Prediction of protein conformation on the basis of a search for compact structures: test on avian pancreatic polypeptide.

Based on the concept that hydrophobic interactions cause a polypeptide chain to adopt a compact structure, a method is proposed to predict the structure of a protein. The procedure is carried out in four stages: (1) use of a virtual-bond united-residue approximation with the side chains represented by spheres to search conformational space extensively using specially designed interactions to lead to a collapsed structure, (2) conversion of the lowest-energy virtual-bond united-residue chain to one with a real polypeptide backbone, with optimization of the hydrogen-bond network among the backbone groups, (3) perturbation of the latter structure by the electrostatically driven Monte Carlo (EDMC) procedure, and (4) conversion of the spherical representation of the side chains to real groups and perturbation of the whole molecule by the EDMC procedure using the empirical conformational energy program for peptides (ECEPP/2) energy function plus hydration. Application of this procedure to the 36-residue avian pancreatic polypeptide led to a structure that resembled the one determined by X-ray crystallography; it had an alpha-helix starting at residue 13, with the N-terminal portion of the chain in an extended conformation packed against the alpha-helix. Similar structures with slightly higher energies, but looser packing, were also obtained.     

Hydration of the left spiral of the poly-L-proline type. Study by the Monte Carlo method]

The paper exhibits results of hydration shell Monte Carlo calculations in poly-L-proline II and extended helix conformation and in alpha-helical and beta-structural conformations for comparison. It was found that left-handed helix of poly-L-proline II type as well as epsilon-helix are characterized by very favorable hydration. Therefore this conformation has preference as compared to other standard conformations of the main polypeptide chain. This determined inevitability of cold denaturation of protein.     

On the multiple-minima problem in the conformational analysis of polypeptides. IV. Application of the electrostatically driven Monte Carlo method to the 20-residue membrane-bound portion of melittin

The conformational space of the membrane-bound portion of melittin has been searched using the electrostatically driven Monte Carlo (EDMC) method with the ECEPP/2 (empirical conformational energy program for peptides) algorithm. The former methodology assumes that a polypeptide or protein molecule is driven toward the native structure by the combined action of electrostatic interactions and stochastic conformational changes associated with thermal movements. The algorithm produces a Monte Carlo search in the conformational hyperspace of the polypeptide using electrostatic predictions and a random sampling technique, combined with local minimization of the energy function, to locate low-energy conformations. As a result of 8 test calculations on the 20-residue membrane-bound portion of melittin, starting from six arbitrary and two completely random conformations, the method was able to locate a very low-energy region of the potential with a well-defined structure for the backbone. In all of the cases under study, the method found a cluster of similar low-energy conformations that agree well with the structure deduced from x-ray diffraction experiments and with one computed earlier by the build-up procedure.     

Optimal protocol and trajectory visualization for conformational searches of peptides and proteins.

Conformational searches by molecular dynamics and different types of Monte Carlo or build-up methods usually aim to find the lowest-energy conformation. However, this is often misleading, as the energy functions used in conformational calculations are imprecise. For instance, though positions of local minima defined by the repulsive part of the Lennard-Jones potential are usually altered only slightly by functional modification, the relative depths of the minima could change significantly. Thus, the purpose of conformational searches and, correspondingly, performance criteria should be reformulated and appropriate methods found to extract different local minima from the search trajectory and allow visualization in the search space. Attempts at convergence to the lowest-energy structure should be replaced with efforts to visit a maximum number of different local energy minima with energies within a certain range. We use this quantitative criterion consistently to evaluate performances of different search procedures. To utilize information generated in the course of simulation, a "stack" of low energy conformations is created and stored. It keeps track of variables and visit numbers for the best representatives of different conformational families. To visualize the search, projection of multidimensional walks onto a principal plane defined by a set of reference structures is used. With Met-enkephalin as a structural example and a Monte Carlo procedure combined with energy minimization (MCM) as a basic search method, we analyzed the influence on search efficiency of different characteristics as temperature schedules, the step size for variable modification, constrained random step and response mechanisms to search difficulties. Simulated annealing MCM had comparable efficiency with MCM at constant and elevated temperature (about 600 K). Constraining the randomized choice of side-chain chi angles to optimal values (rotamers) on every MCM step did not improve, but rather worsened, the search efficiency. Two low-energy Met-enkephalin conformations with parallel Tyr1 and Phe4 rings, a gamma-turn around the Gly2 residue, and Phe4 and Met5 side-chains forming together a compact hydrophobic cluster were found and are suggested as possible structural candidates for interaction with a receptor or a membrane.     

