CCSD calculations on C(14), C(18), and C(22) carbon clusters

The structure and energetics of the ring isomers of C(4n+2) (n=3-5) carbon clusters were studied by using coupled-cluster singles and doubles excitation theory to overcome the vast differences existing in the literature. The results obtained in the present study clearly indicate that C(14), C(18), and C(22) carbon rings have bond-length and bond-angle alternated acetylenic minimum energy structures. Contrarily, density functional theory calculations were unable to predict these acetylenic-type structures and they ended up with the cumulenic structures. It is found from the coupled-cluster studies that the lowest-energy ring isomer for the first two members of C(4n+2) series is a bond-angle alternated cumulenic D((2n+1)h) symmetry structure while the same for the remaining members is a bond-length and bond-angle alternated C((2n+1)h) symmetry structure. In C(4n+2) carbon rings, Peierls-type distortion, transformation from bond-angle alternated to bond-length alternated minimum energy structures, occurs at C(14) carbon ring.     

Application of some methods of constrained optimization to the calculation of the molecular strain energy

The Lagrange multipliers method is applied to the minimization algorithm of the molecular potential energy proposed by Boyd in order to keep the bond lengths constant during the optimization. The results obtained for a series of molecules and the approximations supposed in the new algorithm are analysed.The first steps to include the penalty methods in the minimization of the molecular potential energy with constraints in the valence coordinates are given.     

分子力学计算的参数化过程

介绍了如何通过设计模型分子构造参数的方法和过程：首先设计模型分子；在平衡位置附近选择几个点，对模型分子进行分子力学和量子化学的计算；计算出量子化学能量Eqm和分子力学能量Emm的差值；然后对结构参数（健长，键角，二面角）和能量差值进行拟合，得拟合曲线的方程，从方程的系数可求出参数．文章给出了一些实例．     

Spatially constrained minimization of macromolecules

A structural minimization procedure which converges rapidly and restricts the atomic shifts is outlined. It is implemented by adding a harmonic penalty term for the displacements of atomic positions and resetting the reference coordinates with respect to which the constraints are computed during the minimization. The resetting serves to reduce the constraint energy of the minimized structure to negligible levels.     

A fast SHAKE algorithm to solve distance constraint equations for small molecules in molecular dynamics simulations

A common method for the application of distance constraints in molecular simulations employing Cartesian coordinates is the SHAKE procedure for determining the Lagrange multipliers regarding the constraints. This method relies on the linearization and decoupling of the equations governing the atomic coordinate resetting corresponding to each constraint in a molecule, and is thus iterative. In the present study, we consider an alternative method, M‐SHAKE, which solves the coupled equations simultaneously by matrix inversion. The performances of the two methods are compared in simulations of the pure solvents water, dimethyl sulfoxide, and chloroform. It is concluded that M‐SHAKE is significantly faster than SHAKE when either (1) the molecules contain few distance constraints (solvent), or (2) when a high level of accuracy is required in the application of the constraints. © 2001 John Wiley & Sons, Inc. J Comput Chem 22: 501–508, 2001     

Gradient SHAKE: An improved method for constrained energy minimization in macromolecular simulations

Current macromolecular energy minimization algorithms become inefficient and prone to failure when bond length constraints are imposed. They are required to relieve steric stresses in biomolecules prior to a molecular dynamics simulation. Unfortunately, the latter often require constraints, leading to difficulties in initiating trajectories from unconstrained energy minima. This difficulty was overcome by requiring that the components of the energy gradient vanish along the constrained bonds. The modified energy minimization algorithm converges to a lower energy in a fewer number of iterations and is more robust than current implementations. The method has been successfully applied to the Dickerson DNA dodecamer, CGCGAATTCGCG. © 1995 John Wiley & Sons, Inc.     

