Přehled

Title: Methodological and Empirical Strategies for LAG3-Targeted Immunotherapy in Oncology
Study program: Biomedical Technology and Bioinformatics
Supervisor: Sudeep Roy, PhD

Topic description:

Lymphocyte Activation Gene-3 (LAG3; CD223) represents a promising target for cancer immunotherapy, given its function as a negative regulator of T cells and its ability, when paired with PD1, to induce a state of exhaustion. The impetus for investigating LAG-3 as a protein target in cancer immunotherapy arises from its significant function in immune regulation, its synergistic interactions with other immune checkpoints, and its binding affinity to various ligands, including MHC Class II, FGL1, Galectin-3, and LSECtin. The advancement of LAG-3 targeted immunotherapies in oncology depends on both computational and experimental methodologies to discern, refine, and authenticate potential therapeutic candidates. Investigations into the structural dynamics of LAG-3 interactions with its ligands, including MHC class II and FGL1, have elucidated the mechanisms underlying binding processes. These investigations inform the systematic development of small molecules or antibodies that interfere with these interactions. The processes of pre-clinical validation, structural validation, and approaches centered on combination therapies facilitate the development of more effective treatments customized to the unique profiles of individual patients.

The applicant possesses an extensive background of collaboration with various national medical institutions, such as Mendel University, FNUSA, and ICRC Brno. Furthermore, he is collaborating with international partners located in Germany, the United Kingdom, and India, each of whom possesses specialized expertise and will contribute to different phases of the project’s execution.

Your task:

  • To undertake original research by planning and carrying out a research project that adds to existing knowledge in one’s subject, with the end result being a dissertation or thesis.
  • To become an expert independent researcher by developing advanced research abilities in specialised techniques, data analysis, and project management.
  • To communicate discoveries through engaging with the academic community, presenting at conferences, and publishing research articles in peer-reviewed publications.
  • Learn more about the field and get better at what you do while also getting experience in areas like leadership, mentoring, and teaching.
  • Through networking and the acquisition of appropriate skills, establish a professional profile that is in line with aspirations for a career in academia, industry, or another field.

Requirements:

  • Strong educational background in chemistry, bioinformatics, computer science, mathematics, physics, or biochemistry is required.
  • A Master’s degree in a relevant field is frequently necessary, along with training or experience in cheminformatics, computational chemistry, or molecular modelling.
  • Expertise in programming languages like Python.
  • Proficiency in cheminformatics tools and methodologies, including molecular docking, pharmacophore modelling, machine learning, and data analysis. Expertise in computational drug design, database management, and statistical analysis for pharmaceutical applications.
  • Demonstrates effective written and verbal communication abilities for publishing research findings and working in multidisciplinary teams.

We offer:

  • • HPC Clusters: Essential for large-scale chemical simulations, virtual screening, and machine learning applications (GPU-accelerated servers with NVIDIA GPUs).
  • • Modelling and Docking Software:
    • Molecular Operating Environment (MOE): Provides tools for docking, pharmacophore
      modelling, QSAR research, and structural optimisation.
    • AutoDock is an open-source docking software employed for virtual screening of small
      compounds against protein targets.
    • Glide (docking), Maestro (visualisation), and Desmond (molecular dynamics) comprise
      the Schrödinger Suite, a proprietary drug discovery platform.
    • PyMOL: Protein-ligand interaction visualisation.
  • Engaged in interdisciplinary collaborations across biology, pharmacology, and computer
    science.

Contact: Sudeep Roy – roy@vut.cz

Relevant publications:

How to apply:

Please apply and submit your motivation letter and CV via university website from April 1 to April 30, https://www.vut.cz/eprihlaska/cs/zadani/vybrat-obor/fakulta/5

Funding:
Funding is provided as a combination of part-time or full-time research projects and/or regular scholarships.