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The Dynameomics project contains native state and unfolding simulations of 807 protein domains, where each domain is representative of a different metafold; these metafolds encompass ~97% of protein fold space. There is a long-standing question in structural biology as to whether proteins in the same fold family share the same folding/unfolding characteristics. Using molecular dynamics simulations from the Dynameomics project, we conducted a detailed study of protein unfolding/folding pathways for 5 protein domains from the immunoglobulin (Ig)-like β-sandwich metafold (the highest ranked metafold in our database). The domains have sequence similarities ranging from 4 to 15% and are all from different SCOP superfamilies, yet they share the same overall Ig-like topology. Despite having very different amino acid sequences, the dominant unfolding pathway is very similar for the 5 proteins, and the secondary structures that are peripheral to the aligned, shared core domain add variability to the unfolding pathway. Aligned residues in the core domain display consensus structure in the transition state primarily through conservation of hydrophobic positions. Commonalities in the obligate folding nucleus indicate that insights into the major events in the folding/unfolding of other domains from this metafold may be obtainable from unfolding simulations of a few representative proteins., (© The Author(s) 2019. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.)

Computational resources have contributed to the design and engineering of novel proteins by integrating genomic, structural and dynamic aspects of proteins. Non-canonical amino acids, such as d-amino acids, expand the available sequence space for designing and engineering proteins; however, the rotamer libraries for d-amino acids are usually constructed as the mirror images of l-amino acid rotamer libraries, an assumption that has not been tested. To this end, we have performed molecular dynamics (MD) simulations of model host-guest peptide systems containing d-amino acids. Our simulations systematically address the applicability of the mirror image convention as well as the effects of neighboring residue chirality. Rotamer libraries derived from these systems provide realistic rotamer distributions suitable for use in both rational and computational design workflows. Our simulations also address the impact of chirality on the intrinsic conformational preferences of amino acids, providing fundamental insights into the relationship between chirality and biomolecular dynamics. While d-amino acids are rare in naturally occurring proteins, they are used in designed proteins to stabilize a desired conformation, increase bioavailability or confer favorable biochemical and physical attributes. Here, we present d-amino acid rotamer libraries derived from MD simulations of alanine-based host-guest pentapeptides and show how certain residues can deviate from mirror image symmetry. Our simulations directly model d-amino acids as guest residues within the chiral l-Ala and d-Ala pentapeptide series to explicitly incorporate any contributions resulting from the chiralities of neighboring residues.

The p53 tumor suppressor protein performs a critical role in stimulating apoptosis and cell cycle arrest in response to oncogenic stress. The function of p53 can be compromised by mutation, leading to increased risk of cancer; approximately 50% of cancers are associated with mutations in the p53 gene, the majority of which are in the core DNA-binding domain. The Y220C mutation of p53, for example, destabilizes the core domain by 4 kcal/mol, leading to rapid denaturation and aggregation. The associated loss of tumor suppressor functionality is associated with approximately 75 000 new cancer cases every year. Destabilized p53 mutants can be 'rescued' and their function restored; binding of a small molecule into a pocket on the surface of mutant p53 can stabilize its wild-type structure and restore its function. Here, we describe an in silico algorithm for identifying potential rescue pockets, including the algorithm's integration with the Dynameomics molecular dynamics data warehouse and the DIVE visual analytics engine. We discuss the results of the application of the method to the Y220C p53 mutant, entailing finding a putative rescue pocket through MD simulations followed by an in silico search for stabilizing ligands that dock into the putative rescue pocket. The top three compounds from this search were tested experimentally and one of them bound in the pocket, as shown by nuclear magnetic resonance, and weakly stabilized the mutant., (© The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.)

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., (© The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.)

D-amino acids are useful building blocks for de novo peptide design and they play a role in aging-related diseases associated with gradual protein racemization. For amino acids with achiral side chains, one should be able to presume that the conformational propensities of L- and D-amino acids are a reflection of one another due to the straightforward geometric inversion at the Cα atom. However, this presumption does not account for the directionality of the backbone dipole and the inverted propensities have never been definitively confirmed in this context. Furthermore, there is little known of how alternative side chain chirality affects the backbone conformations of isoleucine and threonine. Using a GGXGG host-guest pentapeptide system, we have completed exhaustive sampling of the conformational propensities of the D-amino acids, including D-allo-isoleucine and D-allo-threonine, using atomistic molecular dynamics simulations. Comparison of these simulations with the same systems hosting the cognate L-amino acids verifies that the intrinsic backbone conformational propensities of the D-amino acids are the inverse of their cognate L-enantiomers. Where amino acids have a chiral center in their side chain (Thr, Ile) the β-configuration affects the backbone sampling, which in turn can confer different biological properties., (© The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.)

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.

