Dynameomics: large-scale assessment of native protein flexibility

Assessment of Four Theoretical Approaches to Predict Protein Flexibility in the Crystal Phase and Solution

In this paper, we evaluated the ability of four coarse-grained methods to predict protein flexible regions with potential biological importance, UNRES-flex, UNRES-DSSP-flex (based on the united residue model of polypeptide chains without and with secondary structure restraints, respectively), CABS-flex (based on the C-α, C-β, and side chain model), and nonlinear rigid block normal mode analysis (NOLB) with a set of 100 protein structures determined by NMR spectroscopy or X-ray crystallography, with all secondary structure types. End regions with high fluctuations were excluded from analysis. The Pearson and Spearman correlation coefficients were used to quantify the conformity between the calculated and experimental fluctuation profiles, the latter determined from NMR ensembles and X-ray B-factors, respectively. For X-ray structures (corresponding to proteins in a crowded environment), NOLB resulted in the best agreement between the predicted and experimental fluctuation profiles, while for NMR structures (corresponding to proteins in solution), the ranking of performance is CABS-flex > UNRES-DSSP-flex > UNRES-flex > NOLB; however, CABS-flex sometimes exaggerated the extent of small fluctuations, as opposed to UNRES-DSSP-flex.

Cheminformatics-based identification of phosphorylated RET tyrosine kinase inhibitors for human cancer

Background

Rearranged during transfection (RET), an oncogenic protein, is associated with various cancers, including non-small-cell lung cancer (NSCLC), papillary thyroid cancer (PTC), pancreatic cancer, medullary thyroid cancer (MTC), breast cancer, and colorectal cancer. Dysregulation of RET contributes to cancer development, highlighting the importance of identifying lead compounds targeting this protein due to its pivotal role in cancer progression. Therefore, this study aims to discover effective lead compounds targeting RET across different cancer types and evaluate their potential to inhibit cancer progression.

Methods

This study used a range of computational techniques, including Phase database creation, high-throughput virtual screening (HTVS), molecular docking, molecular mechanics with generalized Born surface area (MM-GBSA) solvation, assessment of pharmacokinetic (PK) properties, and molecular dynamics (MD) simulations, to identify potential lead compounds targeting RET.

Results

Initially, a high-throughput virtual screening of the ZINC database identified 2,550 compounds from a pool of 170,269. Subsequent molecular docking studies revealed 10 compounds with promising negative binding scores ranging from -8.458 to -7.791 kcal/mol. MM-GBSA analysis further confirmed the potential of four compounds to exhibit negative binding scores. MD simulations demonstrated the stability of CID 95842900, CID 137030374, CID 124958150, and CID 110126793 with the target receptors.

Conclusion

These findings suggest that these selected four compounds have the potential to inhibit phosphorylated RET (pRET) tyrosine kinase activity and may represent promising candidates for the treatment of various cancers.

Illuminating ligand-induced dynamics in nuclear receptors through MD simulations

Nuclear receptors (NRs) regulate gene expression in critical physiological processes, with their functionality finely tuned by ligand-induced conformational changes. While NRs may sometimes undergo significant conformational motions in response to ligand-binding, these effects are more commonly subtle and challenging to study by traditional structural or biophysical methods. Molecular dynamics (MD) simulations are a powerful tool to bridge the gap between static protein-ligand structures and dynamical changes that govern NR function. Here, we summarize a handful of recent studies that apply MD simulations to study NRs. We present diverse methodologies for analyzing simulation data with a detailed examination of the information each method can yield. By delving into the strengths, limitations and unique contributions of these tools, this review provides guidance for extracting meaningful data from MD simulations to advance the goal of understanding the intricate mechanisms by which ligands orchestrate a range of functional outcomes in NRs.

Neuropharmacological assessment and identification of possible lead compound (apomorphine) from Hygrophila spinosa through in-vivo and in-silico approaches

The aim of this research is to examine possible neurological activity of methanol, ethyl acetate, and aqueous extracts of Hygrophila spinosa and identify possible lead compounds through in silico analysis. In vivo, neuropharmacological activity was evaluated by using four distinct neuropharmacological assessment assays. Previously reported GC-MS data and earlier literature were utilized to identify the phytochemicals present in Hygrophila spinosa. Computational studies notably molecular docking and molecular dynamic simulations were conducted with responsible receptors to assess the stability of the best interacting compound. Pharmacokinetics properties like absorption, distribution, metabolism, excretion, and toxicity were considered to evaluate the drug likeliness properties of the identified compounds. All the in vivo results support the notion that different extracts (methanol, ethyl acetate, and aqueous) of Hygrophila spinosa have significant (*p = 0.05) sedative-hypnotic, anxiolytic, and anti-depressant activity. Among all the extracts, specifically methanol extracts of Hygrophila spinosa (MHS 400 mg/kg.b.w.) showed better sedative, anxiolytic and antidepressant activity than aqueous and ethyl acetate extracts. In silico molecular docking analysis revealed that among 53 compounds 7 compounds showed good binding affinities and one compound, namely apomorphine (CID: 6005), surprisingly showed promising binding affinity to all the receptors . An analysis of molecular dynamics simulations confirmed that apomorphine (CID: 6005) had a high level of stability at the protein binding site. Evidence suggests that Hygrophila spinosa has significant sedative, anxiolytic, and antidepressant activity. In silico analysis revealed that a particular compound (apomorphine) is responsible for this action. Further research is required in order to establish apomorphine as a drug for anxiety, depression, and sleep disorders.Communicated by Ramaswamy H. Sarma.

