LazyAF, a pipeline for accessible medium-scale in silico prediction of protein-protein interactions.

Artificial intelligence has revolutionized the field of protein structure prediction. However, with more powerful and complex software being developed, it is accessibility and ease of use rather than capability that is quickly becoming a limiting factor to end users. LazyAF is a Google Colaboratory-based pipeline which integrates the existing ColabFold BATCH software to streamline the process of medium-scale protein-protein interaction prediction. LazyAF was used to predict the interactome of the 76 proteins encoded on the broad-host-range multi-drug resistance plasmid RK2, demonstrating the ease and accessibility the pipeline provides.

A Model of the Full-Length Cytokinin Receptor: New Insights and Prospects.

Cytokinins (CK) are one of the most important classes of phytohormones that regulate a wide range of processes in plants. A CK receptor, a sensor hybrid histidine kinase, was discovered more than 20 years ago, but the structural basis for its signaling is still a challenge for plant biologists. To date, only two fragments of the CK receptor structure, the sensory module and the receiver domain, were experimentally resolved. Some other regions were built up by molecular modeling based on structures of proteins homologous to CK receptors. However, in the long term, these data have proven insufficient for solving the structure of the full-sized CK receptor. The functional unit of CK receptor is the receptor dimer. In this article, a molecular structure of the dimeric form of the full-length CK receptor based on AlphaFold Multimer and ColabFold modeling is presented for the first time. Structural changes of the receptor upon interacting with phosphotransfer protein are visualized. According to mathematical simulation and available data, both types of dimeric receptor complexes with hormones, either half- or fully liganded, appear to be active in triggering signals. In addition, the prospects of using this and similar models to address remaining fundamental problems of CK signaling were outlined.

Conservation of Three-Dimensional Structure of Lepidoptera and Trichoptera L-Fibroins for 290 Million Years.

The divergence of sister orders Trichoptera (caddisflies) and Lepidoptera (moths and butterflies) from a silk-spinning ancestor occurred around 290 million years ago. Trichoptera larvae are mainly aquatic, and Lepidoptera larvae are almost entirely terrestrial-distinct habitats that required molecular adaptation of their silk for deployment in water and air, respectively. The major protein components of their silks are heavy chain and light chain fibroins. In an effort to identify molecular changes in L-fibroins that may have contributed to the divergent use of silk in water and air, we used the ColabFold implementation of AlphaFold2 to predict three-dimensional structures of L-fibroins from both orders. A comparison of the structures revealed that despite the ancient divergence, profoundly different habitats, and low sequence conservation, a novel 10-helix core structure was strongly conserved in L-fibroins from both orders. Previously known intra- and intermolecular disulfide linkages were accurately predicted. Structural variations outside of the core may represent molecular changes that contributed to the evolution of insect silks adapted to water or air. The distributions of electrostatic potential, for example, were not conserved and present distinct order-specific surfaces for potential interactions with or modulation by external factors. Additionally, the interactions of L-fibroins with the H-fibroin C-termini are different for these orders; lepidopteran L-fibroins have N-terminal insertions that are not present in trichopteran L-fibroins, which form an unstructured ribbon in isolation but become part of an intermolecular ß-sheet when folded with their corresponding H-fibroin C-termini. The results are an example of protein structure prediction from deep sequence data of understudied proteins made possible by AlphaFold2.

E and M SARS-CoV-2 membrane protein expression and enrichment with plant lipid droplets.

Plants are gaining traction as a cost-effective and scalable platform for producing recombinant proteins. However, expressing integral membrane proteins in plants is challenging due to their hydrophobic nature. In our study, we used transient and stable expression systems in Nicotiana benthamiana and Camelina sativa respectively to express SARS-CoV-2 E and M integral proteins, and target them to lipid droplets (LDs). LDs offer an ideal environment for folding hydrophobic proteins and aid in their purification through flotation. We tested various protein fusions with different linkers and tags and used three dimensional structure predictions to assess their effects. E and M mostly localized in the ER in N. benthamiana leaves but E could be targeted to LDs in oil accumulating tobacco when fused with oleosin, a LD integral protein. In Camelina sativa seeds, E and M were however found associated with purified LDs. By enhancing the accumulation of E and M within LDs through oleosin, we enriched these proteins in the purified floating fraction. This strategy provides an alternative approach for efficiently producing and purifying hydrophobic pharmaceuticals and vaccines using plant systems.

