Fragment-Based Discovery of a Series of Allosteric-Binding Site Modulators of ß-Glucocerebrosidase.

ß-Glucocerebrosidase (GBA/GCase) mutations leading to misfolded protein cause Gaucher's disease and are a major genetic risk factor for Parkinson's disease and dementia with Lewy bodies. The identification of small molecule pharmacological chaperones that can stabilize the misfolded protein and increase delivery of degradation-prone mutant GCase to the lysosome is a strategy under active investigation. Here, we describe the first use of fragment-based drug discovery (FBDD) to identify pharmacological chaperones of GCase. The fragment hits were identified by using X-ray crystallography and biophysical techniques. This work led to the discovery of a series of compounds that bind GCase with nM potency and positively modulate GCase activity in cells.

Fragment-Based Discovery of Allosteric Inhibitors of SH2 Domain-Containing Protein Tyrosine Phosphatase-2 (SHP2).

The ubiquitously expressed protein tyrosine phosphatase SHP2 is required for signaling downstream of receptor tyrosine kinases (RTKs) and plays a role in regulating many cellular processes. Genetic knockdown and pharmacological inhibition of SHP2 suppresses RAS/MAPK signaling and inhibit the proliferation of RTK-driven cancer cell lines. Here, we describe the first reported fragment-to-lead campaign against SHP2, where X-ray crystallography and biophysical techniques were used to identify fragments binding to multiple sites on SHP2. Structure-guided optimization, including several computational methods, led to the discovery of two structurally distinct series of SHP2 inhibitors binding to the previously reported allosteric tunnel binding site (Tunnel Site). One of these series was advanced to a low-nanomolar lead that inhibited tumor growth when dosed orally to mice bearing HCC827 xenografts. Furthermore, a third series of SHP2 inhibitors was discovered binding to a previously unreported site, lying at the interface of the C-terminal SH2 and catalytic domains.

The Good, the Bad, and the Twisted Revisited: An Analysis of Ligand Geometry in Highly Resolved Protein-Ligand X-ray Structures.

An analysis of the rotatable bond geometry of drug-like ligand models is reported for high-resolution (<1.1 Å) crystallographic protein-ligand complexes. In cases where the ligand fit to the electron density is very good, unusual torsional geometry is rare and, most often, though not exclusively, associated with strong polar, metal, or covalent ligand-protein interactions. It is rarely associated with a torsional strain of greater than 2 kcal mol-1 by calculation. An unusual torsional geometry is more prevalent where the fit to electron density is not perfect. Multiple low-strain conformer bindings were observed in 21% of the set and, it is suggested, may also lie behind many of the 35% of single-occupancy cases, where a poor fit to the e-density was found. It is concluded that multiple conformer ligand binding is an under-recognized phenomenon in structure-based drug design and that there is a need for more robust crystallographic refinement methods to better handle such cases.

New active leads for tuberculosis booster drugs by structure-based drug discovery.

The transcriptional repressor EthR from Mycobacterium tuberculosis, a member of the TetR family of prokaryotic homo-dimeric transcription factors, controls the expression of the mycobacterial mono-oxygenase EthA. EthA is responsible for the bio-activation of the second-line tuberculosis pro-drug ethionamide, and consequently EthR inhibitors boost drug efficacy. Here, we present a comprehensive in silico structure-based screening protocol that led to the identification of a number of novel scaffolds of EthR inhibitors in subsequent biophysical screening by thermal shift assay. Growth inhibition assays demonstrated that five of the twenty biophysical hits were capable of boosting ethionamide activity in vitro, with the best novel scaffold displaying an EC50 of 34 µM. In addition, the co-crystal structures of EthR with four new ligands at resolution ranging from 2.1 to 1.4 Å confirm the binding and inactivation mode, and will enable future lead development.

Structural and docking studies of potent ethionamide boosters.