Identification of potential inhibitor against Leishmania donovani mitochondrial DNA primase through in-silico and in vitro drug repurposing approaches

Leishmania donovani is the causal organism of leishmaniasis with critical health implications affecting about 12 million people around the globe. Due to less efficacy, adverse side effects, and resistance, the available therapeutic molecules fail to control leishmaniasis. The mitochondrial primase of Leishmania donovani (LdmtPRI1) is a vital cog in the DNA replication mechanism, as the enzyme initiates the replication of the mitochondrial genome of Leishmania donovani. Hence, we target this protein as a probable drug target against leishmaniasis. The de-novo approach enabled computational prediction of the three-dimensional structure of LdmtPRI1, and its active sites were identified. Ligands from commercially available drug compounds were selected and docked against LdmtPRI1. The compounds were chosen for pharmacokinetic study and molecular dynamics simulation based on their binding energies and protein interactions. The LdmtPRI1 gene was cloned, overexpressed, and purified, and a primase activity assay was performed. The selected compounds were verified experimentally by the parasite and primase inhibition assay. Capecitabine was observed to be effective against the promastigote form of Leishmania donovani, as well as inhibiting primase activity. This study's findings suggest capecitabine might be a potential anti-leishmanial drug candidate after adequate further studies.

Wordom update 2: A user-friendly program for the analysis of molecular structures and conformational ensembles

We present the second update of Wordom, a user-friendly and efficient program for manipulation and analysis of conformational ensembles from molecular simulations. The actual update expands some of the existing modules and adds 21 new modules to the update 1 published in 2011. The new adds can be divided into three sets that: 1) analyze atomic fluctuations and structural communication; 2) explore ion-channel conformational dynamics and ionic translocation; and 3) compute geometrical indices of structural deformation. Set 1 serves to compute correlations of motions, find geometrically stable domains, identify a dynamically invariant core, find changes in domain-domain separation and mutual orientation, perform wavelet analysis of large-scale simulations, process the output of principal component analysis of atomic fluctuations, perform functional mode analysis, infer regions of mechanical rigidity, analyze overall fluctuations, and perform the perturbation response scanning. Set 2 includes modules specific for ion channels, which serve to monitor the pore radius as well as water or ion fluxes, and measure functional collective motions like receptor twisting or tilting angles. Finally, set 3 includes tools to monitor structural deformations by computing angles, perimeter, area, volume, β-sheet curvature, radial distribution function, and center of mass. The ring perception module is also included, helpful to monitor supramolecular self-assemblies. This update places Wordom among the most suitable, complete, user-friendly, and efficient software for the analysis of biomolecular simulations. The source code of Wordom and the relative documentation are available under the GNU general public license at http://wordom.sf.net.

Design of short peptides and peptide amphiphiles as collagen mimics and an investigation of their interactions with collagen using molecular dynamics simulations and docking studies

Short peptide sequences and bolaamphiphiles derived from natural proteins are gaining importance due to their ability to form unique nanoscale architectures for a variety of biological applications. In this work, we have designed six short peptides (triplet or monomeric forms) and two peptide bolaamphiphiles that either incorporate the bioactive collagen motif (Gly-X-Y) or sequences where Gly, Pro, or hydroxyproline (Hyp) are replaced by Ala or His. For the bolaamphiphiles, a malate moiety was used as the aliphatic linker for connecting His with Hyp to create collagen mimics. Stability of the assemblies was assessed through molecular dynamics simulations and results indicated that (Pro-Ala-His)₃ and (Ala-His-Hyp)₃ formed the most stable structures, while the amphiphiles and the monomers showed some disintegration over the course of the 200 ns simulation, though most regained structural integrity and formed fibrillar structures, and micelles by the end of the simulation, likely due to the formation of more thermodynamically stable conformations. Multiple replica simulations (REMD) were also conducted where the sequences were simulated at different temperatures. Our results showed excellent convergence in most cases compared to constant temperature molecular dynamics simulation. Furthermore, molecular docking and MD simulations of the sequences bound to collagen triple helix structure revealed that several of the sequences had a high binding affinity and formed stable complexes, particularly (Pro-Ala-His)₃ and (Ala-His-Hyp)₃. Thus, we have designed new hybrid-peptide-based sequences which may be developed for potential applications as biomaterials for tissue engineering or drug delivery.

Molecular Modeling is an Enabling Approach to Complement and Enhance Channelopathy Research

Hundreds of human membrane proteins form channels that transport necessary ions and compounds, including drugs and metabolites, yet details of their normal function or how function is altered by genetic variants to cause diseases are often unknown. Without this knowledge, researchers are less equipped to develop approaches to diagnose and treat channelopathies. High-resolution computational approaches such as molecular modeling enable researchers to investigate channelopathy protein function, facilitate detailed hypothesis generation, and produce data that is difficult to gather experimentally. Molecular modeling can be tailored to each physiologic context that a protein may act within, some of which may currently be difficult or impossible to assay experimentally. Because many genomic variants are observed in channelopathy proteins from high-throughput sequencing studies, methods with mechanistic value are needed to interpret their effects. The eminent field of structural bioinformatics integrates techniques from multiple disciplines including molecular modeling, computational chemistry, biophysics, and biochemistry, to develop mechanistic hypotheses and enhance the information available for understanding function. Molecular modeling and simulation access 3D and time-dependent information, not currently predictable from sequence. Thus, molecular modeling is valuable for increasing the resolution with which the natural function of protein channels can be investigated, and for interpreting how genomic variants alter them to produce physiologic changes that manifest as channelopathies. © 2022 American Physiological Society. Compr Physiol 12:3141-3166, 2022.

Co-evolutionary distance predictions contain flexibility information

MOTIVATION

Co-evolution analysis can be used to accurately predict residue-residue contacts from multiple sequence alignments. The introduction of machine-learning techniques has enabled substantial improvements in precision and a shift from predicting binary contacts to predict distances between pairs of residues. These developments have significantly improved the accuracy of de novo prediction of static protein structures. With AlphaFold2 lifting the accuracy of some predicted protein models close to experimental levels, structure prediction research will move on to other challenges. One of those areas is the prediction of more than one conformation of a protein. Here, we examine the potential of residue-residue distance predictions to be informative of protein flexibility rather than simply static structure.

