Conformational plasticity of an enzyme during catalysis: intricate coupling between cyclophilin A dynamics and substrate turnover

PyInteraph2 and PyInKnife2 to Analyze Networks in Protein Structural Ensembles

Due to the complex nature of noncovalent interactions and their long-range effects, analyzing protein conformations using network theory can be enlightening. Protein Structure Networks (PSNs) provide a convenient formalism to study protein structures in relation to essential properties such as key residues for structural stability, allosteric communication, and the effects of modifications of the protein. PSNs can be defined according to very different principles, and the available tools have limitations in input formats, supported models, and version control. Other outstanding problems are related to the definition of network cutoffs and the assessment of the stability of the network properties. The protein science community could benefit from a common framework to carry out these analyses and make them easier to reproduce, reuse, and evaluate. We here provide two open-source software packages, PyInteraph2 and PyInKnife2, to implement and analyze PSNs in a reproducible and documented manner. PyInteraph2 interfaces with multiple formats for protein ensembles and incorporates different network models with the possibility of integrating them into a macronetwork and performing various downstream analyses, including hubs, connected components, and several other centrality measures, and visualizes the networks or further analyzes them thanks to compatibility with Cytoscape.PyInKnife2 that supports the network models implemented in PyInteraph2. It employs a jackknife resampling approach to estimate the convergence of network properties and streamline the selection of distance cutoffs. We foresee that the modular structure of the code and the supported version control system will promote the transition to a community-driven effort, boost reproducibility, and establish common protocols in the PSN field. As developers, we will guarantee the introduction of new functionalities and maintenance, assistance, and training of new contributors.

Schistosomal Sulfotransferase Interaction with Oxamniquine Involves Hybrid Mechanism of Induced-fit and Conformational Selection

Background:

Sulfotransferase family comprises key enzymes involved in drug metabolism. Oxamniquine is a pro-drug converted into its active form by schistosomal sulfotransferase. The conformational dynamics of side-chain amino acid residues at the binding site of schistosomal sulfotransferase towards activation of oxamniquine has not received attention.

Objective:

The study investigated the conformational dynamics of binding site residues in free and oxamniquine bound schistosomal sulfotransferase systems and their contribution to the mechanism of oxamniquine activation by schistosomal sulfotransferase using molecular dynamics simulations and binding energy calculations.

Methods:

Schistosomal sulfotransferase was obtained from Protein Data Bank and both the free and oxamniquine bound forms were subjected to molecular dynamics simulations using GROMACS-4.5.5 after modeling it’s missing amino acid residues with SWISS-MODEL. Amino acid residues at its binding site for oxamniquine was determined and used for Principal Component Analysis and calculations of side-chain dihedrals. In addition, binding energy of the oxamniquine bound system was calculated using g_MMPBSA.

Results:

The results showed that binding site amino acid residues in free and oxamniquine bound sulfotransferase sampled different conformational space involving several rotameric states. Importantly, Phe45, Ile145 and Leu241 generated newly induced conformations, whereas Phe41 exhibited shift in equilibrium of its conformational distribution. In addition, the result showed binding energy of -130.091 ± 8.800 KJ/mol and Phe45 contributed -9.8576 KJ/mol.

Conclusion:

The results showed that schistosomal sulfotransferase binds oxamniquine by relying on hybrid mechanism of induced fit and conformational selection models. The findings offer new insight into sulfotransferase engineering and design of new drugs that target sulfotransferase.

Dynamic design: manipulation of millisecond timescale motions on the energy landscape of cyclophilin A

Proteins need to interconvert between many conformations in order to function, many of which are formed transiently, and sparsely populated. Particularly when the lifetimes of these states approach the millisecond timescale, identifying the relevant structures and the mechanism by which they interconvert remains a tremendous challenge. Here we introduce a novel combination of accelerated MD (aMD) simulations and Markov state modelling (MSM) to explore these 'excited' conformational states. Applying this to the highly dynamic protein CypA, a protein involved in immune response and associated with HIV infection, we identify five principally populated conformational states and the atomistic mechanism by which they interconvert. A rational design strategy predicted that the mutant D66A should stabilise the minor conformations and substantially alter the dynamics, whereas the similar mutant H70A should leave the landscape broadly unchanged. These predictions are confirmed using CPMG and R1ρ solution state NMR measurements. By efficiently exploring functionally relevant, but sparsely populated conformations with millisecond lifetimes in silico, our aMD/MSM method has tremendous promise for the design of dynamic protein free energy landscapes for both protein engineering and drug discovery.

