Predicting Antimicrobial Activity of Conjugated Oligoelectrolyte Molecules via Machine Learning.

New antibiotics are needed to battle growing antibiotic resistance, but the development process from hit, to lead, and ultimately to a useful drug takes decades. Although progress in molecular property prediction using machine-learning methods has opened up new pathways for aiding the antibiotics development process, many existing solutions rely on large data sets and finding structural similarities to existing antibiotics. Challenges remain in modeling unconventional antibiotic classes that are drawing increasing research attention. In response, we developed an antimicrobial activity prediction model for conjugated oligoelectrolyte molecules, a new class of antibiotics that lacks extensive prior structure-activity relationship studies. Our approach enables us to predict the minimum inhibitory concentration for E. coli K12, with 21 molecular descriptors selected by recursive elimination from a set of 5305 descriptors. This predictive model achieves an R2 of 0.65 with no prior knowledge of the underlying mechanism. We find the molecular representation optimum for the domain is the key to good predictions of antimicrobial activity. In the case of conjugated oligoelectrolytes, a representation reflecting the three-dimensional shape of the molecules is most critical. Although it is demonstrated with a specific example of conjugated oligoelectrolytes, our proposed approach for creating the predictive model can be readily adapted to other novel antibiotic candidate domains.

Cross-reactivity of rPvs48/45, a recombinant Plasmodium vivax protein, with sera from Plasmodium falciparum endemic areas of Africa.

Background: Ps48/45, a Plasmodium gametocyte surface protein, is a promising candidate for malaria transmission-blocking (TB) vaccine. Due to its relevance for a multispecies vaccine, we explored the cross-reactivity and TB activity of a recombinant P. vivax Ps48/45 protein (rPvs48/45) with sera from P. falciparum-exposed African donors. Methods: rPvs48/45 was produced in Chinese hamster ovary cell lines and tested by ELISA for its cross-reactivity with sera from Burkina Faso, Tanzania, Mali, and Nigeria - In addition, BALB/c mice were immunized with the rPvs48/45 protein formulated in Montanide ISA-51 and inoculated with a crude extract of P. falciparum NF-54 gametocytes to evaluate the parasite-boosting effect on rPvs48/45 antibody titers. Specific anti-rPvs48/45 IgG purified from African sera was used to evaluate the ex vivo TB activity on P. falciparum, using standard mosquito membrane feeding assays (SMFA). Results: rPvs48/45 protein showed cross-reactivity with sera of individuals from all four African countries, in proportions ranging from 94% (Tanzania) to 40% (Nigeria). Also, the level of cross-reactive antibodies varied significantly between countries (p<0.0001), with a higher antibody level in Mali and the lowest in Nigeria. In addition, antibody levels were higher in adults (≥ 17 years) than young children (≤ 5 years) in both Mali and Tanzania, with a higher proportion of responders in adults (90%) than in children (61%) (p<0.0001) in Mali, where male (75%) and female (80%) displayed similar antibody responses. Furthermore, immunization of mice with P. falciparum gametocytes boosted anti-Pvs48/45 antibody responses, recognizing P. falciparum gametocytes in indirect immunofluorescence antibody test. Notably, rPvs48/45 affinity-purified African IgG exhibited a TB activity of 61% against P. falciparum in SMFA. Conclusion: African sera (exposed only to P. falciparum) cross-recognized the rPvs48/45 protein. This, together with the functional activity of IgG, warrants further studies for the potential development of a P. vivax and P. falciparum cross-protective TB vaccine.

Seroprevalence of SARS-CoV-2 Antibodies and Associated Factors in Bamako, Mali: A Population-Based Cross-Sectional Study in September 2022.

BACKGROUND: The sero-epidemiological characteristics of SARS-CoV-2 infections in Mali are not yet well understood. This study assessed SARS-CoV-2 antibody seroprevalence and factors associated with antibody responses in the general population of Bamako, the capital city and epicenter of COVID-19, to assess the magnitude of the pandemic and contribute to control strategy improvements in Mali. METHODS: A cross-sectional survey was conducted in September 2022 to collect sociodemographic information, clinical characteristics, comorbid factors, and blood samples. ELISA was performed to determine anti-Spike (anti-S) and anti-RBD antibody levels. A total of 3601 participants were enrolled in REDCap. R-Studio was used for the statistical analysis. The chi-squared (χ2) test was used to compare the proportions across different groups. Logistic regression models were used to elucidate factors associated with antibody responses. RESULT: The sex ratio for female-to-male was 3.6:1. The most representative groups were the 20-29-year-olds (28.9%, n = 1043) and the 30-39-year-olds (26.9%, n = 967). The COVID-19 vaccine coverage among the participants was 35.8%, with vaccines from Covishield AstraZeneca (13.4%), Johnson & Johnson (16.7%), Sinovac (3.9%), and BioNTech Pfizer (1.8%). Overall, S protein and RBD antibody seroprevalences were remarkably high in the study population (98% and 97%, respectively). Factors such as youth (1-9 years old) and male sex were associated with lower SARS-CoV-2 antibody responses, whereas COVID-19 vaccinations were associated with increased antibody responses. CONCLUSION: This serosurvey demonstrated the high seroprevalence of SARS-CoV-2 antibodies and highlighted the factors influencing antibody responses, while clearly underlining an underestimation of the pandemic in Mali.

Seroreactivity of the Severe Acute Respiratory Syndrome Coronavirus 2 Recombinant S Protein, Receptor-Binding Domain, and Its Receptor-Binding Motif in COVID-19 Patients and Their Cross-Reactivity With Pre-COVID-19 Samples From Malaria-Endemic Areas.

Despite the global interest and the unprecedented number of scientific studies triggered by the COVID-19 pandemic, few data are available from developing and low-income countries. In these regions, communities live under the threat of various transmissible diseases aside from COVID-19, including malaria. This study aims to determine the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) seroreactivity of antibodies from COVID-19 and pre-COVID-19 samples of individuals in Mali (West Africa). Blood samples from COVID-19 patients (n = 266) at Bamako Dermatology Hospital (HDB) and pre-COVID-19 donors (n = 283) from a previous malaria survey conducted in Dangassa village were tested by ELISA to assess IgG antibodies specific to the full-length spike (S) protein, the receptor-binding domain (RBD), and the receptor-binding motif (RBM436-507). Study participants were categorized by age, gender, treatment duration for COVID-19, and comorbidities. In addition, the cross-seroreactivity of samples from pre-COVID-19, malaria-positive patients against the three antigens was assessed. Recognition of the SARS-CoV-2 proteins by sera from COVID-19 patients was 80.5% for S, 71.1% for RBD, and 31.9% for RBM (p < 0.001). While antibody responses to S and RBD tended to be age-dependent, responses to RBM were not. Responses were not gender-dependent for any of the antigens. Higher antibody levels to S, RBD, and RBM at hospital entry were associated with shorter treatment durations, particularly for RBD (p < 0.01). In contrast, higher body weights negatively influenced the anti-S antibody response, and asthma and diabetes weakened the anti-RBM antibody responses. Although lower, a significant cross-reactive antibody response to S (21.9%), RBD (6.7%), and RBM (8.8%) was detected in the pre-COVID-19 and malaria samples. Cross-reactive antibody responses to RBM were mostly associated (p < 0.01) with the absence of current Plasmodium falciparum infection, warranting further study.