RESULTS

We used DMPfold to predict distance distributions for every residue pair in a set of proteins that showed both rigid and flexible behaviour. Residue pairs that were in contact in at least one reference structure were classified as rigid, flexible or neither. The predicted distance distribution of each residue pair was analysed for local maxima of probability indicating the most likely distance or distances between a pair of residues. We found that rigid residue pairs tended to have only a single local maximum in their predicted distance distributions while flexible residue pairs more often had multiple local maxima. These results suggest that the shape of predicted distance distributions contains information on the rigidity or flexibility of a protein and its constituent residues.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Exploring the effect of inhibitor AKB-9778 on VE-PTP by molecular docking and molecular dynamics simulation

Diabetic macular edema, also known as diabetic eye disease, is mainly caused by the overexpression of vascular endothelial protein tyrosine phosphatase (VE-PTP) at hypoxia/ischemic. AKB-9778 is a known VE-PTP inhibitor that can effectively interact with the active site of VE-PTP to inhibit the activity of VE-PTP. However, the binding pattern of VE-PTP with AKB-9778 and the dynamic implications of AKB-9778 on VE-PTP system at the molecular level are poorly understood. Through molecular docking, it was found that the AKB-9778 was docked well in the binding pocket of VE-PTP by the interactions of hydrogen bond and Van der Waals. Furthermore, after molecular dynamic simulations on VE-PTP system and VE-PTP ^AKB-9778 system, a series of postdynamic analyses found that the flexibility and conformation of the active site undergone an obvious transition after VE-PTP binding with AKB-9778. Moreover, by constructing the RIN, it was found that the different interactions in the active site were the detailed reasons for the conformational differences between these two systems. Thus, the finding here might provide a deeper understanding of AKB-9778 as VE-PTP Inhibitor.

Quality and bias of protein disorder predictors

Disorder in proteins is vital for biological function, yet it is challenging to characterize. Therefore, methods for predicting protein disorder from sequence are fundamental. Currently, predictors are trained and evaluated using data from X-ray structures or from various biochemical or spectroscopic data. However, the prediction accuracy of disordered predictors is not calibrated, nor is it established whether predictors are intrinsically biased towards one of the extremes of the order-disorder axis. We therefore generated and validated a comprehensive experimental benchmarking set of site-specific and continuous disorder, using deposited NMR chemical shift data. This novel experimental data collection is fully appropriate and represents the full spectrum of disorder. We subsequently analyzed the performance of 26 widely-used disorder prediction methods and found that these vary noticeably. At the same time, a distinct bias for over-predicting order was identified for some algorithms. Our analysis has important implications for the validity and the interpretation of protein disorder, as utilized, for example, in assessing the content of disorder in proteomes.

Computational design of structured loops for new protein functions

The ability to engineer the precise geometries, fine-tuned energetics and subtle dynamics that are characteristic of functional proteins is a major unsolved challenge in the field of computational protein design. In natural proteins, functional sites exhibiting these properties often feature structured loops. However, unlike the elements of secondary structures that comprise idealized protein folds, structured loops have been difficult to design computationally. Addressing this shortcoming in a general way is a necessary first step towards the routine design of protein function. In this perspective, we will describe the progress that has been made on this problem and discuss how recent advances in the field of loop structure prediction can be harnessed and applied to the inverse problem of computational loop design.

Predicting loop conformational ensembles

Motivation

Protein function is often facilitated by the existence of multiple stable conformations. Structure prediction algorithms need to be able to model these different conformations accurately and produce an ensemble of structures that represent a target's conformational diversity rather than just a single state. Here, we investigate whether current loop prediction algorithms are capable of this. We use the algorithms to predict the structures of loops with multiple experimentally determined conformations, and the structures of loops with only one conformation, and assess their ability to generate and select decoys that are close to any, or all, of the observed structures.

Results

We find that while loops with only one known conformation are predicted well, conformationally diverse loops are modelled poorly, and in most cases the predictions returned by the methods do not resemble any of the known conformers. Our results contradict the often-held assumption that multiple native conformations will be present in the decoy set, making the production of accurate conformational ensembles impossible, and hence indicating that current methodologies are not well suited to prediction of conformationally diverse, often functionally important protein regions.

Contact

marks@stats.ox.ac.uk.

Supplementary information

Supplementary data are available at Bioinformatics online.

A strategy based on thermal flexibility to design triosephosphate isomerase proteins with increased or decreased kinetic stability

Kinetic stability of proteins determines their susceptibility to irreversibly unfold in a time-dependent process, and therefore its half-life. A residue displacement analysis of temperature-induced unfolding molecular dynamics simulations was recently employed to define the thermal flexibility of proteins. This property was found to be correlated with the activation energy barrier (E_act) separating the native from the transition state in the denaturation process. The E_act was determined from the application of a two-state irreversible model to temperature unfolding experiments using differential scanning calorimetry (DSC). The contribution of each residue to the thermal flexibility of proteins is used here to propose multiple mutations in triosephosphate isomerase (TIM) from Trypanosoma brucei (TbTIM) and Trypanosoma cruzi (TcTIM), two parasites closely related by evolution. These two enzymes, taken as model systems, have practically identical structure but large differences in their kinetic stability. We constructed two functional TIM variants with more than twice and less than half the activation energy of their respective wild-type reference structures. The results show that the proposed strategy is able to identify the crucial residues for the kinetic stability in these enzymes. As it occurs with other protein properties reflecting their complex behavior, kinetic stability appears to be the consequence of an extensive network of inter-residue interactions, acting in a concerted manner. The proposed strategy to design variants can be used with other proteins, to increase or decrease their functional half-life.