Enzyme activity and structural features of three single-domain phloem cyclophilins from Brassica napus

Cyclophilins (CYPs) are a group of ubiquitous prolyl cis/trans isomerases (PPIases). It was shown that plants possess the most diverse CYP families and that these are abundant in the phloem long-distance translocation stream. Since phloem exudate showed PPIase activity, three single-domain CYPs that occur in phloem samples from Brassica napus were characterised on functional and structural levels. It could be shown that they exhibit isomerase activity and that this activity is controlled by a redox regulation mechanism, which has been postulated for divergent CYPs. The structure determination by small-angle X-ray scattering experiments revealed a conserved globular shape. In addition, the high-resolution crystal structure of BnCYP19-1 was resolved and refined to 2.0 Å resolution, and the active sites of related CYPs as well as substrate binding were modelled. The obtained data and results support the hypothesis that single domain phloem CYPs are active phloem PPIases that may function as chaperones.

Biliverdin Reductase B Dynamics Are Coupled to Coenzyme Binding

Biliverdin reductase B (BLVRB) is a newly identified cellular redox regulator that catalyzes the NADPH-dependent reduction of multiple substrates. Through mass spectrometry analysis, we identified high levels of BLVRB in mature red blood cells, highlighting the importance of BLVRB in redox regulation. The BLVRB conformational changes that occur during conezyme/substrate binding and the role of dynamics in BLVRB function, however, remain unknown. Through a combination of NMR, kinetics, and isothermal titration calorimetry studies, we determined that BLVRB binds its coenzyme 500-fold more tightly than its substrate. While the active site of apo BLVRB is highly dynamic on multiple timescales, active site dynamics are largely quenched within holo BLVRB, in which dynamics are redistributed to other regions of the enzyme. We show that a single point mutation of Arg78➔Ala leads to both an increase in active site micro-millisecond motions and an increase in the microscopic rate constants of coenzyme binding. This demonstrates that altering BLVRB active site dynamics can directly cause a change in functional characteristics. Our studies thus address the solution behavior of apo and holo BLVRB and identify a role of enzyme dynamics in coenzyme binding.

Structural basis of interaction between dimeric cyclophilin 1 and Myb1 transcription factor in Trichomonas vaginalis

Cyclophilin 1 (TvCyP1), a cyclophilin type peptidyl-prolyl isomerase present in the human parasite Trichomonas vaginalis, interacts with Myb1 and assists in its nuclear translocation. Myb1 regulates the expression of ap65-1 gene that encodes for a disease causing cytoadherence enzyme. Here, we determined the crystal structures of TvCyP1 and its complex with the minimum TvCyP1-binding sequence of Myb1 (Myb1^104-111), where TvCyP1 formed a homodimer, unlike other single domain cyclophilins. In the complex structure, one Myb1^104-111 peptide was bound to each TvCyP1 protomer, with G106-P107 and Y105 fitting well into the active site and auxiliary S2 pocket, respectively. NMR data further showed that TvCyP1 can catalyze the cis/trans isomerization of P107 in Myb1^104-111. Interestingly, in the well-folded Myb1 protein (Myb1^35-141), the minimum binding sequence adopted a different conformation from that of unstructured Myb1^104-111 peptide, that could make P107 binding to the active site of TvCyP1 difficult. However, NMR studies showed that similar to Myb1^104-111 peptide, Myb1^35-141 also interacted with the active site of TvCyP1 and the dynamics of the Myb1^35-141 residues near P107 was reduced upon interaction. Together, the structure of TvCyP1 and detailed structural insights on TvCyP1-Myb1 interaction provided here could pave the way for newer drugs to treat drug-resistant strains.

