Protein-protein interactions (PPIs) play crucial roles in many biological processes, such as viral self-assembly, cell proliferation, growth, differentiation, signal transduction, and programmed cell death. Therefore, PPIs have been regarded as promising drug targets with broad-spectrum therapeutic implications. With years of experience, we provide customized computational design of protein-protein interactions service to precisely meet customer requirements.

Introduction of Protein-Protein Interactions Design

Interactions between proteins are central to many processes within cells and organisms, from the assembly of cellular structural scaffolds to immune defense and cellular communication. Because of their ubiquity and critical importance, PPIs are considered potential therapeutic targets for large-scale diseases and pathological states, including those for which effective treatments are lacking. To date, the U.S. Food and Drug Association (FDA) has approved 5 PPI modulators for clinical use in cancer, dry eye syndrome and autoimmune diseases. Despite some progress in the regulation of PPIs in recent years, however, traditional experimental methods face serious challenges in studying PPIs due to their general properties, such as flat surfaces, featureless conformations, complex topologies, and shallow pockets. Currently, the rapid development of computational chemistry and structural biology methods has facilitated the application of PPIs in drug discovery. These techniques improve their cost-effectiveness and high-throughput properties and enable the study of dynamic PPI interfaces, bringing instructive insights into the modulation of PPIs.

Fig 1. Computational methods-guided design of modulators targeting protein-protein interactions (PPIs). (Qiu Y, et al., 2020)

Services

Computational protein design strategies have been developed as an automated, generalizable way to redesign protein interfaces. Creative BioMart has successfully used various computational approaches to modulate protein interactions, allowing the design of new protein interactions and would ultimately open the way to engineer new functions and modulate cellular behavior in a predictive manner. Our services support the design of PPI drug discovery to address those non-drug targets and generate potential therapeutics. Our tailored computationally aided pipeline for PPI drug design:

(1) Identifying hotspots: we employ molecular dynamics simulation-based energy calculations, virtual alanine scanning mutagenesis, and probe-based molecular dynamics simulations to calculate the features of protein-protein complex structures, and provide reliable insights into hotspot distribution.

(2) Determination of lead structures: we establish novel compound libraries targeting PPIs with greater chemical diversity, such as virtual compound libraries. In addition, native proteins or native protein-mimicking compounds can also be used as lead structures.

(3) Using computational programs to guide the optimization of lead compounds: we use empirical functions and various energy algorithms to automatically predict the potential structures of lead compounds. In addition, a virtual screening method was used as a filter to screen candidate compounds.

Creative BioMart is committed to providing global customers with high-quality computational design of protein-protein interactions to discover small molecule in silico structure-based methods for binding to PPI interfaces. We will work with you to develop the most appropriate strategy and provide the most meaningful data for your research for accelerating the research of life sciences. If you are interested in our services, please do not hesitate to contact us for more information.

References

1. Shin WH, Christoffer CW, Kihara D. (2017) In silico structure-based approaches to discover protein-protein interaction-targeting drugs. Methods. 131: 22-32.
2. Qiu Y, Li X, et al.. (2020) Computational methods-guided design of modulators targeting protein-protein interactions (PPIs). Eur J Med Chem. 207:112764.

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