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Complex and coordinated dynamics are closely connected with protein functions, including the binding of antibodies to antigens. Knowledge of such dynamics could improve the design of antibodies. Molecular dynamics (MD) simulations provide a "computational microscope" that can resolve atomic motions and inform antibody design efforts., (© 2023. Springer Science+Business Media, LLC, part of Springer Nature.)

The p53 protein is a commonly studied cancer target because of its role in tumor suppression. Unfortunately, it is susceptible to mutation-associated loss of function; approximately 50% of cancers are associated with mutations to p53, the majority of which are located in the central DNA-binding domain. Here, we report molecular dynamics simulations of wild-type (WT) p53 and 20 different mutants, including a stabilized pseudo-WT mutant. Our findings indicate that p53 mutants tend to exacerbate latent structural-disruption tendencies, or vulnerabilities, already present in the WT protein, suggesting that it may be possible to develop cancer therapies by targeting a relatively small set of structural-disruption motifs rather than a multitude of effects specific to each mutant. In addition, α-sheet secondary structure formed in almost all of the proteins. α-Sheet has been hypothesized and recently demonstrated to play a role in amyloidogenesis, and its presence in the reported p53 simulations coincides with the recent re-consideration of cancer as an amyloid disease., (© 2020 The Protein Society.)

Far from the static, idealized conformations deposited into structural databases, proteins are highly dynamic molecules that undergo conformational changes on temporal and spatial scales that may span several orders of magnitude. These conformational changes, often intimately connected to the functional roles that proteins play, may be obscured by traditional biophysical techniques. Over the past 40 years, molecular dynamics (MD) simulations have complemented these techniques by providing the "hidden" atomistic details that underlie protein dynamics. However, there are limitations of the degree to which molecular simulations accurately and quantitatively describe protein motions. Here we show that although four molecular dynamics simulation packages (AMBER, GROMACS, NAMD, and ilmm) reproduced a variety of experimental observables for two different proteins (engrailed homeodomain and RNase H) equally well overall at room temperature, there were subtle differences in the underlying conformational distributions and the extent of conformational sampling obtained. This leads to ambiguity about which results are correct, as experiment cannot always provide the necessary detailed information to distinguish between the underlying conformational ensembles. However, the results with different packages diverged more when considering larger amplitude motion, for example, the thermal unfolding process and conformational states sampled, with some packages failing to allow the protein to unfold at high temperature or providing results at odds with experiment. While most differences between MD simulations performed with different packages are attributed to the force fields themselves, there are many other factors that influence the outcome, including the water model, algorithms that constrain motion, how atomic interactions are handled, and the simulation ensemble employed. Here four different MD packages were tested each using best practices as established by the developers, utilizing three different protein force fields and three different water models. Differences between the simulated protein behavior using two different packages but the same force field, as well as two different packages with different force fields but the same water models and approaches to restraining motion, show how other factors can influence the behavior, and it is incorrect to place all the blame for deviations and errors on force fields or to expect improvements in force fields alone to solve such problems.

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.

Myosin activation is a viable approach to treat systolic heart failure. We previously demonstrated that striated muscle myosin is a promiscuous ATPase that can use most nucleoside triphosphates as energy substrates for contraction. When 2-deoxy ATP (dATP) is used, it acts as a myosin activator, enhancing cross-bridge binding and cycling. In vivo, we have demonstrated that elevated dATP levels increase basal cardiac function and rescues function of infarcted rodent and pig hearts. Here we investigate the molecular mechanism underlying this physiological effect. We show with molecular dynamics simulations that the binding of dADP.Pi (dATP hydrolysis products) to myosin alters the structure and dynamics of the nucleotide binding pocket, myosin cleft conformation, and actin binding sites, which collectively yield a myosin conformation that we predict favors weak, electrostatic binding to actin. In vitro motility assays at high ionic strength were conducted to test this prediction and we found that dATP increased motility. These results highlight alterations to myosin that enhance cross-bridge formation and reveal a potential mechanism that may underlie dATP-induced improvements in cardiac function., (© 2017 The Protein Society.)

