Estimating entropies from molecular dynamics simulations

The methods to compute the excess entropy and the entropy of solvation using liquid water as a test system were studied. The accuracy and convergence behavior of five methods based on thermodynamic integration and perturbation techniques was evaluated. Through the thermodynamic integration accurate entropy differences were obtained in which many copies of a solute were desolvated. Only two methods yield useful results, the calculation of solute-solvent entropy through thermodynamic integration and the calculation of solvation entropy through the temperature derivative of the corresponding free-energy difference, when one solute molecule is involved

Effect of the integration method on the accuracy and computational efficiency of free energy calculations using thermodynamic integration

Although calculations of free energy using molecular dynamics simulations have gained significant importance in the chemical and biochemical fields, they still remain quite computationally intensive. Furthermore, when using thermodynamic integration, numerical evaluation of the integral of the Hamiltonian with respect to the coupling parameter may introduce unwanted errors in the free energy. In this paper, we compare the performance of two numerical integration techniques-the trapezoidal and Simpson's rules and propose a new method, based on the analytic integration of physically based fitting functions that are able to accurately describe the behavior of the data. We develop and test our methodology by performing detailed studies on two prototype systems, hydrated methane and hydrated methanol, and treat Lennard-Jones and electrostatic contributions separately. We conclude that the widely used trapezoidal rule may introduce systematic errors in the calculation, but these errors are reduced if Simpson's rule is employed, at least for the electrostatic component. Furthermore, by fitting thermodynamic integration data, we are able to obtain precise free energy estimates using significantly fewer data points (5 intermediate states for the electrostatic component and 11 for the Lennard-Jones term), thus significantly decreasing the associated computational cost. Our method and improved protocol were successfully validated by computing the free energy of more complex systems hydration of 2-methylbutanol and of 4-nitrophenol-thus paving the way for widespread use in solvation free energy calculations of drug molecules

Assessment of the Performance Potential of Advanced Subsonic Transport Concepts for NASA's Environmentally Responsible Aviation Project

NASA's Environmentally Responsible Aviation (ERA) project has matured technologies to enable simultaneous reductions in fuel burn, noise, and nitrogen oxide (NOx) emissions for future subsonic commercial transport aircraft. The fuel burn reduction target was a 50% reduction in block fuel burn (relative to a 2005 best-in-class baseline aircraft), utilizing technologies with an estimated Technology Readiness Level (TRL) of 4-6 by 2020. Progress towards this fuel burn reduction target was measured through the conceptual design and analysis of advanced subsonic commercial transport concepts spanning vehicle size classes from regional jet (98 passengers) to very large twin aisle size (400 passengers). Both conventional tube-and-wing (T+W) concepts and unconventional (over-wing-nacelle (OWN), hybrid wing body (HWB), mid-fuselage nacelle (MFN)) concepts were developed. A set of propulsion and airframe technologies were defined and integrated onto these advanced concepts which were then sized to meet the baseline mission requirements. Block fuel burn performance was then estimated, resulting in reductions relative to the 2005 best-in-class baseline performance ranging from 39% to 49%. The advanced single-aisle and large twin aisle T+W concepts had reductions of 43% and 41%, respectively, relative to the 737-800 and 777-200LR aircraft. The single-aisle OWN concept and the large twin aisle class HWB concept had reductions of 45% and 47%, respectively. In addition to their estimated fuel burn reduction performance, these unconventional concepts have the potential to provide significant noise reductions due, in part, to engine shielding provided by the airframe. Finally, all of the advanced concepts also have the potential for significant NOx emissions reductions due to the use of advanced combustor technology. Noise and NOx emissions reduction estimates were also generated for these concepts as part of the ERA project

Effects of Restrained Sampling Space and Nonplanar Amino Groups on Free-Energy Predictions for RNA with Imino and Sheared Tandem GA Base Pairs Flanked by GC, CG, iGiC or iCiG Base Pairs

