Search

The isotropic hyperfine coupling constant (HFCC, Aiso) of a pH-sensitive spin probe in a solution, HMI (2,2,3,4,5,5-hexamethylimidazolidin-1-oxyl, C9H19N2O) in water, is computed using an ensemble of state-of-the-art computational techniques and is gauged against X-band continuous wave electron paramagnetic resonance (EPR) measurement spectra at room temperature. Fundamentally, the investigation aims to delineate the cutting edge of current first-principles-based calculations of EPR parameters in aqueous solutions based on using rigorous statistical mechanics combined with correlated electronic structure techniques. In particular, the impact of solvation is described by exploiting fully atomistic, RISM integral equation, and implicit solvation approaches as offered by ab initio molecular dynamics (AIMD) of the periodic bulk solution (using the spin-polarized revPBE0-D3 hybrid functional), embedded cluster reference interaction site model integral equation theory (EC-RISM), and polarizable continuum embedding (using CPCM) of microsolvated complexes, respectively. HFCCs are obtained from efficient coupled cluster calculations (using open-shell DLPNO-CCSD theory) as well as from hybrid density functional theory (using revPBE0-D3). Re-solvation of "vertically desolvated" spin probe configuration snapshots by EC-RISM embedding is shown to provide significantly improved results compared to CPCM since only the former captures the inherent structural heterogeneity of the solvent close to the spin probe. The average values of the Aiso parameter obtained based on configurational statistics using explicit water within AIMD and from EC-RISM solvation are found to be satisfactorily close. Using either such explicit or RISM solvation in conjunction with DLPNO-CCSD calculations of the HFCCs provides an average Aiso parameter for HMI in aqueous solution at 300 K and 1 bar that is in good agreement with the experimentally determined one. The developed computational strategy is general in the sense that it can be readily applied to other spin probes of similar molecular complexity, to aqueous solutions beyond ambient conditions, as well as to other solvents in the longer run.

Inspired by the successful application of the embedded cluster reference interaction site model (EC-RISM), a combination of quantum–mechanical calculations with three-dimensional RISM theory to predict Gibbs energies of species in solution within the SAMPL6.1 (acidity constants, pKa) and SAMPL6.2 (octanol–water partition coefficients, log P) the methodology was applied to the recent SAMPL7 physical property challenge on aqueous pKa and octanol–water log P values. Not part of the challenge but provided by the organizers, we also computed distribution coefficients log D7.4 from predicted pKa and log P data. While macroscopic pKa predictions compared very favorably with experimental data (root mean square error, RMSE 0.72 pK units), the performance of the log P model (RMSE 1.84) fell behind expectations from the SAMPL6.2 challenge, leading to reasonable log D7.4 predictions (RMSE 1.69) from combining the independent calculations. In the post-submission phase, conformations generated by different methodology yielded results that did not significantly improve the original predictions. While overall satisfactory compared to previous log D challenges, the predicted data suggest that further effort is needed for optimizing the robustness of the partition coefficient model within EC-RISM calculations and for shaping the agreement between experimental conditions and the corresponding model description., Journal of computer aided molecular design.;Band 35, Heft 8, Seiten 933-941

The Statistical Assessment of Modeling of Proteins and Ligands (SAMPL) challenges focuses the computational modeling community on areas in need of improvement for rational drug design. The SAMPL7 physical property challenge dealt with prediction of octanol-water partition coefficients and pKa for 22 compounds. The dataset was composed of a series of N-acylsulfonamides and related bioisosteres. 17 research groups participated in the log P challenge, submitting 33 blind submissions total. For the pKa challenge, 7 different groups participated, submitting 9 blind submissions in total. Overall, the accuracy of octanol-water log P predictions in the SAMPL7 challenge was lower than octanol-water log P predictions in SAMPL6, likely due to a more diverse dataset. Compared to the SAMPL6 pKa challenge, accuracy remains unchanged in SAMPL7. Interestingly, here, though macroscopic pKa values were often predicted with reasonable accuracy, there was dramatically more disagreement among participants as to which microscopic transitions produced these values (with methods often disagreeing even as to the sign of the free energy change associated with certain transitions), indicating far more work needs to be done on pKa prediction methods.

Modulating the activity of ion channels by blockers yields information on both the mode of drug action and on the biophysics of ion transport. Here we investigate the interplay between ions in the selectivity filter (SF) of K+ channels and the release kinetics of the blocker tetrapropylammonium in the model channel KcvNTS. A quantitative expression calculates blocker release rate constants directly from voltage-dependent ion occupation probabilities in the SF. The latter are obtained by a kinetic model of single-channel currents recorded in the absence of the blocker. The resulting model contains only two adjustable parameters of ion-blocker interaction and holds for both symmetric and asymmetric ionic conditions. This data-derived model is corroborated by 3D reference interaction site model (3D RISM) calculations on several model systems, which show that the K+ occupation probability is unaffected by the blocker, a direct consequence of the strength of the ion-carbonyl attraction in the SF, independent of the specific protein background. Hence, KcvNTS channel blocker release kinetics can be reduced to a small number of system-specific parameters. The pore-independent asymmetric interplay between K+ and blocker ions potentially allows for generalizing these results to similar potassium channels.

