Analytical approximation to the accessible surface area of proteins

Q-Dock: Low-resolution flexible ligand docking with pocket-specific threading restraints

The rapidly growing number of theoretically predicted protein structures requires robust methods that can utilize low-quality receptor structures as targets for ligand docking. Typically, docking accuracy falls off dramatically when apo or modeled receptors are used in docking experiments. Low-resolution ligand docking techniques have been developed to deal with structural inaccuracies in predicted receptor models. In this spirit, we describe the development and optimization of a knowledge-based potential implemented in Q-Dock, a low-resolution flexible ligand docking approach. Self-docking experiments using crystal structures reveals satisfactory accuracy, comparable with all-atom docking. All-atom models reconstructed from Q-Dock's low-resolution models can be further refined by even a simple all-atom energy minimization. In decoy-docking against distorted receptor models with a root-mean-square deviation, RMSD, from native of approximately 3 A, Q-Dock recovers on average 15-20% more specific contacts and 25-35% more binding residues than all-atom methods. To further improve docking accuracy against low-quality protein models, we propose a pocket-specific protein-ligand interaction potential derived from weakly homologous threading holo-templates. The success rate of Q-Dock employing a pocket-specific potential is 6.3 times higher than that previously reported for the Dolores method, another low-resolution docking approach.

Parallel, stochastic measurement of molecular surface area

Biochemists often wish to compute surface areas of proteins. A variety of algorithms have been developed for this task, but they are designed for traditional single-processor architectures. The current trend in computer hardware is towards increasingly parallel architectures for which these algorithms are not well suited. We describe a parallel, stochastic algorithm for molecular surface area computation that maps well to the emerging multi-core architectures. Our algorithm is also progressive, providing a rough estimate of surface area immediately and refining this estimate as time goes on. Furthermore, the algorithm generates points on the molecular surface which can be used for point-based rendering. We demonstrate a GPU implementation of our algorithm and show that it compares favorably with several existing molecular surface computation programs, giving fast estimates of the molecular surface area with good accuracy.

Consistent free energy landscapes and thermodynamic properties of small proteins based on a single all-atom force field employing an implicit solvation

We have attempted to improve the PARAM99 force field in conjunction with the generalized Born (GB) solvation model with a surface area correction for more consistent protein folding simulations. For this purpose, using an extended alphabeta training set of five well-studied molecules with various folds (alpha, beta, and betabetaalpha), a previously modified version of PARAM99/GBSA is further refined, such that all native states of the five training species correspond to their lowest free energy minimum states. The resulting modified force field (PARAM99MOD5/GBSA) clearly produces reasonably acceptable conformational free energy surfaces of the training set with correct identifications of their native states in the free energy minimum states. Moreover, due to its well-balanced nature, this new force field is expected to describe secondary structure propensities of diverse folds in a more consistent manner. Remarkably, temperature dependent behaviors simulated with the current force field are in good agreement with the experiment. This agreement is a significant improvement over the existing standard all-atom force fields. In addition, fundamentally important thermodynamic quantities, such as folding enthalpy (DeltaH) and entropy (DeltaS), agree reasonably well with the experimental data.

Protein-protein interaction: an analysis by computer simulation

A survey of protein-protein interactions in structures derived by X-ray crystallography of protease-inhibitor and antigen-antibody complexes shows that they form close-packed interfaces from which water is excluded. The interfaces are of almost constant size, and they contain about ten hydrogen bonds. These features account for the stability of the complexes. To test whether they also account for specificity, we designed a computer simulation that searches for complementary surfaces on two protein molecules. In all cases tested, the simulation finds a number of complexes having interfaces and hydrogen bonds equivalent to those of the native complexes. These artificial complexes might represent secondary specificities, which can be detected when normal association is prevented by mutation or other means.

Joint neighbors approximation of macromolecular solvent accessible surface area

A new method for approximate analytical calculations of solvent accessible surface area (SASA) for arbitrary molecules and their gradients with respect to their atomic coordinates was developed. This method is based on the recursive procedure of pairwise joining of neighboring atoms. Unlike other available methods of approximate SASA calculations, the method has no empirical parameters, and therefore can be used with comparable accuracy in calculations of SASA in folded and unfolded conformations of macromolecules of any chemical nature. As shown by tests with globular proteins in folded conformations, average errors in absolute atomic surface area is around 1 A2, while for unfolded protein conformations it varies from 1.65 to 1.87 A2. Computational times of the method are comparable with those by GETAREA, one of the fastest exact analytical methods available today.