New developments of the electrostatically driven monte carlo method: Test on the membrane-bound portion of melittin

The electrostatically driven Monte Carlo (EDMC) method has been greatly improved by adding a series of new features, including a procedure for cluster analysis of the accepted conformations. This information is used to guide the search for the global energy minimum. Alternative procedures for generating perturbed conformations to sample the conformational space were also included. These procedures enhance the efficiency of the method by generating a larger number of low-energy conformations. The improved EDMC method has been used to explore the conformational space of a 20-residue polypeptide chain whose sequence corresponds to the membrane-bound portion of melittin. The ECEPP/3 (Empirical Conformational Energy Program for Peptides) algorithm was used to describe the conformational energy of the chain. After an exhaustive search involving 14 independent runs, the lowest energy conformation (LEC) (−91.0 kcal/mol) of the entire study was encountered in four of the runs, while conformations higher in energy by no more than 1.8 kcal/mol were found in the remaining runs with the exception of one of them (run 8). The LEC is identical to the conformation found recently by J. Lee, H.A. Scheraga, and S. Rackovsky [(1998) “Conformational Analysis of the 20-Residue Membrane-Bound Portion of Melittin by Conformational Space Annealing,” Biopolymers, Vol. 46, pp. 103–115] as the lowest energy conformation obtained in their study using the conformational space annealing method. These results suggest that this conformation corresponds to the global energy minimum of the ECEPP/3 potential function for this specific sequence; it also appears to be the conformation of lowest free energy. © 1998 John Wiley & Sons, Inc. Biopoly 46: 117–126, 1998     

The electrostatically driven Monte Carlo method: application to conformational analysis of decaglycine

The Electrostatically Driven Monte Carlo (EDMC) method was applied in a study of a decamer of glycine whose conformational behavior is described by the Empirical Conformational Energy Program for Peptides (ECEPP/2) potential energy model. When free neutral end groups were used, it was found that conformations that were not alpha-helical had significantly lower potential energies than fully alpha-helical ones. However, when the N- and C-termini were blocked by acetyl and methyl amide groups, respectively, the number of unsatisfied hydrogen-bond donors and acceptors at the helix termini was diminished from 8 to 6; in this case, the possibility of forming two additional alpha-helical hydrogen bonds was an important enough factor in making the alpha-helical conformation the one with the lowest energy. The EDMC method was used as a global energy optimizer since it does not often become trapped in high-energy local minima.     

A comparison of the CHARMM, AMBER and ECEPP potentials for peptides. I. Conformational predictions for the tandemly repeated peptide (Asn-Ala-Asn-Pro)9

A search for low-energy helical and near-helical conformations of the tandemly repeated peptide (Asn-Ala-Asn-Pro)9 was undertaken by minimization of the CHARMM potential energy function from eight starting conformations; the latter were obtained from the two low-energy conformations of this repeated peptide found by Gibson & Scheraga, Proc. Natl. Acad. Sci. USA 83, 5649-5653 (1986), and the single conformation found by Brooks et al., Proc. Natl. Acad. Sci. USA 84, 4470-4474 (1987), and from modifications of these three conformations. The same eight starting conformations, as determined by dihedral angles, were used for minimizations of the AMBER and ECEPP potentials. Comparison of the final conformations by least-squares superposition of their C alpha atoms, and by inspection of the parameters of the ideal helix or coiled coil that most closely matched the coordinates of their C alpha atoms in a least-squares sense, showed that: (1) energy minimization, starting from the same conformation but using any two different potentials, could lead to final conformations whose resemblance to each other varied from acceptable to highly unsatisfactory; (2) the ordering of the final energy-minimized conformations, and the energy differences between them, were quite different for all three potentials; (3) the extent of agreement or disagreement between pairs of conformations generated using CHARMM and AMBER, CHARMM and ECEPP, or AMBER and ECEPP, respectively, was not significantly different. The lowest-energy conformation generated using each of the potentials was a left-handed helix, whose pitch and number of residues per turn were similar to those of the left-handed helix found by Gibson & Scheraga. Although the starting conformation which led to the lowest-energy conformation was different for all three potentials, pairwise superposition of the C alpha atoms in the final conformations showed root-mean-square deviations of only 1.0-1.3 A. It is concluded that energy minimizations starting from a large enough sample of initial conformations might on occasion lead to essentially the same conformational prediction whichever potential is used; however, if the sample of starting points is small, predictions based on the three potentials will usually diverge.     

