Functional and Modeling Studies of the Transmembrane Region of the TRPM8 Channel.

Members of the transient receptor potential (TRP) ion channel family act as polymodal cellular sensors, which aid in regulating Ca(2+) homeostasis. Within the TRP family, TRPM8 is the cold receptor that forms a nonselective homotetrameric cation channel. In the absence of TRPM8 crystal structure, little is known about the relationship between structure and function. Inferences of TRPM8 structure have come from mutagenesis experiments coupled to electrophysiology, mainly regarding the fourth transmembrane helix (S4), which constitutes a moderate voltage-sensing domain, and about cold sensor and phosphatidylinositol 4,5-bisphosphate binding sites, which are both located in the C-terminus of TRPM8. In this study, we use a combination of molecular modeling and experimental techniques to examine the structure of the TRPM8 transmembrane and pore helix region including the conducting conformation of the selectivity filter. The model is consistent with a large amount of functional data and was further tested by mutagenesis. We present structural insight into the role of residues involved in intra- and intersubunit interactions and their link with the channel activity, sensitivity to icilin, menthol and cold, and impact on channel oligomerization.

Repurposing of bisphosphonates for the prevention and therapy of nonsmall cell lung and breast cancer.

A variety of human cancers, including nonsmall cell lung (NSCLC), breast, and colon cancers, are driven by the human epidermal growth factor receptor (HER) family of receptor tyrosine kinases. Having shown that bisphosphonates, a class of drugs used widely for the therapy of osteoporosis and metastatic bone disease, reduce cancer cell viability by targeting HER1, we explored their potential utility in the prevention and therapy of HER-driven cancers. We show that bisphosphonates inhibit colony formation by HER1(ΔE746-A750)-driven HCC827 NSCLCs and HER1(wt)-expressing MB231 triple negative breast cancers, but not by HER(low)-SW620 colon cancers. In parallel, oral gavage with bisphosphonates of mice xenografted with HCC827 or MB231 cells led to a significant reduction in tumor volume in both treatment and prevention protocols. This result was not seen with mice harboring HER(low) SW620 xenografts. We next explored whether bisphosphonates can serve as adjunctive therapies to tyrosine kinase inhibitors (TKIs), namely gefitinib and erlotinib, and whether the drugs can target TKI-resistant NSCLCs. In silico docking, together with molecular dynamics and anisotropic network modeling, showed that bisphosphonates bind to TKIs within the HER1 kinase domain. As predicted from this combinatorial binding, bisphosphonates enhanced the effects of TKIs in reducing cell viability and driving tumor regression in mice. Impressively, the drugs also overcame erlotinib resistance acquired through the gatekeeper mutation T790M, thus offering an option for TKI-resistant NSCLCs. We suggest that bisphosphonates can potentially be repurposed for the prevention and adjunctive therapy of HER1-driven cancers.

Bisphosphonates inactivate human EGFRs to exert antitumor actions.

Bisphosphonates are the most commonly prescribed medicines for osteoporosis and skeletal metastases. The drugs have also been shown to reduce cancer progression, but only in certain patient subgroups, suggesting that there is a molecular entity that mediates bisphosphonate action on tumor cells. Using connectivity mapping, we identified human epidermal growth factor receptors (human EGFR or HER) as a potential new molecular entity for bisphosphonate action. Protein thermal shift and cell-free kinase assays, together with computational modeling, demonstrated that N-containing bisphosphonates directly bind to the kinase domain of HER1/2 to cause a global reduction in downstream signaling. By doing so, the drugs kill lung, breast, and colon cancer cells that are driven by activating mutations or overexpression of HER1. Knocking down HER isoforms thus abrogates cell killing by bisphosphonates, establishing complete HER dependence and ruling out a significant role for other receptor tyrosine kinases or the enzyme farnesyl pyrophosphate synthase. Consistent with this finding, colon cancer cells expressing low levels of HER do not respond to bisphosphonates. The results suggest that bisphosphonates can potentially be repurposed for the prevention and therapy of HER family-driven cancers.

