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 multiple-minima problem in the conformational analysis of polypeptides. III. An Electrostatically Driven Monte Carlo Method: Tests on enkephalin

The three-dimensional conformation of Met-enkephalin, corresponding to the lowest minimum of the empirical potential energy function ECEPP/2 (empirical conformational energy program for peptides), has been determined using a new algorithm, viz. the Electrostatically Driven Monte Carlo Method. This 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. These features are included in the algorithm that produces a Monte Carlo search in the conformational hyperspace of the polypeptide, using electrostatic predictions and a random sampling technique to locate low-energy conformations. In addition, we have incorporated an alternative mechanism that allows the structure to escape from some conformational regions representing metastable local energy minima and even from regions of the conformational space with great stability. In 33 test calculations on Met-enkephalin, starting from arbitrary or completely random conformations, the structure corresponding to the global energy minimum was found inall the cases analyzed, with a relatively small search of the conformational space. Some of these starting conformations wereright orleft-handed -helices, characterized by good electrostatic interactions involving their backbone peptide dipoles; nevertheless, the procedure was able to convert such locally stable structures to the global-minimum conformation.On leave from the National University of San Luis, Faculty of Sciences and Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Instituto de Matemática Aplicada, San Luis, Ejército de los Andes 950, 5700 San Luis, Argentina.     

Identification of putative unfolding intermediates of the mutant His‐107‐tyr of human carbonic anhydrase II in a multidimensional property space

In this article, we develop an extensive search procedure of the multi‐dimensional folding energy landscape of a protein. Our aim is to identify different classes of structures that have different aggregation propensities and catalytic activity. Following earlier studies by Daggett et al. [Jong, D. D.; Riley, R.: Alonso, D.O.: Dagett, V. J. Mol. Biol. 2002, 319, 229], a series of high temperature all‐atom classical molecular simulation studies has been carried out to derive a multi‐dimensional property space. Dynamical changes in these properties are then monitored by projecting them along a one‐dimensional reaction coordinate, d_mean. We have focused on the application of this method to partition a wide array of conformations of wild type human carbonic anhydrase II (HCA II) and its unstable mutant His‐107‐Tyr along d_mean by sampling a 35‐dimensional property space. The resultant partitioning not only reveals the distribution of conformations corresponding to stable structures of HCA II and its mutant, but also allows the monitoring of several partially unfolded and less stable conformations of the mutant. We have investigated the population of these conformations at different stages of unfolding and collected separate sets of structures that are widely separated in the property space. The dynamical diversity of these sets are examined in terms of the loading of their respective first principal component. The partially unfolded structures thus collected are qualitatively mapped on to the experimentally postulated light molten globule (MGL) and molten globule (MG) intermediates with distinct aggregation propensities and catalytic activities. Proteins 2016; 84:726–743. © 2016 Wiley Periodicals, Inc.     

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.     

A population-based evolutionary search approach to the multiple minima problem in de novo protein structure prediction

Background

Elucidating the native structure of a protein molecule from its sequence of amino acids, a problem known as de novo structure prediction, is a long standing challenge in computational structural biology. Difficulties in silico arise due to the high dimensionality of the protein conformational space and the ruggedness of the associated energy surface. The issue of multiple minima is a particularly troublesome hallmark of energy surfaces probed with current energy functions. In contrast to the true energy surface, these surfaces are weakly-funneled and rich in comparably deep minima populated by non-native structures. For this reason, many algorithms seek to be inclusive and obtain a broad view of the low-energy regions through an ensemble of low-energy (decoy) conformations. Conformational diversity in this ensemble is key to increasing the likelihood that the native structure has been captured.

Methods

We propose an evolutionary search approach to address the multiple-minima problem in decoy sampling for de novo structure prediction. Two population-based evolutionary search algorithms are presented that follow the basic approach of treating conformations as individuals in an evolving population. Coarse graining and molecular fragment replacement are used to efficiently obtain protein-like child conformations from parents. Potential energy is used both to bias parent selection and determine which subset of parents and children will be retained in the evolving population. The effect on the decoy ensemble of sampling minima directly is measured by additionally mapping a conformation to its nearest local minimum before considering it for retainment. The resulting memetic algorithm thus evolves not just a population of conformations but a population of local minima.

