Mathematical and Structural Characterization of Strong Nonadditive Structure-Activity Relationship Caused by Protein Conformational Changes.

In medicinal chemistry, accurate prediction of additivity-based structure-activity relationship (SAR) analysis rests on three assumptions: (1) a consistent binding pose of the central scaffold, (2) no interaction between the R group substituents, and (3) a relatively rigid binding pocket in which the R group substituents act independently. Previously, examples of nonadditive SAR have been documented in systems that deviate from the first two assumptions. Local protein structural change upon ligand binding, through induced fit or conformational selection, although a well-known phenomenon that invalidates the third assumption, has not been linked to nonadditive SAR conclusively. Here, for the first time, we present clear structural evidence that the formation of a hydrophobic pocket upon ligand binding in PDE2 catalytic site reduces the size of another distinct subpocket and contributes to strong nonadditive SAR between two otherwise distant R groups.

Elucidating the Aß42 Anti-Aggregation Mechanism of Action of Tramiprosate in Alzheimer's Disease: Integrating Molecular Analytical Methods, Pharmacokinetic and Clinical Data.

BACKGROUND: Amyloid beta (Aß) oligomers play a critical role in the pathogenesis of Alzheimer's disease (AD) and represent a promising target for drug development. Tramiprosate is a small-molecule Aß anti-aggregation agent that was evaluated in phase III clinical trials for AD but did not meet the primary efficacy endpoints; however, a pre-specified subgroup analysis revealed robust, sustained, and clinically meaningful cognitive and functional effects in patients with AD homozygous for the ε4 allele of apolipoprotein E4 (APOE4/4 homozygotes), who carry an increased risk for the disease. Therefore, to build on this important efficacy attribute and to further improve its pharmaceutical properties, we have developed a prodrug of tramiprosate ALZ-801 that is in advanced stages of clinical development. To elucidate how tramiprosate works, we investigated its molecular mechanism of action (MOA) and the translation to observed clinical outcomes. OBJECTIVE: The two main objectives of this research were to (1) elucidate and characterize the MOA of tramiprosate via an integrated application of three independent molecular methodologies and (2) present an integrated translational analysis that links the MOA, conformation of the target, stoichiometry, and pharmacokinetic dose exposure to the observed clinical outcome in APOE4/4 homozygote subjects. METHOD: We used three molecular analytical methods-ion mobility spectrometry-mass spectrometry (IMS-MS), nuclear magnetic resonance (NMR), and molecular dynamics-to characterize the concentration-related interactions of tramiprosate versus Aß42 monomers and the resultant conformational alterations affecting aggregation into oligomers. The molecular stoichiometry of the tramiprosate versus Aß42 interaction was further analyzed in the context of clinical pharmacokinetic dose exposure and central nervous system Aß42 levels (i.e., pharmacokinetic-pharmacodynamic translation in humans). RESULTS: We observed a multi-ligand interaction of tramiprosate with monomeric Aß42, which differs from the traditional 1:1 binding. This resulted in the stabilization of Aß42 monomers and inhibition of oligomer formation and elongation, as demonstrated by IMS-MS and molecular dynamics. Using NMR spectroscopy and molecular dynamics, we also showed that tramiprosate bound to Lys16, Lys28, and Asp23, the key amino acid side chains of Aß42 that are responsible for both conformational seed formation and neuronal toxicity. The projected molar excess of tramiprosate versus Aß42 in humans using the dose effective in patients with AD aligned with the molecular stoichiometry of the interaction, providing a clear clinical translation of the MOA. A consistent alignment of these preclinical-to-clinical elements describes a unique example of translational medicine and supports the efficacy seen in symptomatic patients with AD. This unique "enveloping mechanism" of tramiprosate also provides a potential basis for tramiprosate dose selection for patients with homozygous AD at earlier stages of disease. CONCLUSION: We have identified the molecular mechanism that may account for the observed clinical efficacy of tramiprosate in patients with APOE4/4 homozygous AD. In addition, the integrated application of the molecular methodologies (i.e., IMS-MS, NMR, and thermodynamics analysis) indicates that it is feasible to modulate and control the Aß42 conformational dynamics landscape by a small molecule, resulting in a favorable Aß42 conformational change that leads to a clinically relevant amyloid anti-aggregation effect and inhibition of oligomer formation. This novel enveloping MOA of tramiprosate has potential utility in the development of disease-modifying therapies for AD and other neurodegenerative diseases caused by misfolded proteins.

