Drug-like compounds are most of the time denied approval and use owing to the unexpected clinical side effects and cross-reactivity observed during clinical trials. These unexpected outcomes resulting in significant increase in attrition rate centralizes on the selected drug targets. These targets may be disease candidate proteins or genes, biological pathways, disease-associated microRNAs, disease-related biomarkers, abnormal molecular phenotypes, crucial nodes of biological network or molecular functions. This is generally linked to several factors, including incomplete knowledge on the drug targets and unpredicted pharmacokinetic expressions upon target interaction or off-target effects. A method used to identify targets, especially for polygenic diseases, is essential and constitutes a major bottleneck in drug development with the fundamental stage being the identification and validation of drug targets of interest for further downstream processes. Thus, various computational methods have been developed to complement experimental approaches in drug discovery. Here, we present an overview of various computational methods and tools applied in predicting or validating drug targets and drug-like molecules. We provide an overview on their advantages and compare these methods to identify effective methods which likely lead to optimal results. We also explore major sources of drug failure considering the challenges and opportunities involved. This review might guide researchers on selecting the most efficient approach or technique during the computational drug discovery process.

Understanding the epidemiology of asymptomatic Plasmodium falciparum infections is critical for countries to move toward malaria elimination. Using different methods for parasite detection, we evaluated how seasonality, spatial location, and other factors affect the age-specific epidemiology of asymptomatic malaria in Bongo District, Ghana. Asymptomatic prevalence by microscopy decreased significantly from 42.5% at the end of the wet to 27.5% at the end of the dry season (P < 0.001). Using the 18S rRNA polymerase chain reactions (PCRs), all microscopy-negative samples were screened and prevalence of submicroscopic infections also decreased significantly from the wet (55.4%) to the dry (20.7%) season (P < 0.001). Combining detection methods, 74.4% and 42.5% of the population in the wet and dry seasons, respectively, had evidence of a P. falciparum infection. Interestingly in those > 20 years of age, we found evidence of infection in 64.3% of the population in the wet and 27.0% in the dry season. Using both microscopy and PCR, the asymptomatic P. falciparum reservoir peaks at the end of the wet season and infections in all age groups constitute the reservoir of malaria infection. At the end of the wet season, spatial heterogeneity in the prevalence and density of P. falciparum infections was observed between the two catchment areas surveyed in Bongo District. These results indicate that if elimination is to succeed, interventions will need to target not just P. falciparum infections in children but also in adults, and be implemented toward the end of the dry season in this area of West Africa.

Background: Asymptomatic Plasmodium infections significantly drive malaria transmission and impact control and elimination strategies, but are largely uncharacterized. We investigated the prevalence and risk factors of asymptomatic malaria infections to inform malaria control strategies in Ghana. Method: Five cross-sectional surveys were conducted at the end of the peak transmission season (August–September) on 4892 school children aged between 6 and 14 years in two distinct ecological settings in Ghana between 2013 and 2017. The study sites were Begoro (forest ecology) and Cape Coast (coastal ecology). The children were screened for malaria parasites by microscopic examination of Giemsa-stained thin and thick blood films. Hemoglobin levels were measured using the Hemocue HB analyzer. In addition, height was measured and the height-for-age z-scores estimated from the reference population defined by WHO to determine children who were stunted. Proportions of categorical and means of continuous variables were compared using Chi-square test and Student’s t-test respectively, and multivariable logistic regression was done to assess risk factors associated with asymptomatic infections. Results: The overall prevalence of asymptomatic malaria in the school children was higher in Begoro compared to Cape Coast (27% (95% CI: 17, 24%) vs. 24% (95% CI: 17, 24%), p value = 0.04). The study recorded three species of Plasmodium (Plasmodia falciparum, malariae, and ovale) in both sites. Plasmodium falciparum was the predominant species, accounting for about 85% of infections in both study sites. The asymptomatic school children were more likely to be anaemic (OR = 2.01, p value< 0.001) and stunted in growth (OR = 1.46, p value< 0.001). Males carried more asymptomatic infection than females (OR = 1.18, p value = 0.015). School children aged 12–14 years had more asymptomatic infections than those aged 6–8 years (OR = 1.28, p value = 0.005). Conclusion: There is a considerable burden of asymptomatic malaria in the two regions of Ghana, which is associated with males, older children, anaemia, and stunted growth in children, and may have implications for malaria control and elimination strategies in Ghana.

