A poke in the eye: inhibiting HIV-1 protease through its flap-recognition pocket

A novel mechanism of inhibiting HIV-1 protease (HIVp) is presented. Using computational solvent mapping to identify complementary interactions and the Multiple Protein Structure method to incorporate protein flexibility, we generated a receptor-based pharmacophore model of the flexible flap region of the semiopen, apo state of HIVp. Complementary interactions were consistently observed at the base of the flap, only within a cleft with a specific structural role. In the closed, bound state of HIVp, each flap tip docks against the opposite monomer, occupying this cleft. This flap-recognition site is filled by the protein and cannot be identified using traditional approaches based on bound, closed structures. Virtual screening and dynamics simulations show how small molecules can be identified to complement this cleft. Subsequent experimental testing confirms inhibitory activity of this new class of inhibitor. This may be the first new inhibitor class for HIVp since dimerization inhibitors were introduced 17 years ago.     

Predicting functional residues in Plasmodium falciparum plasmepsins by combining sequence and structural analysis with molecular dynamics simulations

Plasmepsins are aspartic proteases involved in the initial steps of the hemoglobin degradation pathway, a critical stage in the Plasmodium falciparum life cycle during human infection. Thus, they are attractive targets for novel therapeutic compounds to treat malaria, which remains one of the world's biggest health problems. The three-dimensional structures available for P. falciparum plasmepsins II and IV make structure-based drug design of antimalarial compounds that focus on inhibiting plasmepsins possible. However, the structural flexibility of the plasmepsin active site cavity combined with insufficient knowledge of the functional residues and of those determining the specificity of parasitic enzymes is a drawback when designing specific inhibitors. In this study, we have combined a sequence and structural analysis with molecular dynamics simulations to predict the functional residues in P. falciparum plasmepsins. The careful analysis of X-ray structures and 3D models carried out here suggests that residues Y17, V105, T108, L191, L242, Q275, and T298 are important for plasmepsin function. These seven amino acids are conserved across the malarial strains but not in human aspartic proteases. Residues V105 and T108 are localized in a flap of an interior pocket and they only establish contacts with a specific non-peptide achiral inhibitor. We also observed a rapid conformational change in the L3 region of plasmepsins that closes the active site of the enzyme, which explains earlier experimental findings. These results shed light on the role of V105 and T108 residues in plasmepsin specificities, and they should be useful in structure-based design of novel, selective inhibitors that may serve as antimalarial drugs.     

Binding to the open conformation of HIV-1 protease

A recent crystal structure of HIV-1 protease (HIVp) was the first to experimentally observe a ligand targeting an open-flap conformation. Researchers studying a symmetric pyrrolidine inhibitor found that two ligands cocrystallized with the protease, forcing an unusual configuration and unique crystallographic contacts. One molecule is centered in the traditional binding site (α pose) and the other binds between the flaps (β pose). The ligands stack against each other in a region termed the "eye" site. Ligands bound to the eye site should prevent flap closure, but it is unclear if the pyrrolidine inhibitors or the crystal packing are causing the open state. Molecular dynamics simulations were used to examine the solution-state behavior of three possible binding modes: the ternary complex of HIVp+αβ and the binary complexes, HIVp+α and HIVp+β. We show that HIVp+α is the most stable of the three states. During conformational sampling, α takes an asymmetric binding pose, with one naphthyl ring occupying the eye site and the other reoriented down to occupy positions seen with traditional inhibitors. This finding supports previous studies that reveal a requirement for asymmetric binding at the eye site. In fact, if the α pose is modified to splay both naphthyl rings across the binding site like traditional inhibitors, one ring consistently flips to occupy the eye site. Our simulations reveal that interactions to the eye site encourage a conformationally restrained state, and understanding those contacts may aid the design of ligands to specifically target alternate conformations of the protease.     

Flexible ligand docking to multiple receptor conformations: a practical alternative

State of the art docking algorithms predict an incorrect binding pose for about 50-70% of all ligands when only a single fixed receptor conformation is considered. In many more cases, lack of receptor flexibility results in meaningless ligand binding scores, even when the correct pose is obtained. Incorporating conformational rearrangements of the receptor binding pocket into predictions of both ligand binding pose and binding score is crucial for improving structure-based drug design and virtual ligand screening methodologies. However, direct modeling of protein binding site flexibility remains challenging because of the large conformational space that must be sampled, and difficulties remain in constructing a suitably accurate energy function. Here we show that using multiple fixed receptor conformations, either experimentally determined by crystallography or NMR, or computationally generated, is a practical shortcut that may improve docking calculations. In several cases, such an approach has led to experimentally validated predictions.     

