标题少了一个e,可能是世界潜在地告诉我学习CADD不是那么easy。

收集了一些CADD教程,资源总结

如有疏漏,烦请指正,邮箱:luskyqi@outlook.com

感谢@Tong-Du 的贡献

• 药物设计综合软件
• 三维可视化工具
• 小分子对接
• 分子动力学模拟
• 蛋白设计
• 量化
• 常用代码包
• 其余教程资源总结

1. Schrödinger:薛定谔公司,https://www.schrodinger.com/

2. Discovery Studio:https://www.3ds.com/products-services/biovia/products/molecular-modeling-simulation/biovia-discovery-studio/

3. CCDC套装:剑桥晶体数据库,各个大学和科研机构购买的较多,https://www.ccdc.cam.ac.uk/

1. PyMol:分为开源和免费两个版本,建议从官网下载:https://pymol.org/2/,官网教程:https://pymolwiki.org/index.php/Main_Page

   • 论文:
     1. The PyMOL Molecular Graphics System, Version 1.2r3pre, Schrödinger, LLC.

2. Chimera:开源 ,http://www.cgl.ucsf.edu/chimera/,官网使用手册:http://www.cgl.ucsf.edu/chimera/docindex.html

   • 论文:
     1. Pettersen EF, Goddard TD, Huang CC, Couch GS, Greenblatt DM, Meng EC, Ferrin TE. UCSF Chimera--a visualization system for exploratory research and analysis. J Comput Chem. 2004 Oct;25(13):1605-12. doi: 10.1002/jcc.20084. PMID: 15264254.

3. VMD:开源,https://www.ks.uiuc.edu/Research/vmd/

   • 论文:
     1. Humphrey W, Dalke A, Schulten K. VMD: visual molecular dynamics. J Mol Graph. 1996 Feb;14(1):33-8, 27-8. doi: 10.1016/0263-7855(96)00018-5. PMID: 8744570.

1. Vina:官网:http://vina.scripps.edu/

   • 论文:
     1. Vina 1.2.0: Eberhardt J, Santos-Martins D, Tillack A, Forli S. AutoDock Vina 1.2.0: New Docking Methods, Expanded Force Field, and Python Bindings. ChemRxiv. Cambridge: Cambridge Open Engage; 2021; This content is a preprint and has not been peer-reviewed.
     2. Vina 1.1.2 :Trott O, Olson AJ. AutoDock Vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading. J Comput Chem. 2010 Jan 30;31(2):455-61. doi: 10.1002/jcc.21334. PMID: 19499576; PMCID: PMC3041641.

2. AutoDock:官网:http://autodock.scripps.edu/

   • 论文:
     1. AutoDock 4.2:Morris, G. M., Huey, R., Lindstrom, W., Sanner, M. F., Belew, R. K., Goodsell, D. S. and Olson, A. J. (2009) Autodock4 and AutoDockTools4: automated docking with selective receptor flexiblity. J. Computational Chemistry 2009, 16: 2785-91.
     2. AutoDock 3 & 4:Morris, G. M., Goodsell, D. S., Halliday, R.S., Huey, R., Hart, W. E., Belew, R. K. and Olson, A. J. (1998), Automated Docking Using a Lamarckian Genetic Algorithm and and Empirical Binding Free Energy Function J. Computational Chemistry, 19: 1639-1662.
     3. AutoDock 4 Scoring Function:Huey, R., Morris, G. M., Olson, A. J. and Goodsell, D. S. (2007), A Semiempirical Free Energy Force Field with Charge-Based Desolvation J. Computational Chemistry, 28: 1145-1152.
     4. AutoDock 2.4:Morris, G. M., Goodsell, D. S., Huey, R. and Olson, A. J. (1996), Distributed automated docking of flexible ligands to proteins: Parallel applications of AutoDock 2.4 J. Computer-Aided Molecular Design, 10: 293-304.
     5. AutoDock 1:Goodsell, D. S. and Olson, A. J. (1990), Automated Docking of Substrates to Proteins by Simulated Annealing Proteins:Structure, Function and Genetics., 8: 195-202.

3. DOCK:官网:http://dock.compbio.ucsf.edu/

   • 论文:
     1. DOCK 6: Allen WJ, Balius TE, Mukherjee S, Brozell SR, Moustakas DT, Lang PT, Case DA, Kuntz ID, Rizzo RC. DOCK 6: Impact of new features and current docking performance. J Comput Chem. 2015 Jun 5;36(15):1132-56. doi: 10.1002/jcc.23905. PMID: 25914306; PMCID: PMC4469538.
     2. DOCK 3: Goodford PJ. A computational procedure for determining energetically favorable binding sites on biologically important macromolecules. J Med Chem. 1985 Jul;28(7):849-57. doi: 10.1021/jm00145a002. PMID: 3892003.

4. LeDock:官网:http://www.lephar.com/software.htm

   • 论文:
     1. 引用文献,非原始文献:Lee A, Kim D. CRDS: Consensus Reverse Docking System for target fishing. Bioinformatics. 2020 Feb 1;36(3):959-960. doi: 10.1093/bioinformatics/btz656. PMID: 31432077.

