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Exploring Protein-Protein Interactions as Drug Targets for Anti-cancer Therapy with In Silico Workflows.

ABSTRACT: We describe a computational protocol to aid the design of small molecule and peptide drugs that target protein-protein interactions, particularly for anti-cancer therapy. To achieve this goal, we explore multiple strategies, including finding binding hot spots, incorporating chemical similarity and bioactivity data, and sampling similar binding sites from homologous protein complexes. We demonstrate how to combine existing interdisciplinary resources with examples of semi-automated workflows. Finally, we discuss several major problems, including the occurrence of drug-resistant mutations, drug promiscuity, and the design of dual-effect inhibitors.

SUBMITTER: Goncearenco A

PROVIDER: S-EPMC5880202 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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Exploring Protein-Protein Interactions as Drug Targets for Anti-cancer Therapy with In Silico Workflows.

Goncearenco Alexander A Li Minghui M Simonetti Franco L FL Shoemaker Benjamin A BA Panchenko Anna R AR

Methods in molecular biology (Clifton, N.J.) 20170101

We describe a computational protocol to aid the design of small molecule and peptide drugs that target protein-protein interactions, particularly for anti-cancer therapy. To achieve this goal, we explore multiple strategies, including finding binding hot spots, incorporating chemical similarity and bioactivity data, and sampling similar binding sites from homologous protein complexes. We demonstrate how to combine existing interdisciplinary resources with examples of semi-automated workflows. Fi ...[more]

PMID: 28809006

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Project description:As hematopoietic progenitors supply a large number of blood cells, therapeutic strategies targeting hematopoietic progenitors are potentially beneficial to eliminate unwanted blood cells, such as leukemic cells and immune cells causing diseases. However, due to their pluripotency, targeting those cells may impair the production of multiple cell lineages, leading to serious side effects such as anemia and increased susceptibility to infection. To minimize those side effects, it is important to identify monopotent progenitors that give rise to a particular cell lineage. Monocytes and monocyte-derived macrophages play important roles in the development of inflammatory diseases and tumors. Recently, we identified human monocyte-restricted progenitors, namely, common monocyte progenitors and pre-monocytes, both of which express high levels of CD64, a well-known monocyte marker. Here, we introduce a dimeric pyrrolobenzodiazepine (dPBD)-conjugated anti-CD64 antibody (anti-CD64-dPBD) that selectively induces the apoptosis of proliferating human monocyte-restricted progenitors but not non-proliferating mature monocytes. Treatment with anti-CD64-dPBD did not affect other types of hematopoietic cells including hematopoietic stem and progenitor cells, neutrophils, lymphocytes and platelets, suggesting that its off-target effects are negligible. In line with these findings, treatment with anti-CD64-dPBD directly killed proliferating monocytic leukemia cells and prevented monocytic leukemia cell generation from bone marrow progenitors of chronic myelomonocytic leukemia patients in a patient-derived xenograft model. Furthermore, by depleting the source of monocytes, treatment with anti-CD64-dPBD ultimately eliminated tumor-associated macrophages and significantly reduced tumor size in humanized mice bearing solid tumors. Given the selective action of anti-CD64-dPBD on proliferating monocyte progenitors and monocytic leukemia cells, it should be a promising tool to target cancers and other monocyte-related inflammatory disorders with minimal side effects on other cell lineages.

Dataset Information

Exploring Protein-Protein Interactions as Drug Targets for Anti-cancer Therapy with In Silico Workflows.

Publications

Exploring Protein-Protein Interactions as Drug Targets for Anti-cancer Therapy with In Silico Workflows.

Similar Datasets

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