DNA‐encoded compound libraries are a widely used small molecule screening technology. One important aim in library design is the coverage of chemical space through structurally diverse molecules. Yet, the chemical reactivity of native DNA barcodes limits the toolbox of reactions for library design. Substituting the chemically vulnerable purines by 7‐deazaadenine, which exhibits tautomerization stability similar to natural adenine with respect to the formation of stable Watson–Crick pairs, yielded ligation‐competent, amplifiable, and readable DNA barcodes for encoded chemistry with enhanced stability against protic acid‐ and metal ion‐promoted depurination. The barcode stability allowed for straightforward translation of 16 exemplary reactions that included isocyanide multicomponent reactions, acid‐promoted Pictet–Spengler and Biginelli reactions, and metal‐promoted pyrazole syntheses on controlled pore glass‐coupled barcodes for diverse DEL design. The Boc protective group of reaction products offered a convenient handle for encoded compound purification., DNA‐encoded compound libraries (DELs) are a widely used screening technology. DNA reactivity limits the reaction scope for library synthesis. Substituting the purines by 7‐deazaadenine yielded functional DNA barcodes with enhanced chemical stability. Controlled pore glass‐coupled barcodes tolerated isocyanide multicomponent reactions, the acid‐promoted Pictet–Spengler reaction, and YbIII‐ and AuI‐mediated pyrazole syntheses for DEL design.

We report the x-ray crystal structure of intact, full-length human immunoglobulin (IgG4) at 1.8 A resolution. The data for IgG4 (S228P), an antibody targeting the natriuretic peptide receptor A, show a previously unrecognized type of Fab-Fc orientation with a distorted λ-shape in which one Fab-arm is oriented toward the Fc portion. Detailed structural analysis by x-ray crystallography and molecular simulations suggest that this is one of several conformations coexisting in a dynamic equilibrium state. These results were confirmed by small angle x-ray scattering in solution. Furthermore, electron microscopy supported these findings by preserving molecule classes of different conformations. This study fosters our understanding of IgG4 in particular and our appreciation of antibody flexibility in general. Moreover, we give insights into potential biological implications, specifically for the interaction of human anti-natriuretic peptide receptor A IgG4 with the neonatal Fc receptor, Fcγ receptors, and complement-activating C1q by considering conformational flexibility.

Joint academic–industrial projects supporting drug discovery are frequently pursued to deploy and benchmark cutting-edge methodical developments from academia in a real-world industrial environment at different scales. The dimensionality of tasks ranges from small molecule physicochemical property assessment over protein–ligand interaction up to statistical analyses of biological data. This way, method development and usability both benefit from insights gained at both ends, when predictiveness and readiness of novel approaches are confirmed, but the pharmaceutical drug makers get early access to novel tools for the quality of drug products and benefit of patients. Quantum–mechanical and simulation methods particularly fall into this group of methods, as they require skills and expense in their development but also significant resources in their application, thus are comparatively slowly dripping into the realm of industrial use. Nevertheless, these physics-based methods are becoming more and more useful. Starting with a general overview of these and in particular quantum–mechanical methods for drug discovery we review a decade-long and ongoing collaboration between Sanofi and the Kast group focused on the application of the embedded cluster reference interaction site model (EC-RISM), a solvation model for quantum chemistry, to study small molecule chemistry in the context of joint participation in several SAMPL (Statistical Assessment of Modeling of Proteins and Ligands) blind prediction challenges. Starting with early application to tautomer equilibria in water (SAMPL2) the methodology was further developed to allow for challenge contributions related to predictions of distribution coefficients (SAMPL5) and acidity constants (SAMPL6) over the years. Particular emphasis is put on a frequently overlooked aspect of measuring the quality of models, namely the retrospective analysis of earlier datasets and predictions in light of more recent and advanced developments. We therefore demonstrate the performance of the current methodical state of the art as developed and optimized for the SAMPL6 pKa and octanol–water log P challenges when re-applied to the earlier SAMPL5 cyclohexane-water log D and SAMPL2 tautomer equilibria datasets. Systematic improvement is not consistently found throughout despite the similarity of the problem class, i.e. protonation reactions and phase distribution. Hence, it is possible to learn about hidden bias in model assessment, as results derived from more elaborate methods do not necessarily improve quantitative agreement. This indicates the role of chance or coincidence for model development on the one hand which allows for the identification of systematic error and opportunities toward improvement and reveals possible sources of experimental uncertainty on the other. These insights are particularly useful for further academia–industry collaborations, as both partners are then enabled to optimize both the computational and experimental settings for data generation., Journal of computer-aided molecular design;35

Evolution has yielded biopolymers that are constructed from exactly four building blocks and are able to support Darwinian evolution. Synthetic biology aims to extend this alphabet, and we recently showed that 8-letter (hachimoji) DNA can support rule-based information encoding. One source of replicative error in non-natural DNA-like systems, however, is the occurrence of alternative tautomeric forms, which pair differently. Unfortunately, little is known about how structural modifications impact free-energy differences between tautomers of the non-natural nucleo¬bases used in the hachimoji expanded genetic alphabet. Determining experimental tautomer ratios is technically difficult and so strategies for improving hachimoji DNA replication efficiency will benefit from accurate computational predictions of equilibrium tautomeric ratios. We now report that high-level quantum-chemical calculations in aqueous solution by the embedded cluster reference interaction site model (EC-RISM), benchmarked against free energy molecular simulations for solvation thermodynamics, provide useful quantitative information on the tautomer ratios of both Watson-Crick and hachimoji nucleobases. In agreement with previous computational studies, all four Watson-Crick nucleobases adopt essentially only one tautomer in water. This is not the case, however, for non-natural nucleobases and their analogs. For example, although the enols of isoguanine and a series of related purines are not populated in water, these heterocycles possess N1-H and N3-H keto tautomers that are similar in energy thereby adversely impacting accurate nucleobase pairing. These robust computational strategies offer a firm basis for improving experimental measurements of tautomeric ratios, which are currently limited to studying molecules that exist only as two tautomers in solution.

