From d8d2c56b90bb2e05b13deb8f63308a0f6dbf38ca Mon Sep 17 00:00:00 2001 From: promptadmin Date: Sat, 8 Aug 2026 15:31:06 +0000 Subject: [PATCH] [upstream-sync] README.md from yboulaamane/awesome-drug-discovery@4815deff [catalogue] --- .../catalogue/README.md | 208 +++++++----------- 1 file changed, 85 insertions(+), 123 deletions(-) diff --git a/upstream/yboulaamane-awesome-drug-discovery/catalogue/README.md b/upstream/yboulaamane-awesome-drug-discovery/catalogue/README.md index 66dd5875..0d39f03d 100644 --- a/upstream/yboulaamane-awesome-drug-discovery/catalogue/README.md +++ b/upstream/yboulaamane-awesome-drug-discovery/catalogue/README.md @@ -2,9 +2,9 @@ title: "Awesome Drug Discovery [![Awesome](https://awesome.re/badge.svg)](https://awesome.re)" task: "" lineage_type: import -upstream_source: https://github.com/yboulaamane/awesome-drug-discovery/blob/1b8ee074/README.md -upstream_sha: 1b8ee074 -imported_at: 2026-07-16 +upstream_source: https://github.com/yboulaamane/awesome-drug-discovery/blob/4815deff/README.md +upstream_sha: 4815deff +imported_at: 2026-08-08 prompt_class: catalogue upstream_changes: accepted author: upstream @@ -12,62 +12,56 @@ validated: false --- # Awesome Drug Discovery [![Awesome](https://awesome.re/badge.svg)](https://awesome.re) -A meticulously curated resource list focused on computational methods for drug discovery. +Computational methods for identifying and developing new drug candidates. > Drug discovery is the process by which new candidate medications are identified, designed, and developed using experimental, computational, and informational techniques to address complex challenges in biology, chemistry, and medicine. — [Wikipedia](https://en.wikipedia.org/wiki/Drug_discovery) ---- - ## Contents -- [Databases and Chemical Libraries](#databases-and-chemical-libraries) - - [General Compound Libraries](#general-compound-libraries) - - [Natural Product Libraries](#natural-product-libraries) - - [Bioactivity Databases](#bioactivity-databases) -- [Target and Protein Data](#target-and-protein-data) - - [Protein Structures](#protein-structures) - - [Binding Site and Pocket Detection](#binding-site-and-pocket-detection) +- [Databases and Chemical Libraries](#databases-and-chemical-libraries) + - [General Compound Libraries](#general-compound-libraries) + - [Natural Product Libraries](#natural-product-libraries) + - [Bioactivity Databases](#bioactivity-databases) +- [Target and Protein Data](#target-and-protein-data) + - [Protein Structures](#protein-structures) + - [Binding Site and Pocket Detection](#binding-site-and-pocket-detection) - [Protein Engineering and Modeling](#protein-engineering-and-modeling) -- [Network Pharmacology](#network-pharmacology) -- [Ligand Design and Optimization](#ligand-design-and-optimization) - - [Pharmacophore Modeling](#pharmacophore-modeling) - - [QSAR and Descriptor Tools](#qsar-and-descriptor-tools) +- [Network Pharmacology](#network-pharmacology) +- [Ligand Design and Optimization](#ligand-design-and-optimization) + - [Pharmacophore Modeling](#pharmacophore-modeling) + - [QSAR and Descriptor Tools](#qsar-and-descriptor-tools) - [Descriptor and Featurization Tools](#descriptor-and-featurization-tools) - - [Molecular Property Prediction](#molecular-property-prediction) - - [Fragment-Based Drug Design](#fragment-based-drug-design) -- [Virtual Screening and Docking](#virtual-screening-and-docking) -- [Interaction Analysis and Visualization](#interaction-analysis-and-visualization) -- [Molecular Dynamics and Simulation](#molecular-dynamics-and-simulation) - - [Engines](#engines) - - [Topology and Force Field Tools](#topology-and-force-field-tools) - - [Analysis Tools](#analysis-tools) -- [Synthesis and Retrosynthesis Planning](#synthesis-and-retrosynthesis-planning) -- [Specialized Modalities](#specialized-modalities) - - [PROTACs