Methods for the assessment of akinesia in the unilateral rat Parkinson model have so far been lacking.

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Understanding the driving forces underlying molecular recognition is of fundamental importance in chemistry and biology. The challenge is to unravel the binding thermodynamics into separate contributions and to interpret these in molecular terms. Entropic contributions to the free energy of binding are particularly difficult to assess in this regard. Here we pinpoint the molecular determinants underlying differences in ligand affinity to the carbohydrate recognition domain of galectin-3, using a combination of isothermal titration calorimetry, X-ray crystallography, NMR relaxation, and molecular dynamics simulations followed by conformational entropy and grid inhomogeneous solvation theory (GIST) analyses. Using a pair of diastereomeric ligands that have essentially identical chemical potential in the unbound state, we reduced the problem of dissecting the thermodynamics to a comparison of the two protein–ligand complexes. While the free energies of binding are nearly equal for the R and S diastereomers, greater differences are observed for the enthalpy and entropy, which consequently exhibit compensatory behavior, ΔΔ H°(R – S) = −5 ± 1 kJ/mol and −TΔΔ S°(R – S) = 3 ± 1 kJ/mol. NMR relaxation experiments and molecular dynamics simulations indicate that the protein in complex with the S-stereoisomer has greater conformational entropy than in the R-complex. GIST calculations reveal additional, but smaller, contributions from solvation entropy, again in favor of the S-complex. Thus, conformational entropy apparently dominates over solvation entropy in dictating the difference in the overall entropy of binding. This case highlights an interplay between conformational entropy and solvation entropy, pointing to both opportunities and challenges in drug design.

The developmental potential of neural progenitors derived from the E13.5-E14 lateral or medial ganglionic eminences (LGE and MGE, respectively) or the E12 ventral mesencephalon (VM) was examined in cross-species transplantation model. After injection into the E15 rat forebrain ventricle, mouse LGE progenitors (unlike those of the MGE or VM) were consistently integrated into the host striatum, expressing neurochemical phenotypes and axonal projections characteristic of striatal projection neurons. Additionally, both LGE and MGE precursors displayed widespread incorporation into distinct forebrain and midbrain structures, whereas the more caudally derived VM cells were largely confined to midbrain structures. These results suggest that many LGE precursors are positionally specified for striatal incorporation, while a portion also possess greater potential reflected in more widespread integration following intraventricular injection.

IMPORTANCEEvidence is accumulating that repeated mild traumatic brain injury (mTBI) incidents can lead to persistent, long-term debilitating symptoms and in some cases a progressive neurodegenerative condition referred to as chronic traumatic encephalopathy. However, to our knowledge, there are no objective tools to examine to which degree persistent symptoms after mTBI are caused by neuronal injury.OBJECTIVE To determine whether persistent symptoms after mTBI are associated with brain injury as evaluated by cerebrospinal fluid biochemical markers for axonal damage and other aspects of central nervous system injury. DESIGN, SETTINGS, AND PARTICIPANTSA multicenter cross-sectional study involving professional Swedish ice hockey players who have had repeated mTBI, had postconcussion symptoms for more than 3 months, and fulfilled the criteria for postconcussion syndrome (PCS) according to the Diagnostic and Statistical Manual of Mental Disorders (Fourth Edition) matched with neurologically healthy control individuals. The participants were enrolled between January 2014 and February 2016. The players were also assessed with Rivermead Post Concussion Symptoms Questionnaire and magnetic resonance imaging. MAIN OUTCOMES AND MEASURESNeurofilament light protein, total tau, glial fibrillary acidic protein, amyloid β, phosphorylated tau, and neurogranin concentrations in cerebrospinal fluid.RESULTS A total of 31 participants (16 men with PCS; median age, 31 years; range, 22-53 years; and 15 control individuals [11 men and 4 women]; median age, 25 years; range, 21-35 years) were assessed. Of 16 players with PCS, 9 had PCS symptoms for more than 1 year, while the remaining 7 returned to play within a year. Neurofilament light proteins were significantly increased in players with PCS for more than 1 year (median, 410 pg/mL; range, 230-1440 pg/mL) compared with players whose PCS resolved within 1 year (median, 210 pg/mL; range, 140-460 pg/mL) as well as control individuals (median 238 pg/mL, range 128-526 pg/mL; P = .04 and P = .02, respectively). Furthermore, neurofilament light protein concentrations correlated with Rivermead Post Concussion Symptoms Questionnaire scores and lifetime concussion events (ρ = 0.58, P = .02 and ρ = 0.52, P = .04, respectively). Overall, players with PCS had significantly lower cerebrospinal fluid amyloid-β levels compared with control individuals (median, 1094 pg/mL; range, 845-1305 pg/mL; P = .05).CONCLUSIONS AND RELEVANCE Increased cerebrospinal fluid neurofilament light proteins and reduced amyloid β were observed in patients with PCS, suggestive of axonal white matter injury and amyloid deposition. Measurement of these biomarkers may be an objective tool to assess the degree of central nervous system injury in individuals with PCS and to distinguish individuals who are at risk of developing chronic traumatic encephalopathy.

We have compared two approaches to calculate relative binding free energies employing molecular dynamics simulations at the combined quantum-mechanical/molecular mechanics (QM/MM) level. As a test case, we study the binding of nine cyclic carboxylate ligands to the octa-acid deep-cavitand host system. The ligand is treated with the semiempirical PM6-DH+ QM method. In the first approach, we perform direct alchemical QM/MM free energy perturbation (FEP). In the second, reference-potential approach, we convert the ligands with FEP at the molecular mechanics (MM) level and then perform also MM → QM/MM FEP for each ligand. We show that the two approaches give identical results within statistical uncertainty. For the reference-potential approach, the MM → QM/MM perturbation converges in terms of energies, uncertainties, and overlap measures with two intermediate states, giving a precision of 0.5-0.9 kJ/mol for all eight transformations considered. On the other hand, the QM/MM-FEP approach requires 17-18 intermediate states, showing that the reference-potential approach is more effective. Previous calculations with single-step exponential averaging (i.e., entirely avoiding QM/MM simulations) required fewer QM/MM energy calculations, but they gave worse precision and involved approximations with an unclear effect on the results.

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In this article, the convergence of quantum mechanical (QM) free‐energy simulations based on molecular dynamics simulations at the molecular mechanics (MM) level has been investigated. We have estimated relative free energies for the binding of nine cyclic carboxylate ligands to the octa‐acid deep‐cavity host, including the host, the ligand, and all water molecules within 4.5 Å of the ligand in the QM calculations (158–224 atoms). We use single‐step exponential averaging (ssEA) and the non‐Boltzmann Bennett acceptance ratio (NBB) methods to estimate QM/MM free energy with the semi‐empirical PM6‐DH2X method, both based on interaction energies. We show that ssEA with cumulant expansion gives a better convergence and uses half as many QM calculations as NBB, although the two methods give consistent results. With 720,000 QM calculations per transformation, QM/MM free‐energy estimates with a precision of 1 kJ/mol can be obtained for all eight relative energies with ssEA, showing that this approach can be used to calculate converged QM/MM binding free energies for realistic systems and large QM partitions. © 2016 The Authors. Journal of Computational Chemistry Published by Wiley Periodicals, Inc.