A thermostabilized variant (UVF) of the engrailed homeodomain (EnHD) was previously engineered by Mayo and co-workers. The melting temperature of the non-natural, designed protein is 50°C higher than the natural wild-type protein (>99 vs. 52°C), and the two proteins share 22% sequence identity. We have performed extensive (1 μs) all-atom, explicit solvent molecular dynamics simulations of the wild-type and engineered proteins to investigate their structural and dynamic properties at room temperature and at 100°C. Our simulations are in good agreement with nuclear magnetic resonance data available for the two proteins [nuclear Overhauser effect crosspeaks (NOEs), J-coupling constants and order parameters for EnHD; and NOEs for UVF], showing that we reproduce the backbone dynamics and side chain packing in the native state of both proteins. UVF was more dynamic at room temperature than EnHD, with respect to both its backbone and side chain motion. When the temperature was raised, the thermostable protein maintained this mobility while retaining its native conformation. EnHD, on the other hand, was unable to maintain its more rigid native structure at higher temperature and began to unfold. Heightened protein dynamics leading to promiscuous and dynamically interchangeable amino acid contacts makes UVF more tolerant to increasing temperature, providing a molecular explanation for heightened thermostability of this protein.

The prion diseases are a class of neurodegenerative diseases caused by the misfolding and aggregation of the prion protein (PrP(C)) into toxic and infectious oligomers (PrP(Sc)). These oligomers are critical to understanding and combating these diseases. Differences in the sequence of PrP affect disease susceptibility, likely by shifting the tolerance of the protein for adaptation to PrP(Sc) conformations and/or the recognition event between PrP(Sc) and PrP(C) prior to conversion of the PrP(C). We selected two sets of PrP(Sc)-resistant mutant sequences for solvated atomistic molecular dynamics simulation to investigate the structural basis of resistance. The first group involved mutation in the X-loop (residues 164-171) resulting from selective breeding of sheep. The second group included eight mutants in mice identified by random mutagenesis targeting helix C followed by screening in cell cultures. Multiple simulations were performed of 14 different mutant and control constructs under different pH conditions for a total of 3.6 μs of simulation time. The X-loop formed a stable turn at neutral pH in wild-type PrP from both species. PrP(Sc)-resistant mutations disrupted this turn even though only one of the mutants is in the X-loop. The X-loop is compact and buried in our previously described spiral models of PrP(Sc)-like oligomers. On the basis of the findings presented here and in the context of the spiral oligomer model, we propose that expansion of the X-loop disrupts protofibril packing, providing a structural basis for resistance.

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.

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.

It has been suggested that denatured proteins are predisposed toward the left-handed polyproline II (P(II)) conformation. One possible source of P(II) stability in the denatured state is water bridges. Water bridges are networks of water molecules that link nearby hydrogen bond acceptors and/or donors on proteins. On the basis of the proposed behavior of P(II) and water bridges, the propensity of a residue to participate in water bridges should be correlated with its P(II) propensity. To test this hypothesis, we analyzed the following data sets: 2351 high-resolution crystal structures, and the native and denatured states of 188 different proteins from all-atom, explicit-solvent molecular dynamics (MD) simulations, which are part of our Dynameomics effort. We found that water bridges do not explain the high frequency of P(II) in denatured states; such bridges are less frequent around P(II) than around other conformations. Thus, this analysis casts doubt on water bridges as a dominant factor determining the residue-based P(II) propensities.

Protein L-isoaspartate O-methyltransferase (PIMT) repairs isoaspartate residues in damaged proteins, and it contains a Val-Ile polymorphismin in alpha5, approximately 13 A from its active site. Val119 has lower activity and thermal stability but increased affinity for endogenous substrates. Studies suggest that heterozygosity for Val/Ile favors efficient isoaspartate repair. We have performed multiple molecular dynamics simulations of 119I and 119V PIMT. Both V119 and I119 interact with the same residues throughout all of the simulations. However, the larger Ile altered the orientations of alpha5 and beta5, both of which have co-substrate binding residues on their distal ends. I119 increases the flexibility of several residues, loosening up the S-adenosylmethionine (SAM)-binding site. These subtle changes are propagated towards the isoaspartate-docking site via residues common to both active sites. The increased mobility in 119I PIMT reorients alpha3, resulting in a salt-bridge network at the substrate-binding interface that disrupts several key side-chain interactions in the isoaspartate site. In contrast, 119V PIMT remains quite rigid with little change to the co-substrate binding site, which could hinder SAM's binding and release, accounting for the decreased activity. These results shed light on the molecular basis behind the decreased activity and increased specificity for endogenous substrates of 119V PIMT relative to the 119I variant. 119I PIMT catalyzes the methylation reaction but may have difficulties recognizing and orienting specific substrates due to its distorted substrate-binding site. Heterozygosity for both the Ile and Val alleles may provide the best of both worlds, allowing the fast and specific methylation of damaged proteins.

