**7. Applications of energy minimization**

Energy Minimization is very widely used in molecular modeling and is an integral part of techniques such as conformational search procedures. Energy Minimization is also used to prepare a system for other types of calculation. For example, energy mini- Minimization may be used prior to a molecular dynamics or Monte Carlo simulation in order to relieve any unfavorable interactions in the initial configuration of the system [24]. This is especially recommended for simulations of complex systems such as macromolecules or large molecular assemblies.

**131**

**Author details**

Budhayash Gautam

**Acknowledgements**

complete the present work.

**Conflict of interest**

Prayagraj, U. P., India

Sam Higginbottom University of Agriculture, Technology and Sciences,

© 2020 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium,

The authors are grateful to the Sam Higginbottom University of Agriculture, Technology and Sciences, Allahabad, for providing the facilities and support to

\*Address all correspondence to: budhayashgautam@gmail.com

The author declares no conflict of interest.

provided the original work is properly cited.

*Energy Minimization*

**8. Conclusion**

*DOI: http://dx.doi.org/10.5772/intechopen.94809*

The energetic state of a protein is one of the most important representative parameter of its stability. The energy of a protein (E) can be defined as a function of its atomic coordinates, thus providing a quantitative criterion for model selection and refinement. This energy function consists of several components e.g. (1) Bond energy and angle energy, representative of the covalent bonds, bond angles. (2) Dihedral energy, due to the dihedral angles. (3) A van der Waals term (also called Leonard-Jones potential) to ensure that atoms do not have steric clashes. (4) Electrostatic energy accounting for the Coulomb's Law m protein structure, i.e. the long-range forces between charged and partially charged atoms. All these quantitative terms have been parameterized and are collectively referred to as the 'forcefield'. The goal of energy Minimization is to find a set of coordinates representing the minimum energy conformation for the given structure. Various algorithms have been formulated by varying the use of derivatives. The common algorithm used for this optimization is steepest descent, conjugate gradient and Newton–Raphson etc. These methods complement each other in search of the local minima. Therefore, a reasonable energy Minimization protocol involves few initial steps of steepest descent, followed by a larger number of conjugate gradient iterations. Although energy Minimization is a tool to achieve the nearest local minima, it is also an indispensable tool in correcting structural anomalies, viz. bad stereo-chemistry and short contacts. An efficient optimization protocol could be devised from these methods in conjunction with a larger space exploration algorithm, e.g. molecular dynamics.
