skip to main content

Attention:

The NSF Public Access Repository (PAR) system and access will be unavailable from 11:00 PM ET on Friday, December 13 until 2:00 AM ET on Saturday, December 14 due to maintenance. We apologize for the inconvenience.


This content will become publicly available on August 21, 2025

Title: Utilizing AfDesign for Developing a Small Molecule Inhibitor of PICK 1-PDZ
<p><p>Introduction: The PICK1 PDZ domain has been identified as a potential drug target forneurological disorders. After many years of effort, a few inhibitors, such as TAT-C5 and mPD5,have been discovered experimentally to bind to the PDZ domain with a relatively high bindingaffinity. With the rapid growth of computational research, there is an urgent need for more efficientcomputational methods to design viable ligands that target proteins.</p><p>Method: Recently, a newly developed program called AfDesign (part of ColabDesign) at https://github.com/sokrypton/ColabDesign), an open-source software built on AlphaFold, has beensuggested to be capable of generating ligands that bind to targeted proteins, thus potentially facilitatingthe ligand development process. To evaluate the performance of this program, we exploredits ability to target the PICK1 PDZ domain, given our current understanding of it. We found thatthe designated length of the ligand and the number of recycles play vital roles in generating ligandswith optimal properties.</p><p>Results: Utilizing AfDesign with a sequence length of 5 for the ligand produced the highest comparableligands to that of prior identified ligands. Moreover, these designed ligands displayed significantlylower binding energy compared to manually created sequences.</p><p>Conclusion: This work demonstrated that AfDesign can potentially be a powerful tool to facilitatethe exploration of the ligand space for the purpose of targeting PDZ domains.</p></p></sec> </span> <a href='#' class='show open-abstract' style='margin-left:10px;'>more »</a> <a href='#' class='hide close-abstract' style='margin-left:10px;'>« less</a> <div style="clear:both;margin-bottom:20px;"></div> <dl class="dl-horizontal small semi-colon-delimited-data"> <dt>Award ID(s):</dt> <dd> <span> <a target="_blank" rel="noopener noreferrer" href="https://par.nsf.gov/search/award_ids:2137558"> 2137558</a> </span> </dd> </dl> <dl class="dl-horizontal small"> <dt>PAR ID:</dt> <dd>10546338</dd> </dl> <dl class="dl-horizontal small"> <dt>Author(s) / Creator(s):</dt> <dd> <a target="_blank" rel="noopener noreferrer" href="https://par.nsf.gov/search/author:"Hendrix, Emily""><span class="author" itemprop="author">Hendrix, Emily</span></a><span class="sep">; </span><a target="_blank" rel="noopener noreferrer" href="https://par.nsf.gov/search/author:"Xia, Xinyu""><span class="author" itemprop="author">Xia, Xinyu</span></a><span class="sep">; </span><a target="_blank" rel="noopener noreferrer" href="https://par.nsf.gov/search/author:"Stevens, Amy O""><span class="author" itemprop="author">Stevens, Amy O</span></a><span class="sep">; </span><a target="_blank" rel="noopener noreferrer" href="https://par.nsf.gov/search/author:"He, Yi""><span class="author" itemprop="author">He, Yi</span></a></dd> </dl> <dl class="dl-horizontal small"> <dt>Publisher / Repository:</dt> <dd itemprop="publisher">Bentham Science</dd> </dl> <dl class="dl-horizontal small"> <dt>Date Published:</dt> <dd> <time itemprop="datePublished" datetime="2024-08-21">2024-08-21</time> </dd> </dl> <dl class="dl-horizontal small"> <dt>Journal Name:</dt> <dd>Current Protein & Peptide Science</dd> </dl> <dl class="dl-horizontal small"> <dt>Volume:</dt> <dd>25</dd> </dl> <dl class="dl-horizontal small"> <dt>ISSN:</dt> <dd>1389-2037</dd> </dl> <dl class="dl-horizontal small"> <dt>Format(s):</dt> <dd>Medium: X</dd> </dl> <dl class="dl-horizontal small semi-colon-delimited-data"> <dt>Sponsoring Org:</dt> <dd itemprop="sourceOrganization"> <span>National Science Foundation</span> </dd> </dl> <div class="clearfix"></div> </div> </div> <div id="citation-addl" class="hidden-print"> <h5 id='mlt-header'>More Like this</h5> <ol class="item-list documents" id="citation-mlt" style="min-height: 80px;"> <li> <div class="article item document" itemscope itemtype="http://schema.org/TechArticle"> <div class="item-info"> <div class="title"> <a href="https://par.nsf.gov/biblio/10372387-motifanalyzerpdz-computational-program-investigate-evolution-pdzbinding-target-specificity" itemprop="url"> <span class='span-link' itemprop="name">MotifAnalyzer‐PDZ : A computational program to investigate the evolution of PDZ‐binding target specificity</span> </a> </div> <div> <strong> <a class="misc external-link" href="https://doi.org/10.1002/pro.3741" target="_blank" title="Link to document DOI">https://doi.org/10.1002/pro.3741  <span class="fas fa-external-link-alt"></span></a> </strong> </div> <div class="metadata"> <span class="authors"> <span class="author" itemprop="author">Valgardson, Jordan</span> <span class="sep">; </span><span class="author" itemprop="author">Cosbey, Robin</span> <span class="sep">; </span><span class="author" itemprop="author">Houser, Paul</span> <span class="sep">; </span><span class="author" itemprop="author">Rupp, Milo</span> <span class="sep">; </span><span class="author" itemprop="author">Van Bronkhorst, Raiden</span> <span class="sep">; </span><span class="author" itemprop="author">Lee, Michael</span> <span class="sep">; </span><span class="author" itemprop="author">Jagodzinski, Filip</span> <span class="sep">; </span><span class="author" itemprop="author">Amacher, Jeanine F.</span> </span> <span class="year">( <time itemprop="datePublished" datetime="2019-11-01">November 2019</time> , Protein Science) </span> </div> <div style="cursor: pointer;-webkit-line-clamp: 5;" class="abstract" itemprop="description"> <title>Abstract

