Browsing by Author "Kwarteng, Alexander"
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- ItemMolecular characterization of interactions between the D614G variant of SARS-CoV-2 S-protein and neutralizing antibodies: A computational approach(Infection, Genetics and Evolution, 2021) Kwarteng, Alexander; Asiedu, Ebenezer; Sylverken, Augustina Angelina; Larbi, Amma; Sakyi, Samuel Asamoah; Asiedu, Samuel Opoku; 0000-0002-0893-2908; 0000-0003-2867-1984; 0000-0002-7691-914X; 0000-0002-3814-6924; 0000-0001-5168-4762; 0000-0002-0352-3195The D614G variant of SARS-CoV-2 S-protein emerged in early 2020 and quickly became the dominant circulating strain in Europe and its environs. The variant was characterized by the higher viral load, which is not associated with disease severity, higher incorporation into the virion, and high cell entry via ACE-2 and TMPRSS2. Previous strains of the coronavirus and the current SARS-CoV-2 have demonstrated the selection of mutations as a mechanism of escaping immune responses. In this study, we used molecular dynamics simulation and MM-PBSA binding energy analysis to provide insights into the behaviour of the D614G S-protein at the molecular level and describe the neutralization mechanism of this variant. Our results show that the D614G S-protein adopts distinct conformational dynamics which is skewed towards the open-state conformation more than the closed-state conformation of the wild-type S-protein. Residue-specific variation of amino acid flexibility and domain specific RMSD suggest that the mutation causes an allosteric conformational change in the RBD. Evaluation of the interaction energies between the S-protein and neutralizing antibodies show that the mutation may enhance, reduce or not affect the neutralizing interactions depending on the neutralizing antibody, especially if it targets the RBD. The results of this study have shed insights into the behaviour of the D614G S-protein at the molecular level and provided a glimpse of the neutralization mechanism of this variant.
- ItemUse of social media in a national Tuberculosis Drug Resistance Survey: lessons from the first anti-tuberculosis drug resistance survey in Ghana(AAS Open Research, 2019) Sylverken, Augustina Angelina; Owusu-Dabo, Ellis; Kwarteng, Alexander; Twumasi-Ankrah, Sampson; Owusu, Michael; Adu-Amoah, Louis; Dumevi, Rexford Mawunyo; Arthur, Rejoice Agyeiwaa; Addofoh, Nicholas; Dzata, Francisca; Bonsu, Frank; 0000-0002-7691-914X; 0000-0003-4232-4292; 0000-0002-0893-2908; 0000-0002-9183-1883; 0000-0001-5066-150X; 0000-0001-6755-2545; 0000-0002-7135-2754Background: The widespread use of social media applications on mobile phones indicate that smart phones have become more than just a simple medium for voice calling. Several studies have shown the potential benefit of these social media applications in discussing many health conditions. We report on tracking sample transport by public and private transport providers using WhatsApp during the first nationwide drug resistance tuberculosis (TB) survey in Ghana. Methods: The survey was conducted between February 2016 and June 2017, and involved 33 TB diagnostic sites selected on the basis of a two-stage cluster randomized sampling design on both anticipated yield and probability proportional to size method. We engaged the services of privately and publicly owned vehicles’ union to transport samples to the central laboratories in Kumasi for further laboratory processing.We created a mobile social group platform (‘National TBDRS’) on WhatsApp consisting of two representatives from each site as well as other stakeholders. The purpose was to notify a laboratory team in Kumasi, on the following details of the sample: date and time of dispatch, driver’s name, car number, estimated time of arrival, and bus terminal name. Results: A total 3077 WhatsApp messages were received during the survey period. Of these, 2879 (93.57%) messages were related to the survey. We observed a positive correlation between the total number of messages received and the total number of well-packaged sputum samples sent (r=0.89, p=0.02). There were no major transport delays (11:44±03:50) and all samples arrived within a 3-day window from the survey sites. Conclusions: Using WhatsApp as a platform of communication can significantly aid in improving tracking of samples, enhance accountability of for example drivers handling the samples over at a road crossing and communication across health facilities.