A Molecular Dynamics Investigation of Mycobacterium tuberculosis Prenyl Synthases: Conformational Flexibility and Implications for Computer-aided Drug Discovery.

With the rise in antibiotic resistance, there is interest in discovering new drugs active against new targets. Here, we investigate the dynamic structures of three isoprenoid synthases from Mycobacterium tuberculosis using molecular dynamics (MD) methods with a view to discovering new drug leads. Two of the enzymes, cis-farnesyl diphosphate synthase (cis-FPPS) and cis-decaprenyl diphosphate synthase (cis-DPPS), are involved in bacterial cell wall biosynthesis, while the third, tuberculosinyl adenosine synthase (Rv3378c), is involved in virulence factor formation. The MD results for these three enzymes were then compared with previous results on undecaprenyl diphosphate synthase (UPPS) by means of active site volume fluctuation and principal component analyses. In addition, an analysis of the binding of prenyl diphosphates to cis-FPPS, cis-DPPS, and UPPS utilizing the new MD results is reported. We also screened libraries of inhibitors against cis-DPPS, finding ~1 µm inhibitors, and used the receiver operating characteristic-area under the curve (ROC-AUC) method to test the predictive power of X-ray and MD-derived cis-DPPS receptors. We found that one compound with potent M. tuberculosis cell growth inhibition activity was an IC(50) ~0.5- to 20-µm inhibitor (depending on substrate) of cis-DPPS, a ~660-nm inhibitor of Rv3378c as well as a 4.8-µm inhibitor of cis-FPPS, opening up the possibility of multitarget inhibition involving both cell wall biosynthesis and virulence factor formation.

Improved Reweighting of Accelerated Molecular Dynamics Simulations for Free Energy Calculation.

Accelerated molecular dynamics (aMD) simulations greatly improve the efficiency of conventional molecular dynamics (cMD) for sampling biomolecular conformations, but they require proper reweighting for free energy calculation. In this work, we systematically compare the accuracy of different reweighting algorithms including the exponential average, Maclaurin series, and cumulant expansion on three model systems: alanine dipeptide, chignolin, and Trp-cage. Exponential average reweighting can recover the original free energy profiles easily only when the distribution of the boost potential is narrow (e.g., the range ≤20kBT) as found in dihedral-boost aMD simulation of alanine dipeptide. In dual-boost aMD simulations of the studied systems, exponential average generally leads to high energetic fluctuations, largely due to the fact that the Boltzmann reweighting factors are dominated by a very few high boost potential frames. In comparison, reweighting based on Maclaurin series expansion (equivalent to cumulant expansion on the first order) greatly suppresses the energetic noise but often gives incorrect energy minimum positions and significant errors at the energy barriers (∼2-3kBT). Finally, reweighting using cumulant expansion to the second order is able to recover the most accurate free energy profiles within statistical errors of ∼kBT, particularly when the distribution of the boost potential exhibits low anharmonicity (i.e., near-Gaussian distribution), and should be of wide applicability. A toolkit of Python scripts for aMD reweighting "PyReweighting" is distributed free of charge at http://mccammon.ucsd.edu/computing/amdReweighting/.

Undecaprenyl diphosphate synthase inhibitors: antibacterial drug leads.