Recognition of short linear motifs (SLiMs) or peptides by proteins is an important component of many cellular processes. However, due to limited and degenerate binding motifs, prediction of cellular targets is challenging. In addition, many of these interactions are transient and of relatively low affinity. Here, we focus on one of the largest families of SLiM‐binding domains in the human proteome, the PDZ domain. These domains bind the extreme C‐terminus of target proteins, and are involved in many signaling and trafficking pathways. To predict endogenous targets of PDZ domains, we developedMotifAnalyzer‐PDZ, a program that filters and compares all motif‐satisfying sequences in any publicly available proteome. This approach enables us to determine possible PDZ binding targets in humans and other organisms. Using this program, we predicted and biochemically tested novel human PDZ targets by looking for strong sequence conservation in evolution. We also identified three C‐terminal sequences in choanoflagellates that bind a choanoflagellate PDZ domain, theMonsiga brevicollisSHANK1 PDZ domain (mbSHANK1), with endogenously‐relevant affinities, despite a lack of conservation with the targets of a homologous human PDZ domain, SHANK1. All three are predicted to be signaling proteins, with strong sequence homology to cytosolic and receptor tyrosine kinases. Finally, we analyzed and compared the positional amino acid enrichments in PDZ motif‐satisfying sequences from over a dozen organisms. Overall,MotifAnalyzer‐PDZis a versatile program to investigate potential PDZ interactions. This proof‐of‐concept work is poised to enable similar types of analyses for other SLiM‐binding domains (e.g.,MotifAnalyzer‐Kinase).MotifAnalyzer‐PDZis available athttp://motifAnalyzerPDZ.cs.wwu.edu.

