KGS2 is a software patch of scoring functions, which has its objective to improve the prediction accuracy of scoring functions. Our basic assumption is that molecular systems with similar structures have similar properties, a strategy that has been applied successfully to the computation of some physicochemical properties such as partition coefficient and water solubility. Accordingly, the unknown binding affinity of a given complex can be estimated more reliably from the known binding affinity of a reference complex, which shares a similar pattern of protein-ligand interactions with the query complex.
Figure 1. The query complex (B) and reference complex (A) share a similar pattern of protein-ligand interactions
Click this link for a copy of the user manual of KGS2, [User manual of KGS2]
Basically, you need to register and sign a license agreement. The KGS2 software suite is now available for free or under a modest license fee. The license fee is collected for non-profit purpose, e.g. maintenance and personnel cost. Different license fees apply to different categories of users:
- (1) KGS2 is free for all academic, governmental, and other non-profit organizations.
- (2) The license fee for all commercial, industrial, and other for-profit organizations is 5000 USD. This fee grants a site license with an unlimited number of users.
- (3) The license fee for non-profit computing centers is 3000 USD; while the license fee for for-profit computing centers is the same as the commercial site license, i.e. 5000 USD.
To obtain the KGS2 software suite, please go to the following [REGISTRATION] page, select the correct category (i.e. academic/government or commercial) and fill in necessary contact information. Upon registration, an end-user license agreement must be signed for copyright protection. For whom have paid license fees, we will provide you a formal invoice with payment information. Once we receive the payment, we will send you through e-mail further instruction on downloading the KGS2 software suite.
The KGS2 suite includes the scripts and executable codes for Linux platform of all major functions, the user manual, and the necessary material for running the several demo examples described in our publication. It is provided as a TAR.gz package (~20 MB in size).
Reference:
- Jie Liu, Minyi Su, Zhihai Liu, Jie Li, Yan Li *, Renxiao Wang *. Enhance the Performance of Current Scoring Functions with the Aid of 3D Protein-Ligand Interaction Fingerprints. BMC Bioinformatics 2017, In press (KGS version 2)
- Tiejun, Cheng.;Zhihai Liu,; Renxiao Wang. A knowledge-guided strategy for improving the accuracy of scoring functions in binding affinity prediction. BMC Bioinformatics 2010, 11, 193 (KGS version 1)
- Renxiao, Wang.;Luhua, Lai.; Shaomeng, Wang. Further development and validation of empirical scoring functions for structure-based binding affinity prediction. Journal of Computer-Aided Molecular Design, 2002, 16, 11–26