A consistent description of HYdrogen bond and DEhydration energies in protein-ligand complexes: methods behind the HYDE scoring function.

The estimation of free energy of binding is a key problem in structure-based design. We developed the scoring function HYDE based on a consistent description of HYdrogen bond and DEhydration energies in protein-ligand complexes. HYDE is applicable to all types of protein targets since it is not calibrated on experimental binding affinity data or protein-ligand complexes. The comprehensible atom-based score of HYDE is visualized by applying a very intuitive coloring scheme, thereby facilitating the analysis of protein-ligand complexes in the lead optimization process. In this paper, we have revised several aspects of the former version of HYDE which was described in detail previously. The revised HYDE version was already validated in large-scale redocking and screening experiments which were performed in the course of the Docking and Scoring Symposium at 241st ACS National Meeting. In this study, we additionally evaluate the ability of the revised HYDE version to predict binding affinities. On the PDBbind 2007 coreset, HYDE achieves a correlation coefficient of 0.62 between the experimental binding constants and the predicted binding energy, performing second best on this dataset compared to 17 other well-established scoring functions. Further, we show that the performance of HYDE in large-scale redocking and virtual screening experiments on the Astex diverse set and the DUD dataset respectively, is comparable to the best methods in this field.

Substantial improvements in large-scale redocking and screening using the novel HYDE scoring function.

The HYDE scoring function consistently describes hydrogen bonding, the hydrophobic effect and desolvation. It relies on HYdration and DEsolvation terms which are calibrated using octanol/water partition coefficients of small molecules. We do not use affinity data for calibration, therefore HYDE is generally applicable to all protein targets. HYDE reflects the Gibbs free energy of binding while only considering the essential interactions of protein-ligand complexes. The greatest benefit of HYDE is that it yields a very intuitive atom-based score, which can be mapped onto the ligand and protein atoms. This allows the direct visualization of the score and consequently facilitates analysis of protein-ligand complexes during the lead optimization process. In this study, we validated our new scoring function by applying it in large-scale docking experiments. We could successfully predict the correct binding mode in 93% of complexes in redocking calculations on the Astex diverse set, while our performance in virtual screening experiments using the DUD dataset showed significant enrichment values with a mean AUC of 0.77 across all protein targets with little or no structural defects. As part of these studies, we also carried out a very detailed analysis of the data that revealed interesting pitfalls, which we highlight here and which should be addressed in future benchmark datasets.

Qualitative troponin I estimation in the diagnosis of acute coronary syndromes in three rural hospitals.

OBJECTIVE: To examine the utility of point-of-care qualitative troponin I (TnI) testing in patients with possible acute coronary syndromes (ACS). METHODS: A retrospective chart review of all patients undergoing qualitative TnI testing between September 2001 and February 2002 was conducted at the emergency departments of 3 rural hospitals in Alberta. We looked at the incidence of ACS, the comparison between TnI and creatine kinase (CK) testing and the timing of testing. RESULTS: Of the 235 patients tested, 8 had ST-elevation myocardial infarctions and 11 non ST-elevation infarctions. One patient had unstable angina with minimal myocardial damage. Qualitative TnI testing was positive in all 14 cases of infarction tested more than 6 hours after symptom onset, and CK elevation occurred in 15/17 cases (TnI sensitivity 1.0 [95% confidence interval (CI) 0.78-1.0], CK sensitivity 0.882 [95% CI 0.66-0.97]). There were 3 positive TnI tests and 33 raised CK levels in patients without evidence for ACS (TnI specificity 0.986 [95% CI 0.96-0.99], likelihood ratio [LR] 72.0 [95% CI 23.4-221.5]); CK specificity 0.847 [95% CI 0.79-0.89], LR 5.8 [95% CI 4.0-8.3]). In 44 patients (20.8%) TnI testing was inappropriately not repeated more than 6 hours after symptom onset. CONCLUSION: Qualitative TnI testing appears highly sensitive and more specific than CK estimation in detecting myocardial infarction. Diagnostic algorithms must emphasize the importance of testing 6 or more hours after symptom onset.

The FlexX database docking environment--rational extraction of receptor based pharmacophores.

We present an integrated docking environment that allows for iterative and interactive detailed analysis of many docking solutions. All docking information is stored in an ORACLE database. New scoring schemes (e.g. target-specific scoring functions) as well as various types of filters can be easily defined and tested within this environment. As an example application we investigated the validity of the following hypothesis: If a docking procedure can lead to enrichments significantly better than random then a bias towards (partially) correct placements should be detectable. Such bias in terms of a preference for certain interacting groups within the active site can be used to select a set of receptor-based pharmacophore constraints, which in turn might be used to enhance the docking procedure. As a proof of concept for this approach we performed docking studies on three targets: thrombin, the cyclin-dependent kinase 2 (CDK2) and the angiotensin converting enzyme (ACE). We docked a set of known active compounds with standard FlexX and derived three sets of target-specific receptor-based pharmacophore constraints by statistical analysis of the predicted placements. Applying these receptor-based constraints in a virtual screening protocol utilizing FlexX-Pharm led to significantly improved enrichments.

Flexible docking under pharmacophore type constraints.

FLEXX-PHARM, an extended version of the flexible docking tool FLEXX, allows the incorporation of information about important characteristics of protein-ligand binding modes into a docking calculation. This information is introduced as a simple set of constraints derived from receptor-based type pharmacophore features. The constraints are determined by selected FLEXX interactions and inclusion volumes in the receptor active site. They guide the docking process to produce a set of docking solutions with particular properties. By applying a series of look-ahead checks during the flexible construction of ligand fragments within the active site, FLEXX-PHARM determines which partially built docking solutions can potentially obey the constraints. Solutions that will not obey the constraints are deleted as early as possible, often decreasing the calculation time and enabling new docking solutions to emerge. FLEXX-PHARM was evaluated on various individual protein-ligand complexes where the top docking solutions generated by FLEXX had high root mean square deviations (RMSD) from the experimentally observed binding modes. FLEXX-PHARM showed an improvement in the RMSD of the top solutions in most cases, along with a reduction in run time. We also tested FLEXX-PHARM as a database screening tool on a small dataset of molecules for three target proteins. In two cases, FLEXX-PHARM missed one or two of the active molecules due to the constraints selected. However, in general FLEXX-PHARM maintained or improved the enrichment shown with FLEXX, while completing the screen in considerably less run time.