[SMMP] A modern package for simulation of proteins

Eisenmenger, Frank; Hansmann, Ulrich H. E.; Hayryan, Shura; Hu, Chin Kun

doi:10.1016/s0010-4655(01)00197-7

Cited by 118 publications

(109 citation statements)

References 59 publications

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“…The interaction between the atoms is described by a standard force field, ECEPP/2, [16] (as implemented in the program package SMMP [17]) and is given by:…”

Section: Methodsmentioning

confidence: 99%

Helix formation and folding in an artificial peptide

Alves

Hansmann

2002

The Journal of Chemical Physics

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We study the relation between α-helix formation and folding for a simple artificial peptide, Ala10-Gly5-Ala10. Our data rely on multicanonical Monte Carlo simulations where the interactions among all atoms are taken into account. The free-energy landscape of the peptide is evaluated for various temperatures. Our data indicate that folding of this peptide is a two-step process: in a first step two α-helices are formed which afterwards re-arrange themselves into a U-like structure.

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“…The interaction between the atoms is described by a standard force field, ECEPP/2, [16] (as implemented in the program package SMMP [17]) and is given by:…”

Section: Methodsmentioning

confidence: 99%

Helix formation and folding in an artificial peptide

Alves

Hansmann

2002

The Journal of Chemical Physics

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Section: Introductionmentioning

confidence: 99%

“…With its well-defined secondary and tertiary structure [10] it is sufficiently complex and with 596 atoms large enough that numerical simulations become indeed a challenge [11]. Using the computer program SMMP [12] we simulate eight copies of HP-36 at temperature T = 300 K, with energies given by:E tot (i) = a i E LJ + E C + E HB + E Tors + E Solv = a i E LJ + E other .Here, the interactions between the atoms of the HP-36 molecule are described by the ECEPP/ 2 force field [13] given by the sum of an electrostatic term E C , the Lennard-Jones energy E LJ , hydrogen-bond term E HB and torsion energy E tor . The protein-water interactions are approximated by E Solv = ∑ i σ i A i .…”

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confidence: 99%

Efficient Sampling of Protein Structures by Model Hopping

Kwak

Hansmann

2005

Phys. Rev. Lett.

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We introduce a novel simulation method, model hopping, that enhances sampling of low-energy configurations in complex systems. The approach is illustrated for a protein folding problem. Thermodynamic quantities of proteins with up to 46 residues are evaluated from all-atom simulations with this method.The solution of many pharmacological and medical problems, such as rational drug design or the pathology of diseases associated with the mis-folding of proteins, requires a detailed understanding of the relation between chemical composition and structure of proteins. However, despite more than two decades of research, this so-called protein-folding problem has remained a hard computational task. This is because proteins in an all-atom representation are characterized by a rough energy landscape with a huge number of local minima separated by high energy barriers. Various numerical techniques exist that can alleviate this multiple minima problem. One popular example is parallel tempering (also known as replica exchange method) [1], a technique that was first introduced to protein studies in Ref. [2]. In its most common form, one considers an artificial system built up of N non-interacting copies of a molecule, each at a different temperature T i . In addition to standard Monte Carlo or molecular dynamics moves that affect only one copy, parallel tempering allows also the exchange of conformations between two copies i and j = i + 1 with probability w(C old → C new ) = min(1, exp(ΔβΔE)). The resulting random walk in temperature enables configurations to cross energy barriers and move out of local minima leading in this way to an enhanced sampling of lowenergy structures. Variants of parallel tempering introducing non-canonical weights have been proposed [2,3].Here, we introduce another variant of this idea, dubbed by us "model hopping" (MH), where as in the Hamilton Exchange method [4] or the Multi-Self-Overlap-Ensemble [5] the random walk in temperatures is replaced by one through an ensemble of models with slightly altered energy functions. For this we assume that the energy function can be separated in two terms: E = E A + aE B . As in parallel tempering, MH considers N non-interacting copies of the molecule, but copies are now exchanged according toHere, Δa = a j − a i and ΔE B = E B (C j ) − E B (C i ). Due to this exchange move configurations perform a random walk on a ladder of models with a 1 = 1 > a 2 > a 3 > …. > a N that differ by the relative contributions of E B to the total energy E of the molecule. For instance, barriers in the energy landscape of proteins often arise from van der Waals repulsion between atoms that come too close. Generalized-ensemble techniques circumvent the problem by performing a random walk in energy that allows crossing of these barriers. On the other hand, in MH the protein walks randomly up and down on a ladder of models with successively smaller contributions from the van der Waals energy. While the "physical" system is on one side of the ladder (at a 1 = 1), the (non-p...

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“…Peptides with 20 amino acids have been successfully studied with this potential energy function and program package [15,16]. There are also other folding and optimization packages based on Monte Carlo techniques with open codes like SMMP [17], GROMACS [18], and FANTOM [19]. SMMP code contains various generalized ensemble algorithms and performs calculations on the basis of ECEPP force field with different atomic solvation parameter sets for implicit solvent approximation.…”

Section: Methodsmentioning

confidence: 99%

Secondary structure prediction of beta-hairpin peptide tryptophan zipper-I

Gökoğlu

Çelik

2008

Physica A: Statistical Mechanics and its Applications

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We have investigated the folding properties of tryptophan zipper-I molecule which folds into a stable β-hairpin motif in aqueous solution as suggested by nuclear magnetic resonance (NMR) experiments. An all-atom presentation, including hydrogen, was used with an implicit solvent. As a simulation technique, simulated tempering algorithm was used to obtain equilibrium conformations of the molecule at ten distinct temperatures. Our minimum energy configuration obtained from simulated tempering algorithm is a β-hairpin motif with 1.30Å backbone root-mean-square deviation from the reference PDB structure (1le0.pdb). Several quantities and exhaustive folding free energy landscapes were determined and discussed in order to clarify the folding behavior.

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[SMMP] A modern package for simulation of proteins

Cited by 118 publications

References 59 publications

Helix formation and folding in an artificial peptide

Helix formation and folding in an artificial peptide

Efficient Sampling of Protein Structures by Model Hopping

Secondary structure prediction of beta-hairpin peptide tryptophan zipper-I

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