and Ternary Complexes](#protacs-and-ternary-complexes) - - [Peptide Design](#peptide-design) -- [Machine Learning and AI](#machine-learning-and-ai) - - [Core Libraries](#core-libraries) - - [Chemistry-focused ML Frameworks](#chemistry-focused-ml-frameworks) - - [Pretrained Models](#pretrained-models) - - [AutoML and Optimization](#automl-and-optimization) - - [Molecule Standardization](#molecule-standardization) -- [Utility and Workflow Tools](#utility-and-workflow-tools) -- [Learning Resources](#learning-resources) - - [Free Courses](#free-courses) - - [Blogs](#blogs) + - [Molecular Property Prediction](#molecular-property-prediction) + - [Fragment-Based Drug Design](#fragment-based-drug-design) +- [Virtual Screening and Docking](#virtual-screening-and-docking) +- [Interaction Analysis and Visualization](#interaction-analysis-and-visualization) +- [Molecular Dynamics and Simulation](#molecular-dynamics-and-simulation) + - [Engines](#engines) + - [Topology and Force Field Tools](#topology-and-force-field-tools) + - [Analysis Tools](#analysis-tools) +- [Synthesis and Retrosynthesis Planning](#synthesis-and-retrosynthesis-planning) +- [Specialized Modalities](#specialized-modalities) + - [PROTACs and Ternary Complexes](#protacs-and-ternary-complexes) + - [Peptide Design](#peptide-design) +- [Machine Learning and AI](#machine-learning-and-ai) + - [Chemistry-focused ML Frameworks](#chemistry-focused-ml-frameworks) + - [Pretrained Models](#pretrained-models) + - [Molecule Standardization](#molecule-standardization) +- [Utility and Workflow Tools](#utility-and-workflow-tools) +- [Learning Resources](#learning-resources) + - [Free Courses](#free-courses) + - [Blogs](#blogs) - [Instructional Notebooks](#instructional-notebooks) - [Labs and Research Groups](#labs-and-research-groups) ---- - ## Databases and Chemical Libraries ### General Compound Libraries - [DrugBank](https://go.drugbank.com/) - Comprehensive data on approved and investigational drugs. -- [ZINC](https://zinc.docking.org/) - Free compounds for screening. -- [ChemSpider](http://www.chemspider.com/) - Chemical structures and data. -- [DrugSpaceX](https://drugspacex.simm.ac.cn/) - Chemical and biological spaces. -- [Mcule](https://mcule.com/) - Virtual screening platform with purchasable compounds. -- [Otava Chemicals](https://www.otavachemicals.com/) - Screening compounds and building blocks. +- [ZINC](https://zinc.docking.org/) - Free compounds for screening. +- [ChemSpider](http://www.chemspider.com/) - Chemical structures and data. +- [DrugSpaceX](https://drugspacex.simm.ac.cn/) - Chemical and biological spaces. +- [Mcule](https://mcule.com/) - Virtual screening platform with purchasable compounds. +- [Otava Chemicals](https://www.otavachemicals.com/) - Screening compounds and building blocks. - [Vitas-M Laboratory](https://vitasmlab.biz/) - Chemical libraries for HTS and lead discovery. - [Eximed](https://eximedlab.com/Screening-Compounds.html) - 60k+ compounds for virtual screening. - [OTAVA NP-like Library](https://otavachemicals.com/sdf) - Screening compounds for prompt delivery. @@ -75,34 +69,32 @@ A meticulously curated resource list focused on computational methods for drug d - [VAST Chemical Space](https://www.aifchem.com/vast) - 4.6 billion synthetically accessible compounds for virtual screening and hit expansion. ### Natural Product Libraries -- [ZINC15 Natural Products](https://zinc15.docking.org/substances/subsets/natural-products/) - 200k+ natural compounds. -- [COCONUT](https://coconut.naturalproducts.net/) - 400k+ natural products. -- [LOTUS](https://lotus.naturalproducts.net/) - Annotated molecular data with sourcing organisms. -- [NPASS](http://bidd.group/NPASS/index.php) - 94k activity-species links. -- [ANPDB](https://phabidb.vm.uni-freiburg.de/anpdb/) - 27k+ African medicinal plant