Are kuravirus capsid diameters quantized? The first all-atom genome tracing method for double-stranded DNA viruses.

The revolution in cryo-electron microscopy has resulted in unprecedented power to resolve large macromolecular complexes including viruses. Many methods exist to explain density corresponding to proteins and thus entire protein capsids have been solved at the all-atom level. However methods for nucleic acids lag behind, and no all-atom viral double-stranded DNA genomes have been published at all. We here present a method which exploits the spiral winding patterns of DNA in icosahedral capsids. The method quickly generates shells of DNA wound in user-specified, idealized spherical or cylindrical spirals. For transition regions, the method allows guided semiflexible fitting. For the kuravirus SU10, our method explains most of the density in a semiautomated fashion. The results suggest rules for DNA turns in the end caps under which two discrete parameters determine the capsid inner diameter. We suggest that other kuraviruses viruses may follow the same winding scheme, producing a discrete rather than continuous spectrum of capsid inner diameters. Our software may be used to explain the published density maps of other double-stranded DNA viruses and uncover their genome packaging principles.

Amino acid substitutions in human growth hormone affect secondary structure and receptor binding.

The interaction between human Growth Hormone (hGH) and hGH Receptor (hGHR) has basic relevance to cancer and growth disorders, and hGH is the scaffold for Pegvisomant, an anti-acromegaly therapeutic. For the latter reason, hGH has been extensively engineered by early workers to improve binding and other properties. We are particularly interested in E174 which belongs to the hGH zinc-binding triad; the substitution E174A is known to significantly increase binding, but to now no explanation has been offered. We generated this and several computationally-selected single-residue substitutions at the hGHR-binding site of hGH. We find that, while many successfully slow down dissociation of the hGH-hGHR complex once bound, they also slow down the association of hGH to hGHR. The E174A substitution induces a change in the Circular Dichroism spectrum that suggests the appearance of coiled-coiling. Here we show that E174A increases affinity of hGH against hGHR because the off-rate is slowed down more than the on-rate. For E174Y (and certain mutations at other sites) the slowdown in on-rate was greater than that of the off-rate, leading to decreased affinity. The results point to a link between structure, zinc binding, and hGHR-binding affinity in hGH.

Mining the Protein Data Bank to improve prediction of changes in protein-protein binding.

Predicting the effect of mutations on protein-protein interactions is important for relating structure to function, as well as for in silico affinity maturation. The effect of mutations on protein-protein binding energy (ΔΔG) can be predicted by a variety of atomic simulation methods involving full or limited flexibility, and explicit or implicit solvent. Methods which consider only limited flexibility are naturally more economical, and many of them are quite accurate, however results are dependent on the atomic coordinate set used. In this work we perform a sequence and structure based search of the Protein Data Bank to find additional coordinate sets and repeat the calculation on each. The method increases precision and Positive Predictive Value, and decreases Root Mean Square Error, compared to using single structures. Given the ongoing growth of near-redundant structures in the Protein Data Bank, our method will only increase in applicability and accuracy.

Molecular Dynamics Simulations Suggest a Non-Doublet Decoding Model of -1 Frameshifting by tRNASer3.

In-frame decoding in the ribosome occurs through canonical or wobble Watson-Crick pairing of three mRNA codon bases (a triplet) with a triplet of anticodon bases in tRNA. Departures from the triplet-triplet interaction can result in frameshifting, meaning downstream mRNA codons are then read in a different register. There are many mechanisms to induce frameshifting, and most are insufficiently understood. One previously proposed mechanism is doublet decoding, in which only codon bases 1 and 2 are read by anticodon bases 34 and 35, which would lead to -1 frameshifting. In E. coli, tRNASer3GCU can induce -1 frameshifting at alanine (GCA) codons. The logic of the doublet decoding model is that the Ala codon's GC could pair with the tRNASer3's GC, leaving the third anticodon residue U36 making no interactions with mRNA. Under that model, a U36C mutation would still induce -1 frameshifting, but experiments refute this. We perform all-atom simulations of wild-type tRNASer3, as well as a U36C mutant. Our simulations revealed a hydrogen bond between U36 of the anticodon and G1 of the codon. The U36C mutant cannot make this interaction, as it lacks the hydrogen-bond-donating H3. The simulation thus suggests a novel, non-doublet decoding mechanism for -1 frameshifting by tRNASer3 at Ala codons.

