The Determination of Free Energy of Hydration of Water Ions from First Principles.

We model the autoionization of water by determining the free energy of hydration of the major intermediate species of water ions. We represent the smallest ions─the hydroxide ion OH-, the hydronium ion H3O+, and the Zundel ion H5O2+─by bonded models and the more extended ionic structures by strong nonbonded interactions (e.g., the Eigen H9O4+ = H3O+ + 3(H2O) and the Stoyanov H13O6+ = H5O2+ + 4(H2O)). Our models are faithful to the precise QM energies and their components to within 1% or less. Using the calculated free energies and atomization energies, we compute the pKa of pure water from first principles as a consistency check and arrive at a value within 1.3 log units of the experimental one. From these calculations, we conclude that the hydronium ion, and its hydrated state, the Eigen cation, are the dominant species in the water autoionization process.

Combining Force Fields and Neural Networks for an Accurate Representation of Bonded Interactions.

We present a formalism of a neural network encoding bonded interactions in molecules. This intramolecular encoding is consistent with the models of intermolecular interactions previously designed by this group. Variants of the encoding fed into a corresponding neural network may be used to economically improve the representation of torsional degrees of freedom in any force field. We test the accuracy of the reproduction of the ab initio potential energy surface on a set of conformations of two dipeptides, methyl-capped ALA and ASP, in several scenarios. The encoding, either alone or in conjunction with an analytical potential, improves agreement with ab initio energies that are on par with those of other neural network-based potentials. Using the encoding and neural nets in tandem with an analytical model places the agreements firmly within "chemical accuracy" of ±0.5 kcal/mol.

Neural Network Corrections to Intermolecular Interaction Terms of a Molecular Force Field Capture Nuclear Quantum Effects in Calculations of Liquid Thermodynamic Properties.

We incorporate nuclear quantum effects (NQE) in condensed matter simulations by introducing short-range neural network (NN) corrections to the ab initio fitted molecular force field ARROW. Force field NN corrections are fitted to average interaction energies and forces of molecular dimers, which are simulated using the Path Integral Molecular Dynamics (PIMD) technique with restrained centroid positions. The NN-corrected force field allows reproduction of the NQE for computed liquid water and methane properties such as density, radial distribution function (RDF), heat of evaporation (HVAP), and solvation free energy. Accounting for NQE through molecular force field corrections circumvents the need for explicit computationally expensive PIMD simulations in accurate calculations of the properties of chemical and biological systems. The accuracy and locality of pairwise NN NQE corrections indicate that this approach could be applicable to complex heterogeneous systems, such as proteins.

Combining Force Fields and Neural Networks for an Accurate Representation of Chemically Diverse Molecular Interactions.

A key goal of molecular modeling is the accurate reproduction of the true quantum mechanical potential energy of arbitrary molecular ensembles with a tractable classical approximation. The challenges are that analytical expressions found in general purpose force fields struggle to faithfully represent the intermolecular quantum potential energy surface at close distances and in strong interaction regimes; that the more accurate neural network approximations do not capture crucial physics concepts, e.g., nonadditive inductive contributions and application of electric fields; and that the ultra-accurate narrowly targeted models have difficulty generalizing to the entire chemical space. We therefore designed a hybrid wide-coverage intermolecular interaction model consisting of an analytically polarizable force field combined with a short-range neural network correction for the total intermolecular interaction energy. Here, we describe the methodology and apply the model to accurately determine the properties of water, the free energy of solvation of neutral and charged molecules, and the binding free energy of ligands to proteins. The correction is subtyped for distinct chemical species to match the underlying force field, to segment and reduce the amount of quantum training data, and to increase accuracy and computational speed. For the systems considered, the hybrid ab initio parametrized Hamiltonian reproduces the two-body dimer quantum mechanics (QM) energies to within 0.03 kcal/mol and the nonadditive many-molecule contributions to within 2%. Simulations of molecular systems using this interaction model run at speeds of several nanoseconds per day.

Protein-Ligand Binding Free-Energy Calculations with ARROW─A Purely First-Principles Parameterized Polarizable Force Field.