Re-emergence of an orphan therapeutic target for the treatment of resistant prostate cancer - a thorough conformational and binding analysis for ROR-γ protein

Recent studies have linked a deadly form of prostate cancer known as metastatic castration-resistant prostate cancer to retinoic acid-related orphan-receptor gamma (ROR-γ). Most of these studies continued to place ROR-γ as orphan because of unidentifiable inhibitor. Recently identified inhibitors of ROR-γ and their therapeutic potential were evaluated, among which inhibitor XY018 was the potent. However, molecular understanding of the conformational features of XY018-ROR-γ complex is still elusive. Herein, molecular dynamics simulations were conducted on HC9-ROR-γ and XY018-ROR-γ complexes to understand their conformational features at molecular level and the influence of XY018 binding on the dynamics of ROR-γ with the aid of post-dynamic analytical tools. These include; principal component analysis, radius of gyration, binding free energy calculation (MM/GBSA), per-residue fluctuation and hydrogen bond occupancy. Findings from this study revealed that (1) hydrophobic packing contributes significantly to binding free energy, (2) Ile136 and Leu60 exhibited high hydrogen-bond occupancy in XY018-ROR-γ and HC9-ROR-γ, respectively, (3) XY018-ROR-γ displayed a relatively high loop region residue fluctuation compared to HC9-ROR-γ, (4) electrostatic interactions are a potential binding force in XY018-ROR-γ complex compared to HC9-ROR-γ, (5) XY018-ROR-γ assumes a rigid conformation which is highlighted by a decrease in residual fluctuation, (6) XY018 could potentially induce pseudoporphyria, nephritis and interstitial nephritis but potentially safe in renal failure. This study could serve as a base line for the design of new potential ROR-γ inhibitors.

Interplay between Protein Thermal Flexibility and Kinetic Stability

Kinetic stability is a key parameter to comprehend protein behavior and it plays a central role to understand how evolution has reached the balance between function and stability in cell-relevant timescales. Using an approach that includes simulations, protein engineering, and calorimetry, we show that there is a clear correlation between kinetic stability determined by differential scanning calorimetry and protein thermal flexibility obtained from a novel method based on temperature-induced unfolding molecular dynamics simulations. Thermal flexibility quantitatively measures the increment of the conformational space available to the protein when energy in provided. The (β/α)₈ barrel fold of two closely related by evolution triosephosphate isomerases from two trypanosomes are used as model systems. The kinetic stability-thermal flexibility correlation has predictive power for the studied proteins, suggesting that the strategy and methodology discussed here might be applied to other proteins in biotechnological developments, evolutionary studies, and the design of protein based therapeutics.

Non-active site mutations disturb the loop dynamics, dimerization, viral budding and egress of VP40 of the Ebola virus

The first account of the dynamic features of the loop region of VP40 of the Ebola virus (EboV) using accelerated molecular dynamics (aMD) simulations is reported herein. Due to its major role in the Ebola life cycle, VP40 is considered a promising therapeutic target. The available experimental data on the N-terminal domain (NTD) loop indicates that mutations K127A, T129A and N130A demonstrate an unrecognized role for NTD-plasma membrane (PM) interaction for efficient VP40-PM localization, oligomerization, matrix assembly and egress. Despite experimental results, the molecular description of VP40 and the information it can provide still remain vague. Therefore, to gain further molecular insight into the effect of mutations on the loop region of VP40 and its effects on the overall protein conformation and VP40 dimerization, aMD simulations and post-dynamic analyses were employed for wildtype (WT) and mutant systems. The results showed significant variations in the presence of mutations as per RMSF, RMSD, R_g, PCA and distance calculations in comparison to the WT. These results could provide researchers with insight with regards to the conformational aspects concerning VP40 and its close relation to the experimental data. We believe that the results presented in this study will ultimately provide a useful understanding of the structural landscape of the loop region of VP40, which would contribute towards the discovery of novel EboV inhibitors.

Early Folding Events, Local Interactions, and Conservation of Protein Backbone Rigidity

Protein folding is in its early stages largely determined by the protein sequence and complex local interactions between amino acids, resulting in lower energy conformations that provide the context for further folding into the native state. We compiled a comprehensive data set of early folding residues based on pulsed labeling hydrogen deuterium exchange experiments. These early folding residues have corresponding higher backbone rigidity as predicted by DynaMine from sequence, an effect also present when accounting for the secondary structures in the folded protein. We then show that the amino acids involved in early folding events are not more conserved than others, but rather, early folding fragments and the secondary structure elements they are part of show a clear trend toward conserving a rigid backbone. We therefore propose that backbone rigidity is a fundamental physical feature conserved by proteins that can provide important insights into their folding mechanisms and stability.

Impacts of the G145R Mutation on the Structure and Immunogenic Activity of the Hepatitis B Surface Antigen: A Computational Analysis

BACKGROUND

Vaccine-escaped hepatitis B virus (HBV) mutations occur within the "a" determinant area, which is located in the major hydrophilic region (MHR) of the hepatitis B surface antigen (HBsAg) protein. It is now well established that the common G145R mutation is highly capable of escaping from HBsAg immune recognition. However, the impacts of this mutation on the structure and immunogenic activity of HBsAg have been poorly investigated.

OBJECTIVES

The present study analyzed the effects of the G145R mutation on the structure and immunogenic activity of the HBsAg.

MATERIALS AND METHODS

Three-dimensional (3D) structure of HBsAg for both the wild-type and G145R mutant were predicted and refined using several web tools. After quantitative evaluations, the effects of the G145R mutation on the secondary and 3D structures of the HBsAg were investigated. In parallel, the immunogenic activity of the wild-type and mutant HBsAg was also analyzed using a ClusPro docking server as well as the IEDB web tool. Further analyses were performed via molecular dynamics (MD) simulations using the GROMACS v5.0.2 simulation package.

RESULTS

The G145R mutation causes a considerable reduction in the immunogenic activity of the HBsAg through a conformational change in the HBsAg antigenic loops. This mutation inserts a new β-strand in the "a" determinant region of the HBsAg, leading to a reduced binding affinity to its monoclonal antibody, MAb12. The G145R mutation also increased the compactness and stability of the HBsAg by enhancing the rigidity of the "a" determinant.

CONCLUSIONS

These data will be beneficial for designing more advanced antibodies for the recognition of the HBsAg in diagnostics. In addition, the results of this study may assist in the design or development of more effective hepatitis B vaccines.

