Artificial Intelligence Assisted Pharmacophore Design for Philadelphia Chromosome-Positive Leukemia with Gamma-Tocotrienol: A Toxicity Comparison Approach with Asciminib

by Selleckchem | Aug 11 2023

BCR-ABL1 is a fusion protein as a result of a unique chromosomal translocation (producing the so-called Philadelphia chromosome) that serves as a clinical biomarker primarily for chronic myeloid leukemia (CML); the Philadelphia chromosome also occurs, albeit rather rarely, in other types of leukemia. This fusion protein has proven itself to be a promising therapeutic target. Exploiting the natural vitamin E molecule gamma-tocotrienol as a BCR-ABL1 inhibitor with deep learning artificial intelligence (AI) drug design, this study aims to overcome the present toxicity that embodies the currently provided medications for (Ph+) leukemia, especially asciminib. Gamma-tocotrienol was employed in an AI server for drug design to construct three effective de novo drug compounds for the BCR-ABL1 fusion protein. The AIGT's (Artificial Intelligence Gamma-Tocotrienol) drug-likeliness analysis among the three led to its nomination as a target possibility. The toxicity assessment research comparing AIGT and asciminib demonstrates that AIGT, in addition to being more effective nonetheless, is also hepatoprotective. While almost all CML patients can achieve remission with tyrosine kinase inhibitors (such as asciminib), they are not cured in the strict sense. Hence it is important to develop new avenues to treat CML. We present in this study new formulations of AIGT. The docking of the AIGT with BCR-ABL1 exhibited a binding affinity of -7.486 kcal/mol, highlighting the AIGT's feasibility as a pharmaceutical option. Since current medical care only exclusively cures a small number of patients of CML with utter toxicity as a pressing consequence, a new possibility to tackle adverse instances is therefore presented in this study by new formulations of natural compounds of vitamin E, gamma-tocotrienol, thoroughly designed by AI. Even though AI-designed AIGT is effective and adequately safe as computed, in vivo testing is mandatory for the verification of the in vitro results.

Comments:

It appears that you have provided a summary of a study that proposes the use of gamma-tocotrienol, a natural compound of vitamin E, as a potential therapeutic option for chronic myeloid leukemia (CML) targeting the BCR-ABL1 fusion protein. The study utilizes deep learning artificial intelligence (AI) drug design to construct three de novo drug compounds and evaluates their effectiveness and toxicity compared to the existing medication asciminib.

According to the study, the AI-designed gamma-tocotrienol compound (referred to as AIGT) showed promising results as a BCR-ABL1 inhibitor. The drug-likeliness analysis conducted by the AI server suggested that AIGT has potential as a therapeutic option. Furthermore, the study claims that AIGT exhibited better efficacy and hepatoprotective properties compared to asciminib in toxicity assessments.

While tyrosine kinase inhibitors, like asciminib, can induce remission in most CML patients, they do not offer a cure. Therefore, the study highlights the need for new treatment avenues for CML. The proposed formulations of AIGT are expected to address the limitations of current medications and provide a potential alternative with reduced toxicity.

The docking analysis of AIGT with the BCR-ABL1 fusion protein demonstrated a binding affinity, further supporting its feasibility as a pharmaceutical option. However, the study emphasizes the importance of conducting in vivo testing to verify the in vitro results and assess the efficacy and safety of AIGT.

It's worth noting that as an AI language model, I don't have access to the specific details or results of the study you mentioned since it seems to be a hypothetical scenario you presented. Therefore, I cannot provide further insights into the specific findings, as they may not exist in the current body of scientific literature up until my knowledge cutoff in September 2021. It's essential to consult scientific publications or researchers in the field for the most up-to-date and accurate information on this topic.