Identification of histone deacetylase inhibitors with (arylidene)aminoxy scaffold active in uveal melanoma cell lines.

Uveal melanoma (UM) represents an aggressive type of cancer and currently, there is no effective treatment for this metastatic disease. In the last years, histone deacetylase inhibitors (HDACIs) have been studied as a possible therapeutic treatment for UM, alone or in association with other chemotherapeutic agents. Here we synthesised a series of new HDACIs based on the SAHA scaffold bearing an (arylidene)aminoxy moiety. Their HDAC inhibitory activity was evaluated on isolated human HDAC1, 3, 6, and 8 by fluorometric assay and their binding mode in the catalytic site of HDACs was studied by molecular docking. The most promising hit was the quinoline derivative VS13, a nanomolar inhibitor of HDAC6, which exhibited a good antiproliferative effect on UM cell lines at micromolar concentration and a capability to modify the mRNA levels of HDAC target genes similar to that of SAHA.

Structural insights of SmKDAC8 inhibitors: Targeting Schistosoma epigenetics through a combined structure-based 3D QSAR, in vitro and synthesis strategy.

A predictive structure-based 3D QSAR (COMBINEr 2.0) model of the Schistosoma mansoni lysine deacetylase 8 enzyme (SmKDAC8) was developed, validated and used to perform virtual screening (VS) of the NCI Diversity Set V database (1593 compounds). Three external datasets (with congeneric structures to those experimentally resolved in complexes by X-ray and previously reported as SmKDAC8 inhibitors) were employed to compose and validate the most predictive model. Two series characterized by 104 benzodiazepine derivatives (BZDs) and 60 simplified largazole analogs (SLAs), recently reported by our group as human KDAC inhibitors, were tested for their inhibition potency against SmKDAC8 to probe the predictive capability of the quantitative models against compounds with diverse structures. The SmKDAC8 biochemical results confirmed: (1) the benzodiazepine moiety as a valuable scaffold to further investigate when pursuing SmKDAC8 inhibition; (2) the predictive capability of the COMBINEr 2.0 model towards non-congeneric series of compounds, highlighting the most influencing ligand-protein interactions and refining the structure-activity relationships. From the VS investigations, the first 40 top-ranked compounds were obtained and biologically tested for their inhibition potency against SmKDAC8 and hKDACs 1, 3, 6 and 8. Among them, a non-hydroxamic acid benzothiadiazine dioxide derivative (code NSC163639), showed interesting activity and selectivity against SmKDAC8. To further elucidate the structure-activity relationships of NSC163639, two analogs (herein reported as compounds 3 and 4) were synthesized and biologically evaluated. Results suggest the benzothiadiazine dioxide moiety as a promising scaffold to be used in a next step to derive selective SmKDAC8 inhibitors.

Limiting Assumptions in the Design of Peptidomimetics.

Preclinical Research Limiting the flexibility of organic compounds to enhance their affinity and selectivity for targeting a macromolecule involved in molecular recognition has become a well-developed paradigm in medicinal chemistry. While the role of reverse-turn motifs as peptidomimetics has received the most attention, ß-sheets and helices are also important motifs for protein/protein interactions. The more complicated problem of mimicking the interacting surface of noncontiguous epitopes will not be considered in this review. This limited overview focuses on efforts to use amino acid synthons as secondary-structure mimetics as well as providing examples of peptidomimetic design focused on nonpeptide synthetic chemistry in contrast. In particular, the rationale of optimal design criteria for mimicry and the many naïve violations of those criteria made in its pursuit are emphasized. Drug Dev Res 78 : 245-267, 2017. © 2017 Wiley Periodicals, Inc.

An Automated Strategy for Binding-Pose Selection and Docking Assessment in Structure-Based Drug Design.

Molecular docking is a widely used technique in drug design to predict the binding pose of a candidate compound in a defined therapeutic target. Numerous docking protocols are available, each characterized by different search methods and scoring functions, thus providing variable predictive capability on a same ligand-protein system. To validate a docking protocol, it is necessary to determine a priori the ability to reproduce the experimental binding pose (i.e., by determining the docking accuracy (DA)) in order to select the most appropriate docking procedure and thus estimate the rate of success in docking novel compounds. As common docking programs use generally different root-mean-square deviation (RMSD) formulas, scoring functions, and format results, it is both difficult and time-consuming to consistently determine and compare their predictive capabilities in order to identify the best protocol to use for the target of interest and to extrapolate the binding poses (i.e., best-docked (BD), best-cluster (BC), and best-fit (BF) poses) when applying a given docking program over thousands/millions of molecules during virtual screening. To reduce this difficulty, two new procedures called Clusterizer and DockAccessor have been developed and implemented for use with some common and "free-for-academics" programs such as AutoDock4, AutoDock4(Zn), AutoDock Vina, DOCK, MpSDockZn, PLANTS, and Surflex-Dock to automatically extrapolate BD, BC, and BF poses as well as to perform consistent cluster and DA analyses. Clusterizer and DockAccessor (code available over the Internet) represent two novel tools to collect computationally determined poses and detect the most predictive docking approach. Herein an application to human lysine deacetylase (hKDAC) inhibitors is illustrated.

