Binding mode prediction for a flexible ligand in a flexible pocket using multi-conformation simulated annealing pseudo crystallographic refinement

Structure-based Methods for Binding Mode and Binding Affinity Prediction for Peptide-MHC Complexes

Understanding the mechanisms involved in the activation of an immune response is essential to many fields in human health, including vaccine development and personalized cancer immunotherapy. A central step in the activation of the adaptive immune response is the recognition, by T-cell lymphocytes, of peptides displayed by a special type of receptor known as Major Histocompatibility Complex (MHC). Considering the key role of MHC receptors in T-cell activation, the computational prediction of peptide binding to MHC has been an important goal for many immunological applications. Sequence- based methods have become the gold standard for peptide-MHC binding affinity prediction, but structure-based methods are expected to provide more general predictions (i.e., predictions applicable to all types of MHC receptors). In addition, structural modeling of peptide-MHC complexes has the potential to uncover yet unknown drivers of T-cell activation, thus allowing for the development of better and safer therapies. In this review, we discuss the use of computational methods for the structural modeling of peptide-MHC complexes (i.e., binding mode prediction) and for the structure-based prediction of binding affinity.

Protein flexibility in docking and surface mapping

Structure-based drug design has become an essential tool for rapid lead discovery and optimization. As available structural information has increased, researchers have become increasingly aware of the importance of protein flexibility for accurate description of the native state. Typical protein-ligand docking efforts still rely on a single rigid receptor, which is an incomplete representation of potential binding conformations of the protein. These rigid docking efforts typically show the best performance rates between 50 and 75%, while fully flexible docking methods can enhance pose prediction up to 80-95%. This review examines the current toolbox for flexible protein-ligand docking and receptor surface mapping. Present limitations and possibilities for future development are discussed.

Drug design for ever, from hype to hope

In its first 25 years JCAMD has been disseminating a large number of techniques aimed at finding better medicines faster. These include genetic algorithms, COMFA, QSAR, structure based techniques, homology modelling, high throughput screening, combichem, and dozens more that were a hype in their time and that now are just a useful addition to the drug-designers toolbox. Despite massive efforts throughout academic and industrial drug design research departments, the number of FDA-approved new molecular entities per year stagnates, and the pharmaceutical industry is reorganising accordingly. The recent spate of industrial consolidations and the concomitant move towards outsourcing of research activities requires better integration of all activities along the chain from bench to bedside. The next 25 years will undoubtedly show a series of translational science activities that are aimed at a better communication between all parties involved, from quantum chemistry to bedside and from academia to industry. This will above all include understanding the underlying biological problem and optimal use of all available data.

Structure-based discovery of antibacterial drugs

The modern era of antibacterial chemotherapy began in the 1930s, and the next four decades saw the discovery of almost all the major classes of antibacterial agents that are currently in use. However, bacterial resistance to many of these drugs is becoming an increasing problem. As such, the discovery of drugs with novel modes of action will be vital to meet the threats created by the emergence of resistance. Success in discovering inhibitors using high-throughput screening of chemical libraries is rare. In this Review we explore the exciting opportunities for antibacterial-drug discovery arising from structure-based drug design.

Identification of a function-specific mutation of clathrin heavy chain (CHC) required for p53 transactivation

The p53 pathway is activated in response to various cellular stresses to protect cells from malignant transformation. We have previously shown that clathrin heavy chain (CHC), which is a cytosolic protein regulating endocytosis, is present in nuclei and binds to p53 to promote p53-mediated transcription. However, details of the binding interface between p53 and CHC remain unclear. Here, we report on the binding mode between p53 and CHC using mutation analyses and a structural model of the interaction generated by molecular dynamics. Structural modeling analyses predict that an Asn1288 residue in CHC is crucial for binding to p53. In fact, substitution of this Asn to Ala of CHC diminished its ability to interact with p53, leading to reduced activity to transactivate p53. Surprisingly, this mutation had little effect on receptor-mediated endocytosis. Thus, the function-specific mutation of CHC will clarify physiological roles of CHC in the regulation of the p53 pathway.