Results are reported for octanol–water partition coefficients (log P) of the neutral states of drug-like molecules provided during the SAMPL6 (Statistical Assessment of Modeling of Proteins and Ligands) blind prediction challenge from applying the “embedded cluster reference interaction site model” (EC-RISM) as a solvation model for quantum-chemical calculations. Following the strategy outlined during earlier SAMPL challenges we first train 1- and 2-parameter water-free (“dry”) and water-saturated (“wet”) models for n-octanol solvation Gibbs energies with respect to experimental values from the “Minnesota Solvation Database” (MNSOL), yielding a root mean square error (RMSE) of 1.5 kcal mol−1 for the best-performing 2-parameter wet model, while the optimal water model developed for the pKa part of the SAMPL6 challenge is kept unchanged (RMSE 1.6 kcal mol−1 for neutral compounds from a model trained on both neutral and ionic species). Applying these models to the blind prediction set yields a log P RMSE of less than 0.5 for our best model (2-parameters, wet). Further analysis of our results reveals that a single compound is responsible for most of the error, SM15, without which the RMSE drops to 0.2. Since this is the only compound in the challenge dataset with a hydroxyl group we investigate other alcohols for which Gibbs energy of solvation data for both water and n-octanol are available in the MNSOL database to demonstrate a systematic cause of error and to discuss strategies for improvement., J Comput Aided Mol Des;34

The “embedded cluster reference interaction site model” (EC-RISM) integral equation theory is applied to the problem of predicting aqueous pKa values for drug-like molecules based on an ensemble of tautomers. EC-RISM is based on self-consistent calculations of a solute’s electronic structure and the distribution function of surrounding water. Following-up on the workflow developed after the SAMPL5 challenge on cyclohexane-water distribution coefficients we extended and improved the methodology by taking into account exact electrostatic solute–solvent interactions taken from the wave function in solution. As before, the model is calibrated against Gibbs energies of hydration from the “Minnesota Solvation Database” and a public dataset of acidity constants of organic acids and bases by adjusting in total 4 parameters, among which only 3 are relevant for predicting pKa values. While the best-performing training model yields a root-mean-square error (RMSE) of 1 pK unit, the corresponding test set prediction on the full SAMPL6 dataset of macroscopic pKa values using the same level of theory exhibits slightly larger error (1.7 pK units) than the best test set model submitted (1.7 pK units for corresponding training set vs. test set performance of 1.6). Post-submission analysis revealed a number of physical optimization options regarding the numerical treatment of electrostatic interactions and conformational sampling. While the experimental test set data revealed after submission was not used for reparametrizing the methodology, the best physically optimized models consequentially result in RMSEs of 1.5 if only improved electrostatic interactions are considered and of 1.1 if, in addition, conformational sampling accounts for quantum-chemically derived rankings. We conclude that these numbers are probably near the ultimate accuracy achievable with the simple 3-parameter model using a single or the two best-ranking conformations per tautomer or microstate. Finally, relations of the present macrostate approach to microstate pKa results are discussed and some illustrative results for microstate populations are presented.

A neglect of diatomic differential overlap (NDDO) Hamiltonian has been parametrized as an electronic component of a polarizable force field. Coulomb and exchange potentials derived directly from the NDDO Hamiltonian in principle can be used with classical potentials, thus forming the basis for a new generation of efficiently applicable multipolar polarizable force fields. The new hpCADD Hamiltonian uses force-field-like atom types and reproduces the electrostatic properties (dipole moment, molecular electrostatic potential) and Koopmans' theorem ionization potentials closely, as demonstrated for a large training set and an independent test set of small molecules. The Hamiltonian is not intended to reproduce geometries or total energies well, as these will be controlled by the classical force-field potentials. In order to establish the hpCADD Hamiltonian as an electronic component in force-field-based calculations, we tested its performance in combination with the 3D reference interaction site model (3D RISM) for aqueous solutions. Comparison of the resulting solvation free energies for the training and test sets to atomic charges derived from standard procedures, exact solute-solvent electrostatics based on high-level quantum-chemical reference data, and established semiempirical Hamiltonians demonstrates the advantages of the hpCADD parametrization.

Water molecules play an essential role for mediating interactions between ligands and protein binding sites. Displacement of specific water molecules can favorably modulate the free energy of binding of protein-ligand complexes. Here, the nature of water interactions in protein binding sites is investigated by 3D RISM (three-dimensional reference interaction site model) integral equation theory to understand and exploit local thermodynamic features of water molecules by ranking their possible displacement in structure-based design. Unlike molecular dynamics-based approaches, 3D RISM theory allows for fast and noise-free calculations using the same detailed level of solute-solvent interaction description. Here we correlate molecular water entities instead of mere site density maxima with local contributions to the solvation free energy using novel algorithms. Distinct water molecules and hydration sites are investigated in multiple protein-ligand X-ray structures, namely streptavidin, factor Xa, and factor VIIa, based on 3D RISM-derived free energy density fields. Our approach allows the semiquantitative assessment of whether a given structural water molecule can potentially be targeted for replacement in structure-based design. Finally, PLS-based regression models from free energy density fields used within a 3D-QSAR approach (CARMa - comparative analysis of 3D RISM Maps) are shown to be able to extract relevant information for the interpretation of structure-activity relationship (SAR) trends, as demonstrated for a series of serine protease inhibitors.