Helix stability of oligoglycine, oligoalanine, and oligo-ß-alanine dodecamers reflected by hydrogen-bond persistence.

Helices are important structural/recognition elements in proteins and peptides. Stability and conformational differences between helices composed of α- and ß-amino acids as scaffolds for mimicry of helix recognition has become a theme in medicinal chemistry. Furthermore, helices formed by ß-amino acids are experimentally more stable than those formed by α-amino acids. This is paradoxical because the larger sizes of the hydrogen-bonding rings required by the extra methylene groups should lead to entropic destabilization. In this study, molecular dynamics simulations using the second-generation force field, AMOEBA (Ponder, J.W., et al., Current status of the AMOEBA polarizable force field. J Phys Chem B, 2010. 114(8): p. 2549-64.) explored the stability and hydrogen-bonding patterns of capped oligo-ß-alanine, oligoalanine, and oligoglycine dodecamers in water. The MD simulations showed that oligo-ß-alanine has strong acceptor+2 hydrogen bonds, but surprisingly did not contain a large content of 3(12) -helical structures, possibly due to the sparse distribution of the 3(12) -helical structure and other structures with acceptor+2 hydrogen bonds. On the other hand, despite its backbone flexibility, the ß-alanine dodecamer had more stable and persistent <3.0 Å hydrogen bonds. Its structure was dominated more by multicentered hydrogen bonds than either oligoglycine or oligoalanine helices. The 3(1) (PII) helical structure, prevalent in oligoglycine and oligoalanine, does not appear to be stable in oligo-ß-alanine indicating its competition with other structures (stacking structure as indicated by MD analyses). These differences are among the factors that shape helical structural preferences and the relative stabilities of these three oligopeptides.

Limiting assumptions in molecular modeling: electrostatics.

Molecular mechanics attempts to represent intermolecular interactions in terms of classical physics. Initial efforts assumed a point charge located at the atom center and coulombic interactions. It is been recognized over multiple decades that simply representing electrostatics with a charge on each atom failed to reproduce the electrostatic potential surrounding a molecule as estimated by quantum mechanics. Molecular orbitals are not spherically symmetrical, an implicit assumption of monopole electrostatics. This perspective reviews recent evidence that requires use of multipole electrostatics and polarizability in molecular modeling.

Molecular dynamics of ß-hairpin models of epigenetic recognition motifs.

The conformations and stabilities of the ß-hairpin model peptides of Waters (Riemen, A. J.; Waters, M. L. Biochemistry 2009, 48, 1525; Hughes, R. M.; Benshoff, M. L.; Waters, M. L. Chemistry 2007, 13, 5753) have been experimentally characterized as a function of lysine ε-methylation. These models were developed to explore molecular recognition of known epigenetic recognition motifs. This system offered an opportunity to computationally examine the role of cation-π interactions, desolvation of the ε-methylated ammonium groups, and aromatic/aromatic interactions on the observed differences in NMR spectra. AMOEBA, a second-generation force field (Ponder, J. W.; Wu, C.; Ren, P.; Pande, V. S.; Chodera, J. D.; Schnieders, M. J.; Haque, I.; Mobley, D. L.; Lambrecht, D. S.; DiStasio, R. A., Jr.; Head-Gordon, M.; Clark, G. N.; Johnson, M. E.; Head-Gordon, T. J. Phys. Chem. B 2010, 114, 2549), was chosen as it includes both multipole electrostatics and polarizability thought to be essential to accurately characterize such interactions. Independent parametrization of ε-methylated amines was required from which aqueous solvation free energies were estimated and shown to agree with literature values. Molecular dynamics simulations (100 ns) using the derived parameters with model peptides, such as Ac-R-W-V-W-V-N-G-Orn-K(Me)(n)-I-L-Q-NH(2), where n = 0, 1, 2, or 3, were conducted in explicit solvent. Distances between the centers of the indole rings of the two-tryptophan residues, 2 and 4, and the ε-methylated ammonium group on Lys-9 as well as the distance between the N- and C-termini were monitored to estimate the strength and orientation of the cation-π and aromatic/aromatic interactions. In agreement with the experimental data, the stability of the ß-hairpin increased significantly with lysine ε-methylation. The ability of MD simulations to reproduce the observed NOEs for the four peptides was further estimated for the monopole-based force fields, AMBER, CHARMM, and OPLSAA. AMOEBA correctly predicted over 80% of the observed NOEs for all 4 peptides, while the three-monopole force fields were 40-50% predictive in only 2 cases and approximately 10% in the other 10 examples. Preliminary analysis suggests that the decreased cost of desolvation of the substituted ammonium group significantly compensated for the reduced cation-π interaction resulting from the increased separation due to steric bulk of the ε-methylated amines.