Novel Binding Sites on Clathrin and Adaptors Regulate Distinct Aspects of Coat Assembly

Clathrin-coated vesicles (CCVs) sort proteins at the plasma membrane, endosomes and trans Golgi network for multiple membrane traffic pathways. Clathrin recruitment to membranes and its self-assembly into a polyhedral coat depends on adaptor molecules, which interact with membrane-associated vesicle cargo. To determine how adaptors induce clathrin recruitment and assembly, we mapped novel interaction sites between these coat components. A site in the ankle domain of the clathrin triskelion leg was identified that binds a common site on the appendages of tetrameric [AP1 and AP2] and monomeric (GGA1) adaptors. Mutagenesis and modeling studies suggested that the clathrin-GGA1 appendage interface is nonlinear, unlike other peptide-appendage interactions, but overlaps with a sandwich domain binding site for accessory protein peptides, allowing for competitive regulation of coated vesicle formation. A novel clathrin box in the GGA1 hinge region was also identified and shown to mediate membrane recruitment of clathrin, while disruption of the clathrin-GGA1 appendage interaction did not affect recruitment. Thus, the distinct sites for clathrin-adaptor interactions perform distinct functions, revealing new aspects to regulation of CCV formation.

Structural prediction of peptides binding to MHC class I molecules

Peptide binding to class I major histocompatibility complex (MHCI) molecules is a key step in the immune response and the structural details of this interaction are of importance in the design of peptide vaccines. Algorithms based on primary sequence have had success in predicting potential antigenic peptides for MHCI, but such algorithms have limited accuracy and provide no structural information. Here, we present an algorithm, PePSSI (peptide-MHC prediction of structure through solvated interfaces), for the prediction of peptide structure when bound to the MHCI molecule, HLA-A2. The algorithm combines sampling of peptide backbone conformations and flexible movement of MHC side chains and is unique among other prediction algorithms in its incorporation of explicit water molecules at the peptide-MHC interface. In an initial test of the algorithm, PePSSI was used to predict the conformation of eight peptides bound to HLA-A2, for which X-ray data are available. Comparison of the predicted and X-ray conformations of these peptides gave RMSD values between 1.301 and 2.475 A. Binding conformations of 266 peptides with known binding affinities for HLA-A2 were then predicted using PePSSI. Structural analyses of these peptide-HLA-A2 conformations showed that peptide binding affinity is positively correlated with the number of peptide-MHC contacts and negatively correlated with the number of interfacial water molecules. These results are consistent with the relatively hydrophobic binding nature of the HLA-A2 peptide binding interface. In summary, PePSSI is capable of rapid and accurate prediction of peptide-MHC binding conformations, which may in turn allow estimation of MHCI-peptide binding affinity.

Binding of the viral immunogenic octapeptide VSV8 to native glucose-regulated protein Grp94 (gp96) and its inhibition by the physiological ligands ATP and Ca2+

The molecular chaperone Grp94 (gp96) of the endoplasmic reticulum (ER) lumen plays an essential role in the structural maturation and/or secretion of proteins destined for transport to the cell surface. Its proposed role in binding and transferring peptides for immune recognition is, however, controversial. Using SPR spectroscopy, we studied the interaction of native glycosylated Grp94 at neutral pH and 25 and 37 degrees C with the viral immunogenic octapeptide RGYVYQGL (VSV8), derived from vesicular stomatitis virus nucleoprotein (52-59). The peptide binds reversibly with low affinity ([A]0.5 approximately 640 microM) and a hyperbolic binding isotherm, and the binding is partially inhibited by ATP and Ca2+ at concentrations that are present in the ER lumen, and the effects are explained by conformational changes in the native chaperone induced by these ligands. Our data present experimental support for the recent proposal that, under native conditions, VSV8 binds to Grp94 by an adsorptive, rather than a bioselective, mechanism, and thus further challenge the proposed in vivo peptide acceptor-donor function of the chaperone in the context of antigen-presenting cell activation.