The miniature channel, Kcv, is a structural equivalent of the pore of all K+ channels. Here, we follow up on a previous observation that a largely voltage-insensitive channel can be converted into a slow activating inward rectifier after extending the outer transmembrane domain by one Ala. This gain of rectification can be rationalized by dynamic salt bridges at the cytosolic entrance to the channel; opening is favored by voltage-sensitive formation of salt bridges and counteracted by their disruption. Such latent voltage sensitivity in the pore could be relevant for the understanding of voltage gating in complex Kv channels.

The study of the pressure response by NMR spectroscopy provides information on the thermodynamics of conformational equilibria in proteins and nucleic acids. For obtaining a database for expected pressure effects on free nucleotides and nucleotides bound in macromolecular complexes, the pressure response of

Molecular simulations based on classical force fields are a powerful method for shedding light on the complex behavior of biomolecules in solution. When cosolutes are present in addition to water and biomolecules, subtle balances of weak intermolecular forces have to be accounted for. This imposes high demands on the quality of the underlying force fields, and therefore force field development for small cosolutes is still an active field. Here, we present the development of a new urea force field from studies of urea solutions at ambient and elevated hydrostatic pressures based on a combination of experimental and theoretical approaches. Experimental densities and solvation shell properties from ab initio molecular dynamics simulations at ambient conditions served as the target properties for the force field optimization. Since urea is present in many marine life forms, elevated hydrostatic pressure was rigorously addressed: densities at high pressure were measured by vibrating tube densitometry up to 500 bar and by X-ray absorption up to 5 kbar. Densities were determined by the perturbed-chain statistical associating fluid theory equation of state. Solvation properties were determined by embedded cluster integral equation theory and ab initio molecular dynamics. Our new force field is able to capture the properties of urea solutions at high pressures without further high-pressure adaption, unlike trimethylamine-N-oxide, for which a high-pressure adaption is necessary.

Calculations of acidities of molecules with multiple tautomeric and/or conformational states require adequate treatment of the relative energetics of accessible states accompanied by a statistical-mechanical formulation of their contribution to the macroscopic pK

We predict cyclohexane–water distribution coefficients (log D 7.4) for drug-like molecules taken from the SAMPL5 blind prediction challenge by the “embedded cluster reference interaction site model” (EC-RISM) integral equation theory. This task involves the coupled problem of predicting both partition coefficients (log P) of neutral species between the solvents and aqueous acidity constants (pK a) in order to account for a change of protonation states. The first issue is addressed by calibrating an EC-RISM-based model for solvation free energies derived from the “Minnesota Solvation Database” (MNSOL) for both water and cyclohexane utilizing a correction based on the partial molar volume, yielding a root mean square error (RMSE) of 2.4 kcal mol−1 for water and 0.8–0.9 kcal mol−1 for cyclohexane depending on the parametrization. The second one is treated by employing on one hand an empirical pK a model (MoKa) and, on the other hand, an EC-RISM-derived regression of published acidity constants (RMSE of 1.5 for a single model covering acids and bases). In total, at most 8 adjustable parameters are necessary (2–3 for each solvent and two for the pK a) for training solvation and acidity models. Applying the final models to the log D 7.4 dataset corresponds to evaluating an independent test set comprising other, composite observables, yielding, for different cyclohexane parametrizations, 2.0–2.1 for the RMSE with the first and 2.2–2.8 with the combined first and second SAMPL5 data set batches. Notably, a pure log P model (assuming neutral species only) performs statistically similarly for these particular compounds. The nature of the approximations and possible perspectives for future developments are discussed.

Recent methodological progress in quantum-chemical calculations using the “embedded cluster reference interaction site model” (EC-RISM) integral equation theory is reviewed in the context of applying it as a solvation model for calculating pressure-dependent thermodynamic and spectroscopic properties of molecules immersed in water. The methodology is based on self-consistent calculations of electronic and solvation structure around dissolved molecules where pressure enters the equations via an appropriately chosen solvent response function and the pure solvent density. Besides specification of a dispersion-repulsion force field for solute-solvent interactions, the EC-RISM approach derives the electrostatic interaction contributions directly from the wave function. We further develop and apply the method to a variety of benchmark cases for which computational or experimental reference data are either available in the literature or are generated specifically for this purpose in this work. Starting with an enhancement to predict hydration free energies at non-ambient pressures, which is the basis for pressure-dependent molecular population estimation, we demonstrate the performance on the calculation of the autoionization constant of water. Spectroscopic problems are addressed by studying the biologically relevant small osmolyte TMAO (trimethylamine N-oxide). Pressure-dependent NMR shifts are predicted and compared to experiments taking into account proper computational referencing methods that extend earlier work. The experimentally observed IR blue-shifts of certain vibrational bands of TMAO as well as of the cyanide anion are reproduced by novel methodology that allows for weighing equilibrium and non-equilibrium solvent relaxation effects. Taken together, the model systems investigated allow for an assessment of the reliability of the EC-RISM approach for studying pressure-dependent biophysical processes.

