Collection of computational Approaches and "Free" Resources to Assist Drug Discovery, Chemical Biology & Precision Medicine

Tools list: http://www.vls3d.com/links/51-shortlist

Src: http://www.vls3d.com/

#Tools
#DrugDiscovery
#Bioinformatics
#Cheminformatics
#StructureBioinformatics

channel: @llbschool

#ShareTool #StructureBioinformatics #MD

Learn how to energy Minimisation and prepare system in GROMAC'S using its new SAMSON tool.

https://documentation.samson-connect.net/gromacs-wizard/

#EBIStructural #VirtualWorkshop #StructureBioinformatics

Apply: https://www.ebi.ac.uk/training/events/2020/structural-bioinformatics-virtual

@llbschool

#InterestingArticle #StructureBioinformatics #AIDeNovo #MoleculeDesign

Develop a generative LSTM deep learning model for COVID-19 ligand molecule design and screening using Python, Google Colab and AutoDock Vina
https://medium.com/swlh/ai-de-novo-molecule-design-aed30465e293

@LetsLearnBioinformatics

#bioinformaticstips #structurebioinformatics

Martini md focused on membrane proteins:

https://youtu.be/7F5ujJyurfw
https://youtu.be/K-3pkzvaVSY
https://youtu.be/htY6nGxEBkI
https://youtu.be/enhBHBfA5NU
https://youtu.be/u3vKKBq4G6s

@letslearnbioinformatics

#dockingtools
#structurebioinformatics

Please find the list of Docking Softwares

Autodock. Free open source EA based docking software. Flexible ligand. Flexible protein side chains. Maintained by the Molecular Graphics Laboratory, The Scripps Research Institute, la Jolla.

DOCK. Anchor-and-Grow based docking program. Free for academic usage. Flexible ligand. Flexible protein. Maintained by the Soichet group at the UCSF.

GOLD. GA based docking program. Flexible ligand. Partial flexibility for protein. Product from a collaboration between the university of Sheffield, GlaxoSmithKline plc and CCDC.

SCIGRESS. Desktop/server molecular modeling software suite employing linear scaling semiempirical quantum methods for protein optimization and ligand docking. Developed and distributed by Fujitsu, Ltd.

GlamDock. Docking program based on a Monte-Carlo with minimization (basin hopping) search in a hybrid interaction matching / internal coordinate search space. Part of the Chil2 suite. Open for general research.

FlexAID. A small-molecule docking algorithm that accounts for target side-chain flexibility and utilizes a soft scoring function. The pairwise energy parameters were derived from a large dataset of true positive poses and negative decoys from the PDBbind database through an iterative process using Monte Carlo simulations. Precompiled Linux, MacOS and Windows versions are made available by the University of Sherbrooke, Canada.

GEMDOCK. Generic Evolutionary Method for molecular DOCKing. Program for computing a ligand conformation and orientation relative to the active site of target protein

iGEMDOCK. Graphic environment for the docking, virtual screening, and post-screening analysis. Free for non commercial researches. For Windows and Linux.

HomDock. Progam for similarity-based docking, based on a combination of the ligand based GMA molecular alignment tool and the docking tool GlamDock. Part of the Chil2 suite. Open for general research.

ICM. Docking program based on pseudo-Brownian sampling and local minimization. Ligand and protein flexible. Provided by MolSoft.

FlexX, Flex-Ensemble (FlexE). Incremental build based docking program. Flexible ligand. Protein flexibility through ensemble of protein structure. Provided by BioSolveIT.

Fleksy. Program for flexible and induced fit docking using receptor ensemble (constructed using backbone-dependent rotamer library) to describe protein flexibility. Provided by the Centre for Molecular and Biomolecular Informatics, Radboud University Nijmegen.

FITTED. (Flexibility Induced Through Targeted Evolutionary Description). Suite of programs to dock flexible ligands into flexible proteins. This software relies on a genetic algorithm to account for flexibility of the two molecules and location of water molecules, and on a novel application of a switching function to retain or displace water molecules and to form potential covalent bonds (covalent docking) with the protein side-chains. Part of the Molecular FORECASTER package and FITTED Suite. Free for an academic site license (excluding cluster).

VLifeDock. Multiple approaches for protein - ligand docking. Provides three docking approches: Grid based docking, GA docking and VLife's own GRIP docking program. Several scoring functions can be used: PLP score, XCscore and Steric + Electrostatic score. Available for Linux and Windows. Provided by VLife.

ParaDockS. (Parallel Docking Suite). Free, open source program, for docking small, drug-like molecules to a rigid receptor employing either the knowledge-based potential PMF04 or the empirical energy function p-Score.

DAIM-SEED-FFLD. Free open source fragment-based docking suite. The docking is realized in three steps. DAIM (Decomposition And Identification of Molecules) decomposes the molecules into molecular fragments that are docked using SEED (Program for docking libraries of fragments with solvation energy evaluation). Finally, the molecules are reconstructed ''in situ'' from the docked fragments using the FFLD program (Program for fragment-based flexible ligand docking). Deve

#llbfutura #structurebioinformatics

Send email to the given address in the image

@llbschool

#newtool #alphafold #deepmind #structurebioinformatics

This package provides an implementation of the contact prediction network, associated model weights and CASP13 dataset as published in Nature.

Any publication that discloses findings arising from using this source code must cite Improved protein structure prediction using potentials from deep learning

The paper abstract can be found on Nature's site 10.1038/s41586-019-1923-7 and the full text can be accessed directly at https://rdcu.be/b0mtx.

