Graphical abstract

We previously reported the design of a library of de novo amino acid sequences targeted to fold into four-helix bundles. The design of these sequences was based on a "binary code" strategy, in which the patterning of polar and nonpolar amino acids is specified explicitly, but the exact identities of the side chains is varied extensively (Kamtekar S, Schiffer JM, Xiong H, Babik JM, Hecht MH, 1993, Science 262:1680-1685. Because of this variability, the resulting collection of amino acid sequences may include de novo proteins capable of binding biologically important cofactors. To probe for such binding, the de novo sequences were screened for their ability to bind the heme cofactor. Among an initial collection of 30 binary code sequences, 15 are shown to bind heme and form bright red complexes. Characterization of several of these de novo heme proteins demonstrated that their absorption spectra and resonance Raman spectra resemble those of natural cytochromes. Because the design of these sequences is based on global features of polar/ nonpolar patterning, the finding that half of them bind heme highlights the power of the binary code strategy, and demonstrates that isolating de novo heme proteins does not require explicit design of the cofactor binding site. Because bound heme plays a key role in the functions of many natural proteins, these results suggest that binary code sequences may serve as initial prototypes for the development of large collections of functionally active de novo proteins.Keywords: binary code; combinatorial libraries; de novo proteins; heme binding; protein designThe two central goals of protein design are: (1) to devise novel amino acid sequences that fold into particular target structures; and (2) to obtain from such sequences proteins that perform specific functions.Our strategy for achieving the first goal employs binary patterning of polar and nonpolar amino acids as the cornerstone for designing target protein structures (Kamtekar et al., 1993). In this strategy, the sequence locations of polar and nonpolar residues are specified explicitly, but the precise identities of these residues are not constrained. Thus, a binary pattern designed to fold into a particular target structure is compatible with many different amino acid sequences. We tested the utility of the binary code strategy by designing a binary pattern for a four-helix bundle, constructing a

The in silico study of medicinal plants is a rapidly growing field. Techniques such as reverse screening and network pharmacology are used to study the complex cellular action of medicinal plants against disease. However, it is difficult to produce a meaningful visualization of phytochemical-protein interactions (PCPIs) in the cell. This study introduces a novel workflow combining various tools to visualize a PCPI network for a medicinal plant against a disease. The five steps are 1) phytochemical compilation, 2) reverse screening, 3) network building, 4) network visualization, and 5) evaluation. The output is a PCPI network that encodes multiple dimensions of information, including subcellular location, phytochemical class, pharmacokinetic data, and prediction probability. As a proof of concept, we built a PCPI network for bitter gourd (Momordica charantia L.) against colorectal cancer. The network and workflow are available at https://yumibriones.github.io/network/. The PCPI network highlights high-confidence interactions for further in vitro or in vivo study. The overall workflow is broadly transferable and can be used to visualize the action of other medicinal plants or small molecules against other diseases.

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