In silico frameworks for systematic pre-clinical screening of potential anti-leukemia therapeutics

ABSTRACT

Introduction: Leukemia is a collection of highly heterogeneous cancers that arise from neoplastic transformation and clonal expansion of immature hematopoietic cells. Post-treatment recurrence is high, especially among elderly patients, thus necessitating more effective treatment modalities. Development of novel anti-leukemic compounds relies heavily on traditional in vitro screens which require extensive resources and time. Therefore, integration of in silico screens prior to experimental validation can improve the efficiency of pre-clinical drug development.

Areas covered: This article reviews different methods and frameworks used to computationally screen for anti-leukemic agents. In particular, three approaches are discussed including molecular docking, transcriptomic integration, and network analysis.

Expert opinion: Today’s data deluge presents novel opportunities to develop computational tools and pipelines to screen for likely therapeutic candidates in the treatment of leukemia. Formal integration of these methodologies can accelerate and improve the efficiency of modern day anti-leukemic drug discovery and ease the economic and healthcare burden associated with it.

KEYWORDS:

• Computational drug repositioning
• molecular docking
• transcription profiling
• network analysis
• leukemia

Article highlights

• Molecular docking, transcriptomic profiling, and network analysis have been applied to computationally screen for novel anti-leukemia drugs.

• Molecular docking studies allow researchers to screen through millions of small-molecules given that a drug target is known.

• Transcriptomic profiling compares drug treatment gene expression profiles with disease profiles to identify novel candidates without requiring knowledge of the drug targets.

• Network analysis of somatic and germline variants in leukemia can identify novel drug targets

• Integration of these approaches into drug discovery pipelines can increase the efficiency of the drug screening process

This box summarizes key points contained in the article.

Declaration of interest

The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.

Additional information

Funding

This work was supported by American Cancer Society research grant #IRG-82-003-30, the National Center for Advancing Translational Sciences of the National Institutes of Health under Award Number KL2TR001088, the start-up funding package provided to C Cheng by the Geisel School of Medicine from Dartmouth College and the Rosaline Borison Memorial Pre-doctoral fellowship provided to MH Ung.