Laboratory of Modeling of Cellular Processes
Team leader: dr hab. Dorota Latek
Team leader’s e-mail address: dlatek@chem.uw.edu.pl
Brief description of the research topic:
The research team has identified several cutting-edge areas of focus that align with modern scientific challenges and opportunities. These include machine learning and artificial intelligence, particularly in the context of web applications to enhance biochemical data processing and predictive analytics. By leveraging ML algorithms and cloud-based platforms, the team enhances the accessibility and scalability of various cheminformatic tools. These innovations not only facilitate the design of new drug candidates but also allow for rapid iteration and refinement of molecular models of protein drug targets. The synergy between computational frameworks and web technologies ensures that the vast amount of data generated can be efficiently shared and analyzed, accelerating advancements in medical science. Additionally, developed databases with protein structures and cheminformatic data play a key role in advancing drug discovery and design, with a particular interest in targeting G protein-coupled receptors (GPCRs). The team aims to unravel the mechanisms of GPCR receptor activation, detect important activation macro- and microswitches to better understand biased signaling and interactions with effector proteins. This research has implications for anti-cancer and anti-viral drug development, as well as treatments for chronic and acute inflammation. Additional areas of interest include endocrinology and metabolism, with a focus on diabetes type 2, and immune system dynamics, immune receptors, chemotactic receptors, and the complement system. Efforts are directed at addressing challenges in transplantation and allograft rejection, aiming to develop advanced anti-inflammatory therapies. The comprehensive interdisciplinary approach ensures that these topics are at the forefront of innovation, fostering collaborations across multiple domains to achieve impactful outcomes. To complement its computational and theoretical approaches, the research team emphasizes the importance of experimental validation in drug design. Functional assays, binding assays, and other in-vitro methodologies are applied in collaboration with other research groups to confirm hypotheses derived from biochemical and pharmacological data analytics. These assays are pivotal for verifying the activity of designed molecules, assessing their interactions with GPCR receptors, and optimizing drug candidates. Through rigorous experimental frameworks, the team joins computational predictions and real-world applications, ensuring that drug design translates into effective medical solutions.