Leveraging binding pose metadynamics to optimise target fishing predictions for three diverse ligands and their true targets.

Computational target fishing plays an important role in target identification, particularly in drug discovery campaigns utilizing phenotypic screening. Numerous approaches exist to predict potential targets for a given ligand, but true targets may be inconsistently ranked. More advanced simulation methods may provide benefit in such cases by reranking these initial predictions. We evaluated the ability of binding pose metadynamics to improve the predicted rankings for three diverse ligands and their six true targets. Initial predictions using pharmacophore mapping showed no true targets ranked in the top 50 and two targets each ranked within the 50-100, 100-150, and 250-300 ranges respectively. Following binding pose metadynamics, ranking of true targets improved for four out of the six targets and included the highest ranked predictions overall, while rankings deteriorated for two targets. The revised rankings predicted two true targets ranked within the top 50, and one target each within the 50-100, 100-150, 150-200, and 200-250 ranges respectively. The findings of this study demonstrate that binding pose metadynamics may be of benefit in refining initial predictions from structure-based target fishing algorithms, thereby improving the efficiency of the target identification process in drug discovery efforts.

A survey of the adoption and perception of mobile health applications among community pharmacists in Malaysia.

OBJECTIVES: To determine the adoption and perception of mobile health (mHealth) applications among community pharmacists in Malaysia. METHODS: A cross-sectional survey using a self-administered questionnaire was conducted with 300 community pharmacists in the Klang Valley, Malaysia using a stratified sampling approach. The questionnaire consisted of 36 questions with three sections: demographic data, adoption of mHealth applications and perception towards mHealth applications. Descriptive and inferential tests as well as exploratory factor analysis were used to analyse the data. KEY FINDINGS: Adoption of mHealth applications by community pharmacists for both professional and personal use was relatively high at 79.7%. Utilised mHealth applications were primarily from the medical references category, while applications for patient monitoring, personal care and fitness were used to a lesser degree. Among mHealth application users, only 65.7% recommended them to their patients. Overall perception towards mHealth applications was positive, but perception towards the benefits and favour of mHealth applications for their patients was lower. This was corroborated by the factor analysis, which identified four main factors explaining 59.9% of variance in the dataset. These factors were perception towards use in their own professional practice, perception on benefits and use in their patients, perception on specific features of mHealth applications, and reliability of mHealth applications. CONCLUSIONS: Adoption of mHealth applications among community pharmacists in Malaysia is high. Community pharmacists are more likely to use mHealth applications professionally and personally but less likely to recommend them to patients due to less favourable perceptions on how patients will benefit from mHealth applications.

Consensus scoring evaluated using the GPCR-Bench dataset: Reconsidering the role of MM/GBSA.

The recent availability of large numbers of GPCR crystal structures has provided an unprecedented opportunity to evaluate their performance in virtual screening protocols using established benchmarking datasets. In this study, we evaluated the ability of MM/GBSA in consensus scoring-based virtual screening enrichment together with nine classical scoring functions, using the GPCR-Bench dataset consisting of 24 GPCR crystal structures and 254,646 actives and decoys. While the performance of consensus scoring was modest overall, combinations which included MM/GBSA performed relatively well compared to combinations of classical scoring functions. Combinations of MM/GBSA and good-performing scoring functions provided the highest proportion of improvements, with improvements observed in 32% and 19% of all combinations across all targets at the EF1% and EF5% levels respectively. Combinations of MM/GBSA and poor-performing scoring functions still outperformed classical scoring functions, with improvements observed in 26% and 17% of all combinations at the EF1% and EF5% levels. In comparison, only 14-22% and 6-11% of combinations of classical scoring functions produced improvements at EF1% and EF5% respectively. Efforts to improve performance by increasing the number of scoring functions in consensus scoring to three were mostly ineffective. We also observed that consensus scoring performed better for individual scoring functions possessing initially low enrichment factors, potentially implying their benefits are more relevant in such scenarios. Overall, this study demonstrated the first implementation of MM/GBSA in consensus scoring using the GPCR-Bench dataset and could provide a valuable benchmark of the performance of MM/GBSA in comparison to classical scoring functions in consensus scoring for GPCRs.

An exploratory analysis of general practitioner prescribing patterns in Malaysia using a health insurance claims database.