N-substituted piperazinopyridylsteroid derivatives as abiraterone analogues inhibit growth and induce pro-apoptosis in human hormone-independent prostate cancer cell lines.

Nine new 17-(piperazin-1-yl)pyridin-5-yl)steroids as abiraterone analogues were synthesized. Compounds 5d and 5g showed selective activities against 17α-hydroxylase/C17,20-lyase (CYP17A1) and aromatase (CYP19), respectively. IC50 values of 5d were 5.09 and >50 µm, whereas these values for 5g were >50 µm and 7.40 µm, respectively, for CYP17A1 and CYP19. Molecular modelling highlighted that the inhibitor designed to bind cytochrome P450 haem iron is a necessary condition but not the only rationale to explain inhibitory activity. These abiraterone analogues were then evaluated on hormone-independent prostate cancer cell lines DU-145 and PC-3 and on hormone-dependent breast and prostate cancer cell lines MCF-7 and LNCaP, respectively. Compounds 5e, 5g and 5i have showed potent activities only on hormone-independent prostate cancer cell lines DU-145 and PC-3 with 60-85% inhibition of both cell viability and growth at 10 nm with pro-apoptotic mechanism as illustrated in PC-3 cells by DNA ladder assay and Western blotting of Bax, Casp-3 and its substrate, the poly (ADP-ribose) polymerase. We conclude that hybrid heterocycle steroids could be good lead compounds in the drug design especially against hormone-independent prostate cancer.

Anthrax SET protein: a potential virulence determinant that epigenetically represses NF-κB activation in infected macrophages.

Toxins play a major role in the pathogenesis of Bacillus anthracis by subverting the host defenses. However, besides toxins, B. anthracis expresses effector proteins, whose role in pathogenesis are yet to be investigated. Here we present that suppressor-of-variegation, enhancer-of-zeste, trithorax protein from B. anthracis (BaSET) methylates human histone H1, resulting in repression of NF-κB functions. Notably, BaSET is secreted and undergoes nuclear translocation to enhance H1 methylation in B. anthracis-infected macrophages. Compared with wild type Sterne, delayed growth kinetics and altered septum formation were observed in the BaSET knock-out (BaΔSET) bacilli. Uncontrolled BaSET expression during complementation of the BaSET gene in BaΔSET partially restored growth during stationary phase but resulted in substantially shorter bacilli throughout the growth cycle. Importantly, in contrast to Sterne, the BaΔSET B. anthracis is avirulent in a lethal murine bacteremia model of infection. Collectively, BaSET is required for repression of host transcription as well as proper B. anthracis growth, making it a potentially unique virulence determinant.

Conformational dynamics of the human propeller telomeric DNA quadruplex on a microsecond time scale.

The human telomeric DNA sequence with four repeats can fold into a parallel-stranded propeller-type topology. NMR structures solved under molecular crowding experiments correlate with the crystal structures found with crystal-packing interactions that are effectively equivalent to molecular crowding. This topology has been used for rationalization of ligand design and occurs experimentally in a number of complexes with a diversity of ligands, at least in the crystalline state. Although G-quartet stems have been well characterized, the interactions of the TTA loop with the G-quartets are much less defined. To better understand the conformational variability and structural dynamics of the propeller-type topology, we performed molecular dynamics simulations in explicit solvent up to 1.5 µs. The analysis provides a detailed atomistic account of the dynamic nature of the TTA loops highlighting their interactions with the G-quartets including formation of an A:A base pair, triad, pentad and hexad. The results present a threshold in quadruplex simulations, with regards to understanding the flexible nature of the sugar-phosphate backbone in formation of unusual architecture within the topology. Furthermore, this study stresses the importance of simulation time in sampling conformational space for this topology.

Structure-phenotype correlations of human CYP21A2 mutations in congenital adrenal hyperplasia.