Various host-guest peptide series are used by experimentalists as reference conformational states. One such use is as a baseline for random-coil NMR chemical shifts. Comparison to this random-coil baseline, through secondary chemical shifts, is used to infer protein secondary structure. The use of these random-coil data sets rests on the perception that the reference chemical shifts arise from states where there is little or no conformational bias. However, there is growing evidence that the conformational composition of natively and nonnatively unfolded proteins fail to approach anything that can be construed as random coil. Here, we use molecular dynamics simulations of an alanine-based host-guest peptide series (AAXAA) as a model of unfolded and denatured states to examine the intrinsic propensities of the amino acids. We produced ensembles that are in good agreement with the experimental NMR chemical shifts and confirm that the sampling of the 20 natural amino acids in this peptide series is be far from random. Preferences toward certain regions of conformational space were both present and dependent upon the environment when compared under conditions typically used to denature proteins, i.e., thermal and chemical denaturation. Moreover, the simulations allowed us to examine the conformational makeup of the underlying ensembles giving rise to the ensemble-averaged chemical shifts. We present these data as an intrinsic backbone propensity library that forms part of our Structural Library of Intrinsic Residue Propensities to inform model building, to aid in interpretation of experiment, and for structure prediction of natively and nonnatively unfolded states., (Copyright © 2016 Biophysical Society. Published by Elsevier Inc. All rights reserved.)

Most rotamer libraries are generated from subsets of the PDB and do not fully represent the conformational scope of protein side chains. Previous attempts to rectify this sparse coverage of conformational space have involved application of weighting and smoothing functions. We resolve these limitations by using physics-based molecular dynamics simulations to determine more accurate frequencies of rotameric states. This work forms part of our Dynameomics initiative and uses a set of 807 proteins selected to represent 97% of known autonomous protein folds, thereby eliminating the bias toward common topologies found within the PDB. Our Dynameomics derived rotamer libraries encompass 4.8 × 10(9) rotamers, sampled from at least 51,000 occurrences of each of 93,642 residues. Here, we provide a backbone-dependent rotamer library, based on secondary structure ϕ/ψ regions, and an update to our 2011 backbone-independent library that addresses the doubling of our dataset since its original publication., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

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., (© 2014 The Protein Society.)

Integrative structural biology attempts to model the structures of protein complexes that are challenging or intractable by classical structural methods (due to size, dynamics, or heterogeneity) by combining computational structural modeling with data from experimental methods. One such experimental method is chemical crosslinking mass spectrometry (XL-MS), in which protein complexes are crosslinked and characterized using liquid chromatography-mass spectrometry to pinpoint specific amino acid residues in close structural proximity. The commonly used lysine-reactive N-hydroxysuccinimide ester reagents disuccinimidylsuberate (DSS) and bis(sulfosuccinimidyl)suberate (BS(3) ) have a linker arm that is 11.4 Å long when fully extended, allowing Cα (alpha carbon of protein backbone) atoms of crosslinked lysine residues to be up to ∼24 Å apart. However, XL-MS studies on proteins of known structure frequently report crosslinks that exceed this distance. Typically, a tolerance of ∼3 Å is added to the theoretical maximum to account for this observation, with limited justification for the chosen value. We used the Dynameomics database, a repository of high-quality molecular dynamics simulations of 807 proteins representative of diverse protein folds, to investigate the relationship between lysine-lysine distances in experimental starting structures and in simulation ensembles. We conclude that for DSS/BS(3), a distance constraint of 26-30 Å between Cα atoms is appropriate. This analysis provides a theoretical basis for the widespread practice of adding a tolerance to the crosslinker length when comparing XL-MS results to structures or in modeling. We also discuss the comparison of XL-MS results to MD simulations and known structures as a means to test and validate experimental XL-MS methods., (© 2014 The Protein Society.)

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., (Copyright © 2013. Published by Elsevier Inc.)

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.