OBJECTIVES: To determine the prescribing patterns and identify potentially inappropriate prescribing practices among general practitioners in the private primary care sector by analysing a large electronic health insurance claims database. METHODS: Medical claims records from February 2019 to February 2020 were extracted from a health insurance claims database. Data cleaning and data analysis were performed using Python 3.7 with the Pandas, NumPy and Matplotlib libraries. The top five most common diagnoses were identified, and for each diagnosis, the most common medication classes and medications prescribed were quantified. Potentially inappropriate prescribing practices were identified by comparing the medications prescribed with relevant clinical guidelines. KEY FINDINGS: The five most common diagnoses were upper respiratory tract infection (41.5%), diarrhoea (7.7%), musculoskeletal pain (7.6%), headache (6.7%) and gastritis (4.0%). Medications prescribed by general practitioners were largely as expected for symptomatic management of the respective conditions. One area of potentially inappropriate prescribing identified was inappropriate antibiotic choice. Same-class polypharmacy that may lead to an increased risk of adverse events were also identified, primarily involving multiple paracetamol-containing products, non-steroidal anti-inflammatory drugs (NSAIDs), and antihistamines. Other areas of non-adherence to guidelines identified included the potential overuse of oral corticosteroids and oral salbutamol, and inappropriate gastroprotection for patients receiving NSAIDs. CONCLUSIONS: While prescribing practices are generally appropriate within the private primary care sector, there remain several areas where some potentially inappropriate prescribing occurs. The areas identified should be the focus in continuing efforts to improve prescribing practices to obtain the optimal clinical outcomes while reducing unnecessary risks and healthcare costs.

Awareness of osteoporosis risk assessment tools and screening recommendations among community pharmacists in Malaysia.

Background The incidence of osteoporosis in Malaysia is increasing due to a fast-ageing population. Because of its silent nature, various osteoporosis risk assessment tools exist to detect high-risk patients and facilitate referrals for bone mineral density measurements. As an accessible point of contact, community pharmacists would benefit from the utilization of these tools and familiarity with guideline recommendations for osteoporosis screening. Aim This study aimed to investigate the awareness of osteoporosis risk assessment tools, practice behaviour towards osteoporosis, and knowledge of guideline recommendations among community pharmacists in the Klang Valley, Malaysia. Setting Community pharmacies. Methods This study was a cross-sectional study which sampled 284 community pharmacists practicing in the Klang Valley, using a stratified sampling approach. The study was conducted using a self-administered questionnaire which was divided into three sections: demographic data, knowledge of osteoporosis risk assessment tools and guideline recommendations, and practice behaviour towards osteoporosis. Practice behaviour was assessed with 15 items using a 5-point Likert scale. Main outcome measure. Proportion of respondents aware of osteoporosis risk assessment tools and respondent knowledge on guideline recommendations for osteoporosis screening. Results A total of 284 community pharmacists participated in the study. 84.1% of the respondents were aware of at least one risk assessment tool. However, only a small proportion of pharmacists (14.9%) regularly used these tools in their practice. Respondents perceived these tools to be relevant and beneficial, but perception towards their accessibility, ease-of-use, and administration time was mixed, suggesting unfamiliarity. Respondents preferred to conduct clinical assessments based on risk factors, with respondents identifying a mean of 10.1 ± 3.4 out of 15 risk factors. However, several clinically relevant risk factors were frequently unidentified. Knowledge of guideline recommendations among respondents was low. Conclusion There is some awareness of osteoporosis risk assessment tools but use in practice remains low among community pharmacists in Malaysia. There is potential to increase the use of these tools and knowledge of recommendations for osteoporosis screening and referral among community pharmacists.

Benchmarking the performance of MM/PBSA in virtual screening enrichment using the GPCR-Bench dataset.

Recent breakthroughs in G protein-coupled receptor (GPCR) crystallography and the subsequent increase in number of solved GPCR structures has allowed for the unprecedented opportunity to utilize their experimental structures for structure-based drug discovery applications. As virtual screening represents one of the primary computational methods used for the discovery of novel leads, the GPCR-Bench dataset was created to facilitate comparison among various virtual screening protocols. In this study, we have benchmarked the performance of Molecular Mechanics/Poisson-Boltzmann Surface Area (MM/PBSA) in improving virtual screening enrichment in comparison to docking with Glide, using the entire GPCR-Bench dataset of 24 GPCR targets and 254,646 actives and decoys. Reranking the top 10% of the docked dataset using MM/PBSA resulted in improvements for six targets at EF1% and nine targets at EF5%, with the gains in enrichment being more pronounced at the EF1% level. We additionally assessed the utility of rescoring the top ten poses from docking and the ability of short MD simulations to refine the binding poses prior to MM/PBSA calculations. There was no clear trend of the benefit observed in both cases, suggesting that utilizing a single energy minimized structure for MM/PBSA calculations may be the most computationally efficient approach in virtual screening. Overall, the performance of MM/PBSA rescoring in improving virtual screening enrichment obtained from docking of the GPCR-Bench dataset was found to be relatively modest and target-specific, highlighting the need for validation of MM/PBSA-based protocols prior to prospective use.

