"I have used Schrödinger software for approximately nine years. I really appreciate the fact that there is a very strong team of scientists that are constantly working towards improving the software, implementing the latest methods available for docking, scoring, chemoinformatics, etc. The integration of several required steps of a pipeline on one platform allows for faster and less error-prone execution of projects. In the last year, we carried out docking predictions of protein-ligand inhibitors and I was pleased to see that our predictions have been confirmed experimentally. Moreover, I find that the user-friendly interface makes it very easy, even for students without any experience, to carry out significant amounts of work in a reasonably short amount of time. Computational projects based on the Schrödinger software have always been very popular in my lab!" - Irilenia Nobeli, Lecturer in Bioinformatics Birkbeck, University of London
Glide Docking Software Free Download
Structure-based docking screens of large compound libraries have become common in early drug and probe discovery. As computer efficiency has improved and compound libraries have grown, the ability to screen hundreds of millions, and even billions, of compounds has become feasible for modest-sized computer clusters. This allows the rapid and cost-effective exploration and categorization of vast chemical space into a subset enriched with potential hits for a given target. To accomplish this goal at speed, approximations are used that result in undersampling of possible configurations and inaccurate predictions of absolute binding energies. Accordingly, it is important to establish controls, as are common in other fields, to enhance the likelihood of success in spite of these challenges. Here we outline best practices and control docking calculations that help evaluate docking parameters for a given target prior to undertaking a large-scale prospective screen, with exemplification in one particular target, the melatonin receptor, where following this procedure led to direct docking hits with activities in the subnanomolar range. Additional controls are suggested to ensure specific activity for experimentally validated hit compounds. These guidelines should be useful regardless of the docking software used. Docking software described in the outlined protocol (DOCK3.7) is made freely available for academic research to explore new hits for a range of targets.
The two required inputs for such a screen are the target structure and a screening database. Prior to using the database, the target structure must be converted into a representation used by the docking software and the pocket should be optimized with control calculations using retrospective analysis on known actives. After the prospective library has been docked, top-ranked hits can be filtered and selected for experiment. Multiple assays and controls are typically necessary to confirm activity.
DOCK3.7.5: apply for a license from _Licensing/dock_license_application.html. Licenses are free for nonprofit academic research. Once your application is approved, you will be directed to a download for the source code. The code should run without issue on most Linux environments, but can be optimized by recompiling with gfortran if needed. Questions related to installation can be addressed to dock_fans@googlegroups.com
(Optional) 3D ligand building software: if interested in 3D ligand building in-house (not necessary for this protocol), licenses will also need to be obtained for ChemAxon ( ), OpenEye Omega ( ) and Corina ( -am.com/products/corina). We note that, for many campaigns, 3D molecular structures with all necessary physical properties may be downloaded directly from ZINC20. This tutorial makes use of a webserver for 3D ligand building that is suitable for small control sets. Please apply for an account at , which is free of charge
Example data: an example set of files used in this protocol including ligand and decoy sets, default docking grids and optimized docking grids can be downloaded from _protocol.tar.gz. The example dataset uses the MT1 structure (PDB: 6ME3) co-crystallized with 2-phenylmelatonin
An example set of files used in this protocol, including ligand and decoy sets, default docking grids and optimized docking grids, can be downloaded from _protocol.tar.gz. The example dataset uses the MT1 structure (PDB: 6ME3) co-crystallized with 2-phenylmelatonin.
Molecular docking methods are commonly used for predicting binding modes and energies of ligands to proteins. For accurate complex geometry and binding energy estimation, an appropriate method for calculating partial charges is essential. AutoDockTools software, the interface for preparing input files for one of the most widely used docking programs AutoDock 4, utilizes the Gasteiger partial charge calculation method for both protein and ligand charge calculation. However, it has already been shown that more accurate partial charge calculation - and as a consequence, more accurate docking- can be achieved by using quantum chemical methods. For docking calculations quantum chemical partial charge calculation as a routine was only used for ligands so far. The newly developed Mozyme function of MOPAC2009 allows fast partial charge calculation of proteins by quantum mechanical semi-empirical methods. Thus, in the current study, the effect of semi-empirical quantum-mechanical partial charge calculation on docking accuracy could be investigated.