Identification of sperm antigens as a first step towards the generation of a contraceptive vaccine to decrease fossorial water vole Arvicola terrestris Scherman proliferations

Immunocontraceptive strategies have proved to be efficient in controlling fertility of various mammalian species. In the present study we have made the first steps towards the identification of Arvicola terrestris sperm antigens that could be used as targets in the development of a contraceptive vaccine to limit the proliferations of this pest rodent. Rabbit-raised polyclonal antisera directed against complete A. terrestris spermatozoa were used to identify and characterize on 2D-gels coupled with a MALDI-TOF mass spectrometry analysis A. terrestris sperm proteins. Amongst the proteins pinpointed by this approach some were further investigated based on their tissue- and/or sperm-specific expression, and their relevance to fertility or sperm/egg interaction. In parallel, three proteins that have been already reported in the literature to be appropriate targets for the development of contraceptive vaccines in other mammalian species have also been looked for in A. terrestris. With the selected protein targets, a reverse-PCR approach using degenerate primers was employed to amplify corresponding A. terrestris cDNAs. After conceptual translation and sequence alignment, different proteins were studied to determine zones with sufficient sequence divergence and of antigenic/immunogenic nature that could be used in future assays to immunize animals.

OPUS-Ca: a knowledge-based potential function requiring only Calpha positions

In this paper, we report a knowledge-based potential function, named the OPUS-Ca potential, that requires only Calpha positions as input. The contributions from other atomic positions were established from pseudo-positions artificially built from a Calpha trace for auxiliary purposes. The potential function is formed based on seven major representative molecular interactions in proteins: distance-dependent pairwise energy with orientational preference, hydrogen bonding energy, short-range energy, packing energy, tri-peptide packing energy, three-body energy, and solvation energy. From the testing of decoy recognition on a number of commonly used decoy sets, it is shown that the new potential function outperforms all known Calpha-based potentials and most other coarse-grained ones that require more information than Calpha positions. We hope that this potential function adds a new tool for protein structural modeling.

Implicit solvent models

Implicit solvent models for biomolecular simulations are reviewed and their underlying statistical mechanical basis is discussed. The fundamental quantity that implicit models seek to approximate is the solute potential of mean force, which determines the statistical weight of solute conformations, and which is obtained by averaging over the solvent degrees of freedom. It is possible to express the total free energy as the reversible work performed in two successive steps. First, the solute is inserted in the solvent with zero atomic partial charges; second, the atomic partial charges of the solute are switched from zero to their full values. Consequently, the total solvation free energy corresponds to a sum of non-polar and electrostatic contributions. These two contributions are often approximated by simple geometrical models (such as solvent exposed area models) and by macroscopic continuum electrostatics, respectively. One powerful route is to approximate the average solvent density distribution around the solute, i.e. the solute-solvent density correlation functions, as in statistical mechanical integral equations. Recent progress with semi-analytical approximations makes continuum electrostatics treatments very efficient. Still more efficient are fully empirical, knowledge-based models, whose relation to explicit solvent treatments is not fully resolved, however. Continuum models that treat both solute and solvent as dielectric continua are also discussed, and the relation between the solute fluctuations and its macroscopic dielectric constant(s) clarified.

Statistical potential for assessment and prediction of protein structures

Protein structures in the Protein Data Bank provide a wealth of data about the interactions that determine the native states of proteins. Using the probability theory, we derive an atomic distance-dependent statistical potential from a sample of native structures that does not depend on any adjustable parameters (Discrete Optimized Protein Energy, or DOPE). DOPE is based on an improved reference state that corresponds to noninteracting atoms in a homogeneous sphere with the radius dependent on a sample native structure; it thus accounts for the finite and spherical shape of the native structures. The DOPE potential was extracted from a nonredundant set of 1472 crystallographic structures. We tested DOPE and five other scoring functions by the detection of the native state among six multiple target decoy sets, the correlation between the score and model error, and the identification of the most accurate non-native structure in the decoy set. For all decoy sets, DOPE is the best performing function in terms of all criteria, except for a tie in one criterion for one decoy set. To facilitate its use in various applications, such as model assessment, loop modeling, and fitting into cryo-electron microscopy mass density maps combined with comparative protein structure modeling, DOPE was incorporated into the modeling package MODELLER-8.