Using Wavelet Analysis To Assist in Identification of Significant Events in Molecular Dynamics Simulations

Long time scale molecular dynamics (MD) simulations of biological systems are becoming increasingly commonplace due to the availability of both large-scale computational resources and significant advances in the underlying simulation methodologies. Therefore, it is useful to investigate and develop data mining and analysis techniques to quickly and efficiently extract the biologically relevant information from the incredible amount of generated data. Wavelet analysis (WA) is a technique that can quickly reveal significant motions during an MD simulation. Here, the application of WA on well-converged long time scale (tens of μs) simulations of a DNA helix is described. We show how WA combined with a simple clustering method can be used to identify both the physical and temporal locations of events with significant motion in MD trajectories. We also show that WA can not only distinguish and quantify the locations and time scales of significant motions, but by changing the maximum time scale of WA a more complete characterization of these motions can be obtained. This allows motions of different time scales to be identified or ignored as desired.

The effect of chirality and steric hindrance on intrinsic backbone conformational propensities: tools for protein design

The conformational propensities of amino acids are an amalgamation of sequence effects, environmental effects and underlying intrinsic behavior. Many have attempted to investigate neighboring residue effects to aid in our understanding of protein folding and improve structure prediction efforts, especially with respect to difficult to characterize states, such as disordered or unfolded states. Host-guest peptide series are a useful tool in examining the propensities of the amino acids free from the surrounding protein structure. Here, we compare the distributions of the backbone dihedral angles (φ/ψ) of the 20 proteogenic amino acids in two different sequence contexts using the AAXAA and GGXGG host-guest pentapeptide series. We further examine their intrinsic behaviors across three environmental contexts: water at 298 K, water at 498 K, and 8 M urea at 298 K. The GGXGG systems provide the intrinsic amino acid propensities devoid of any conformational context. The alanine residues in the AAXAA series enforce backbone chirality, thereby providing a model of the intrinsic behavior of amino acids in a protein chain. Our results show modest differences in φ/ψ distributions due to the steric constraints of the Ala side chains, the magnitudes of which are dependent on the denaturing conditions. One of the strongest factors modulating φ/ψ distributions was the protonation of titratable side chains, and the largest differences observed were in the amino acid propensities for the rarely sampled αL region.

REMD Simulations Reveal the Dynamic Profile and Mechanism of Action of Deleterious, Rescuing, and Stabilizing Perturbations to NBD1 from CFTR

Cystic Fibrosis (CF) is a lethal, genetic disease caused by mutations to the CFTR chloride channel. The most common CF causing mutation is the deletion of F508 from the first Nucleotide Binding Domain (F508del-NBD1). This mutation leads to a thermally unstable domain and a misfolded, nonfunctioning CFTR. Replica Exchange MD simulations were used to simulate seven NBD1 constructs including wt and F508del-NBD1 both alone and in the presence of known rescuing mutations as well as F508del-NBD1 in complex with a known small (ligand) stabilizer. Analyzing the resulting trajectories suggests that differences in the biochemical properties of the constructs result from local and coupled differences in their dynamic profiles. A comparative analysis of these profiles as well as of the resulting trajectories reveals how the different perturbations exert their deleterious, rescuing, and stabilizing effects on NBD1. These simulations may therefore be useful for the design and mechanism-of-action analysis of new NBD1 stabilizers.

N-alkylacylamides in thin films display infrared spectra of 3₁₀-, α-, and π-helices with visible static and dynamic growth phases

A peptide model is a physical system containing a CONH group, the simplest being HCONHCH3 , N-methylformamide (NMF). We have discovered that NMF and N-methylacetamide (NMA), which form hydrogen-bonded oligomers in thin films on a planar AgX fiber, display infrared (IR) spectra with peaks like those of polypeptide helices. Structures can be assigned by their amide I maxima near 1672 (3(10)), 1655 (3(10)), 1653 (α), 1655 (π), and 1635 cm(-1) (π), which are the first IR data for the π-helix. Sharp peaks are an outcome of immobilization of polar species on the polar surface of silver halides. We report the first use of expanded thin-film IR spectroscopy, in which plots of every spectrum over the amide I-II range show pauses or slow stages in the increase or decrease of absorption. These are identified as static phases followed by dynamic phases, with the incremental gain or loss of a helix turn. A general theory can be stated for such processes. Density functional calculations show that the NMA α-helix pentamer (crystal structure geometry) is transformed into a π-helix-like form. For the first time, an entire sequence (3(10)-helix, α-helix, π-helix, quasiplanar species) of spectra has been recorded for NMA.

Coagulation, flocculation, and denaturation: a century of research into protoplasmic theories of anesthesia

Within two decades of the discovery of anesthesia, the physicochemical concept of colloid and the biological concept of protoplasm had emerged. Fusion of these concepts into a theoretical framework, which has been largely forgotten decades ago, promised to uncover fundamental biological truths and determined research into anesthetic mechanisms for a century after "Ether Day." Observations of optical changes in unstained tissue were condensed into a theory of anesthesia by coagulation of protoplasm in the 1870s. The underlying hypotheses, conformational changes of proteins within the protoplasm cause all behavioral effects of anesthesia, continued to be pursued well into the 20th century. The goal was to explain anesthesia using physical chemistry within a fundamental cell biological framework. This large body of work, swept aside during the decades of lipid membrane hegemony, has remained in obscurity even after proteins in excitable membranes became firmly established as mediators of the immediate anesthetic effects. This article is a reminder of the prolonged interdisciplinary research effort dedicated to "protoplasmic theories" at a time when attention is increasingly directed toward examining the nature of (un)consciousness well as noncanonical consequences of anesthetic exposure that are not easily accounted for within conventional pharmacological concepts.

Dynameomics: data-driven methods and models for utilizing large-scale protein structure repositories for improving fragment-based loop prediction

Protein function is intimately linked to protein structure and dynamics yet experimentally determined structures frequently omit regions within a protein due to indeterminate data, which is often due protein dynamics. We propose that atomistic molecular dynamics simulations provide a diverse sampling of biologically relevant structures for these missing segments (and beyond) to improve structural modeling and structure prediction. Here we make use of the Dynameomics data warehouse, which contains simulations of representatives of essentially all known protein folds. We developed novel computational methods to efficiently identify, rank and retrieve small peptide structures, or fragments, from this database. We also created a novel data model to analyze and compare large repositories of structural data, such as contained within the Protein Data Bank and the Dynameomics data warehouse. Our evaluation compares these structural repositories for improving loop predictions and analyzes the utility of our methods and models. Using a standard set of loop structures, containing 510 loops, 30 for each loop length from 4 to 20 residues, we find that the inclusion of Dynameomics structures in fragment-based methods improves the quality of the loop predictions without being dependent on sequence homology. Depending on loop length, ∼ 25-75% of the best predictions came from the Dynameomics set, resulting in lower main chain root-mean-square deviations for all fragment lengths using the combined fragment library. We also provide specific cases where Dynameomics fragments provide better predictions for NMR loop structures than fragments from crystal structures. Online access to these fragment libraries is available at http://www.dynameomics.org/fragments.

