Simulating protein flexibility is a major issue in the docking-based drug-design process for which a single methodological solution does not exist. In our search of new anti-Alzheimer ligands, we were faced with the challenge of including receptor plasticity in a virtual screening campaign aimed at finding new β-Secretase inhibitors. To this aim, we incorporated protein flexibility in our simulations by using an ensemble of static X-ray enzyme structures to screen the National Cancer Institute database. A unified description of the protein motion was also generated by computing and combining a set of grid maps using an energy weighting scheme. Such a description was used in an energy-weighted virtual screening experiment on the same molecular database. Assessment of the enrichment factors from these two virtual screening approaches demonstrated comparable predictive powers, with the energy-weighted method being faster than the ensemble method. The in vitro evaluation demonstrated that out of the 32 tested ligands, 17 featured the predicted enzyme inhibiting property. Such an impressive success rate (53.1%) demonstrates the enhanced power of the two methodologies and suggests that energy-weighted virtual screening is a more than valid alternative to ensemble virtual screening given its reduced computational demands and comparable performance.
Docking; Virtual Screening; Receptor Flexibility; Drug Design; BACE-1
In modeling ligand-protein interactions, the representation and role of water is of great importance. We introduce a forcefield and hydration docking method that enables the automated prediction of waters mediating the binding of ligands with target proteins. The method presumes no prior knowledge of the apo or holo protein hydration state, and is potentially useful in the process of structure-based drug discovery. The hydration forcefield accounts for the entropic and enthalpic contributions of discrete waters to ligand binding, improving energy estimation accuracy and docking performance. The forcefield has been calibrated and validated on a total of 417 complexes (197 training set; 220 test set), then tested in cross-docking experiments, for a total of 1649 ligand-protein complexes evaluated. The method is computationally efficient and was used to model up to 35 waters during docking. The method was implemented and tested using unaltered AutoDock4 with new forcefield tables.
We describe the testing and release of AutoDock4 and the accompanying graphical user interface AutoDockTools. AutoDock4 incorporates limited flexibility in the receptor. Several tests are reported here, including a redocking experiment with 188 diverse ligand-protein complexes and a cross-docking experiment using flexible sidechains in 87 HIV protease complexes. We also report its utility in analysis of covalently-bound ligands, using both a grid-based docking method and a modification of the flexible sidechain technique.
AutoDock; computational docking; protein flexibility; covalent ligands; computer-aided drug design
Signaling of the tissue factor-FVIIa complex regulates angiogenesis, tumor growth and inflammation. TF-FVIIa triggers cell signaling events by cleavage of protease activated receptor (PAR2) at the Arg36-Ser37 scissile bond. The recognition of PAR2 by the FVIIa protease domain is poorly understood. We perform molecular modeling and dynamics simulations to derive the PAR2-FVIIa interactions. Docking of the PAR2 Arg36-Ser37 scissile bond to the S1 site and subsequent molecular dynamics leads to interactions of the PAR2 ectodomain with P and P’ sites of the FVIIa catalytic cleft as well as to electrostatic interactions between a stably folded region of PAR2 and a cluster of basic residues remote from the catalytic cleft of FVIIa. To address the functional significance of this interaction for PAR2 cleavage, we employed two antibodies with epitopes previously mapped to this cluster of basic residues. Although these antibodies do not block the catalytic cleft, both antibodies completely abrogated PAR2 activation by TF-FVIIa. Our simulations indicate a conformation of the PAR2 ectodomain that limits the cleavage site to no more than 33 A from its membrane proximal residue. Since the active site of FVIIa in the TF-FVIIa complex is ~ 75A above the membrane, cleavage of the folded conformation of PAR2 would require tilting of the TF-FVIIa complex toward the membrane, indicating that additional cellular factors may be required to properly align the scissile bond of PAR2 with TF-FVIIa.
TF-FVIIa signaling; PAR2 cleavage; serine protease; molecular dynamics simulation
Crystal structures of the 6s-98S FIV protease chimera with darunavir and lopinavir bound have been determined at 1.7 and 1.8 Å resolution, respectively.
