Background:
Design of small molecules which are able to bind to the protein responsible for a
disease is the key step of the entire process of the new medicine discovery. Atomistic computer modeling
can significantly improve effectiveness of such design. The accurate calculation of the free energy of
binding a small molecule (a ligand) to the target protein is the most important problem of such modeling.
Docking is one of the most popular molecular modeling methods for finding ligand binding poses in the
target protein and calculating the protein-ligand binding energy. This energy is used for finding the most
active compounds for the given target protein. This short review aims to give a concise description of
distinctive features of docking programs focusing on computation methods and approximations influencing
their accuracy.
Methods:
This review is based on the peer-reviewed research literature including author’s own publications.
The main features of several representative docking programs are briefly described focusing on
their characteristics influencing docking accuracy: force fields, energy calculations, solvent models, algorithms
of the best ligand pose search, global and local optimizations, ligand and target protein flexibility,
and the simplifications made for the docking accelerating. Apart from other recent reviews focused mainly
on the performance of different docking programs, in this work, an attempt is made to extract the most
important functional characteristics defining the docking accuracy. Also a roadmap for increasing the
docking accuracy is proposed. This is based on the new generation of docking programs which have been
realized recently. These programs and respective new global optimization algorithms are described shortly.
Results:
Several popular conventional docking programs are considered. Their search of the best ligand
pose is based explicitly or implicitly on the global optimization problem. Several algorithms are used to
solve this problem, and among them, the heuristic genetic algorithm is distinguished by its popularity and
an elaborate design. All conventional docking programs for their acceleration use the preliminary calculated
grids of protein-ligand interaction potentials or preferable points of protein and ligand conjugation.
These approaches and commonly used fitting parameters restrict strongly the docking accuracy. Solvent
is considered in exceedingly simplified approaches in the course of the global optimization and the search
for the best ligand poses. More accurate approaches on the base of implicit solvent models are used frequently
for more careful binding energy calculations after docking. The new generation of docking programs
are developed recently. They find the spectrum of low energy minima of a protein-ligand complex
including the global minimum. These programs should be more accurate because they do not use a preliminary
calculated grid of protein-ligand interaction potentials and other simplifications, the energy of
any conformation of the molecular system is calculated in the frame of a given force field and there are no
fitting parameters. A new docking algorithm is developed and fulfilled specially for the new docking programs.
This algorithm allows docking a flexible ligand into a flexible protein with several dozen mobile
atoms on the base of the global energy minimum search. Such docking results in improving the accuracy
of ligand positioning in the docking process. The adequate choice of the method of molecular energy calculations
also results in the better docking positioning accuracy. An advancement in the application of
quantum chemistry methods to docking and scoring is revealed.
Conclusion:
The findings of this review confirm the great demand in docking programs for discovery of
new medicine substances with the help of molecular modeling. New trends in docking programs design
are revealed. These trends are focused on the increase of the docking accuracy at the expense of more
accurate molecular energy calculations without any fitting parameters, including quantum-chemical
methods and implicit solvent models, and by using new global optimization algorithms which make it
possible to treat flexibility of ligands and mobility of protein atoms simultaneously. Finally, it is shown
that all the necessary prerequisites for increasing the docking accuracy can be accomplished in practice.
Implicit solvent models fail to reproduce secondary structures of de novo designed peptides