compounds. -- [SANCDB](https://sancdb.rubi.ru.ac.za/) - Natural compounds from the plant and marine life in and around South Africa. -- [CMNPD](https://www.cmnpd.org/) - 31k+ marine natural products. -- [The Natural Products Atlas](https://www.npatlas.org/) - An open-access database for microbial natural products structures and metadata. -- [CoumarinDB](https://yboulaamane.github.io/CoumarinDB/) - A manually curated database on coumarins from plants. -- [ArtemisiaDB](https://yboulaamane.github.io/ArtemisiaDB/) - Artemisia genus compounds. -- [BIAdb](https://webs.iiitd.edu.in/raghava/biadb/type.php?tp=natural) - A database for benzylisoquinoline alkaloids. -- [IMPPAT](https://cb.imsc.res.in/imppat/home) - Phytochemicals from Indian medicinal plants. -- [NP-MRD](https://np-mrd.org/natural_products) - 280k+ NMR-based NP studies. -- [IBS Natural Compounds](https://www.ibscreen.com/natural-compounds) - 60k+ compounds. -- [PhytoHub](https://phytohub.eu/) - Dietary phytochemicals and metabolites. -- [Dr. Duke's Phytochemical DB](https://phytochem.nal.usda.gov/) - Plant compounds and uses. -- [CyanoMetDB](https://zenodo.org/records/13854577) - Over 3,000 cyanobacterial metabolites. -- [Seaweed Metabolite DB](https://www.swmd.co.in/) - Marine algae compounds. -- [FooDB](https://foodb.ca/) - A comprehensive resource on food constituents. +- [ZINC15 Natural Products](https://zinc15.docking.org/substances/subsets/natural-products/) - 200k+ natural compounds. +- [COCONUT](https://coconut.naturalproducts.net/) - 400k+ natural products. +- [LOTUS](https://lotus.naturalproducts.net/) - Annotated molecular data with sourcing organisms. +- [NPASS](http://bidd.group/NPASS/index.php) - 94k activity-species links. +- [ANPDB](https://phabidb.vm.uni-freiburg.de/anpdb/) - 27k+ African medicinal plant compounds. +- [SANCDB](https://sancdb.rubi.ru.ac.za/) - Natural compounds from the plant and marine life in and around South Africa. +- [CMNPD](https://www.cmnpd.org/) - 31k+ marine natural products. +- [The Natural Products Atlas](https://www.npatlas.org/) - An open-access database for microbial natural products structures and metadata. +- [BIAdb](https://webs.iiitd.edu.in/raghava/biadb/type.php?tp=natural) - A database for benzylisoquinoline alkaloids. +- [IMPPAT](https://cb.imsc.res.in/imppat/home) - Phytochemicals from Indian medicinal plants. +- [NP-MRD](https://np-mrd.org/natural_products) - 280k+ NMR-based NP studies. +- [IBS Natural Compounds](https://www.ibscreen.com/natural-compounds) - 60k+ compounds. +- [PhytoHub](https://phytohub.eu/) - Dietary phytochemicals and metabolites. +- [Dr. Duke's Phytochemical DB](https://phytochem.nal.usda.gov/) - Plant compounds and uses. +- [CyanoMetDB](https://zenodo.org/records/13854577) - Over 3,000 cyanobacterial metabolites. +- [Seaweed Metabolite DB](https://www.swmd.co.in/) - Marine algae compounds. +- [FooDB](https://foodb.ca/) - A comprehensive resource on food constituents. ### Bioactivity Databases -- [ChEMBL](https://www.ebi.ac.uk/chembl/) - Bioactivity and ADMET data. -- [SureChEMBL](https://www.surechembl.org/) - Patent chemistry search. -- [BindingDB](https://www.bindingdb.org/) - Binding affinities for biomolecules. -- [PubChem](https://pubchem.ncbi.nlm.nih.gov/) - Structures, properties, and bioassays. -- [PDBbind](http://www.pdbbind.org.cn/index.php) - Protein-ligand affinity data. -- [BRENDA](https://www.brenda-enzymes.org/) - Enzyme properties and functions. -- [ExCAPE-DB](https://solr.ideaconsult.net/search/excape/) - A large-scale chemogenomics database. +- [ChEMBL](https://www.ebi.ac.uk/chembl/) - Bioactivity and ADMET data. +- [SureChEMBL](https://www.surechembl.org/) - Patent chemistry search. +- [BindingDB](https://www.bindingdb.org/) - Binding affinities for biomolecules. +- [PubChem](https://pubchem.ncbi.nlm.nih.gov/) - Structures, properties, and