There is a significant need for new antibiotics due to the rise in drug resistance. Drugs such as methicillin and vancomycin target bacterial cell wall biosynthesis, but methicillin-resistant Staphylococcus aureus (MRSA) and vancomycin-resistant Enterococci (VRE) have now arisen and are of major concern. Inhibitors acting on new targets in cell wall biosynthesis are thus of particular interest since they might also restore sensitivity to existing drugs, and the cis-prenyl transferase undecaprenyl diphosphate synthase (UPPS), essential for lipid I, lipid II, and thus, peptidoglycan biosynthesis, is one such target. We used 12 UPPS crystal structures to validate virtual screening models and then assayed 100 virtual hits (from 450,000 compounds) against UPPS from S. aureus and Escherichia coli. The most promising inhibitors (IC50 ∼2 µM, Ki ∼300 nM) had activity against MRSA, Listeria monocytogenes, Bacillus anthracis, and a vancomycin-resistant Enterococcus sp. with MIC or IC50 values in the 0.25-4 µg/mL range. Moreover, one compound (1), a rhodanine with close structural similarity to the commercial diabetes drug epalrestat, exhibited good activity as well as a fractional inhibitory concentration index (FICI) of 0.1 with methicillin against the community-acquired MRSA USA300 strain, indicating strong synergism.

Exploring the role of receptor flexibility in structure-based drug discovery.

The proper understanding of biomolecular recognition mechanisms that take place in a drug target is of paramount importance to improve the efficiency of drug discovery and development. The intrinsic dynamic character of proteins has a strong influence on biomolecular recognition mechanisms and models such as conformational selection have been widely used to account for this dynamic association process. However, conformational changes occurring in the receptor prior and upon association with other molecules are diverse and not obvious to predict when only a few structures of the receptor are available. In view of the prominent role of protein flexibility in ligand binding and its implications for drug discovery, it is of great interest to identify receptor conformations that play a major role in biomolecular recognition before starting rational drug design efforts. In this review, we discuss a number of recent advances in computer-aided drug discovery techniques that have been proposed to incorporate receptor flexibility into structure-based drug design. The allowance for receptor flexibility provided by computational techniques such as molecular dynamics simulations or enhanced sampling techniques helps to improve the accuracy of methods used to estimate binding affinities and, thus, such methods can contribute to the discovery of novel drug leads.

Population based reweighting of scaled molecular dynamics.

Molecular dynamics simulation using enhanced sampling methods is one of the powerful computational tools used to explore protein conformations and free energy landscapes. Enhanced sampling methods often employ either an increase in temperature or a flattening of the potential energy surface to rapidly sample phase space, and a corresponding reweighting algorithm is used to recover the Boltzmann statistics. However, potential energies of complex biomolecules usually involve large fluctuations on a magnitude of hundreds of kcal/mol despite minimal structural changes during simulation. This leads to noisy reweighting statistics and complicates the obtainment of accurate final results. To overcome this common issue in enhanced conformational sampling, we propose a scaled molecular dynamics method, which modifies the biomolecular potential energy surface and employs a reweighting scheme based on configurational populations. Statistical mechanical theory is applied to derive the reweighting formula, and the canonical ensemble of simulated structures is recovered accordingly. Test simulations on alanine dipeptide and the fast folding polypeptide Chignolin exhibit sufficiently enhanced conformational sampling and accurate recovery of free energy surfaces and thermodynamic properties. The results are comparable to long conventional molecular dynamics simulations and exhibit better recovery of canonical statistics over methods which employ a potential energy term in reweighting.

w-REXAMD: A Hamiltonian Replica Exchange Approach to Improve Free Energy Calculations for Systems with Kinetically Trapped Conformations.

Free energy governs the equilibrium extent of many biological processes. High barriers separating free energy minima often limit the sampling in molecular dynamics (MD) simulations, leading to inaccurate free energies. Here, we demonstrate enhanced sampling and improved free energy calculations, relative to conventional MD, using windowed accelerated MD within a Hamiltonian replica exchange framework (w-REXAMD). We show that for a case in which multiple conformations are separated by large free energy barriers, w-REXAMD is a useful enhanced sampling technique, without any necessary reweighting.