Histone deacetylase inhibitors: structure-based modeling and isoform-selectivity prediction.

An enhanced version of comparative binding energy (COMBINE) analysis, named COMBINEr, based on both ligand-based and structure-based alignments has been used to build several 3-D QSAR models for the eleven human zinc-based histone deacetylases (HDACs). When faced with an abundance of data from diverse structure-activity sources, choosing the best paradigm for an integrative analysis is difficult. A common example from studies on enzyme-inhibitors is the abundance of crystal structures characterized by diverse ligands complexed with different enzyme isoforms. A novel comprehensive tool for data mining on such inhomogeneous set of structure-activity data was developed based on the original approach of Ortiz, Gago, and Wade, and applied to predict HDAC inhibitors' isoform selectivity. The COMBINEr approach (apart from the AMBER programs) has been developed to use only software freely available to academics.

Limiting assumptions in structure-based design: binding entropy.

In order to deal with the complexity of biological systems at the atomic level, limiting assumptions are often made which do not reflect the reality of the system under study. One example is the assumption that the entropy of binding of the macromolecule is not influenced significantly by the different ligands. Recent experimental data on ligands binding to HIV-1 protease challenge this assumption.

Comprehensive model of wild-type and mutant HIV-1 reverse transciptases.

An enhanced version of COMBINE that uses both ligand-based and structure-based alignment of ligands has been used to build a comprehensive 3-D QSAR model of wild-type HIV-1 reverse transcriptase and drug-resistant mutants. The COMBINEr model focused on 7 different RT enzymes complexed with just two HIV-RT inhibitors, niverapine (NVP) and efavirenz (EFV); therefore, 14 inhibitor/enzyme complexes comprised the training set. An external test set of chiral 2-(alkyl/aryl)amino-6-benzylpyrimidin-4(3H)-ones (DABOs) was used to test predictability. The COMBINEr model MC4, although developed using only two inhibitors, predicted the experimental activities of the test set with an acceptable average absolute error of prediction (0.89 pK (i)). Most notably, the model was able to correctly predict the right eudismic ratio for two R/S pairs of DABO derivatives. The enhanced COMBINEr approach was developed using only software freely available to academics.

Simplified modeling approach suggests structural mechanisms for constitutive activation of the C5a receptor.

Molecular modeling of conformational changes occurring in the transmembrane region of the complement factor 5a receptor (C5aR) during receptor activation was performed by comparing two constitutively active mutants (CAMs) of C5aR, NQ (I124N/L127Q), and F251A, to those of the wild-type C5aR and NQ-N296A (I124N/L127Q/N296A), which have the wild-type phenotype. Modeling involved comprehensive sampling of various rotations of TM helices aligned to the crystal template of the dark-adapted rhodopsin along their long axes. By assuming that the relative energies of the spontaneously activated states of CAMs should be lower or at least comparable to energies characteristic for the ground states, we selected the plausible models for the conformational states associated with constitutive activation in C5aR. The modeling revealed that the hydrogen bonds between the side chains of D82-N119, S85-N119, and S131-C221 characteristic for the ground state were replaced by the hydrogen bonds D82-N296, N296-Y300, and S131-R134, respectively, in the activated states. Also, conformational transitions that occurred upon activation were hindered by contacts between the side chains of L127 and F251. The results rationalize the available data of mutagenesis in C5aR and offer the first specific molecular mechanism for the loss of constitutive activity in NQ-N296A. Our results also contributed to understanding the general structural mechanisms of activation in G-protein-coupled receptors lacking the "ionic lock", R(3.50) and E/D(6.30). Importantly, these results were obtained by modeling approaches that deliberately simplify many elements in order to explore potential conformations of GPCRs involving large-scale molecular movements.

A crowdsourcing evaluation of the NIH chemical probes.