Prediction of the native conformation of a polypeptide by a statistical-mechanical procedure. II. Average backbone structure of enkephalin

The average conformation of Met-enkephalin was determined by using an adaptive, importance-sampling Monte Carlo algorithm (SMAPPS—Statistical Mechanical Algorithm for Predicting Protein Structure). In the calculation, only the backbone dihedral angles (? and ψ) were allowed to vary; i.e., all side-chain (χ) and peptide-bond (ω) dihedral angles were kept fixed at the values corresponding to a low-energy structure of the pentapeptide. The total conformational energy for each randomly generated structure of the polypeptide was obtained by summing over the interaction energies of all pairs of nonbonded atoms of the whole molecule. The interaction energies were computed by the program ECEPP/2 (Empirical Conformational Energy Program for Peptides). Solvent effects were not included in the computation. The calculation was repeated until a total of 10 independent average conformations were established. The regions of conformational space occupied by the average structures were compared with the regions of low conditional free energy obtained by SMAPPS in the first paper of this series. Such a comparison provides an analysis of the capacity of SMAPPS to adjust the Monte Carlo search to regions of highest probability. The results demonstrate that the ability of SMAPPS to focus the Monte Carlo search is excellent. Finally, the 10 independent average conformations and the mean of the 10 average structures were utilized as the initial conformations for a direct energy minimization of the pentapeptide. Of the 11 final energy-minimized structures, three of the conformations were found to be equivalent to the conformation of lowest energy determined previously. In addition, all but two of the remaining energy-minimized structures were found to correspond to one of the two other conformations of high probability obtained in the first paper of this series. These results indicate that a set of independent average conformations can provide a rational, unbiased choice for the initial conformation, to be used in a direct energy minimization of a polypeptide. The final energy-minimized structures consequently constitute a set of low-energy conformations, which include the global energy minimum.     

On the pH-conformational dependence of the unblocked SYPYD peptide.

Simulations were carried out for an unblocked pentapeptide with the sequence Ser-Tyr-Pro-Tyr-Asp (SYPYD) with explicit consideration of the coupling between the conformation of the molecule and the ionization equilibria at a given pH. The available NMR experimental data indicate a high preference for the cis isomeric turn-like form of Tyr-Pro at intermediate pH (approximately 6) and a destabilization of the cis form at both high (approximately 9) and low (approximately 3) pH. In order to identify the source of the stability of the conformation of this pentapeptide as a function of pH, Monte Carlo simulations were used to generate an ensemble of low-energy conformations at different pH values (viz. 3, 6 and 9). The total free energy function used in these calculations includes terms that account for the solvation free energy and free energy of ionization. These terms are evaluated by means of a fast multigrid boundary element (MBE) method. In good qualitative agreement with the experiments, our results indicate that the Boltzmann averaged population of the cis isomeric form of the pentapeptide has a maximum (45 %) at pH 6 and is significantly smaller (25 % and 23 %) for higher and lower pH values, respectively, following the trend of the experimental data. Also, the degree of charge for the lowest-energy conformations, as well as the contribution of electrostatic interactions to the stability of the preferred conformations, vary widely at the different pH values. Different kinds of packing of the aromatic side-chains of Tyr2 and Tyr4 against the proline ring are observed at different pH values, indicating that their contribution to the stability of the low-energy conformations is also pH-dependent. In summary, our results provide a basis for discussing the nature of the interactions that stabilize turn-like conformations of the peptide SYPYD as a function of pH.     

Dependence on the dielectric model and pH in a synthetic helical peptide studied by Monte Carlo simulated annealing

Monte Carlo simulated annealing is applied to the tertiary structure prediction of a 17-residue synthetic peptide, which is known by experiment to exhibit high helical content at low pH. Two dielectric models are considered: sigmoidal distance-dependent dielectric function and a constant dielectric function (? = 2). Starting from completely random initial conformations, our simulations for both dielectric models at low pH gave many helical conformations. The obtained low-energy conformations are compared with the nuclear Overhauser effect spectroscopy cross-peak data for both main chain and side chains, and it is shown that the results for the sigmoidal dielectric function are in remarkable agreement with the experimental data. The results predict the existence of two disjoint helices around residues 5–9 and 11–16, while nmr experiments imply significant α-helix content between residues 5 and 14. Simulations with high pH, on the other hand, hardly gave a helical conformation, which is also in accord with the experiment. These findings indicate that when side chains are charged, electrostatic interactions due to these charges play a major role in the helix stability. Our results are compared with the previous 500 ps molecular dynamics simulations of the same peptide. It is argued that simulated annealing is superior to molecular dynamics in two respects: (1) direct folding of α-helix from completely random initial conformations is possible for the former, whereas only unfolding of an α-helix can be studied by the latter; (2) while both methods predict high helix content for low pH, the results for high pH agree with experiment (low helix content) only for the former method. © 1994 John Wiley & Sons, Inc.     