Results and conclusions

Results show that both algorithms are effective in terms of sampling conformations in proximity of the known native structure. The additional minimization is shown to be key to enhancing sampling capability and obtaining a diverse ensemble of decoy conformations, circumventing premature convergence to sub-optimal regions in the conformational space, and approaching the native structure with proximity that is comparable to state-of-the-art decoy sampling methods. The results are shown to be robust and valid when using two representative state-of-the-art coarse-grained energy functions.

     

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.     

Stereochemical studies on cyclic peptides: Detailed energy minimization studies on hydrogen bonded all-trans cyclic pentapeptide backbones

Conformational studies have been carried out on hydrogenbonded all-trans cyclic pentapeptide backbone. Application of a combination of grid search and energy minimization on this system has resulted in obtaining 23 minimum energy conformations, which are characterized by unique patterns of hydrogen bonding comprising of β- and γ-turns. A study of the minimum energy conformationsvis-a-vis non-planar deviation of the peptide units reveals that non-planarity is an inherent feature in many cases. A study on conformational clustering of minimum energy conformations shows that the minimum energy conformations fall into 6 distinct conformational families. Preliminary comparison with available X-ray structures of cyclic pentapeptide indicates that only some of the minimum energy conformations have formed crystal structures. The set of minimum energy conformations worked out in the present study can form a consolidated database of prototypes for hydrogen bonded backbone and be useful for modelling cyclic pentapeptides both synthetic and bioactive in nature. This is part XV of the series. Part XIV in this series is Ramakrishnanet al 1987.     

Evolutionary-inspired probabilistic search for enhancing sampling of local minima in the protein energy surface

Background

Despite computational challenges, elucidating conformations that a protein system assumes under physiologic conditions for the purpose of biological activity is a central problem in computational structural biology. While these conformations are associated with low energies in the energy surface that underlies the protein conformational space, few existing conformational search algorithms focus on explicitly sampling low-energy local minima in the protein energy surface.

Methods

This work proposes a novel probabilistic search framework, PLOW, that explicitly samples low-energy local minima in the protein energy surface. The framework combines algorithmic ingredients from evolutionary computation and computational structural biology to effectively explore the subspace of local minima. A greedy local search maps a conformation sampled in conformational space to a nearby local minimum. A perturbation move jumps out of a local minimum to obtain a new starting conformation for the greedy local search. The process repeats in an iterative fashion, resulting in a trajectory-based exploration of the subspace of local minima.

Results and conclusions

The analysis of PLOW's performance shows that, by navigating only the subspace of local minima, PLOW is able to sample conformations near a protein's native structure, either more effectively or as well as state-of-the-art methods that focus on reproducing the native structure for a protein system. Analysis of the actual subspace of local minima shows that PLOW samples this subspace more effectively that a naive sampling approach. Additional theoretical analysis reveals that the perturbation function employed by PLOW is key to its ability to sample a diverse set of low-energy conformations. This analysis also suggests directions for further research and novel applications for the proposed framework.

     

Evaluation of the conformational free energies of loops in proteins

In this paper we discuss the problem of including solvation free energies in evaluating the relative stabilities of loops in proteins. A conformational search based on a gas-phase potential function is used to generate a large number of trial conformations. As has been found previously, the energy minimization step in this process tends to pack charged and polar side chains against the protein surface, resulting in conformations which are unstable in the aqueous phase. Various solvation models can easily identify such structures. In order to provide a more severe test of solvation models, gas phase conformations were generated in which side chains were kept extended so as to maximize their interaction with the solvent. The free energies of these conformations were compared to that calculated for the crystal structure in three loops of the protein E. coli RNase H, with lengths of 7, 8, and 9 residues. Free energies were evaluated with a finite difference Poisson-Boltzmann (FDPB) calculation for electrostatics and a surface area-based term for nonpolar contributions. These were added to a gas-phase potential function. A free energy function based on atomic solvation parameters was also tested. Both functions were quite successful in selecting, based on a free energy criterion, conformations quite close to the crystal structure for two of the three loops. For one loop, which is involved in crystal contacts, conformations that are quite different from the crystal structure were also selected. A method to avoid precision problems associated with using the FDPB method to evaluate conformational free energies in proteins is described. © 1994 John Wiley & Sons, Inc.     