Protein-ligand binding free-energy calculations using molecular dynamics (MD) simulations have emerged as a powerful tool for in silico drug design. Here, we present results obtained with the ARROW force field (FF)─a multipolar polarizable and physics-based model with all parameters fitted entirely to high-level ab initio quantum mechanical (QM) calculations. ARROW has already proven its ability to determine solvation free energy of arbitrary neutral compounds with unprecedented accuracy. The ARROW FF parameterization is now extended to include coverage of all amino acids including charged groups, allowing molecular simulations of a series of protein-ligand systems and prediction of their relative binding free energies. We ensure adequate sampling by applying a novel technique that is based on coupling the Hamiltonian Replica exchange (HREX) with a conformation reservoir generated via potential softening and nonequilibrium MD. ARROW provides predictions with near chemical accuracy (mean absolute error of ∼0.5 kcal/mol) for two of the three protein systems studied here (MCL1 and Thrombin). The third protein system (CDK2) reveals the difficulty in accurately describing dimer interaction energies involving polar and charged species. Overall, for all of the three protein systems studied here, ARROW FF predicts relative binding free energies of ligands with a similar accuracy level as leading nonpolarizable force fields.

Molecular Dynamics Simulations of Rhodamine B Zwitterion Diffusion in Polyelectrolyte Solutions.

Polyelectrolytes continue to find wide interest and application in science and engineering, including areas such as water purification, drug delivery, and multilayer thin films. We have been interested in the dynamics of small molecules in a variety of polyelectrolyte (PE) environments; in this paper, we report simulations and analysis of the small dye molecule rhodamine B (RB) in several very simple polyelectrolyte solutions. Translational diffusion of the RB zwitterion has been measured in fully atomistic, 2 µs long molecular dynamics simulations in four different polyelectrolyte solutions. Two solutions contain the common polyanion sodium poly(styrene sulfonate) (PSS), one with a 30-mer chain and the other with 10 trimers. The other two solutions contain the common polycation poly(allyldimethylammonium) chloride (PDDA), one with two 15-mers and the other with 10 trimers. RB diffusion was also simulated in several polymer-free solutions to verify its known experimental value for the translational diffusion coefficient, DRB, of 4.7 × 10-6 cm2/s at 300 K. RB diffusion was slowed in all four simulated PE solutions, but to varying degrees. DRB values of 3.07 × 10-6 and 3.22 × 10-6 cm2/s were found in PSS 30-mer and PSS trimer solutions, respectively, whereas PDDA 15-mer and trimer solutions yielded values of 2.19 × 10-6 and 3.34 × 10-6 cm2/s. Significant associations between RB and the PEs were analyzed and interpreted via a two-state diffusion model (bound and free diffusion) that describes the data well. Crowder size effects and anomalous diffusion were also analyzed. Finally, RB translation along the polyelectrolytes during association was characterized.

Accurate determination of solvation free energies of neutral organic compounds from first principles.

The main goal of molecular simulation is to accurately predict experimental observables of molecular systems. Another long-standing goal is to devise models for arbitrary neutral organic molecules with little or no reliance on experimental data. While separately these goals have been met to various degrees, for an arbitrary system of molecules they have not been achieved simultaneously. For biophysical ensembles that exist at room temperature and pressure, and where the entropic contributions are on par with interaction strengths, it is the free energies that are both most important and most difficult to predict. We compute the free energies of solvation for a diverse set of neutral organic compounds using a polarizable force field fitted entirely to ab initio calculations. The mean absolute errors (MAE) of hydration, cyclohexane solvation, and corresponding partition coefficients are 0.2 kcal/mol, 0.3 kcal/mol and 0.22 log units, i.e. within chemical accuracy. The model (ARROW FF) is multipolar, polarizable, and its accompanying simulation stack includes nuclear quantum effects (NQE). The simulation tools' computational efficiency is on a par with current state-of-the-art packages. The construction of a wide-coverage molecular modelling toolset from first principles, together with its excellent predictive ability in the liquid phase is a major advance in biomolecular simulation.

Reduced efficacy of a Src kinase inhibitor in crowded protein solution.

