Inhibitors of protein-protein interactions

蛋白质-蛋白质相互作用的抑制剂

• 批准号: 10486806
• 负责人: Nadya Tarasova
• 金额: $ 49.37万
• 依托单位: DIVISION OF BASIC SCIENCES - NCI
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10486806
• 关键词: Affect; Amino Acid Sequence; Apoptosis; Biological Process; Biology; Blood Circulation; CCR; Cancer Model; Cells; Chemicals; Collaborations; Communicable Diseases; Cyclization; Databases; Development; Disease; Drug Targeting; Equipment and supply inventories; Erinaceidae; Generations; Goals; Growth; Human; Hydrocarbons; ITIM; Insulin-Like-Growth Factor I Receptor; Interferon Type II; Interleukin-10; KRAS2 gene; Knowledge; Lead; Libraries; Ligands; Malignant Neoplasms; Mammary Neoplasms; Membrane; Methods; Molecular Conformation; N-terminal; Oncoproteins; Pathway interactions; Penetration; Peptides; Permeability; Pharmaceutical Preparations; Phase; Phosphotransferases; Process; Prostatic Neoplasms; Protein Fragment; Proteins; Ras Inhibitor; Regulation; Research; SARS-CoV-2 spike protein; STAT1 gene; STAT3 gene; Screening procedure; Signal Transduction; Speed; Stat5 protein; Structure; T-Lymphocyte; Technology; Testing; Therapeutic; Transcriptional Activation; Tuberculosis; alpha helix; beta pleated sheet; drug discovery; high throughput screening; human disease; improved; in silico; inhibitor/antagonist; mouse model; mutant; novel; novel strategies; peptidomimetics; pre-clinical; protein protein interaction; ras Oncogene; screening; simulation; small molecule; tool; transcription factor; tumor; virtual; virtual library; virtual screening

Protein-protein interactions control practically all biological processes. Ability to manipulate these interactions is crucial for finding cures for the vast majority of human diseases. Conventional high-throughput screens for small molecule blockers of protein-protein interactions produce a disappointingly small number of lead compounds. In addition, screening procedures and subsequent structure optimization are laborious, lengthy and expensive. Meanwhile, specific folds inherent at the interfaces of the interacting proteins have been successfully mimicked for inhibition of the target interactions. Protein fragments involved in interaction can be used for inhibition of these interactions. However, peptides corresponding to fragments of protein primary structures tend to have little or no defined conformation, which results in low efficacy and poor stability in circulation. Consequently, the major effort in mimicking the interface is directed towards making the mimicking peptide or peptidomimetic as rigid as feasible. Strategies have been developed that allow simulation of reverse turns, beta-sheets and alpha-helixes. Cyclization is the most frequently used approach to affect stabilization of both beta-turns and alpha-helices. However, for inhibitors of intracellular protein-protein contacts, there remains the problem of cell permeability. Hydrocarbon-stapled alpha-helix peptidomimetics have demonstrated improved cell penetration, but this method is applicable only to helical fragments of proteins. We have recently found that membrane tethering stabilizes the structure of a peptide and converts it into a potent cell-permeable inhibitor of the corresponding protein. The approach allows for straightforward generation of potent and selective inhibitors of the target proteins. Utilizing the approach, we have developed selective inhibitors of STAT1, STAT3, STAT5 transcription factors, Hedgehog pathway, insulin-like growth factor 1 receptor, Jak1 and Jak2 kinases, interleukin 10 and interferon gamma signaling and Ras oncogenes. Inhibitors of STAT1, STAT3 and RAS oncogenes have been tested in mouse models of cancer and have demonstrated remarkable anti-tumor activity. Ras inhibitor is currently in preclinical phase of development. Lipopeptides represent a new type of potential therapeutics with a wide range of applications. Lipopeptide inhibitors are also powerful chemical biology tools. Utilization of selective inhibitors of Ras oncoproteins allowed for uncovering of two previously unknown mechanisms of regulation of the proteins that are responsible for the growth of over 30% of all human tumors. Inhibitors of STAT3 N-terminal domain were instrumental in discovering that this transcription factor is involved in activation of transcription of apoptosis-inhibiting proteins in breast and prostate tumors, but not normal cells. The studies have identified STAT3 N-terminal domain as a promising drug target not only for cancer but infectious diseases like tuberculosis. In addition, we are utilizing in silico screening of specially constructed virtual libraries of compounds for identification of potential inhibitors of protein-protein interactions. The developed technologies allowed for the discoveries of ligands for several non-druggable targets. In addition, virtual screening of super-large libraries containing billions of compounds utilizing novel computational approaches allowed for identification of ligands for several proteins widely considered non-druggable. These include mutant K-ras, STAT3 N-terminal domain, TIGIT (T cell immunoreceptor with Ig and ITIM domains) and several SARS-Cov2 proteins. The studies have shown that expanding synthetically accessible chemical space allows for successful identification of ligands even for very challenging drug targets.