Background: Molecular dynamics (MD) simulations offer the ability to observe the dynamics and interactions of both whole macromolecules and individual atoms as a function of time. Taken in context with experimental data, atomic interactions from simulation provide insight into the mechanics of protein folding, dynamics, and function. The calculation of atomic interactions or contacts from an MD trajectory is computationally demanding and the work required grows exponentially with the size of the simulation system. We describe the implementation of a spatial indexing algorithm in our multi-terabyte MD simulation database that significantly reduces the run-time required for discovery of contacts. The approach is applied to the Dynameomics project data. Spatial indexing, also known as spatial hashing, is a method that divides the simulation space into regular sized bins and attributes an index to each bin. Since, the calculation of contacts is widely employed in the simulation field, we also use this as the basis for testing compression of data tables. We investigate the effects of compression of the trajectory coordinate tables with different options of data and index compression within MS SQL SERVER 2008., Results: Our implementation of spatial indexing speeds up the calculation of contacts over a 1 nanosecond (ns) simulation window by between 14% and 90% (i.e., 1.2 and 10.3 times faster). For a 'full' simulation trajectory (51 ns) spatial indexing reduces the calculation run-time between 31 and 81% (between 1.4 and 5.3 times faster). Compression resulted in reduced table sizes but resulted in no significant difference in the total execution time for neighbour discovery. The greatest compression (~36%) was achieved using page level compression on both the data and indexes., Conclusions: The spatial indexing scheme significantly decreases the time taken to calculate atomic contacts and could be applied to other multidimensional neighbor discovery problems. The speed up enables on-the-fly calculation and visualization of contacts and rapid cross simulation analysis for knowledge discovery. Using page compression for the atomic coordinate tables and indexes saves ~36% of disk space without any significant decrease in calculation time and should be considered for other non-transactional databases in MS SQL SERVER 2008.

We have recently completed systematic molecular dynamics simulations of 807 different proteins representing 95% of the known autonomous protein folds in an effort we refer to as Dynameomics. Here we focus on the analysis of side chain conformations and dynamics to create a dynamic rotamer library. Overall this library is derived from 31,000 occurrences of each of 86,217 different residues, or 2.7 × 10(9) rotamers. This dynamic library has 74% overlap of rotamer distributions with rotamer libraries derived from static high-resolution crystal structures. Seventy-five percent of the residues had an assignable primary conformation, and 68% of the residues had at least one significant alternate conformation. The average correlation time for switching between rotamers ranged from 22 ps for Met to over 8 ns for Cys; this time decreased 20-fold on the surface of the protein and modestly for dihedral angles further from the main chain. Side chain S(2) axis order parameters were calculated and they correlated well with those derived from NMR relaxation experiments (R = 0.9). Relationships relating the S(2) axis order parameters to rotamer occupancy were derived. Overall the Dynameomics rotamer library offers a comprehensive depiction of side chain rotamer preferences and dynamics in solution, and more realistic distributions for dynamic proteins in solution at ambient temperature than libraries derived from crystal structures, in particular charged surface residues are better represented. Details of the rotamer library are presented here and the library itself can be downloaded at http://www.dynameomics.org., (Copyright © 2010 The Protein Society.)

Computer simulation of protein dynamics offers unique high-resolution information that complements experiment. Using experimentally derived structures of the natively folded prion protein (PrP), physically realistic dynamics and conformational changes can be simulated, including the initial steps of misfolding. By introducing mutations in silico, the effect of pathogenic mutations on PrP conformation and dynamics can be assessed. Here, we briefly introduce molecular dynamics methods and review the application of molecular dynamics simulations to obtain insight into various aspects of the PrP, including the mechanism of misfolding, the response to changes in the environment, and the influence of disease-related mutations.

The ultrafast folding pathway of the engrailed homeodomain has been exceptionally well characterized by experiment and simulation. Helices II and III of the three-helix bundle protein form the native helix-turn-helix motif as an on-pathway intermediate within a few microseconds. The slow step is then the proper docking of the helices in approximately 15 mus. However, there is still the unexplained puzzle of why helix docking is relatively slow, which is part of the more general question as to why rearrangements of intermediates occur slowly. To address this problem, we performed 46 all-atom molecular dynamics refolding simulations in explicit water, for a total of 15 micros of simulation time. The simulations started from an intermediate state structure that was generated in an unfolding simulation at 498 K and was then quenched to folding-permissive temperatures. The protein refolded successfully in only one of the 46 simulations, and in that case the refolding pathway mirrored the unfolding pathway at high temperature. In the 45 simulations in which the protein did not fully fold, nonnative salt bridges trapped the protein, which explains why the protein folds relatively slowly from the intermediate state., (Copyright 2010 Biophysical Society. Published by Elsevier Inc. All rights reserved.)