The inside of a cell is highly crowded with proteins and other biomolecules. How proteins express their specific functions together with many off-target proteins in crowded cellular environments is largely unknown. Here, we investigate an inhibitor binding with c-Src kinase using atomistic molecular dynamics (MD) simulations in dilute as well as crowded protein solution. The populations of the inhibitor, 4-amino-5-(4-methylphenyl)-7-(t-butyl)pyrazolo[3,4-d]pyrimidine (PP1), in bulk solution and on the surface of c-Src kinase are reduced as the concentration of crowder bovine serum albumins (BSAs) increases. This observation is consistent with the reduced PP1 inhibitor efficacy in experimental c-Src kinase assays in addition with BSAs. The crowded environment changes the major binding pathway of PP1 toward c-Src kinase compared to that in dilute solution. This change is explained based on the population shift mechanism of local conformations near the inhibitor binding site in c-Src kinase.

Charge-driven condensation of RNA and proteins suggests broad role of phase separation in cytoplasmic environments.

Phase separation processes are increasingly being recognized as important organizing mechanisms of biological macromolecules in cellular environments. Well-established drivers of phase separation are multi-valency and intrinsic disorder. Here, we show that globular macromolecules may condense simply based on electrostatic complementarity. More specifically, phase separation of mixtures between RNA and positively charged proteins is described from a combination of multiscale computer simulations with microscopy and spectroscopy experiments. Phase diagrams were mapped out as a function of molecular concentrations in experiment and as a function of molecular size and temperature via simulations. The resulting condensates were found to retain at least some degree of internal dynamics varying as a function of the molecular composition. The results suggest a more general principle for phase separation that is based primarily on electrostatic complementarity without invoking polymer properties as in most previous studies. Simulation results furthermore suggest that such phase separation may occur widely in heterogenous cellular environment between nucleic acid and protein components.

Neoadjuvant chemotherapy with or without oxaliplatin after short-course radiotherapy in high-risk rectal cancer: A subgroup analysis from a prospective study.

AIM: To evaluate the role of oxaliplatin in neoadjuvant chemotherapy delivered after short-course irradiation. BACKGROUND: Using oxaliplatin in the above setting is uncertain. PATIENTS AND METHODS: A subgroup of 136 patients managed by short-course radiotherapy and 3 cycles of consolidation chemotherapy within the framework of a randomised study was included in this post-hoc analysis. Sixty-seven patients received FOLFOX4 (oxaliplatin group) while oxaliplatin was omitted in the second period of accrual in 69 patients because of protocol amendment (fluorouracil-only group). RESULTS: Grade 3+ acute toxicity from neoadjuvant treatment was observed in 30% of patients in the oxaliplatin group vs. 16% in the fluorouracil-only group (p = 0.053). The corresponding proportions of patients having radical surgery or achieving complete pathological response were 72% vs. 77% (odds ratio [OR] = 0.88; 95% confidence interval [CI]: 0.39-1.98; p = 0.75) and 15% vs. 7% (OR = 2.25; 95% CI: 0.83-6.94; p = 0.16), respectively. The long-term outcomes were similar in the two groups. Overall and disease-free survival rates at 5 years were 63% vs. 56% (p = 0.78) and 49% vs. 44% (p = 0.59), respectively. The corresponding numbers for cumulative incidence of local failure or distant metastases were 33% vs. 38% (hazard ratio [HR] = 0.89; 95% CI: 0.52-1.52; p = 0.68) and 33% vs. 33% (HR = 0.78; 95% CI: 0.43-1.40; p = 0.41), respectively. CONCLUSION: Our findings do not support adding oxaliplatin to three cycles of chemotherapy delivered after short-course irradiation.

Clustering and dynamics of crowded proteins near membranes and their influence on membrane bending.

Atomistic molecular dynamics simulations of concentrated protein solutions in the presence of a phospholipid bilayer are presented to gain insights into the dynamics and interactions at the cytosol-membrane interface. The main finding is that proteins that are not known to specifically interact with membranes are preferentially excluded from the membrane, leaving a depletion zone near the membrane surface. As a consequence, effective protein concentrations increase, leading to increased protein contacts and clustering, whereas protein diffusion becomes faster near the membrane for proteins that do occasionally enter the depletion zone. Since protein-membrane contacts are infrequent and short-lived in this study, the structure of the lipid bilayer remains largely unaffected by the crowded protein solution, but when proteins do contact lipid head groups, small but statistically significant local membrane curvature is induced, on average.

Effect of protein-protein interactions and solvent viscosity on the rotational diffusion of proteins in crowded environments.

