Biomedical subjects

Lydia E Kavraki

Publications and source records attributed to Lydia E Kavraki.

3 recordsLinked to original sources

PubMed2026

FOXM1-Specific TCR-Engineered T Cells Target Non-Small Cell Lung Cancer.

FOXM1 is highly expressed in various cancer types and considered a key driver of cancer progression. Accordingly, we evaluated the immunogenicity of FOXM1 and investigated the feasibility of targeting this transcription factor using T-cell receptor (TCR) engineering. We identified epitopes derived from FOXM1 which were immunogenic on HLA-A*02:01, HLA-A*24:02, and HLA-A*23:01, endogenously processed and presented, and resulted in T-cell activation and cytotoxic T-cell responses. Following the generation of TCR-T cells, sensitivity and specificity were confirmed by peptide dose-response and X-scan, respectively. Most importantly, adoptive transfer of TCR-engineered T cells led to a significant reduction in tumor growth, as well as significantly prolonged survival in a tumor-bearing immunocompromised murine model. Our studies confirm the immunogenicity of FOXM1 and feasibility of targeting this antigen using TCR engineering.

Forkhead Box Protein M1↗

PubMed2003

Understanding protein flexibility through dimensionality reduction.

This work shows how to decrease the complexity of modeling flexibility in proteins by reducing the number of dimensions necessary to model important macromolecular motions such as the induced-fit process. Induced fit occurs during the binding of a protein to other proteins, nucleic acids, or small molecules (ligands) and is a critical part of protein function. It is now widely accepted that conformational changes of proteins can affect their ability to bind other molecules and that any progress in modeling protein motion and flexibility will contribute to the understanding of key biological functions. However, modeling protein flexibility has proven a very difficult task. Experimental laboratory methods, such as x-ray crystallography, produce rather limited information, while computational methods such as molecular dynamics are too slow for routine use with large systems. In this work, we show how to use the principal component analysis method, a dimensionality reduction technique, to transform the original high-dimensional representation of protein motion into a lower dimensional representation that captures the dominant modes of motions of proteins. For a medium-sized protein, this corresponds to reducing a problem with a few thousand degrees of freedom to one with less than fifty. Although there is inevitably some loss in accuracy, we show that we can obtain conformations that have been observed in laboratory experiments, starting from different initial conformations and working in a drastically reduced search space.

Aldehyde Reductase↗

PubMedDate not supplied

A new method for fast and accurate derivation of molecular conformations.

During molecular simulations, three-dimensional conformations of biomolecules are calculated from the values of their bond angles, bond lengths, and torsional angles. In this paper we study how to efficiently derive three-dimensional molecular conformations from the values of torsional angles. This case is of broad interest as torsional angles greatly affect molecular shape and are always taken into account during simulations. We first review two widely used methods for deriving molecular conformations, the simple rotations scheme and the Denavit-Hartenberg local frames method. We discuss their disadvantages which include extensive bookkeeping, accumulation of numerical errors, and redundancies in the local frames used. Then we introduce a new, fast, and accurate method called the atomgroup local frames method. This new method not only eliminates the disadvantages of earlier approaches but also provides lazy evaluation of atom positions and reduces the computational cost. Our method is especially useful in applications where many conformations are generated or updated such as in energy minimization and conformational search.

Journal Article↗