5. GOLD:属于CCDC套装,官网:https://www.ccdc.cam.ac.uk/

   • 论文:
     1. GOLD_2:Verdonk, Marcel & Cole, Jason & Hartshorn, Michael & Murray, Christopher & Taylor, Richard. (2003). Improved Protein–ligand docking using GOLD. Proteins. 52. 609-23. 10.1002/prot.10465.
     2. GOLD_1:J ones G, Willett P, Glen RC, Leach AR, Taylor R. Development and validation of a genetic algorithm for flexible docking. J Mol Biol. 1997 Apr 4;267(3):727-48. doi: 10.1006/jmbi.1996.0897. PMID: 9126849.
     3. CHEMPLP:Korb O, Stützle T, Exner TE. Empirical scoring functions for advanced protein-ligand docking with PLANTS. J Chem Inf Model. 2009 Jan;49(1):84-96. doi: 10.1021/ci800298z. PMID: 19125657.

6. Glide:属于薛定谔:https://www.schrodinger.com/

   • 论文:
     1. Friesner RA, Banks JL, Murphy RB, Halgren TA, Klicic JJ, Mainz DT, Repasky MP, Knoll EH, Shelley M, Perry JK, Shaw DE, Francis P, Shenkin PS. Glide: a new approach for rapid, accurate docking and scoring. 1. Method and assessment of docking accuracy. J Med Chem. 2004 Mar 25;47(7):1739-49. doi: 10.1021/jm0306430. PMID: 15027865.

7. cdocker:属于DiscoveryStudio,官网:https://www.3ds.com/products-services/biovia/products/molecular-modeling-simulation/biovia-discovery-studio/

   • 论文:
     1. Gagnon JK, Law SM, Brooks CL 3rd. Flexible CDOCKER: Development and application of a pseudo-explicit structure-based docking method within CHARMM. J Comput Chem. 2016 Mar 30;37(8):753-62. doi: 10.1002/jcc.24259. Epub 2015 Dec 21. PMID: 26691274; PMCID: PMC4776757.

1. Gromacs:官网:www.gromacs.org

   • 论文:
     1. Van Der Spoel D, Lindahl E, Hess B, Groenhof G, Mark AE, Berendsen HJ. GROMACS: fast, flexible, and free. J Comput Chem. 2005 Dec;26(16):1701-18. doi: 10.1002/jcc.20291. PMID: 16211538.

2. Amber:官网:http://ambermd.org/

   • 论文:
     1. R. Salomon-Ferrer, D.A. Case, R.C. Walker. An overview of the Amber biomolecular simulation package. WIREs Comput. Mol. Sci. 3, 198-210 (2013).

暂无,待补充

3. NAMD:官网:https://www.ks.uiuc.edu/Research/namd/

   • 论文:
     1. James C. Phillips, Rosemary Braun, Wei Wang, James Gumbart, Emad Tajkhorshid, Elizabeth Villa, Christophe Chipot, Robert D. Skeel, Laxmikant Kale, and Klaus Schulten. Journal of Computational Chemistry, 26:1781-1802, 2005.

4. OpenMM:官网:https://openmm.org/

   • 论文:
     1. Eastman P, Swails J, Chodera JD, McGibbon RT, Zhao Y, Beauchamp KA, Wang LP, Simmonett AC, Harrigan MP, Stern CD, Wiewiora RP, Brooks BR, Pande VS. OpenMM 7: Rapid development of high performance algorithms for molecular dynamics. PLoS Comput Biol. 2017 Jul 26;13(7):e1005659. doi: 10.1371/journal.pcbi.1005659. PMID: 28746339; PMCID: PMC5549999.

5. Charmm:官网:https://www.charmm.org

暂无

6. Desmond:官网:https://www.deshawresearch.com/resources_desmond.html

   • 论文:
     1. https://www.deshawresearch.com/publications.html

暂无,待补充

7. Schrödinger:官网:薛定谔公司,https://www.schrodinger.com/

暂无,待补充

8. Discovery Studio:官网:https://www.3ds.com/products-services/biovia/products/molecular-modeling-simulation/biovia-discovery-studio/

暂无,待补充

1. Rosetta

   • 论文:
     1. http://new.rosettacommons.org/docs/latest/getting_started/Rosetta-canon

2. AlphaFold

   • 论文:
     1. Jumper, J., Evans, R., Pritzel, A. et al. Highly accurate protein structure prediction with AlphaFold. Nature (2021). https://doi.org/10.1038/s41586-021-03819-2

仅有B站链接:https://www.bilibili.com/video/BV1Yg411L7Sh

1. Rdkit:C++,python,官网:https://rdkit.org

   • 论文:
     1. RDKit: Open-source cheminformatics; http://www.rdkit.org

2. OpenBabel:官网:http://openbabel.org/wiki/Main_Page

   • 论文:
     1. O'Boyle NM, Banck M, James CA, Morley C, Vandermeersch T, Hutchison GR. Open Babel: An open chemical toolbox. J Cheminform. 2011 Oct 7;3:33. doi: 10.1186/1758-2946-3-33. PMID: 21982300; PMCID: PMC3198950.

1. 一系列开源的化学信息学资源:https://github.com/PatWalters/resources/blob/main/cheminformatics_resources.md 综合性较强,内含博客,教程,ML,Python工具等等,英文
2. teachopencadd:https://github.com/volkamerlab/TeachOpenCADD 如果你是新手接触CADD,可以从这里入手,由初学者为了初学者创建,有paper 英文