Computational library design for increasing haloalkane dehalogenase stability

We explored the use of a computational design framework for the stabilization of the haloalkane dehalogenase LinB. Energy calculations, disulfide bond design, molecular dynamics simulations, and rational inspection of mutant structures predicted many stabilizing mutations. Screening of these in small mutant libraries led to the discovery of seventeen point mutations and one disulfide bond that enhanced thermostability. Mutations located in or contacting flexible regions of the protein had a larger stabilizing effect than mutations outside such regions. The combined introduction of twelve stabilizing mutations resulted in a LinB mutant with a 23 °C increase in apparent melting temperature (Tm,app , 72.5 °C) and an over 200-fold longer half-life at 60 °C. The most stable LinB variants also displayed increased compatibility with co-solvents, thus allowing substrate conversion and kinetic resolution at much higher concentrations than with the wild-type enzyme.

Enzymatic activity of Lecithin:retinol acyltransferase: a thermostable and highly active enzyme with a likely mode of interfacial activation

Lecithin:retinol acyltransferase (LRAT) plays a major role in the vertebrate visual cycle. Indeed, it is responsible for the esterification of all-trans retinol into all-trans retinyl esters, which can then be stored in microsomes or further metabolized to produce the chromophore of rhodopsin. In the present study, a detailed characterization of the enzymatic properties of truncated LRAT (tLRAT) has been achieved using in vitro assay conditions. A much larger tLRAT activity has been obtained compared to previous reports and to an enzyme with a similar activity. In addition, tLRAT is able to hydrolyze phospholipids bearing different chain lengths with a preference for micellar aggregated substrates. It therefore presents an interfacial activation property, which is typical of classical phospholipases. Furthermore, given that stability is a very important quality of an enzyme, the influence of different parameters on the activity and stability of tLRAT has thus been studied in detail. For example, storage buffer has a strong effect on tLRAT activity and high enzyme stability has been observed at room temperature. The thermostability of tLRAT has also been investigated using circular dichroism and infrared spectroscopy. A decrease in the activity of tLRAT was observed beyond 70°C, accompanied by a modification of its secondary structure, i.e. a decrease of its α-helical content and the appearance of unordered structures and aggregated β-sheets. Nevertheless, residual activity could still be observed after heating tLRAT up to 100°C. The results of this study highly improved our understanding of this enzyme.

The influence of N-linked glycans on the molecular dynamics of the HIV-1 gp120 V3 loop

N-linked glycans attached to specific amino acids of the gp120 envelope trimer of a HIV virion can modulate the binding affinity of gp120 to CD4, influence coreceptor tropism, and play an important role in neutralising antibody responses. Because of the challenges associated with crystallising fully glycosylated proteins, most structural investigations have focused on describing the features of a non-glycosylated HIV-1 gp120 protein. Here, we use a computational approach to determine the influence of N-linked glycans on the dynamics of the HIV-1 gp120 protein and, in particular, the V3 loop. We compare the conformational dynamics of a non-glycosylated gp120 structure to that of two glycosylated gp120 structures, one with a single, and a second with five, covalently linked high-mannose glycans. Our findings provide a clear illustration of the significant effect that N-linked glycosylation has on the temporal and spatial properties of the underlying protein structure. We find that glycans surrounding the V3 loop modulate its dynamics, conferring to the loop a marked propensity towards a more narrow conformation relative to its non-glycosylated counterpart. The conformational effect on the V3 loop provides further support for the suggestion that N-linked glycosylation plays a role in determining HIV-1 coreceptor tropism.

Early steps in thermal unfolding of superoxide dismutase 1 are similar to the conformational changes associated with the ALS-associated A4V mutation

There are over 100 mutations in Cu/Zn superoxide dismutase (SOD1) that result in a subset of familial amyotrophic lateral sclerosis (fALS) cases. The hypothesis that dissociation of the dimer, misfolding of the monomer and subsequent aggregation of mutant SOD1 leads to fALS has been gaining support as an explanation for how these disparate missense mutations cause the same disease. These forms are only responsible for a fraction of the ALS cases; however, the rest are sporadic. Starting with a folded apo monomer, the species considered most likely to be involved in misfolding, we used high-temperature all-atom molecular dynamics simulations to explore the events of the wild-type protein unfolding through the denatured state. All simulations showed early loss of structure along the β5-β6 edge of the β-sandwich, supporting earlier findings of instability in this region. Transition state structures identified from the simulations are in good agreement with experiment, providing detailed, validated molecular models for this elusive state. Furthermore, we compare the process of thermal unfolding investigated here to that of the lethal A4V mutant-induced unfolding at physiological temperature and find that the pathways are very similar.

