AIMS
Disagreement exists on effective and sensitive outcome measures in neuropathy associated with impaired glucose tolerance (IGT). Nerve conduction studies and skin biopsies are costly, invasive and may have their problems with reproducibility and clinical applicability. A clinical measure of neuropathy that has sufficient sensitivity and correlates to invasive measures would enable significant future research.
METHODS
Data was collected prospectively on patients with IGT and symptomatic early neuropathy (neuropathy symptoms < 2 years) and normal controls. The seven scales that were examined were the Neuropathy Impairment Score of the Lower Limb (NIS-LL), Michigan Diabetic Neuropathy Score (MNDS), modified Toronto Clinical Neuropathy Scale (mTCNS), Total Neuropathy Score (Clinical) (TNSc), The Utah Early Neuropathy Scale (UENS), the Early Neuropathy Score (ENS), and the Neuropathy Disability Score (NDS).
RESULTS
All seven clinical scales were determined to be excellent in discriminating between patients with neuropathy from controls without neuropathy. The strongest discrimination was seen with the mTCNS. The best sensitivity and specificity for the range of scores obtained, as determined by using receiver operating characteristic curves, was seen for the mTCNS followed by the TNSc. Most scales show a stronger correlation with measures of large than small fiber neuropathy.
CONCULSIONS
All seven scales identify patients with neuropathy. For the purpose of screening potential patients for a clinical study, the mTCNS followed by the TNSc would be most helpful to select patients with neuropathy.
A computational model of the non-nucleoside inhibitor 8-Cl TIBO complexed with HIV-1 reverse transcriptase (RT) was constructed in order to determine the binding free energies. Using Monte Carlo simulations, both free energy perturbation and linear response calculations were carried out for the transformation of wild-type RT to two key mutants, Y181C and L100I. The newer linear response method estimates binding free energies based on changes in electrostatic and van der Waals energies and solvent-accessible surface areas. In addition, the change in stability of the protein between the folded and unfolded states was estimated for each of these mutations, which are known to emerge upon treatment with the inhibitor. Results from the calculations revealed that there is a large hydrophobic contribution to protein stability in the native, folded state. The calculated absolute free energies of binding from both the linear response, and also the more rigorous free energy perturbation method, gave excellent agreement with the experimental differences in activity. The success of the relatively rapid linear response method in predicting experimental activities holds promise for estimating the activity of the inhibitors not only against the wild-type RT, but also against key protein variants whose emergence undermines the efficacy of the drugs.
The energies and physical descriptors for the binding of 21 novel 1-(2,6-difluorobenzyl)-2-(2,6-difluorophenyl)-benzimidazole (BPBI) analogs to HIV-1 reverse transcriptase (RT) variants Y181C, L100I, V106A, and K103N have been determined using Monte Carlo (MC) simulations. The crystallographic structure of the lead compound, 4-methyl BPBI, was used as a starting point to model the inhibitors in both the mutant bound and the unbound states. The energy terms and physical descriptors obtained from the calculations were reasonably correlated with the respective experimental EC50 values for the inhibitors against the various mutant RTs. Using the linear response correlations from the calculations, 2 novel BPBI inhibitors have been designed and simulations have been carried out. The results show the computed deltaG(binding) values match the experimental data for the analogs. Given the ongoing problem with drug resistance, the ability to predict the activity of novel analogs against variants prior to synthesis is highly advantageous.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.