*2.3.1 Approaches based on energy minimization*

The energy minimization method is also known as the *ab-initio* (*de* novo) method for protein structure prediction and is based on the theory that the native structure of protein is always at thermodynamic equilibrium with minimum energy, which is calculated using basic laws of physics and chemistry (**Figure 1**). Energy minimizationbased methods always attempt to detect the global minima in free energy surface of the protein molecule as it is thought that global minima correspond to the native conformation. This method is not very helpful to design protein sequence length of more than 150 amino acid residues. However, it can be used to design small stable peptides that can bind to any specific therapeutic targets [16]. Two types of energy minimization methods are broadly used in *de novo* structure prediction approach, namely static and dynamical minimization methods. Some of the major FF used for energy minimizations are GROMOS, AMBER, CHARMM and ECEPP [17, 18]. One of the *ab-initio* protein structure prediction software packages is ROSETTA. This software package is based on the postulation that local interactions lead the conformation of short segments while global interactions establish the 3D protein structure [19]. The advantage of *ab-initio* approach is that it is based on physicochemical principles, however, these principles are hampered by the vast number of degrees of freedom which are needed to be looked after and also the performance of energy functions are

limited. The disadvantage of this method is that it requires high computations and for such studies there are no "good enough" interaction potentials which can model the native structure of a protein with atomic detail [20].

#### *2.3.2 Approaches based on knowledge*

The available protein structures are used to derive the knowledge based potentials [21, 22]. Further, these potentials are used to obtain the secondary structural information from amino acid sequence. The methods, based on the knowledge procured from known protein structures are of two types.

#### *2.3.2.1 Homology modeling*

One of the most powerful methods used to predict the 3D structure of proteins is the homology modeling. This method, also known as comparative modeling, uses a query protein having sequence similar with the target protein, having known tertiary structure [23–25]. The basis of this method lies on the observation that structures are more conserved than their sequences. Thus, if a target sequence has some degree of similarity with a protein sequence having known 3D structure, then that structure can be used to precisely model the target protein. A plethora of review articles are available on the strategies and challenges of computational protein structure prediction [8, 26].

For an accurate model building of a protein using homology modeling approach, the first step is template selection. The most crucial step involves the generation of a structure-based alignment between the query and the template protein sequence [27]. Models cannot be constructed for alignments having less than 20% identity. Additionally, the environment of the template such as the type of solvent, pH, presence of ligands, etc. and the quality of the experimentally-derived template structure must be taken into account. Once a desired template structure has been selected, a target-template alignment must be performed using standard sequence alignment techniques. After the creation of the template-target alignment, the 3D model of the target protein is created using several algorithms. Distance geometry is one of the commonly used methods to satisfy the spatial restraints obtained from the target-template alignment. MODELLER is one of the reliable homology

**37**

**Figure 2.**

*A scheme of homology modeling.*

*2.3.2.2 Threading*

*Role of Force Fields in Protein Function Prediction DOI: http://dx.doi.org/10.5772/intechopen.93901*

dynamics to follow the spatial restraints [28].

modeling program and it imposes spatial restraints that are derived from the bond distances and angles in the target structure that are based on its alignment with the template structure, and stereo-chemical restraints on bond distance and dihedral angle preferences that are obtained from a representative set of all known protein structures. Then the constructed model is getting minimized using molecular

After the creation of 3D model, the next step is to perform the quality assessment of the predicted model. From last few decades, many methods have been developed to assess the quality and correctness of modeled protein structures which analyze their stereochemistry. Some of the programs for such analysis are PROCHECK [29] and WhatCheck [30]. Another method to analyze the modeled protein is to calculate a residue-by-residue energy profile, where a peak in the profile corresponds to an error in the model. But this method has a drawback considering that a section of residues may appear to be inaccurate, while in reality they will be interacting with an incorrectly modeled region. Thus, for the assessment of modeled proteins,