Evaluation of estrogen receptor alpha activation by glyphosate-based herbicide constituents

The safety, including the endocrine disruptive capability, of glyphosate-based herbicides (GBHs) is a matter of intense debate. We evaluated the estrogenic potential of glyphosate, commercial GBHs and polyethoxylated tallowamine adjuvants present as co-formulants in GBHs. Glyphosate (≥10,000 μg/L or 59 μM) promoted proliferation of estrogen-dependent MCF-7 human breast cancer cells. Glyphosate also increased the expression of an estrogen response element-luciferase reporter gene (ERE-luc) in T47D-KBluc cells, which was blocked by the estrogen antagonist ICI 182,780. Commercial GBH formulations or their adjuvants alone did not exhibit estrogenic effects in either assay. Transcriptomics analysis of MCF-7 cells treated with glyphosate revealed changes in gene expression reflective of hormone-induced cell proliferation but did not overlap with an ERα gene expression biomarker. Calculation of glyphosate binding energy to ERα predicts a weak and unstable interaction (-4.10 kcal mol-1) compared to estradiol (-25.79 kcal mol-1), which suggests that activation of this receptor by glyphosate is via a ligand-independent mechanism. Induction of ERE-luc expression by the PKA signalling activator IBMX shows that ERE-luc is responsive to ligand-independent activation, suggesting a possible mechanism of glyphosate-mediated activation. Our study reveals that glyphosate, but not other components present in GBHs, can activate ERα in vitro, albeit at relatively high concentrations.

In Silico Studies of Small Molecule Interactions with Enzymes Reveal Aspects of Catalytic Function

Small molecules, such as solvent, substrate, and cofactor molecules, are key players in enzyme catalysis. Computational methods are powerful tools for exploring the dynamics and thermodynamics of these small molecules as they participate in or contribute to enzymatic processes. In-depth knowledge of how small molecule interactions and dynamics influence protein conformational dynamics and function is critical for progress in the field of enzyme catalysis. Although numerous computational studies have focused on enzyme-substrate complexes to gain insight into catalytic mechanisms, transition states and reaction rates, the dynamics of solvents, substrates, and cofactors are generally less well studied. Also, solvent dynamics within the biomolecular solvation layer play an important part in enzyme catalysis, but a full understanding of its role is hampered by its complexity. Moreover, passive substrate transport has been identified in certain enzymes, and the underlying principles of molecular recognition are an area of active investigation. Enzymes are highly dynamic entities that undergo different conformational changes, which range from side chain rearrangement of a residue to larger-scale conformational dynamics involving domains. These events may happen nearby or far away from the catalytic site, and may occur on different time scales, yet many are related to biological and catalytic function. Computational studies, primarily molecular dynamics (MD) simulations, provide atomistic-level insight and site-specific information on small molecule interactions, and their role in conformational pre-reorganization and dynamics in enzyme catalysis. The review is focused on MD simulation studies of small molecule interactions and dynamics to characterize and comprehend protein dynamics and function in catalyzed reactions. Experimental and theoretical methods available to complement and expand insight from MD simulations are discussed briefly.

Single Mutations Reshape the Structural Correlation Network of the DMXAA-Human STING Complex

Subtle changes in protein sequences are able to alter ligand-protein interactions. Unraveling the mechanism of such phenomena is important for understanding ligand-protein interactions, including the DMXAA-STING interaction. DMXAA specifically binds to mouse STING instead of human STING. However, the S162A mutation and a newly discovered E260I mutation endow human STING^AQ with DMXAA sensitivity. Through molecular dynamics simulations, we revealed how these single mutations alter the DMXAA-STING interaction. Compared to mutated systems, structural correlations in the interaction of STING^AQ with DMXAA are stronger, and the correlations are cross-protomers in the dimeric protein. Analyses on correlation coefficients lead to the identification of two key interactions that mediate the strong cross-protomer correlation in the DMXAA-STING^AQ interaction network: DMXAA-267T-162S* and 238R-260E*. These two interactions are partially and totally interrupted by the S162A and E260I mutations, respectively. Moreover, a smaller number of water molecules are displaced upon DMXAA binding to STING^AQ than that on binding to its mutants, leading to a larger entropic penalty for the former. Considering the sensitivity of STING^AQ and two of its mutants to DMXAA, a strong structural correlation appears to discourage DMXAA-STING binding. Such an observation suggests that DMXAA derivatives, which are deprived of hydrogen-bond interaction with both 162S* and 267T, are potential agonists of human STING.