A chimeric feline immunodeficiency virus (FIV) protease (PR) has been engineered that supports infectivity but confers sensitivity to the human immunodeficiency virus (HIV) PR inhibitors darunavir (DRV) and lopinavir (LPV). The 6s-98S PR has five replacements mimicking homologous residues in HIV PR and a sixth which mutated from Pro to Ser during selection. Crystal structures of the 6s-98S FIV PR chimera with DRV and LPV bound have been determined at 1.7 and 1.8 Å resolution, respectively. The structures reveal the role of a flexible 90s loop and residue 98 in supporting Gag processing and infectivity and the roles of residue 37 in the active site and residues 55, 57 and 59 in the flap in conferring the ability to specifically recognize HIV PR drugs. Specifically, Ile37Val preserves tertiary structure but prevents steric clashes with DRV and LPV. Asn55Met and Val59Ile induce a distinct kink in the flap and a new hydrogen bond to DRV. Ile98Pro→Ser and Pro100Asn increase 90s loop flexibility, Gln99Val contributes hydrophobic contacts to DRV and LPV, and Pro100Asn forms compensatory hydrogen bonds. The chimeric PR exhibits a comparable number of hydrogen bonds, electrostatic interactions and hydrophobic contacts with DRV and LPV as in the corresponding HIV PR complexes, consistent with IC50 values in the nanomolar range.
chimeric FIV/HIV protease; feline immunodeficiency virus; darunavir; lopinavir
Increasingly complex research has made it more difficult to prepare data for publication, education, and outreach. Many scientists must also wade through black-box code to interface computational algorithms from diverse sources to supplement their bench work. To reduce these barriers, we have developed an open-source plug-in, embedded Python Molecular Viewer (ePMV), that runs molecular modeling software directly inside of professional 3D animation applications (hosts) to provide simultaneous access to the capabilities of these newly connected systems. Uniting host and scientific algorithms into a single interface allows users from varied backgrounds to assemble professional quality visuals and to perform computational experiments with relative ease. By enabling easy exchange of algorithms, ePMV can facilitate interdisciplinary research, smooth communication between broadly diverse specialties and provide a common platform to frame and visualize the increasingly detailed intersection(s) of cellular and molecular biology.
Nucleocytoplasmic transport of macromolecules is a fundamental process of eukaryotic cells. Translocation of proteins and many RNAs between the nucleus and cytoplasm is carried out by shuttling receptors of the β-karyopherin family, also called importins and exportins. Leptomycin B, a small molecule inhibitor of the exportin CRM1, has proved to be an invaluable tool for cell biologists, but up to now no small molecule inhibitors of nuclear import have been described. We devised a microtiter plate based permeabilized cell screen for small molecule inhibitors of the importin α/β pathway. By analyzing peptidomimetic libraries, we identified β-turn and α-helix peptidomimetic compounds that selectively inhibit nuclear import by importin α/β but not by transportin. Structure-activity relationship analysis showed that large aromatic residues and/or a histidine side chain are required for effective import inhibition by these compounds. Our validated inhibitors can be useful for in vitro studies of nuclear import, and can also provide a framework for synthesis of higher potency nuclear import inhibitors.
high content screening; nucleocytoplasmic transport; importin β; small molecule inhibitor; peptidomimetics
α-Cobratoxin (Cbtx), the neurotoxin isolated from the venom of the Thai cobra Naja kaouthia, causes paralysis by preventing acetylcholine (ACh) binding to nicotinic acetylcholine receptors (nAChRs). In the current study, the region of the Cbtx molecule that is directly involved in binding to nAChRs is used as the target for anticobratoxin drug design. The crystal structure (1YI5) of Cbtx in complex with the acetylcholine binding protein (AChBP), a soluble homolog of the extracellular binding domain of nAChRs, was selected to prepare an α-cobratoxin active binding site for docking. The amino acid residues (Ser182-Tyr192) of the AChBP structure, the binding site of Cbtx, were used as the positive control to validate the prepared Cbtx active binding site (root mean square deviation < 1.2 Å). Virtual screening of the National Cancer Institute diversity set, a library of 1990 compounds with nonredundant pharmacophore profiles, using AutoDock against the Cbtx active site, revealed 39 potential inhibitor candidates. The adapted in vitro radioligand competition assays using [3H]epibatidine and [125I]bungarotoxin against the AChBPs from the marine species, Aplysia californica (Ac), and from the freshwater snails, Lymnaea stagnalis (Ls) and Bolinus truncates (Bt), revealed 4 compounds from the list of inhibitor candidates that had micromolar to nanomolar interferences for the toxin binding to AChBPs. Three hits (NSC42258, NSC121865, and NSC134754) can prolong the survival time of the mice if administered 30 min before injection with Cbtx, but only NSC121865 and NSC134754 can prolong the survival time if injected immediately after injection with Cbtx. These inhibitors serve as novel templates/scaffolds for the development of more potent and specific anticobratoxin.
