Toward computational determination of peptide-receptor structure (original) (raw)
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Chemistry & Biology, 2001
Background: Using fixed receptor sites derived from highresolution crystal structures in structure-based drug design does not properly account for ligand-induced enzyme conformational change and imparts a bias into the discovery and design of novel ligands. We sought to facilitate the design of improved drug leads by defining residues most likely to change conformation, and then defining a minimal manifold of possible conformations of a target site for drug design based on a small number of identified flexible residues. Results: The crystal structure of thymidylate synthase from an important pathogenic target Pneumocystis carinii (PcTS) bound to its substrate and the inhibitor, BW1843U89, is reported here and reveals a new conformation with respect to the structure of PcTS bound to substrate and the more conventional antifolate inhibitor, CB3717. We developed an algorithm for determining which residues provide`soft spots' in the protein, regions where conformational adaptation suggests possible modifications for a drug lead that may yield higher affinity. Remodeling the active site of thymidylate synthase with new conformations for only three residues that were identified with this algorithm yields scores for ligands that are compatible with experimental kinetic data. Conclusions: Based on the examination of many protein/ligand complexes, we develop an algorithm (SOFTSPOTS) for identifying regions of a protein target that are more likely to accommodate plastically to regions of a drug molecule. Using these indicators we develop a second algorithm (PLASTIC) that provides a minimal manifold of possible conformations of a protein target for drug design, reducing the bias in structure-based drug design imparted by structures of enzymes co-crystallized with inhibitors.
Computational studies on protein-ligand docking
1999
This thesis describes the development and refinement of a number of techniques for molecular docking and ligand database screening, as well as the application of these techniques to predict the structures of several protein-ligand complexes and to discover novel ligands of an important receptor protein. Global energy optimisation by Monte-Carlo minimisation in internal co-ordinates was used to predict bound conformations of eight protein-ligand complexes. Experimental X-ray crystallography structures became available after the predictions were made. Comparison with the X-ray structures showed that the docking procedure placed 30 to 70% of the ligand molecule correctly within 1.5A from the native structure. The discrimination potential for identification of high-affinity ligands was derived and optimised using a large set of available protein-ligand complex structures. A fast boundary-element solvation electrostatic calculation algorithm was implemented to evaluate the solvation comp...
Docking of peptides to GPCRs using a combination of CABS-dock with FlexPepDock refinement
2020
The structural description of peptide ligands bound to G protein-coupled receptors (GPCRs) is important for the discovery of new drugs and deeper understanding of the molecular mechanisms of life. Here we describe a three-stage protocol for the molecular docking of peptides to GPCRs using a set of different programs: (1) CABS-dock for docking fully flexible peptides; (2) PD2 method for the reconstruction of atomistic structures from C-alpha traces provided by CABS-dock and (3) Rosetta FlexPepDock for the refinement of protein-peptide complex structures and model scoring. We evaluated the proposed protocol on the set of 7 different GPCR-peptide complexes (including one containing a cyclic peptide) for which crystallographic structures are available. We show that CABS-dock produces high resolution models in the sets of top-scored models. These sets of models, after reconstruction to all-atom representation, can be further improved by Rosetta high-resolution refinement and/or minimizat...
Computation of the binding of fully flexible peptides to proteins with flexible side chains
The FASEB Journal, 1997
Docking algorithms play an important role in the process of rational drug design and in understanding the mechanism of molecular recognition. An important determinant for successful docking is the extent to which the configurational space (including conformational changes) of the iigandlreceptor system is searched. Here we describe a new, combinatorial method for flexible docking of peptides to proteins that allows full rotation around all single bonds of the peptide ligand and around
PLOS ONE, 2016
Incorporating receptor flexibility in small ligand-protein docking still poses a challenge for proteins undergoing large conformational changes. In the absence of bound structures, sampling conformers that are accessible by apo state may facilitate docking and drug design studies. For this aim, we developed an unbiased conformational search algorithm, by integrating global modes from elastic network model, clustering and energy minimization with implicit solvation. Our dataset consists of five diverse proteins with apo to complex RMSDs 4.7-15 Å. Applying this iterative algorithm on apo structures, conformers close to the bound-state (RMSD 1.4-3.8 Å), as well as the intermediate states were generated. Dockings to a sequence of conformers consisting of a closed structure and its "parents" up to the apo were performed to compare binding poses on different states of the receptor. For two periplasmic binding proteins and biotin carboxylase that exhibit hinge-type closure of two dynamics domains, the best pose was obtained for the conformer closest to the bound structure (ligand RMSDs 1.5-2 Å). In contrast, the best pose for adenylate kinase corresponded to an intermediate state with partially closed LID domain and open NMP domain, in line with recent studies (ligand RMSD 2.9 Å). The docking of a helical peptide to calmodulin was the most challenging case due to the complexity of its 15 Å transition, for which a two-stage procedure was necessary. The technique was first applied on the extended calmodulin to generate intermediate conformers; then peptide docking and a second generation stage on the complex were performed, which in turn yielded a final peptide RMSD of 2.9 Å. Our algorithm is effective in producing conformational states based on the apo state. This study underlines the importance of such intermediate states for ligand docking to proteins undergoing large transitions.
