The structural basis for cancer drug interactions with the catalytic and allosteric sites of SAMHD1.

SAMHD1 is a deoxynucleoside triphosphate triphosphohydrolase (dNTPase) that depletes cellular dNTPs in noncycling cells to promote genome stability and to inhibit retroviral and herpes viral replication. In addition to being substrates, cellular nucleotides also allosterically regulate SAMHD1 activity. Recently, it was shown that high expression levels of SAMHD1 are also correlated with significantly worse patient responses to nucleotide analog drugs important for treating a variety of cancers, including acute myeloid leukemia (AML). In this study, we used biochemical, structural, and cellular methods to examine the interactions of various cancer drugs with SAMHD1. We found that both the catalytic and the allosteric sites of SAMHD1 are sensitive to sugar modifications of the nucleotide analogs, with the allosteric site being significantly more restrictive. We crystallized cladribine-TP, clofarabine-TP, fludarabine-TP, vidarabine-TP, cytarabine-TP, and gemcitabine-TP in the catalytic pocket of SAMHD1. We found that all of these drugs are substrates of SAMHD1 and that the efficacy of most of these drugs is affected by SAMHD1 activity. Of the nucleotide analogs tested, only cladribine-TP with a deoxyribose sugar efficiently induced the catalytically active SAMHD1 tetramer. Together, these results establish a detailed framework for understanding the substrate specificity and allosteric activation of SAMHD1 with regard to nucleotide analogs, which can be used to improve current cancer and antiviral therapies.

Comparison of the umbrella sampling and the double decoupling method in binding free energy predictions for SAMPL6 octa-acid host-guest challenges.

We calculate the absolute binding free energies of tetra-methylated octa-acids host-guest systems as a part of the SAMPL6 blind challenge (receipt ID vq30p). We employed two different free energy simulation methods, i.e., the umbrella sampling (US) and double decoupling method (DDM). The US method was used with the weighted histogram analysis method (WHAM) (US-WHAM scheme). In the DDM scheme, Hamiltonian replica-exchange method (HREM) was combined with the Bennett acceptance ratio (BAR) (HREM-BAR scheme). We obtained initial binding poses via molecular docking using GalaxyDock-HG program, which is developed for the SAMPL challenge. The root mean square deviation (RMSD) and the mean absolute deviations (MAD) using US-WHAM scheme were 1.33 and 1.02 kcal/mol, respectively. The MAD was the top among all submissions, however the correlation with respect to experiment was unexceptional. While the RMSD and MAD via HREM-BAR scheme were greater than US-WHAM scheme, (i.e., 2.09 and 1.76 kcal/mol), their correlations were slightly better than US-WHAM. The correlation between the two methods was high. Further discussion on the DDM method can be found in a companion paper by Han et al. (receipt ID 3z83m) in the same issue.

Prediction of CB[8] host-guest binding free energies in SAMPL6 using the double-decoupling method.

This study reports the results of binding free energy calculations for CB[8] host-guest systems in the SAMPL6 blind challenge (receipt ID 3z83m). Force-field parameters were developed specific for each of host and guest molecules to improve configurational sampling. We used quantum mechanical (QM) implicit solvent calculations and QM force matching to determine non-bonded (partial atomic charges) and bonded terms, respectively. Free energy calculations were carried out using the double-decoupling method (DDM) combined with Hamiltonian replica exchange method (HREM) and Bennett acceptance ratio (BAR) method. The root mean square error (RMSE) of the predicted values using DDM with respect to the experimental results was 4.32 kcal/mol. The coefficient of determination (R2) and Kendall rank coefficient (τ) were 0.49 and 0.52, respectively, highest of all submissions. In addition, these were compared to the results obtained by umbrella sampling (US) and weighted histogram analysis method (WHAM). Overall, DDM achieved a higher prediction accuracy than the US method. Results are discussed in terms of parameterization and free energy simulations.

Absolute binding free energies for octa-acids and guests in SAMPL5 : Evaluating binding free energies for octa-acid and guest complexes in the SAMPL5 blind challenge.

As part of the SAMPL5 blind prediction challenge, we calculate the absolute binding free energies of six guest molecules to an octa-acid (OAH) and to a methylated octa-acid (OAMe). We use the double decoupling method via thermodynamic integration (TI) or Hamiltonian replica exchange in connection with the Bennett acceptance ratio (HREM-BAR). We produce the binding poses either through manual docking or by using GalaxyDock-HG, a docking software developed specifically for this study. The root mean square deviations for our most accurate predictions are 1.4 kcal mol-1 for OAH with TI and 1.9 kcal mol-1 for OAMe with HREM-BAR. Our best results for OAMe were obtained for systems with ionic concentrations corresponding to the ionic strength of the experimental solution. The most problematic system contains a halogenated guest. Our attempt to model the σ-hole of the bromine using a constrained off-site point charge, does not improve results. We use results from molecular dynamics simulations to argue that the distinct binding affinities of this guest to OAH and OAMe are due to a difference in the flexibility of the host. We believe that the results of this extensive analysis of host-guest complexes will help improve the protocol used in predicting binding affinities for larger systems, such as protein-substrate compounds.