Fast accurate evaluation of protein solvent exposure

Protein solvation energies are often taken to be proportional to solvent-accessible surface areas. Computation of these areas is numerically demanding and may become a bottleneck for folding and design applications. Fast graph-based methods, such as dead-end elimination (DEE), become possible if all energies, including solvation energies, are expressed as single-residue and pair-residue terms. To this end, Street and Mayo originated a pair-residue approximation for solvent-accessible surface areas (Street AG, Mayo SL. Pairwise calculation of protein solvent accessible surface areas. Fold Des 1998;3:253-258). The dominant source of error in this method is the overlapping burial of side-chain surfaces in the protein core. Here we report a new pair-residue approximation, which greatly reduces this overlap error by the use of optimized generic side-chains. We have tested the generic-side-chain method for the ten proteins studied by Street and Mayo and for 377 single-domain proteins from the CATH database (Orengo CA, Michie AD, Jones S, Jones DT, Swindells MB, Thornton JM. CATH-A hierarchic classification of protein domain structures. Structure 1997;5:1093-1108). With little additional cost in computation, the new method consistently reduces error for total areas and residue-by-residue areas by more than a factor of two. For example, the residue-by-residue error (for buried area) is reduced from 7.42 A(2) to 3.70 A(2). This difference translates into a solvation energy difference of approximately 0.2 kcal/mol per residue, amounting to a reduction in root-mean-square energy error of 2 kcal/mol for a 100 residue chain, a potentially critical difference for both protein folding and design applications.

POPSCOMP: an automated interaction analysis of biomolecular complexes

Large-scale analysis of biomolecular complexes reveals the functional network within the cell. Computational methods are required to extract the essential information from the available data. The POPSCOMP server is designed to calculate the interaction surface between all components of a given complex structure consisting of proteins, DNA or RNA molecules. The server returns matrices and graphs of surface area burial that can be used to automatically annotate components and residues that are involved in complex formation, to pinpoint conformational changes and to estimate molecular interaction energies. The analysis can be performed on a per-atom level or alternatively on a per-residue level for low-resolution structures. Here, we present an analysis of ribosomal structures in complex with various antibiotics to exemplify the potential and limitations of automated complex analysis. The POPSCOMP server is accessible at .

Evaluation of local structure alphabets based on residue burial

Residue burial, which describes a protein residue's exposure to solvent and neighboring atoms, is key to protein structure prediction, modeling, and analysis. We assessed 21 alphabets representing residue burial, according to their predictability from amino acid sequence, conservation in structural alignments, and utility in one fold-recognition scenario. This follows upon our previous work in assessing nine representations of backbone geometry.1 The alphabet found to be most effective overall has seven states and is based on a count of C(beta) atoms within a 14 A-radius sphere centered at the C(beta) of a residue of interest. When incorporated into a hidden Markov model (HMM), this alphabet gave us a 38% performance boost in fold recognition and 23% in alignment quality.

Efficient approximate all-atom solvent accessible surface area method parameterized for folded and denatured protein conformations

Continuing advances in computer hardware and software are permitting atomic-resolution molecular simulations for longer time scales and on larger systems. Despite these advances, routinely performing atomistic simulations with explicit water for even small proteins, which reach the folding time of such proteins, remains intractable for the foreseeable future. An implicit approximation of the solvent environment using a solvent accessible surface area (SASA) term in a molecular mechanics potential function allows exclusion of the explicit water molecules in protein simulations. This reduces the number of particles by approximately an order of magnitude. We present a fast and acceptably accurate approximate all-atom SASA method parameterized using a set of folded and heat-denatured conformations of globular proteins. The parameters are shown to be transferable to folded and heat-denatured conformations for another set of proteins. Calculation of the approximate SASA and the associated derivatives with respect to atomic positions for a 4644 atom protein requires only 1/11th the CPU time required for calculation of the nonbonded interactions for this system. On a per atom basis, this algorithm is three times faster than the fastest previously published approximate SASA method and achieves the same level of accuracy.

Energy functions for protein design I: efficient and accurate continuum electrostatics and solvation

Electrostatics and solvation energies are important for defining protein stability, structural specificity, and molecular recognition. Because these energies are difficult to compute quickly and accurately, they are often ignored or modeled very crudely in computational protein design. To address this problem, we have developed a simple, fast, and accurate approximation for calculating Born radii in the context of protein design calculations. When these approximate Born radii are used with the generalized Born continuum dielectric model, energies calculated by the 10(6)-fold slower finite difference Poisson-Boltzmann model are faithfully reproduced. A similar approach can be used for estimating solvent-accessible surface areas (SASAs). As an independent test, we show that these approximations can be used to accurately predict the experimentally determined pK(a)s of >200 ionizable groups from 15 proteins.

