Accompanying files for "A bridge-like lipid transfer protein is critical for generation of invasive stages in malaria parasites"

This upload contains files documented in a preprint. Preprint: https://doi.org/10.1101/2025.07.25.666630 The files uploaded here are: Structures: Alphafold3 (1) predictions for PfVPS13L1 (split in 2 pieces: 1-3600; 3281-5988), PfVPS13L2 (split in 3 pieces: 1-2822; 2140-5096; 4401-7594), PfVPS13L5 (split in 2 pieces: 1-4805; 3668-6769) and PfVPS13L16 (split in 2 pieces: 1-4916; 3868-5415) used for the domain cartoons presented in Fig. 3D. Five confidence-ranked structures are presented for each protein sequence. The annotated full length structure of PfVPS13L1 (presented in Fig. 4B-D) was aligned on PyMOL (2) and is also included in the PfVPS13L1 zip as a .pse file. Alphafold3 (1) interaction prediction of PfVPS13L1 N-term (a.a. 1-2976) and PfVAP (presented in Fig. S5F). Plasmids: All partially annotated sequences for all transfected plasmids in the study, organized into 4 categories. Code: Python codes for identifying FFAT motifs in a given fasta file using the scoring matrix from Slee et al. (3) or the one proposed for Plasmodium in this article. The code was partially written by ChatGPT (OpenAI, 2025). References 1. Abramson, J et al. Accurate structure prediction of biomolecular interactions with AlphaFold 3. Nature (2024). 2. The PyMOL Molecular Graphics System, Version 2.0. Schrödinger LLC. 3. Slee, J.A. & Levine, T.P. Systematic prediction of FFAT motifs across eukaryote proteomes identifies nucleolar and eisosome proteins with the predicted capacity to form bridges to the endoplasmic reticulum. Contact (Thousand Oaks) (2019).