Molecular docking methodology explores the behavior of small molecules in the binding site of a target protein. As more protein structures are determined experimentally using X-ray crystallography or nuclear magnetic resonance NMR spectroscopy, molecular docking is increasingly used as a tool in drug discovery. Docking against homology-modeled targets also becomes possible for proteins whose structures are not known. With the docking strategies, the druggability of the compounds and their specificity against a particular target can be calculated for further lead optimization processes. Molecular docking programs perform a search algorithm in which the conformation of the ligand is evaluated recursively until the convergence to the minimum energy is reached. The driving forces for these specific interactions in biological systems aim toward complementarities between the shape and electrostatics of the binding site surfaces and the ligand or substrate.
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Molecular docking methodology explores the behavior of small molecules in the binding site of a target protein. As more protein structures are determined experimentally using X-ray crystallography or nuclear magnetic resonance NMR spectroscopy, molecular docking is increasingly used as a tool in drug discovery. Docking against homology-modeled targets also becomes possible for proteins whose structures are not known. With the docking strategies, the druggability of the compounds and their specificity against a particular target can be calculated for further lead optimization processes.
Molecular docking programs perform a search algorithm in which the conformation of the ligand is evaluated recursively until the convergence to the minimum energy is reached. The driving forces for these specific interactions in biological systems aim toward complementarities between the shape and electrostatics of the binding site surfaces and the ligand or substrate. In modern drug discovery, protein—ligand or protein—protein docking plays an important role in predicting the orientation of the ligand when it is bound to a protein receptor or enzyme using shape and electrostatic interactions to quantify it.
The van der Waals interactions also play an important role, in addition to Coulombic interactions and the formation of hydrogen bonds. The sum of all these interactions is approximated by a docking score, which represents potentiality of binding. In the simplest rigid-body systems, the ligand is searched in a six-dimensional rotational or translational space to fit in the binding site, which can serve as a lead compound for drug design Alberg and Schreiber The docking accuracy in a rigid-body approach is much greater for bound complexes than uncomplexed molecules Shoichet and Kuntz Even though the observed structural changes between the bound and free forms are small, the difference in accuracy implies that the assumption of rigidity is not fully warranted Totrov and Abagyan Also, the difference between the near native structures and others far from native cannot be distinguished, even with simple scoring functions such as measures of surface complementarity Katchalski-Katzir et al.
Hence, the docking procedures were improved by several groups by allowing for receptor and ligand flexibility. The entropy loss of a flexible ligand in rigid six body degrees of freedom in an anisotropic environment of the receptor and the change in its internal energy upon binding can greatly affect the binding affinity. Introducing local minimization of a molecular-mechanics energy function such as in the CHARMM package yields only limited improvement Brooks et al.
Consequently, information regarding the binding site location before the docking processes became very important to increase the docking efficiency. There are several cavity detection programs or online servers that can detect putative active sites within proteins, e. The earliest reported docking methods were based on the lock-and-key assumption proposed by Fischer, stating that both the ligand and the receptor can be treated as rigid bodies and their affinity is directly proportional to a geometric fit between their shapes Mezei Each backbone movement affects multiple side chains in contrast to relatively independent side chains.
Consequently, these flexible docking algorithms not only predict the binding mode of a molecule more accurately than rigid body algorithms, but also its binding affinity relative to other compounds Verkhivker et al. Over the last two decades, more than 60 different docking tools and programs have been developed for both academic and commercial, use such as DOCK Venkatachalam et al.
Although strategies in the ligand placement differ one from another, these programs are broadly categorized as ranging from incremental construction approaches, such as FlexX Rarey et al. With the exception of GOLD, almost all current flexible ligand docking programs treat the receptor as rigid Jones et al.
These programs were evaluated to test their abilities in producing the correct binding mode of a ligand to its biological target and identifying the known compounds with top scores in virtual screening trials. In order to assesses the docking accuracy and mode of binding, initially, FlexX was evaluated on a set of 19 protein—ligand complexes, with a subsequent evaluation on a larger set of complexes Rarey et al.
The docking accuracy of Glide was assessed by redocking ligands from co-crystallized PDB complexes, while GOLD was validated on and complexes Friesner et al. Further, ligandFit was reported for 19 protein—ligand complexes Venkatachalam et al.
Overall, it was reported recently that these docking programs are able to predict experimental poses with root-mean-squared deviations RMSDs averaging from 1. However, flexible receptor docking, especially backbone flexibility in receptors, still presents a major challenge for the available docking methods.