The rotational diffusion of a protein in the presence of protein crowder molecules was analyzed via computer simulations. Cluster formation as a result of transient intermolecular contacts was identified as the dominant effect for reduced rotational diffusion upon crowding. The slow-down in diffusion was primarily correlated with direct protein-protein contacts rather than indirect interactions via shared hydration layers. But increased solvent viscosity due to crowding contributed to a lesser extent. Key protein-protein contacts correlated with a slow-down in diffusion involve largely interactions between charged and polar groups suggesting that the surface composition of a given protein and the resulting propensity for forming interactions with surrounding proteins in a crowded cellular environment may be the major determinant of its diffusive properties.

Intramolecular Diffusion in α-Synuclein: It Depends on How You Measure It.

Intramolecular protein diffusion, the motion of one part of the polypeptide chain relative to another part, is a fundamental aspect of protein folding and may modulate amyloidogenesis of disease-associated intrinsically disordered proteins. Much work has determined such diffusion coefficients using a variety of probes, but there has been an apparent discrepancy between measurements using long-range probes, such as fluorescence resonance energy transfer, and short-range probes, such as Trp-Cys quenching. In this work, we make both such measurements on the same protein, α-synuclein, and confirm that such discrepancy exists. Molecular dynamics simulations suggest that such differences result from a diffusion coefficient that depends on the spatial distance between probes. Diffusional estimates in good quantitative agreement with experiment are obtained by accounting for the distinct distance ranges probed by fluorescence resonance energy transfer and Trp-Cys quenching.

Challenges and opportunities in connecting simulations with experiments via molecular dynamics of cellular environments.

Computer simulations are widely used to study molecular systems, especially in biology. As simulations have greatly increased in scale reaching cellular levels there are now significant challenges in managing, analyzing, and interpreting such data in comparison with experiments that are being discussed. Management challenges revolve around storing and sharing terabyte to petabyte scale data sets whereas the analysis of simulations of highly complex systems will increasingly require automated machine learning and artificial intelligence approaches. The comparison between simulations and experiments is furthermore complicated not just by the complexity of the data but also by difficulties in interpreting experiments for highly heterogeneous systems. As an example, the interpretation of NMR relaxation measurements and comparison with simulations for highly crowded systems is discussed.

Slow-Down in Diffusion in Crowded Protein Solutions Correlates with Transient Cluster Formation.

For a long time, the effect of a crowded cellular environment on protein dynamics has been largely ignored. Recent experiments indicate that proteins diffuse more slowly in a living cell than in a diluted solution, and further studies suggest that the diffusion depends on the local surroundings. Here, detailed insight into how diffusion depends on protein-protein contacts is presented based on extensive all-atom molecular dynamics simulations of concentrated villin headpiece solutions. After force field adjustments in the form of increased protein-water interactions to reproduce experimental data, translational and rotational diffusion was analyzed in detail. Although internal protein dynamics remained largely unaltered, rotational diffusion was found to slow down more significantly than translational diffusion as the protein concentration increased. The decrease in diffusion is interpreted in terms of a transient formation of protein clusters. These clusters persist on sub-microsecond time scales and follow distributions that increasingly shift toward larger cluster size with increasing protein concentrations. Weighting diffusion coefficients estimated for different clusters extracted from the simulations with the distribution of clusters largely reproduces the overall observed diffusion rates, suggesting that transient cluster formation is a primary cause for a slow-down in diffusion upon crowding with other proteins.

Crowding in Cellular Environments at an Atomistic Level from Computer Simulations.

The effects of crowding in biological environments on biomolecular structure, dynamics, and function remain not well understood. Computer simulations of atomistic models of concentrated peptide and protein systems at different levels of complexity are beginning to provide new insights. Crowding, weak interactions with other macromolecules and metabolites, and altered solvent properties within cellular environments appear to remodel the energy landscape of peptides and proteins in significant ways including the possibility of native state destabilization. Crowding is also seen to affect dynamic properties, both conformational dynamics and diffusional properties of macromolecules. Recent simulations that address these questions are reviewed here and discussed in the context of relevant experiments.

CHARMM36m: an improved force field for folded and intrinsically disordered proteins.

The all-atom additive CHARMM36 protein force field is widely used in molecular modeling and simulations. We present its refinement, CHARMM36m (http://mackerell.umaryland.edu/charmm_ff.shtml), with improved accuracy in generating polypeptide backbone conformational ensembles for intrinsically disordered peptides and proteins.

