Predicting Residence Time of GPCR Ligands with Machine Learning

Drug-target residence time, the duration of binding at a given protein target, has been shown in some protein families to be more significant for conferring efficacy than binding affinity. To carry out efficient optimization of residence time in drug discovery, machine learning models that can predict that value need to be developed. One of the main challenges with predicting residence time is the paucity of data. This chapter outlines all of the currently available ligand kinetic data, providing a repository that contains the largest publicly available source of GPCR-ligand kinetic data to date. To help decipher the features of kinetic data that might be beneficial to include in computational models for the prediction of residence time, the experimental evidence for properties that influence residence time are summarized. Finally, two different workflows for predicting residence time with machine learning are outlined. The first is a single-target model trained on ligand features; the second is a multi-target model trained on features generated from molecular dynamics simulations

Parenting stress of caregivers of young children who are HIV Positive

Objective: Paediatric HIV remains a major challenge in Sub-Saharan Africa. Paediatric HIV is a multi-generational disorder with far-reaching implications for the whole family. Parenting stress in caregivers of HIV infected children has been studied in developed countries but never in South Africa. The aim of this study was to determine the extent of parenting stress in caregivers of children infected with HIV in South Africa. Further objectives were to monitor the levels of stress over one year after caregivers started attending a paediatric HIV clinic and to ascertain what factors were predictive of a decrease in parenting stress over that time. Method: One hundred and twenty two caregiver and children dyads were recruited into this study. Caregivers completed the Parenting Stress Index/ Short form at baseline and after six and 12 months. Demographic information was collected and the children's heights, weights and CD4 counts were recorded at each visit. Results: The families that participated in this study came from very poor socio-economic backgrounds. Eighty five percent of the children were still being cared for by their biological mothers. The parenting stress levels of the caregivers in this study were extremely high at baseline. Although the parenting stress levels did come down significantly over the study period (p< 0.001) they remained high and warrant further investigation and management. A better level of education, better housing facilities and fewer adults living in the household were the three most important factors predicting a decrease in parenting stress over a one year period. Conclusion: Parenting stress of caregivers of young children infected with HIV is extremely high and warrants further investigation and long term management.African Journal of Psychiatry Vol. 10 (4) 2007: pp. 210-21

Paediatric HIV - Looking beyond CD4 counts

Paediatric HIV remains a significant health and social challenge in sub-Saharan Africa despite many countries gaining improved access to antiretroviral treatment. Paediatric HIV affects multiple body systems and has the potential to cause wide ranging impairments as well as activity and participation limitations. The aim of this paper is to highlight some of the impairments that remain, despite the children having access to better medical care, in order to establish a possible role for physiotherapists. Nine studies conducted through the department of physiotherapy at the University of the Witwatersrand, South Africa are presented. The results of these studies demonstrate the neurodevelopmental, musculoskeletal, respiratory and quality of life challenges which children infected with HIV as well as their caregivers continue to face. The need for long term, multidisciplinary follow up of children infected with HIV is emphasized

Long Time Scale Ensemble Methods in Molecular Dynamics: Ligand-Protein Interactions and Allostery in SARS-CoV-2 Targets

We subject a series of five protein–ligand systems which contain important SARS-CoV-2 targets, 3-chymotrypsin-like protease (3CLPro), papain-like protease, and adenosine ribose phosphatase, to long time scale and adaptive sampling molecular dynamics simulations. By performing ensembles of ten or twelve 10 μs simulations for each system, we accurately and reproducibly determine ligand binding sites, both crystallographically resolved and otherwise, thereby discovering binding sites that can be exploited for drug discovery. We also report robust, ensemble-based observation of conformational changes that occur at the main binding site of 3CLPro due to the presence of another ligand at an allosteric binding site explaining the underlying cascade of events responsible for its inhibitory effect. Using our simulations, we have discovered a novel allosteric mechanism of inhibition for a ligand known to bind only at the substrate binding site. Due to the chaotic nature of molecular dynamics trajectories, regardless of their temporal duration individual trajectories do not allow for accurate or reproducible elucidation of macroscopic expectation values. Unprecedentedly at this time scale, we compare the statistical distribution of protein–ligand contact frequencies for these ten/twelve 10 μs trajectories and find that over 90% of trajectories have significantly different contact frequency distributions. Furthermore, using a direct binding free energy calculation protocol, we determine the ligand binding free energies for each of the identified sites using long time scale simulations. The free energies differ by 0.77 to 7.26 kcal/mol across individual trajectories depending on the binding site and the system. We show that, although this is the standard way such quantities are currently reported at long time scale, individual simulations do not yield reliable free energies. Ensembles of independent trajectories are necessary to overcome the aleatoric uncertainty in order to obtain statistically meaningful and reproducible results. Finally, we compare the application of different free energy methods to these systems and discuss their advantages and disadvantages. Our findings here are generally applicable to all molecular dynamics based applications and not confined to the free energy methods used in this study