Accounting for receptor flexibility and enhanced sampling methods in computer-aided drug design.

Protein flexibility plays a major role in biomolecular recognition. In many cases, it is not obvious how molecular structure will change upon association with other molecules. In proteins, these changes can be major, with large deviations in overall backbone structure, or they can be more subtle as in a side-chain rotation. Either way the algorithms that predict the favorability of biomolecular association require relatively accurate predictions of the bound structure to give an accurate assessment of the energy involved in association. Here, we review a number of techniques that have been proposed to accommodate receptor flexibility in the simulation of small molecules binding to protein receptors. We investigate modifications to standard rigid receptor docking algorithms and also explore enhanced sampling techniques, and the combination of free energy calculations and enhanced sampling techniques. The understanding and allowance for receptor flexibility are helping to make computer simulations of ligand protein binding more accurate. These developments may help improve the efficiency of drug discovery and development. Efficiency will be essential as we begin to see personalized medicine tailored to individual patients, which means specific drugs are needed for each patient's genetic makeup.

Antibacterial drug leads targeting isoprenoid biosynthesis.

With the rise in resistance to antibiotics such as methicillin, there is a need for new drugs. We report here the discovery and X-ray crystallographic structures of 10 chemically diverse compounds (benzoic, diketo, and phosphonic acids, as well as a bisamidine and a bisamine) that inhibit bacterial undecaprenyl diphosphate synthase, an essential enzyme involved in cell wall biosynthesis. The inhibitors bind to one or more of the four undecaprenyl diphosphate synthase inhibitor binding sites identified previously, with the most active leads binding to site 4, outside the catalytic center. The most potent leads are active against Staphylococcus aureus [minimal inhibitory concentration (MIC)(90) ∼0.25 µg/mL], and one potently synergizes with methicillin (fractional inhibitory concentration index = 0.25) and is protective in a mouse infection model. These results provide numerous leads for antibacterial development and open up the possibility of restoring sensitivity to drugs such as methicillin, using combination therapies.

Protecting High Energy Barriers: A New Equation to Regulate Boost Energy in Accelerated Molecular Dynamics Simulations.

Molecular dynamics (MD) is one of the most common tools in computational chemistry. Recently, our group has employed accelerated molecular dynamics (aMD) to improve the conformational sampling over conventional molecular dynamics techniques. In the original aMD implementation, sampling is greatly improved by raising energy wells below a predefined energy level. Recently, our group presented an alternative aMD implementation where simulations are accelerated by lowering energy barriers of the potential energy surface. When coupled with thermodynamic integration simulations, this implementation showed very promising results. However, when applied to large systems, such as proteins, the simulation tends to be biased to high energy regions of the potential landscape. The reason for this behavior lies in the boost equation used since the highest energy barriers are dramatically more affected than the lower ones. To address this issue, in this work, we present a new boost equation that prevents oversampling of unfavorable high energy conformational states. The new boost potential provides not only better recovery of statistics throughout the simulation but also enhanced sampling of statistically relevant regions in explicit solvent MD simulations.

Guide to virtual screening: application to the Akt phosphatase PHLPP.

We present an example-based description of virtual screening (VS) techniques used to identify new regulators of the Akt phosphatase PHLPP (PH domain Leucine repeat Protein Phosphatase). This enzyme opposes the effects of two kinases, Akt and PKC, which play a major role in cell growth and survival. Therefore, PHLPP is a potential therapeutic target in pathophysiologies where these pathways are either repressed, such as in diabetes and cardiovascular diseases, or over-activated as in cancer. To the best of our knowledge, no PHLPP inhibitors have been reported so far in the literature. In this study, we used a combination of chemical and virtual screening techniques that led to the identification of a number of inhibiting compounds with diverse scaffolds. These compounds bind PHLPP and inhibit cell death when tested in cellular assays. We employed GLIDE docking software to screen a library of more than 40,000 compounds selected from the NCI open depository (250,000 compounds) by similarity searches. We compare the efficiency at which we determined binding compounds from the chemical screen, and compare enrichment factors of the virtually discovered compounds over chemical screening.