Mutations in the cytochrome p450 (CYP)21A2 gene, which encodes the enzyme steroid 21-hydroxylase, cause the majority of cases in congenital adrenal hyperplasia, an autosomal recessive disorder. To date, more than 100 CYP21A2 mutations have been reported. These mutations can be associated either with severe salt-wasting or simple virilizing phenotypes or with milder nonclassical phenotypes. Not all CYP21A2 mutations have, however, been characterized biochemically, and the clinical consequences of these mutations remain unknown. Using the crystal structure of its bovine homolog as a template, we have constructed a humanized model of CYP21A2 to provide comprehensive structural explanations for the clinical manifestations caused by each of the known disease-causing missense mutations in CYP21A2. Mutations that affect membrane anchoring, disrupt heme and/or substrate binding, or impair stability of CYP21A2 cause complete loss of function and salt-wasting disease. In contrast, mutations altering the transmembrane region or conserved hydrophobic patches cause up to a 98% reduction in enzyme activity and simple virilizing disease. Mild nonclassical disease can result from interference in oxidoreductase interactions, salt-bridge and hydrogen-bonding networks, and nonconserved hydrophobic clusters. A simple in silico evaluation of previously uncharacterized gene mutations could, thus, potentially help predict the often diverse phenotypes of a monogenic disorder.

Application of a post-docking procedure based on MM-PBSA and MM-GBSA on single and multiple protein conformations.

In the last decades, molecular docking has emerged as an increasingly useful tool in the modern drug discovery process, but it still needs to overcome many hurdles and limitations such as how to account for protein flexibility and poor scoring function performance. For this reason, it has been recognized that in many cases docking results need to be post-processed to achieve a significant agreement with experimental activities. In this study, we have evaluated the performance of MM-PBSA and MM-GBSA scoring functions, implemented in our post-docking procedure BEAR, in rescoring docking solutions. For the first time, the performance of this post-docking procedure has been evaluated on six different biological targets (namely estrogen receptor, thymidine kinase, factor Xa, adenosine deaminase, aldose reductase, and enoyl ACP reductase) by using i) both a single and a multiple protein conformation approach, and ii) two different software, namely AutoDock and LibDock. The assessment has been based on two of the most important criteria for the evaluation of docking methods, i.e., the ability of known ligands to enrich the top positions of a ranked database with respect to molecular decoys, and the consistency of the docking poses with crystallographic binding modes. We found that, in many cases, MM-PBSA and MM-GBSA are able to yield higher enrichment factors compared to those obtained with the docking scoring functions alone. However, for only a minority of the cases, the enrichment factors obtained by using multiple protein conformations were higher than those obtained by using only one protein conformation.

Molecular dynamics of HIV1-integrase in complex with 93del - a structural perspective on the mechanism of inhibition.

HIV1 integrase is an important target for the antiviral therapy. Guanine-rich quadruplex, such as 93del, have been shown to be potent inhibitors of this enzyme and thus representing a new class of antiviral agents. Although X-ray and NMR structures of HIV1 integrase and 93del have been reported, there is no structural information of the complex and the mechanism of inhibition still remains unexplored. A number of computational methods including automated protein-DNA docking and molecular dynamics simulation in explicit solvent were used to model the binding of 93del to HIV1 integrase. Analysis of the dynamic behaviour of the complex using principal components analysis and elastic network modelling techniques allow us to understand how the binding of 93del aptamer and its interactions with key residues affect the intrinsic motions of the catalytic loops by stabilising them in catalytically inactive conformations. Such insights into the structural mechanism of inhibition can aid in improving the design of anti-HIV aptamers.

Exploring the binding site of C-terminal hsp90 inhibitors.

The 90 kDa heat shock protein (Hsp90) is a prominent target for anticancer drug discovery. While its N-terminal domain has been widely exploited, several lines of evidence are emerging in favor of targeting its C-terminal domain to conceive innovative drugs based on perturbation of the dimer interface. Here, we describe the application of several computational approaches useful to predict the location of the C-terminal binding site.