Absolute binding free energy calculations of CBClip host-guest systems in the SAMPL5 blind challenge.

Herein, we report the absolute binding free energy calculations of CBClip complexes in the SAMPL5 blind challenge. Initial conformations of CBClip complexes were obtained using docking and molecular dynamics simulations. Free energy calculations were performed using thermodynamic integration (TI) with soft-core potentials and Bennett's acceptance ratio (BAR) method based on a serial insertion scheme. We compared the results obtained with TI simulations with soft-core potentials and Hamiltonian replica exchange simulations with the serial insertion method combined with the BAR method. The results show that the difference between the two methods can be mainly attributed to the van der Waals free energies, suggesting that either the simulations used for TI or the simulations used for BAR, or both are not fully converged and the two sets of simulations may have sampled difference phase space regions. The penalty scores of force field parameters of the 10 guest molecules provided by CHARMM Generalized Force Field can be an indicator of the accuracy of binding free energy calculations. Among our submissions, the combination of docking and TI performed best, which yielded the root mean square deviation of 2.94 kcal/mol and an average unsigned error of 3.41 kcal/mol for the ten guest molecules. These values were best overall among all participants. However, our submissions had little correlation with experiments.

Blind prediction of distribution in the SAMPL5 challenge with QM based protomer and pK a corrections.

The computation of distribution coefficients between polar and apolar phases requires both an accurate characterization of transfer free energies between phases and proper accounting of ionization and protomerization. We present a protocol for accurately predicting partition coefficients between two immiscible phases, and then apply it to 53 drug-like molecules in the SAMPL5 blind prediction challenge. Our results combine implicit solvent QM calculations with classical MD simulations using the non-Boltzmann Bennett free energy estimator. The OLYP/DZP/SMD method yields predictions that have a small deviation from experiment (RMSD = 2.3 [Formula: see text] D units), relative to other participants in the challenge. Our free energy corrections based on QM protomer and [Formula: see text] calculations increase the correlation between predicted and experimental distribution coefficients, for all methods used. Unfortunately, these corrections are overly hydrophilic, and fail to account for additional effects such as aggregation, water dragging and the presence of polar impurities in the apolar phase. We show that, although expensive, QM-NBB free energy calculations offer an accurate and robust method that is superior to standard MM and QM techniques alone.

Calculating distribution coefficients based on multi-scale free energy simulations: an evaluation of MM and QM/MM explicit solvent simulations of water-cyclohexane transfer in the SAMPL5 challenge.

One of the central aspects of biomolecular recognition is the hydrophobic effect, which is experimentally evaluated by measuring the distribution coefficients of compounds between polar and apolar phases. We use our predictions of the distribution coefficients between water and cyclohexane from the SAMPL5 challenge to estimate the hydrophobicity of different explicit solvent simulation techniques. Based on molecular dynamics trajectories with the CHARMM General Force Field, we compare pure molecular mechanics (MM) with quantum-mechanical (QM) calculations based on QM/MM schemes that treat the solvent at the MM level. We perform QM/MM with both density functional theory (BLYP) and semi-empirical methods (OM1, OM2, OM3, PM3). The calculations also serve to test the sensitivity of partition coefficients to solute polarizability as well as the interplay of the quantum-mechanical region with the fixed-charge molecular mechanics environment. Our results indicate that QM/MM with both BLYP and OM2 outperforms pure MM. However, this observation is limited to a subset of cases where convergence of the free energy can be achieved.

Membrane Protein Structure, Function, and Dynamics: a Perspective from Experiments and Theory.

Membrane proteins mediate processes that are fundamental for the flourishing of biological cells. Membrane-embedded transporters move ions and larger solutes across membranes; receptors mediate communication between the cell and its environment and membrane-embedded enzymes catalyze chemical reactions. Understanding these mechanisms of action requires knowledge of how the proteins couple to their fluid, hydrated lipid membrane environment. We present here current studies in computational and experimental membrane protein biophysics, and show how they address outstanding challenges in understanding the complex environmental effects on the structure, function, and dynamics of membrane proteins.