蛋白质 - 蛋白质相互作用实际上控制了所有生物过程。操纵这些相互作用的能力对于寻找绝大多数人类疾病的治疗方法至关重要。用于蛋白质蛋白质相互作用的小分子阻滞剂的常规高通量筛选产生了令人失望的少量铅化合物。此外，筛选程序和随后的结构优化是费力的，冗长且昂贵的。同时，已经成功模仿了相互作用蛋白界面固有的特定折叠以抑制目标相互作用。参与相互作用的蛋白质片段可用于抑制这些相互作用。但是，与蛋白质原发性结构片段相对应的肽往往几乎没有或没有确定的构象，从而导致循环中的疗效低和稳定性较差。因此，模仿界面的主要努力是为了使模仿肽或肽类似型刚性一样刚性。已经制定了允许模拟反向转弯，β表和α-螺旋的策略。环化是影响β-转变和α-螺旋稳定的最常用方法。但是，对于细胞内蛋白质蛋白接触的抑制剂，仍然存在细胞渗透性的问题。碳氢化合物的α-螺旋肽仪显示出改善的细胞渗透率，但该方法仅适用于蛋白质的螺旋片段。我们最近发现，膜绑扎稳定肽的结构，并将其转化为相应蛋白质的有效细胞抑制剂。该方法可以直接生成目标蛋白的有效抑制剂和选择性抑制剂。利用该方法，我们开发了STAT1，STAT3，STAT5转录因子，刺猬途径，胰岛素样生长因子1受体，JAK1和JAK2激酶，Interleukin 10和Interleukin Gamma信号传导和Ras Oncogenes的选择性抑制剂。 STAT1，STAT3和RAS癌基因的抑制剂已经在癌症的小鼠模型中进行了测试，并显示出显着的抗肿瘤活性。 RAS抑制剂目前处于开发的临床前阶段。脂肽代表一种具有广泛应用的新型潜在疗法。脂肽抑制剂也是强大的化学生物学工具。利用Ras癌蛋白的选择性抑制剂，可以发现两种先前未知的调节机制，用于调节蛋白质的调节，这些机制造成了所有人类肿瘤的30％以上的生长。 STAT3 N末端结构域的抑制剂有助于发现该转录因子参与乳腺癌和前列腺肿瘤中抑制蛋白质凋亡蛋白的转录激活，而不是正常细胞。这些研究已将STAT3 N末端结构域确定为癌症的有前途的药物靶标，而且是结核病等传染病。此外，我们还利用了对化合物的特殊构造的虚拟文库的硅筛选，以鉴定蛋白质 - 蛋白质相互作用的潜在抑制剂。开发的技术允许为几个不可驱动的目标发现配体的发现。此外，利用新型计算方法的虚拟筛选含有数十亿种化合物的超大库库可以鉴定几种被广泛认为不可驱动的蛋白质的配体。这些包括突变k-ras，STAT3 N末端结构域，Tigit（具有Ig和ITIM结构域的T细胞免疫受体）和几种SARS-COV2蛋白。研究表明，扩大合成可访问的化学空间可以成功识别配体，即使对于非常具有挑战性的药物靶标也是如此。