α-cobratoxin; virtual screening; docking; neurotoxin; nicotinic acetylcholine receptor
Importance to the field
Virtual screening is a computer-based technique for identifying promising compounds to bind to a target molecule of known structure. Given the rapidly increasing number of protein and nucleic acid structures, virtual screening continues to grow as an effective method for the discovery of new inhibitors and drug molecules.
Areas covered in this review
We describe virtual screening methods that are available in the AutoDock suite of programs, and several of our successes in using AutoDock virtual screening in pharmaceutical lead discovery.
What the reader will gain
A general overview of the challenges of virtual screening is presented, along with the tools available in the AutoDock suite of programs for addressing these challenges.
Take home message
Virtual screening is an effective tool for the discovery of compounds for use as leads in drug discovery, and the free, open source program AutoDock is an effective tool for virtual screening.
virtual screening; computer-aided drug design; computational docking; AutoDock
Human immunodeficiency virus type 1 (HIV-1) integrase is one of three virally encoded enzymes essential for replication and, therefore, a rational choice as a drug target for the treatment of HIV-1 infected individuals. In 2007 raltegravir became the first integrase inhibitor approved for use in the treatment of HIV infected patients, more than a decade since the approval of the first protease inhibitor (saquinavir, Hoffman La-Roche, 1995) and two decades since the approval of the first reverse transcriptase inhibitor (retrovir, Glaxo Smithkline, 1987). The slow progress towards a clinically effective HIV-1 integrase inhibitor can at least in part be attributed to a poor structural understanding of this key viral protein.
Here we describe the development of a restrained molecular dynamics protocol that produces a more accurate model of the active site of this drug target. This model provides an advance on previously described models as it ensures that the catalytic DDE motif makes correct, monodentate, interactions with the two active site magnesium ions. Dynamic restraints applied to this coordination state create models with the correct solvation sphere for the metal ion complex and highlight the coordination sites available for metal binding ligands. Applying appropriate dynamic flexibility to the core domain allowed the inclusion of multiple conformational states in subsequent docking studies.
These models have allowed us to (1) explore the effects of key drug resistance mutations on the dynamic flexibility and conformational preferences of HIV integrase and to (2) study raltegravir binding in the context of these dynamic models of both wild type and the G140S/Q148H drug resistant enzyme.
HIV integrase inhibitor docking; restrained Molecular Dynamics; Relaxed Complex Scheme; metalloprotein modeling; mechanisms of drug resistance
The results from reiterated docking experiments may be used to evaluate an empirical configurational entropy of binding in ligand-protein complexes. We have tested several methods for evaluating the configurational entropy of binding of 22 nucleotide analogues to the enzyme APS reductase. These include two cluster size methods that measure the probability of finding a particular conformation, a method that estimates the extent of the local energetic well by looking at the scatter of conformations within clustered results, and an RMSD-based method that uses the overall scatter and clustering of all conformations. We have also directly characterized the local energy landscape by randomly sampling around docked conformations. The simple cluster size method shows the best performance, greatly improving the ranking of conformations in multiple docking experiments.
AutoDock; empirical free energy force fields; conformational entropy; computational docking
AutoDock Vina, a new program for molecular docking and virtual screening, is presented. AutoDock Vina achieves an approximately two orders of magnitude speed-up compared to the molecular docking software previously developed in our lab (AutoDock 4), while also significantly improving the accuracy of the binding mode predictions, judging by our tests on the training set used in AutoDock 4 development. Further speed-up is achieved from parallelism, by using multithreading on multi-core machines. AutoDock Vina automatically calculates the grid maps and clusters the results in a way transparent to the user.
Biological complexes typically exhibit intermolecular interfaces of high shape complementarity. Many computational docking approaches use this surface complementarity as a guide in the search for predicting the structures of protein-protein complexes. Proteins often undergo conformational changes in order to create a highly complementary interface when associating. These conformational changes are a major cause of failure for automated docking procedures when predicting binding modes between proteins using their unbound conformations. Low resolution surfaces in which high frequency geometric details are omitted have been used to address this problem. These smoothed, or blurred, surfaces are expected to minimize the differences between free and bound structures, especially those that are due to side chain conformations or small backbone deviations.
In spite of the fact that this approach has been used in many docking protocols, there has yet to be a systematic study of the effects of such surface smoothing on the shape complementarity of the resulting interfaces. Here we investigate this question by computing shape complementarity of a set of 66 protein-protein complexes represented by multi-resolution blurred surfaces. Complexed and unbound structures are available for these protein-protein complexes. They are a subset of complexes from a non-redundant docking benchmark selected for rigidity (i.e. the proteins undergo limited conformational changes between their bound and unbound states). In this work we construct the surfaces by isocontouring a density map obtained by accumulating the densities of Gaussian functions placed at all atom centers of the molecule. The smoothness or resolution is specified by a Gaussian fall-off coefficient, termed “blobbyness”. Shape complementarity is quantified using a histogram of the shortest distances between two proteins' surface mesh vertices for both the crystallographic complexes and the complexes built using the protein structures in their unbound conformation.
