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Peptide-Based Drug Design

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116 Copps et al.<br />

Fig. 1. Potential energy function for general class I force field.<br />

shown in Fig. 1(1). In class I empirical force fields, bond stretching and angle<br />

bending relative to equilibrium radius and angle values are described by the<br />

classical, not quantum harmonic oscillator function, necessitating the use of<br />

constraints to approximate the quantum effects of vibrating bonds and bond<br />

angles. Bond rotation is described by a sinusoidal function that approximates the<br />

peak energy from repulsion when a torsional angle is in the cis configuration, and<br />

the minimum when it is in trans configuration. Finally, nonbonded interactions<br />

are described by Lennard-Jones as well as Coulombic potentials, which approximate<br />

the long-range forces between uncharged and charged atoms, respectively.<br />

However, they overestimate the effect of molecular dipoles and cannot simulate<br />

molecules with significantly different polar attributes simultaneously, and this<br />

affects real equilibrium distance values because of the movement of atoms based<br />

on polarization. Class I force fields also cannot compute properties which are far<br />

from equilibrium or accurately predict vibrational spectra and they are temperature<br />

dependent. Class II empirical force fields approximate the forces upon<br />

molecules using more descriptive, complicated functions, such as using a Morse<br />

potential in place of the harmonic oscillator in describing bond stretching and<br />

angle bending, and higher-order terms in describing nonbonded interactions.<br />

This increases the accuracy of prediction, but also increases the computation<br />

time, often prohibitively.<br />

The choice of a particular force field depends on the type of system for<br />

which it has been designed. Several class I force fields have been designed for<br />

description of polypeptides, including AMBER (2), CHARMM (3), OPLSand<br />

OPLS-AA (4,5), and GROMOS96 (1). The computational study of peptides<br />

and proteins can yield information regarding the importance of residues and<br />

functional groups in determining the structure, folding and solubility in various<br />

environments. This information can then be applied to the study of the structureactivity<br />

relationships of those molecules in ligand–receptor complexes and aid<br />

in the design of new therapeutics.

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