New analytic approximation to the standard molecular volume definition and its application to generalized Born calculations

In a recent article (Lee, M. S.; Salsbury, F. R. Jr.; Brooks, C. L., III. J Chem Phys 2002, 116, 10606), we demonstrated that generalized Born (GB) theory provides a good approximation to Poisson electrostatic solvation energy calculations if one uses the same definitions of molecular volume for each. In this work, we present a new and improved analytic method for reproducing the Lee-Richards molecular volume, which is the most common volume definition for Poisson calculations. Overall, 1% errors are achieved for absolute solvation energies of a large set of proteins and relative solvation energies of protein conformations. We also introduce an accurate SASA approximation that uses the same machinery employed by our GB method and requires a small addition of computational cost. The combined methodology is shown to yield an efficient and accurate implicit solvent representation for simulations of biopolymers.

POPS: A fast algorithm for solvent accessible surface areas at atomic and residue level

POPS (Parameter OPtimsed Surfaces) is a new method to calculate solvent accessible surface areas, which is based on an empirically parameterisable analytical formula and fast to compute. Atomic and residue areas (the latter represented by a single sphere centered on the C(alpha) atom of amino acids and at the P atom of nucleotides) have been optimised versus accurate all-atom methods. The parameterisation has been derived from a selected dataset of proteins and nucleic acids of different sizes and topologies. The residue based approach POPS-R, has been devised as a useful tool for the analysis of large macromolecular assemblies like the ribosome and it is specially suited for the refinement of low resolution structures. POPS-R also allows for estimates of the loss of free energy of solvation upon complex formation, which should be particularly useful for the design of new protein-protein and protein-nucleic acid complexes. The program POPS is available at http://mathbio.nimr.mrc.ac.uk/~ffranca/POPS and at the mirror site http://www.cs.vu.nl/~ibivu/programs/popswww.

Parameter optimized surfaces (POPS): analysis of key interactions and conformational changes in the ribosome

We present a new method for the calculation of solvent accessible surface areas at the atomic and residue levels, which we call parameter optimized surfaces (POPS-A and POPS-R ). Atomic and residue areas (the latter simulated with a single sphere centered at the C(alpha)s atom for amino acids and at the P atom for nucleotides) have been optimized versus accurate all-atoms methods. We concentrated on an analytical formula for the approximation of solvent accessibilities. The formula is simple, easily derivable and fast to compute, therefore it is practical for use in molecular dynamics simulations as an approximation to the first solvation shell. The residue based approach POPS-R has been derived as a useful tool for the analysis of large macromolecular assemblies like the ribosome, and is especially suited for use in refinement of low resolution structures. The structures of the 70S, 50S and 30S ribosomes have been analyzed in detail and most of the interactions within the subunits and at their interfaces were clearly identified. Some interesting differences between 30S alone and within the 70S have been highlighted. Owing to the presence of the P-tRNA in the 70S ribosome, localized conformational rearrangements occur within the subunits, exposing Arg and Lys residues to negatively charged binding sites of P-tRNA. POPS-R also allows for estimates of the loss of free energy of solvation upon complex formation, particularly useful in designing new protein-RNA complexes and in suggesting more focused experimental work.

A fast pairwise evaluation of molecular surface area

A fast and general analytical approach was developed for the calculation of the approximate van der Waals and solvent-accessible surface areas. The method is based on three basic ideas: the use of the Lorentz transformation formula, a rigid-geometry approximation, and a single fitting parameter that can be refitted on the fly during a simulation. The Lorentz transformation equation is used for the summation of the areas of an atom buried by its neighboring contacting atoms, and implies that a sum of the buried pairwise areas cannot be larger than the surface area of the isolated spherical atom itself. In a rigid-geometry approximation we numerically calculate and keep constant the surface of each atom buried by the atoms involved in 1-2 and 1-3 interactions. Only the contributions from the nonbonded atoms (1-4 and higher interactions) are considered in terms of the pairwise approximation. The accuracy and speed of the method is competitive with other pairwise algorithms. A major strength of the method is the ease of parametrization.

