Why design a tool for specific macromolecule?

Uniprot, Pfam are “flat” structures vis-a-vis the atomic models. There is value in building a layer in between.

  • want to centralize computations around the data, but not reinvent other tools. whati s the right balance?

  • data sovereignty within the community

General structural biology & bioinformatics operations:

  • align sequences
  • look up
  • ..
  • ligand binding

Target specific structural biology & bioinformatics operations:

Tubulin:

  • libraries of cleaned-up ligands ready to go (via rosetta)
  • ..
  • ..

Sea change due to the deep learning models

  • molecular dynamics
  • neural force fields
  • evo2
  • alphafold
  • esmfold

MCPs

slide: the layers of tools and their evolutions wrt each other over time last slide: where this is going (deep learning models, czii cryoet) go through charlie harris’s db: design companies

Ontology | General:

  • connective tissue in a fragmented ecosystem (Structural:(pfam, uniprot, pdb, etc.), Bioinformatics:(blast, clustal, etc.), Computational:(rosetta, pymol, etc.), Deep Learning:(alphafold, esmfold, etc.), Molecular Dynamics:(gromacs, namd, etc.), cryoEM/ET:(modelangelo))

  • sovereignty and facility for future models (ELABORATE)

assembling hybrid/chimeric microtubules

  • instant retrieval of the binding site only for further dokcing/simulation/md

Our crystallographic fragment screen now revealed four sites that are targeted by both fragments and secondary structural elements of major cellular microtubule regulators including tau, dynein, kinesin-13, kinesin-5, TPX2, and CPAP/SAS-4.

Regarding MAPs (Microtubule-Associated Proteins), there are dozens of well-characterized MAPs that have been studied worldwide. They can be broadly categorized into:

Structural MAPs: Including MAP1, MAP2, MAP4, tau proteins Motor proteins: Kinesins (40+ members) and dyneins Plus-end tracking proteins (+TIPs): EB1, CLIP-170, CLASP Minus-end targeting proteins (-TIPs): CAMSAPs/Patronin Microtubule nucleators and organizers: γ-tubulin and associated proteins Microtubule-severing proteins: Katanin, spastin, fidgetin Destabilizing proteins: Stathmin, kinesin-13 family

The exact number of MAPs that have been characterized is difficult to specify precisely, as new ones continue to be discovered and characterized at varying levels of detail. The field likely encompasses 100-200 distinct proteins that directly interact with microtubules, with the most extensively studied numbering several dozen.

Tools

https://pymolwiki.org/index.php/Pytms https://pubmed.ncbi.nlm.nih.gov/37902126/

DBs

https://pmc.ncbi.nlm.nih.gov/articles/PMC10707541/pdf/pone.0295279.pdf

https://research.bioinformatics.udel.edu/iptmnet/

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I’m building a platform that would facilitate the handling of TUBULIN and MT data and extraction of information (sequence and structural, but also correlative, ligand, dynamics) from the available 3D structures and density maps.

Basically i’ve developed something of smaller scale for the ribosomal data and want to apply a similar architecture as before. In few short steps: - reclassify the availalbe sequences according to a standardized classificatio nnomenclature (this will have to be developed since none is proposed) - build HMMs for these classes - a neo4j database graph database for tracking semantic data, conecting of the PDB strucutres with sequence classes, ligands, etc. - a backend with the twofold function: 1. communicating with thd database and providing an API to all the indexed/reindexed data. 2. setting up interfaces for further enriching data and running computations, simulatons on it (seq to structure via folds, PTMs reconstruction, ligand docking, molecular dynamics etc.)

From the point of view of the tubulin community, intimately familiar with the molecule: What biologically relevat operations, loci and knowledge should this application possess? What classifications should it make?

[atoms] ; acetylated lysine (ALY) ; nr type resnr resid atom cgnr charge mass 1 N 1 ALY N 1 -0.3479 14.0067 … 8 CE 1 ALY CE 8 -0.0015 12.011 ; modified from standard LYS 9 NZ 1 ALY NZ 9 -0.6510 14.0067 ; substantially different charge 10 HZ 1 ALY HZ 10 0.3400 1.008 ; reduced from 3 to 1 hydrogen 11 C1 1 ALY C1 11 0.7286 12.011 ; acetyl carbon (new) 12 O1 1 ALY O1 12 -0.5894 15.9994 ; acetyl oxygen (new) 13 C2 1 ALY C2 13 -0.2400 12.011 ; methyl group (new) …

[bonds] ; acetyl group bonds NZ C1 1 1.335 418400 ; amide bond parameters C1 O1 1 1.229 476976 ; carbonyl parameters C1 C2 1 1.522 265265 ; carbon-carbon bond

[angles] ; modified angles for acetyl group CE NZ C1 1 123.5 418.4 NZ C1 O1 1 122.9 669.4 ; amide plane geometry NZ C1 C2 1 115.2 585.8

[dihedrals] ; proper dihedrals CE NZ C1 O1 9 180.0 10.5 2 ; keep acetyl group planar