Towards structure-based protein drug design

Structure-based drug design for chemical molecules has been widely used in drug discovery in the last 30 years. Many successful applications have been reported, especially in the field of virtual screening based on molecular docking. Recently, there has been much progress in fragment-based as well as de novo drug discovery. As many protein-protein interactions can be used as key targets for drug design, one of the solutions is to design protein drugs based directly on the protein complexes or the target structure. Compared with protein-ligand interactions, protein-protein interactions are more complicated and present more challenges for design. Over the last decade, both sampling efficiency and scoring accuracy of protein-protein docking have increased significantly. We have developed several strategies for structure-based protein drug design. A grafting strategy for key interaction residues has been developed and successfully applied in designing erythropoietin receptor-binding proteins. Similarly to small-molecule design, we also tested de novo protein-binder design and a virtual screen of protein binders using protein-protein docking calculations. In comparison with the development of structure-based small-molecule drug design, we believe that structure-based protein drug design has come of age.     

Conformational Transitions upon Ligand Binding: Holo-Structure Prediction from Apo Conformations

Biological function of proteins is frequently associated with the formation of complexes with small-molecule ligands. Experimental structure determination of such complexes at atomic resolution, however, can be time-consuming and costly. Computational methods for structure prediction of protein/ligand complexes, particularly docking, are as yet restricted by their limited consideration of receptor flexibility, rendering them not applicable for predicting protein/ligand complexes if large conformational changes of the receptor upon ligand binding are involved. Accurate receptor models in the ligand-bound state (holo structures), however, are a prerequisite for successful structure-based drug design. Hence, if only an unbound (apo) structure is available distinct from the ligand-bound conformation, structure-based drug design is severely limited. We present a method to predict the structure of protein/ligand complexes based solely on the apo structure, the ligand and the radius of gyration of the holo structure. The method is applied to ten cases in which proteins undergo structural rearrangements of up to 7.1 Å backbone RMSD upon ligand binding. In all cases, receptor models within 1.6 Å backbone RMSD to the target were predicted and close-to-native ligand binding poses were obtained for 8 of 10 cases in the top-ranked complex models. A protocol is presented that is expected to enable structure modeling of protein/ligand complexes and structure-based drug design for cases where crystal structures of ligand-bound conformations are not available.     

Conformational control in structure-based drug design

In structure-based drug design, the basic goal is to design molecules that fit complementarily to a given binding pocket. Since such computationally modeled molecules may not adopt the intended bound conformation outside the binding pocket, one challenge is to ensure that the designed ligands adopt similar low energy conformations both inside and outside of the binding pocket. Computational chemistry methods and conformational preferences of small molecules from PDB and Cambridge Structural Database (CSD) can be used to predict the bound structures of the designed molecules. Herein, we review applications of conformational control in structure-based drug design using selected examples from the recent medicinal chemistry literature. The main purpose is to highlight some intriguing conformational features that can be applied to other drug discovery programs.     

Ab initio folding of proteins with all-atom discrete molecular dynamics

Discrete molecular dynamics (DMD) is a rapid sampling method used in protein folding and aggregation studies. Until now, DMD was used to perform simulations of simplified protein models in conjunction with structure-based force fields. Here, we develop an all-atom protein model and a transferable force field featuring packing, solvation, and environment-dependent hydrogen bond interactions. We performed folding simulations of six small proteins (20-60 residues) with distinct native structures by the replica exchange method. In all cases, native or near-native states were reached in simulations. For three small proteins, multiple folding transitions are observed, and the computationally characterized thermodynamics are in qualitative agreement with experiments. The predictive power of all-atom DMD highlights the importance of environment-dependent hydrogen bond interactions in modeling protein folding. The developed approach can be used for accurate and rapid sampling of conformational spaces of proteins and protein-protein complexes and applied to protein engineering and design of protein-protein interactions.     

Structural adaptation of extreme halophilic proteins through decrease of conserved hydrophobic contact surface

Background

Disrupting protein-protein interactions by small organic molecules is nowadays a promising strategy employed to block protein targets involved in different pathologies. However, structural changes occurring at the binding interfaces make difficult drug discovery processes using structure-based drug design/virtual screening approaches. Here we focused on two homologous calcium binding proteins, calmodulin and human centrin 2, involved in different cellular functions via protein-protein interactions, and known to undergo important conformational changes upon ligand binding.