Insights from engineering the Affibody-Fc interaction with a computational-experimental method.

The interaction between the Staphylococcal Protein A (SpA) domain B (the basis of the Affibody) molecule and the Fc of IgG is key to the use of Affibodies in affinity chromatography and in potential therapies against certain inflammatory diseases. Despite its importance and four-decade history, to our knowledge this interaction has never been affinity matured. We elucidate reasons why single-substitutions in the SpA which improve affinity to Fc may be very rare, and also discover substitutions which potentially serve several engineering purposes. We used a variation of FoldX to predict changes in protein-protein-binding affinity, and produce a list of 41 single-amino acid substitutions on the SpA molecule, of which four are near wild type (wt) and five are at most a factor of four from wt affinity. The nine substitutions include one which removes lysine, and several others which change charge. Subtle modulations in affinity may be useful for modifying column elution conditions. The method is applicable to other protein-protein systems, providing molecular insights with lower workload than existing experimental techniques.

Modeling and fitting protein-protein complexes to predict change of binding energy.

It is possible to accurately and economically predict change in protein-protein interaction energy upon mutation (ΔΔG), when a high-resolution structure of the complex is available. This is of growing usefulness for design of high-affinity or otherwise modified binding proteins for therapeutic, diagnostic, industrial, and basic science applications. Recently the field has begun to pursue ΔΔG prediction for homology modeled complexes, but so far this has worked mostly for cases of high sequence identity. If the interacting proteins have been crystallized in free (uncomplexed) form, in a majority of cases it is possible to find a structurally similar complex which can be used as the basis for template-based modeling. We describe how to use MMB to create such models, and then use them to predict ΔΔG, using a dataset consisting of free target structures, co-crystallized template complexes with sequence identify with respect to the targets as low as 44%, and experimental ΔΔG measurements. We obtain similar results by fitting to a low-resolution Cryo-EM density map. Results suggest that other structural constraints may lead to a similar outcome, making the method even more broadly applicable.

MMB-GUI: a fast morphing method demonstrates a possible ribosomal tRNA translocation trajectory.

Easy-to-use macromolecular viewers, such as UCSF Chimera, are a standard tool in structural biology. They allow rendering and performing geometric operations on large complexes, such as viruses and ribosomes. Dynamical simulation codes enable modeling of conformational changes, but may require considerable time and many CPUs. There is an unmet demand from structural and molecular biologists for software in the middle ground, which would allow visualization combined with quick and interactive modeling of conformational changes, even of large complexes. This motivates MMB-GUI. MMB uses an internal-coordinate, multiscale approach, yielding as much as a 2000-fold speedup over conventional simulation methods. We use Chimera as an interactive graphical interface to control MMB. We show how this can be used for morphing of macromolecules that can be heterogeneous in biopolymer type, sequence, and chain count, accurately recapitulating structural intermediates. We use MMB-GUI to create a possible trajectory of EF-G mediated gate-passing translocation in the ribosome, with all-atom structures. This shows that the GUI makes modeling of large macromolecules accessible to a wide audience. The morph highlights similarities in tRNA conformational changes as tRNA translocates from A to P and from P to E sites and suggests that tRNA flexibility is critical for translocation completion.

A multiscale approach to predicting affinity changes in protein-protein interfaces.