Tuberculosis remains the second only to HIV as the leading cause of death by infectious disease worldwide, and was responsible for 1.4 million deaths globally in 2011. One of the essential drugs of the second-line antitubercular regimen is the prodrug ethionamide, introduced in the 1960s. Ethionamide is primarily used in cases of multi-drug resistant (MDR) and extensively drug resistant (XDR) TB due to severe adverse side effects. As a prodrug, ethionamide is bioactivated by EthA, a mono-oxygenase whose activity is repressed by EthR, a member of the TetR family of regulators. Previous studies have established that inhibition of EthR improves ethionamide potency. We report here the crystal structures of three EthR inhibitors at 0.8 Šresolution (3-oxo-3-{4-[3-(thiophen-2-yl)-1,2,4-oxadiazol-5-yl]piperidin-1-yl}propanenitrile (BDM31343), 4,4,4-trifluoro-1-{4-[3-(6-methoxy-1,3-benzothiazol-2-yl)-1,2,4-oxadiazol-5-yl]piperidin-1-yl}butanone (BDM41325) and 5,5,5-trifluoro-1-{4-[3-(4-methanesulfonylphenyl)-1,2,4-oxadiazol-5-yl]piperidin-1-yl}pentanone (BDM41907)), and the docking studies undertaken to investigate possible binding modes. The results revealed two distinct orientations of the three compounds in the binding channel, a direct consequence of the promiscuous nature of the largely lipophilic binding site.

Potential and limitations of ensemble docking.

A major problem in structure-based virtual screening applications is the appropriate selection of a single or even multiple protein structures to be used in the virtual screening process. A priori it is unknown which protein structure(s) will perform best in a virtual screening experiment. We investigated the performance of ensemble docking, as a function of ensemble size, for eight targets of pharmaceutical interest. Starting from single protein structure docking results, for each ensemble size up to 500,000 combinations of protein structures were generated, and, for each ensemble, pose prediction and virtual screening results were derived. Comparison of single to multiple protein structure results suggests improvements when looking at the performance of the worst and the average over all single protein structures to the performance of the worst and average over all protein ensembles of size two or greater, respectively. We identified several key factors affecting ensemble docking performance, including the sampling accuracy of the docking algorithm, the choice of the scoring function, and the similarity of database ligands to the cocrystallized ligands of ligand-bound protein structures in an ensemble. Due to these factors, the prospective selection of optimum ensembles is a challenging task, shown by a reassessment of published ensemble selection protocols.

Validating and understanding ring conformations using small molecule crystallographic data.

Understanding the conformational preferences of ring structures is fundamental to structure-based drug design. Although the Cambridge Structural Database (CSD) provides information on the preferred conformations of small molecules, analyzing this data can be very time-consuming. In order to overcome this hurdle, tools have been developed for quickly extracting geometrical preferences from the CSD. Here we describe how the program Mogul has been extended to analyze and compare ring conformations, using a library derived from over 900 000 ring fragments in the CSD. We illustrate how these can be used to understand the conformational preferences of molecules in a crystal lattice and bound to proteins.

Pose prediction and virtual screening performance of GOLD scoring functions in a standardized test.

The performance of all four GOLD scoring functions has been evaluated for pose prediction and virtual screening under the standardized conditions of the comparative docking and scoring experiment reported in this Edition. Excellent pose prediction and good virtual screening performance was demonstrated using unmodified protein models and default parameter settings. The best performing scoring function for both pose prediction and virtual screening was demonstrated to be the recently introduced scoring function ChemPLP. We conclude that existing docking programs already perform close to optimally in the cognate pose prediction experiments currently carried out and that more stringent pose prediction tests should be used in the future. These should employ cross-docking sets. Evaluation of virtual screening performance remains problematic and much remains to be done to improve the usefulness of publically available active and decoy sets for virtual screening. Finally we suggest that, for certain target/scoring function combinations, good enrichment may sometimes be a consequence of 2D property recognition rather than a modelling of the correct 3D interactions.

The hydrogen bond environments of 1H-tetrazole and tetrazolate rings: the structural basis for tetrazole-carboxylic acid bioisosterism.

Bioisosterism involving replacement of a carboxylic acid substituent by 1H-tetrazole, yielding deprotonated carboxylate and tetrazolate under physiological conditions, is a well-known synthetic strategy in medicinal chemistry. To improve our overall understanding of bioisosterism, we have used this example to study the geometrical and energetic aspects of the functional group replacement. Specifically, we use crystal structure informatics and high-level ab initio calculations to study the hydrogen bond (H-bond) energy landscapes of the protonated and deprotonated bioisosteric pairs. Each pair exhibits very similar H-bond environments in crystal structures retrieved from the CSD, and the attractive energies of these H-bonds are also very similar. However, by comparison with -COOH and -COO(-), the H-bond environments around 1H-tetrazole and tetrazolate substituents extend further, by about 1.2 Å, from the core of the connected molecule. Analysis of pairs of PDB structures containing ligands which differ only in having a tetrazole or a carboxyl substituent and which are bound to the same protein indicates that the protein binding site must flex sufficiently to form strong H-bonds to either substituent. A survey of DrugBank shows a rather small number of tetrazole-containing drugs in the 'approved' and 'experimental' drug sections of that database.