bioassays. +- [PDBbind](http://www.pdbbind.org.cn/index.php) - Protein-ligand affinity data. +- [BRENDA](https://www.brenda-enzymes.org/) - Enzyme properties and functions. +- [ExCAPE-DB](https://solr.ideaconsult.net/search/excape/) - A large-scale chemogenomics database. - [Therapeutics Data Commons](https://tdcommons.ai/) - AI/ML-ready datasets and learning tasks for therapeutics. - [Therapeutic Target Database (TTD)](https://idrblab.net/ttd/) - Drug targets with linked diseases and compounds. - [Aircheck Datasets](https://aircheck.ai/datasets) - Curated DEL datasets for AI‑driven drug discovery, enabling benchmarking and model development. @@ -112,8 +104,6 @@ A meticulously curated resource list focused on computational methods for drug d - [CovalentInDB (CIDB)](https://cadd.zju.edu.cn/cidb/) - A comprehensive database dedicated to covalent inhibitors, targets, and experimental data. - [HSADab](https://github.com/proszxppp/HSADab) - Database of binding thermodynamics, structures, and docking data for human serum albumin. ---- - ## Target and Protein Data ### Protein Structures @@ -145,8 +135,6 @@ A meticulously curated resource list focused on computational methods for drug d - [RFdiffusion](https://github.com/RosettaCommons/RFdiffusion) - Open-source method for de novo protein design using structure-guided diffusion models. - [Melodia](https://github.com/rwmontalvao/Melodia_py) - Python library for analyzing and comparing protein structure shapes via differential geometry. ---- - ## Network Pharmacology - [GeneCards](https://www.genecards.org/) - Human gene database with genomic, proteomic, and clinical data. - [SwissTargetPrediction](http://www.swisstargetprediction.ch/) - Predicts targets of small molecules via similarity-based screening. @@ -165,8 +153,6 @@ A meticulously curated resource list focused on computational methods for drug d - [Polypharmacology Browser PPB3](https://ppb3.gdb.tools/) - Deep learning tool predicting off-target effects and polypharmacology for bioactive molecules. - [Drug-Target Interaction Explorer](https://github.com/yashhhhhhhhh504/Drug-Target-Interaction-Explorer) - Dashboard for exploring and visualizing drug-target interaction networks. ---- - ## Ligand Design and Optimization ### Pharmacophore Modeling @@ -184,11 +170,11 @@ A meticulously curated resource list focused on computational methods for drug d - [pyADA](https://github.com/jeffrichardchemistry/pyADA) - Assesses the applicability domain of molecular fingerprints via similarity-based thresholds for QSAR validation. ### Descriptor and Featurization Tools -- [RDKit](https://www.rdkit.org/) - Open-source cheminformatics toolkit with descriptor, fingerprint, and molecular manipulation support. -- [PaDEL-Descriptor](http://www.yapcwsoft.com/dd/padeldescriptor/) - Java tool for calculating molecular descriptors and fingerprints. -- [Mordred](https://github.com/mordred-descriptor/mordred) - Python library with 1800+ molecular descriptors. -- [CDK](https://cdk.github.io/) - Java cheminformatics library with descriptor calculators. -- [alvaDesc](https://www.alvascience.com/alvadesc/) - Commercial software for molecular descriptors and fingerprints. +- [RDKit](https://www.rdkit.org/) - Open-source cheminformatics toolkit with descriptor, fingerprint, and molecular manipulation support. +- [PaDEL-Descriptor](http://www.yapcwsoft.com/dd/padeldescriptor/) - Java tool for calculating molecular descriptors and fingerprints. +- [Mordred](https://github.com/mordred-descriptor/mordred) - Python library with 1800+ molecular descriptors. +- [CDK](https://cdk.github.io/) - Java cheminformatics library with descriptor calculators. +- [alvaDesc](https://www.alvascience.com/alvadesc/) - Commercial software for molecular descriptors and fingerprints. - [MolFeat](https://molfeat.datamol.io/) - Python package for