Results

In order to find suitable protein conformations of calmodulin and centrin for further structure-based drug design/virtual screening, we performed in silico structural/energetic analysis and molecular docking of terphenyl (a mimicking alpha-helical molecule known to inhibit protein-protein interactions of calmodulin) into X-ray and NMR ensembles of calmodulin and centrin. We employed several scoring methods in order to find the best protein conformations. Our results show that docking on NMR structures of calmodulin and centrin can be very helpful to take into account conformational changes occurring at protein-protein interfaces.

Conclusions

NMR structures of protein-protein complexes nowadays available could efficiently be exploited for further structure-based drug design/virtual screening processes employed to design small molecule inhibitors of protein-protein interactions.     

Computational study of EGFR inhibition: molecular dynamics studies on the active and inactive protein conformations

The structural diversity observed across protein kinases, resulting in subtly different active site cavities, is highly desirable in the pursuit of selective inhibitors, yet it can also be a hindrance from a structure-based design perspective. An important challenge in structure-based design is to better understand the dynamic nature of protein kinases and the underlying reasons for specific conformational preferences in the presence of different inhibitors. To investigate this issue, we performed molecular dynamics simulation on both the active and inactive wild type epidermal growth factor receptor (EGFR) protein with both type-I and type-II inhibitors. Our goal is to better understand the origin of the two distinct EGFR protein conformations, their dynamic differences, and their relative preference for Type-I inhibitors such as gefitinib and Type-II inhibitors such as lapatinib. We discuss the implications of protein dynamics from a structure-based design perspective.     

Crystal structures of DPP-IV (CD26) from rat kidney exhibit flexible accommodation of peptidase-selective inhibitors

Dipeptidyl peptidase IV (DPP-IV) belongs to a family of serine peptidases, and due to its indirect regulatory role in plasma glucose modulation, DPP-IV has become an attractive pharmaceutical target for diabetes therapy. DPP-IV inactivates the glucagon-like peptide (GLP-1) and several other naturally produced bioactive peptides that contain preferentially a proline or alanine residue in the second amino acid sequence position by cleaving the N-terminal dipeptide. To elucidate the details of the active site for structure-based drug design, we crystallized a natural source preparation of DPP-IV isolated from rat kidney and determined its three-dimensional structure using X-ray diffraction techniques. With a high degree of similarity to structures of human DPP-IV, the active site architecture provides important details for the design of inhibitory compounds, and structures of inhibitor-protein complexes offer detailed insight into three-dimensional structure-activity relationships that include a conformational change of Tyr548. Such accommodation is exemplified by the response to chemical substitution on 2-cyanopyrrolidine inhibitors at the 5 position, which conveys inhibitory selectivity for DPP-IV over closely related homologues. A similar conformational change is also observed in the complex with an unrelated synthetic inhibitor containing a xanthine core that is also selective for DPP-IV. These results suggest the conformational flexibility of Tyr548 is unique among protein family members and may be utilized in drug design to achieve peptidase selectivity.     

Intricacies of interactions,dynamics and solvent effects in enzyme catalysis: a computational perspective on cyclophilin A

The essential role of enzymes in biological processes has continually ignited sparks of interest in their mechanism of action. Fully understanding the mechanism of enzymes has broad implications in protein engineering and drug design. The more than five order of magnitude speed-up in the rate of peptidyl–prolyl cis–trans isomerisation by cyclophilin A (CypA) has been the target of intense research. CypA serves as a tractable model system, because it reversibly catalyses the rotation around peptidyl–prolyl bonds without any bond breakage or formation. Here, we discuss the results of recent computational approaches used to study the mechanism of CypA. We highlight the critical role of enzyme and substrate conformational dynamics in the developing interactions as the substrate approaches the transition state that results in an astonishing enhancement of isomerisation rate. The rate of isomerisation is affected by the intricate coupling between the dynamics of the substrate, enzyme and solvent. CypA binds its substrates via conformational selection, where rearrangements of key active site residues are necessary for substrate recognition. The conformational plasticity of the active site allows the enzyme to accommodate the most favourable interactions with the transition state that can be exploited for structure-based drug design.     

Retrospective molecular docking study of WY-25105 ligand to β-secretase and bias of the three-dimensional structure flexibility

β-Secretase (BACE) is a very promising target in the search for a treatment for Alzheimer’s disease using a protein–ligand inhibition approach. Given the many published X-ray structures of BACE protein, structure-based drug design has been used extensively to support new inhibitor discovery programs. Due to the high flexibility and large catalytic site of this protein, sampling of the huge conformational space of the binding site is the big challenge to overcome and is the main limitation of the most widely used docking programs. Incorrect treatment of these pitfalls can introduce bias into ligand docking and could affect the results. This is especially the case with the WY-25105 compound reported by the Wyeth Corporation as a BACE ligand that did not fit into any of the known crystal structures. In the present retrospective study, a set of available X-ray enzyme structures was selected and molecular dynamics simulations were conducted to generate more diverse representative BACE protein conformations. These conformations were then used for a docking study of the WY-25105 compound. The results confirmed the need to use an ensemble of structures in protein–ligand docking for identification of new binding modes in structure-based drug design of BACE inhibitors.