Guanine-adenine (GA) base pairs play important roles in determining the structure, dynamics, and stability of RNA. In RNA internal loops, GA base pairs often occur in tandem arrangements and their structure is context and sequence dependent. Calculations reported here test the thermodynamic integration (TI) approach with the amber99 force field by comparing computational predictions of free energy differences with the free energy differences expected on the basis of NMR determined structures of the RNA motifs (5′-GCGGACGC-3′)2, (5′-GCiGGAiCGC-3′)2, (5′-GGCGAGCC-3′)2, and (5′-GGiCGAiGCC-3′)2. Here, iG and iC denote isoguanosine and isocytidine, which have amino and carbonyl groups transposed relative to guanosine and cytidine. The NMR structures show that the GA base pairs adopt either imino (cis Watson−Crick/Watson−Crick A-G) or sheared (trans Hoogsteen/Sugar edge A-G) conformations depending on the identity and orientation of the adjacent base pair. A new mixing function for the TI method is developed that allows alchemical transitions in which atoms can disappear in both the initial and final states. Unrestrained calculations gave ΔG° values 2−4 kcal/mol different from expectations based on NMR data. Restraining the structures with hydrogen bond restraints did not improve the predictions. Agreement with NMR data was improved by 0.7 to 1.5 kcal/mol, however, when structures were restrained with weak positional restraints to sample around the experimentally determined NMR structures. The amber99 force field was modified to partially include pyramidalization effects of the unpaired amino group of guanosine in imino GA base pairs. This provided little or no improvement in comparisons with experiment. The marginal improvement is observed when the structure has potential cross-strand out-of-plane hydrogen bonding with the G amino group. The calculations using positional restraints and a nonplanar amino group reproduce the signs of ΔG° from the experimental results and are, thus, capable of providing useful qualitative insights complementing the NMR experiments. Decomposition of the terms in the calculations reveals that the dominant terms are from electrostatic and interstrand interactions other than hydrogen bonds in the base pairs. The results suggest that a better description of the backbone is key to reproducing the experimental free energy results with computational free energy predictions

Enhancing Production of Bio-Isoprene Using Hybrid MVA Pathway and Isoprene Synthase in E. coli

The depleting petroleum reserve, increasingly severe energy crisis, and global climate change are reigniting enthusiasm for seeking sustainable technologies to replace petroleum as a source of fuel and chemicals. In this paper, the efficiency of the MVA pathway on isoprene production has been improved as follows: firstly, in order to increase MVA production, the source of the “upper pathway” which contains HMG-CoA synthase, acetyl-CoA acetyltransferase and HMG-CoA reductase to covert acetyl-CoA into MVA has been changed from Saccharomyces cerevisiae to Enterococcus faecalis; secondly, to further enhance the production of MVA and isoprene, a alanine 110 of the mvaS gene has been mutated to a glycine. The final genetic strain YJM25 containing the optimized MVA pathway and isoprene synthase from Populus alba can accumulate isoprene up to 6.3 g/L after 40 h of fed-batch cultivation

Combining Experiments and Simulations Using the Maximum Entropy Principle

A key component of computational biology is to compare the results of computer modelling with experimental measurements. Despite substantial progress in the models and algorithms used in many areas of computational biology, such comparisons sometimes reveal that the computations are not in quantitative agreement with experimental data. The principle of maximum entropy is a general procedure for constructing probability distributions in the light of new data, making it a natural tool in cases when an initial model provides results that are at odds with experiments. The number of maximum entropy applications in our field has grown steadily in recent years, in areas as diverse as sequence analysis, structural modelling, and neurobiology. In this Perspectives article, we give a broad introduction to the method, in an attempt to encourage its further adoption. The general procedure is explained in the context of a simple example, after which we proceed with a real-world application in the field of molecular simulations, where the maximum entropy procedure has recently provided new insight. Given the limited accuracy of force fields, macromolecular simulations sometimes produce results that are at not in complete and quantitative accordance with experiments. A common solution to this problem is to explicitly ensure agreement between the two by perturbing the potential energy function towards the experimental data. So far, a general consensus for how such perturbations should be implemented has been lacking. Three very recent papers have explored this problem using the maximum entropy approach, providing both new theoretical and practical insights to the problem. We highlight each of these contributions in turn and conclude with a discussion on remaining challenges

Renal malformations associated with mutations of developmental genes: messages from the clinic

Renal tract malformations (RTMs) account for about 40% of children with end-stage renal failure. RTMs can be caused by mutations of genes normally active in the developing kidney and lower renal tract. Moreover, some RTMs occur in the context of multi-organ malformation syndromes. For these reasons, and because genetic testing is becoming more widely available, pediatric nephrologists should work closely with clinical geneticists to make genetic diagnoses in children with RTMs, followed by appropriate family counseling. Here we highlight families with renal cysts and diabetes, renal coloboma and Fraser syndromes, and a child with microdeletion of chromosome 19q who had a rare combination of malformations. Such diagnoses provide families with often long-sought answers to the question “why was our child born with kidney disease”. Precise genetic diagnoses will also help to define cohorts of children with RTMs for long-term clinical outcome studies