Interactions of aqueous amino acids and proteins with the (110) surface of ZnS in molecular dynamics simulations.

The growing usage of nanoparticles of zinc sulfide as quantum dots and biosensors calls for a theoretical assessment of interactions of ZnS with biomolecules. We employ the molecular-dynamics-based umbrella sampling method to determine potentials of mean force for 20 single amino acids near the ZnS (110) surface in aqueous solutions. We find that five amino acids do not bind at all and the binding energy of the remaining amino acids does not exceed 4.3 kJ/mol. Such energies are comparable to those found for ZnO (and to hydrogen bonds in proteins) but the nature of the specificity is different. Cysteine can bind with ZnS in a covalent way, e.g., by forming the disulfide bond with S in the solid. If this effect is included within a model incorporating the Morse potential, then the potential well becomes much deeper--the binding energy is close to 98 kJ/mol. We then consider tryptophan cage, a protein of 20 residues, and characterize its events of adsorption to ZnS. We demonstrate the relevance of interactions between the amino acids in the selection of optimal adsorbed conformations and recognize the key role of cysteine in generation of lasting adsorption. We show that ZnS is more hydrophobic than ZnO and that the density profile of water is quite different than that forming near ZnO--it has only a minor articulation into layers. Furthermore, the first layer of water is disordered and mobile.

Liver transplantation for nonresectable metastatic solid pseudopapillary pancreatic cancer.

BACKGROUND: Solid pseudopapillary tumor (SPT) of the pancreas, also known as Franz tumor, Hamoudie tumor, solid-cystic-papillary epithelial neoplasm, or solid and cystic tumor, is a neoplasm of transitory (potential) malignancy, seen predominantly in young women. CASE REPORT: This report presents a female patient treated for a solid pseudopapillary tumor of the pancreas with hepatic metastases. The tumor was first diagnosed in 2006. Non-specific abdominal pain was the first presenting symptom. The patient underwent distal pancreatic resection and splenectomy in July 2006. Multifocal metastatic disease seen at surgery precluded radical resection. Following definitive pathology confirmation and the exclusion of extrahepatic metastases, the patient was referred to our transplant centre 18 months after pancreatic surgery, to be considered for orthotopic liver transplantation (OLTx). The extent of the disease was once again evaluated by imaging studies, followed by exploratory laparotomy. The patient underwent cadaveric liver transplantation in March 2008, with triple immunosuppression (tacrolimus, MMF, and steroids) following surgery. Presently, more than 5 years post-transplant, the patient has no signs of recurrent neoplasmatic disease. CONCLUSIONS: This is the first liver transplantation for a metastatic pancreatic pseudopapillary tumor in Poland, with the longest follow-up period described in the literature. Follow-up suggests a cautiously optimistic prognosis despite primary unresectability of hepatic metastases and the necessity for immunosuppressive therapy.

Amino acids and proteins at ZnO-water interfaces in molecular dynamics simulations.

We determine potentials of the mean force for interactions of amino acids with four common surfaces of ZnO in aqueous solutions. The method involves all-atom molecular dynamics simulations combined with the umbrella sampling technique. The profiled nature of the density of water with the strongly adsorbed first layer affects the approach of amino acids to the surface and generates either repulsion or weak binding. The largest binding energy is found for tyrosine interacting with the surface in which the Zn ions are at the top. It is equal to 7 kJ mol(-1) which is comparable to that of the hydrogen bonds in a protein. This makes the adsorption of amino acids onto the ZnO surface much weaker than onto the well studied surface of gold. Under vacuum, binding energies are more than 40 times stronger (for one of the surfaces). The precise manner in which water molecules interact with a given surface influences the binding energies in a way that depends on the surface. Among the four considered surfaces the one with Zn at the top is recognized as binding almost all amino acids with an average binding energy of 2.60 kJ mol(-1). Another (O at the top) is non-binding for most amino acids. For binding situations the average energy is 0.66 kJ mol(-1). The remaining two surfaces bind nearly as many amino acids as they do not and the average binding energies are 1.46 and 1.22 kJ mol(-1). For all of the surfaces the binding energies vary between amino acids significantly: the dispersion in the range of 68-154% of the mean. A small protein is shown to adsorb onto ZnO only intermittently and with only a small deformation. Various adsorption events lead to different patterns in mobilities of amino acids within the protein.