GitHub - draskot/Vini: The Vini in silico model of cancer

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Name		Name	Last commit message	Last commit date
Latest commit History 256 Commits
DU145_th1_results_mAb_drugs		DU145_th1_results_mAb_drugs
DU145_th2_results_small_drugs		DU145_th2_results_small_drugs
DU145_th3_results_small_drugs		DU145_th3_results_small_drugs
PDBChainNameSupstitutor.jar		PDBChainNameSupstitutor.jar
ViniGUI		ViniGUI
binaries		binaries
genes		genes
pmemd		pmemd
sander		sander
.gitignore		.gitignore
AD4_parameters.dat.orig		AD4_parameters.dat.orig
AD4_parameters_for_metal_ions		AD4_parameters_for_metal_ions
COPYING		COPYING
COPYRIGHT		COPYRIGHT
INSTALL		INSTALL
Kolmogorov_Smirnov.py		Kolmogorov_Smirnov.py
MD_run.mpi		MD_run.mpi
PDBChainNameSupstitutor-1.0-SNAPSHOT-shaded.jar		PDBChainNameSupstitutor-1.0-SNAPSHOT-shaded.jar
README		README
VERSION		VERSION
VelikaVini		VelikaVini
Vini		Vini
add_cell_expressions_to_receptors		add_cell_expressions_to_receptors
add_expressions_to_receptors		add_expressions_to_receptors
add_expressions_to_relations		add_expressions_to_relations
add_missing_residues.py		add_missing_residues.py
adjust_pdb.awk		adjust_pdb.awk
all.csv		all.csv
analyze_chains.py		analyze_chains.py
apolar_sasa.mdp		apolar_sasa.mdp
autogrid4		autogrid4
automodel		automodel
batch_calculate_gene_expressions.py		batch_calculate_gene_expressions.py
calculate_cancer_drug_efficacy		calculate_cancer_drug_efficacy
calculate_gene_expression.py		calculate_gene_expression.py
calculate_gene_expression_cell_line		calculate_gene_expression_cell_line
calculate_gene_expression_cell_line.py		calculate_gene_expression_cell_line.py
calculate_z_scores		calculate_z_scores
calculate_z_scores_script		calculate_z_scores_script
chimera		chimera
chimera.script		chimera.script
clean		clean
clean_pdb.py		clean_pdb.py
clean_pdb_keep_ligand.py		clean_pdb_keep_ligand.py
compute_SLEM		compute_SLEM
compute_eigenvalues.py		compute_eigenvalues.py
compute_mean.py		compute_mean.py
compute_normal_distribution.py		compute_normal_distribution.py
convert_pkd_to_Gibbs.py		convert_pkd_to_Gibbs.py
cosmicTools.py		cosmicTools.py
cosmicTools.pyc		cosmicTools.pyc
create_NSC_numbers_file		create_NSC_numbers_file
create_SLEM_named_list		create_SLEM_named_list
create_SLEM_wings_list		create_SLEM_wings_list
create_SLEM_wings_named_list		create_SLEM_wings_named_list
create_Vina_config_file		create_Vina_config_file
create_affinity_vectors		create_affinity_vectors
create_completeness_list		create_completeness_list
create_energy_binding_matrix.py		create_energy_binding_matrix.py
create_receptor_structures		create_receptor_structures
create_relations_receptors_files		create_relations_receptors_files
create_vector		create_vector
create_vector.py		create_vector.py
csv_splitter.py		csv_splitter.py
csv_splitter.pyc		csv_splitter.pyc
delete_SLEM_entries_with_equal_indices		delete_SLEM_entries_with_equal_indices
density.in		density.in
determine_SGE_environment		determine_SGE_environment
dock.xml		dock.xml
docking		docking
docking.mac		docking.mac
download_Cosmic_Gene_Expressions		download_Cosmic_Gene_Expressions
download_Cosmic_data		download_Cosmic_data
download_Drugbank_fasta_structures		download_Drugbank_fasta_structures
download_Drugbank_pdb_structures		download_Drugbank_pdb_structures
download_KEGG_pathway		download_KEGG_pathway
download_SWISS_MODEL_metadata		download_SWISS_MODEL_metadata
download_pdb_structure		download_pdb_structure
download_substance_structure		download_substance_structure
drugbank_vocabulary.csv		drugbank_vocabulary.csv
equil.in		equil.in
extract_affinity.py		extract_affinity.py
extract_docked_ligand_coordinates.py		extract_docked_ligand_coordinates.py
find_longest_frame		find_longest_frame
find_longest_frame.py		find_longest_frame.py
flag_global_docking		flag_global_docking
flag_input_relax		flag_input_relax
flag_ligand_docking		flag_ligand_docking
gather_hardware_info		gather_hardware_info
generateMutatedFASTAseq.py		generateMutatedFASTAseq.py
generateMutatedFASTAseqCellLine.py		generateMutatedFASTAseqCellLine.py
generate_mutated_fasta_sequences		generate_mutated_fasta_sequences
generate_qsub_command.sh		generate_qsub_command.sh
generate_sbatch_command.sh		generate_sbatch_command.sh
getCosmicCompleteGeneExpression		getCosmicCompleteGeneExpression
get_gene_expression_parallel.py		get_gene_expression_parallel.py
get_gene_expressions_from_CosmicDB		get_gene_expressions_from_CosmicDB
get_gene_mutation.py		get_gene_mutation.py
get_gene_mutation_cell_line.py		get_gene_mutation_cell_line.py
get_gene_mutations_from_CosmicDB		get_gene_mutations_from_CosmicDB

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Program: Vini in silico model of cancer, version 4.0

Description: Vini is in silico model of cancer. It can be used for the pathway-based virtual drug screening, or for testing various hypothesis related to cancer.

The development team: Drasko Tomic, Josip Mesaric

Licensing:
----------

Vini code is free to download and use. It is distributed under GNU General Public License v3.0 (GNU GPLv3). This license is in COPYING file. However, Vini also uses other programs and databes, like Autodock Vina, ADFR, MGL Tools, Chimera, Rosetta, Drugbank, COSMIC, KEGG, and SWISS-MODEL, that request license agreement. They are free to use for academic purpouses.

Hardware & OS requirements:
---------------------------
Vini is the supercomputing applications and needs at least 10 cluster nodes to run smoothly.

For the prediction of protein structures, Vini offers a choice between two tools: AlphaFold and Swiss-Model. If AlphaFold is used, predictions can run in parallel, provided that the minimum memory size of each computing node is 128GB. Swiss-Model does not have such a limitation because the predictions are done on an external server. However, predictions are then executed sequentially, one by one.

Vini has been tested on RHEL 7, and CENTOS 7 and 8. The supported workload manager is SLURM.

Registering for third party programs and external databases/services:
----------------------------------------------------------------------
Vini uses third party programs and data from external databes and services. Registration for some of them is needed before running Vini. This registrations are free for academic institutions and approvals are tipically received within one hour or less.

It is strongly recommended that all registrations be done before starting Vini. Registration links:

Drugbank: https://go.drugbank.com/public_users/sign_up and register
Cosmic: https://cancer.sanger.ac.uk/cosmic/register and register
Swiss-Model: https://swissmodel.expasy.org/, pick <create account> in the right uper corner and register
Chimera: https://www.cgl.ucsf.edu/cgi-bin/chimera_registration.py and register
Rosetta: https://els2.comotion.uw.edu/product/rosetta

Installing and running Vini:
----------------------------
Download code from Git: git clone https://github.com/draskot/Vini

Start Vini (sh Vini) and follow the instructions.