Application of the frozen atom approximation to the GB/SA continuum model for solvation free energy

The generalized Born/surface area (GB/SA) continuum model for solvation free energy is a fast and accurate alternative to using discrete water molecules in molecular simulations of solvated systems. However, computational studies of large solvated molecular systems such as enzyme-ligand complexes can still be computationally expensive even with continuum solvation methods simply because of the large number of atoms in the solute molecules. Because in such systems often only a relatively small portion of the system such as the ligand binding site is under study, it becomes less attractive to calculate energies and derivatives for all atoms in the system. To curtail computation while still maintaining high energetic accuracy, atoms distant from the site of interest are often frozen; that is, their coordinates are made invariant. Such frozen atoms do not require energetic and derivative updates during the course of a simulation. Herein we describe methodology and results for applying the frozen atom approach to both the generalized Born (GB) and the solvent accessible surface area (SASA) parts of the GB/SA continuum model for solvation free energy. For strictly pairwise energetic terms, such as the Coulombic and van-der-Waals energies, contributions from pairs of frozen atoms can be ignored. This leaves energetic differences unaffected for conformations that vary only in the positions of nonfrozen atoms. Due to the nonlocal nature of the GB analytical form, however, excluding such pairs from a GB calculation leads to unacceptable inaccuracies. To apply a frozen-atom scheme to GB calculations, a buffer region within the frozen-atom zone is generated based on a user-definable cutoff distance from the nonfrozen atoms. Certain pairwise interactions between frozen atoms in the buffer region are retained in the GB computation. This allows high accuracy in conformational GB comparisons to be maintained while achieving significant savings in computational time compared to the full (nonfrozen) calculation. A similar approach for using a buffer region of frozen atoms is taken for the SASA calculation. The SASA calculation is local in nature, and thus exact SASA energies are maintained. With a buffer region of 8 A for the frozen-atom cases, excellent agreement in differences in energies for three different conformations of cytochrome P450 with a bound camphor ligand are obtained with respect to the nonfrozen cases. For various minimization protocols, simulations run 2 to 10.5 times faster and memory usage is reduced by a factor of 1.5 to 5. Application of the frozen atom method for GB/SA calculations thus can render computationally tractable biologically and medically important simulations such as those used to study ligand-receptor binding conformations and energies in a solvated environment.

Exploratory studies of ab initio protein structure prediction: multiple copy simulated annealing, AMBER energy functions, and a generalized born/solvent accessibility solvation model

A theoretical and computational approach to ab initio structure prediction for polypeptides in water is described and applied to selected amino acid sequences for testing and preliminary validation. The method builds systematically on the extensive efforts applied to parameterization of molecular dynamics (MD) force fields, employs an empirically well-validated continuum dielectric model for solvation, and an eminently parallelizable approach to conformational search. The effective free energy of polypeptide chains is estimated from AMBER united atom potential functions, with internal degrees of freedom for both backbone and amino acid side chains explicitly treated. The hydration free energy of each structure is determined using the Generalized Born/Solvent Accessibility (GBSA) method, modified and reparameterized to include atom types consistent with the AMBER force field. The conformational search procedure employs a multiple copy, Monte Carlo simulated annealing (MCSA) protocol in full torsion angle space, applied iteratively on sets of structures of progressively lower free energy until a prediction of a structure with lowest effective free energy is obtained. Calibration tests for the effective energy function and search algorithm are performed on the alanine dipeptide, selected protein crystal structures, and united atom decoys on barnase, crambin, and six examples from the Rosetta set. Specific demonstration cases of the method are provided for the 8-mer sequence of Ala residues, a 12-residue peptide with longer side chains QLLKKLLQQLKQ, a de novo designed 16 residue peptide of sequence (AAQAA)3Y, a 15-residue sequence with a beta sheet motif, GEWTWDATKTFTVTE, and a 36 residue small protein, Villin headpiece. The Ala 8-mer readily formed an alpha-helix. An alpha-helix structure was predicted for the 16-mer, consistent with observed results from IR and CD spectroscopy and with the pattern in psi/straight phi angles of known protein structures. The predicted structure for the 12-mer, composed of a mix of helix and less regular elements of secondary structure, lies 2.65 A RMS from the observed crystal structure. Structure prediction for the 8-mer beta-motif resulted in form 4.50 A RMS from the crystal geometry. For Villin, the predicted native form is very close to the crystal structure, RMS values of 3.5 A (including sidechains), and 1.01 A (main chain only). The methodology permits a detailed analysis of the molecular forces which dominate various segments of the predicted folding trajectory. Analysis of the results in terms of internal torsional, electrostatic and van der Waals and the electrostatic and non-electrostatic contributions to hydration, including the hydrophobic effect, is presented.