Protein Ensembles: How Does Nature Harness Thermodynamic Fluctuations for Life? The Diverse Functional Roles of Conformational Ensembles in the Cell

All soluble proteins populate conformational ensembles that together constitute the native state. Their fluctuations in water are intrinsic thermodynamic phenomena, and the distributions of the states on the energy landscape are determined by statistical thermodynamics; however, they are optimized to perform their biological functions. In this review we briefly describe advances in free energy landscape studies of protein conformational ensembles. Experimental (nuclear magnetic resonance, small-angle X-ray scattering, single-molecule spectroscopy, and cryo-electron microscopy) and computational (replica-exchange molecular dynamics, metadynamics, and Markov state models) approaches have made great progress in recent years. These address the challenging characterization of the highly flexible and heterogeneous protein ensembles. We focus on structural aspects of protein conformational distributions, from collective motions of single- and multi-domain proteins, intrinsically disordered proteins, to multiprotein complexes. Importantly, we highlight recent studies that illustrate functional adjustment of protein conformational ensembles in the crowded cellular environment. We center on the role of the ensemble in recognition of small- and macro-molecules (protein and RNA/DNA) and emphasize emerging concepts of protein dynamics in enzyme catalysis. Overall, protein ensembles link fundamental physicochemical principles and protein behavior and the cellular network and its regulation.

Isolation and purification of Bacillus thuringiensis var. israelensis IМV В-7465 peptidase with specificity toward elastin and collagen

Peptidase of Bacillus thuringiensis var. israelensis IМV В-7465 was isolated from culture supernatant using consecutive fractionations by an ammonium sulphate (60% saturation), ion-exchange chromatography and gel-filtration on the TSK-gels Toyoperl HW-55 and DEAE 650(M). Specific elastase (442 U∙mg of protein-1) and collagenase (212.7 U∙mg of protein-1) activities of the purified enzyme preparation were 8.0- and 6.1-fold, respectively higher than ones of the culture supernatant. Peptidase yields were 33.5% for elastase activity and 30.1% for collagenase activity. It was established that the enzyme is serine metal-dependent alkaline peptidase with Mr about 37 kDa. Maximal hydrolysis of elastin and collagen occurs at the optimum pH 8.0 and t° – 40 and 50 °С, respectively. The purified preparation has high stability at pH in the range of 7.0 to 10.0 and 40-50 °С.

Dynamical network of residue-residue contacts reveals coupled allosteric effects in recognition, catalysis, and mutation

Detailed understanding of how conformational dynamics orchestrates function in allosteric regulation of recognition and catalysis remains ambiguous. Here, we simulate CypA using multiple-microsecond-long atomistic molecular dynamics in explicit solvent and carry out NMR experiments. We analyze a large amount of time-dependent multidimensional data with a coarse-grained approach and map key dynamical features within individual macrostates by defining dynamics in terms of residue-residue contacts. The effects of substrate binding are observed to be largely sensed at a location over 15 Å from the active site, implying its importance in allostery. Using NMR experiments, we confirm that a dynamic cluster of residues in this distal region is directly coupled to the active site. Furthermore, the dynamical network of interresidue contacts is found to be coupled and temporally dispersed, ranging over 4 to 5 orders of magnitude. Finally, using network centrality measures we demonstrate the changes in the communication network, connectivity, and influence of CypA residues upon substrate binding, mutation, and during catalysis. We identify key residues that potentially act as a bottleneck in the communication flow through the distinct regions in CypA and, therefore, as targets for future mutational studies. Mapping these dynamical features and the coupling of dynamics to function has crucial ramifications in understanding allosteric regulation in enzymes and proteins, in general.