Applying molecular dynamics simulations to identify rarely sampled ligand-bound conformational states of undecaprenyl pyrophosphate synthase, an antibacterial target.

Undecaprenyl pyrophosphate synthase is a cis-prenyltransferase enzyme, which is required for cell wall biosynthesis in bacteria. Undecaprenyl pyrophosphate synthase is an attractive target for antimicrobial therapy. We performed long molecular dynamics simulations and docking studies on undecaprenyl pyrophosphate synthase to investigate its dynamic behavior and the influence of protein flexibility on the design of undecaprenyl pyrophosphate synthase inhibitors. We also describe the first X-ray crystallographic structure of Escherichia coli apo-undecaprenyl pyrophosphate synthase. The molecular dynamics simulations indicate that undecaprenyl pyrophosphate synthase is a highly flexible protein, with mobile binding pockets in the active site. By carrying out docking studies with experimentally validated undecaprenyl pyrophosphate synthase inhibitors using high- and low-populated conformational states extracted from the molecular dynamics simulations, we show that structurally dissimilar compounds can bind preferentially to different and rarely sampled conformational states. By performing structural analyses on the newly obtained apo-undecaprenyl pyrophosphate synthase and other crystal structures previously published, we show that the changes observed during the molecular dynamics simulation are very similar to those seen in the crystal structures obtained in the presence or absence of ligands. We believe that this is the first time that a rare 'expanded pocket' state, key to drug design and verified by crystallography, has been extracted from a molecular dynamics simulation.

The wake-promoting effects of hypocretin-1 are attenuated in old rats.

Disruption of sleep is a frequent complaint among elderly humans and is also evident in aged laboratory rodents. The neurobiological bases of age-related sleep/wake disruption are unknown. Given the critical role of the hypocretins in sleep/wake regulation, we sought to determine whether the wake-promoting effect of hypocretin changes with age in Wistar rats, a strain in which age-related changes in both sleep and hypocretin signaling have been reported. Intracerebroventricular infusions of hypocretin-1 (10 and 30 µg) significantly increased wake time relative to vehicle in both young (3 mos) and old (25 mos) Wistar rats. However, the magnitude and duration of the wake-promoting effects were attenuated with age. An increase of parameters associated with homeostatic sleep recovery after sleep deprivation, including non-rapid eye movement (NR) sleep time, NR delta power, the ratio of NR to rapid eye movement (REM) sleep, and NR consolidation, occurred subsequent to Hcrt-induced waking in young but not old rats. ICV infusions of hypocretin-2 (10 and 30 µg) produced fewer effects in both young and old rats. These data demonstrate that activation of a major sleep/wake regulatory pathway is attenuated in old rats.

Discovery of small molecule inhibitors of the PH domain leucine-rich repeat protein phosphatase (PHLPP) by chemical and virtual screening.

PH domain Leucine-rich repeat protein phosphatase (PHLPP) directly dephosphorylates and inactivates Akt and protein kinase C, poising it as a prime target for pharmacological intervention of two major survival pathways. Here we report on the discovery of small molecule inhibitors of the phosphatase activity of PHLPP, a member of the PP2C family of phosphatases for which there are no general pharmacological inhibitors. First, the Diversity Set of the NCI was screened for inhibition of the purified phosphatase domain of PHLPP2 in vitro. Second, selected libraries from the open NCI database were docked into a virtual model of the phosphatase domain of PHLPP2, previously trained with our experimental data set, unveiling additional inhibitors. Biochemical and cellular assays resulted in the identification of two structurally diverse compounds that selectively inhibit PHLPP in vitro, increase Akt signaling in cells, and prevent apoptosis. Thus, chemical and virtual screening has resulted in the identification of small molecules that promote Akt signaling by inhibiting its negative regulator PHLPP.