The molecular potential energy surface and vibrational energy levels of methyl fluoride. Part II

New analytical bending and stretching, ground electronic state, potential energy surfaces for CH(3)F are reported. The surfaces are expressed in bond-length, bond-angle internal coordinates. The four-dimensional stretching surface is an accurate, least squares fit to over 2000 symmetrically unique ab initio points calculated at the CCSD(T) level. Similarly, the five-dimensional bending surface is a fit to over 1200 symmetrically unique ab initio points. This is an important first stage towards a full nine-dimensional potential energy surface for the prototype CH(3)F molecule. Using these surfaces, highly excited stretching and (separately) bending vibrational energy levels of CH(3)F are calculated variationally using a finite basis representation method. The method uses the exact vibrational kinetic energy operator derived for XY(3)Z systems by Manson and Law (preceding paper, Part I, Phys. Chem. Chem. Phys., 2006, 8, DOI: 10.1039/b603106d). We use the full C(3v) symmetry and the computer codes are designed to use an arbitrary potential energy function. Ultimately, these results will be used to design a compact basis for fully coupled stretch-bend calculations of the vibrational energy levels of the CH(3)F system.     

Comparison of algorithms for conical intersection optimisation using semiempirical methods

We present a comparison of three previously published algorithms for optimising the minimum energy crossing point between two Born–Oppenheimer electronic states. The algorithms are implemented in a development version of the MNDO electronic structure package for use with semiempirical configuration interaction methods. The penalty function method requires only the energies and gradients of the states involved, whereas the gradient projection and Lagrange–Newton methods also require the calculation of non-adiabatic coupling terms. The performance of the algorithms is measured against a set of well-known small molecule conical intersections. The Lagrange–Newton method is found to be the most efficient, with the projected gradient method also competitive. The penalty function method can only be recommended for situations where non-adiabatic coupling terms cannot be calculated. Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

LINCS: A linear constraint solver for molecular simulations

In this article, we present a new LINear Constraint Solver (LINCS) for molecular simulations with bond constraints. The algorithm is inherently stable, as the constraints themselves are reset instead of derivatives of the constraints, thereby eliminating drift. Although the derivation of the algorithm is presented in terms of matrices, no matrix matrix multiplications are needed and only the nonzero matrix elements have to be stored, making the method useful for very large molecules. At the same accuracy, the LINCS algorithm is three to four times faster than the SHAKE algorithm. Parallelization of the algorithm is straightforward. © 1997 John Wiley & Sons, Inc. J Comput Chem 18 : 1463–1472, 1997     

MILCH SHAKE: An efficient method for constraint dynamics applied to alkanes

We describe a method to impose constraints in a molecular dynamics simulation. A technique developed to solve the special case of a linear topology (MILC SHAKE) is hybridized with the SHAKE algorithm. The methodology, which we term MILC‐hybridized SHAKE (or MILCH SHAKE), applies to more complex topologies. Here we consider the important case of all atom models of alkanes. Exploiting the mass difference between carbon and hydrogen we show that for higher alkanes MILCH SHAKE can be an order of magnitude faster than SHAKE. © 2009 Wiley Periodicals, Inc. J Comput Chem, 2009     

用于真实蛋白质结构预测的一种新的优化方法

用"相对熵"作为优化函数,提出了一个有效快速的折叠预测优化算法.使用了非格点模型,预测只关心蛋白质主链的走向.其中只用到了蛋白质主链上的两两连续的Cα原子间的距离信息以及20种氨基酸的接触势的一个扩展形式.对几个真实蛋白质做了算法测试,预测的初始结构都为比较大的去折叠态,预测构象相对于它们天然结构的均方根偏差(RMSD)为5～7 A.从原理上讲,该方法是对能量优化的改进.     

Genetic algorithms for protein conformation sampling and optimization in a discrete backbone dihedral angle space

We have investigated protein conformation sampling and optimization based on the genetic algorithm and discrete main chain dihedral state model. An efficient approach combining the genetic algorithm with local minimization and with a niche technique based on the sharing function is proposed. Using two different types of potential energy functions, a Go-type potential function and a knowledge-based pairwise potential energy function, and a test set containing small proteins of varying sizes and secondary structure compositions, we demonstrated the importance of local minimization and population diversity in protein conformation optimization with genetic algorithms. Some general properties of the sampled conformations such as their native-likeness and the influences of including side-chains are discussed.     