A key drawback to monitoring the emergence and spread of antimalarial drug resistance in sub-Saharan Africa is early detection and containment. Next-generation sequencing methods offer the resolution, sensitivity, and scale required to fill this gap by surveilling for molecular markers of drug resistance. We performed targeted sequencing using molecular inversion probes to interrogate five Plasmodium falciparum genes ( pfcrt , pfmdr1 , pfdhps , pfdhfr , and pfk13 ) implicated in chloroquine, sulfadoxine-pyrimethamine (SP), and artemisinin resistance in two sites in Ghana.

High-malaria burden countries in sub-Saharan Africa are shifting from malaria control towards elimination. Hence, there is need to gain a contemporary understanding of how indoor residual spraying (IRS) with non-pyrethroid insecticides when combined with long-lasting insecticidal nets (LLINs) impregnated with pyrethroid insecticides, contribute to the efforts of National Malaria Control Programmes to interrupt transmission and reduce the reservoir of Plasmodium falciparum infections across all ages. Using an interrupted time-series study design, four age-stratified malariometric surveys, each of ~2,000 participants, were undertaken pre- and post-IRS in Bongo District, Ghana. Following the application of three-rounds of IRS, P. falciparum transmission intensity declined, as measured by a >90% reduction in the monthly entomological inoculation rate. This decline was accompanied by reductions in parasitological parameters, with participants of all ages being significantly less likely to harbor P. falciparum infections at the end of the wet season post-IRS (aOR = 0.22 [95% CI: 0.19–0.26], p-value < 0.001). In addition, multiplicity of infection (MOI_var) was measured using a parasite fingerprinting tool, designed to capture within-host genome diversity. At the end of the wet season post-IRS, the prevalence of multi-genome infections declined from 75.6% to 54.1%. This study demonstrates that in areas characterized by high seasonal malaria transmission, IRS in combination with LLINs can significantly reduce the reservoir of P. falciparum infection. Nonetheless despite this success, 41.6% of the population, especially older children and adolescents, still harboured multi-genome infections. Given the persistence of this diverse reservoir across all ages, these data highlight the importance of sustaining vector control in combination with targeted chemotherapy to move high-transmission settings towards pre-elimination. This study also points to the benefits of molecular surveillance to ensure that incremental achievements are not lost and that the goals advocated for in the WHO’s High Burden to High Impact strategy are realized.

Transmission dynamics is an important indicator for malaria control and elimination. As we move closer to eliminating malaria in Sub-Saharan Africa (sSA), transmission indices with higher resolution (genomic approaches) will complement our current measurements of transmission. Most of the present programmatic knowledge of malaria transmission patterns are derived from assessments of epidemiologic and clinical data, such as case counts, parasitological estimates of parasite prevalence, and Entomological Inoculation Rates (EIR). However, to eliminate malaria from endemic areas, we need to track changes in the parasite population and how they will impact transmission. This is made possible through the evolving field of genomics and genetics, as well as the development of tools for more in-depth studies on the diversity of parasites and the complexity of infections, among other topics. If malaria elimination is to be achieved globally, country-specific elimination activities should be supported by parasite genomic data from regularly collected blood samples for diagnosis, surveillance and possibly from other programmatic interventions. This presents a unique opportunity to track the spread of malaria parasites and shed additional light on intervention efficacy. In this review, various genetic techniques are highlighted along with their significance for an enhanced understanding of transmission patterns in distinct topological settings throughout Sub-Saharan Africa. The importance of these methods and their limitations in malaria surveillance to guide control and elimination strategies, are explored.