Prion diseases, in which the conformational transition of the native prion protein (PrP) to a misfolded form causes aggregation and subsequent neurodegeneration, have fascinated the scientific community as this transmissible disease appears to be purely protein-based. Disease can arise due to genetic factors only. At least 30 single point mutations have been indicated to cause disease in humans. Somehow, these mutations must influence the stability, processing and/or cellular interactions of PrP, such that aggregation can occur and disease develops. In this review, the current evidence for such effects of single point mutations is discussed, indicating that PrP can be affected in many different ways, although questions remain about the mechanism by which mutations cause disease.

The goal of Dynameomics is to perform atomistic molecular dynamics (MD) simulations of representative proteins from all known folds in explicit water in their native state and along their thermal unfolding pathways. Here we present 188-fold representatives and their native state simulations and analyses. These 188 targets represent 67% of all the structures in the Protein Data Bank. The behavior of several specific targets is highlighted to illustrate general properties in the full dataset and to demonstrate the role of MD in understanding protein function and stability. As an example of what can be learned from mining the Dynameomics database, we identified a protein fold with heightened localized dynamics. In one member of this fold family, the motion affects the exposure of its phosphorylation site and acts as an entropy sink to offset another portion of the protein that is relatively immobile in order to present a consistent interface for protein docking. In another member of this family, a polymorphism in the highly mobile region leads to a host of disease phenotypes. We have constructed a web site to provide access to a novel hybrid relational/multidimensional database (described in the succeeding two papers) to view and interrogate simulations of the top 30 targets: http://www.dynameomics.org. The Dynameomics database, currently the largest collection of protein simulations and protein structures in the world, should also be useful for determining the rules governing protein folding and kinetic stability, which should aid in deciphering genomic information and for protein engineering and design.

Dynameomics is a project to investigate and catalog the native-state dynamics and thermal unfolding pathways of representatives of all protein folds using solvated molecular dynamics simulations, as described in the preceding paper. Here we introduce the design of the molecular dynamics data warehouse, a scalable, reliable repository that houses simulation data that vastly simplifies management and access. In the succeeding paper, we describe the development of a complementary multidimensional database. A single protein unfolding or native-state simulation can take weeks to months to complete, and produces gigabytes of coordinate and analysis data. Mining information from over 3000 completed simulations is complicated and time-consuming. Even the simplest queries involve writing intricate programs that must be built from low-level file system access primitives and include significant logic to correctly locate and parse data of interest. As a result, programs to answer questions that require data from hundreds of simulations are very difficult to write. Thus, organization and access to simulation data have been major obstacles to the discovery of new knowledge in the Dynameomics project. This repository is used internally and is the foundation of the Dynameomics portal site http://www.dynameomics.org. By organizing simulation data into a scalable, manageable and accessible form, we can begin to address substantial questions that move us closer to solving biomedical and bioengineering problems.

The Dynameomics project is our effort to characterize the native-state dynamics and folding/unfolding pathways of representatives of all known protein folds by way of molecular dynamics simulations, as described by Beck et al. (in Protein Eng. Des. Select., the first paper in this series). The data produced by these simulations are highly multidimensional in structure and multi-terabytes in size. Both of these features present significant challenges for storage, retrieval and analysis. For optimal data modeling and flexibility, we needed a platform that supported both multidimensional indices and hierarchical relationships between related types of data and that could be integrated within our data warehouse, as described in the accompanying paper directly preceding this one. For these reasons, we have chosen On-line Analytical Processing (OLAP), a multi-dimensional analysis optimized database, as an analytical platform for these data. OLAP is a mature technology in the financial sector, but it has not been used extensively for scientific analysis. Our project is further more unusual for its focus on the multidimensional and analytical capabilities of OLAP rather than its aggregation capacities. The dimensional data model and hierarchies are very flexible. The query language is concise for complex analysis and rapid data retrieval. OLAP shows great promise for the dynamic protein analysis for bioengineering and biomedical applications. In addition, OLAP may have similar potential for other scientific and engineering applications involving large and complex datasets.

Transthyretin (TTR)-containing amyloid fibrils are deposited in cardiac tissue as a natural consequence of aging. A large number of inherited mutations lead to amyloid diseases by accelerating TTR deposition in other organs. Amyloid formation is preceded by a disruption of the quaternary structure of TTR and conformational changes in the monomer. To study conformational changes preceding the formation of amyloid, we performed molecular dynamics simulations of the wild-type monomer, amyloidogenic variants (V30M, L55P, V122I) and a protective variant (T119M) at neutral and low pH. At low pH, the D strand dissociated from the beta-sheet to expose the A strand, consistent with experimental studies. In amyloidogenic variants and in the wild-type at low pH, there was a conformational change in the beta-sheets into alpha-sheet via peptide bond flips that was not observed at neutral pH in the wild-type monomer. The same residues participated in conversion in each amyloidogenic variant simulation, originating in the G strand between residues 106 and 109, with accelerated conversion at low pH. The T119M protective variant changed the local conformation of the H strand and suppressed the conversion observed in amyloidogenic variants.