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

Translation and initial validation of the Medication Adherence Report Scale (MARS) in Italian patients with Crohn's Disease

The MARS-5 (Medication Adherence Report Scale) was developed in English. The aim of this project was to analyse the MARS-5I (© Prof Rob Horne) psychometric properties and to identify whether its Italian translation is suitable for assessing medication adherence in Crohn Disease (CD) Italian patients. The MARS was translated and linguistically validated in Italian. The MARS-5I was used for evaluating medication adherence in the SOLE study, conducted in Italy on 552 subjects with CD. In order to un-bias the questionnaire results from the effects of treatment change and/or effectiveness, the analyses were performed on the 277 patients whose disease activity remained stable, selected among the 371 patients who maintained the same treatment between two consecutive visits. Internal consistency was high (Cronbach's alpha of 0.86). Pearson's correlation coefficient was 0.50 (p < 0.001) and 0.86 (p < 0.001- outliers removed), indicating satisfactory test-retest. MARS 5I scores were not correlated with Treatment Satisfaction Questionnaire for Medication but a small and statistically significant correlation was shown with physician-evaluated medication adherence, indicating convergent validity. MARS-5I, the Italian translation of the English MARS, showed satisfactory internal consistency and test-retest, and a low but statistically significant convergent validity. We confirmed the utility of this tool in patients with CD

A two-step target binding and selectivity support vector machines approach for virtual screening of dopamine receptor subtype-selective ligands

10.1371/journal.pone.0039076PLoS ONE76

Effects of Short- and Long-Term Tracheal Intubation on the Ventilation with cLMA\u2122 for PDT. Effects of Short- and Long-Term Tracheal Intubation on the Ventilation with cLMA\u2122 for PDT.

Annual Meeting of American Society of Anesthesiologist

Exploring Potency and Selectivity Receptor Antagonist Profiles Using a Multilabel Classification Approach: The Human Adenosine Receptors as a Key Study

Nowadays, in medicinal chem. adenosine receptors represent some of the most studied targets, and there is growing interest on the different adenosine receptor (AR) subtypes. The AR subtypes selectivity is highly desired in the development of potent ligands to achieve the therapeutic success. So far, very few ligand-based strategies have been investigated to predict the receptor subtypes selectivity. In the present study, we have carried out a novel application of the multilabel classification approach by combining our recently reported autocorrelated mol. descriptors encoding for the mol. electrostatic potential (autoMEP) with support vector machines (SVMs). Three valuable models, based on decreasing thresholds of potency, have been generated as in series quant. sieves for the simultaneous prediction of the hA1R, hA2AR, hA2BR, and hA3R subtypes potency profile and selectivity of a large collection, more than 500, of known inverse agonists such as xanthine, pyrazolo-triazolo-pyrimidine, and triazolo-pyrimidine analogs. The robustness and reliability of our multilabel classification models were assessed by predicting an internal test set. Finally, we have applied our strategy to 13 newly synthesized pyrazolo-triazolo-pyrimidine derivs. inferring their full adenosine receptor potency spectrum and hAR subtypes selectivity profil