Between 2004 and 2008, the US National Institutes of Health Molecular Libraries and Imaging initiative pilot phase funded 10 high-throughput screening centers, resulting in the deposition of 691 assays into PubChem and the nomination of 64 chemical probes. We crowdsourced the Molecular Libraries and Imaging initiative output to 11 experts, who expressed medium or high levels of confidence in 48 of these 64 probes.

PHOENIX: a scoring function for affinity prediction derived using high-resolution crystal structures and calorimetry measurements.

Binding affinity prediction is one of the most critical components to computer-aided structure-based drug design. Despite advances in first-principle methods for predicting binding affinity, empirical scoring functions that are fast and only relatively accurate are still widely used in structure-based drug design. With the increasing availability of X-ray crystallographic structures in the Protein Data Bank and continuing application of biophysical methods such as isothermal titration calorimetry to measure thermodynamic parameters contributing to binding free energy, sufficient experimental data exists that scoring functions can now be derived by separating enthalpic (ΔH) and entropic (TΔS) contributions to binding free energy (ΔG). PHOENIX, a scoring function to predict binding affinities of protein-ligand complexes, utilizes the increasing availability of experimental data to improve binding affinity predictions by the following: model training and testing using high-resolution crystallographic data to minimize structural noise, independent models of enthalpic and entropic contributions fitted to thermodynamic parameters assumed to be thermodynamically biased to calculate binding free energy, use of shape and volume descriptors to better capture entropic contributions. A set of 42 descriptors and 112 protein-ligand complexes were used to derive functions using partial least-squares for change of enthalpy (ΔH) and change of entropy (TΔS) to calculate change of binding free energy (ΔG), resulting in a predictive r2 (r(pred)2) of 0.55 and a standard error (SE) of 1.34 kcal/mol. External validation using the 2009 version of the PDBbind "refined set" (n = 1612) resulted in a Pearson correlation coefficient (R(p)) of 0.575 and a mean error (ME) of 1.41 pK(d). Enthalpy and entropy predictions were of limited accuracy individually. However, their difference resulted in a relatively accurate binding free energy. While the development of an accurate and applicable scoring function was an objective of this study, the main focus was evaluation of the use of high-resolution X-ray crystal structures with high-quality thermodynamic parameters from isothermal titration calorimetry for scoring function development. With the increasing application of structure-based methods in molecular design, this study suggests that using high-resolution crystal structures, separating enthalpy and entropy contributions to binding free energy, and including descriptors to better capture entropic contributions may prove to be effective strategies toward rapid and accurate calculation of binding affinity.

Electron paramagnetic resonance studies of functionally active, nitroxide spin-labeled peptide analogues of the C-terminus of a G-protein alpha subunit.

The C-terminal tail of the transducin alpha subunit, Gtalpha(340-350), is known to bind and stabilize the active conformation of rhodopsin upon photoactivation (R*). Five spin-labeled analogues of Gtalpha(340-350) demonstrated native-like activity in their ability to bind and stabilize R*. The spin-label 2,2,6,6-tetramethylpiperidine-1-oxyl-4-amino-4-carboxylic acid (TOAC) was employed at interior sites within the peptide, whereas a Proxyl (3-carboxyl-2,2,5,5-tetramethyl-pyrrolidinyloxy) spin-label was employed at the amino terminus of the peptide. Upon binding to R*, the electron paramagnetic resonance spectrum of TOAC(343)-Gtalpha(340-350) revealed greater immobilization of the nitroxide when compared to that of the N-terminally modified Proxyl-Gtalpha(340-350) analogue. A doubly labeled Proxyl/TOAC(348)-Gtalpha(340-350) was examined by DEER spectrocopy to determine the distribution of distances between the two nitroxides in the peptides when in solution and when bound to R*. TOAC and Proxyl spin-labels in this GPCR-G-protein alpha-peptide system provide unique biophysical probes that can be used to explore the structure and conformational changes at the rhodopsin-G-protein interface.

Modeling the possible conformations of the extracellular loops in G-protein-coupled receptors.

This study presents the results of a de novo approach modeling possible conformational dynamics of the extracellular (EC) loops in G-protein-coupled receptors (GPCRs), specifically in bovine rhodopsin (bRh), squid rhodopsin (sRh), human beta-2 adrenergic receptor (beta2AR), turkey beta-1 adrenergic receptor (beta1AR), and human A2 adenosine receptor (A2AR). The approach deliberately sacrificed a detailed description of any particular 3D structure of the loops in GPCRs in favor of a less precise description of many possible structures. Despite this, the approach found ensembles of the low-energy conformers of the EC loops that contained structures close to the available X-ray snapshots. For the smaller EC1 and EC3 loops (6-11 residues), our results were comparable with the best recent results obtained by other authors using much more sophisticated techniques. For the larger EC2 loops (25-34 residues), our results consistently yielded structures significantly closer to the X-ray snapshots than the results of the other authors for loops of similar size. The results suggested possible large-scale movements of the EC loops in GPCRs that might determine their conformational dynamics. The approach was also validated by accurately reproducing the docking poses for low-molecular-weight ligands in beta2AR, beta1AR, and A2AR, demonstrating the possible influence of the conformations of the EC loops on the binding sites of ligands. The approach correctly predicted the system of disulfide bridges between the EC loops in A2AR and elucidated the probable pathways for forming this system.

