Therapeutic Targeting a Non-Hodgkin Lymphoma Driver Using AI

使用人工智能治疗非霍奇金淋巴瘤司机 项目总结 贝勒医学院(BCM)和ATOM公司在发现、优化和测试方面进行了合作 使用人工智能(AI)抑制无法下药的癌蛋白。霍奇金淋巴瘤和非霍奇金淋巴瘤 霍奇金淋巴瘤(NHL)是一种始于淋巴细胞的癌症，淋巴细胞是人体免疫系统的一部分。 霍奇金淋巴瘤和非霍奇金淋巴瘤的主要区别在于各自涉及的特定淋巴细胞： 如果存在称为Reed-Sternberg细胞的异常细胞，则将其归类为霍奇金淋巴瘤；否则， 被归类为NHL。非霍奇金淋巴瘤是最常见的血癌，每年导致超过2万人死亡。 美国。大约有90种类型的非霍奇金淋巴瘤，通常发生在 淋巴细胞。MYD88基因编码髓系分化初级反应88蛋白，这是一种关键的通用蛋白 在炎症和免疫方面具有基本功能的适配器。在刺激Toll样受体之后， MyD88传递信号以激活负责先天性和获得性免疫反应的基因。 MyD88是一种在B细胞非霍奇金淋巴瘤中频繁突变的致癌基因。最常见的误解 突变为L265P，它将265位的亮氨酸改变为脯氨酸，约占所有MYD88的90% 突变。MyD88 L265P存在于~90%的Waldenström巨球蛋白血症(WM，一种罕见的非霍奇金淋巴瘤)中，&GT；50% 原发性结外淋巴瘤，约29%的活化B细胞弥漫性大B细胞淋巴瘤(DLBCL)。WM是 被认为是不治之症。约40%的DLBCL患者可以治愈，但携带MYD88 L265P的患者有 比那些没有的人存活得更差。BCM与第一个深度学习人工智能的发明者原子合作 基于神经网络的技术和人工智能辅助药物发现的领先者，虚拟筛选270万 化合物。我们鉴定了数十个针对MYD88中L265P附近结合位点的人工智能选择的化合物。我们 通过评估它们对MYD88 L265P泛素化和异种移植瘤形成的抑制作用来验证这些HITS。 一种化合物能抑制MYD88 L265P诱导的NHL细胞淋巴瘤生长，但不能抑制WT MYD88诱导的NHL细胞淋巴瘤生长。 我们假设，MYD88 L265P等接头癌蛋白可以成为人工智能的靶点。在这 应用，我们提出了两个特定的目标来开发针对NHL的MYD88 L265P候选药物 心理治疗。在目标1中，我们将使用人工智能来虚拟筛选数十亿种化合物来发现新的候选药物 以MYD88中L265P附近的结合位点为靶点。在目标2中，我们将优化经过验证的Hit化合物的目标 MyD88 L265P。这一伙伴关系产生的数据将为治疗提供坚实的科学平台 针对致癌基因MYD88 L265P的开发，同时保留WT MYD88，这对先天的 和适应性免疫。这项工作解决了未满足的临床需求，直接针对MYD88 L265P和 针对突变特定驱动因素推进药物开发。

Therapeutic Targeting a Non-Hodgkin Lymphoma Driver using AI PROJECT SUMMARY Baylor College of Medicine (BCM) and Atomwise Incorporation have partnered to discover, optimize, and test inhibitors to undruggable oncoproteins using artificial intelligence (AI). Both Hodgkin lymphoma and non- Hodgkin lymphoma (NHL) are cancers that start in lymphocytes, which are part of the body’s immune system. The main difference between Hodgkin lymphoma and NHL is in the specific lymphocyte each involves: in the presence of abnormal cells called Reed-Sternberg cells, the lymphoma is classified as Hodgkin’s; otherwise, it is classified as NHL. NHL is the most common blood cancer and causes over 20,000 deaths every year in the United States. There are about 90 types of NHL, which usually develop when mutations occur within a lymphocyte. The gene MYD88 encodes myeloid differentiation primary response 88 protein, a critical universal adapter with essential functions in inflammation and immunity. Following stimulation of toll-like receptors, MYD88 transduces the signal to activate genes responsible for innate and adaptive immune responses. MYD88 is a driver oncogene that is frequently mutated in B-cell NHLs. The most frequent missense mutation is L265P, which changes leucine at position 265 to proline and accounts for ~90% of all MYD88 mutations. MYD88 L265P is found in ~90% of Waldenström macroglobulinemia (WM, a rare NHL), >50% of primary extranodal lymphomas, and ~29% of activated B-cell diffuse large B-cell lymphomas (DLBCL). WM is considered incurable. DLBCL can be cured in about 40% of the patients, but those with MYD88 L265P have poorer survival than those without. BCM collaborates with Atomwise, the inventor of the first deep learning AI technology based on neural networks and a leader in AI-assisted drug discovery, to virtually screen 2.7 million compounds. We identified scores of AI-selected compounds targeting a binding site near L265P in MYD88. We validated these hits by evaluating their inhibition of MYD88 L265P ubiquitination and xenograft tumorigenesis. One compound attenuated lymphoma growth from NHL cells with MYD88 L265P, but not that with WT MYD88. We hypothesize that adaptor oncoproteins such as MYD88 L265P can be targeted by AI. In this application, we propose two specific aims to develop drug candidates that target MYD88 L265P for NHL therapy. In Aim 1, we will use AI to virtually screen billions of compounds to discover novel drug candidates targeting a binding site near L265P in MYD88. In Aim 2, we will optimize validated hit compounds targeting MYD88 L265P. Data generated from this partnership will provide a solid scientific platform for therapeutic development targeting the oncogenic MYD88 L265P while sparing WT MYD88, which is critical for both innate and adaptive immunity. This work addresses the unmet clinical need to target MYD88 L265P directly and advances drug development against mutation-specific drivers.