2023 MOLECULAR GEOMETRY

 

 

MOLECULAR GEOMETRY TUTORIAL PLAYLIST (8 VIDEOS)

https://www.youtube.com/watch?v=OIgOdixkKLs&list=PLQin2YWXjZMgjW-HeR7p819nIpfTM7kVC
 

 

MOLECULAR GEOMETRY TOOLS

 

1. Open Babel is a free and open-source software library for chemical data conversion. It can be used to convert between a wide variety of chemical file formats, including molfiles, PDB files, and SMILES strings. It can also be used to generate molecular representations, such as 3D coordinates and bond topologies. Image of Open Babel software: https://open-babel.readthedocs.io/
    

2. RDKit is a free and open-source software library for cheminformatics. It can be used to perform a variety of cheminformatics tasks, including molecular structure manipulation, molecular property prediction, and machine learning. It also includes a variety of tools for molecular geometry analysis, such as calculating bond lengths, angles, and torsion angles. Image of RDKit software: https://www.rdkit.org/
    

3. NWChem is a free and open-source software package for quantum chemistry and molecular simulation. It can be used to perform a variety of quantum chemistry calculations, including electronic structure calculations, molecular dynamics simulations, and vibrational spectroscopy. It also includes a variety of tools for molecular geometry analysis, such as calculating bond lengths, angles, and torsion angles. Image of NWChem software: https://www.nwchem-sw.org/
    

4. Psi4 is a free and open-source software package for quantum chemistry and molecular physics. It can be used to perform a variety of quantum chemistry calculations, including electronic structure calculations, molecular dynamics simulations, and spectroscopic properties. It also includes a variety of tools for molecular geometry analysis, such as calculating bond lengths, angles, and torsion angles. Image of Psi4 software: https://psicode.org/
    

5. Avogadro is a free and open-source software package for molecular visualization and analysis. It can be used to visualize molecular structures in 2D and 3D, and to perform a variety of molecular analysis tasks, such as calculating bond lengths, angles, and torsion angles. Image of Avogadro software: https://avogadro.cc/
    

6. VMD is a free and open-source software package for molecular visualization and analysis. It can be used to visualize molecular structures in 2D and 3D, and to perform a variety of molecular analysis tasks, such as calculating bond lengths, angles, and torsion angles. It also includes a variety of tools for analyzing molecular dynamics simulations. Image of VMD software: https://www.ks.uiuc.edu/Research/vmd/
    

7. ChemDoodle3D: Chem Doodle 3D is a great way to visualize molecular geometry in 3D. https://www.chemdoodle.com/3d

 

OPEN SOURCE ARTIFICIAL INTELLIGENCE TOOLS FOR MOLECULAR GEOMETRY

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MolNet is a free and open-source machine learning benchmark for molecular property prediction. It provides a variety of datasets for training and evaluating machine learning models to predict molecular properties such as geometry, energy, and reactivity. MolNet is used by researchers in academia and industry to develop new machine learning methods for molecular property prediction. https://arxiv.org/abs/2203.09456
 

• OpenBabel is a free and open-source software library for chemical data conversion and analysis. It can be used to convert between a wide variety of chemical file formats, including molfiles, PDB files, and SMILES strings. OpenBabel can also be used to generate molecular representations, such as 3D coordinates and bond topologies, which can be used by machine learning models to predict molecular geometry. https://open-babel.readthedocs.io/
   

• RDKit is a free and open-source software library for cheminformatics. It can be used to perform a variety of cheminformatics tasks, including molecular structure manipulation, molecular property prediction, and machine learning. RDKit includes a variety of machine learning algorithms that can be used to predict molecular geometry, such as support vector machines (SVMs) and random forests. https://www.rdkit.org/
   

• ChemML is a free and open-source software library for machine learning in chemistry and materials science. It can be used to perform a variety of machine learning tasks for molecular geometry prediction, such as molecular property prediction, molecular design, and materials discovery. ChemML includes a variety of machine learning algorithms that can be used to predict molecular geometry, such as deep neural networks and graph neural networks. https://hachmannlab.github.io/chemml/
  
   

MOLECULAR GEOMETRY PREDICTION TOOLS
 

MolNet: MolNet is a machine learning benchmark for molecular property prediction, including geometry. It provides a variety of datasets for training and evaluating machine learning models to predict molecular properties.
 