Anchor profiles of HLA-specific peptides: analysis by a novel affinity scoring method and experimental validation

The study of intermolecular interactions is a fundamental research subject in biology. Here we report on the development of a quantitative structure-based affinity scoring method for peptide-protein complexes, named PepScope. The method operates on the basis of a highly specific force field function (CHARMM) that is applied to all-atom structural representations of peptide-receptor complexes. Peptide side-chain contributions to total affinity are scored after detailed rotameric sampling followed by controlled energy refinement. A de novo approach to estimate dehydration energies was developed, based on the simulation of individual amino acids in a solvent box filled with explicit water molecules. Transferability of the method was demonstrated by its application to the hydrophobic HLA-A2 and -A24 receptors, the polar HLA-A1, and the sterically ruled HLA-B7 receptor. A combined theoretical and experimental study on 39 anchor substitutions in FxSKQYMTx/HLA-A2 and -A24 complexes indicated a prediction accuracy of about two thirds of a log-unit in Kd. Analysis of free energy contributions identified a great role of desolvation and conformational strain effects in establishing a given specificity profile. Interestingly, the method rightly predicted that most anchor profiles are less specific than so far assumed. This suggests that many potential T-cell epitopes could be missed with current prediction methods. The results presented in this work may therefore significantly affect T-cell epitope discovery programs applied in the field of peptide vaccine development.

Structural prediction of peptides bound to MHC class I

An ab initio structure prediction approach adapted to the peptide-major histocompatibility complex (MHC) class I system is presented. Based on structure comparisons of a large set of peptide-MHC class I complexes, a molecular dynamics protocol is proposed using simulated annealing (SA) cycles to sample the conformational space of the peptide in its fixed MHC environment. A set of 14 peptide-human leukocyte antigen (HLA) A0201 and 27 peptide-non-HLA A0201 complexes for which X-ray structures are available is used to test the accuracy of the prediction method. For each complex, 1000 peptide conformers are obtained from the SA sampling. A graph theory clustering algorithm based on heavy atom root-mean-square deviation (RMSD) values is applied to the sampled conformers. The clusters are ranked using cluster size, mean effective or conformational free energies, with solvation free energies computed using Generalized Born MV 2 (GB-MV2) and Poisson-Boltzmann (PB) continuum models. The final conformation is chosen as the center of the best-ranked cluster. With conformational free energies, the overall prediction success is 83% using a 1.00 Angstroms crystal RMSD criterion for main-chain atoms, and 76% using a 1.50 Angstroms RMSD criterion for heavy atoms. The prediction success is even higher for the set of 14 peptide-HLA A0201 complexes: 100% of the peptides have main-chain RMSD values < or =1.00 Angstroms and 93% of the peptides have heavy atom RMSD values < or =1.50 Angstroms. This structure prediction method can be applied to complexes of natural or modified antigenic peptides in their MHC environment with the aim to perform rational structure-based optimizations of tumor vaccines.

The process of structure-based drug design

The field of structure-based drug design is a rapidly growing area in which many successes have occurred in recent years. The explosion of genomic, proteomic, and structural information has provided hundreds of new targets and opportunities for future drug lead discovery. This review summarizes the process of structure-based drug design and includes, primarily, the choice of a target, the evaluation of a structure of that target, the pivotal questions to consider in choosing a method for drug lead discovery, and evaluation of the drug leads. Key principles in the field of structure-based drug design will be illustrated through a case study that explores drug design for AmpC beta-lactamase.

MHC–Peptide Binding is Assisted by Bound Water Molecules

Water plays an important role in determining the high affinity of epitopes to the class I MHC complex. To study the energy and dynamics of water interactions in the complex we performed molecular dynamics simulation of the class I MHC-HLA2 complex bound to the HIV reverse transcriptase epitope, ILKEPVHGV, and in the absence of the epitope. Each simulation was extended for 5ns. We studied the processes of water penetration in the interface between MHC and peptide, and identified 14 water molecules that stay bound for periods longer than 1ns in regions previously identified by crystallography. These water molecules in the interface perform definite "tasks" contributing to the binding energy: hydrogen bond bridges between MHC and peptide and filling empty spaces in the groove which enhance affinity without contributing to epitope specificity. We calculate the binding energy for interfacial water molecules and find that there is an overall gain in free energy resulting from the formation of water clusters at the epitope-MHC interface. Water molecules serving the task of filling empty spaces bind at the interface with a net gain in entropy, relative to their entropy in bulk. We conclude that water molecules at the interface play the role of active mediators in the MHC-peptide interaction, and might be responsible for the large binding affinity of the MHC complex to a large number of epitope sequences.