The emergence of acquired resistance against targeted drugs remains a major clinical challenge in lung adenocarcinoma patients. In a subgroup of these patients we identified an association between selection of EGFRT790M-negative but EGFRG724S-positive subclones and osimertinib resistance. We demonstrate that EGFRG724S limits the activity of third-generation EGFR inhibitors both in vitro and in vivo. Structural analyses and computational modeling indicate that EGFRG724S mutations may induce a conformation of the glycine-rich loop, which is incompatible with the binding of third-generation TKIs. Systematic inhibitor screening and in-depth kinetic profiling validate these findings and show that second-generation EGFR inhibitors retain kinase affinity and overcome EGFRG724S-mediated resistance. In the case of afatinib this profile translates into a robust reduction of colony formation and tumor growth of EGFRG724S-driven cells. Our data provide a mechanistic basis for the osimertinib-induced selection of EGFRG724S-mutant clones and a rationale to treat these patients with clinically approved second-generation EGFR inhibitors., Acquired resistance to targeted drugs remains a major clinical challenge in lung adenocarcinoma patients. Here, the authors show how the acquired EGFRG724S mutation induces resistance to third-generation EGFR inhibitors and why the mutant kinase remains susceptible to second-generation inhibitors.

Oncogenic fusion events have been identified in a broad range of tumors. Among them, RET rearrangements represent distinct and potentially druggable targets that are recurrently found in lung adenocarcinomas. We provide further evidence that current anti-RET drugs may not be potent enough to induce durable responses in such tumors. We report that potent inhibitors, such as AD80 or ponatinib, that stably bind in the DFG-out conformation of RET may overcome these limitations and selectively kill RET-rearranged tumors. Using chemical genomics in conjunction with phosphoproteomic analyses in RET-rearranged cells, we identify the CCDC6-RETI788N mutation and drug-induced mitogen-activated protein kinase pathway reactivation as possible mechanisms by which tumors may escape the activity of RET inhibitors. Our data provide mechanistic insight into the druggability of RET kinase fusions that may be of help for the development of effective therapies targeting such tumors.

[Image: see text] Gating of ion channels is based on structural transitions between open and closed states. To uncover the chemical basis of individual gates, we performed a comparative experimental and computational analysis between two K(+) channels, Kcv(S) and Kcv(NTS). These small viral encoded K(+) channel proteins, with a monomer size of only 82 amino acids, resemble the pore module of all complex K(+) channels in terms of structure and function. Even though both proteins share about 90% amino acid sequence identity, they exhibit different open probabilities with ca. 90% in Kcv(NTS) and 40% in Kcv(S). Single channel analysis, mutational studies and molecular dynamics simulations show that the difference in open probability is caused by one long closed state in Kcv(S). This state is structurally created in the tetrameric channel by a transient, Ser mediated, intrahelical hydrogen bond. The resulting kink in the inner transmembrane domain swings the aromatic rings from downstream Phes in the cavity of the channel, which blocks ion flux. The frequent occurrence of Ser or Thr based helical kinks in membrane proteins suggests that a similar mechanism could also occur in the gating of other ion channels.

This study explores the thermodynamic and vibrational properties of water in the three-dimensional environment of solvated ions and small molecules using molecular simulations. The spectrum of intermolecular vibrations in liquid solvents provides detailed information on the shape of the local potential energy surface, which in turn determines local thermodynamic properties such as the entropy. Here, we extract this information using a spatially resolved extension of the two-phase thermodynamics method to estimate hydration water entropies based on the local vibrational density of states (3D-2PT). Combined with an analysis of solute–water and water–water interaction energies, this allows us to resolve local contributions to the solvation enthalpy, entropy, and free energy. We use this approach to study effects of ions on their surrounding water hydrogen bond network, its spectrum of intermolecular vibrations, and resulting thermodynamic properties. In the three-dimensional environment of polar and nonpolar functional groups of molecular solutes, we identify distinct hydration water species and classify them by their characteristic vibrational density of states and molecular entropies. In each case, we are able to assign variations in local hydration water entropies to specific changes in the spectrum of intermolecular vibrations. This provides an important link for the thermodynamic interpretation of vibrational spectra that are accessible to far-infrared absorption and Raman spectroscopy experiments. Our analysis provides unique microscopic details regarding the hydration of hydrophobic and hydrophilic functional groups, which enable us to identify interactions and molecular degrees of freedom that determine relevant contributions to the solvation entropy and consequently the free energy.

The bridge function of a simple liquid is calculated for the repulsive part of the Weeks–Chandler–Andersen (WCA) separation of the Lennard–Jones potential. We employ explicit molecular dynamics simulations of the potential of mean force between constrained dimers in order to extract bridge data near zero separation and illustrate the difference to full Lennard–Jones results. We compare direct, reciprocal space and iterative, real space inversions of the Ornstein–Zernike equation. Bridge functions for various thermodynamic states are analyzed as to their parametric dependence on the renormalized indirect correlation function, which has consequences for the analytic representation of the free energy functional.