Homology modeling for the prediction of protein 3D structures consists of multiple steps (**Figure 2**). Although a number of tools and web-servers are available, but no single server or tool can be considered as best in every aspect as compared to others. The function of a protein is dependent on the 3D structure; therefore, it is very important to enhance the quality of the predicted model. Homology modeling has a wide variety of applications in structural biology and plays a vital role in drug discovery process, as because for the study of drug-receptor (protein) interaction, the structure of the receptor (protein) is of utmost importance. However, this

Threading, also known as fold recognition is a method that searches the protein structure template in a library of folds with the lowest possible energy for a given query sequence [15]. Fold recognition of a sequence requires a precise alignment of the query sequence corresponding to the positions of the amino acid residues of a folding motif. A set of possible positions of the amino acids in 3D space is

energy profile should not be the only means of identifying a good model.

approach does not work if homologous structures are not available.

#### *Role of Force Fields in Protein Function Prediction DOI: http://dx.doi.org/10.5772/intechopen.93901*

*Homology Molecular Modeling - Perspectives and Applications*

native structure of a protein with atomic detail [20].

procured from known protein structures are of two types.

*2.3.2 Approaches based on knowledge*

*An example of ab-initio structure prediction.*

protein structure prediction [8, 26].

*2.3.2.1 Homology modeling*

**Figure 1.**

limited. The disadvantage of this method is that it requires high computations and for such studies there are no "good enough" interaction potentials which can model the

The available protein structures are used to derive the knowledge based potentials [21, 22]. Further, these potentials are used to obtain the secondary structural information from amino acid sequence. The methods, based on the knowledge

One of the most powerful methods used to predict the 3D structure of proteins is the homology modeling. This method, also known as comparative modeling, uses a query protein having sequence similar with the target protein, having known tertiary structure [23–25]. The basis of this method lies on the observation that structures are more conserved than their sequences. Thus, if a target sequence has some degree of similarity with a protein sequence having known 3D structure, then that structure can be used to precisely model the target protein. A plethora of review articles are available on the strategies and challenges of computational

For an accurate model building of a protein using homology modeling approach, the first step is template selection. The most crucial step involves the generation of a structure-based alignment between the query and the template protein sequence [27]. Models cannot be constructed for alignments having less than 20% identity. Additionally, the environment of the template such as the type of solvent, pH, presence of ligands, etc. and the quality of the experimentally-derived template structure must be taken into account. Once a desired template structure has been selected, a target-template alignment must be performed using standard sequence alignment techniques. After the creation of the template-target alignment, the 3D model of the target protein is created using several algorithms. Distance geometry is one of the commonly used methods to satisfy the spatial restraints obtained from the target-template alignment. MODELLER is one of the reliable homology

**36**

modeling program and it imposes spatial restraints that are derived from the bond distances and angles in the target structure that are based on its alignment with the template structure, and stereo-chemical restraints on bond distance and dihedral angle preferences that are obtained from a representative set of all known protein structures. Then the constructed model is getting minimized using molecular dynamics to follow the spatial restraints [28].

After the creation of 3D model, the next step is to perform the quality assessment of the predicted model. From last few decades, many methods have been developed to assess the quality and correctness of modeled protein structures which analyze their stereochemistry. Some of the programs for such analysis are PROCHECK [29] and WhatCheck [30]. Another method to analyze the modeled protein is to calculate a residue-by-residue energy profile, where a peak in the profile corresponds to an error in the model. But this method has a drawback considering that a section of residues may appear to be inaccurate, while in reality they will be interacting with an incorrectly modeled region. Thus, for the assessment of modeled proteins, energy profile should not be the only means of identifying a good model.

Homology modeling for the prediction of protein 3D structures consists of multiple steps (**Figure 2**). Although a number of tools and web-servers are available, but no single server or tool can be considered as best in every aspect as compared to others. The function of a protein is dependent on the 3D structure; therefore, it is very important to enhance the quality of the predicted model. Homology modeling has a wide variety of applications in structural biology and plays a vital role in drug discovery process, as because for the study of drug-receptor (protein) interaction, the structure of the receptor (protein) is of utmost importance. However, this approach does not work if homologous structures are not available.