Rigid body docking produces a large number of docked conformations with favorable surface complementarity, followed by the reranking of the conformations using the free energy of approximation. Later, polar Fourier correlations were used to accelerate the search for candidate low-energy conformations Ritchie and Kemp Additionally, other approaches such as computer vision concepts Wolfson and Nussinov , Boolean operations Palma et al.
There are also other types of useful FFT based rigid-body docking tools without a 3D grid-based searching system, such as Hex Ritchie and Kemp ; Ritchie and Venkatraman HEX uses spherical polar Fourier correlations for both rotational and translational space. Furthermore, the efficiency of Fourier transform-based algorithms is further accelerated computationally with the help of advanced software packages, such as the 3D convolution library Pierce et al.
Finally, the sum of intermolecular energies of electrostatic and atomic desolvation energies as a correlation function for all the generated configurations are computed efficiently with FFTs Roberts et al. Using these two programs, the core signal process in the bacterial chemotaxis pathway has been identified Matsuzaki et al. Later, a soft docking approach in FFT was developed where the ligand and the receptor are considered as rigid bodies, and their conformational changes are calculated by allowing a certain degree of inter-protein penetration Katchalski-Katzir et al.
These domain—domain poses were also scored by binding energy and a pseudo-energy term based on restraints derived from linker and end-to-end distances in pyDockTET tethered-docking.
This grid-based system is similar to FFT-based grid searches, except that it has simpler values on the grid. Apart from electrostatics, the hydrophobic complementarity based on geometry was incorporated in the MolFit FFT program to calculate the interface of a protein—protein complex Katchalski-Katzir et al. Recently, PIPER was developed to predict mutual orientation of the two proteins using pairwise interaction potential between the atoms i and j. The contributions to the scoring function are evaluated in discretized 6D space as the sum of terms representing shape complementarity, electrostatic, and desolvation energies.
The structures obtained in PIPER are very close to their native conformations due to the decomposition of eigenvalue—eigenvector, which is the key to the efficient use of this potential Kozakov et al. However, these algorithms are not well suited for unbound crystal structures and yield many false-positives far from the native complex, though they have good surface complementarity.
To improve in silico prediction further, F 2 Dock was developed, which also uses shape complementarity and scores based on Coulombic potentials. This program is also structured to incorporate the Lennard-Jones potential and docking solutions were reranked based on desolvation energy. The lowest RMSD was improved by at least 0. In fact, DOCK was one of the first programs that involved shape complementarity through a set of spheres in the determination of ligand—protein interactions.
The volume occupied by the ligand depends on the diameter of the spheres inside the binding pocket of the protein Kuntz et al. The initial orientation of the ligand inside the binding pocket is determined by a maximum clique detection method based on distance compatibility. However, the data can be accessed rapidly though geometric hashing by matching features in triplets.
The features are represented in the form of spheres and are clustered as poses Fischer et al. SDOCK performs global searches by incorporating the van der Waals attractive potential, geometric collision, screened electrostatic potential, and Lazaridis—Karplus desolvation energy into the scoring function.
Structure flexibility was based on stepwise potentials that were generated from the corresponding continuous forms Zhang and Lai Cell-Dock also performs the global scan using the translational and rotational space of two molecules based on surface complementarity and electrostatics. A paramount difference with FTDock is that the value of the grid size is fixed in a number of cells that reflects grid cell resolution and total span in Angstroms Pons et al. Furthermore, to reduce the size of molecules from large compound libraries, shape complementarity was introduced between ligand and protein in MS-DOCK to perform efficient multiple conformation rigid-body docking Sauton et al.
The contact surface between the ligand and the protein is further optimized by a Gaussian shape fitting function in FLOG Miller et al. The TagDock toolkit produces macromolecular complexes from rigid monomers by generating randomly posed docked pairs decoys that agree with inter-monomer distance restraints determined experimentally by using a penalty for each decoy Smith et al. Examples of other docking programs that use local shape featuring algorithms include LZerD Venkatraman et al.
Geometric hashing algorithms also perform a global protein—protein docking using local shape descriptors, such as surface patches in PatchDock Harrison et al. The method models both side chain and backbone flexibility and performs rigid body optimization of the ligand orientation using modified Patchdock and Fiberdock Hurwitz et al.
Docking was considered successful if the binding of a ligand into its active site was closer than a given threshold from the X-ray solution.
The DOCK program applied to aspartic protease of HIV resulted in a candidate inhibitor with high potency turned out to be several orders of magnitude too low for clinical use.
