The C-kit gene is located on human chromosome 4q12-13 and belongs to the type III receptor tyrosine kinase family members encoded by the proto-oncogene C-kit. The kit protein encoded by the C-kit gene is composed of an intracellular tyrosine kinase domain, a transmembrane domain and an extracellular domain with a ligand binding site. After binding to its ligand, it can activate its own tyrosine protease activity. A series of responses activate downstream signal transduction pathways, thereby regulating cell growth and proliferation. After the KIT receptor binds to the ligand SCF (stem cell factor), it forms a dimer and activates downstream signals, including Ras, Raf, MAPK pathways, etc., and finally activates transcription factors in cells, thereby regulating gene expression, controlling cell growth and proliferation. As a receptor of stem cell factors, C-KIT can participate in the regulation of hematopoietic stem cell proliferation and differentiation through a series of signaling pathways. Recent studies have found that mutations in c-kit gene, especially activating mutations, are closely related to the pathogenesis, treatment and prognosis of acute leukemia. In addition, the study found that the mutation rate of c-kit gene in gastrointestinal stromal tumors (GIST) is about 90%, and the mutation forms are diverse. As a result, the activation of Kit protein does not require the participation of ligand SCF to stimulate the continuous proliferation of tumor cells and the uncontrolled anti-apoptotic signal. Choosing C-KIT as a drug for tumor treatment is a good choice. CD ComputaBio provides C-KIT targeting services to customers to accelerate their research progress.

Figure 1. Mast cell c-KIT (CD117) receptor structure. (Jeffrey A Gilreath, et al.; 2019)

Our Services

We provide professional services in computer-aided drug design.

In the early stages of drug development, guesswork in drug discovery can be expensive and time-consuming. Our team is here to avoid it for you. With our services, your team will get:

• Significantly enhanced visualization of new binding sites for proteins developed for new drug development.
• Use professional computational physics-based algorithms to map proteins at an unprecedented level of detail.
• Well-designed small molecules optimized for affinity, specificity, and drug-like properties.
• Maximize atomic interactions between ligands and targets, using our specialized drug design platform to reveal where changes can be made to enhance drug-like properties without sacrificing affinity or specificity.
• Facilitate formulation of biologics through comprehensive excipient and protein-protein interaction profiling.

Why work with us?

• CD ComputaBio can accurately and efficiently discover and confirm drug targets through bioinformatics software, support vector machine algorithm and reverse molecular docking technology;
• We can combine structure-based drug design and ligand-based drug design (pharmacophore model construction, quantitative structure-activity relationship analysis and high-throughput virtual screening) methods to efficiently discover and optimize lead compounds;
• We can also use computer software (such as TIMES, METEOR, ADMET Predictor) to assist in the study of the laws of final drug absorption (A), distribution (D), metabolism (M) and excretion (E) in the body, so as to exclude the candidate of drug-free prospects. The drugs are excluded from research at an early stage, thereby reducing R&D costs and improving R&D efficiency.

Our Capabilities

In each therapeutic area, CD ComputaBio has accumulated deep expertise in discovery informatics, computational chemistry/molecular modeling, medicinal chemistry, structural biology, in vivo andin vitro pharmacology, and translational science. During the drug discovery process, our team focuses on early lead compounds in different target classes and uses a wide range of techniques, including molecular screening, molecular modeling, medicinal chemistry, structural biology, bioinformatics and computational chemistry, to identify new target the direction of drug development, and then select suitable drug candidates through low-cost, high-efficiency computer simulations to ensure high efficiency and low risk in the later drug development process. Our computational biology team has extensive experience in the research of C-KIT targets. Please consult our professional team for details.

References

1. Shah YM, et al.; c-Kit as a Novel Potential Therapeutic Target in Colorectal Cancer. Gastroenterology. 2015,149(3):534-7.
2. Andre C, et al.; Sequence analysis of two genomic regions containing the KIT and the FMS receptor tyrosine kinase genes". Genomics. 1997, 39 (2): 216–26.
3. Jean-Loup Huret. "KIT". Atlas of Genetics and Cytogenetics in Oncology and Haematology. Retrieved 2008-03-01.
4. Jeffrey A Gilreath, et al.; Novel approaches to treating advanced systemic mastocytosis. Clinical Pharmacology: Advances and Applications. 2019, Volume 11:77-92.