No abstract

The use of kinase-directed precision medicine has been heavily pursued since the discovery and development of imatinib. Annually, it is estimated that around ∼20 000 new cases of tropomyosin receptor kinase (TRK) cancers are diagnosed, with the majority of cases exhibiting a TRK genomic rearrangement. In this Perspective, we discuss current development and clinical applications for TRK precision medicine by providing the following: (1) the biological background and significance of the TRK kinase family, (2) a compilation of known TRK inhibitors and analysis of their cocrystal structures, (3) an overview of TRK clinical trials, and (4) future perspectives for drug discovery and development of TRK inhibitors.

The COVID-19 pandemic has overwhelmed the existing healthcare infrastructure in many parts of the world. Healthcare professionals are not only over-burdened but also at a high risk of nosocomial transmission from COVID-19 patients. Screening and monitoring the health of a large number of susceptible or infected individuals is a challenging task. Although professional medical attention and hospitalization are necessary for high-risk COVID-19 patients, home isolation is an effective strategy for low and medium risk patients as well as for those who are at risk of infection and have been quarantined. However, this necessitates effective techniques for remotely monitoring the patients’ symptoms. Recent advances in Machine Learning (ML) and Deep Learning (DL) have strengthened the power of imaging techniques and can be used to remotely perform several tasks that previously required the physical presence of a medical professional. In this work, we study the prospects of vital signs monitoring for COVID-19 infected as well as quarantined individuals by using DL and image/signal-processing techniques, many of which can be deployed using simple cameras and sensors available on a smartphone or a personal computer, without the need of specialized equipment. We demonstrate the potential of ML-enabled workflows for several vital signs such as heart and respiratory rates, cough, blood pressure, and oxygen saturation. We also discuss the challenges involved in implementing ML-enabled techniques.

Rearranged during transfection (RET) is a receptor tyrosine kinase essential for the normal development and maturation of a diverse range of tissues. Aberrant RET signaling in cancers, due to RET mutations, gene fusions, and overexpression, results in the activation of downstream pathways promoting survival, growth, and metastasis. Pharmacological manipulation of RET is effective in treating RET-driven cancers, and efforts toward developing RET-specific therapies have increased over the last 5 years. In 2020, RET-selective inhibitors pralsetinib and selpercatinib achieved clinical approval, which marked the first approvals for kinase inhibitors specifically developed to target the RET oncoprotein. This Perspective discusses current development and clinical applications for RET precision medicine by providing an overview of the incremental improvement of kinase inhibitors for use in RET-driven malignancies.

Chirality is important in drug discovery because stereoselective drugs can ameliorate therapeutic difficulties including adverse toxicity and poor pharmacokinetic profiles. The human kinome, a major druggable enzyme class has been exploited to treat a wide range of diseases. However, many kinase inhibitors are planar and overlap in chemical space, which leads to selectivity and toxicity issues. By exploring chirality within the kinome, a new iteration of kinase inhibitors is being developed to better utilize the three-dimensional nature of the kinase active site. Exploration into novel chemical space, in turn, will also improve drug solubility and pharmacokinetic profiles. This perspective explores the role of chirality to improve kinome druggability and will serve as a resource for pioneering kinase inhibitor development to address current therapeutic needs.