The goal of the Dynameomics project is to perform, store, and analyze molecular dynamics simulations of representative proteins, of all known globular folds, in their native state and along their unfolding pathways. To analyze unfolding simulations, the location of the protein along the unfolding reaction coordinate (RXN) must be determined. Properties such as the fraction of native contacts and radius of gyration are often used; however, there is an issue regarding degeneracy with these properties, as native and nonnative species can overlap. Here, we used 15 physical properties of the protein to construct a multidimensional-embedded, one-dimensional RXN coordinate that faithfully captures the complex nature of unfolding. The unfolding RXN coordinates for 188 proteins (1534 simulations and 22.9 mus in explicit water) were calculated. Native, transition, intermediate, and denatured states were readily identified with the use of this RXN coordinate. A global native ensemble based on the native-state properties of the 188 proteins was created. This ensemble was shown to be effective for calculating RXN coordinates for folds outside the initial 188 targets. These RXN coordinates enable, high-throughput assignment of conformational states, which represents an important step in comparing protein properties across fold space as well as characterizing the unfolding of individual proteins., (Copyright (c) 2010 Biophysical Society. Published by Elsevier Inc. All rights reserved.)

The Dynameomics project aims to simulate a representative sample of all globular protein metafolds under both native and unfolding conditions. We have identified protein unfolding transition state (TS) ensembles from multiple molecular dynamics simulations of high-temperature unfolding in 183 structurally distinct proteins. These data can be used to study individual proteins and individual protein metafolds and to mine for TS structural features common across all proteins. Separating the TS structures into four different fold classes (all proteins, all-alpha, all-beta, and mixed alpha/beta and alpha +beta) resulted in no significant difference in the overall protein properties. The residues with the most contacts in the native state lost the most contacts in the TS ensemble. On average, residues beginning in an alpha-helix maintained more structure in the TS ensemble than did residues starting in beta-strands or any other conformation. The metafolds studied here represent 67% of all known protein structures, and this is, to our knowledge, the largest, most comprehensive study of the protein folding/unfolding TS ensemble to date. One might have expected broad distributions in the average global properties of the TS relative to the native state, indicating variability in the amount of structure present in the TS. Instead, the average global properties converged with low standard deviations across metafolds, suggesting that there are general rules governing the structure and properties of the TS.

Key points: Skeletal muscle relaxation has been primarily studied by assessing the kinetics of force decay. Little is known about the resultant dynamics of structural changes in myosin heads during relaxation.The naturally occurring nucleotide 2‐deoxy‐ATP (dATP) is a myosin activator that enhances cross‐bridge binding and kinetics.X‐ray diffraction data indicate that with elevated dATP, myosin heads were extended closer to actin in relaxed muscle and myosin heads return to an ordered, resting state after contraction more quickly.Molecular dynamics simulations of post‐powerstroke myosin suggest that dATP induces structural changes in myosin heads that increase the surface area of the actin‐binding regions promoting myosin interaction with actin, which could explain the observed delays in the onset of relaxation.This study of the dATP‐induced changes in myosin may be instructive for determining the structural changes desired for other potential myosin‐targeted molecular compounds to treat muscle diseases. Here we used time‐resolved small‐angle X‐ray diffraction coupled with force measurements to study the structural changes in FVB mouse skeletal muscle sarcomeres during relaxation after tetanus contraction. To estimate the rate of myosin deactivation, we followed the rate of the intensity recovery of the first‐order myosin layer line (MLL1) and restoration of the resting spacing of the third and sixth order of meridional reflection (SM3 and SM6) following tetanic contraction. A transgenic mouse model with elevated skeletal muscle 2‐deoxy‐ATP (dATP) was used to study how myosin activators may affect soleus muscle relaxation. X‐ray diffraction evidence indicates that with elevated dATP, myosin heads were extended closer to actin in resting muscle. Following contraction, there is a slight but significant delay in the decay of force relative to WT muscle while the return of myosin heads to an ordered resting state was initially slower, then became more rapid than in WT muscle. Molecular dynamics simulations of post‐powerstroke myosin suggest that dATP induces structural changes in myosin that increase the surface area of the actin‐binding regions, promoting myosin interaction with actin. With dATP, myosin heads may remain in an activated state near the thin filaments following relaxation, accounting for the delay in force decay and the initial delay in recovery of resting head configuration, and this could facilitate subsequent contractions. Key points: Skeletal muscle relaxation has been primarily studied by assessing the kinetics of force decay. Little is known about the resultant dynamics of structural changes in myosin heads during relaxation.The naturally occurring nucleotide 2‐deoxy‐ATP (dATP) is a myosin activator that enhances cross‐bridge binding and kinetics.X‐ray diffraction data indicate that with elevated dATP, myosin heads were extended closer to actin in relaxed muscle and myosin heads return to an ordered, resting state after contraction more quickly.Molecular dynamics simulations of post‐powerstroke myosin suggest that dATP induces structural changes in myosin heads that increase the surface area of the actin‐binding regions promoting myosin interaction with actin, which could explain the observed delays in the onset of relaxation.This study of the dATP‐induced changes in myosin may be instructive for determining the structural changes desired for other potential myosin‐targeted molecular compounds to treat muscle diseases. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