SOD1 exhibits allosteric frustration to facilitate metal binding affinity

Superoxide dismutase-1 (SOD1) is a ubiquitous, Cu and Zn binding, free-radical defense enzyme whose misfolding and aggregation play a potential key role in amyotrophic lateral sclerosis, an invariably fatal neurodegenerative disease. Over 150 mutations in SOD1 have been identified with a familial form of the disease, but it is presently not clear what unifying features, if any, these mutants share to make them pathogenic. Here, we develop several unique computational assays for probing the thermo-mechanical properties of both ALS-associated and rationally designed SOD1 variants. Allosteric interaction-free energies between residues and metals are calculated, and a series of atomic force microscopy experiments are simulated with variable tether positions to quantify mechanical rigidity "fingerprints" for SOD1 variants. Mechanical fingerprinting studies of a series of C-terminally truncated mutants, along with an analysis of equilibrium dynamic fluctuations while varying native constraints, potential energy change upon mutation, frustratometer analysis, and analysis of the coupling between local frustration and metal binding interactions for a glycine scan of 90 residues together, reveal that the apo protein is internally frustrated, that these internal stresses are partially relieved by mutation but at the expense of metal-binding affinity, and that the frustration of a residue is directly related to its role in binding metals. This evidence points to apo SOD1 as a strained intermediate with "self-allostery" for high metal-binding affinity. Thus, the prerequisites for the function of SOD1 as an antioxidant compete with apo state thermo-mechanical stability, increasing the susceptibility of the protein to misfold in the apo state.

Using simulations to provide the framework for experimental protein folding studies

Molecular dynamics simulations are a powerful theoretical tool to model the protein folding process in atomistic details under realistic conditions. Combined with a number of experimental techniques, simulations provide a detailed picture of how a protein folds or unfolds in the presence of explicit solvent and other molecular species, such as cosolvents, osmolytes, cofactors, active binding partners or inert crowding agents. The denaturing effects of temperature, pressure and external mechanical forces can also be probed. Qualitative and quantitative agreement with experiment contributes to a comprehensive molecular picture of protein states along the folding/unfolding pathway. The variety of systems examined reveals key features of the protein folding process.

When a domain is not a domain, and why it is important to properly filter proteins in databases: conflicting definitions and fold classification systems for structural domains make filtering of such databases imperative

Membership in a protein domain database does not a domain make; a feature we realized when generating a consensus view of protein fold space with our consensus domain dictionary (CDD). This dictionary was used to select representative structures for characterization of the protein dynameome: the Dynameomics initiative. Through this endeavor we rejected a surprising 40% of the 1,695 folds in the CDD as being non-autonomous folding units. Although some of this was due to the challenges of grouping similar fold topologies, the dissonance between the cataloguing and structural qualification of protein domains remains surprising. Another potential factor is previously overlooked intrinsic disorder; predictions suggest that 40% of proteins have either local or global disorder. One thing is clear, filtering a structural database and ensuring a consistent definition for protein domains is crucial, and caution is prescribed when generalizations of globular domains are drawn from unfiltered protein domain datasets.

Dynamic features of homodimer interfaces calculated by normal-mode analysis

Knowledge of the dynamic features of protein interfaces is necessary for a deeper understanding of protein-protein interactions. We performed normal-mode analysis (NMA) of 517 nonredundant homodimers and their protomers to characterize dimer interfaces from a dynamic perspective. The motion vector calculated by NMA for each atom of a dimer was decomposed into internal and external motion vectors in individual component subunits, followed by the averaging of time-averaged correlations between these vectors over atom pairs in the interface. This averaged correlation coefficient (ACC) was defined for various combinations of vectors and investigated in detail. ACCs decrease exponentially with an increasing interface area and r-value, that is, interface area divided by the entire subunit surface area. As the r-value reflects the nature of dimer formation, the result suggests that both the interface area and the nature of dimer formation are responsible for the dynamic properties of dimer interfaces. For interfaces with small or medium r-values and without intersubunit entanglements, ACCs are found to increase on dimer formation when compared with those in the protomer state. In contrast, ACCs do not increase on dimer formation for interfaces with large r-values and intersubunit entanglements such as in interwinding dimers. Furthermore, relationships between ACCs for intrasubunit atom pairs and for intersubunit atom pairs are found to significantly differ between interwinding and noninterwinding dimers for external motions. External motions are considered as an important factor for characterizing dimer interfaces.

A comparison of multiscale methods for the analysis of molecular dynamics simulations

Molecular dynamics (MD) is the only technique available for obtaining dynamic protein data at atomic spatial resolution and picosecond or finer temporal resolution. In recent years, the cost of computational resources has decreased exponentially while the number of known protein structures, many of which are not characterized biochemically, has increased rapidly. These events have led to an increase in the use of MD in biological research, both to examine phenomena that cannot be resolved experimentally and to generate hypotheses that direct further experimental research. In fact, several databases of MD simulations have arisen in recent years. MD simulations, and especially MD simulation databases, contain massive amounts of data, yet interesting phenomena often occur over very short time periods and on the scale of only a few atoms. Analysis of such data must balance these fine-detail events with the global picture they create. Here, we address the multiscale nature of the problem by comparing several MD analysis methods to show their strengths and weaknesses at various scales using the wild-type and R282W mutant forms of the DNA-binding domain of protein p53. By leveraging these techniques together, we are able to pinpoint fine-detail and big picture differences between the protein's variants. Our analyses indicate that the R282W mutation of p53 destabilizes the L1 loop and loosens the H2 helix conformation, but the loosened L1 loop can be rescued by residue H115, preventing the R282W mutation from completely destabilizing the protein or abolishing activity.

Protein structure along the order-disorder continuum

Thermal fluctuations cause proteins to adopt an ensemble of conformations wherein the relative stability of the different ensemble members is determined by the topography of the underlying energy landscape. “Folded” proteins have relatively homogeneous ensembles, while “unfolded” proteins have heterogeneous ensembles. Hence, the labels “folded” and “unfolded” represent attempts to provide a qualitative characterization of the extent of structural heterogeneity within the underlying ensemble. In this work, we introduce an information-theoretic order parameter to quantify this conformational heterogeneity. We demonstrate that this order parameter can be estimated in a straightforward manner from an ensemble and is applicable to both unfolded and folded proteins. In addition, a simple formula for approximating the order parameter directly from crystallographic B factors is presented. By applying these metrics to a large sample of proteins, we show that proteins span the full range of the order–disorder axis.

