover, protein side chains of greater length exhibit higher transition rates on average in the aMD-enhanced sampling. Side chains of the same length (particularly Nχ = 2) exhibit decreasing transition rates with residues when going from hydrophobic to polar, then charged and aromatic chemical types. The reduction of dihedral transition rates is found to be correlated with increasing energy barriers as identified through ABF free energy calculations. These general trends of dihedral conformational transitions provide important insights into the hierarchical dynamics and complex free energy landscapes of functional proteins.

Partial unfolding and refolding for structure refinement: A unified approach of geometric simulations and molecular dynamics

The most successful protein structure prediction methods to date have been template-based modeling (TBM) or homology modeling, which predicts protein structure based on experimental structures. These high accuracy predictions sometimes retain structural errors due to incorrect templates or a lack of accurate templates in the case of low sequence similarity, making these structures inadequate in drug-design studies or molecular dynamics simulations. We have developed a new physics based approach to the protein refinement problem by mimicking the mechanism of chaperons that rehabilitate misfolded proteins. The template structure is unfolded by selectively (targeted) pulling on different portions of the protein using the geometric based technique FRODA, and then refolded using hierarchically restrained replica exchange molecular dynamics simulations (hr-REMD). FRODA unfolding is used to create a diverse set of topologies for surveying near native-like structures from a template and to provide a set of persistent contacts to be employed during re-folding. We have tested our approach on 13 previous CASP targets and observed that this method of folding an ensemble of partially unfolded structures, through the hierarchical addition of contact restraints (that is, first local and then nonlocal interactions), leads to a refolding of the structure along with refinement in most cases (12/13). Although this approach yields refined models through advancement in sampling, the task of blind selection of the best refined models still needs to be solved. Overall, the method can be useful for improved sampling for low resolution models where certain of the portions of the structure are incorrectly modeled.