Structure-based development of potent and selective type-II kinase inhibitors of RIPK1

Receptor-interacting serine/threonine-protein kinase 1 (RIPK1) functions as a key regulator in inflammation and cell death and is involved in mediating a variety of inflammatory or degenerative diseases. A number of allosteric RIPK1 inhibitors (RIPK1i) have been developed, and some of them have already advanced into clinical evaluation. Recently, selective RIPK1i that interact with both the allosteric pocket and the ATP-binding site of RIPK1 have started to emerge. Here, we report the rational development of a new series of type-II RIPK1i based on the rediscovery of a reported but mechanistically atypical RIPK3i. We also describe the structure-guided lead optimization of a potent, selective, and orally bioavailable RIPK1i, 62, which exhibits extraordinary efficacies in mouse models of acute or chronic inflammatory diseases. Collectively, 62 provides a useful tool for evaluating RIPK1 in animal disease models and a promising lead for further drug development.

Discovery of novel KRAS‒PDEδ inhibitors with potent activity in patient-derived human pancreatic tumor xenograft models

KRAS‒PDEδ interaction is revealed as a promising target for suppressing the function of mutant KRAS. The bottleneck in clinical development of PDEδ inhibitors is the poor antitumor activity of known chemotypes. Here, we identified novel spiro-cyclic PDEδ inhibitors with potent antitumor activity both in vitro and in vivo. In particular, compound 36l (K D = 127 ± 16 nmol/L) effectively bound to PDEδ and interfered with KRAS-PDEδ interaction. It influenced the distribution of KRAS in Mia PaCa-2 cells, downregulated the phosphorylation of t-ERK and t-AKT and promoted apoptosis of the cells. The novel inhibitor 36l exhibited significant in vivo antitumor potency in pancreatic cancer patient-derived xenograft (PDX) models. It represents a promising lead compound for investigating the druggability of KRAS‒PDEδ interaction.

Application of computational methods for anticancer drug discovery, design, and optimization / Aplicación de métodos computacionales para el descubrimiento, diseño y optimización de fármacos contra el cáncer

Abstract: Developing a novel drug is a complex, risky, expensive and time-consuming venture. It is estimated that the conventional drug discovery process ending with a new medicine ready for the market can take up to 15 years and more than a billion USD. Fortunately, this scenario has recently changed with the arrival of new approaches. Many novel technologies and methodologies have been developed to increase the efficiency of the drug discovery process, and computational methodologies have become a crucial component of many drug discovery programs. From hit identification to lead optimization, techniques such as ligand- or structure-based virtual screening are widely used in many discovery efforts. It is the case for designing potential anticancer drugs and drug candidates, where these computational approaches have had a major impact over the years and have provided fruitful insights into the field of cancer. In this paper, we review the concept of rational design presenting some of the most representative examples of molecules identified by means of it. Key principles are illustrated through case studies including specifically successful achievements in the field of anticancer drug design to demonstrate that research advances, with the aid of in silico drug design, have the potential to create novel anticancer drugs.

Resumen: El desarrollo de un nuevo fármaco es un proceso complejo y arriesgado que requiere una enorme cantidad de tiempo y dinero. Se estima que el proceso estándar para producir un nuevo fármaco, desde su descubrimiento hasta que acaba en el mercado, puede tardar hasta 15 años y tener un costo de mil millones de dólares (USD). Por fortuna, este escenario ha cambiado recientemente con la llegada de nuevas tecnologías y metodologías. Entre ellas, los métodos computacionales se han convertido en un componente determinante en muchos programas de descubrimiento de fármacos. En un esfuerzo por incrementar las posibilidades de encontrar nuevas moléculas con potencial farmacológico, se utilizan técnicas como el cribado virtual de quimiotecas construidas con base en ligandos o estructuras para la identificación de hits y hasta para la optimización de compuestos líder. En lo que respecta al diseño y descubrimiento de nuevos candidatos a fármacos contra el cáncer, estos enfoques tienen, a la fecha, un impacto importante y aportan nuevas posibilidades terapéuticas. En este artículo se revisa el concepto del diseño racional de moléculas con potencial farmacológico, ilustrando los principios clave con algunos de los ejemplos más representativos y exitosos de moléculas identificadas mediante estas aproximaciones. Se incluyen casos desarrollados en el campo del diseño de fármacos contra el cáncer con la finalidad de mostrar cómo, con la ayuda del diseño asistido por computadora, se pueden generar nuevos fármacos que den esperanza a millones de pacientes.