molecular featurization and embeddings. - [Dragon](https://www.talete.mi.it/products/dragon_description.htm) - Commercial molecular descriptor calculator (widely cited). - [ChemDescriptor](https://github.com/darkreactions/chemdescriptor) - Open-source tool for generating chemical descriptors and fingerprints, supporting cheminformatics workflows. @@ -210,13 +196,11 @@ A meticulously curated resource list focused on computational methods for drug d - [SwissSidechain](https://www.swisssidechain.ch/) - Fragment and linker library for small molecule design. - [BoBER](http://bober.insilab.org/) - Bioisosteric replacements for lead optimization. -- [FragBuilder](https://github.com/andersx/fragbuilder) - Python API for building peptide-like and small molecule fragments. +- [FragBuilder](https://github.com/andersx/fragbuilder) - Python API for building peptide-like and small molecule fragments. - [SeeSAR](https://www.biosolveit.de/SeeSAR/) - Fragment growing and linking software (free academic version). - [Enamine Fragment Libraries](https://enamine.net/compound-libraries/fragment-libraries) - Large curated collection of diverse fragments for FBDD. - [FragmentFinder](https://github.com/1JELC1/FragmentFinder) - Computational tool for identifying and matching structural fragments in drug discovery workflows. ---- - ## Virtual Screening and Docking - [OpenBabel](https://openbabel.org/index.html) - Format conversion and ligand prep. - [Meeko](https://github.com/forlilab/Meeko) - Prepares ligands/receptors for AutoDock by assigning partial charges and atom types. @@ -225,8 +209,8 @@ A meticulously curated resource list focused on computational methods for drug d - [AutoDockTools](https://autodocksuite.scripps.edu/adt/) - AutoDock GUI. - [AutoDock Vina](https://vina.scripps.edu/) - Popular docking software. - [AutoDock-GPU](https://github.com/ccsb-scripps/AutoDock-GPU) - GPU-accelerated version of AutoDock for faster ligand-receptor docking. -- [DiffDock](https://github.com/gcorso/DiffDock) - Deep learning-based docking tool that predicts ligand poses directly from protein structures using diffusion models. -- [EasyDockVina2](https://github.com/S3cr3t-SDN/EasyDockVina2) - Vina automation. +- [DiffDock](https://github.com/gcorso/DiffDock) - Deep learning-based docking tool that predicts ligand poses directly from protein structures using diffusion models. +- [EasyDockVina2](https://github.com/S3cr3t-SDN/EasyDockVina2) - Vina automation. - [Webina](https://durrantlab.pitt.edu/webina/) - Web-based Vina. - [Smina](https://github.com/mwojcikowski/smina) - Vina fork with extra features. - [Gnina](https://github.com/gnina/gnina) - CNN-scoring docking. @@ -244,8 +228,6 @@ A meticulously curated resource list focused on computational methods for drug d - [Chopdock](https://github.com/JanoschMenke/chopdock) - Molecular docking and cheminformatics tool for structural interaction analysis and fragment-based design. - [Boltzmann Maps](https://boltzmannmaps.com/) - Web application for structure-guided drug design using pre-computed water and chemical fragment maps. ---- - ## Interaction Analysis and Visualization - [PLIP](https://plip-tool.biotec.tu-dresden.de/plip-web/plip/index) - Protein-ligand interaction profiling. - [posecheck-fast](https://github.com/LigandPro/posecheck-fast) - High-throughput docking pose validation with symmetry-corrected RMSD and lightweight distance and clash filters. @@ -258,8 +240,6 @@ A meticulously curated resource list focused on computational methods for drug d - [xyzrender](https://github.com/aligfellow/xyzrender) - CLI for producing publication-quality molecular graphics, GIFs, and SVGs from coordinate files. - [pymol-sifts](https://github.com/connyyu/pymol_sifts/) - PyMOL plugin for integrating and visually mapping SIFTS structural and sequence data. ---- - ## Molecular