Testing assumptions and hypotheses for rescoring success in protein-ligand docking.

In protein-ligand docking, the scoring function is responsible for identifying the correct pose of a particular ligand as well as separating ligands from nonligands. Recently there has been considerable interest in schemes that combine results from several scoring functions in an effort to achieve improved performance in virtual screens. One such scheme is consensus scoring, which involves combining the results from several rescoring experiments. Although there have been a number of studies that have investigated factors affecting success in consensus scoring, these studies have not addressed the question of why a rescoring strategy works in the first place. Here we propose and test two alternative hypotheses for why rescoring has the potential to improve results, using GOLD 4.0. The "consensus" hypothesis is that rescoring is a way of combining results from two scoring functions such that only true positives are likely to score highly. The "complementary" hypothesis is that the two scoring functions used in rescoring have complementary strengths; one is better at ranking actives with respect to inactives while the other is better at ranking poses of actives. We find that in general it is this hypothesis that explains success in a rescoring experiment. We also test an assumption of any rescoring method, which is that the scores obtained are representative of the fitness of the docked pose. We find that although rescored poses tended to have slightly higher clash values than their docked equivalents, in general the scores were representative.

Evaluating docking programs: keeping the playing field level.

Over recent years many enrichment studies have been published which purport to rigorously compare the performance of two or more docking protocols. It has become clear however that such studies often have flaws within their methodologies, which cast doubt on the rigour of the conclusions. Setting up such comparisons is fraught with difficulties and no best mode of practice is available to guide the experimenter. Careful choice of structural models and ligands appropriate to those models is important. The protein structure should be representative for the target. In addition the set of active ligands selected should be appropriate to the structure in cases where different forms of the protein bind different classes of ligand. Binding site definition is also an area in which errors arise. Particular care is needed in deciding which crystallographic waters to retain and again this may be predicated by knowledge of the likely binding modes of the ligands making up the active ligand list. Geometric integrity of the ligand structures used is clearly important yet it is apparent that published sets of actives + decoys may contain sometimes high proportions of incorrect structures. Choice of protocol for docking and analysis needs careful consideration as many programs can be tweaked for optimum performance. Should studies be run using 'black box' protocols supplied by the software provider? Lastly, the correct method of analysis of enrichment studies is a much discussed topic at the moment. However currently promoted approaches do not consider a crucial aspect of a successful virtual screen, namely that a good structural diversity of hits be returned. Overall there is much to consider in the experimental design of enrichment studies. Hopefully this study will be of benefit in helping others plan such experiments.

Investigation of the terminal P4 domain in a series of D-phenylglycinamide-based factor Xa inhibitors.

Several P4 domain derivatives of the general d-phenylglycinamide-based scaffold (2) were synthesized and evaluated for their ability to bind to the serine protease factor Xa. Some of the more potent compounds were evaluated for their anticoagulant effects in vitro. A select subset containing various P1 indole constructs was further evaluated for their pharmacokinetic properties after oral administration to rats.

A four component coupling strategy for the synthesis of D-phenylglycinamide-derived non-covalent factor Xa inhibitors.

A novel isonitrile derivative was synthesized and used in an Ugi four component coupling reaction to explore aryl group substitution effects on inhibition of the coagulation cascade serine protease factor Xa.

PRO_SELECT: combining structure-based drug design and array-based chemistry for rapid lead discovery. 2. The development of a series of highly potent and selective factor Xa inhibitors.

In silico screening of combinatorial libraries prior to synthesis promises to be a valuable aid to lead discovery. PRO_SELECT, a tool for the virtual screening of libraries for fit to a protein active site, has been used to find novel leads against the serine protease factor Xa. A small seed template was built upon using three iterations of library design, virtual screening, synthesis, and biological testing. Highly potent molecules with selectivity for factor Xa over other serine proteases were rapidly obtained.