Monte Carlo simulations of a protein molecule with and without hydration energy calculated by the hydration-shell model

Monte Carlo simulations of a small protein, carmbin, were carried out with and without hydration energy. The methodology presented here is characterized, as compared with the other similar simulations of proteins in solution, by two points: (1) protein conformations are treated in fixed geometry so that dihedral angles are independent variables rather than cartesian coordinates of atoms; and (2) instead of treating water molecules explicitly in the calculation, hydration energy is incorporated in the conformational energy function in the form of g _i A _i, whereA _i is the accessible surface area of an atomic groupi in a given conformation, andg _i is the free energy of hydration per unit surface area of the atomic group (i.e., hydration-shell model). Reality of this model was tested by carrying out Monte Carlo simulations for the two kinds of starting conformations, native and unfolded ones, and in the two kinds of systems,in vacuo and solution. In the simulations starting from the native conformation, the differences between the mean propertiesin vacuo and solution simulations are not very large, but their fluctuations around the mean conformation during the simulation are relatively smaller in solution thanin vacuo. On the other hand, in the simulations starting from the unfolded conformation, the molecule fluctuates much more largely in solution thanin vacuo, and the effects of taking into account the hydration energy are pronounced very much. The results suggest that the method presented in this paper is useful for the simulations of proteins in solution.     

Application of the multiensemble sampling to the equilibrium folding of proteins

MOTIVATION: Conventional Monte Carlo and molecular dynamics simulations of proteins in the canonical ensemble are of little use, because they tend to get trapped in states of energy local minima at low temperatures. One way to surmount this difficulty is to use a non-Boltzmann sampling method in which conformations are sampled upon a general weighting function instead of the conventional Boltzmann weighting function. The multiensemble sampling (MES) method is a non-Boltzmann sampling method that was originally developed to estimate free energy differences between systems with different potential energies and/or at different thermodynamic states. The method has not yet been applied to studies of complex molecular systems such as proteins. RESULTS: MES Monte Carlo simulations of small proteins have been carried out using a united-residue force field. The proteins at several temperatures from the unfolded to the folded states were simulated in a single MC run at a time and their equilibrium thermodynamic properties were calculated correctly. The distributions of sampled conformations clearly indicate that, when going through states of energy local minima, the MES simulation did not get trapped in them but escaped from them so quickly that all the relevant parts of conformation space could be sampled properly. A two-step folding process consisting of a collapse transition followed by a folding transition is observed. This study demonstrates that the use of MES alleviates the multiple-minima problem greatly. AVAILABILITY: Available on request from the authors.     

A pH-dependent variation in alpha-helix structure of the S-peptide of ribonuclease A studied by Monte Carlo simulated annealing.

Low-energy conformations of the S-peptide fragment (20 amino acid residues long) of ribonuclease A were studied by Monte Carlo simulated annealing. The obtained lowest-energy structures have alpha-helices with different size and location, depending distinctively on the ionizing states of acidic amino acid residues. The simulation started from completely random initial conformation and was performed without any bias toward a particular structure. The most conspicuous alpha-helices arose from the simulation when both Glu 9 and Asp 14 were assumed to be electrically neutral, whereas the resulting conformations became much less helical when Asp 14 rather than Glu 9 was allowed to have a negative charge. Together with experimental evidence that the alpha-helix in the S-peptide is most stable at pH 3.8, we consider the helix formation need the carboxyl group of Asp 14 to be electrically neutral in this weakly acidic condition. In contrast, a negative charge at Asp 14 appears to function in support of a view that this residue is crucial to helix termination owing to its possibility to form a salt bridge with His 12. These results indicate that the conformation of the S-peptide depends considerably on the ionizing state of Asp 14.     