Conformational Changes and Free Energies in a Proline Isomerase

Proteins are dynamic molecules and their ability to adopt alternative conformations is central to their biological function. The structural and biophysical properties of transiently and sparsely populated states are, however, difficult to study and an atomic-level description of those states is challenging. We have used enhanced-sampling all-atom, explicit-solvent molecular simulations, guided by structural information from X-ray crystallography and NMR, to describe quantitatively the transition between the major and a minor state of Cyclophilin A, thus providing new insight into how dynamics can affect enzyme function. We calculate the conformational free energy between the two states, and comparison with experiments demonstrates a surprisingly high accuracy for both the wild type protein and a mutant that traps the protein in its alternative conformation. Our results demonstrate how the combination of state-of-the-art force fields and enhanced sampling methods can provide a detailed and quantitative description of the conformational changes in proteins such as those observed in Cyclophilin A.

Comparison of the Internal Dynamics of Metalloproteases Provides New Insights on Their Function and Evolution

Metalloproteases have evolved in a vast number of biological systems, being one of the most diverse types of proteases and presenting a wide range of folds and catalytic metal ions. Given the increasing understanding of protein internal dynamics and its role in enzyme function, we are interested in assessing how the structural heterogeneity of metalloproteases translates into their dynamics. Therefore, the dynamical profile of the clan MA type protein thermolysin, derived from an Elastic Network Model of protein structure, was evaluated against those obtained from a set of experimental structures and molecular dynamics simulation trajectories. A close correspondence was obtained between modes derived from the coarse-grained model and the subspace of functionally-relevant motions observed experimentally, the later being shown to be encoded in the internal dynamics of the protein. This prompted the use of dynamics-based comparison methods that employ such coarse-grained models in a representative set of clan members, allowing for its quantitative description in terms of structural and dynamical variability. Although members show structural similarity, they nonetheless present distinct dynamical profiles, with no apparent correlation between structural and dynamical relatedness. However, previously unnoticed dynamical similarity was found between the relevant members Carboxypeptidase Pfu, Leishmanolysin, and Botulinum Neurotoxin Type A, despite sharing no structural similarity. Inspection of the respective alignments shows that dynamical similarity has a functional basis, namely the need for maintaining proper intermolecular interactions with the respective substrates. These results suggest that distinct selective pressure mechanisms act on metalloproteases at structural and dynamical levels through the course of their evolution. This work shows how new insights on metalloprotease function and evolution can be assessed with comparison schemes that incorporate information on protein dynamics. The integration of these newly developed tools, if applied to other protein families, can lead to more accurate and descriptive protein classification systems.

Cyclophilin40 isomerase activity is regulated by a temperature-dependent allosteric interaction with Hsp90

Cyclophilin 40 (Cyp40) comprises an N-terminal cyclophilin domain with peptidyl-prolyl isomerase (PPIase) activity and a C-terminal tetratricopeptide repeat (TPR) domain that binds to the C-terminal-EEVD sequence common to both heat shock protein 70 (Hsp70) and Hsp90. We show in the present study that binding of peptides containing the MEEVD motif reduces the PPIase activity by ∼30%. CD and fluorescence assays show that the TPR domain is less stable than the cyclophilin domain and is stabilized by peptide binding. Isothermal titration calorimetry (ITC) shows that the affinity for the-MEEVD peptide is temperature sensitive in the physiological temperature range. Results from these biophysical studies fit with the MD simulations of the apo and holo (peptide-bound) structures which show a significant reduction in root mean square (RMS) fluctuation in both TPR and cyclophilin domains when-MEEVD is bound. The MD simulations of the apo-protein also highlight strong anti-correlated motions between residues around the PPIase-active site and a band of residues running across four of the seven helices in the TPR domain. Peptide binding leads to a distortion in the shape of the active site and a significant reduction in these strongly anti-correlated motions, providing an explanation for the allosteric effect of ligand binding and loss of PPIase activity. Together the experimental and MD results suggest that on heat shock, dissociation of Cyp40 from complexes mediated by the TPR domain leads to an increased pool of free Cyp40 capable of acting as an isomerase/chaperone in conditions of cellular stress.