Journal of the American Chemical Society, 2006
Bulky, flexible molecules such as peptides and peptidomimetics are often used as lead compounds during the drug discovery process. Pathophysiological events, e.g., the formation of amyloid fibrils in Alzheimer's disease, the conformational changes of prion proteins, or -secretase activity, may be successfully hindered by the use of rationally designed peptide sequences. A key step in the molecular engineering of such potent lead compounds is the prediction of the energetics of their binding to the macromolecular targets. Although sophisticated experimental and in silico methods are available to help this issue, the structure-based calculation of the binding free energies of large, flexible ligands to proteins is problematic. In this study, a fast and accurate calculation strategy is presented, following modification of the scoring function of the popular docking program package AutoDock and the involvement of ligandbased two-dimensional descriptors. Quantitative structure-activity relationships with good predictive power were developed. Thorough cross-validation tests and verifications were performed on the basis of experimental binding data of biologically important systems. The capabilities and limitations of the ligandbased descriptors were analyzed. Application of these results in the early phase of lead design will contribute to precise predictions, correct selections, and consequently a higher success rate of rational drug discovery.
Locating Large, Flexible Ligands on Proteins
Many biologically important ligands of proteins are large, flexible, and often charged molecules that bind to extended regions on the protein surface. It is infeasible or expensive to locate such ligands on proteins with standard methods such as docking or molecular dynamics (MD) simulation. The alternative approach proposed here is the scanning of a spatial and angular grid around the protein with smaller fragments of the large ligand. Energy values for complete grids can be computed efficiently with a well-known Fast Fourier Transform accelerated algorithm and a physically meaningful interaction model. We show that the approach can readily incorporate flexibility of protein and ligand. The energy grids (EGs) resulting from the ligand fragment scans can be transformed into probability distributions, and then directly compared to probability distributions estimated from MD simulations and experimental structural data. We test the approach on a diverse set of complexes between proteins and large, flexible ligands, including a complex of Sonic Hedgehog protein and heparin, three heparin sulfate substrates or non-substrates of an epimerase, a multi-branched supramolecular ligand that stabilizes a protein-peptide complex, and a flexible zwitterionic ligand that binds to a surface basin of a Kringle domain. In all cases the EG approach gives results that are in good agreement with experimental data or MD simulations.
Incorporating receptor flexibility in the molecular design of protein interfaces
Protein Engineering Design and Selection, 2009
The success of antibody-based pharmaceuticals has led to a resurgence in interest in computational structure-based design. Most efforts to date have been on the redesign of existing interfaces. These efforts have mostly neglected the inherent flexibility of the receptor that is critical for binding. In this work, we extend on a previous study to perform a series of designs of protein binding interfaces by incorporating receptor flexibility using an ensemble of conformers collected from explicit-solvent molecular dynamics (MD) simulations. All designer complexes are subjected to 30 ns of MD in explicit solvent to assess for stability for a total of 480 ns of dynamics. This is followed by end-point free energy calculations whereby intermolecular potential energy, polar and non-polar solvation energy and entropy of ligand and receptor are subtracted from that of the complex and averaged over 320 snapshots collected from each of the 30 ns MD simulations. Our initial effort consisted of redesigning the interface of three well-studied complexes, namely barnase-barstar, lysozyme-antibody D1.3 and trypsin-BPTI. The design was performed with flexible backbone approach. MD simulations revealed that all three complexes remained stable. Interestingly, the redesigned trypsin-BPTI complex was significantly more favorable than the native complex. This was attributed to the favorable electrostatics and entropy that complemented the already favorable non-polar component. Another aspect of this work consisted of grafting the surface of three proteins, namely tenascin, CheY and MBP1 to bind to barnase, trypsin and lysozyme. The process was initially performed using fixed backbone, and more than 300 ns of the explicitsolvent MD simulation revealed some of the complexes to dissociate over the course of the trajectories, whereas others remained stable. Free energy calculations confirmed that the non-polar component of the free energy as computed by summing the van der Waals energy and the non-polar solvation energy was a strong predictor of stability. Four complexes (two stable and two unstable) were selected, and redesigned using multiple conformers collected from the MD simulation. The resulting designer systems were then immersed in explicit solvent and 30 ns of MD was carried out on each. Interestingly, those complexes that were initially stable remained stable, whereas one of the unstable complexes became stable following redesign with flexible backbone. Free energy calculations showed significant improvements in the affinity for most complexes, revealing that the use of multiple conformers in protein design may significantly enhance such efforts.
Docking flexible molecules: A case study of three proteins
Journal of Computational Chemistry, 1995
A genetic algorithm (GA) conformation search method is used to dock a series of flexible molecules into one of three proteins. The proteins examined are thermolysin (tmn), carboxypeptidase A (cpa), and dihydrofolate reductase (dfr). In the latter two proteins, the crystal ligand was redocked. For thermolysin, we docked eight ligands into a protein conformation derived from a single crystal structure. The bound conformations of the other ligands in tmn are known. In the cpa and dfr cases, and in seven of the eight tmn ligands, the GA docking method found conformations within 1.6 A root mean square (rms) of the relaxed crystal conformation.