A computational workflow for the design of irreversible inhibitors of protein kinases.

Design of irreversible inhibitors is an emerging and relatively less explored strategy for the design of protein kinase inhibitors. In this paper, we present a computational workflow that was specifically conceived to assist such design. The workflow takes the form of a multi-step procedure that includes: the creation of a database of already known reversible inhibitors of protein kinases, the selection of the most promising scaffolds that bind one or more desired kinase templates, the modification of the scaffolds by introduction of chemically reactive groups (suitable cysteine traps) and the final evaluation of the reversible and irreversible protein-ligand complexes with molecular dynamics simulations and binding free energy predictions. Most of these steps were automated. In order to prove that this is viable, the workflow was tested on a database of known inhibitors of ERK2, a protein kinase possessing a cysteine in the ATP site. The modeled ERK2-ligand complexes and the values of the estimated binding free energies of the putative ligands provide useful indicators of their aptitude to bind reversibly and irreversibly to the protein kinase. Moreover, the computational data are used to rank the ligands according to their computed binding free energies and their ability to bind specific protein residues in the reversible and irreversible complexes, thereby providing a useful decision-making tool for each step of the design. In this work we present the overall procedure and the first proof of concept results.

Fast and accurate predictions of binding free energies using MM-PBSA and MM-GBSA.

In the drug discovery process, accurate methods of computing the affinity of small molecules with a biological target are strongly needed. This is particularly true for molecular docking and virtual screening methods, which use approximated scoring functions and struggle in estimating binding energies in correlation with experimental values. Among the various methods, MM-PBSA and MM-GBSA are emerging as useful and effective approaches. Although these methods are typically applied to large collections of equilibrated structures of protein-ligand complexes sampled during molecular dynamics in water, the possibility to reliably estimate ligand affinity using a single energy-minimized structure and implicit solvation models has not been explored in sufficient detail. Herein, we thoroughly investigate this hypothesis by comparing different methods for the generation of protein-ligand complexes and diverse methods for free energy prediction for their ability to correlate with experimental values. The methods were tested on a series of structurally diverse inhibitors of Plasmodium falciparum DHFR with known binding mode and measured affinities. The results showed that correlations between MM-PBSA or MM-GBSA binding free energies with experimental affinities were in most cases excellent. Importantly, we found that correlations obtained with the use of a single protein-ligand minimized structure and with implicit solvation models were similar to those obtained after averaging over multiple MD snapshots with explicit water molecules, with consequent save of computing time without loss of accuracy. When applied to a virtual screening experiment, such an approach proved to discriminate between true binders and decoy molecules and yielded significantly better enrichment curves.

Structure-based and in silico design of Hsp90 inhibitors.

The molecular chaperone Hsp90 is responsible for activation and stabilization of several oncoproteins in cancer cells, and has emerged as an important target in cancer treatment because of this pivotal role. In recent years, interests have arisen around structure-based design of small molecules aimed at inhibiting the chaperone activity of Hsp90. In this review, we illustrate the recent advances in structure-based and in silico strategies aimed at discovering and optimizing Hsp90 inhibitors.

Binding estimation after refinement, a new automated procedure for the refinement and rescoring of docked ligands in virtual screening.

Binding estimation after refinement (BEAR) is a novel automated computational procedure suitable for correcting and overcoming limitations of docking procedures such as poor scoring function and the generation of unreasonable ligand conformations. BEAR makes use of molecular dynamics simulation followed by MM-PBSA and MM-GBSA binding free energy estimates as tools to refine and rescore the structures obtained from docking virtual screenings. As binding estimation after refinement relies on molecular dynamics, the entire procedure can be tailored to the needs of the end-user in terms of computational time and the desired accuracy of the results. In a validation test, binding estimation after refinement and rescoring resulted in a significant enrichment of known ligands among top scoring compounds compared with the original docking results. Binding estimation after refinement has direct and straightforward application in virtual screening for correcting both false-positive and false-negative hits, and should facilitate more reliable selection of biologically active molecules from compound databases.