The miniature channel, Kcv, is a structural equivalent of the pore of all K

Complex formation between molecules in solution is the key process by which molecular interactions are translated into functional systems. These processes are governed by the binding or free energy of association which depends on both direct molecular interactions and the solvation contribution. A design goal frequently addressed in pharmaceutical sciences is the optimization of chemical properties of the complex partners in the sense of minimizing their binding free energy with respect to a change in chemical structure. Here, we demonstrate that liquid-state theory in the form of the solute-solute equation of the reference interaction site model provides all necessary information for such a task with high efficiency. In particular, computing derivatives of the potential of mean force (PMF), which defines the free-energy surface of complex formation, with respect to potential parameters can be viewed as a means to define a direction in chemical space toward better binders. We illustrate the methodology in the benchmark case of alkali ion binding to the crown ether 18-crown-6 in aqueous solution. In order to examine the validity of the underlying solute-solute theory, we first compare PMFs computed by different approaches, including explicit free-energy molecular dynamics simulations as a reference. Predictions of an optimally binding ion radius based on free-energy derivatives are then shown to yield consistent results for different ion parameter sets and to compare well with earlier, orders-of-magnitude more costly explicit simulation results. This proof-of-principle study, therefore, demonstrates the potential of liquid-state theory for molecular design problems.

Accurate force fields are one of the major pillars on which successful molecular dynamics simulations of complex biomolecular processes rest. They have been optimized for ambient conditions, whereas high-pressure simulations become increasingly important in pressure perturbation studies, using pressure as an independent thermodynamic variable. Here, we explore the design of non-polarizable force fields tailored to work well in the realm of kilobar pressures – while avoiding complete reparameterization. Our key is to first compute the pressure-induced electronic and structural response of a solute by combining an integral equation approach to include pressure effects on solvent structure with a quantum-chemical treatment of the solute within the embedded cluster reference interaction site model (EC-RISM) framework. Next, the solute’s response to compression is taken into account by introducing pressure-dependence into selected parameters of a well-established force field. In our proof-of-principle study, the full machinery is applied to N,N,N-trimethylamine-N-oxide (TMAO) in water being a potent osmolyte that counteracts pressure denaturation. EC-RISM theory is shown to describe well the charge redistribution upon compression of TMAO(aq) to 10 kbar, which is then embodied in force field molecular dynamics by pressure-dependent partial charges. The performance of the high pressure force field is assessed by comparing to experimental and ab initio molecular dynamics data. Beyond its broad usefulness for designing non-polarizable force fields for extreme thermodynamic conditions, a good description of the pressure-response of solutions is highly recommended when constructing and validating polarizable force fields.

Author(s): Fechner, Uli; de Graaf, Chris; Torda, Andrew E; Gussregen, Stefan; Evers, Andreas; Matter, Hans; Hessler, Gerhard; Richmond, Nicola J; Schmidtke, Peter; Segler, Marwin HS; Waller, Mark P; Pleik, Stefanie; Shea, Joan-Emma; Levine, Zachary; Mullen, Ryan; van den Broek, Karina; Epple, Matthias; Kuhn, Hubert; Truszkowski, Andreas; Zielesny, Achim; Fraaije, Johannes Hans; Gracia, Ruben Serral; Kast, Stefan M; Bulusu, Krishna C; Bender, Andreas; Yosipof, Abraham; Nahum, Oren; Senderowitz, Hanoch; Krotzky, Timo; Schulz, Robert; Wolber, Gerhard; Bietz, Stefan; Rarey, Matthias; Zimmermann, Markus O; Lange, Andreas; Ruff, Manuel; Heidrich, Johannes; Onlia, Ionut; Exner, Thomas E; Boeckler, Frank M; Bermudez, Marcel; Firaha, Dzmitry S; Holloczki, Oldamur; Kirchner, Barbara; Tautermann, Christofer S; Volkamer, Andrea; Eid, Sameh; Turk, Samo; Rippmann, Friedrich; Fulle, Simone; Saleh, Noureldin; Saladino, Giorgio; Gervasio, Francesco L; Haensele, Elke; Banting, Lee; Whitley, David C; Oliveira Santos, Jana Sopkova-de; Bureau, Ronan; Clark, Timothy; Sandmann, Achim; Lanig, Harald; Kibies, Patrick; Heil, Jochen; Hoffgaard, Franziska; Frach, Roland; Engel, Julian; Smith, Steven; Basu, Debjit; Rauh, Daniel; Kohlbacher, Oliver; Boeckler, Frank M; Essex, Jonathan W; Bodnarchuk, Michael S; Ross, Gregory A; Finkelmann, Arndt R; Goller, Andreas H; Schneider, Gisbert; Husch, Tamara; Schutter, Christoph; Balducci, Andrea; Korth, Martin; Ntie-Kang, Fidele; Gunther, Stefan; Sippl, Wolfgang; Mbaze, Luc Meva'a

Biophysics under extreme conditions is the fundamental platform for scrutinizing life in unusual habitats, such as those in the deep sea or continental subsurfaces, but also for putative extraterrestrial organisms. Therefore, an important thermodynamic variable to explore is pressure. It is shown that the combination of infrared spectroscopy with simulation is an exquisite approach for unraveling the intricate pressure response of the solvation pattern of TMAO in water, which is expected to be transferable to biomolecules in their native solvent. Pressure-enhanced hydrogen bonding was found for TMAO in water. TMAO is a molecule known to stabilize proteins against pressure-induced denaturation in deep-sea organisms.