An approximate but fast method to impose flexible distance constraints in molecular dynamics simulations

A fast but approximative method to apply flexible constraints to bond lengths in molecular dynamics simulations is presented and the effects of the approximation are investigated. The method is not energy conserving, but coupling to a temperature bath results in stable simulations. The high frequencies from bond-length vibrations are successfully removed from the system while maintaining the flexibility of the bonds. As a test liquid neopentane is simulated at different pressures. Energetic and dynamic properties are not affected by the new flexible constraint simulation method.     

An analysis of the structural and energetic properties of deoxyribose by potential energy methods

We discuss the three fundamental issues of a computational approach in structure prediction by potential energy minimization, and analyze them for the nucleic acid component deoxyribose. Predicting the conformation of deoxyribose is important not only because of the molecule's central conformational role in the nucleotide backbone, but also because energetic and geometric discrepancies from experimental data have exposed some underlying uncertainties in potential energy calculations. The three fundamental issues examined here are: (i) choice of coordinate system to represent the molecular conformation; (ii) construction of the potential energy function; and (iii) choice of the minimization technique. For our study, we use the following combination. First, the molecular conformation is represented in cartesian coordinate space with the full set of degrees of freedom. This provides an opportunity for comparison with the pseudorotation approximation. Second, the potential energy function is constructed so that all the interactions other than the nonbonded terms are represented by polynomials of the coordinate variables. Third, two powerful Newton methods that are globally and quadratically convergent are implemented: Gill and Murray's Modified Newton method and a Truncated Newton method, specifically developed for potential energy minimization. These strategies have produced the two experimentally-observed structures of deoxyribose with geometric data (bond angles and dihedral angles) in very good agreement with experiment. More generally, the application of these modeling and minimization techniques to potential energy investigations is promising. The use of cartesian variables and polynomial representation of bond length, bond angle and torsional potentials promotes efficient second-derivative computation and, hence, application of Newton methods. The truncated Newton, in particular, is ideally suited for potential energy minimization not only because the storage and computational requirements of Newton methods are made manageable, but also because it contains an important algorithmic adaptive feature: the minimization search is diverted from regions where the function is nonconvex and is directed quickly toward physically interesting regions.     

Poling: Promoting conformational variation

This article introduces several methods of assessing the extent to which a collection of conformations represents or covers conformational space. It also describes poling: a novel technique for promoting conformational variation that can be applied to any method of conformational analysis that locally minimizes a penalty or energy function. The function being minimized is modified to force similar conformers away from each other. The method is independent of the origin of the initial conformers and of the particular minimization method used. It is found that, with the modification of the penalty function, clustering of the resulting conformers is generally unnecessary because the conformers are forced to be dissimilar. The functional form of the poling function is presented, and the merits are discussed with reference to (1) efficacy at promoting variation and (2) perturbation of the unmodified function. Results will be presented using conformers obtained from distance geometry with and without poling. It will be shown that the addition of poling eliminates much redundancy in conformer generation and improves the coverage of the conformational space. © 1995 by John Wiley & Sons, Inc.     

SHAKE,rattle, and roll: Efficient constraint algorithms for linked rigid bodies

We present an iterative constraint algorithm, QSHAKE, for use with semirigid molecules in molecular dynamics simulations. The algorithm is based on “SHAKE-ing” bond constraints between rigid bodies, whose equations of motion are solved in the quaternion framework. The algorithm is derived and its performance compared with SHAKE for liquid octane. QSHAKE is significantly more efficient whenever SHAKE requires triangles (or tetrahedra) of constraints to maintain molecular shape. Efficiencies are gained because QSHAKE reduces the number of holonomic constraints that must be solved iteratively and requires fewer iterations to obtain convergence. The gains in efficiency are most noticeable when a high degree of precision is imposed on the constraint criteria. QSHAKE is also stable at larger time steps than SHAKE, thus allowing for even more efficient exploration of phase space for semirigid molecules. © 1998 John Wiley & Sons, Inc. J Comput Chem 19: 102–111, 1998     