Dynamics and Simulation ### Engines @@ -290,8 +270,6 @@ A meticulously curated resource list focused on computational methods for drug d - [cmd-viewer](https://github.com/Kopec-Lab/cmd-viewer) - Tool for visualizing and analyzing MD simulation trajectories and structural data. - [Pharmacon](https://github.com/k-georgiou/pharmacon) - Open-source toolkit for molecular dynamics simulation analysis in medicinal chemistry. ---- - ## Synthesis and Retrosynthesis Planning - [Spaya](https://spaya.ai/app/search) - AI-driven retrosynthesis engine with route ranking and synthetic feasibility scoring. - [AiZynthFinder](https://github.com/MolecularAI/aizynthfinder) - Monte Carlo tree search-based retrosynthesis using trained neural networks. @@ -300,8 +278,6 @@ A meticulously curated resource list focused on computational methods for drug d - [MANIFOLD](https://postera.ai/) - Search engine for synthetically accessible molecules and building blocks. - [onepot.ai](https://www.onepot.ai/) - AI-enabled molecular editor and synthesis planning platform with an encrypted structure environment. ---- - ## Specialized Modalities ### PROTACs and Ternary Complexes @@ -313,23 +289,11 @@ A meticulously curated resource list focused on computational methods for drug d - [PEP-SiteFinder](https://bioserv.rpbs.univ-paris-diderot.fr/services/PEP-SiteFinder/) - Predicts peptide-binding sites on protein structures using drug-like ligand mapping. - [PEP-FOLD3](https://bioserv.rpbs.univ-paris-diderot.fr/services/PEP-FOLD3/) - De novo peptide structure prediction framework. ---- - ## Machine Learning and AI -### Core Libraries -- [scikit-learn](https://scikit-learn.org/) - General-purpose ML library for classification, regression, clustering, and model evaluation. -- [PyTorch](https://pytorch.org/) - Deep learning framework with extensive support for neural network modeling. -- [TensorFlow](https://www.tensorflow.org/) - End-to-end ML platform for scalable model development and deployment. -- [Keras](https://keras.io/) - High-level neural network API running on top of TensorFlow, designed for fast experimentation. -- [NumPy](https://numpy.org/) - Core library for numerical computing with support for arrays, matrices, and linear algebra. -- [Pandas](https://pandas.pydata.org/) - Data manipulation and analysis toolkit built on top of NumPy. -- [Matplotlib](https://matplotlib.org/) - Comprehensive library for creating static, animated, and interactive visualizations in Python. -- [Seaborn](https://seaborn.pydata.org/) - Statistical data visualization library built on top of Matplotlib. - ### Chemistry-focused ML Frameworks - [DeepChem](https://github.com/deepchem/deepchem) - Open-source deep learning framework for chemistry and biology. -- [scikit-mol](https://github.com/EBjerrum/scikit-mol) - Open-source toolkit bridging RDKit and scikit-learn for molecular ML workflows. +- [scikit-mol](https://github.com/EBjerrum/scikit-mol) - Open-source toolkit bridging RDKit and scikit-learn for molecular ML workflows. - [Chemprop](https://github.com/chemprop/chemprop) - Directed message passing neural networks for molecular property prediction. - [ChemML](https://github.com/hachmannlab/chemml) - Machine learning and informatics suite for analyzing, mining, and modeling chemical and materials data. - [Oloren ChemEngine](https://pypi.org/project/olorenchemengine/) - Unified API for molecular property prediction with uncertainty quantification, interpretability, and model tuning. @@ -348,17 +312,10 @@ A meticulously curated resource list focused on computational methods for drug d - [Boltz-2](https://github.com/jwohlwend/boltz) - A foundation model that jointly predicts structure and binding affinity, rivaling physics-based FEP methods in accuracy. - [Zatom](https://github.com/Zatom-AI/zatom) - AI-driven generative chemistry platform for