1. OpenBabel: OpenBabel is a chemical data conversion and analysis software library. It can be used to convert between a wide variety of chemical file formats, including molfiles, PDB files, and SMILES strings. OpenBabel can also be used to generate molecular representations, such as 3D coordinates and bond topologies, which can then be used by machine learning models to predict molecular geometry.
    

2. RDKit: RDKit is a cheminformatics software library. It can be used to perform a variety of cheminformatics tasks, including molecular structure manipulation, molecular property prediction, and machine learning. RDKit includes a variety of machine learning algorithms that can be used to predict molecular geometry, such as support vector machines (SVMs) and random forests.
    

3. ChemML: ChemML is a software library for machine learning in chemistry and materials science. It can be used to perform a variety of machine learning tasks for molecular geometry prediction, such as molecular property prediction, molecular design, and materials discovery. ChemML includes a variety of machine learning algorithms that can be used to predict molecular geometry, such as deep neural networks and graph neural networks.
    

4. FEgrow: FEgrow is a workflow for building and scoring binding poses of congeneric ligands in protein binding pockets for input to free energy calculations. It can be used to predict the geometry of ligand-protein complexes.
    

5. MolGraph.jl: MolGraph.jl is a Julia library for graph-based molecule modeling. It can be used to manipulate and analyze molecular graphs, which can then be used to predict molecular geometry.
    

6. AtomsBase.jl: AtomsBase.jl is a Julia library for abstracting atomic structures. It provides a common interface for working with atomic structures, regardless of the specific implementation, which can be used to predict molecular geometry.
    

7. ChemistryFeaturization.jl: ChemistryFeaturization.jl is a Julia library for featurizing atomic structures. It can be used to convert atomic structures into feature vectors, which can then be used by machine learning models to predict molecular geometry.
    

8. OpenSMILES.jl: OpenSMILES.jl is a Julia library for parsing OpenSMILES strings. OpenSMILES is a chemical string notation that can be used to represent chemical structures, which can be used to predict molecular geometry.
    

9. Synchrony.jl: Synchrony.jl is a Julia library for calculating coherence and phase-locking statistics. This can be useful for tasks such as analyzing molecular dynamics simulations, which can be used to predict molecular geometry.
    

10. Auto3D: Auto3D is a tool for generating the low-energy 3D structures of molecules using ANI neural network potentials. It can be used to predict the geometry of molecules.

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MOLECULAR GEOMETRY TOPICS

 

• Valence shell electron pair repulsion (VSEPR) theory: This theory is used to predict the shapes of molecules based on the repulsion between valence electron pairs. The five basic shapes predicted by VSEPR theory are linear, trigonal planar, tetrahedral, trigonal bipyramidal, and octahedral.
   

• Hybridization: Hybridization is the mixing of atomic orbitals to form new orbitals with different shapes and energies. Hybridization is used to explain the shapes of molecules with more than two electron pairs around the central atom.
   

• Bond angles: Bond angles are the angles between adjacent bonds in a molecule. Bond angles are determined by the repulsion between electron pairs and the hybridization of the central atom.
   

• Dipole moments: A dipole moment is a measure of the separation of positive and negative charge in a molecule. Dipole moments are caused by the uneven distribution of electrons in a molecule.
   

• Molecular orbitals: Molecular orbitals are formed when atomic orbitals overlap. Molecular orbitals are used to describe the bonding and antibonding interactions between atoms in a molecule.
   

• Symmetry: Symmetry is a property of molecules that describes how they are arranged in space. Symmetry can be used to predict the properties of molecules, such as their bond angles and dipole moments.
   

• Intermolecular forces: Intermolecular forces are the forces that hold molecules together. The four main types of intermolecular forces are London dispersion forces, dipole-dipole interactions, hydrogen bonding, and ion-dipole interactions.
   

• Molecular spectroscopy: Molecular spectroscopy is the study of the interaction between electromagnetic radiation and molecules. Molecular spectroscopy can be used to determine the structure and composition of molecules.
   

• Computational chemistry: Computational chemistry is the use of computers to model and simulate chemical processes. Computational chemistry can be used to predict the shapes and properties of molecules.
   

Molecular geometry is a complex and fascinating subject with many subtopics. I hope this brief overview has given you a better understanding of the field.