Conformational analysis of the 20-residue membrane-bound portion of melittin by conformational space annealing

The conformational space of the 20-residue membrane-bound portion of melittin has been investigated extensively with the conformational space annealing (CSA) method and the ECEPP/3 (Empirical Conformational Energy Program for Peptides) algorithm. Starting from random conformations, the CSA method finds that there are at least five different classes of conformations, within 4 kcal/mol, which have distinct backbone structures. We find that the lowest energy conformation of this peptide from previous investigations is not the global minimum-energy conformation (GMEC); but it belongs to the second lowest energy class of the five classes found here. In four independent runs, one conformation is found repeatedly as the lowest energy conformation of the peptide (two of the four lowest energy conformations are identical; the other two have essentially identical backbone conformations but slightly different side-chain conformations). We propose this conformation, whose energy is lower than that found previously by 1.9 kcal/mol, as the GMEC of the ECEPP/3 force field. The structure of the proposed GMEC is less helical and more compact than the previous one. It appears that the CSA method can find several classes of conformations of a 20-residue peptide starting from random conformations utilizing only its amino acid sequence information. The proposed GMEC has also been found with a modified electrostatically driven Monte Carlo method [D. R. Ripoll, A. Liwo, and H.A. Scheraga (1998) “New Developments of the Electrostatically Driven Monte Carlo Method: Test on the Membrane-Bound Portion of Melittin,” Biopolymers, Vol. 46, pp. 117–126]. © 1998 John Wiley & Sons, Inc. Biopoly 46: 103–115, 1998     

Conformational energy studies of linear dipeptides H-X-L-Pro-OH

Empirical conformational energy calculations with the use of ECEPP energy functions have been carried out for linear dipeptides H-X-L -Pro-OH, with X = Gly, L -Ala, D -Ala, L -Leu, D -Leu, L -Phe, and D -Phe, in different states of protonation of the end groups. The results of these calculations are compared with the previously reported experimental equilibrium populations for the cis and trans isomers of the X-Pro bond in the different species. For all the protonation states of the seven dipeptides, the calculated nonbonded interactions and the conformational entropy term lead to a preference of the trans forms over the cis isomers by at least 1 kcal/mol. The electrostatic interactions stabilize the cis conformations in all species except the cationic forms of the D ,L -peptides, and it could further be shown that only the carbonyl group of X and the two end groups contribute significantly to the total electrostatic energy. One of the principal results of the experimental studies, i.e., the occurrence of 5–15% cis-proline in all the peptides with an uncharged C-terminus, was corroborated by our investigation of the cationic species. A detailed assessment of the electrostatic contribution to the total energy of the different conformations of H-Gly-L -Pro-OH indicates that the standard ECEPP parameters tend to overestimate the electrostatic interactions in aqueous solutions of the X-Pro dipeptides.     

Conformational energy calculations on glycosylated turns in glycoproteins

Analysis of the amino acid sequence of glycoproteins has suggested the β-turn as a likely site of glycosylation in glycoproteins. According to this model, the peptide chain traverses the interior of a globular protein, reversing its direction at the protein surface, a likely point for the attachment of hydrophilic carbohydrate residues. In order to search for plausible conformations of glycosylated β-turns in asparagine-linked glycoproteins, we have adapted the conformational energy calculation method of Scheraga and coworkers for use in carbohydrates. The parameters for nonbonded and hydrogen-bonded interactions have been published, and electrostatic parameters are derived from a CNDO calculation on a model glycopeptide. Our results indicate that the orientation of the glycosyl amide bond having the amide proton nearly trans to the anomeric proton of the sugar has the lowest energy. Although CD and nmr experiments in our laboratory have consistently found this conformation, our calculations show the conformation having these two protons in a cis relationship to lie very close in energy. Calculations on the glycopeptide linkage model, α-N-acetyl, δ-N(2-acetamido-1,2-dideoxy-β-D -glucopyranosyl)-N′-methyl-L -asparaginyl amide show that several distinct geometries are allowed for glycosylated β-turns. For a type I β-turn, three conformations of the glycosylated side chain are found within 4 kcal of the minimum, while two conformations of the glycosylated side chain are allowed for a type II turn. The hydrogen-bonded C7 conformation is also allowed. Stereoviews of the low-energy conformations reveal no major hydrogen-bonding interaction between the peptide and sugar.     