Use of surface area computations to describe atom-atom interactions

Accessible surface (ASA) and atomic contact (ACA) areas are powerful tools for protein structure analysis. However, their use for analysis purposes could be extended if a relationship between them and protein stability could be found. At present, this is the case only for ASAs, which have been used to assess the contribution of the hydrophobic effect to protein stability. In the present work we study whether there is a relationship between atomic contact areas and the free energy associated to atom-atom interactions. We utilise a model in which the contribution of atomic interactions to protein stability is expressed as a linear function of the accessible surface area buried between atom pairs. We assess the validity of this hypothesis, using a set of 124 lysozyme mutants (Matthews, 1995, Adv Protein Chem, 249-278) for which both the X-ray structure and the experimental stability are known. We tested this assumption for residue representations with increasing numbers of atom types. Our results indicate that for simple residue representations, with only 4 to 5 atom types, there is not a clear linear relationship between stability and buried accessible area. However, this relationship is observed for representations with 6 to 9 atom types, where gross heterogeneities in the atom type definition are eliminated. Finally, we also study a version of the linear model in which the atom- atom interactions are represented utilising a simple function for the buried accessible area, which may be useful for protein structure prediction studies.

Review: protein design--where we were, where we are, where we're going

Protein design has become a powerful approach for understanding the relationship between amino acid sequence and 3-dimensional structure. In the past 5 years, there have been many breakthroughs in the development of computational methods that allow the selection of novel sequences given the structure of a protein backbone. Successful design of protein scaffolds has now paved the way for new endeavors to design function. The ability to design sequences compatible with a fold may also be useful in structural and functional genomics by expanding the range of proteins used for fold recognition and for the identification of functionally important domains from multiple sequence alignments.

Identification and ab initio simulations of early folding units in proteins

The location of protein subunits that form early during folding, constituted of consecutive secondary structure elements with some intrinsic stability and favorable tertiary interactions, is predicted using a combination of threading algorithms and local structure prediction methods. Two folding units are selected among the candidates identified in a database of known protein structures: the fragment 15-55 of 434 cro, an all-alpha protein, and the fragment 1-35 of ubiquitin, an alpha/beta protein. These units are further analyzed by means of Monte Carlo simulated annealing using several database-derived potentials describing different types of interactions. Our results suggest that the local interactions along the chain dominate in the first folding steps of both fragments, and that the formation of some of the secondary structures necessarily occurs before structure compaction. These findings led us to define a prediction protocol, which is efficient to improve the accuracy of the predicted structures. It involves a first simulation with a local interaction potential only, whose final conformation is used as a starting structure of a second simulation that uses a combination of local interaction and distance potentials. The root mean square deviations between the coordinates of predicted and native structures are as low as 2-4 A in most trials. The possibility of extending this protocol to the prediction of full proteins is discussed. Proteins 2001;42:164-176.

A widely applicable set of descriptors

Three sets of molecular descriptors computable from connection table information are defined. These descriptors are based on atomic contributions to van der Waals surface area, log P (octanol/water), molar refractivity, and partial charge. The descriptors are applied to the construction of QSAR/QSPR models for boiling point, vapor pressure, free energy of solvation in water, solubility in water, thrombin/trypsin/factor Xa activity, blood-brain barrier permeability, and compound classification. The wide applicability of these descriptors suggests uses in QSAR/QSPR, combinatorial library design, and molecular diversity work.

Molecular dynamics simulations of beta-hairpin folding

Molecular dynamics simulations of beta-hairpin folding have been carried out with a solvent-referenced potential at 274 K. The model peptide V4DPGV4 formed stable beta-hairpin conformations and the beta-hairpin ratio calculated by the DSSP algorithm was about 56% in the 50-ns simulation. Folding into beta-hairpin conformations is independent of the initial conformations. The simulations provided insights into the folding mechanism. The hydrogen bond often formed in a beta-turn first, and then propagated by forming more hydrogen bonds along the strands. Unfolding and refolding occurred repeatedly during the simulations. Both the hydrogen bonding and the hydrophobic interaction played important roles in forming the ordered structure. Without the hydrophobic effect, stable beta-hairpin conformations did not form in the simulations. With the same energy functions, the alanine-based peptide (AAQAA)3Y folded into helical conformations, in agreement with experiments. Folding into an alpha-helix or a beta-hairpin is amino acid sequence-dependent.