Folding simulations of small proteins

Understanding how a protein folds is a long-standing challenge in modern science. We have used an optimized atomistic model (united-residue force field) to simulate folding of small proteins of various structures: HP-36 (alpha protein), protein A (beta), 1fsd (alpha+beta), and betanova (beta). Extensive Monte Carlo folding simulations (ten independent runs with 10(9) Monte Carlo steps at a temperature) starting from non-native conformations are carried out for each protein. In all cases, proteins fold into their native-like conformations at appropriate temperatures, and glassy transitions occur at low temperatures. To investigate early folding trajectories, 200 independent runs with 10(6) Monte Carlo steps are also performed at a fixed temperature for a protein. There are a variety of possible pathways during non-equilibrium early processes (fast process, approximately 10(4) Monte Carlo steps). Finally, these pathways converge to the point unique for each protein. The convergence point of the early folding pathways can be determined only by direct folding simulations. The free energy surface, an equilibrium thermodynamic property, dictates the rest of the folding (slow process, approximately 10(8) Monte Carlo steps).     

Prediction of the native conformation of a polypeptide by a statistical-mechanical procedure. I. Backbone structure of enkephalin

A new methodology for theoretically predicting the native, three-dimensional structure of a polypeptide is presented. Based on equilibrium statistical mechanics, an algorithm has been designed to determine the probable conformation of a polypeptide by calculating conditional free-energy maps for each residue of the macromolecule. The conditional free-energy map of each residue is computed from a set of probability integrals, obtained by summing over the interaction energies of all pairs of nonbonded atoms of the whole molecule. By locating the region(s) of lowest free energy for each map, the probable conformation for each residue can be identified. The native structure of the polypeptide is assumed to be the combination of the probable conformations of the individual residues. All multidimensional probability integrals are evaluated by an adaptive Monte Carlo algorithm (SMAPPS —Statistical-Mechanical Algorithm for Predicting Protein Structure). The Monte Carlo algorithm searches the entire conformational space, adjusting itself automatically to concentrate its sampling in regions where the magnitude of the integrand is largest (“importance sampling”). No assumptions are made about the native conformation. The only prior knowledge necessary for the prediction of the native conformation is the amino acid sequence of the polypeptide. To test the effectiveness of the algorithm, SMAPPS was applied to the prediction of the native conformation of the backbone of Met-enkephalin, a pentapeptide. In the calculations, only the backbone dihedral angles (? and ψ) were allowed to vary; all side-chain (χ) and peptide-bond (ω) dihedral angles were kept fixed at the values corresponding to the alleged global minimum energy previously determined by direct energy minimization. For each conformation generated randomly by the Monte Carlo algorithm, the total conformational energy of the polypeptide was obtained from established empirical potential energy functions. Solvent effects were not included in the computations. With this initial application of SMAPPS , three distinct low-free-energy β-bend structures of Met-enkephalin were found. In particular, one of the structures has a conformation remarkably similar to the one associated with the previously alleged global minimum energy. The two additional structures of the pentapeptide have conformational energies lower than the previously computed low-energy structure. However, the Monte Carlo results are in agreement with an improved energy-minimization procedure. These initial results on the backbone structure of Met-enkephalin indicate that an equilibrium statistical-mechanical procedure, coupled with an adaptive Monte Carlo algorithm, can overcome many of the problems associated with the standard methods of direct energy minimization.     

Prediction of the native conformation of a polypeptide by a statistical-mechanical procedure. III. Probable and average conformations of enkephalin

The program SMAPPS (Statistical-Mechanical Algorithm for Predicting Protein Structure) was originally designed to determine the probable and average backbone (?, ψ) conformations of a polypeptide by the application of equilibrium statistical mechanics in conjunction with an adaptive importance sampling Monte Carlo procedure. In the present paper, the algorithm has been extended to include the variation of all side-chain (χ) and peptide-bond (ω) dihedral angles of a polypeptide during the Monte Carlo search of the conformational space. To test the effectiveness of the generalized algorithm, SMAPPS was used to calculate the probable and average conformations of Met-enkephalin for which all dihedral angles of the pentapeptide were allowed to vary. The total conformational energy for each randomly generated structure of Met-enkephalin was obtained by summing over the interaction energies of all pairs of nonbonded atoms of the whole molecule. The interaction energies were computed by the program ECEPP /2 (Empirical Conformational Energy Program for Peptides). Solvent effects were not included in the computation. The results of the Monte Carlo calculation of the structure of Met-enkephalin indicate that the thermodynamically preferred conformation of the pentapeptide contains a γ-turn involving the three residues Gly²-Gly³-Phe⁴. The γ-turn conformation, however, does not correspond to the structure of lowest conformational energy. Rather, the global minimum-energy conformation, recently determined by a new optimization technique developed in this laboratory, contains a type II′ β-bend that is formed by the interaction of the four residues Gly²-Gly³-Phe⁴-Met⁵. A similar minimum-energy conformation is found by the SMAPPS procedure. The thermodynamically preferred γ-turn structure has a conformational energy of 4.93 kcal/mole higher than the β-bend structure of lowest energy but, because of the inclusion of entropy in the SMAPPS procedure, it is estimated to be ～ 9 kcal/mole lower in free energy. The calculation of the average conformation of Met-enkephalin was repeated until a total of ten independent average conformations were established. As far as the phenylalanine residue of the pentapeptide is concerned, the results of the ten independent average conformations were all found to lie in the region of conformational space corresponding to the γ-turn. These results further support the conclusion that the γturn conformation is thermodynamically favored.     