discovering and analyzing molecular structures. -### AutoML and Optimization -- [Auto-sklearn](https://automl.github.io/auto-sklearn/master/) - Automated machine learning for scikit-learn. -- [TPOT](https://epistasislab.github.io/tpot/) - Genetic programming-based AutoML for optimizing ML pipelines. -- [Optuna](https://optuna.org/) - Hyperparameter optimization framework for machine learning. - ### Molecule Standardization - [MolVS](https://github.com/mcs07/MolVS) - Molecule validation and standardization library based on RDKit. - [cleanmol](https://github.com/nurtilekgalimov/cleanmol) - Python library for cleaning, standardizing, and preparing molecular structures for cheminformatics workflows. ---- - ## Utility and Workflow Tools - [ProteinsPlus](https://proteins.plus/) - A web-based platform designed to assist life scientists in analyzing and working with protein structures. - [OPSIN](https://opsin.ch.cam.ac.uk) - Convert IUPAC names to chemical structures. @@ -391,8 +348,6 @@ A meticulously curated resource list focused on computational methods for drug d - [PyChem-Pro](https://github.com/vijaymasand/PyChem-Pro) - Pure-Python desktop application for molecular visualization, geometry optimization, and cheminformatics. - [rdkit-agent](https://github.com/scottmreed/rdkit-agent) - Agent-first cheminformatics CLI powered by RDKit WASM for structure validation and format conversion. ---- - ## Learning Resources ### Free Courses @@ -408,6 +363,10 @@ A meticulously curated resource list focused on computational methods for drug d - [MDTutorials](http://www.mdtutorials.com/gmx/) - Step-by-step tutorials for MD simulations using GROMACS. - [Resources for Learning Bioinformatics](https://learnbioinformatics.org/) - Curated collection of tutorials and materials for bioinformatics and computational biology. - [Synthesis Workshop](https://synthesis-workshop.com/) - Open-access video podcast on advanced organic synthesis and medicinal chemistry. +- [AI for Chemistry (ai4chem Book)](https://zzhenglab.github.io/ai4chem/intro.html) - An open-access book and interactive guide to machine learning and AI in chemistry. +- [AI for Chemistry Course](https://github.com/schwallergroup/ai4chem_course) - Lecture slides, Jupyter notebooks, and exercises for machine learning in chemistry. +- [CCAS Training Materials](https://ccas.nd.edu/research/training-materials/) - Training resources for computer-assisted synthesis tools, reaction modeling, and machine learning. +- [ML in Chemistry (CHEM 542)](https://sites.rutgers.edu/sun-lab/teach-chem542/) - Rutgers University course materials covering machine learning applications in chemical sciences. ### Blogs - [Practical Fragments](http://practicalfragments.blogspot.com/) - Insights into fragment-based drug discovery. @@ -424,8 +383,12 @@ A meticulously curated resource list focused on computational methods for drug d - [Jeremy Monat](https://bertiewooster.github.io/) - Cheminformatics research and academic resources. - [RDKit blog](https://greglandrum.github.io/rdkit-blog/) - A rich collection of tutorials, technical tips, and experimental insights from Greg Landrum. - [DeepMedChem](https://www.deepmedchem.com/) - AI-powered insights, tool reviews, and workflows for modern drug discovery. +- [The Data Chemist's Handbook](https://data-chemist-handbook.github.io/) - A curated handbook with guidelines, code snippets, and tools for data-driven chemistry. +- [Awesome Learning Digital Chemistry](https://github.com/mlederbauer/awesome-learning-digital-chemistry) - Curated compilation of resources for learning digital chemistry, including courses, tutorials, and books. +- [CCAS Data sets, Tools, and Workflows](https://ccas.nd.edu/research/data-sets-tools-and-workflows/) - A repository of datasets and computational workflows for computer-assisted organic synthesis. ### Instructional