Keep on moving: discovering and perturbing the conformational dynamics of enzymes

CONSPECTUS: Because living organisms are in constant motion, the word "dynamics" can hold many meanings to biologists. Here we focus specifically on the conformational changes that occur in proteins and how studying these protein dynamics may provide insights into enzymatic catalysis. Advances in integrating techniques such as X-ray crystallography, nuclear magnetic resonance, and electron cryomicroscopy (cryo EM) allow us to model the dominant structures and exchange rates for many proteins and protein complexes. For proteins amenable to atomic resolution techniques, the major questions shift from simply describing the motions to discovering their role in function. Concurrently, there is an increasing need for using perturbations to test predictive models of dynamics-function relationships. Examples are the catalytic cycles of dihydrofolate reductase (DHFR) and cyclophilin A (CypA). In DHFR, mutations that alter the ability of the active site to sample productive higher energy states on the millisecond time scale reduce the rate of hydride transfer significantly. Recently identified rescue mutations restore function, but the mechanism by which they do so remains unclear. The exact role of any changes in the dynamics remains an open question. For CypA, a network of side chains that exchange between two conformations is critical for catalysis. Mutations that lock the network in one state also reduce catalytic activity. A further understanding of enzyme dynamics of well-studied enzymes such as dihydrofolate reductase and cyclophilin A will lead to improvement in ability to modulate the functions of computationally designed enzymes and large macromolecular machines. In designed enzymes, directed evolution experiments increase catalytic rates. Detailed X-ray studies suggest that these mutations likely limit the conformational space explored by residues in the active site. For proteins where atomic resolution information is currently inaccessible, other techniques such as cryo-EM and high-resolution single molecule microscopy continue to advance. Understanding the conformational dynamics of larger systems such as protein machines will likely become more accessible and provide new opportunities to rationally modulate protein function.

Computational perspective and evaluation of plausible catalytic mechanisms of peptidyl-prolyl cis-trans isomerases

BACKGROUND

Peptidyl prolyl cis-trans isomerization of the protein backbone is involved in the regulation of many biological processes. Cis-trans isomerization is notoriously slow and is catalyzed by a family of cis-trans peptidyl prolyl isomerases (PPIases) that have been implicated in many diseases. A general consensus on how these enzymes speed up prolyl isomerization has not been reached after decades of both experimental and computational studies.

SCOPE OF REVIEW

Computational studies carried out to understand the catalytic mechanism of the prototypical FK506 binding protein 12, Cyclophilin A and peptidyl-prolyl cis-trans isomerase NIMA-interacting 1 (Pin1) are reviewed. A summary and an evaluation of the implications of the proposed mechanisms from computational studies are presented.

MAJOR CONCLUSIONS

The analysis of computational studies and evaluation of the proposed mechanisms provide a general consensus and a better understanding of PPIase catalysis. The speedup of the rate of peptidyl-prolyl isomerization by PPIases can be best described by a catalytic mechanism in which the substrate in transition state configuration is stabilized. The enzymes preferentially bind the transition state configuration of the substrate relative to the cis conformation, which in most cases is bound better than the trans conformation of the substrate. Stabilization of the transition state configuration of the substrate leads to a lower free energy barrier and a faster rate of isomerization when compared to the uncatalyzed isomerization reaction.

GENERAL SIGNIFICANCE

Fully understanding the catalytic mechanism of PPIases has broad implications for drug design, elucidation of the molecular basis of many diseases, protein engineering, and enzyme catalysis in general. This article is part of a Special Issue entitled Proline-directed Foldases: Cell Signaling Catalysts and Drug Targets.

Full Atom Simulations of Spin Label Conformations

Interpretation of EPR measurables from spin labels in terms of structure and dynamics requires knowledge of label behavior. General strategies were developed for simulation of labels used in EPR of proteins. The criteria for those simulations are (a) exhaustive sampling of rotamer space, (b) consensus of results independent of starting points, and (c) inclusion of entropy. These criteria are satisfied only when the number of transitions in any dihedral angle exceeds 100 and the simulation maintains thermodynamic equilibrium. Methods such as conventional MD do not efficiently cross energetic barriers, simulated anealing, Monte Carlo or popular Rotamer Library methodologies are potential energy based and ignore entropy (in addition to their specific shortcomings: environment fluctuations, fixed environment, or electrostatics). The Simulated scaling method avoids the above flaws by modulating the force fields between a reduced (allowing crossing energy barriers) and full potential (sampling minima). Spin label diffuses on this surface while remaining in thermodynamic equilibrium. Simulations show that (a) adopting a single conformation is rare, often there are two to four populated rotamers and (b) position of the NO varies up to 16 Å. These results illustrate necessity for caution when interpreting EPR signals in terms of molecular structure. For example, the 10-16 Å distance change in DEER should not be interpreted as a large conformational change, it can well be a flip about Cα-Cβ bond. Rigorous exploration of possible rotamer structures of a spin label is paramount in signal interpretation. We advocate use of bifunctional labels, motion of which is restricted 10,000-fold and the NO position is restricted to 2-5 Å.