Structural models and binding site prediction of the C-terminal domain of human Hsp90: a new target for anticancer drugs.

Heat shock protein 90 is a valuable target for anticancer drugs because of its role in the activation and stabilization of multiple oncogenic signalling proteins. While several compounds inhibit heat shock protein 90 by binding the N-terminal domain, recent studies have proved that the C-terminal domain is important for dimerization of the chaperone and contains an additional binding site for inhibitors. Heat shock protein 90 inhibition achieved with molecules binding to the C-terminal domain provides an additional and novel opportunity to design and develop drugs. Therefore, for the first time, we have investigated the structure and the dynamic behaviour of the C-terminal domain of human heat shock protein 90 with and without the small-middle domain, using homology modelling and molecular dynamics simulations. In addition, secondary structure predictions and peptide folding simulations proved useful to investigate a putative additional alpha-helix located between H18 and beta20 of the C-terminal domain. Finally, we used the structural information to infer the location of the binding site located in the C-terminal domain by using a number of computational tools. The predicted pocket is formed by two grooves located between helix H18, the loop downstream of H18 and the loop connecting helices H20 and H21 of each monomer of the C-terminal domain, with only two amino acids contributing from each middle domain.

Validation of an automated procedure for the prediction of relative free energies of binding on a set of aldose reductase inhibitors.

Among the available methods for predicting free energies of binding of ligands to a protein, the molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) and molecular mechanics generalized Born surface area (MM-GBSA) approaches have been validated for a relatively limited number of targets and compounds in the training set. Here, we report the results of an extensive study on a series of 28 inhibitors of aldose reductase with experimentally determined crystal structures and inhibitory activities, in which we evaluate the ability of MM-PBSA and MM-GBSA methods in predicting binding free energies using a number of different simulation conditions. While none of the methods proved able to predict absolute free energies of binding in quantitative agreement with the experimental values, calculated and experimental free energies of binding were significantly correlated. Comparing the predicted and experimental DeltaG of binding, MM-PBSA proved to perform better than MM-GBSA, and within the MM-PBSA methods, the PBSA of Amber performed similarly to Delphi. In particular, significant relationships between experimental and computed free energies of binding were obtained using Amber PBSA and structures minimized with a distance-dependent dielectric function. Importantly, while free energy predictions are usually made on large collections of equilibrated structures sampled during molecular dynamics in water, we have found that a single minimized structure is a reasonable approximation if relative free energies of binding are to be calculated. This finding is particularly relevant, considering that the generation of equilibrated MD ensembles and the subsequent free energy analysis on multiple snapshots is computationally intensive, while the generation and analysis of a single minimized structure of a protein-ligand complex is relatively fast, and therefore suited for high-throughput virtual screening studies. At this aim, we have developed an automated workflow that integrates all the necessary steps required to generate structures and calculate free energies of binding. The procedure is relatively fast and able to screen automatically and iteratively molecules contained in databases and libraries of compounds. Taken altogether, our results suggest that the workflow can be a valuable tool for ligand identification and optimization, being able to automatically and efficiently refine docking poses, which sometimes may not be accurate, and rank the compounds based on more accurate scoring functions.

Relationship between quantum-chemical descriptors of proton dissociation and experimental acidity constants of various hydroxylated coumarins. Identification of the biologically active species for xanthine oxidase inhibition.

Quantum-chemical descriptors related to proton dissociation constants of a set of coumarins hydroxylated in various positions have been computed and related to the experimental pK(a) values. An excellent correlation was found between the computed deprotonation energies of hydroxycoumarins in water and their experimental pK(a) values, and the results were used to predict the pK(a) of other hydroxycoumarins. Then, predicted and experimental pK(a) values were used as a basis for interpreting and discussing the variation of xanthine oxidase inhibitory activities within a subset of coumarins, with the aim of identifying the molecular species most relevant for enzyme inhibition.