Developmental outcome of very low birth weight infants in a developing country

Background: Advances in neonatal care allow survival of extremely premature infants, who are at risk of handicap. Neurodevelopmental follow up of these infants is an essential part of ongoing evaluation of neonatal care. The neonatal care in resource limited developing countries is very different to that in first world settings. Follow up data from developing countries is essential; it is not appropriate to extrapolate data from units in developed countries. This study provides follow up data on a population of very low birth weight (VLBW) infants in Johannesburg, South Africa. Methods: The study sample included all VLBW infants born between 01/06/2006 and 28/02/2007 and discharged from the neonatal unit at Charlotte Maxeke Johannesburg Academic Hospital (CMJAH). Bayley Scales of Infant and Toddler Development Version 111 (BSID) 111 were done to assess development. Regression analysis was done to determine factors associated with poor outcome. Results: 178 infants were discharged, 26 were not available for follow up, 9 of the remaining 152 (5.9%) died before an assessment was done; 106 of the remaining 143 (74.1%) had a BSID 111 assessment. These 106 patients form the study sample; mean birth weight and mean gestational age was 1182 grams (SD: 197.78) and 30.81 weeks (SD: 2.67) respectively. The BSID (111) was done at a median age of 16.48 months. The mean cognitive subscale was 88.6 (95% CI: 85.69-91.59), 9 (8.5%) were < 70, mean language subscale was 87.71 (95% CI: 84.85-90.56), 10 (9.4%) < 70, and mean motor subscale was 90.05 (95% CI: 87.0-93.11), 8 (7.6%) < 70. Approximately one third of infants were identified as being at risk (score between 70 and 85) on each subscale. Cerebral palsy was diagnosed in 4 (3.7%) of babies. Factors associated with poor outcome included cystic periventricular leukomalacia (PVL), resuscitation at birth, maternal parity, prolonged hospitalisation and duration of supplemental oxygen. PVL was associated with poor outcome on all three subscales. Birth weight and gestational age were not predictive of neurodevelopmental outcome. Conclusion: Although the neurodevelopmental outcome of this group of VLBW infants was within the normal range, with a low incidence of cerebral palsy, these results may reflect the low survival of babies with a birth weight below 900 grams. In addition, mean subscale scores were low and one third of the babies were identified as "at risk", indicating that this group of babies warrants long-term follow up into school going age

Developmental outcome of very low birth weight infants in a developing country

BACKGROUND: Advances in neonatal care allow survival of extremely premature infants, who are at risk of handicap. Neurodevelopmental follow up of these infants is an essential part of ongoing evaluation of neonatal care. The neonatal care in resource limited developing countries is very different to that in first world settings. Follow up data from developing countries is essential; it is not appropriate to extrapolate data from units in developed countries. This study provides follow up data on a population of very low birth weight (VLBW) infants in Johannesburg, South Africa. METHODS: The study sample included all VLBW infants born between 01/06/2006 and 28/02/2007 and discharged from the neonatal unit at Charlotte Maxeke Johannesburg Academic Hospital (CMJAH). Bayley Scales of Infant and Toddler Development Version 111 (BSID) 111 were done to assess development. Regression analysis was done to determine factors associated with poor outcome. RESULTS: 178 infants were discharged, 26 were not available for follow up, 9 of the remaining 152 (5.9%) died before an assessment was done; 106 of the remaining 143 (74.1%) had a BSID 111 assessment. These 106 patients form the study sample; mean birth weight and mean gestational age was 1182 grams (SD: 197.78) and 30.81 weeks (SD: 2.67) respectively. The BSID (111) was done at a median age of 16.48 months. The mean cognitive subscale was 88.6 (95% CI: 85.69 - 91.59), 9 (8.5%) were < 70, mean language subscale was 87.71 (95% CI: 84.85 - 90.56), 10 (9.4%) < 70, and mean motor subscale was 90.05 (95% CI: 87.0 - 93.11), 8 (7.6%) < 70. Approximately one third of infants were identified as being at risk (score between 70 and 85) on each subscale. Cerebral palsy was diagnosed in 4 (3.7%) of babies. Factors associated with poor outcome included cystic periventricular leukomalacia (PVL), resuscitation at birth, maternal parity, prolonged hospitalisation and duration of supplemental oxygen. PVL was associated with poor outcome on all three subscales. Birth weight and gestational age were not predictive of neurodevelopmental outcome. CONCLUSION: Although the neurodevelopmental outcome of this group of VLBW infants was within the normal range, with a low incidence of cerebral palsy, these results may reflect the low survival of babies with a birth weight below 900 grams. In addition, mean subscale scores were low and one third of the babies were identified as "at risk", indicating that this group of babies warrants long-term follow up into school going age

Synergistic Use of GPCR Modeling and SDM Experiments to Understand Ligand Binding

There is a substantial amount of historical ligand binding data available from site-directed mutagenesis (SDM) studies of many different GPCR subtypes. This information was generated prior to the wave of GPCR crystal structure, in an effort to understand ligand binding with a view to drug discovery. Concerted efforts to determine the atomic structure of GPCRs have proven extremely successful and there are now more than 80 GPCR crystal structure in the PDB database, many of which have been obtained in the presence of receptor ligands and associated G proteins. These structural data enable the generation of computational model structures for all GPCRs, including those for which crystal structures do not yet exist. The power of these models in designing novel ligands, especially those with improved residence times, and for better understanding receptor function can be enhanced tremendously by combining them synergistically with historic SDM ligand binding data. Here, we describe a protocol by which historic SDM binding data and receptor models may be used together to identify novel key residues for mutagenesis studies

Hit-to-lead and lead optimization binding free energy calculations for G protein-coupled receptors

We apply the hit-to-lead ESMACS (enhanced sampling of molecular dynamics with approximation of continuum solvent) and lead-optimization TIES (thermodynamic integration with enhanced sampling) methods to compute the binding free energies of a series of ligands at the A1 and A2A adenosine receptors, members of a subclass of the GPCR (G protein-coupled receptor) superfamily. Our predicted binding free energies, calculated using ESMACS, show a good correlation with previously reported experimental values of the ligands studied. Relative binding free energies, calculated using TIES, accurately predict experimentally determined values within a mean absolute error of approximately 1 kcal mol−1. Our methodology may be applied widely within the GPCR superfamily and to other small molecule–receptor protein systems

JLigand: a graphical tool for the CCP4 template-restraint library

The CCP4 template-restraint library defines restraints for biopolymers, their modifications and ligands that are used in macromolecular structure refinement. JLigand is a graphical editor for generating descriptions of new ligands and covalent linkages