Structural proteomics in drug discovery

High-throughput, automated or semiautomated methodologies implemented by companies and structural genomics initiatives have accelerated the process of acquiring structural information for proteins via x-ray crystallography. This has enabled the application of structure-based drug design technologies to a variety of new structures that have potential pharmacologic relevance. Although there remain major challenges to applying these approaches more broadly to all classes of drug discovery targets, clearly the continued development and implementation of these structure-based drug design methodologies by the scientific community at large will help to address and provide solutions to these hurdles. The result will be a growing number of protein structures of important pharmacologic targets that will help to streamline the process of identification and optimization of lead compounds for drug development. These lead agonist and antagonist pharmacophores should, in turn, help to alleviate one of the current critical bottlenecks in the drug discovery process; that is, defining the functional relevance of potential novel targets to disease modification. The prospect of generating an increasing number of potential drug candidates will serve to highlight perhaps the most significant future bottleneck for drug development, the cost and complexity of the drug approval process.     

On the development of protein pKa calculation algorithms

Protein pK(a) calculation methods are developed partly to provide fast non-experimental estimates of the ionization constants of protein side chains. However, the most significant reason for developing such methods is that a good pK(a) calculation method is presumed to provide an accurate physical model of protein electrostatics, which can be applied in methods for drug design, protein design, and other structure-based energy calculation methods. We explore the validity of this presumption by simulating the development of a pK(a) calculation method using artificial experimental data derived from a human-defined physical reality. We examine the ability of an RMSD-guided development protocol to retrieve the correct (artificial) physical reality and find that a rugged optimization landscape and a huge parameter space prevent the identification of the correct physical reality. We examine the importance of the training set in developing pK(a) calculation methods and investigate the effect of experimental noise on our ability to identify the correct physical reality, and find that both effects have a significant and detrimental impact on the physical reality of the optimal model identified. Our findings are of relevance to all structure-based methods for protein energy calculations and simulation, and have large implications for all types of current pK(a) calculation methods. Our analysis furthermore suggests that careful and extensive validation on many types of experimental data can go some way in making current models more realistic.     

Structural proteomics in drug discovery

High-throughput, automated or semiautomated methodologies implemented by companies and structural genomics initiatives have accelerated the process of acquiring structural information for proteins via x-ray crystallography. This has enabled the application of structure-based drug design technologies to a variety of new structures that have potential pharmacologic relevance. Although there remain major challenges to applying these approaches more broadly to all classes of drug discovery targets, clearly the continued development and implementation of these structure-based drug design methodologies by the scientific community at large will help to address and provide solutions to these hurdles. The result will be a growing number of protein structures of important pharmacologic targets that will help to streamline the process of identification and optimization of lead compounds for drug development. These lead agonist and antagonist pharmacophores should, in turn, help to alleviate one of the current critical bottlenecks in the drug discovery process; that is, defining the functional relevance of potential novel targets to disease modification. The prospect of generating an increasing number of potential drug candidates will serve to highlight perhaps the most significant future bottleneck for drug development, the cost and complexity of the drug approval process.     

From receptor recognition mechanisms to bioinspired mimetic antagonists in HIV-1/cell docking

Understanding the ways in which two or more proteins interact may give insight into underlying binding and activation mechanisms in biology, methods for protein separation and structure-based antagonism. This review describes ways in which protein recognition has been explored in our laboratory for the HIV-1/cell entry process. Initial contact between an HIV-1 virion particle and a human cell occurs between gp120 (an HIV-1 envelope protein) and CD4 (a human extracellular signaling protein). This interaction leads to a sequence of events which includes a conformational change in gp120, fusion of the HIV-1 and cellular membranes and eventual infection of the cell. Using an optical biosensor and a reporter antibody, we have been able to measure the conformational change in gp120 that occurs upon CD4 binding. We also have used this biosensor system to characterize CD4 mimetics, obtained by peptide synthesis in miniprotein scaffolds. Phage display techniques have been employed to identify novel miniprotein sequences. The combination of biosensor interaction kinetics analysis and phage display provides a useful approach for understanding the recognition mechanisms involved in the HIV/cell docking process. This approach may also be useful in investigating other protein complexes of importance in health and disease.