Computationally designed recombinant-DNA-based compounds production driven in plants during secondary metabolism and their implication in antimalarial therapies

Abstract

Well-established and newly developed genome technologies are revolutionising the field of biomedicine, by providing genomic data and genetic engineered structures that support investigating individual propensity for developing certain diseases, on one hand, and by predicting individual responses to the environmental stimulus due to gene common variants. Indeed, the former has provided innovative ways of combining genotype-phenotype-based therapies for a wide range of diseases, including malaria and its side effects. Ultimately, computationally guided gene modifications via in silico design of plasmids have contributed with the optimal production of recombinant DNA, benefiting from useful species variant traits. On the other hand, natural or semisynthetic plant secondary metabolites-derived compounds have been used in diseases' therapies, particularly treating infectious diseases as malaria. In recent years, major efforts have been made to reduce the burden of infectious diseases worldwide, especially in the developing world. In this context, malaria prevention and treatment have stimulated collective measures, which are widely reported by the World Health Organization (WHO). Therefore, aiming at addressing the latest advances in the field, in this chapter, the relevance of pharmacogenomics and computational design in drug discovery, including information on the benefits of using plants secondary metabolites for the production of anti-malarial compounds, are presented. Moreover, given the plethora of prospective side effects resulting from this burden of disease, including neurocognitive impairment in patients affected by cerebral Plasmodium falciparum infection, a set of key elements in patient-response-based drug screening is discussed, in the context of stem cells technology. All together, we anticipate the above mentioned new technologies to be the precursors of short-term novelty in computationally designed gene-personalised healthcare, bringing about significant improvement in the current malarial therapies.