The effect of multiple simulation parameters on MM/PBSA performance for binding affinity prediction of CB1 cannabinoid receptor agonists and antagonists.

Both the inactive- and active-state CB1 receptor crystal structures have now been solved, allowing their application in various structure-based drug design methods. One potential method utilizing these crystal structures is the Molecular Mechanics/Poisson-Boltzmann Surface Area (MM/PBSA) method of predicting relative binding free.

Awareness of Beers Criteria and knowledge of potentially inappropriate medications among community pharmacists in the Klang Valley, Malaysia.

BACKGROUND: Potentially inappropriate medications (PIMs) in older adults are detrimental to both clinical outcomes and health care costs, with their prominence set to increase in tandem with a fast-growing ageing population. Beers Criteria is one of the most commonly used guidelines that lists specific PIMs. Community pharmacists would therefore benefit from knowledge of Beers Criteria in detecting PIMs in primary care. This study therefore investigates the awareness of Beers Criteria and knowledge of PIMs among community pharmacists in the Klang Valley, Malaysia. METHODS: The study was conducted using a self-administered questionnaire. Knowledge of PIMs was assessed using 10 clinical vignettes based on the 2015 Beers Criteria. Practice behaviour towards older customers was assessed using 10 items with a 5-point Likert scale. Descriptive and inferential statistics were used to analyse the data. RESULTS: A total of 277 community pharmacists participated in the study. Only 27.1% of the pharmacists were aware of Beers Criteria, and of these, only 37.3% were aware of the latest 2015 update. The respondents demonstrated moderate knowledge of PIMs with a mean total score of 5.46 ± 1.89 out of a maximum of 10. Pharmacists who were aware of Beers Criteria had significantly higher scores (6.31 vs 5.14, P < .001). Only a small proportion of pharmacists (17.0%) regularly used Beers Criteria in practice. However, most pharmacists reported good practices when dealing with older customers in terms of asking relevant questions, considering age, referring to other resources, and regularly updating their knowledge through continuous professional development. CONCLUSION: Awareness of Beers Criteria remains low among community pharmacists in Malaysia. Pharmacists who are aware of Beers Criteria have improved knowledge regarding PIMs in the older adults. There is a need to increase the awareness and use of Beers Criteria among community pharmacists.

Evaluating the performance of MM/PBSA for binding affinity prediction using class A GPCR crystal structures.

The recent expansion of GPCR crystal structures provides the opportunity to assess the performance of structure-based drug design methods for the GPCR superfamily. Molecular Mechanics/Poisson-Boltzmann Surface Area (MM/PBSA)-based methods are commonly used for binding affinity prediction, as they provide an intermediate compromise of speed and accuracy between the empirical scoring functions used in docking and more robust free energy perturbation methods. In this study, we systematically assessed the performance of MM/PBSA in predicting experimental binding free energies using twenty Class A GPCR crystal structures and 934 known ligands. Correlations between predicted and experimental binding free energies varied significantly between individual targets, ranging from r = - 0.334 in the inactive-state CB1 cannabinoid receptor to r = 0.781 in the active-state CB1 cannabinoid receptor, while average correlation across all twenty targets was relatively poor (r = 0.183). MM/PBSA provided better predictions of binding free energies compared to docking scores in eight out of the twenty GPCR targets while performing worse for four targets. MM/PBSA binding affinity predictions calculated using a single, energy minimized structure provided comparable predictions to sampling from molecular dynamics simulations and may be more efficient when computational cost becomes restrictive. Additionally, we observed that restricting MM/PBSA calculations to ligands with a high degree of structural similarity to the crystal structure ligands improved performance in several cases. In conclusion, while MM/PBSA remains a valuable tool for GPCR structure-based drug design, its performance in predicting the binding free energies of GPCR ligands remains highly system-specific as demonstrated in a subset of twenty Class A GPCRs, and validation of MM/PBSA-based methods for each individual case is recommended before prospective use.

Ligand discrimination during virtual screening of the CB1 cannabinoid receptor crystal structures following cross-docking and microsecond molecular dynamics simulations.