Utilizing AfDesign for Developing a Small Molecule Inhibitor of PICK 1-PDZ.

INTRODUCTION: The PICK1 PDZ domain has been identified as a potential drug target for neurological 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 binding affinity. With the rapid growth of computational research, there is an urgent need for more efficient computational methods to design viable ligands that target proteins. 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 been suggested to be capable of generating ligands that bind to targeted proteins, thus potentially facilitating the ligand development process. To evaluate the performance of this program, we explored its ability to target the PICK1 PDZ domain, given our current understanding of it. We found that the designated length of the ligand and the number of recycles play vital roles in generating ligands with optimal properties. RESULTS: Utilizing AfDesign with a sequence length of 5 for the ligand produced the highest comparable ligands to that of prior identified ligands. Moreover, these designed ligands displayed significantly lower binding energy compared to manually created sequences. CONCLUSION: This work demonstrated that AfDesign can potentially be a powerful tool to facilitate the exploration of the ligand space for the purpose of targeting PDZ domains.

A comparative study of protein structure prediction tools for challenging targets: Snake venom toxins.

Protein structure determination is a critical aspect of biological research, enabling us to understand protein function and potential applications. Recent advances in deep learning and artificial intelligence have led to the development of several protein structure prediction tools, such as AlphaFold2 and ColabFold. However, their performance has primarily been evaluated on well-characterised proteins and their ability to predict sturtctures of proteins lacking experimental structures, such as many snake venom toxins, has been less scrutinised. In this study, we evaluated three modelling tools on their prediction of over 1000 snake venom toxin structures for which no experimental structures exist. Our findings show that AlphaFold2 (AF2) performed the best across all assessed parameters. We also observed that ColabFold (CF) only scored slightly worse than AF2, while being computationally less intensive. All tools struggled with regions of intrinsic disorder, such as loops and propeptide regions, and performed well in predicting the structure of functional domains. Overall, our study highlights the importance of exercising caution when working with proteins with no experimental structures available, particularly those that are large and contain flexible regions. Nonetheless, leveraging computational structure prediction tools can provide valuable insights into the modelling of protein interactions with different targets and reveal potential binding sites, active sites, and conformational changes, as well as into the design of potential molecular binders for reagent, diagnostic, or therapeutic purposes.

AlphaFold2 for Protein Structure Prediction: Best Practices and Critical Analyses.

AlphaFold2 (AF2) has emerged in recent years as a groundbreaking innovation that has revolutionized several scientific fields, in particular structural biology, drug design, and the elucidation of disease mechanisms. Many scientists now use AF2 on a daily basis, including non-specialist users. This chapter is aimed at the latter. Tips and tricks for getting the most out of AF2 to produce a high-quality biological model are discussed here. We suggest to non-specialist users how to maintain a critical perspective when working with AF2 models and provide guidelines on how to properly evaluate them. After showing how to perform our own structure prediction using ColabFold, we list several ways to improve AF2 models by adding information that is missing from the original AF2 model. By using software such as AlphaFill to add cofactors and ligands to the models, or MODELLER to add disulfide bridges between cysteines, we guide users to build a high-quality biological model suitable for applications such as drug design, protein interaction, or molecular dynamics studies.

Structural insights into the disulfide isomerase and chaperone activity of TrbB of the F plasmid type IV secretion system.