Turning up the heat mimics allosteric signaling in imidazole-glycerol phosphate synthase.

Allosteric drugs have the potential to revolutionize biomedicine due to their enhanced selectivity and protection against overdosage. However, we need to better understand allosteric mechanisms in order to fully harness their potential in drug discovery. In this study, molecular dynamics simulations and nuclear magnetic resonance spectroscopy are used to investigate how increases in temperature affect allostery in imidazole glycerol phosphate synthase. Results demonstrate that temperature increase triggers a cascade of local amino acid-to-amino acid dynamics that remarkably resembles the allosteric activation that takes place upon effector binding. The differences in the allosteric response elicited by temperature increase as opposed to effector binding are conditional to the alterations of collective motions induced by either mode of activation. This work provides an atomistic picture of temperature-dependent allostery, which could be harnessed to more precisely control enzyme function.

Amyloid Fibril Design: Limiting Structural Polymorphism in Alzheimer's Aß Protofilaments.

Nanoscale fibrils formed by amyloid peptides have a polymorphic character, adopting several types of molecular structures in similar growth conditions. As shown by experimental (e.g., solid-state NMR) and computational studies, amyloid fibril polymorphism hinders both the structural characterization of Alzheimer's Aß amyloid protofilaments and fibrils at a molecular level, as well as the possible applications (e.g., development of drugs or biomarkers) that rely on similar, controlled molecular arrangements of the Aß peptides in amyloid fibril structures. We have explored the use of several contact potentials for the efficient identification of minimal sequence mutations that could enhance the stability of specific fibril structures while simultaneously destabilizing competing topologies, controlling thus the amount of structural polymorphism in a rational way. We found that different types of contact potentials, while having only partial accuracy on their own, lead to similar results regarding ranking the compatibility of wild-type (WT) and mutated amyloid sequences with different fibril morphologies. This approach allows exhaustive screening and assessment of possible mutations and the identification of minimal consensus mutations that could stabilize fibrils with the desired topology at the expense of other topology types, a prediction that is further validated using atomistic molecular dynamics with explicit water molecules. We apply this two-step multiscale (i.e., residue and atomistic-level) approach to predict and validate mutations that could bias either parallel or antiparallel packing in the core Alzheimer's Aß9-40 amyloid fibril models based on solid-state NMR experiments. Besides shedding new light on the molecular origins of structural polymorphism in WT Aß fibrils, our study could also lead to efficient tools for assisting future experimental approaches for amyloid fibril determination, and for the development of biomarkers or drugs aimed at interfering with the stability of amyloid fibrils, as well as for the future design of amyloid fibrils with a controlled (e.g., reduced) level of structural polymorphism.

Structural Modulation of Human Amylin Protofilaments by Naturally Occurring Mutations.

Human islet amyloid polypeptide (hIAPP), also known as amylin, is a 37-amino-acid peptide, co-secreted with insulin, and widely found in fibril form in type-2 diabetes patients. By using all-atom molecular dynamics simulations, we study hIAPP fibril segments (i.e., fibrillar oligomers) formed with sequences of naturally occurring variants from cat, rat, and pig, presenting different aggregation propensities. We characterize the effect of mutations on the structural dynamics of solution-formed hIAPP fibril models built from solid-state NMR data. Results from this study are in agreement with experimental observations regarding their respective relative aggregation propensities. We analyze in detail the specific structural characteristics and infer mechanisms that modulate the conformational stability of amylin fibrils. Results provide a platform for further studies and the design of new drugs that could interfere with amylin aggregation and its cytotoxicity. One particular mutation, N31K, has fibril-destabilizing properties, and could potentially improve the solubility of therapeutic amylin analogs.

Modulation of Alzheimer's Aß protofilament-membrane interactions by lipid headgroups.

The molecular pathogenesis of Alzheimer's disease (AD) is complex and sparsely understood. The relationship between AD's amyloid ß (Aß) peptides and neuronal membranes is central to Aß's cytotoxicity and is directly modulated by the composition of the lipid headgroups. Molecular studies of the insertion of model Aß40 protofilaments in lipid bilayers revealed strong interactions that affect the structural integrity of both the membranes and the ordered amyloid aggregates. In particular, electrostatics plays a crucial role in the interaction between Aß protofilaments and palmytoil-oleoyl-phosphatidylethanolamine (POPE) lipids, a common component of neuronal plasma membranes. Here, we use all-atom molecular dynamics and steered molecular dynamics simulations to systematically compare the effects that POPE and palmytoil-oleoyl-phosphatidylcholine (POPC) headgroups have on the Aß-lipid interactions. We find that Aß protofilaments exhibit weaker electrostatic interactions with POPC headgroups and establish significantly shorter-lived contacts with the POPC bilayer. This illustrates the crucial yet complex role of electrostatic and hydrogen bonding interactions in modulating the anchoring and insertion of Aß peptides into lipid bilayers. Our study reveals the atomistic details behind the barrier created by the lipid headgroup region in impeding solution-aggregated fibrillar oligomers to spontaneously insert into POPC bilayers, in contrast to the POPE case. While the biological reality is notoriously more complex (e.g., including other factors such as cholesterol), our results evidence a simple experimentally and computationally testable case for probing the factors that control the insertion of Aß oligomeric aggregates in neuronal cell membranes--a process central to their neurotoxicity.