Towards fast, rigorous and efficient conformational sampling of biomolecules: Advances in accelerated molecular dynamics

BACKGROUND

Accelerated molecular dynamics (aMD) has been proven to be a powerful biasing method for enhanced sampling of biomolecular conformations on general-purpose computational platforms. Biologically important long timescale events that are beyond the reach of standard molecular dynamics can be accessed without losing the detailed atomistic description of the system in aMD. Over other biasing methods, aMD offers the advantages of tuning the level of acceleration to access the desired timescale without any advance knowledge of the reaction coordinate.

SCOPE OF REVIEW

Recent advances in the implementation of aMD and its applications to small peptides and biological macromolecules are reviewed here along with a brief account of all the aMD variants introduced in the last decade.

MAJOR CONCLUSIONS

In comparison to the original implementation of aMD, the recent variant in which all the rotatable dihedral angles are accelerated (RaMD) exhibits faster convergence rates and significant improvement in statistical accuracy of retrieved thermodynamic properties. RaMD in conjunction with accelerating diffusive degrees of freedom, i.e. dual boosting, has been rigorously tested for the most difficult conformational sampling problem, protein folding. It has been shown that RaMD with dual boosting is capable of efficiently sampling multiple folding and unfolding events in small fast folding proteins.

GENERAL SIGNIFICANCE

RaMD with the dual boost approach opens exciting possibilities for sampling multiple timescales in biomolecules. While equilibrium properties can be recovered satisfactorily from aMD-based methods, directly obtaining dynamics and kinetic rates for larger systems presents a future challenge. This article is part of a Special Issue entitled Recent developments of molecular dynamics.

Achieving Rigorous Accelerated Conformational Sampling in Explicit Solvent

Molecular dynamics simulations can provide valuable atomistic insights into biomolecular function. However, the accuracy of molecular simulations on general-purpose computers depends on the time scale of the events of interest. Advanced simulation methods, such as accelerated molecular dynamics, have shown tremendous promise in sampling the conformational dynamics of biomolecules, where standard molecular dynamics simulations are nonergodic. Here we present a sampling method based on accelerated molecular dynamics in which rotatable dihedral angles and nonbonded interactions are boosted separately. This method (RaMD-db) is a different implementation of the dual-boost accelerated molecular dynamics, introduced earlier. The advantage is that this method speeds up sampling of the conformational space of biomolecules in explicit solvent, as the degrees of freedom most relevant for conformational transitions are accelerated. We tested RaMD-db on one of the most difficult sampling problems - protein folding. Starting from fully extended polypeptide chains, two fast folding α-helical proteins (Trpcage and the double mutant of C-terminal fragment of Villin headpiece) and a designed β-hairpin (Chignolin) were completely folded to their native structures in very short simulation time. Multiple folding/unfolding transitions could be observed in a single trajectory. Our results show that RaMD-db is a promisingly fast and efficient sampling method for conformational transitions in explicit solvent. RaMD-db thus opens new avenues for understanding biomolecular self-assembly and functional dynamics occurring on long time and length scales.

The dilemma of conformational dynamics in enzyme catalysis: perspectives from theory and experiment

The role of protein dynamics in catalysis is a contemporary issue that has stirred intense debate in the field. This chapter provides a brief overview of the approaches and findings of a wide range of experimental, computational and theoretical studies that have addressed this issue. We summarize the results of our recent atomistic molecular dynamic studies on cis-trans isomerase. Our results help to reconcile the disparate perspectives regarding the complex role of enzyme dynamics in the catalytic step and emphasize the major contribution of transition state stabilization in rate enhancement.