Bacteria have evolved elaborate mechanisms to thrive in stressful environments. F-like plasmids in gram-negative bacteria encode for a multi-protein Type IV Secretion System (T4SSF) that is functional for bacterial proliferation and adaptation through the process of conjugation. The periplasmic protein TrbB is believed to have a stabilizing chaperone role in the T4SSF assembly, with TrbB exhibiting disulfide isomerase (DI) activity. In the current report, we demonstrate that the deletion of the disordered N-terminus of TrbBWT, resulting in a truncation construct TrbB37-161, does not affect its catalytic in vitro activity compared to the wild-type protein (p = 0.76). Residues W37-K161, which include the active thioredoxin motif, are sufficient for DI activity. The N-terminus of TrbBWT is disordered as indicated by a structural model of GST-TrbBWT based on ColabFold-AlphaFold2 and Small Angle X-Ray Scattering data and 1H-15N Heteronuclear Single Quantum Correlation (HSQC) spectroscopy of the untagged protein. This disordered region likely contributes to the protein's dynamicity; removal of this region results in a more stable protein based on 1H-15N HSQC and Circular Dichroism Spectroscopies. Lastly, size exclusion chromatography analysis of TrbBWT in the presence of TraW, a T4SSF assembly protein predicted to interact with TrbBWT, does not support the inference of a stable complex forming in vitro. This work advances our understanding of TrbB's structure and function, explores the role of structural disorder in protein dynamics in the context of a T4SSF accessory protein, and highlights the importance of redox-assisted protein folding in the T4SSF.

Assembly of JAZ-JAZ and JAZ-NINJA complexes in jasmonate signaling.

Jasmonates (JAs) are plant hormones with crucial roles in development and stress resilience. They activate MYC transcription factors by mediating the proteolysis of MYC inhibitors called JAZ proteins. In the absence of JA, JAZ proteins bind and inhibit MYC through the assembly of MYC-JAZ-Novel Interactor of JAZ (NINJA)-TPL repressor complexes. However, JAZ and NINJA are predicted to be largely intrinsically unstructured, which has precluded their experimental structure determination. Through a combination of biochemical, mutational, and biophysical analyses and AlphaFold-derived ColabFold modeling, we characterized JAZ-JAZ and JAZ-NINJA interactions and generated models with detailed, high-confidence domain interfaces. We demonstrate that JAZ, NINJA, and MYC interface domains are dynamic in isolation and become stabilized in a stepwise order upon complex assembly. By contrast, most JAZ and NINJA regions outside of the interfaces remain highly dynamic and cannot be modeled in a single conformation. Our data indicate that the small JAZ Zinc finger expressed in Inflorescence Meristem (ZIM) motif mediates JAZ-JAZ and JAZ-NINJA interactions through separate surfaces, and our data further suggest that NINJA modulates JAZ dimerization. This study advances our understanding of JA signaling by providing insights into the dynamics, interactions, and structure of the JAZ-NINJA core of the JA repressor complex.

Higher-order structure formation using refined monomer structures of lipid raft markers, Stomatin, Prohibitin, Flotillin, and HflK/C-related proteins.

Currently, information on the higher-order structure of Stomatin, Prohibitin, Flotillin, and HflK/C (SPFH)-domain proteins is limited. Briefly, the coordinate information (Refined PH1511.pdb) of the stomatin ortholog, PH1511 monomer, was obtained using the artificial intelligence, ColabFold: AlphaFold2. Thereafter, the 24mer homo-oligomer structure of PH1511 was constructed using the superposing method, with HflK/C and FtsH (KCF complex) as templates. The 9mer-12mer homo-oligomer structures of PH1511 were also constructed using the ab initio docking method, with the GalaxyHomomer server for artificiality elimination. The features and functional validity of the higher-order structures were discussed. The coordinate information (Refined PH1510.pdb) of the membrane protease PH1510 monomer, which specifically cleaves the C-terminal hydrophobic region of PH1511, was obtained. Thereafter, the PH1510 12mer structure was constructed by superposing 12 molecules of the Refined PH1510.pdb monomer onto a 1510-C prism-like 12mer structure formed along the crystallographic threefold helical axis. The 12mer PH1510 (prism) structure revealed the spatial arrangement of membrane-spanning regions between the 1510-N and 1510-C domains within the membrane tube complex. Based on these refined 3D homo-oligomeric structures, the substrate recognition mechanism of the membrane protease was investigated. These refined 3D homo-oligomer structures are provided via PDB files as Supplementary data and can be used for further reference.