High-pressure (HP) NMR spectroscopy is an important method for detecting rare functional states of proteins by analyzing the pressure response of chemical shifts. However, for the analysis of the shifts it is mandatory to understand the origin of the observed pressure dependence. Here we present experimental HP NMR data on the (15) N-enriched peptide bond model, N-methylacetamide (NMA), in water, combined with quantum-chemical computations of the magnetic parameters using a pressure-sensitive solvation model. Theoretical analysis of NMA and the experimentally used internal reference standard 4,4-dimethyl-4-silapentane-1-sulfonic (DSS) reveal that a substantial part of observed shifts can be attributed to purely solvent-induced electronic polarization of the backbone. DSS is only marginally responsive to pressure changes and is therefore a reliable sensor for variations in the local magnetic field caused by pressure-induced changes of the magnetic susceptibility of the solvent.

Solvent-induced solute polarisation of nondipolar solvents originates mainly from specific directional interactions and higher electrostatic multipole moments. Popular continuum solvation models such as the polarisable continuum models ignore such interactions and, therefore, cannot adequately model solvation effects on electronic structure in these environments. Important examples of nondipolar solvents that are indistinguishable by continuum methods are benzene and hexafluorobenzene. Both substances have very similar macroscopic properties, while solutes dissolved in either benzene or hexafluorobenzene behave differently due to their inverted electrostatic quadrupole moments and slightly different size. As a first step towards a proper and computationally feasible description of nondipolar molecular solvents, we present here integral equation theory results based on various forms of the reference interaction site model coupled to quantum-chemical calculations for benzene and hexafluorobenzene solutions of small molecules. We analyse solvation structures, also in comparison with molecular dynamics simulations, and show that predictions of transfer Gibbs energies, which define partition constants, benefit substantially from considering the exact, wave function-derived electrostatic field distribution beyond a simple point charge solute model in comparison with experimental data. Moreover, by constructing artificial uncharged and charge-inverted toy models of the solvents, it is possible to dissect the relative importance of dispersion and quadrupolar electrostatic effects on the partitioning equilibria. Such insight can help to design specifically optimised solvents to control solubility and selectivity for a wide range of applications.

Transmembrane domains (TMDs) are often flanked by Lys or Arg because they keep their aliphatic parts in the bilayer and their charged groups in the polar interface. Here we examine the relevance of this so-called "snorkeling" of a cationic amino acid, which is conserved in the outer TMD of small viral K(+) channels. Experimentally, snorkeling activity is not mandatory for Kcv(PBCV-1) because K29 can be replaced by most of the natural amino acids without any corruption of function. Two similar channels, Kcv(ATCV-1) and Kcv(MT325), lack a cytosolic N-terminus, and neutralization of their equivalent cationic amino acids inhibits their function. To understand the variable importance of the cationic amino acids, we reanalyzed molecular dynamics simulations of Kcv(PBCV-1) and N-terminally truncated mutants; the truncated mutants mimic Kcv(ATCV-1) and Kcv(MT325). Structures were analyzed with respect to membrane positioning in relation to the orientation of K29. The results indicate that the architecture of the protein (including the selectivity filter) is only weakly dependent on TMD length and protonation of K29. The penetration depth of Lys in a given protonation state is independent of the TMD architecture, which leads to a distortion of shorter proteins. The data imply that snorkeling can be important for K(+) channels; however, its significance depends on the architecture of the entire TMD. The observation that the most severe N-terminal truncation causes the outer TMD to move toward the cytosolic side suggests that snorkeling becomes more relevant if TMDs are not stabilized in the membrane by other domains.

Some algal viruses contain genes that encode proteins with the hallmarks of K(+) channels. One feature of these proteins is that they are less than 100 amino acids in size, which make them truly minimal for a K(+) channel protein. That is, they consist of only the pore module present in more complex K(+) channels. The combination of miniature size and the functional robustness of the viral K(+) channels make them ideal model systems for studying how K(+) channels work. Here we summarize recent structure/function correlates from these channels, which provide insight into functional properties such as gating, pharmacology and sorting in cells.

Proteins are ubiquitous biopolymers that adopt distinct three-dimensional structures and fulfil a multitude of elementary functions in organisms. Recent systematic studies in molecular biology and biotechnology have improved the understanding of basic functional and architectural principles of proteins, making them attractive candidates as concept generators for technological development in material science, particularly in biomedicine and nano(bio)technology. This paper highlights the potential of molecular biomimetics in mimicking high-performance proteins and provides concepts for applications in four case studies, i.e. spider silk, antifreeze proteins, blue mussel adhesive proteins and viral ion channels.

A computational model for the open state of the short viral Kcv potassium channel was created and tested based on homology modeling and extensive molecular-dynamics simulation in a membrane environment. Particular attention was paid to the structure of the highly flexible N-terminal region and to the protonation state of membrane-exposed lysine residues. Data from various experimental sources, NMR spectroscopy, and electrophysiology, as well as results from three-dimensional reference interaction site model integral equation theory were taken into account to select the most reasonable model among possible variants. The final model exhibits spontaneous ion transitions across the complete pore, with and without application of an external field. The nonequilibrium transport events could be induced reproducibly without abnormally large driving potential and without the need to place ions artificially at certain key positions along the transition path. The transport mechanism through the filter region corresponds to the classic view of single-file motion, which in our case is coupled to frequent exchange of ions between the innermost filter position and the cavity.

