Fast automated placement of polar hydrogen atoms in protein-ligand complexes

<p>Abstract</p> <p>Background</p> <p>Hydrogen bonds play a major role in the stabilization of protein-ligand complexes. The ability of a functional group to form them depends on the position of its hydrogen atoms. An accurate knowledge of the positions of hydrogen atoms in proteins is therefore important to correctly identify hydrogen bonds and their properties. The high mobility of hydrogen atoms introduces several degrees of freedom: Tautomeric states, where a hydrogen atom alters its binding partner, torsional changes where the position of the hydrogen atom is rotated around the last heavy-atom bond in a residue, and protonation states, where the number of hydrogen atoms at a functional group may change. Also, side-chain flips in glutamine and asparagine and histidine residues, which are common crystallographic ambiguities must be identified before structure-based calculations can be conducted.</p> <p>Results</p> <p>We have implemented a method to determine the most probable hydrogen atom positions in a given protein-ligand complex. Optimality of hydrogen bond geometries is determined by an empirical scoring function which is used in molecular docking. This allows to evaluate protein-ligand interactions with an established model. Also, our method allows to resolve common crystallographic ambiguities such as as flipped amide groups and histidine residues. To ensure high speed, we make use of a dynamic programming approach.</p> <p>Conclusion</p> <p>Our results were checked against selected high-resolution structures from an external dataset, for which the positions of the hydrogen atoms have been validated manually. The quality of our results is comparable to that of other programs, with the advantage of being fast enough to be applied on-the-fly for interactive usage or during score evaluation.</p

Long Time to Diagnosis of Medulloblastoma in Children Is Not Associated with Decreased Survival or with Worse Neurological Outcome

International audienceBACKGROUND: The long time to diagnosis of medulloblastoma, one of the most frequent brain tumors in children, is the source of painful remorse and sometimes lawsuits. We analyzed its consequences for tumor stage, survival, and sequelae. PATIENTS AND METHODS: This retrospective population-based cohort study included all cases of pediatric medulloblastoma from a region of France between 1990 and 2005. We collected the demographic, clinical, and tumor data and analyzed the relations between the interval from symptom onset until diagnosis, initial disease stage, survival, and neuropsychological and neurological outcome. RESULTS: The median interval from symptom onset until diagnosis for the 166 cases was 65 days (interquartile range 31-121, range 3-457). A long interval (defined as longer than the median) was associated with a lower frequency of metastasis in the univariate and multivariate analyses and with a larger tumor volume, desmoplastic histology, and longer survival in the univariate analysis, but not after adjustment for confounding factors. The time to diagnosis was significantly associated with IQ score among survivors. No significant relation was found between the time to diagnosis and neurological disability. In the 62 patients with metastases, a long prediagnosis interval was associated with a higher T stage, infiltration of the fourth ventricle floor, and incomplete surgical resection; it nonetheless did not influence survival significantly in this subgroup. CONCLUSIONS: We found complex and often inverse relations between time to diagnosis of medulloblastoma in children and initial severity factors, survival, and neuropsychological and neurological outcome. This interval appears due more to the nature of the tumor and its progression than to parental or medical factors. These conclusions should be taken into account in the information provided to parents and in expert assessments produced for malpractice claims

Application of the PM6 semi-empirical method to modeling proteins enhances docking accuracy of AutoDock

<p>Abstract</p> <p>Background</p> <p>Molecular docking methods are commonly used for predicting binding modes and energies of ligands to proteins. For accurate complex geometry and binding energy estimation, an appropriate method for calculating partial charges is essential. AutoDockTools software, the interface for preparing input files for one of the most widely used docking programs AutoDock 4, utilizes the Gasteiger partial charge calculation method for both protein and ligand charge calculation. However, it has already been shown that more accurate partial charge calculation - and as a consequence, more accurate docking- can be achieved by using quantum chemical methods. For docking calculations quantum chemical partial charge calculation as a routine was only used for ligands so far. The newly developed Mozyme function of MOPAC2009 allows fast partial charge calculation of proteins by quantum mechanical semi-empirical methods. Thus, in the current study, the effect of semi-empirical quantum-mechanical partial charge calculation on docking accuracy could be investigated.</p> <p>Results</p> <p>The docking accuracy of AutoDock 4 using the original AutoDock scoring function was investigated on a set of 53 protein ligand complexes using Gasteiger and PM6 partial charge calculation methods. This has enabled us to compare the effect of the partial charge calculation method on docking accuracy utilizing AutoDock 4 software. Our results showed that the docking accuracy in regard to complex geometry (docking result defined as accurate when the RMSD of the first rank docking result complex is within 2 Å of the experimentally determined X-ray structure) significantly increased when partial charges of the ligands and proteins were calculated with the semi-empirical PM6 method.</p> <p>Out of the 53 complexes analyzed in the course of our study, the geometry of 42 complexes were accurately calculated using PM6 partial charges, while the use of Gasteiger charges resulted in only 28 accurate geometries. The binding affinity estimation was not influenced by the partial charge calculation method - for more accurate binding affinity prediction development of a new scoring function for AutoDock is needed.</p> <p>Conclusion</p> <p>Our results demonstrate that the accuracy of determination of complex geometry using AutoDock 4 for docking calculation greatly increases with the use of quantum chemical partial charge calculation on both the ligands and proteins.</p

Overview of diagnosis and management of paediatric headache. Part I: diagnosis

Headache is the most common somatic complaint in children and adolescents. The evaluation should include detailed history of children and adolescents completed by detailed general and neurological examinations. Moreover, the possible role of psychological factors, life events and excessively stressful lifestyle in influencing recurrent headache need to be checked. The choice of laboratory tests rests on the differential diagnosis suggested by the history, the character and temporal pattern of the headache, and the physical and neurological examinations. Subjects who have any signs or symptoms of focal/progressive neurological disturbances should be investigated by neuroimaging techniques. The electroencephalogram and other neurophysiological examinations are of limited value in the routine evaluation of headaches. In a primary headache disorder, headache itself is the illness and headache is not attributed to any other disorder (e.g. migraine, tension-type headache, cluster headache and other trigeminal autonomic cephalgias). In secondary headache disorders, headache is the symptom of identifiable structural, metabolic or other abnormality. Red flags include the first or worst headache ever in the life, recent headache onset, increasing severity or frequency, occipital location, awakening from sleep because of headache, headache occurring exclusively in the morning associated with severe vomiting and headache associated with straining. Thus, the differential diagnosis between primary and secondary headaches rests mainly on clinical criteria. A thorough evaluation of headache in children and adolescents is necessary to make the correct diagnosis and initiate treatment, bearing in mind that children with headache are more likely to experience psychosocial adversity and to grow up with an excess of both headache and other physical and psychiatric symptoms and this creates an important healthcare problem for their future life