Solvent effect
Catalytic water molecules are also crucial in enzyme-substrate recognition and
enzymatic reaction [107, 108]. The electrostatic screening performed by water
molecules helps in identification of ligand binding to the protein [109]. In a living
system, proteins are active and move in solvent environment with a dielectric
constant of around 80, where waters are arranged around the protein with constant
motion [110]. There are many types of water models, and their effect in docking and
simulations are well studied. In both explicit and implicit models, incorporation the
effect of salvation is available, and choice of the model depends on the computational resource available with the user.
Modeling solvent molecules
Explicit water models
The first model for liquid was proposed by Bernal and Flower [111]. Then, ST2
model of water proposed by Stillinger and Rahman [112] was widely used during
initial stages of development of the protein force fields. The SPC [113] and TIP3P
[114] are similar to each other in terms of atomic point charge. In both the models,
three-site rigid water models are parameterized to produce structure which is in bulk
phase. Thermodynamics of liquid water is taken care. There are other advances in
recent times, and newly developed solvent models such as TIP4P and TIP5P have
the most agreement with the experimentally calculated internal energy [115]. There
are different continuum models, majorly COSMO model [116], Poisson–Boltzmann
(PB) models, and the most commonly used Generalized Born (GB) model
[117, 118].
The increase in the computation power as a result of evolution of core processors
and GPU computations helps in the betterment of the force field development and
matches with the experimental data. The design of good potential approximation
used for simulation analysis helps in prediction of ligand binding, protein structure
prediction, and drug designing accurately. Hence, the potential functions and their
approximation are crucial. The development of force field will lead to the better
chemical accuracy that has to be reached for the best simulation of the biological
molecules aiding in studying their properties.
This development of the force field, simulation methods, and algorithms that
make the calculations automatic and varied potential energy descriptors has a great
impact on the aspect of computer-aided drug design (CADD). Molecular optimization and free energy calculations are important to a major extent that will aid in
the understanding of a molecule binding with protein. In drug designing, it should
be noted that simple and fast methods should be used to screen large number of
molecules. There are different model systems available with different properties that
can be used to analyze the ligand binding to the protein and its recognition.
Different models are briefly stated below.
Fixed conformation models
Force field calculations
Most of the molecular mechanics-based assessments of ligand binding with the
receptor follow the below expression
Structure-Based Drug Design…
283
Catalytic water molecules are also crucial in enzyme-substrate recognition and
enzymatic reaction [107, 108]. The electrostatic screening performed by water
molecules helps in identification of ligand binding to the protein [109]. In a living
system, proteins are active and move in solvent environment with a dielectric
constant of around 80, where waters are arranged around the protein with constant
motion [110]. There are many types of water models, and their effect in docking and
simulations are well studied. In both explicit and implicit models, incorporation the
effect of salvation is available, and choice of the model depends on the computational resource available with the user.
Modeling solvent molecules
Explicit water models
The first model for liquid was proposed by Bernal and Flower [111]. Then, ST2
model of water proposed by Stillinger and Rahman [112] was widely used during
initial stages of development of the protein force fields. The SPC [113] and TIP3P
[114] are similar to each other in terms of atomic point charge. In both the models,
three-site rigid water models are parameterized to produce structure which is in bulk
phase. Thermodynamics of liquid water is taken care. There are other advances in
recent times, and newly developed solvent models such as TIP4P and TIP5P have
the most agreement with the experimentally calculated internal energy [115]. There
are different continuum models, majorly COSMO model [116], Poisson–Boltzmann
(PB) models, and the most commonly used Generalized Born (GB) model
[117, 118].
The increase in the computation power as a result of evolution of core processors
and GPU computations helps in the betterment of the force field development and
matches with the experimental data. The design of good potential approximation
used for simulation analysis helps in prediction of ligand binding, protein structure
prediction, and drug designing accurately. Hence, the potential functions and their
approximation are crucial. The development of force field will lead to the better
chemical accuracy that has to be reached for the best simulation of the biological
molecules aiding in studying their properties.
This development of the force field, simulation methods, and algorithms that
make the calculations automatic and varied potential energy descriptors has a great
impact on the aspect of computer-aided drug design (CADD). Molecular optimization and free energy calculations are important to a major extent that will aid in
the understanding of a molecule binding with protein. In drug designing, it should
be noted that simple and fast methods should be used to screen large number of
molecules. There are different model systems available with different properties that
can be used to analyze the ligand binding to the protein and its recognition.
Different models are briefly stated below.
Fixed conformation models
Force field calculations
Most of the molecular mechanics-based assessments of ligand binding with the
receptor follow the below expression
Structure-Based Drug Design…
283