The docking accuracy of AutoDock 4 using the original AutoDock scoring function was investigated on a set of 53 protein ligand complexes using Gasteiger and PM6 partial charge calculation methods. This has enabled us to compare the effect of the partial charge calculation method on docking accuracy utilizing AutoDock 4 software. Our results showed that the docking accuracy in regard to complex geometry (docking result defined as accurate when the RMSD of the first rank docking result complex is within 2 Å of the experimentally determined X-ray structure) significantly increased when partial charges of the ligands and proteins were calculated with the semi-empirical PM6 method.
Molecular docking methods include the search in space for the energetically most favorable conformation of a protein-ligand complex and the scoring of the resulting geometries with respect to binding energy [1, 12]. The production of the right docking pose and the scoring of the complex geometries are often treated as two separate problems. It should be noted however, that many docking programs use the scoring function in the process of finding the complex with lowest energy [13]; thus, scoring and geometry prediction should rather be treated as one problem and it can be assumed that minimizing the RMSD between predicted and experimentally determined complex geometries would lead to more accurate prediction of binding free energies at the same time.
Moreover, in a recent study analyzing the effect of various charge models in docking results it was concluded that the quantum mechanical charge calculation method yielded significantly better docking results [15, 18], both in terms of binding geometry and energy. It should be noted that in these studies only the ligand charges were calculated with the quantum mechanical method, while the protein charges were calculated with the Gasteiger-Hückel method. Still, semi-empirical charge calculation on the ligand was enough to yield more accurate docking results. Quantum mechanical polarization of the ligand also has been shown to greatly improve docking accuracy [19]. Illingworth and his colleagues [20] extended this method by calculating polarization not only on the ligands, but also on the target macromolecules using Amber charges [21]. However, those implementations involve the knowledge of the structure of the complex and iteration of quantum mechanical calculations and thus cannot be treated as a practical tool in docking [20]. Raha and Merz used semi-empirical QM based scoring function for predicting binding energy and binding mode of a diverse set of protein-ligand complexes [22]. The authors used a scoring function designed using semi-empirical QM Hamiltonians to discriminate between native and decoy poses generated from the program AutoDock 4. Recently, a newly developed semi-empirical PM6 method was introduced that corrects major errors in AM1 and PM3 calculations and is useful for semi-empirical charge calculations of small ligands as well as proteins [23]. Besides that, all main group elements and transition metals are parameterized in PM6 in MOPAC2009 software. Thus, using the PM6 method for assigning partial charges to both the ligand and the protein would have two main advantages i.e. docking of metalloproteins can accurately be handled and semi-empirical charge calculation is expected to yield more accurate docking results in general.
In the current study it was analyzed whether PM6 semi-empirical charge calculation on both the ligands and their host proteins increases docking accuracy in terms of complex geometry and binding energy using AutoDock 4 software. To the author's knowledge this is the first study where MOPAC2009 software is used for semi-empirical charge calculations on proteins systematically for preparing input files for docking calculations. 53 protein-ligand complexes were analyzed for which both crystallographic structure determination and binding data were available. The partial charges of the ligands and proteins were calculated using 1.) Gasteiger 2.) PM6 charge calculation methods and the ligands were docked using AutoDock 4 software back into their host proteins. The resulting complex geometries were analyzed for their RMSD as compared to the available X-ray structure and their binding energies as calculated by the AutoDock 4 scoring function (docking result defined as accurate when the RMSD of the first rank docking result complex is within 2 Å of the experimentally determined X-ray structure). Our results indicated that the use of the PM6 semi-empirical charge calculation method for assigning partial charges to both the protein and the ligand atoms greatly increases docking accuracy as compared to the Gasteiger charge calculation method (available in AutoDockTools) in terms of complex geometry. 2ff7e9595c
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