Prediction of cis/trans isomerization in proteins using PSI-BLAST profiles and secondary structure information

Background The majority of peptide bonds in proteins are found to occur in the trans conformation. However, for proline residues, a considerable fraction of Prolyl peptide bonds adopt the cis form. Proline cis/trans isomerization is known to play a critical role in protein folding, splicing, cell signaling and transmembrane active transport. Accurate prediction of proline cis/trans isomerization in proteins would have many important applications towards the understanding of protein structure and function. Results In this paper, we propose a new approach to predict the proline cis/trans isomerization in proteins using support vector machine (SVM). The preliminary results indicated that using Radial Basis Function (RBF) kernels could lead to better prediction performance than that of polynomial and linear kernel functions. We used single sequence information of different local window sizes, amino acid compositions of different local sequences, multiple sequence alignment obtained from PSI-BLAST and the secondary structure information predicted by PSIPRED. We explored these different sequence encoding schemes in order to investigate their effects on the prediction performance. The training and testing of this approach was performed on a newly enlarged dataset of 2424 non-homologous proteins determined by X-Ray diffraction method using 5-fold cross-validation. Selecting the window size 11 provided the best performance for determining the proline cis/trans isomerization based on the single amino acid sequence. It was found that using multiple sequence alignments in the form of PSI-BLAST profiles could significantly improve the prediction performance, the prediction accuracy increased from 62.8% with single sequence to 69.8% and Matthews Correlation Coefficient (MCC) improved from 0.26 with single local sequence to 0.40. Furthermore, if coupled with the predicted secondary structure information by PSIPRED, our method yielded a prediction accuracy of 71.5% and MCC of 0.43, 9% and 0.17 higher than the accuracy achieved based on the singe sequence information, respectively. Conclusion A new method has been developed to predict the proline cis/trans isomerization in proteins based on support vector machine, which used the single amino acid sequence with different local window sizes, the amino acid compositions of local sequence flanking centered proline residues, the position-specific scoring matrices (PSSMs) extracted by PSI-BLAST and the predicted secondary structures generated by PSIPRED. The successful application of SVM approach in this study reinforced that SVM is a powerful tool in predicting proline cis/trans isomerization in proteins and biological sequence analysis.

Timeliness and Clinical Impact of Hospital-Initiated Medication Reviews

Background: Medication-related problems often occur in the immediate post-discharge period. To reduce medication misadventure the Commonwealth Government funds home medicines reviews (HMRs). HMRs are initiated when general practitioners refer consenting patients to their community pharmacists, who then engage accredited pharmacists to review patients' medicines in their homes. Aim: To determine if hospital-initiated medication reviews (HIMRs) can be implemented in a more timely manner than HMRs; and to assess the impact of a bespoke referral form with comorbidity-specific questions on the quality of reports. Method: Eligible medical inpatients at risk of medication misadventure were referred by the hospital liaison pharmacist to participating accredited pharmacists post-discharge from hospital. Social, demographic and laboratory data were collected from medical records and during interviews with consenting patients. Issues raised in the HIMR reports were categorised: intervention/action, information given or recommendation, and assigned a rank of clinical significance. Results: HIMRs were conducted within 11.6 6.6 days postdischarge. 36 HIMR reports were evaluated and 1442 issues identified - information given (n = 1204), recommendations made (n = 88) and actions taken (n = 150). The majority of issues raised (89%) had a minor clinical impact. The bespoke referral form prompted approximately half of the issues raised. Conclusion: HIMRs can be facilitated in a more timely manner than post-discharge HMRs. There was an associated positive clinical impact of issues raised in the HIMR reports.