The structural integrity of the membrane-embedded bacterial division complex FtsQBL studied with molecular dynamics simulations.

The FtsQBL is an essential molecular complex sitting midway through bacterial divisome assembly. To visualize and understand its structure, and the consequences of its membrane anchorage, we produced a model of the E. coli complex using the deep-learning prediction utility, AlphaFold 2. The heterotrimeric model was inserted into a 3-lipid model membrane and subjected to a 500-ns atomistic molecular dynamics simulation. The model is superb in quality and captures most experimentally derived structural features, at both the secondary structure and the side-chain levels. The model consists of a uniquely interlocking module contributed by the C-terminal regions of all three proteins. The functionally important constriction control domain residues of FtsB and FtsL are located at a fixed vertical position of ∼43-49 Å from the membrane surface. While the periplasmic domains of all three proteins are well-defined and rigid, the single transmembrane helices of each are flexible and their collective twisting and bending contribute to most structural variations, according to principal component analysis. Considering FtsQ only, the protein is more flexible in its free state relative to its complexed state-with the biggest structural changes located at the elbow between the transmembrane helix and the α-domain. The disordered N-terminal domains of FtsQ and FtsL associate with the cytoplasmic surface of the inner membrane instead of freely venturing into the solvent. Contact network analysis highlighted the formation of the interlocking trimeric module in FtsQBL as playing a central role in mediating the overall structure of the complex.

Utilizing an artificial intelligence system to build the digital structural proteome of reef-building corals.

BACKGROUND: Reef-building corals play an important role in the marine ecosystem, and analyzing their proteomes from a structural perspective will exert positive effects on exploring their biology. Here we integrated mass spectrometry with newly published ColabFold to obtain digital structural proteomes of dominant reef-building corals. RESULTS: Of the 8,382 homologous proteins in Acropora muricata, Montipora foliosa, and Pocillopora verrucosa identified, 8,166 received predicted structures after about 4,060 GPU hours of computation. The resulting dataset covers 83.6% of residues with a confident prediction, while 25.9% have very high confidence. CONCLUSIONS: Our work provides insight-worthy predictions for coral research, confirms the reliability of ColabFold in practice, and is expected to be a reference case in the impending high-throughput era of structural proteomics.

Sequence Analysis and Structural Predictions of Lipid Transfer Bridges in the Repeating Beta Groove (RBG) Superfamily Reveal Past and Present Domain Variations Affecting Form, Function and Interactions of VPS13, ATG2, SHIP164, Hobbit and Tweek.

Lipid transfer between organelles requires proteins that shield the hydrophobic portions of lipids as they cross the cytoplasm. In the last decade a new structural form of lipid transfer protein (LTP) has been found: long hydrophobic grooves made of beta-sheet that bridge between organelles at membrane contact sites. Eukaryotes have five families of bridge-like LTPs: VPS13, ATG2, SHIP164, Hobbit and Tweek. These are unified into a single superfamily through their bridges being composed of just one domain, called the repeating beta groove (RBG) domain, which builds into rod shaped multimers with a hydrophobic-lined groove and hydrophilic exterior. Here, sequences and predicted structures of the RBG superfamily were analyzed in depth. Phylogenetics showed that the last eukaryotic common ancestor contained all five RBG proteins, with duplicated VPS13s. The current set of long RBG protein appears to have arisen in even earlier ancestors from shorter forms with 4 RBG domains. The extreme ends of most RBG proteins have amphipathic helices that might be an adaptation for direct or indirect bilayer interaction, although this has yet to be tested. The one exception to this is the C-terminus of SHIP164, which instead has a coiled-coil. Finally, the exterior surfaces of the RBG bridges are shown to have conserved residues along most of their length, indicating sites for partner interactions almost all of which are unknown. These findings can inform future cell biological and biochemical experiments.