Approximate solvent-accessible surface areas from tetrahedrally directed neighbor densities

A fast analytical formula (TDND) has been derived for the calculation of approximate atomic and molecular solvent-accessible surface areas (SASA), as well as the first and second derivatives of these quantities with respect to atomic coordinates. Extending the work of Stouten et al. (Molecular Simulation, 1993, Vol. 10, pp. 97-120), as well as our own (Journal of Computational Chemistry, 1999, Vol. 20, pp. 586-596), the method makes use of a Gaussian function to calculate the neighbor density in four tetrahedral directions in three-dimensional space, sometimes twice with different orientations. SASA and first derivatives of the 2366 heavy atoms of penicillopepsin are computed in 0.13 s on an SGI R10000/194 MHz processor. When second derivatives are computed as well, the total time is 0.23 s. This is considerably faster than timings reported previously for other algorithms. Based on a parameterization set of nineteen compounds of different size (11-4346 atoms) and class (organics, proteins, DNA, and various complexes) consisting of a total 23,197 atoms, the method exhibits relative errors in the range 0.2-12.6% for total molecular surface areas and average absolute atomic surface area deviations in the range 1.7 to 3.6 A(2).

Effective energy function for proteins in solution

A Gaussian solvent-exclusion model for the solvation free energy is developed. It is based on theoretical considerations and parametrized with experimental data. When combined with the CHARMM 19 polar hydrogen energy function, it provides an effective energy function (EEF1) for proteins in solution. The solvation model assumes that the solvation free energy of a protein molecule is a sum of group contributions, which are determined from values for small model compounds. For charged groups, the self-energy contribution is accounted for primarily by the exclusion model. Ionic side-chains are neutralized, and a distance-dependent dielectric constant is used to approximate the charge-charge interactions in solution. The resulting EEF1 is subjected to a number of tests. Molecular dynamics simulations at room temperature of several proteins in their native conformation are performed, and stable trajectories are obtained. The deviations from the experimental structures are similar to those observed in explicit water simulations. The calculated enthalpy of unfolding of a polyalanine helix is found to be in good agreement with experimental data. Results reported elsewhere show that EEF1 clearly distinguishes correctly from incorrectly folded proteins, both in static energy evaluations and in molecular dynamics simulations and that unfolding pathways obtained by high-temperature molecular dynamics simulations agree with those obtained by explicit water simulations. Thus, this energy function appears to provide a realistic first approximation to the effective energy hypersurface of proteins.

Simulation of peptide folding with explicit water--a mean solvation method

A new approach to efficiently calculate solvent effect in computer simulation of macromolecular systems has been developed. Explicit solvent molecules are included in the simulation to provide a mean solvation force for the solute conformational search. Simulations of an alanine dipeptide in aqueous solution showed that the new approach is significantly more efficient than conventional molecular dynamics method in conformational search, mainly because the mean solvation force reduced the solvent damping effect. This approach allows the solute and solvent to be simulated separately with different methods. For the macromolecule, the rigid fragment constraint dynamics method we developed previously allows large time-steps. For the solvent, a combination of a modified force-bias Monte Carlo method and a preferential sampling can efficiently sample the conformational space. A folding simulation of a 16-residue peptide in water showed high efficiency of the new approach.

Pairwise calculation of protein solvent-accessible surface areas

BACKGROUND

The tractability of many algorithms for determining the energy state of a system depends on the pairwise nature of an energy expression. Some energy terms, such as the standard implementation of the van der Waals potential, satisfy this criterion whereas others do not. One class of important potentials that are not pairwise involves benefits and penalties for burying hydrophobic and/or polar surface areas. It has been found previously that, in some cases, a pairwise approximation to these surface areas correlates with the true surface areas. We set out to generalize the applicability of this approximation.

RESULTS

We develop a pairwise expression with one scalable parameter that closely reproduces both the true buried and the true exposed solvent-accessible surface areas. We then refit our previously published coiled-coil stability data to give solvation parameters of 26 cal/mol A2 favoring hydrophobic burial and 100 cal/mol A2 opposing polar burial.

CONCLUSIONS

An accurate pairwise approximation to calculate exposed and buried protein solvent-accessible surface area is achieved.

