Publications by authors named "Wresti L Anggayasti"

Cancer research is increasingly focused on discovering strategies to induce cancer cell apoptosis without affecting surrounding normal cells. One potential biocompatible method is mechanical vibration, which has been developed as part of the emerging field of mechanomedicine. Previous studies of mechanical vibration have employed high-frequency vibration, which damages healthy cells.

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High mobility group box 1 (HMGB1) is a damage-associated molecular pattern (DAMP) molecule that triggers the progression of several pro-inflammatory diseases such as diabetes, Alzheimer's disease and cancer, by inducing signals upon interaction with the receptors such as the receptor for advanced glycation end-products (RAGE) and toll-like receptors (TLRs). The acidic C-terminal tail of HMGB1 is an intrinsically disordered region of the protein which is known to determine the interaction of HMGB1 to DNA and histones. This study characterizes its structural properties using a combination of circular dichroism (CD) and molecular dynamics (MD) simulations.

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High mobility group box 1 (HMGB1), a chromatin protein, interacts with DNA and controls gene expression. However, when HMGB1 is released from apoptotic or damaged cells, it triggers proinflammatory reactions by interacting with various receptors, mainly receptor for advanced glycation end-products (RAGE) and toll-like receptors (TLRs). The self-association of HMGB1 has been found to be crucial for its DNA-related biological functions.

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HMGB1 triggers proinflammatory reactions by interacting extracellularly with various receptors. HMGB1 also acts in the nucleus by interacting with DNA and controlling DNA transcription, a process which involves its self-association. The self-association of HMGB1 was characterized using surface plasmon resonance (SPR).

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Surface plasmon resonance (SPR) is a powerful technique for evaluating protein-protein interactions in real time. However, inappropriately optimized experiments can often lead to problems in the interpretation of data, leading to unreliable kinetic constants and binding models. Optimization of SPR experiments involving "sticky" proteins, or proteins that tend to aggregate, represents a typical scenario where it is important to minimize errors in the data and the kinetic analysis of those data.

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