The histograms calculated for the bound complex structures demonstrate that medium resolution smoothing (blobbyness=−0.9) can reproduce about 88% of the shape complementarity of atomic resolution surfaces. Complexes formed from the free component structures show a partial loss of shape complementarity (more overlaps and gaps) with the atomic resolution surfaces. For surfaces smoothed to low resolution (blobbyness=−0.3), we find more consistency of shape complementarity between the complexed and free cases. To further reduce bad contacts without significantly impacting the good contacts we introduce another blurred surface, in which the Gaussian densities of flexible atoms are reduced. From these results we discuss the use of shape complementarity in protein-protein docking.
Protein interactions; protein-protein docking; Gaussian surface; protein side-chain flexibility; protein interfaces; unbound-unbound docking; protein complexes; Blur surface; FlexBlur surface; enzyme-inhibitor complexes
Nitrilases are a large and diverse family of non-peptidic C-N hydrolases. The mammalian genome encodes eight nitrilase enzymes, several of which remain poorly characterized. Prominent among these are nitrilase-1 (Nit1) and nitrilase-2 (Nit2), which, despite having been shown to exert effects on cell growth and possibly serving as tumor suppressor genes, are without known substrates or selective inhibitors. In previous studies, we identified several nitrilases, including Nit1 and Nit2, as targets for dipeptide-chloroacetamide activity-based proteomics probes. Here, we have used these probes, in combination with high-resolution crystallography and molecular modeling, to systematically map the active site of Nit2 and identify residues involved in molecular recognition. We report the 1.4 Å crystal structure of mouse Nit2, and use this structure to identify residues that discriminate probe-labeling between the Nit1 and Nit2 enzymes. Interestingly, some of these residues are conserved across all vertebrate Nit2 enzymes and, conversely, not found in any vertebrate Nit1 enzymes, suggesting that they are key discriminators of molecular recognition between these otherwise highly homologous enzymes. Our findings thus point to a limited set of active site residues that establish distinct patterns of molecular recognition among nitrilases and provide chemical probes to selectively perturb the function of these enzymes in biological systems.
Tuberculosis is among the world’s deadliest infectious diseases. APS reductase catalyzes the first committed step in bacterial sulfate reduction and is a validated drug target against latent tuberculosis infection. We performed a virtual screening to identify APSR inhibitors. These inhibitors represent the first non-phosphate-based molecules to inhibit APSR. Common chemical features lay the foundation for the development of agents which could shorten the duration of chemotherapy by targeting the latent stage of TB infection.
Phage-displayed peptides that selectively bind to aldolase catalytic antibody 93F3 when bound to a particular 1,3-diketone hapten derivative have been developed using designed selection strategies with libraries containing 7 to 12 randomized amino acid residues. These phage-displayed peptides discriminated the particular 93F3-diketone complex from ligand-free 93F3 and from 93F3 bound to other 1,3-diketone hapten derivatives. By altering the selection procedures, phage-displayed peptides that bind to antibody 93F3 in the absence of 1,3-diketone hapten derivatives have also been developed. With using these phage-displayed peptides, ligand-bound states of the antibody were distinguished from each other. A docking model of one of the peptides bound to the antibody 93F3-diketone complex was created using a sequential divide-and-conquer peptide docking strategy; the model suggests that the peptide interacts with both the antibody and the ligand through a delicate hydrogen bonding network.
antibody; ligand; peptide; phage library
Alzheimer's disease is the leading cause of dementia among the elderly, and with the ever-increasing size of this population, cases of Alzheimer's disease are expected to triple over the next 50 years. Consequently, the development of treatments that slow or halt the disease progression have become imperative to both improve the quality of life for patients as well as reduce the health care costs attributable to Alzheimer's disease. Here, we demonstrate that the active component of marijuana, Δ9-tetrahydrocannabinol (THC), competitively inhibits the enzyme acetylcholinesterase (AChE) as well as prevents AChE-induced amyloid β-peptide (Aβ) aggregation, the key pathological marker of Alzheimer's disease. Computational modeling of the THC-AChE interaction revealed that THC binds in the peripheral anionic site of AChE, the critical region involved in amyloidgenesis. Compared to currently approved drugs prescribed for the treatment of Alzheimer's disease, THC is a considerably superior inhibitor of Aβ aggregation, and this study provides a previously unrecognized molecular mechanism through which cannabinoid molecules may directly impact the progression of this debilitating disease.
