| D.A. Case, Computer Simulations of Protein Dynamics and Thermodynamics, IEEE: Computer Science & Engineering, October (1993), 47-57. |
....s i l r i l , 12 2H i l , s i l , r i l ( 6 i l , PHILLIPS, ROSEN, WALKE 4 between the two specific beads (e.g. amino acids) involved. The terms involving r i,l in the Lennard Jones expression represent the Euclidean distance between the beads a i and a l (see [3], 5] 8] The constant H i,l = 1 if beads a i and a l are both H type (attractive monomers) and hence both a repulsive force (ensuring that the chain is self avoiding ) and an attractive force (since the beads are H H) are added to the potential energy. On the other hand, H i,l = 0 if the ....
D.A. Case, Computer Simulations of Protein Dynamics and Thermodynamics, IEEE: Computer Science & Engineering, October (1993), 47-57.
....positions of A i Gamma2 ; A i Gamma1 and A i and the segment A i A i 1 . It is easy to see that the l i s, i s and OE i s define a unique configuration. The goal is to obtain these 3N Gamma 3 values. Let us define the potential energy U , whose global minimum we are seeking as the solution [20]. U = L Theta Phi C where, L = N X i=1 K l (l i Gamma l 0i ) 2 ; Theta = N Gamma1 X i=1 K ( i Gamma 0i ) 2 ; Phi = N Gamma1 X i=2 K n [1 cos(nOE i ffi) C = N X i=1 N X j=1;j i 1 ffl i;j 0 oe i;j r i;j 12 Gamma 2H i;j oe i;j r i;j ....
Case D. A., Computer Simulations of Protein Dynamics and Thermodynamics, IEEE: Computer Science & Engineering, October(1993), 47-57.
....of individual protein and surrounding solvent atoms using Newton s equations of motion. 3 Protein MD simulation is a Grand Challenge problem that is computationally demanding. For example, the simulation of a single medium sized protein in water for a nanosecond requires many CRAY Y MP CPU days [3]. Although having ample concurrency, the application is challenging to parallelize on distributed machines because of the irregular computation and communication patterns. IC CEDAR is based on CEDAR [17] a sequential MD program written partly in C and partly in FORTRAN, and the algorithms shown ....
D. A. Case. Computer simulations of protein dynamics and thermodynamics. IEEE Computer, 26:47, 1993.
....programs (such as molecular dynamics, particle simulations and adaptive mesh refinement) have a data distribution which cannot, in general, be predicted statically. In addition, modern algorithms for such problems depend increasingly on sophisticated data structures to achieve high efficiency [2, 13, 4]. In this domain, a program implementation must adapt itself to the irregular and even dynamic structure of the data (exploiting locality where available) to achieve high performance. This is particularly important when good data distributions are used which clump parts of data structures ....
D. A. Case. Computer simulations of protein dynamics and thermodynamics. IEEE Computer, 26:47, 1993.
....the fastest motion in the system with reasonable accuracy. In a variation of the classic N body problem, the protein dynamics simulation, time step size has to be as little as 10 Gamma15 seconds, and it takes 10 6 to 10 7 steps to complete a folding process in the order of nanoseconds. See [9]. Furthermore, the PYRROS scheduler does not need precise weight information, we expect that small weight perturbations caused by particle movement should not lead to significant deterioration in scheduling performance, which is intuitive and analytically shown in [20] Thus a schedule can be ....
D. A. Case, Computer simulation of protein dynamics and thermodynamics, Computer, pp. 47-57, Oct. 1993.
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