Different families of double-stranded conformations of DNA as revealed by computer calculations

An algorithm has been developed that permits one to find all possible conformations of the sugar-phosphate backbone for any given disposition of DNA base pairs. For each of the conformations thus obtained, the energy of the helix was calculated by the method of atom-atom potentials. Several isolated regions in the space of the bases′ parameters (Arnott's parameters) have been found for energetically favorable helical structures. Two parameters, the distance of a base pair from the helix axis, D, and the windling angle, τ, allow one to subdivide possible conformations into the families of closely related forms. Two regions (ravines) on the (D, τ) map correspond to the know A and B families. In the B family a continuous transition has been obtained in which the double helix undergoes increasing winding, while the base pairs are moving toward the major (nonglycosidic) groove. Interrelationships between the variables, characterizing the spatial structure of the double helix, D, τ, TL and χ, when going along the bottom of the B ravine, were also obtained. Besides the Known A and B families, several new ones were found to be energetically possible. Among these the strongly underwound helices with the negative D values, as well as the forms with the C4-C5 angle in a trans position, should be mentioned. Biological roles of the different double-stranded conformations, in particular, in protein-nuclei acid interaction are discussed.     

1H, 15N and 13C resonance assignments and secondary structure of group II phospholipase A2 from Agkistrodon piscivorus piscivorus: Presence of an amino-terminal helix in solution

Summary ¹H, ¹⁵N and ¹³C resonance assignments are presented for the group II phospholipase A2 (PLA2) from Agkistrodon piscivorus piscivorus. The secondary structure of the enzyme has been inferred from an analysis of coupling constants, interproton distances, chemical shifts, and kinetics of amide exchange. Overall, the secondary structure of this PLA2 is similar to the crystal structure of the homologous group II human nonpancreatic secretory phospholipase [Scott, D.L., White, S.P., Browning, J.L., Rosa, J.J., Gelb, M.H. and Sigler, P.B. (1991) Science, 254, 1007–1010]. In the group I enzyme from porcine pancreas, the amino-terminal helix becomes fully ordered in the ternary complex of enzyme, lipid micelles and inhibitor. The formation of this helix is thought to be important for the increase in activity of phospholipases on aggregated substrates [Van den Berg, B., Tessari, M., Boelens, R., Dijkman, R., De Haas, G.H., Kaptein, R. and Verheij, H.M. (1995) Nature Struct. Biol., 2, 402–406]. However, the group II enzyme from Agkistrodon piscivorus piscivorus possesses a defined and well-positioned aminoterminal helix in the absence of substrate. Therefore, there is a clear difference between the conformations of group I and group II enzymes in solution. These conformational differences suggest that formation of the amino-terminal helix is a necessary, but not sufficient, step in interfacial activation of phospholipases.Abbreviations PLA2 phospholipase A2 - App-D49 phospholipase from Agkistrodon piscivorus piscivorus - NOE nuclear Overhauser effect     

PROCEDURE FOR SELECTING STARTING CONFORMATIONS FOR ENERGY MINIMIZATION OF NUCLEOSIDES AND NUCLEOTIDES

ABSTRACT

The purpose of this study was to carry out a thorough search of the conformational space of various adenine-containing nucleotides, applying a previously published searching procedure, known as the representative method. This method, which reduces the number of starting conformations required to explore all the important regions of conformational space, appears to be successful in finding all (or nearly all) the putative low-energy conformations of each molecule.     

Peptide Free Energy Landscapes Calibrated by Molecular Orbital Calculations

Free energy landscapes of peptide conformations werecalibrated by ab initiomolecular orbital calculations, after enhancedconformational sampling using the multicanonical molecular dynamicssimulations. Three different potentials of mean force for an isolateddipeptide were individually obtained using the conventional force fields,AMBER parm94, AMBER parm96, and CHARMm22. Each potential ofmean force was calibrated based on the umbrella sampling algorithm fromthe adiabatic energy map that was calculated separately by the abinitiomolecular orbital method. All the calibrated potentials of mean forcecoincided well. The calibration was applied to a peptide in explicit water,and the calibrated free energy landscapes did not depend on the force fieldused in conformational sampling, as far as the conformational space waswell sampled.     