Optimum folding pathways of proteins: their determination and properties

We develop a dynamic optimization technique for determining optimum folding pathways of proteins starting from different initial configurations. A coarse-grained Go model is used. Forces acting on each bead are (i) the friction force, (ii) forces from bond length constraints, (iii) excluded volume constraints, and (iv) attractive forces between residue pairs that are in contact in the native state. An objective function is defined as the total attractive energy between nonbonded residues, which are neighbors in the native state. The objective function is minimized over all feasible paths, satisfying bond length and excluded volume constraints. The optimization problem is nonconvex and contains a large number of constraints. An augmented Lagrangian method with a penalty barrier function was used to solve the problem. The method is applied to a 36-residue protein, chicken villin headpiece. Sequences of events during folding of the protein are determined for various pathways and analyzed. The relative time scales are compared and scaled according to experimentally measured events. Formation times of the helices, turn, and the loop agree with experimental data. We obtain the overall folding time of the protein in the range of 600 ns-1.2 micros that is smaller than the experimental result of 4-5 micros, showing that the optimal folding times that we obtain may be possible lower bounds. Time dependent variables during folding and energies associated with short- and long-range interactions between secondary structures are analyzed in modal space using Karhunen-Loeve expansion.     

Performance analysis of the double-iterated Kalman filter for molecular structure estimation

A possible application of a novel double-iterated Kalman filter (DIKF) as an algorithm for molecular structure determination is investigated in this work. Unlike traditional optimization algorithms, the DIKF does not exploit experimental nuclear magnetic resonance (NMR) constraints in a penalty function to be minimized but used them to filter the atomic coordinates. Furthermore, it is a nonlinear Bayesian estimator able to handle the uncertainty in the experimental data and in the computed structures, represented as covariance matrices. The algorithm presented applies all constraints simultaneously, in contrast with DIKF algorithms for structure determination found in literature, which apply the constraints one at a time. The performances of both paradigms are tested and compared with those obtained by a commonly used optimization algorithm (based on the conjugate gradient method). Besides providing estimates of the conformational uncertainty directly in the final covariance matrix, DIKF algorithms appear to generate structures with a better stereochemistry and be able to work with realistically imprecise constraints, while time performances are strongly affected by the heavy matricial calculations they require. © 1996 by John Wiley & Sons, Inc.     

Protein structure prediction using a combination of sequence homology and global energy minimization I. Global energy minimization of surface loops

A procedure has been developed for global energy minimization of surface loops of proteins in the presence of a fixed core. The ECEPP potential function has been modified to allow more accurate representations of hydrogen bond interactions and intrinsic torsional energies. A computationally efficient representation of hydration free energy has been introduced. A local minimization procedure has been developed that uses a cutoff distance, minimization with respect to subsets of degrees of freedom, analytical second derivatives, and distance constraints between rigid segments to achieve efficiency in applications to surface loops. Efficient procedures have been developed for deforming segments of the initial backbone structure and for removing overlaps. Global energy minimization of a surface loop is accomplished by generating a sequence (or a trajectory) of local minima, the component steps of which are generated by searching collections of local minima obtained by deforming seven-residue segments of the surface loop. The search at each component step consists of the following calculations: (1) A large collection of backbone structures is generated by deforming a seven-residue segment of the initial backbone structure. (2) A collection of low-energy backbone structures is generated by applying local energy minimization to the resulting collection of backbone structures (interactions involving side chains that will be searched in this component step are not included in the energy). (3) One low-energy side-chain structure is generated for each of the resulting low-energy backbone structures. (4) A collection of low-energy local minima is generated by applying local energy minimization to the resulting collection of structures. (5) The local minimum with the lowest energy is retained as the next point of the trajectory. Applications of our global search procedure to surface segments of bovine pancreatic trypsin inhibitor (BPTI) and bovine trypsin suggest that component-step searches are reasonably complete. The computational efficiency of component-step searches is such that trajectories consisting of about 10 component steps are feasible using an FPS-5200 array processor. Our procedure for global energy minimization of surface loops is being used to identify and correct problems with the potential function and to calculate protein structure using a combination of sequence homology and global energy minimization.