The functional effect of mutations near the intracellular mouth of the short viral Kcv potassium channel was studied by molecular dynamics simulations. As a model system we used the analogously mutated and truncated KirBac1.1, a channel with known crystal structure that shares genuine local sequence motifs with Kcv. By a novel simulated annealing methodology for structural averaging, information about the structure and dynamics of the intracellular mouth was extracted and complemented by Poisson-Boltzmann and 3D-RISM (reference interaction site model) integral equation theory for the determination of the K+ free energy surface. Besides the wild-type analogue of Kcv with its experimental reference activity (truncated KirBac1.1), two variants were studied: a deletion mutant where the N-terminus is further truncated by eight amino acids, showing inactivity in the Kcv reference system, and a point mutant where the kink-forming proline at position 13 is substituted by alanine, resulting in hyperactivity. The computations reveal that the change of activity is closely related to a hydrophilic intracellular constriction formed by the C-terminal residues of the monomers. Hyperactivity of the point mutant is correlated with both sterical and electrostatic factors, while inactivity of the deletion mutant is related to a loss of specific salt bridge patterns between the C- and N-terminus at the constriction and to the consequences for ion passage barriers, as revealed by integral equation theory. The cytosolic gate, however, is probably formed by the N-terminal segment up to the proline kink and not by the constriction. The results are compared with design principles found for other channels.

Modeling solute polarizability is a key ingredient for improving the description of solvation phenomena. In recent years, polarizable molecular mechanics force fields have emerged that circumvent the limitations of classical fixed charge force fields by the ability to adapt their electrostatic potential distribution to a polarizing environment. Solvation phenomena are characterized by the solute's excess chemical potential, which can be computed by expensive fully atomistic free energy simulations. The alternative is to employ an implicit solvent model, which poses a challenge to the formulation of the solute-solvent interaction term within a polarizable framework. Here, we adapt the three-dimensional reference interaction site model (3D RISM) integral equation theory as a solvent model, which analytically yields the chemical potential, to the polarizable AMOEBA force field using an embedding cluster (EC-RISM) strategy. The methodology is analogous to our earlier approach to the coupling of a quantum-chemical solute description with a classical 3D RISM solvent. We describe the conceptual physical and algorithmic basis as well as the performance for several benchmark cases as a proof of principle. The results consistently show reasonable agreement between AMOEBA and quantum-chemical free energies in solution in general and allow for separate assessment of energetic and solvation-related contributions. We find that, depending on the parametrization, AMOEBA reproduces the chemical potential in better agreement with reference quantum-chemical calculations than the intramolecular energies, which suggests possible routes toward systematic improvement of polarizable force fields.

Receptor tyrosine kinases represent one of the prime targets in cancer therapy, as the dysregulation of these elementary transducers of extracellular signals, like the epidermal growth factor receptor (EGFR), contributes to the onset of cancer, such as non-small cell lung cancer (NSCLC). Strong efforts were directed to the development of irreversible inhibitors and led to compound CO-1686, which takes advantage of increased residence time at EGFR by alkylating Cys797 and thereby preventing toxic effects. Here, we present a structure-based approach, rationalized by subsequent computational analysis of conformational ligand ensembles in solution, to design novel and irreversible EGFR inhibitors based on a screening hit that was identified in a phenotype screen of 80 NSCLC cell lines against approximately 1500 compounds. Using protein X-ray crystallography, we deciphered the binding mode in engineered cSrc (T338M/S345C), a validated model system for EGFR-T790M, which constituted the basis for further rational design approaches. Chemical synthesis led to further compound collections that revealed increased biochemical potency and, in part, selectivity toward mutated (L858R and L858R/T790M) vs nonmutated EGFR. Further cell-based and kinetic studies were performed to substantiate our initial findings. Utilizing proteolytic digestion and nano-LC-MS/MS analysis, we confirmed the alkylation of Cys797.

The virus-coded channel Kcv has the typical structure of a two-transmembrane domain K(+) channel. Exceptional are its cytoplasmic domains: the C terminus basically ends inside the membrane and, hence, precludes the formation of a cytoplasmic gate by the so-called bundle crossing; the cytoplasmic N terminus is composed of only 12 amino acids. According to structural predictions, it is positioned in the membrane/aqueous interface and connected via a proline kink to the outer transmembrane domain (TM1). Here, we show that this proline kink affects channel function by determining the position of TM1 in the membrane bilayer. Extension of the hydrophobic length of TM1 by either eliminating the proline kink or introducing an alanine in TM1 augments a time- and voltage-dependent inward rectification of the channel. This suggests that the positional information of TM1 in the bilayer is transmitted to a channel gate, which is not identical with the cytoplasmic bundle crossing.

The question as to how many tightly or weakly bound water molecules are located in interfaces between protein-protein complex constituents is addressed from a phase equilibrium point of view by developing a theory in the canonical ensemble. A fast method based on free energy simulations is described for computing the number of water molecules in the interface regions. Results are given for 211 interfacial cavities of 26 antigen-antibody complexes for which experimentally determined structures are found in the Protein Data Bank. The accuracy of the method is assessed and the computational water content is compared with experimental data, revealing the amount of water molecules not resolved by experimental approaches.

Molecular integral equation theory is inverted with respect to the calculation of effective potentials for a coarse-grained, reduced molecular model composed of fewer sites than the reference. The methodology is applied to an aqueous solution of cyclohexanol as a model case, the quality of the effective potentials is studied by extensive molecular dynamics simulations. Practical guidelines for the choice of reduced model sites are worked out and perspectives for mesoscale modelling are discussed.