Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules

The overall goal of the following experiment is to design proteins or peptides for improved folding, binding, or functional properties. This is achieved by uploading the protein or complex structure and defining mutation and biological constraints To define the design goal as a second step, sequence selection optimization is performed, which produces a large number of possible protein or peptide sequences with improved stability and interaction properties. Next fold.

Specificity and or approximate binding affinity calculations are performed on the designed sequence in order to validate the designed proteins or peptides for the desired improved properties. Results are obtained that show improved properties of the designed sequences based on computational analysis of the structures produced through the procedure. This protocol has been developed in the laboratory of Professor Chris Doles, a flutist at Princeton University.

This general computational de novo protein design protocol is capable of tackling several important areas of protein design. These include the design of monomeric proteins for increased stability and complexes for increased binding affinity. We've had several notable successful designs in a variety of different therapeutic areas, including inhibitors of H-I-V-G-P 41 inhibitors, targeting EZH two for cancer therapeutics and inhibitors, targeting complement components C3 A.In order to make application of the protein design methodology available to the wider academic community, we have developed a web interface called Protein Wisdom.

This interface allows user to have full control of template submission, design constraint definition, and method parameter specification to easily employ the design methods for a wide variety of design problems Following user registration on the protein wisdom website as described in the text protocol, submit the protein sequence and template structure, but clicking on the user login button. To begin the protein design experiment, the user is presented with the user homepage, which lists the number of jobs submitted, the number of structures uploaded, and a list of the structures uploaded so far. Start a new design job.

By clicking create new job, the user is taken to the job submission page. Give the job a name and indicate if it is based on a previous job. Click continue.

Upload the protein structure of the design template. This template must be in standard protein data bank or PDB format. It can be a rigid template with one set of coordinates for every atom or a flexible template with multiple models such as obtained from NMR solution structures.

For the case of designing a single protein, there can be only one chain. In the template, a user can upload a new template or select from existing templates they have previously uploaded. If multiple templates are uploaded, be sure each model begins with model number and ends with end model.

Ensure every residue is designated by a natural amino acid. Click continue. Once the template has been successfully uploaded and confirmed, the user is taken to the main control page.

On this page, the user can view the job status, modify the mutation sets and biological constraints, and submit the job for stage one sequence selection. At this point, since stage one has not completed, there are no options for stage two. Those appear once results from stage one are available.

Next, click on the mutation sets link on the main control page to define mutation sets, select which residues will be allowed to mutate and select which amino acids they're allowed to mutate to. By default, the allowable amino acids at any given position are selected based upon solvent accessible surface area or SSA mutation sets are required. Click save changes after mutation sets are selected.

Take note of the computational complexity of the optimization to be solved. There is an upper limit of 20 to the 25th power for computational complexity allowed. Then click on the biological constraints link on the main control page to define biological constraints, specify charge or amino acid content constraints across the whole protein or a portion of the protein limit.

The total number of mutations allowed to occur if required, biological constraints are optional. Return to the main control page when finished. Click on the begin stage one link to bring user to submit stage one page.

Select the chain to design the number of sequences to generate the distance dependent force field, and the model calculation. Specific details regarding these selections can be found in the text protocol. Submit the job, the user is redirected back to the main control page.

The job status will be updated to indicate the current progress of the job. The job will become locked for editing after submission. Upon completion of the job, the user receives an email with the results, which consist of a list of designed sequences.

The results are also viewable on the main control page. A box for stage two fold specificity appears on the page to enable the user To perform this validation, click begin stage two fold specificity. To enter the build stage two page, define the upper and lower alpha carbon, alpha carbon distance bounds by specifying the template flexibility factor, either as a percentage of distance or as a fixed distance.

Next, define the upper and lower angle bounds on the PHI and side dihedral angles. By specifying the template flexibility factor as a percentage, click the submit button, specify the number of structures per sequence to generate and click Continue. Note, there is an upper bound of 500 structures per sequence to generate.

Then click continue to confirm intent to submit for fold validation. Stage one and stage two are locked for editing until the completion of stage two. Upon completion of the job, an email is sent to the user with the results, which are also viewable on the main control page.

Here the text files containing designed sequences, corresponding energy values from stage one and fold specificity values from stage two can be viewed and downloaded. In addition, the user may click the view results link, which displays a table in the browser with stage one ranks and energy values, as well as stage two ranks and fold specificity values. Approximate binding affinity calculations are used to determine the affinity of the designed ligand protein or peptide to the rest of the complex.

These calculations can be performed directly after stage one or after fold specificity calculations have been completed. To begin, click on sequence number to select the sequence. To begin the approximate binding affinity calculation, the user will be directed to the select sequence page, which presents a list of the design sequences, along with their sequence selection and fold specificity ranks.

Once the sequence is selected and saved, the user is redirected to the main control page. Then click Begin stage two, approximate binding affinity to submit the job upon completion, results are emailed to the user, which include an attachment containing the sequence number, approximate binding, affinity, and values of the partition functions. For every subsequent approximate binding affinity job, this file contains the results for all the completed sequences.

Full results can also be viewed by accessing the main control page for the job shown. Here is the design template for entry inhibitors of HIV one, which is the crystal structure of C 14 link mid a 14 residue cross-linked peptide in complex with the GP 41 core. This template peptide is a known potent inhibitor and is submitted with the crosslinker removed.

After the design inputs are defined and the system is submitted for stage one sequence selection. The sorted sequence selection results can be accessed through the view results links on the main job page. This link gives an easily readable summary of all the results calculated for a given system, which can be sorted by any of the stage results.

For quick analysis, the results can also be visualized through the sequence results link, which gives a summary of selected sequences in three letter amino acid code. The third option for accessing results is through the energy results link, which gives a summary of the optimization model run with the selected sequences, their energies, and the time it took to solve the model for the solution. Following completion of stage one, sequence selection and submitting of the stage two fold specificity and approximate binding affinity methods, the results can be accessed and sorted in the summary view results section.

Alternatively, they can be viewed individually in the fold Specificity Results section in the fold specificity Results section, the sequence number and fold specificity values are provided as an array. The results of the sample approximate binding affinity calculations are presented as a sortable list In the view results section, all sequences that have been run for the approximate binding affinity calculation have a highlighted link in the view column. The view link takes the user to a design information page.

This page provides downloadable zip files for all the complex and peptide structures used. In the final structure design step for both the complex and peptide structures, the top 10 lowest energy structures are provided in a rank ordered list. Each structure has a view link, which allows the user to view the structure in an interactive JM O environment.

A download link is also provided to allow the user to download each structure individually. Further details of the results are presented in the approximate binding affinity results section. This section provides the values for the peptide protein and complex partition functions, along with the final approximate binding affinity value.

While working with protein wisdom, it's important to remember that the selection of design constraints can have a large impact on the overall design results. Not only do design constraints speed up the overall search by limiting the amount of sequence space that the optimization algorithms must explore, but utilizing optimization constraints derived from experimental information can lead to obtaining biologically relevant protein designs. We hope the availability of the design methods through the web interface protein wisdom will allow for wider use of the design methods.

We continue to expand and develop the capabilities of the design methods and hope to generalize the framework to include multimeric systems Protein DNA interactions and design with post-translational modifications and non-canonical amino acids in the near future. With each expansion, the availability of the methods through protein Wisdom will allow for easy and efficient application by the academic community.