Molecular interactions of Alzheimer's Aß protofilaments with lipid membranes.

Amyloid fibrils and peptide oligomers play central roles in the pathology of Alzheimer's disease, type 2 diabetes, Parkinson's disease, Huntington's disease, and prion-related disease. Here, we investigate the molecular interactions between preformed amyloid ß (Aß) molecular protofilaments and lipid bilayer membranes, in the presence of explicit water molecules, using computational models and all-atom molecular dynamics. These interactions play an important role in the stability and function of both Aß fibrils and the adjacent cellular membrane. Taking advantage of the symmetry-related and directional properties of the protofilaments, we build models that cover several relative protofilament-membrane orientations. Our molecular dynamics simulations reveal the relative contributions of different structural elements to the dynamics and stability of Aß protofilament segments near membranes, and the first steps in the mechanism of fibril-membrane interactions. During this process, we observe a significant alteration of the side-chain contact pattern in protofilaments, although a fraction of the characteristic ß-sheet content is preserved. As a major driving force, we identify the electrostatic interactions between Aß charged side chains, including E22, D23, and K28, and lipid headgroups. Together with hydrogen bonding with atoms from lipid headgroups, these interactions can facilitate the penetration of hydrophobic C-terminal amino acids through the lipid headgroup region, which can finally lead both to further loss of the initial fibril structure and to local membrane-thinning effects. Our results may guide new experiments that could test the extent to which the structural features of water-formed amyloid fibrils are preserved, lost, or reshaped by membrane-mediated interactions.

Alzheimer Aß peptide interactions with lipid membranes: fibrils, oligomers and polymorphic amyloid channels.

Fibrillar aggregates of misfolded amyloid proteins are involved in a variety of diseases such as Alzheimer disease (AD), type 2 diabetes, Parkinson, Huntington and prion-related diseases. In the case of AD amyloid ß (Aß) peptides, the toxicity of amyloid oligomers and larger fibrillar aggregates is related to perturbing the biological function of the adjacent cellular membrane. We used atomistic molecular dynamics (MD) simulations of Aß 9-40 fibrillar oligomers modeled as protofilament segments, including lipid bilayers and explicit water molecules, to probe the first steps in the mechanism of Aß-membrane interactions. Our study identified the electrostatic interaction between charged peptide residues and the lipid headgroups as the principal driving force that can modulate the further penetration of the C-termini of amyloid fibrils or fibrillar oligomers into the hydrophobic region of lipid membranes. These findings advance our understanding of the detailed molecular mechanisms and the effects related to Aß-membrane interactions, and suggest a polymorphic structural character of amyloid ion channels embedded in lipid bilayers. While inter-peptide hydrogen bonds leading to the formation of ß-strands may still play a stabilizing role in amyloid channel structures, these may also present a significant helical content in peptide regions (e.g., termini) that are subject to direct interactions with lipids rather than with neighboring Aß peptides.

Are Peptides Good Two-State Folders?

The folding kinetics of proteins is frequently single-exponential, as basins of folded and unfolded conformations are well separated by a high barrier. However, for relatively short peptides, a two-state character of folding is rather the exception than the rule. In this work, we use a Zwanzig-type model of protein conformational dynamics to study the dependence of folding kinetics on the protein chain length, M. The analysis is focused on the gap in the eigenvalue spectrum of the rate matrix that describes the protein's conformational dynamics. When there is a large gap between the two smallest in magnitude nonzero eigenvalues, the corresponding relaxation times have qualitatively different physical interpretations. The longest of these two times characterizes the interbasin equilibration (i.e., folding), whereas the second time characterizes the intrabasin relaxation. We derive approximate analytical solutions for the two eigenvalues that show how they depend on M. From these solutions, we infer that there is a large gap between the two, and thus, the kinetics is essentially single-exponential when M is large enough such that 2(M+1) is much larger than M(2).