Substitution mutations in protein-protein interfaces can have a substantial effect on binding, which has consequences in basic and applied biomedical research. Experimental expression, purification, and affinity determination of protein complexes is an expensive and time-consuming means of evaluating the effect of mutations, making a fast and accurate in silico method highly desirable. When the structure of the wild-type complex is known, it is possible to economically evaluate the effect of point mutations with knowledge based potentials, which do not model backbone flexibility, but these have been validated only for single mutants. Substitution mutations tend to induce local conformational rearrangements only. Accordingly, ZEMu (Zone Equilibration of Mutants) flexibilizes only a small region around the site of mutation, then computes its dynamics under a physics-based force field. We validate with 1254 experimental mutants (with 1-15 simultaneous substitutions) in a wide variety of different protein environments (65 protein complexes), and obtain a significant improvement in the accuracy of predicted ΔΔG.

Fast fitting to low resolution density maps: elucidating large-scale motions of the ribosome.

Determining the conformational rearrangements of large macromolecules is challenging experimentally and computationally. Case in point is the ribosome; it has been observed by high-resolution crystallography in several states, but many others are known only from low-resolution methods including cryo-electron microscopy. Combining these data into dynamical trajectories that may aid understanding of its largest-scale conformational changes has so far remained out of reach of computational methods. Most existing methods either model all atoms explicitly, resulting in often prohibitive cost, or use approximations that lose interesting structural and dynamical detail. In this work, I introduce Internal Coordinate Flexible Fitting, which uses full atomic forces and flexibility in limited regions of a model, capturing extensive conformational rearrangements at low cost. I use it to turn multiple low-resolution density maps, crystallographic structures and biochemical information into unified all-atoms trajectories of ribosomal translocation. Internal Coordinate Flexible Fitting is three orders of magnitude faster than the most comparable existing method.

Insights into diseases of human telomerase from dynamical modeling.

Mutations in the telomerase complex disrupt either nucleic acid binding or catalysis, and are the cause of numerous human diseases. Despite its importance, the structure of the human telomerase complex has not been observed crystallographically, nor are its dynamics understood in detail. Fragments of this complex from Tetrahymena thermophila and Tribolium castaneum have been crystallized. Biochemical probes provide important insight into dynamics. In this work we summarize evidence that the T. castaneum structure is Telomerase Reverse Transcriptase. We use this structure to build a partial model of the human Telomerase complex. The model suggests an explanation for the structural role of several disease-associated mutations. We then generate a 3D kinematic trajectory of telomere elongation to illustrate a "typewriter" mechanism: the RNA template moves to keep the end of the growing telomeric primer in the active site, disengaging after every 6-residue extension to execute a "carriage return" and go back to its starting position. A hairpin can easily form in the primer, from DNA residues leaving the primer-template duplex. The trajectory is consistent with available experimental evidence. The methodology is extensible to many problems in structural biology in general and personalized medicine in particular.

RNA-Puzzles: a CASP-like evaluation of RNA three-dimensional structure prediction.

We report the results of a first, collective, blind experiment in RNA three-dimensional (3D) structure prediction, encompassing three prediction puzzles. The goals are to assess the leading edge of RNA structure prediction techniques; compare existing methods and tools; and evaluate their relative strengths, weaknesses, and limitations in terms of sequence length and structural complexity. The results should give potential users insight into the suitability of available methods for different applications and facilitate efforts in the RNA structure prediction community in ongoing efforts to improve prediction tools. We also report the creation of an automated evaluation pipeline to facilitate the analysis of future RNA structure prediction exercises.

Fast flexible modeling of RNA structure using internal coordinates.

Modeling the structure and dynamics of large macromolecules remains a critical challenge. Molecular dynamics (MD) simulations are expensive because they model every atom independently, and are difficult to combine with experimentally derived knowledge. Assembly of molecules using fragments from libraries relies on the database of known structures and thus may not work for novel motifs. Coarse-grained modeling methods have yielded good results on large molecules but can suffer from difficulties in creating more detailed full atomic realizations. There is therefore a need for molecular modeling algorithms that remain chemically accurate and economical for large molecules, do not rely on fragment libraries, and can incorporate experimental information. RNABuilder works in the internal coordinate space of dihedral angles and thus has time requirements proportional to the number of moving parts rather than the number of atoms. It provides accurate physics-based response to applied forces, but also allows user-specified forces for incorporating experimental information. A particular strength of RNABuilder is that all Leontis-Westhof basepairs can be specified as primitives by the user to be satisfied during model construction. We apply RNABuilder to predict the structure of an RNA molecule with 160 bases from its secondary structure, as well as experimental information. Our model matches the known structure to 10.2 Angstroms RMSD and has low computational expense.

