which are generally employed in most docking methods are devoid of important
aspects, protein flexibility, and are not calibrated enough to understand the difference in surface recognition by ligands and water. The target surface potential is
roughed, and in addition, local minima are identified which are false. Research
work carried by Lexa et al., analyzed the effect of complete flexible protein and
solvent on simulation and drug identification. The results point out that only when
protein is allowed to be fully flexible the true local minima were identified and also
the accurate identification of ligand-binding regions (hot spots). A protocol with
mixed-solvent molecular dynamics (MixMD) was proposed to map hot spots which
matched with that identified using an experimental method MSCS. MixMD simulations help in finding true binding minima and hot spots, thus retaining the
importance of incorporating flexibility to protein receptors [78].
Importance of protein–ligand interactions in drug design
Enzymatic reaction and ligand binding are the key steps, and the detailed understanding of interaction between small molecules and protein may form the basis for
a rational drug design [79–82] to address the major pathologies such as cancers [83,
84] and cardiovascular [85–87] diseases. Docking studies have been useful to
identify new lead compounds as anti-infection agents for Mycobacterium tuberculosis or Plasmodium falciparum, the two pathogens involved in the development
of TB and malaria, respectively [88].
Protein–protein docking approach
Protein–protein interactions (PPIs) play a vital role in all biological/cellular processes. This results in a formation of the macromolecular assembly crucial for
different cellular functions. Initially, the protein–protein docking was introduced in
1978 itself [89] and was later extended to the interaction between the macro- and
small molecules [34]. Currently, protein–protein docking algorithms have been
developed in light of the critical assessment of prediction of interaction (CAPRI)
rule which has accelerated the development of more efficient protein docking
methods [90]. Prediction of protein complex interface is a major driving factor of
the accurate outcome [91–94]. Incorporation of global and local flexibility in the
docking algorithms provides invaluable information in mutagenesis studies and to
steer drug design applications [95–98]. Residue interaction networks (RINs) are
small-world networks, and their topological analyses have been used in particular to
study protein–protein interfaces [99] and to optimize scoring functions for the
evaluation of docking poses [100, 101]. The docking prediction can be used in
combination with homology-based methodologies and integrated into PPI networks
to enhance the structural information [102, 103]. Several disease-causing mutations
were located at the interface of protein; these key elements could be targeted by
drugs. It was predicted that, on an average, a drug binds to six different targets,
including both the primary target and additional “of targets” [104]. Using the idea,
reverse docking can be performed where one single molecule is screened against
multiple receptors instead of screening multiple small molecules against several
receptors [105, 106].
282
D. Velmurugan et al.
aspects, protein flexibility, and are not calibrated enough to understand the difference in surface recognition by ligands and water. The target surface potential is
roughed, and in addition, local minima are identified which are false. Research
work carried by Lexa et al., analyzed the effect of complete flexible protein and
solvent on simulation and drug identification. The results point out that only when
protein is allowed to be fully flexible the true local minima were identified and also
the accurate identification of ligand-binding regions (hot spots). A protocol with
mixed-solvent molecular dynamics (MixMD) was proposed to map hot spots which
matched with that identified using an experimental method MSCS. MixMD simulations help in finding true binding minima and hot spots, thus retaining the
importance of incorporating flexibility to protein receptors [78].
Importance of protein–ligand interactions in drug design
Enzymatic reaction and ligand binding are the key steps, and the detailed understanding of interaction between small molecules and protein may form the basis for
a rational drug design [79–82] to address the major pathologies such as cancers [83,
84] and cardiovascular [85–87] diseases. Docking studies have been useful to
identify new lead compounds as anti-infection agents for Mycobacterium tuberculosis or Plasmodium falciparum, the two pathogens involved in the development
of TB and malaria, respectively [88].
Protein–protein docking approach
Protein–protein interactions (PPIs) play a vital role in all biological/cellular processes. This results in a formation of the macromolecular assembly crucial for
different cellular functions. Initially, the protein–protein docking was introduced in
1978 itself [89] and was later extended to the interaction between the macro- and
small molecules [34]. Currently, protein–protein docking algorithms have been
developed in light of the critical assessment of prediction of interaction (CAPRI)
rule which has accelerated the development of more efficient protein docking
methods [90]. Prediction of protein complex interface is a major driving factor of
the accurate outcome [91–94]. Incorporation of global and local flexibility in the
docking algorithms provides invaluable information in mutagenesis studies and to
steer drug design applications [95–98]. Residue interaction networks (RINs) are
small-world networks, and their topological analyses have been used in particular to
study protein–protein interfaces [99] and to optimize scoring functions for the
evaluation of docking poses [100, 101]. The docking prediction can be used in
combination with homology-based methodologies and integrated into PPI networks
to enhance the structural information [102, 103]. Several disease-causing mutations
were located at the interface of protein; these key elements could be targeted by
drugs. It was predicted that, on an average, a drug binds to six different targets,
including both the primary target and additional “of targets” [104]. Using the idea,
reverse docking can be performed where one single molecule is screened against
multiple receptors instead of screening multiple small molecules against several
receptors [105, 106].
282
D. Velmurugan et al.