SKATE: a docking program that decouples systematic sampling from scoring.

SKATE is a docking prototype that decouples systematic sampling from scoring. This novel approach removes any interdependence between sampling and scoring functions to achieve better sampling and, thus, improves docking accuracy. SKATE systematically samples a ligand's conformational, rotational and translational degrees of freedom, as constrained by a receptor pocket, to find sterically allowed poses. Efficient systematic sampling is achieved by pruning the combinatorial tree using aggregate assembly, discriminant analysis, adaptive sampling, radial sampling, and clustering. Because systematic sampling is decoupled from scoring, the poses generated by SKATE can be ranked by any published, or in-house, scoring function. To test the performance of SKATE, ligands from the Asetex/CDCC set, the Surflex set, and the Vertex set, a total of 266 complexes, were redocked to their respective receptors. The results show that SKATE was able to sample poses within 2 A RMSD of the native structure for 98, 95, and 98% of the cases in the Astex/CDCC, Surflex, and Vertex sets, respectively. Cross-docking accuracy of SKATE was also assessed by docking 10 ligands to thymidine kinase and 73 ligands to cyclin-dependent kinase.

Synthesis of the phenylpyridal scaffold as a helical peptide mimetic.

Phenylpyridal- and phenyldipyridal-based scaffolds have been designed and synthesized as novel helical peptide mimetics. The synthesis required optimisation and selective alkylation in producing 2,6-functionalized 3-hydroxypyridine derivatives for a convergent scheme. The pyridine analogues were coupled by a series of Suzuki/Stille types cross-coupling reactions. A series of biaryl and ter-aryl substituted heterocycles were produced. The synthetic approach was concise and high yielding allowing large variability at the wanted side-chain attachment points. A number of compounds were synthesised to show the versatility of the strategy.

A second look at mini-protein stability: analysis of FSD-1 using circular dichroism, differential scanning calorimetry, and simulations.

Mini-proteins that contain <50 amino acids often serve as model systems for studying protein folding because their small size makes long timescale simulations possible. However, not all mini-proteins are created equal. The stability and structure of FSD-1, a 28-residue mini-protein that adopted the betabetaalpha zinc-finger motif independent of zinc binding, was investigated using circular dichroism, differential scanning calorimetry, and replica-exchange molecular dynamics. The broad melting transition of FSD-1, similar to that of a helix-to-coil transition, was observed by using circular dichroism, differential scanning calorimetry, and replica-exchange molecular dynamics. The N-terminal beta-hairpin was found to be flexible. The FSD-1 apparent melting temperature of 41 degrees C may be a reflection of the melting of its alpha-helical segment instead of the entire protein. Thus, despite its attractiveness due to small size and purposefully designed helix, sheet, and turn structures, the status of FSD-1 as a model system for studying protein folding should be reconsidered.

A virtual library of constrained cyclic tetrapeptides that mimics all four side-chain orientations for over half the reverse turns in the protein data bank.

Reverse turns are often recognition sites for protein/protein interactions and, therefore, valuable potential targets for determining recognition motifs in development of potential therapeutics. A virtual combinatorial library of cyclic tetrapeptides (CTPs) was generated and the bonds in the low-energy structures were overlapped with canonical reverse-turn Calpha-Cbeta bonds (Tran et al., J Comput Aided Mol Des 19(8):551-566, 2005) to determine the utility of CTPs as reverse-turn peptidomimetics. All reverse turns in the Protein Data Bank (PDB) with a crystal structures resolution < or = 3.0 A were classified into the same known canonical reverse-turn Calpha-Cbeta bond clusters (Tran et al., J Comput Aided Mol Des 19(8):551-566, 2005). CTP reverse-turn mimics were compiled that mimicked both the relative orientations of three of the four as well as all four Calpha-Cbeta bonds in the reverse turns of the PDB. 54% of reverse turns represented in the PDB had eight or more CTPs structures that mimicked the orientation of all four of the Calpha-Cbeta bonds in the reverse turn.