To investigate whether swapping native turns of a globular protein with an elastin-based turn sequence (VPGVG) can increase its thermostability, we have performed molecular dynamics simulations of wild-type chymotrypsin inhibitor 2 (CI2) and variants containing elastin-based turns at 10°C and 40°C. Wild-type CI2 is more stable at 10°C, while both of the variant forms are more stable at 40°C. Detailed analyses indicate that the elastin-based turns do indeed contribute to the inverse temperature behavior of the modified proteins. Therefore, swapping a wild-type turn sequence with an elastin-based turn provides a novel way to both improve stability of target proteins at body temperature and to possibly introduce a temperature-sensitive switch. [Copyright &y& Elsevier]

Muscle myosins are molecular motors that hydrolyze ATP and generate force through coordinated interactions with actin filaments, known as cross-bridge cycling. During the cross-bridge cycle, functional sites in myosin 'sense' changes in interactions with actin filaments and the nucleotide binding region, resulting in allosteric transmission of information throughout the structure. We investigated whether the dynamics of the post-powerstroke state of the cross-bridge cycle are modulated in a nucleotide-dependent fashion. We compared molecular dynamics simulations of the myosin II motor domain (M) from Dictyostelium discoideum in the presence of ADP (M.ADP) versus 2′-deoxy-ADP bound myosin (M.dADP). We found that dADP was more flexible than ADP and the two nucleotides interacted with myosin in different ways. Replacement of ADP with dADP in the post-powerstroke state also altered the conformation of the actin binding region in myosin heads. Our results provide atomic level insights into allosteric communication networks in myosin that provide insight into the nucleotide-dependent dynamics of the cross-bridge cycle. [ABSTRACT FROM AUTHOR]

We have analysed the transition state of folding of the four-helix FF domain from HYPA/FBP11 by high-resolution experiment and simulation as part of a continuing effort to understand the principles of folding and the refinement of predictive methods. The major transition state for folding was subjected to a Φ-value analysis utilising 50 mutants. The transition state contained a nucleus for folding centred around the end of helix 1 (H1) and the beginning of helix 2 (H2). Secondary structure in this region was fully formed (ΦF=0.9–1) and tertiary interactions were well developed. Interactions in the distal part of the native structure were weak (ΦF=0–0.2). The hydrophobic core and other parts of the protein displayed intermediate Φ-values, suggesting that interactions coalesce as the end of H1 and beginning of H2 are in the process of being formed. The distribution of Φ-values resembled that of barnase, which folds via an intermediate, rather than that of CI2 which folds by a concerted nucleation–condensation mechanism. The overall picture of the transition state structure identified in molecular dynamics simulations is in qualitative agreement, with the turn connecting H1 and H2 being formed, a loosened core, and H4 partially unfolded and detached from the core. There are some differences in the details and interpretation of specific Φ-values. [Copyright &y& Elsevier]