Conformational analysis of an EP24.15 inhibitor by NMR and molecular modelling

Summary The enzyme thimet oligopeptidase (EC3.4.24.15, EP24.15) is responsible for the hydrolysis of a number of neuropeptides. Despite much research examining its substrate specificity, little is known about the conformational requirements of its active site. We have used 1D¹H and 2D TOCSY NMR experiments to assign the proton resonances of the EP24.15 inhibitor,N-[1-(R, S)-carboxy-3-phenylpropyl]-Ala-Ala-Tyr-p-aminobenzoate (cFP), and 2D ROESY NMR to investigate whether cFP exhibits any conformational preferences in CD₃OD and in aqueous CD₃OD. Molecular modelling of charged cFP in the gaseous phase generated a number of conformations that were consistent with the NMR data obtained in CD₃OD. Analogous modelling on the uncharged cFP did not result in conformations consistent with any of the NMR data, but did suggest that, under non-polar conditions, cFP could adopt a hairpin conformation which would allow simultaneous coordination of the two carboxyl groups of cFP to the zinc ion in the active site of EP24.15.     

Fast de novo discovery of low‐energy protein loop conformations

In the prediction of protein structure from amino acid sequence, loops are challenging regions for computational methods. Since loops are often located on the protein surface, they can have significant roles in determining protein functions and binding properties. Loop prediction without the aid of a structural template requires extensive conformational sampling and energy minimization, which are computationally difficult. In this article we present a new de novo loop sampling method, the Parallely filtered Energy Targeted All‐atom Loop Sampler (PETALS) to rapidly locate low energy conformations. PETALS explores both backbone and side‐chain positions of the loop region simultaneously according to the energy function selected by the user, and constructs a nonredundant ensemble of low energy loop conformations using filtering criteria. The method is illustrated with the DFIRE potential and DiSGro energy function for loops, and shown to be highly effective at discovering conformations with near‐native (or better) energy. Using the same energy function as the DiSGro algorithm, PETALS samples conformations with both lower RMSDs and lower energies. PETALS is also useful for assessing the accuracy of different energy functions. PETALS runs rapidly, requiring an average time cost of 10 minutes for a length 12 loop on a single 3.2 GHz processor core, comparable to the fastest existing de novo methods for generating an ensemble of conformations. Proteins 2017; 85:1402–1412. © 2017 Wiley Periodicals, Inc.     

Reversible scaling of dihedral angle barriers during molecular dynamics to improve structure prediction of cyclic peptides.

Peptide cyclization or chemical cross-linking has frequently been used to restrict the conformational freedom of a peptide, for example, to enhance its capacity for selective binding to a target receptor molecule. Structure prediction of cyclic peptides is important to evaluate possible conformations prior to synthesis. Because of the conformational constraints imposed by cyclization low energy conformations of cyclic peptides can be separated by large energy barriers. In order to improve the conformational search properties of molecular dynamics (MD) simulations a potential scaling method has been designed. The approach consists of several consecutive MD simulations with a specific lowering of dihedral energy barriers and reduced nonbonded interactions between atoms separated by three atoms followed by gradually scaling the potential until the original barriers are reached. Application to four cyclic penta- and hexa-peptide test cases and a protein loop of known structure indicates that the potential scaling method is more efficient and faster in locating low energy conformations than standard MD simulations. Combined with a generalized Born implicit solvation model the low energy cyclic peptide conformations and the loop structure are in good agreement with experiment. Applications in the presence of explicit water molecules during the simulations showed also improved convergence to structures close to experiment compared with regular MD.     

Targeted Molecular Dynamics Simulation of Conformational Change-Application to the T ↔ R Transition in Insulin

Abstract

A novel method to calculate transition pathways between two known protein conformations is presented. It is based on a molecular dynamics simulation starting from one conformational state as initial structure and using the other for a directing constraint. The method is exemplified with the T ? R transition of insulin. The most striking difference between these conformational states is that in T the 8 N-terminal residues of the B chain are arranged as an extended strand whereas in R they are forming a helix. Both the transition from T to R and from R to T were simulated. The method proves capable of finding a continuous pathway for each direction which are moderately different. The refolding processes are illustrated by a series of transient structures and pairs of Ø, ψ angles selected from the time course of the simulations. In the T → R direction the helix is formed in the →last third of the transition, while in the R → T direction it is preserved during more than half of the simulation period. The results are discussed in comparison with those of an atternative method recently apptied to the T → R transition of insulin which is based on targeted energy minimisation.