However, this molecule can be used as a lead compound for the design of more potent inhibitors. Ring and coworkers designed inhibitors against proteases of schistosome and malaria parasites that are crucial to the pathogenicity by using shape-complementarity function and a simplified molecular-mechanics potential approximating the interaction energy between the protease and ligand Ring et al.
The DOT program successfully predicted the electron transfer complex of the positively charged cytochrome c to the negative region on the cytochrome c oxidase surface formed by subunit II Roberts and Pique With the omission of water molecules, the top-ranking solutions of the MolFit program using geometric and geometric-electrostatic docking identify clusters of nearly correct solutions with limited rotational freedom at the interface for disassembled and unbound structures Heifetz et al.
In 26 cases, the correct poses were ranked first, whereas in the other nine cases, the correct solution is ranked among the first 30 conformations. However, SymmDock only predicts structures with cyclic symmetry. If the input monomers are with different symmetry in its native complex, then SymmDock is not suitable for such a prediction Schneidman-Duhovny et al. For the results of three targets, SKE-DOCK failed in the geometric docking because of improper conformations obtained during the docking step Terashi et al.
Further, Cell-Dock was tested on the unbound structures of protein—protein docking benchmark version 2. These results were also assessed by pyDOCK based on electrostatics, desolvation, and van der Waals energy. With CELL, According to the latest CAPRI experiments carried out in , the ClusPro server was best in automated protein docking equivalent to the best human predictor group.
In standard virtual docking studies, ligands are freely docked into a rigid receptor. However, it has become increasingly clear that side chain flexibility plays a crucial role in ligand—protein complexes.
These changes allow the receptor to alter its binding site according to the orientation of the ligand. Four different strategies are currently in use for docking flexible ligands, namely: a Monte Carlo or molecular-dynamics docking of complete molecules; b in-site combinatorial search, c ligand buildup; and d site mapping and fragment assembly.
Monte Carlo methods accept or reject the random changes of the thermodynamic accessible states by using Metropolis criteria Metropolis and Ulam The configurations with increase in temperature T will be accepted by slow cooling through so-called simulated annealing Kirkpatrick et al. The changes in conformations are quite large, allowing the ligand to cross the energy barriers on the potential energy surface. This technique of conformational searches combined with the potentials of molecular affinity gives an efficient method of substrate docking with known structures Goodsell and Olson Along with affinity potentials, distance constraints were added as soft potentials in simulated annealing Yue AutoDock 2.
ICM software generates the ligand in 3D grid space by Monte Carlo movements and minimization of interaction potentials. The results obtained were highly similar to FNR:Fd complexes of Anabaena and maize, showing a good correlation computationally. QXP is a multistep docking program using a local Monte Carlo search with a restricted rotational angle Pellegrini and Doniach Recently, a newly designed and implemented version of the AutoDock program called AutoDock Vina has been released.
This version abandoned the former empirical scoring function and GA-based optimizer, but adopted a new knowledge-based scoring function with a Monte Carlo sampling technique and the Broyden—Fletcher—Goldfarb—Shanno BFGS method for local optimization. Their simulation results showed a significant improvement in both prediction accuracy and docking time.
In recent years, swarm intelligence algorithms have emerged as a fast and reasonably accurate technique in solving complex search problems in computer science. Three of the programs were modifications of the popular open-source docking program AutoDock, albeit different versions, and all of them showed better predictive performance when compared to the original AutoDock implementation. Furthermore, a novel search method called QPSO-ls quantum-behaved particle swarm optimization was introduced for solving a highly flexible docking problem, which is a hybrid of quantum-behaved particle swarm optimization QPSO and a local search method of Solis and Wets Fu et al.
In another program called GalaxyDock, the receptor side chains were preselected and globally optimized using an AutoDock-based algorithm for flexible side-chain docking Shin and Seok GOLD explores the flexibility of the ligand through the process of evolution by using a genetic algorithm and displaces loosely bound water on ligand binding Jones et al.
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Software for molecular docking: a review
This node takes a protein and a reference molecule to define a binding site. Molecules from the input table are docked with FlexX into this binding site. Alternatively, if a template molecule is provided, those molecules are overlayed onto the template based on the maximum common substructure MCS and scored using the FlexX-scoring function. The solutions with the best scores are written to the output table. Molecules that cannot be docked for whatever reason, are written to the error table. Besides the binding site you will be able to define pharmacophore constraints for your docking results. You want to see the source code for this node?