Structural insights into pre-translocation ribosome motions.

Subsequent to the peptidyl transfer step of the translation elongation cycle, the initially formed pre-translocation ribosome, which we refer to here as R(1), undergoes a ratchet-like intersubunit rotation in order to sample a rotated conformation, referred to here as R(F), that is an obligatory intermediate in the translocation of tRNAs and mRNA through the ribosome during the translocation step of the translation elongation cycle. R(F) and the R(1) to R(F) transition are currently the subject of intense research, driven in part by the potential for developing novel antibiotics which trap R(F) or confound the R(1) to R(F) transition. Currently lacking a 3D atomic structure of the R(F) endpoint of the transition, as well as a preliminary conformational trajectory connecting R(1) and R(F), the dynamics of the mechanistically crucial R(1) to R(F) transition remain elusive. The current literature reports fitting of only a few ribosomal RNA (rRNA) and ribosomal protein (r-protein) components into cryogenic electron microscopy (cryo-EM) reconstructions of the Escherichia coli ribosome in RF. In this work we now fit the entire Thermus thermophilus 16S and 23S rRNAs and most of the remaining T. thermophilus r-proteins into a cryo-EM reconstruction of the E. coli ribosome in R(F) in order to build an almost complete model of the T. thermophilus ribosome in R(F) thus allowing a more detailed view of this crucial conformation. The resulting model validates key predictions from the published literature; in particular it recovers intersubunit bridges known to be maintained throughout the R(1) to R(F) transition and results in new intersubunit bridges that are predicted to exist only in R(F). In addition, we use a recently reported E. coli ribosome structure, apparently trapped in an intermediate state along the R(1) to R(F) transition pathway, referred to here as R(2), as a guide to generate a T. thermophilus ribosome in the R(2) state. This demonstrates a multiresolution method for morphing large complexes and provides us with a structural model of R(2) in the species of interest. The generated structural models form the basis for probing the motion of the deacylated tRNA bound at the peptidyl-tRNA binding site (P site) of the pre-translocation ribosome as it moves from its so-called classical P/P configuration to its so-called hybrid P/E configuration as part of the R(1) to R(F) transition. We create a dynamic model of this process which provides structural insights into the functional significance of R(2) as well as detailed atomic information to guide the design of further experiments. The results suggest extensibility to other steps of protein synthesis as well as to spatially larger systems.

Turning limited experimental information into 3D models of RNA.

Our understanding of RNA functions in the cell is evolving rapidly. As for proteins, the detailed three-dimensional (3D) structure of RNA is often key to understanding its function. Although crystallography and nuclear magnetic resonance (NMR) can determine the atomic coordinates of some RNA structures, many 3D structures present technical challenges that make these methods difficult to apply. The great flexibility of RNA, its charged backbone, dearth of specific surface features, and propensity for kinetic traps all conspire with its long folding time, to challenge in silico methods for physics-based folding. On the other hand, base-pairing interactions (either in runs to form helices or isolated tertiary contacts) and motifs are often available from relatively low-cost experiments or informatics analyses. We present RNABuilder, a novel code that uses internal coordinate mechanics to satisfy user-specified base pairing and steric forces under chemical constraints. The code recapitulates the topology and characteristic L-shape of tRNA and obtains an accurate noncrystallographic structure of the Tetrahymena ribozyme P4/P6 domain. The algorithm scales nearly linearly with molecule size, opening the door to the modeling of significantly larger structures.