Protein folds and protein folding

The classification of protein folds is necessarily based on the structural elements that distinguish domains. Classification of protein domains consists of two problems: the partition of structures into domains and the classification of domains into sets of similar structures (or folds). Although similar topologies may arise by convergent evolution, the similarity of their respective folding pathways is unknown. The discovery and the characterization of the majority of protein folds will be followed by a similar enumeration of available protein folding pathways. Consequently, understanding the intricacies of structural domains is necessary to understanding their collective folding pathways. We review the current state of the art in the field of protein domain classification and discuss methods for the systematic and comprehensive study of protein folding across protein fold space via atomistic molecular dynamics simulation. Finally, we discuss our large-scale Dynameomics project, which includes simulations of representatives of all autonomous protein folds.

Dynameomics: protein dynamics and unfolding across fold space

All currently known structures of proteins together define ‘protein fold space’. To increase the general understanding of protein dynamics and protein folding, we selected a set of 807 proteins and protein domains that represent 95% of the currently known autonomous folded domains present in globular proteins. Native state and unfolding simulations of these representatives are now complete and accessible via a novel database containing over 11 000 simulations. Because protein folding is a microscopically reversible process, these simulations effectively sample protein folding across all of protein fold space. Here, we give an overview of how the representative proteins were selected and how the simulations were performed and validated. We then provide examples of different types of analyses that can be performed across our large set of simulations, made possible by the database approach. We further show how the unfolding simulations can be used to compare unfolding of structural elements in isolation and in different structural contexts, using as an example a short, triple stranded β-sheet that forms the WW domain and is present in several larger unrelated proteins.

Evidence of functional protein dynamics from X-ray crystallographic ensembles

It is widely recognized that representing a protein as a single static conformation is inadequate to describe the dynamics essential to the performance of its biological function. We contrast the amino acid displacements below and above the protein dynamical transition temperature, T_D∼215K, of hen egg white lysozyme using X-ray crystallography ensembles that are analyzed by molecular dynamics simulations as a function of temperature. We show that measuring structural variations across an ensemble of X-ray derived models captures the activation of conformational states that are of functional importance just above T_D, and they remain virtually identical to structural motions measured at 300K. Our results highlight the ability to observe functional structural variations across an ensemble of X-ray crystallographic data, and that residue fluctuations measured in MD simulations at room temperature are in quantitative agreement with the experimental observable.

There is a well-recognized gap between the dynamical motions of proteins required to execute function and the experimental techniques capable of capturing that motion at the atomic level. We show that much experimental detail of dynamical motion is already present in X-ray crystallographic data, which arises from being solved by different research groups using different methodologies under different crystallization conditions, which then capture an ensemble of structures whose variations can be quantified on a residue-by-residue level using local density correlations. We contrast the amino acid displacements below and above the protein dynamical transition temperature, T_D∼215K, of hen egg white lysozyme by comparing the X-ray ensemble to MD ensembles as a function of temperature. We show that measuring structural variations across an ensemble of X-ray derived models captures the activation of conformational states that are of functional importance just above T_D and they remain virtually identical to structural motions measured at 300K. It provides a novel analysis of large X-ray ensemble data that is useful for the broader structural biology community.

Dynameomics: a comprehensive database of protein dynamics

The dynamic behavior of proteins is important for an understanding of their function and folding. We have performed molecular dynamics simulations of the native state and unfolding pathways of over 2000 protein/peptide systems (approximately 11,000 independent simulations) representing the majority of folds in globular proteins. These data are stored and organized using an innovative database approach, which can be mined to obtain both general and specific information about the dynamics and folding/unfolding of proteins, relevant subsets thereof, and individual proteins. Here we describe the project in general terms and the type of information contained in the database. Then we provide examples of mining the database for information relevant to protein folding, structure building, the effect of single-nucleotide polymorphisms, and drug design. The native state simulation data and corresponding analyses for the 100 most populated metafolds, together with related resources, are publicly accessible through http://www.dynameomics.org.

Fine grained sampling of residue characteristics using molecular dynamics simulation

In a fine-grained computational analysis of protein structure, we investigated the relationships between a residue's backbone conformations and its side-chain packing as well as conformations. To produce continuous distributions in high resolution, we ran molecular dynamics simulations over a set of protein folds (dynameome). In effect, the dynameome dataset samples not only the states well represented in the PDB but also the known states that are not well represented in the structural database. In our analysis, we characterized the mutual influence among the backbone phi,psi angles with the first side-chain torsion angles (chi(1)) and the volumes occupied by the side-chains. The dependencies of these relationships on side-chain environment and amino acids are further explored. We found that residue volumes exhibit dependency on backbone 2 degrees structure conformation: side-chains pack more densely in extended beta-sheet than in alpha-helical structures. As expected, residue volumes on the protein surface were larger than those in the interior. The first side-chain torsion angles are found to be dependent on the backbone conformations in agreement with previous studies, but the dynameome dataset provides higher resolution of rotamer preferences based on the backbone conformation. All three gauche(-), gauche(+), and trans rotamers show different patterns of phi,psi dependency, and variations in chi(1) value are skewed from their canonical values to relieve the steric strains. By demonstrating the utility of dynameomic modeling on the native state ensemble, this study reveals details of the interplay among backbone conformations, residue volumes and side-chain conformations.

Temperature dependence of the flexibility of thermophilic and mesophilic flavoenzymes of the nitroreductase fold

A widely held hypothesis regarding the thermostability of thermophilic proteins states asserts that, at any given temperature, thermophilic proteins are more rigid than their mesophilic counterparts. Many experimental and computational studies have addressed this question with conflicting results. Here, we compare two homologous enzymes, one mesophilic (Escherichia coli FMN-dependent nitroreductase; NTR) and one thermophilic (Thermus thermophilus NADH oxidase; NOX), by multiple molecular dynamics simulations at temperatures from 5 to 100 degrees C. We find that the global rigidity/flexibility of the two proteins, assessed by a variety of metrics, is similar on the time scale of our simulations. However, the thermophilic enzyme retains its native conformation to a much greater degree at high temperature than does the mesophilic enzyme, both globally and within the active site. The simulations identify the helix F-helix G 'arm' as the region with the greatest difference in loss of native contacts between the two proteins with increasing temperature. In particular, a network of electrostatic interactions holds helix F to the body of the protein in the thermophilic protein, and this network is absent in the mesophilic counterpart.