Github source file:
https://github.com/deepmind/deepmind-research/tree/master/alphafold_casp13

@letslearnbioinformatics

#toolsperweek #structurebioinformatics #surfaceracer #loopsandstrands #protocols

Surface Racer calculates exact accessible surface area, molecular surface area and average curvature of molecular surface for macromolecules. The program also analyzes cavities in the protein interior inaccessible to solvent from outside. The output includes the surface parameters for each residue in addition to those for individual atoms.

This software could be an option to validate protein-protein docking where the docking poses can be filtered based on the least surface area between two protein chains/objects

LOOPS & STRANDS - Bioinformatics Protocols www.llbschool.org/magazine

@letslearnbioinformatics

#toolsperweek #structurebioinformatics #surfaceracer #loopsandstrands #protocols

Estimating the Solvent Accessible Surface Area of a Protein-Protein Complex

SOURCE:
https://tsodikovlab.createuky.net/index_files/Surface_Racer.htm

INSTALLATION:
1. Download it from here https://tsodikovlab.createuky.net/index_files/Surface_Racer.htm
2. Extract the downloaded file
3. Place all the input structures under the extracted directory name 'SURFACE_RACER_5_0'
4. Execute the below command

COMMAND:
./surface_Racer a input.pdb r m

-a Van del Waals radii sets
(you can choose either 1 - Richards (1977) or 2 - Chothia (1976)

Input.pdb

r Input the probe radius in Angstroms
(which is usually 1.4)

m Enter a number to choose the calculation mode
This can be either one below
1- Accessible surface area only
2- Accessible and molecular surface areas
3- Accessible, molecular surface areas and average curvature of MS

You get the output in result.txt where you can find the Molecular Surface Area (MSA)

Stay tuned for more Bioinformatics protocols
LOOPS & STRANDS: www.llbschool.org/magazine

@letslearnbioinformatics

#loopsnstrands #protocol #alphafold #structureprediction #structurebioinformatics

Article by our previous NyBerMan Bioinformatics Internship Student on
Protein structure prediction using AlphaFold2 Pipeline (Jupyter-Notebook)

✍️Preview:
Deep learning tools have a considerable impact on protein structure prediction. Algorithms like AlphaFold2 can help understand and visualise protein structures not presented in Protein Data Bank. Also, this acceptable method allows generating tons of new data with relatively small costs. Cloud Computing services such as Microsoft Azure Machine Learning make experiment submission much easier and faster. In a couple of words, these services provide researchers with a powerful tool for implementing very complicated tasks like protein structure prediction. In summary, my experiment gave satisfactory results for a full-fledged pipeline of my internship. This work can be used in similar further research and development.

Author:
@gr0mdim0n

📚Read the full length Article on our Bio-IT magazine: Loops & Strands
https://loopsnstrands.com/protein-structure-prediction-using-alphafold2-ea2b7949d96e

👥Follow our Bio-IT Magazine
https://loopsnstrands.com/

#webinar #haddock #proprodock #structurebioinformatics

Webinar on new version of HADDOCK,
a versatile information-driven docking software. HADDOCK 3.0 is a complete rewrite and rethinking of HADDOCK, focused on flexibility, scalability, and user experience

📅 June 7th, 15:00 CEST.

🌐For more info
https://bioexcel.eu/webinar-introducing-haddock3-enabling-modular-integrative-modelling-pipelines-2022-05-24/

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Channel @llbschool
Forum @letslearnbioinformatics

#resource #structurebioinformatics

HOW TO RUN MD SIMULATIONS THROUGH GALAXY ?

Molecular dynamics (MD) is a method to simulate molecular motion by iterative application of Newton’s laws of motion. This tutorial provides an introduction to using high-throughput molecular dynamics to study protein-ligand interaction, as applied to the N-terminal domain of Hsp90 (heat shock protein 90).

🎥 WATCH VIDEO HERE:
https://www.youtube.com/watch?v=LjW3nES04bI&t=1289s

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Channel @llbschool
Forum @letslearnbioinformatics

#internship #structurebioinformatics

INTERNATIONAL VIRTUAL INTERNSHIP ON STRUCTURAL BIOINFORMATICS DOMAINS

🎯Outcomes:
- We provide a platform to learn the majority of Structural Bioinformatics domains such as Computer-Aided Drug Design (CADD), MD Simulations, and Membrane Simulations using CHARMM-GUI
- General Modules covered during the Internship
- Great opportunity to expand network with international students
- Chance To get International Standard Certification

👨🏻‍💼👩‍🏫 Highly Skilled Tutors
- Dr. Fayyaz, Centre for Computational Biology, University of Birmingham, UK
- Ms. Hemavathy N, Ph.D. III year, NyBerMan Structural Bioinformatics, India

👩‍🎓Qualifications:
Anyone interested in learning Structural Bioinformatics

💰Payment and Package details

🌐 Register at
https://tinyurl.com/4pjtvbs2

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Channel @llbschool
Forum @letslearnbioinformatics

#internshipalert #structurebioinformatics #france

Master internship in Computational Chemistry, France
Starting from Feb. 2023 , for 5-6 months

Title of the internship:
Development of CHARMM force field compatible set of parameters to study neonicotinoids with molecular dynamics.

🌐For more info:
https://www.instagram.com/p/CkqPo8TLj8x/?utm_source=ig_web_copy_link

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👉 Follow our Insta page for more exclusive job updates https://www.instagram.com/nybermanbioinfo/

#resource #structurebioinformatics #cheminfi #molplotly

Introducing molplotly, an add-on to plotly using RDKit that draws molecules on mouseover!

Say goodbye to pandas SMILES querying just to figure out what molecule is where :)

✳️Get it through:
"pip install molplotly", or
https://github.com/wjm41/molplotly

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