Improved prediction of HIV-1 protease-inhibitor binding energies by molecular dynamics simulations

BACKGROUND

The accurate prediction of enzyme-substrate interaction energies is one of the major challenges in computational biology. This study describes the improvement of protein-ligand binding energy prediction by incorporating protein flexibility through the use of molecular dynamics (MD) simulations.

RESULTS

Docking experiments were undertaken using the program AutoDock for twenty-five HIV-1 protease-inhibitor complexes determined by x-ray crystallography. Protein-rigid docking without any dynamics produced a low correlation of 0.38 between the experimental and calculated binding energies. Correlations improved significantly for all time scales of MD simulations of the receptor-ligand complex. The highest correlation coefficient of 0.87 between the experimental and calculated energies was obtained after 0.1 picoseconds of dynamics simulation.

CONCLUSION

Our results indicate that relaxation of protein complexes by MD simulation is useful and necessary to obtain binding energies that are representative of the experimentally determined values.

Efficient conformational sampling of local side-chain flexibility

Side-chain flexibility of ligand-binding sites needs to be considered in the rational design of novel inhibitors. We have developed a method to generate conformational ensembles that efficiently sample local side-chain flexibility from a single crystal structure. The rotamer-based approach is tested here for the S1' pocket of human collagenase-1 (MMP-1), which is known to undergo conformational changes in multiple side-chains upon binding of certain inhibitors. First, a raw ensemble consisting of a large number of conformers of the S1' pocket was generated using an exhaustive search of rotamer combinations on a template crystal structure. A combination of principal component analysis and fuzzy clustering was then employed to successfully identify a core ensemble consisting of a low number of representatives from the raw ensemble. The core ensemble contained geometrically diverse conformers of stable nature, as indicated in several cases by a relative energy lower than that of the minimised template crystal structure. Through comparisons with X-ray crystallography and NMR structural data we show that the core ensemble occupied a conformational space similar to that observed under experimental conditions. The synthetic inhibitor RS-104966 is known to induce a conformational change in the side-chains of the S1' pocket of MMP-1 and could not be docked in the template crystal structure. However, the experimental binding mode was reproduced successfully using members of the core ensemble as the docking target, establishing the usefulness of the method in drug design.

Clathrin light and heavy chain interface: alpha-helix binding superhelix loops via critical tryptophans

Clathrin light chain subunits (LCa and LCb) contribute to regulation of coated vesicle formation to sort proteins during receptor-mediated endocytosis and organelle biogenesis. LC binding to clathrin heavy chain (HC) was characterized by genetic and structural approaches. The core interactions were mapped to HC residues 1267-1522 (out of 1675) and LCb residues 90-157 (out of 228), using yeast two-hybrid assays. The C-termini of both subunits also displayed interactions extending beyond the core domains. Mutations to helix breakers within the LCb core disrupted HC association. Further suppressor mutagenesis uncovered compensatory mutations in HC (K1415E or K1326E) capable of rescuing the binding defects of LCb mutations W127R or W105R plus W138R, thereby pinpointing contacts between HC and LCb. Mutant HC K1415E also rescued loss of binding by LCa W130R, indicating that both LCs interact similarly with HC. Based on circular dichroism data, mapping and mutagenesis, LCa and LCb were represented as alpha-helices, aligned along the HC and, using molecular dynamics, a structural model of their interaction was generated with novel implications for LC control of clathrin assembly.

Protein flexibility and drug design: how to hit a moving target

The most advanced methods for computer-aided drug design and database mining incorporate protein flexibility. Such techniques are not only needed to obtain proper results; they are also critical for dealing with the growing body of information from structural genomics.