The therapeutic potential of the CB1 cannabinoid receptor remains underexploited with only a few synthetic ligands on the market. The crystal structures of both the inactive and active-state CB1 receptor have recently been solved, allowing for unprecedented opportunities in structure-based drug discovery applications such as virtual screening. In this study, we have investigated the virtual screening performance of the active and inactive-state CB1 crystal structures and their ability to discriminate between agonist and inverse agonist/antagonist ligands. The ligands of inactive and active-state CB1 receptor crystal structures were then swapped via cross-docking and the resulting structures were subjected to microsecond molecular dynamics (MD) simulations, followed by virtual screening of the MD-extracted structures. The original crystal structures were found to be biased towards ligands matching their activation state during virtual screening. MD simulations of the cross-docked CB1 structures resulted in a minor shift of receptor conformation towards the inactive state for the active-state CB1 structure complexed with the inverse agonist taranabant. Effects on virtual screening were more pronounced, as MD simulations of the cross-docked receptor-ligand complexes reversed the ligand bias in virtual screening observed with the original crystal structures. The simulations also produced receptor conformations that outperformed the crystal structures in virtual screening and in predicting the binding pose of the cognate ligand. The findings of this study highlight the potential of cross-docking and MD simulations to reverse the ligand bias of crystal structures, which may be useful when the crystal structure of only one activation state is available.

Assessing GPCR homology models constructed from templates of various transmembrane sequence identities: Binding mode prediction and docking enrichment.

GPCR crystal structures have become more readily accessible in recent years. However, homology models of GPCRs continue to play an important role as many GPCR structures remain unsolved. The new crystal structures now available provide not only additional templates for homology modelling but also the opportunity to assess the performance of homology models against their respective crystal structures and gain insight into the performance of such models. In this study we have constructed homology models from templates of various transmembrane sequence identities for eight GPCR targets to better understand the relationship between transmembrane sequence identity and model quality. Model quality was assessed relative to the crystal structure in terms of structural accuracy as well as performance in two typical structure-based drug design applications: ligand binding pose prediction and docking enrichment in virtual screening. Crystal structures significantly outperformed homology models in both assessments. Accurate ligand binding pose prediction was possible but difficult to achieve using homology models, even with the use of induced fit docking. In virtual screening using homology models still conferred significant enrichment compared to random selection, with a clear benefit also observed in using models optimized through induced fit docking. Our results indicate that while homology models that are reasonably accurate structurally can be constructed, without significant refinement homology models will be outperformed by crystal structures in ligand binding pose prediction and docking enrichment regardless of the template used, primarily due to the extremely high level of structural accuracy needed for such applications.

Pharmacy students in private institutions of higher education: motivating factors when studying pharmacy and influences on university choice.

OBJECTIVES: To identify factors influencing the decisions of Malaysian first-year pharmacy undergraduate students in private higher education when choosing to pursue a degree in pharmacy as well as their choice of private university. METHODS: This cross-sectional study employed a validated, self-administered questionnaire which was administered to 543 first-year pharmacy students from nine different private universities. Factor analysis was utilised to extract key factors from the responses. Descriptive and inferential statistics were used to analyse the data. KEY FINDINGS: Eight factors motivating students' decision to study pharmacy emerged from the responses, accounting for 63.8% of the variance observed. Students were primarily motivated by intrinsic interests, with work conditions and profession attributes also exerting significant influence. In terms of choice of private university, nine factors were identified, accounting for 73.8% of the variance observed. The image of the school and university were most influential factors in this context, followed by university safety, programme attributes and financial factors. CONCLUSIONS: First-year pharmacy students in the private higher education sector are motivated by intrinsic interest when choosing to study pharmacy over other courses, while their choice of private university is influenced primarily by the image of the school and university.

Global Antimicrobial Stewardship: A Closer Look at the Formidable Implementation Challenges.

Antimicrobial stewardship (AMS) has been touted as one of the key strategies required in tackling worldwide escalation of antibiotic resistance. Although AMS has optimized antibiotic usage and reduced the incidence of resistance development in some regions, its full global potential has been curtailed by various AMS-impeding factors. This article seeks to highlight in a detailed perspective, the key challenges that hamper global AMS endeavors, some of which include the paucity of effective implementation strategies that cater for the challenging settings of developing nations, the slow response of governments, uncoordinated AMS activities as well as implementation fragmentation across different sectors and countries. The authors of this article call upon all stakeholders to pay attention to these seemingly obvious but often under-addressed problems. If left unresolved, this may render all current and future AMS initiatives pointless.