Using Yeast Synthetic Lethality To Inform Drug Combination for Malaria

Computational methods, databases and tools for synthetic lethality prediction

Synthetic lethality (SL) occurs between two genes when the inactivation of either gene alone has no effect on cell survival but the inactivation of both genes results in cell death. SL-based therapy has become one of the most promising targeted cancer therapies in the last decade as PARP inhibitors achieve great success in the clinic. The key point to exploiting SL-based cancer therapy is the identification of robust SL pairs. Although many wet-lab-based methods have been developed to screen SL pairs, known SL pairs are less than 0.1% of all potential pairs due to large number of human gene combinations. Computational prediction methods complement wet-lab-based methods to effectively reduce the search space of SL pairs. In this paper, we review the recent applications of computational methods and commonly used databases for SL prediction. First, we introduce the concept of SL and its screening methods. Second, various SL-related data resources are summarized. Then, computational methods including statistical-based methods, network-based methods, classical machine learning methods and deep learning methods for SL prediction are summarized. In particular, we elaborate on the negative sampling methods applied in these models. Next, representative tools for SL prediction are introduced. Finally, the challenges and future work for SL prediction are discussed.

The emerging paradigm of calcium homeostasis as a new therapeutic target for protozoan parasites

Calcium channels (CCs), a group of ubiquitously expressed membrane proteins, are involved in many pathophysiological processes of protozoan parasites. Our understanding of CCs in cell signaling, organelle function, cellular homeostasis, and cell cycle control has led to improved insights into their structure and functions. In this article, we discuss CCs characteristics of five major protozoan parasites Plasmodium, Leishmania, Toxoplasma, Trypanosoma, and Cryptosporidium. We provide a comprehensive review of current antiparasitic drugs and the potential of using CCs as new therapeutic targets. Interestingly, previous studies have demonstrated that human CC modulators can kill or sensitize parasites to antiparasitic drugs. Still, none of the parasite CCs, pumps, or transporters has been validated as drug targets. Information for this review draws from extensive data mining of genome sequences, chemical library screenings, and drug design studies. Parasitic resistance to currently approved therapeutics is a serious and emerging threat to both disease control and management efforts. In this article, we suggest that the disruption of calcium homeostasis may be an effective approach to develop new anti-parasite drug candidates and reduce parasite resistance.