 
more » « less
  • Choanoflagellates are single-celled eukaryotes with complex signaling pathways. They are considered the closest non-metazoan ancestors to mammals and other metazoans and form multicellular-like states called rosettes. The choanoflagellate Monosiga brevicollis contains over 150 PDZ domains, an important peptide-binding domain in all three domains of life (Archaea, Bacteria, and Eukarya). Therefore, an understanding of PDZ domain signaling pathways in choanoflagellates may provide insight into the origins of multicellularity. PDZ domains recognize the C-terminus of target proteins and regulate signaling and trafficking pathways, as well as cellular adhesion. Here, we developed a computational software suite, Domain Analysis and Motif Matcher (DAMM), that analyzes peptide-binding cleft sequence identity as compared with human PDZ domains and that can be used in combination with literature searches of known human PDZ-interacting sequences to predict target specificity in choanoflagellate PDZ domains. We used this program, protein biochemistry, fluorescence polarization, and structural analyses to characterize the specificity of A9UPE9_MONBE, a M. brevicollis PDZ domain-containing protein with no homology to any metazoan protein, finding that its PDZ domain is most similar to those of the DLG family. We then identified two endogenous sequences that bind A9UPE9 PDZ with <100 μM affinity, a value commonly considered the threshold for cellular PDZ–peptide interactions. Taken together, this approach can be used to predict cellular targets of previously uncharacterized PDZ domains in choanoflagellates and other organisms. Our data contribute to investigations into choanoflagellate signaling and how it informs metazoan evolution. 
    more » « less
  • The PDZ family has drawn attention as possible drug targets because of the domains’ wide ranges of function and highly conserved binding pockets. The PICK1 PDZ domain has been proposed as a possible drug target because the interactions between the PICK1 PDZ domain and the GluA2 subunit of the AMPA receptor have been shown to progress neurodegenerative diseases. BIO124 has been identified as a sub µM inhibitor of the PICK1–GluA2 interaction. Here, we use all-atom molecular dynamics simulations to reveal the atomic-level interaction pattern between the PICK1 PDZ domain and BIO124. Our simulations reveal three unique binding conformations of BIO124 in the PICK1 PDZ binding pocket, referred to here as state 0, state 1, and state 2. Each conformation is defined by a unique hydrogen bonding network and a unique pattern of hydrophobic interactions between BIO124 and the PICK1 PDZ domain. Interestingly, each conformation of BIO124 results in different dynamic changes to the PICK1 PDZ domain. Unlike states 1 and 2, state 0 induces dynamic coupling between BIO124 and the αA helix. Notably, this dynamic coupling with the αA helix is similar to what has been observed in other PDZ–ligand complexes. Our analysis indicates that the interactions formed between BIO124 and I35 may be the key to inducing dynamic coupling with the αA helix. Lastly, we suspect that the conformational shifts observed in our simulations may affect the stability and thus the overall effectiveness of BIO124. We propose that a physically larger inhibitor may be necessary to ensure sufficient interactions that permit stable binding between a drug and the PICK1 PDZ domain. 
    more » « less
  • LINKED ARTICLES

    This article is part of a themed issue on Structure Guided Pharmacology of Membrane Proteins (BJP 75th Anniversary). To view the other articles in this section visithttp://onlinelibrary.wiley.com/doi/10.1111/bph.v179.14/issuetoc

     
    more » « less
  • Abstract

    Protein–protein interactions that involve recognition of short peptides are critical in cellular processes. Protein–peptide interaction surface areas are relatively small and shallow, and there are often overlapping specificities in families of peptide‐binding domains. Therefore, dissecting selectivity determinants can be challenging. PDZ domains are a family of peptide‐binding domains located in several intracellular signaling and trafficking pathways. These domains are also directly targeted by pathogens, and a hallmark of many oncogenic viral proteins is a PDZ‐binding motif. However, amidst sequences that target PDZ domains, there is a wide spectrum in relative promiscuity. For example, the viral HPV16 E6 oncoprotein recognizes over double the number of PDZ domain‐containing proteins as the cystic fibrosis transmembrane conductance regulator (CFTR) in the cell, despite similar PDZ targeting‐sequences and identical motif residues. Here, we determine binding affinities for PDZ domains known to bind either HPV16 E6 alone or both CFTR and HPV16 E6, using peptides matching WT and hybrid sequences. We also use energy minimization to model PDZ–peptide complexes and use sequence analyses to investigate this difference. We find that while the majority of single mutations had marginal effects on overall affinity, the additive effect on the free energy of binding accurately describes the selectivity observed. Taken together, our results describe how complex and differing PDZ interactomes can be programmed in the cell.

     
    more » « less