Cannabinoids; Alzheimer's disease; Acetylcholinesterase
We used feline immunodeficiency virus (FIV) protease (PR) as a mutational framework to define determinants for the observed substrate and inhibitor specificity distinctions between FIV and human immunodeficiency virus (HIV) PRs. Multiple-substitution mutants were constructed by replacing the residues in and around the active site of FIV PR with the structurally equivalent residues of HIV-1 PR. Mutants included combinations of three critical regions (FIV numbering, with equivalent HIV numbering in superscript): I3732V in the active core region; N5546M, M5647I, and V5950I in the flap region; and L9780T, I9881P, Q9982V, P10083N, and L10184I in the 90s loop region. Significant alterations in specificity were observed, consistent with the involvement of these residues in determining the substrate-inhibitor specificity distinctions between FIV and HIV PRs. Two previously identified residues, I35 and I57 of FIV PR, were intolerant to substitution and yielded inactive PRs. Therefore, we attempted to recover the activity by introducing secondary mutations. The addition of G6253F and K6354I, located at the top of the flap and outside the active site, compensated for the activity lost in the I5748G substitution mutants. An additional two substitutions, D10588N and N8874T, facilitated recovery of activity in mutants that included the I3530D substitution. Determination of Ki values of potent HIV-1 PR inhibitors against these mutants showed that inhibitor specificity paralleled that of HIV-1 PR. The findings indicate that maintenance of both substrate and inhibitor specificity is a function of interactions between residues both inside and outside the active site. Thus, mutations apparently peripheral to the active site can have a dramatic influence on inhibitor efficacy.
TL-3 is a protease inhibitor developed using the feline immunodeficiency virus protease as a model. It has been shown to efficiently inhibit replication of human, simian, and feline immunodeficiency viruses and therefore has broad-based activity. We now demonstrate that TL-3 efficiently inhibits the replication of 6 of 12 isolates with confirmed resistance mutations to known protease inhibitors. To dissect the spectrum of molecular changes in protease and viral properties associated with resistance to TL-3, a panel of chronological in vitro escape variants was generated. We have virologically and biochemically characterized mutants with one (V82A), three (M46I/F53L/V82A), or six (L24I/M46I/F53L/L63P/V77I/V82A) changes in the protease and structurally modeled the protease mutant containing six changes. Virus containing six changes was found to be 17-fold more resistant to TL-3 in cell culture than was wild-type virus but maintained similar in vitro replication kinetics compared to the wild-type virus. Analyses of enzyme activity of protease variants with one, three, and six changes indicated that these enzymes, compared to wild-type protease, retained 40, 47, and 61% activity, respectively. These results suggest that deficient protease enzymatic activity is sufficient for function, and the observed protease restoration might imply a selective advantage, at least in vitro, for increased protease activity.
Feline immunodeficiency virus (FIV) protease is structurally very similar to human immunodeficiency virus (HIV) protease but exhibits distinct substrate and inhibitor specificities. We performed mutagenesis of subsite residues of FIV protease in order to define interactions that dictate this specificity. The I37V, N55M, M56I, V59I, and Q99V mutants yielded full activity. The I37V, N55M, V59I, and Q99V mutants showed a significant increase in activity against the HIV-1 reverse transcriptase/integrase and P2/nucleocapsid junction peptides compared with wild-type (wt) FIV protease. The I37V, V59I, and Q99V mutants also showed an increase in activity against two rapidly cleaved peptides selected by cleavage of a phage display library with HIV-1 protease. Mutations at Q54K, I98P, and L101I dramatically reduced activity. Mutants containing a I35D or I57G substitution showed no activity against either FIV or HIV substrates. FIV proteases all failed to cut HIV-1 matrix/capsid, P1/P6, P6/protease, and protease/reverse transcriptase junctions, indicating that none of the substitutions were sufficient to change the specificity completely. The I37V, N55M, M56I, V59I, and Q99V mutants, compared with wt FIV protease, all showed inhibitor specificity more similar to that of HIV-1 protease. The data also suggest that FIV protease prefers a hydrophobic P2/P2′ residue like Val over Asn or Glu, which are utilized by HIV-1 protease, and that S2/S2′ might play a critical role in distinguishing FIV and HIV-1 protease by specificity. The findings extend our observations regarding the interactions involved in substrate binding and aid in the development of broad-based inhibitors.