Laboratory of Genetics, Department of Biotechnology, School of Applied Biology and Biotechnology, Agricultural University of Athens, Athens, Greece.
University Research Institute of Maternal and Child Health & Precision Medicine, National and Kapodistrian University of Athens, Athens, Greece.
Adv Exp Med Biol. 2023;1424:231. doi: 10.1007/978-3-031-31982-2_25.
Modern anticancer research has employed advanced computational techniques and artificial intelligence methods for drug discovery and development, along with the massive amount of generated clinical and in silico data over the last decades. Diverse computational techniques and state-of-the-art algorithms are being developed to enhance traditional Rational Drug Design pipelines and achieve cost-efficient and successful anticancer candidates to promote human health. Towards this direction, we have developed a pharmacophore- based drug design approach against MCT4, a member of the monocarboxylate transporter family (MCT), which is the main carrier of lactate across the membrane and highly involved in cancer cell metabolism. Specifically, MCT4 is a promising target for therapeutic strategies as it overexpresses in glycolytic tumors, and its inhibition has shown promising anticancer effects. Due to the lack of experimentally determined structure, we have elucidated the key features of the protein through an in silico drug design strategy, including for molecular modelling, molecular dynamics, and pharmacophore elucidation, towards the identification of specific inhibitors as a novel anti-cancer strategy.
在过去几十年中，现代抗癌研究已经采用了先进的计算技术和人工智能方法来进行药物发现和开发，同时还产生了大量的临床和计算机数据。正在开发各种计算技术和最先进的算法，以增强传统的合理药物设计管道，并实现具有成本效益和成功的抗癌候选药物，以促进人类健康。为此，我们开发了一种基于药效团的药物设计方法来对抗 MCT4，MCT4 是单羧酸转运蛋白家族（MCT）的成员，是乳酸穿过膜的主要载体，并且高度参与癌细胞代谢。具体来说，MCT4 是治疗策略的一个有前途的靶点，因为它在糖酵解肿瘤中过度表达，其抑制作用已显示出有希望的抗癌作用。由于缺乏实验确定的结构，我们通过计算机药物设计策略阐明了该蛋白质的关键特征，包括分子建模、分子动力学和药效团阐明，以确定特定抑制剂作为一种新的抗癌策略。