Free-energy landscape of the villin headpiece in an all-atom force field

We investigate the landscape of the internal free-energy of the 36 amino acid villin headpiece with a modified basin hopping method in the all-atom force field PFF01, which was previously used to predictively fold several helical proteins with atomic resolution. We identify near native conformations of the protein as the global optimum of the force field. More than half of the twenty best simulations started from random initial conditions converge to the folding funnel of the native conformation, but several competing low-energy metastable conformations were observed. From 76,000 independently generated conformations we derived a decoy tree which illustrates the topological structure of the entire low-energy part of the free-energy landscape and characterizes the ensemble of metastable conformations. These emerge as similar in secondary content, but differ in tertiary arrangement.     

Simulated annealing approach to the study of protein structures

One of the most difficult problems in predicting the three dimensional structure of proteins is how to deal with the local minimum problem. In many cases of practical interest this problem has been reduced to how to select an appropriate set of starting conformations for carrying out energy minimizations. How these starting conformations are selected, however, is often based on the physical intuition of the person doing the calculations, and hence it is hard to avoid bearing some sort of arbitrariness. To improve such a situation, we introduced the simulated annealing Monte Carlo algorithm to locate the optimal starting conformations for energy minimizations. The method developed here is valid for both single and multiple polypeptide chain systems. The annealing process can be conducted with respect to either the internal dihedral angles of a polypeptide chain or the external rotations and translations of various constituent polypeptide chains, and hence is particularly useful for studying the packing arrangements of secondary structures in proteins, such as helix/helix packing, helix/sheet packing and sheet/sheet packing. It was shown via a number of comparative calculations that the final structures obtained through the annealing process not only had lower energies than the corresponding energy-minimized structures reported previously, but also assumed the forms closer to the observations in proteins. All these results indicate that a better result can be obtained in search of low-energy structures of proteins by incorporating the simulated annealing approach.(ABSTRACT TRUNCATED AT 250 WORDS)     

Interaction of water with DNA single-helix in the a conformation

The interaction energy between water and the DNA single helix in the A conformation is computed at a number of planar cross sections perpendicular to the long axis of the helix and for cylindrical surfaces enclosing the helix. In addition, Monte Carlo simulations are presented for a small cluster of water around regions of energy minima. On the basis of these simulations, the structure of water for the DNA (single helix in the A conformation) is proposed and discussed.     

On the roles of substrate binding and hinge unfolding in conformational changes of adenylate kinase

We characterized the conformational change of adenylate kinase (AK) between open and closed forms by conducting five all-atom molecular-dynamics simulations, each of 100 ns duration. Different initial structures and substrate binding configurations were used to probe the pathways of AK conformational change in explicit solvent, and no bias potential was applied. A complete closed-to-open and a partial open-to-closed transition were observed, demonstrating the direct impact of substrate-mediated interactions on shifting protein conformation. The sampled configurations suggest two possible pathways for connecting the open and closed structures of AK, affirming the prediction made based on available x-ray structures and earlier works of coarse-grained modeling. The trajectories of the all-atom molecular-dynamics simulations revealed the complexity of protein dynamics and the coupling between different domains during conformational change. Calculations of solvent density and density fluctuations surrounding AK did not show prominent variation during the transition between closed and open forms. Finally, we characterized the effects of local unfolding of an important hinge near Pro¹⁷⁷ on the closed-to-open transition of AK and identified a novel mechanism by which hinge unfolding modulates protein conformational change. The local unfolding of Pro¹⁷⁷ hinge induces alternative tertiary contacts that stabilize the closed structure and prevent the opening transition.