Characterizing cavities in model inclusion molecules: a comparative study

We have selected fullerene-60 and -70 cavities as model systems in order to test several methods for characterizing inclusion molecules. The methods are based on different technical foundations such as a square and triangular tessellation of the molecule taken as a unitary sphere, spherical tessellation of the molecular surface, numerical integration of the atomic volumes and surfaces, triangular tessellation of the molecular surface, and a cubic lattice approach to a molecular space. Accurate measures of the molecular volume and surface area have been performed with the pseudo-random Monte Carlo (MCVS) and uniform Monte Carlo (UMCVS) methods. These calculations serve as a reference for the rest of the methods. The SURMO2 and MS methods have not recognized the cavities and may not be convenient for intercalation compounds. The programs that have detected the cavities never exceed 5% deviation relative to the reference values for molecular volume and surface area. The GEPOL algorithm, alone or combined with TOPO, shows results in good agreement with those of the UMCVS reference. The uniform random number generator provides the fastest convergence for UMCVS and a correct estimate of the standard deviations. The effect of the internal cavity on the accessible surfaces has been calculated.

Analysis of the stability of hemoglobin S double strands

The deoxyhemoglobin S (deoxy-HbS) double strand is the fundamental building block of both the crystals of deoxy-HbS and the physiologically relevant fibers present within sickle cells. To use the atomic-resolution detail of the hemoglobin-hemoglobin interaction known from the crystallography of HbS as a basis for understanding the interactions in the fibers, it is necessary to define precisely the relationship between the straight double strands in the crystal and the twisted, helical double strands in the fibers. The intermolecular contact conferring the stability of the double strand in both crystal and fiber is between the beta6 valine on one HbS molecule and residues near the EF corner of an adjacent molecule. Models for the helical double strands were constructed by a geometric transformation from crystal to fiber that preserves this critical interaction, minimizes distortion, and makes the transformation as smooth as possible. From these models, the energy of association was calculated over the range of all possible helical twists of the double strands and all possible distances of the double strands from the fiber axis. The calculated association energies reflect the fact that the axial interactions decrease as the distance between the double strand and the fiber axis increases, because of the increased length of the helical path taken by the double strand. The lateral interactions between HbS molecules in a double strand change relatively little between the crystal and possible helical double strands. If the twist of the fiber or the distance between the double strand and the fiber axis is too great, the lateral interaction is broken by intermolecular contacts in the region around the beta6 valine. Consequently, the geometry of the beta6 valine interaction and the residues surrounding it severely restricts the possible helical twist, radius, and handedness of helical aggregates constructed from the double strands. The limitations defined by this analysis establish the structural basis for the right-handed twist observed in HbS fibers and demonstrates that for a subunit twist of 8 degrees, the fiber diameter cannot be more than approximately 300 A, consistent with electron microscope observations. The energy of interaction among HbS molecules in a double strand is very slowly varying with helical pitch, explaining the variable pitch observed in HbS fibers. The analysis results in a model for the HbS double strand, for use in the analysis of interactions between double strands and for refinement of models of the HbS fibers against x-ray diffraction data.

SERF: a program for accessible surface area calculations

The program SERF has been designed to facilitate the greater use of accessible surface area calculations in the analysis of protein structure, including analysis of surface area changes on binding and complexation. For comparative purposes, the program implements a number of alternative methods for calculating surface areas, including those that approximate residues by single spheres. Algorithmic details, comparative performance, and the software implementation of SERF are discussed.

Factors affecting the ability of energy functions to discriminate correct from incorrect folds

Eighteen low and medium resolution empirical energy functions were tested for their ability to distinguish correct from incorrect folds from three test sets of decoy protein conformations. The energy functions included 13 pairwise potentials of mean force, covering a wide range of functional forms and methods of parameterization, four potentials that attempt to detect properly formed hydrophobic cores, and one environment-based potential. the first of the three test sets consists of large ensembles of plausible conformations for eight small proteins, all of which have correct native secondary structure and are reasonably compact. The second is the set of all subconformations in a database of known protein structures applied to the sequences in that database (ungapped threading). The third is a set of ensembles of 1000 conformations each for seven small proteins taken from molecular dynamics simulations at 298 K and 498 K. Our results show that there are functions effective for each challenge set; moreover, success in one test is no guarantee of success in another. We examine the factors that seem to be important for accurate discrimination of correct structures in each of the test sets, and note that extremely simple functions are often as effective as more complex functions.