Notebooks +- [DeepChem Tutorials](https://github.com/deepchem/deepchem/tree/master/examples/tutorials) - Comprehensive set of tutorials covering deep learning for chemistry, biology, and materials science. - [TeachOpenCADD](https://projects.volkamerlab.org/teachopencadd/all_talktorials.html) - Modular Jupyter tutorials for CADD workflows and concepts. - [intro_pharma_ai](https://github.com/kochgroup/intro_pharma_ai) - Notebook-based introduction to AI applications in pharma. - [Practical Cheminformatics Tutorials](https://github.com/PatWalters/practical_cheminformatics_tutorials) - Hands-on Jupyter tutorials for RDKit, SAR, clustering, generative models, and ML pipelines. @@ -438,18 +401,17 @@ A meticulously curated resource list focused on computational methods for drug d - [Carlsson Lab](https://www.carlssonlab.org/) - GPCR modeling, receptor-ligand interactions, MD, docking, and AI for drug discovery. (Uppsala University, Sweden) - [InSiliChem](https://insilichem.com/) - Computational chemobiology and metalloenzyme design. (Universitat Autònoma de Barcelona, Spain) -- [LCBC](https://sites.google.com/view/lcbc) - Molecular dynamics, free energy calculations, retrosynthesis using machine learning. (Seoul National University, Korea) +- [LCBC](https://sites.google.com/view/lcbc) - Molecular dynamics, free energy calculations, retrosynthesis using machine learning. (Seoul National University, Korea) - [Angelo Raymond Rossi](https://angeloraymondrossi.github.io/) - High-performance computing for computational chemistry and cheminformatics. (University of Connecticut, USA) - [Laboratory of Chemoinformatics](https://complex-matter.unistra.fr/en/research-teams/laboratory-of-chemoinformatics/team/) - QSAR/QSPR, chemical similarity, and virtual screening. (Université de Strasbourg / CNRS, France) - [Erastova Lab](https://www.erastova.xyz/) - Molecular modeling of soft matter and biomolecular simulations. (University of Edinburgh, UK) - [The Ballester Group](https://ballestergroup.github.io/) - Developing ML/AI methods for structure-based scoring and virtual screening. (Imperial College London, UK) - [Meiler Lab](https://meilerlab.org/) - Rosetta software, protein design, and ML-based protein engineering. (Vanderbilt / Leipzig University, USA / Germany) -- [COMP3D](https://comp3d.univie.ac.at/) - Develops and applies AI methods to design safe, effective pharmaceuticals and agrochemicals. (University of Vienna, Austria) +- [COMP3D](https://comp3d.univie.ac.at/) - Develops and applies AI methods to design safe, effective pharmaceuticals and agrochemicals. (University of Vienna, Austria) +- [Dral Group](http://dr-dral.com/) - AI-enhanced computational chemistry, quantum chemical methods, and development of MLatom. (Xiamen University, China) - [Bonvin Lab](https://www.bonvinlab.org/) - Computational structural biology, HADDOCK, and integrative modeling. (Utrecht University, Netherlands) - [Volkamer Lab](https://volkamerlab.org/) - Binding site analysis and AI-powered virtual screening. (Saarland University, Germany) -- [AI Laboratory for Molecular Engineering](https://ailab.bio/) - PROTACs, molecular glues, and ML for chemistry and life sciences. (Chalmers University, Sweden) +- [AI Laboratory for Molecular Engineering](https://ailab.bio/) - PROTACs, molecular glues, and ML for chemistry and life sciences. (Chalmers University, Sweden) - [Loschmidt Labs - PEG](https://loschmidt.chemi.muni.cz/peg/) - Protein and enzyme engineering, AI-assisted enzyme design. (Masaryk University, Czechia) - [QSAR4U](https://qsar4u.com/index.php) - Cheminformatics tools, QSAR modeling, CReM, and EasyDock. (Palacky University, Czechia) - [LBMD](https://www.chem.kuleuven.be/lbmd/index.html) - Computational strategies to understand and engineer biomolecular systems. (KU Leuven, Belgium) - ---- -- 2.54.0