https://users.cs.duke.edu/~brd/Teaching/Bio/asmb/Papers/JMB/Knowledge-based%20Scoring%20Function%20to%20Predict%20Protein-Ligand%20Interactions-3371a.pdf

Knowledge-based scoring function to predict protein-ligand interactions

We report on a test of FLEXX, a fully automatic docking tool for flexible ligands, on a highly diverse data set of 200 protein-ligand com- plexes from the Protein Data Bank. In total 46.5% of the complexes of the data set can be reproduced by a FLEXX docking solution at rank 1 with an rms devia- tion (RMSD) from the observed structure of less than 2 A. This rate rises to 70% if one looks at the entire generated solution set. FLEXX produces reli- able results for ligands with up to 15 components which can be docked in 80% of the cases with acceptable accuracy. Ligands with more than 15 components tend to generate wrong solutions more often. The average runtime of FLEXX on this test set is 93 seconds per complex on a SUN Ultra-30 worksta- tion. In addition, we report on ''cross-docking'' ex- periments, in which several receptor structures of complexes with identical proteins have been used for docking all cocrystallized ligands of these com- plexes. In most cases, these experiments show that FLEXX can acceptably dock a ligand into a foreign receptor structure. Finally we report on screening runs of ligands out of a library with 556 entries against ten different proteins. In eight cases FLEXX is able to find the original inhibitor within the top 7% of the total library. Proteins 1999;37:228-241.

https://onlinelibrary.wiley.com/doi/pdf/10.1002/%28SICI%291097-0134%2819991101%2937%3A2%3C228%3A%3AAID-PROT8%3E3.0.CO%3B2-8

Evaluation of the FLEXX incremental construction algorithm for protein-ligand docking.

Molecular docking methodology explores the behavior of small molecules in the binding site of a target protein. As more protein structures are determined experimentally using X-ray crystallography or nuclear magnetic resonance (NMR) spectroscopy, molecular docking is increasingly used as a tool in drug discovery. Docking against homology-modeled targets also becomes possible for proteins whose structures are not known. With the docking strategies, the druggability of the compounds and their specificity against a particular target can be calculated for further lead optimization processes. Molecular docking programs perform a search algorithm in which the conformation of the ligand is evaluated recursively until the convergence to the minimum energy is reached. Finally, an affinity scoring function, ΔG [U total in kcal/mol], is employed to rank the candidate poses as the sum of the electrostatic and van der Waals energies. The driving forces for these specific interactions in biological systems aim toward complementarities between the shape and electrostatics of the binding site surfaces and the ligand or substrate.

Software for molecular docking: a review

Three different database docking programs (Dock, FlexX, Gold) have been used in combination with seven scoring functions (Chemscore, Dock, FlexX, Fresno, Gold, Pmf, Score) to assess the accuracy of virtual screening methods against two protein targets (thymidine kinase, estrogen receptor) of known three-dimensional structure. For both targets, it was generally possible to discriminate about 7 out of 10 true hits from a random database of 990 ligands. The use of consensus lists common to two or three scoring functions clearly enhances hit rates among the top 5% scorers from 10% (single scoring) to 25−40% (double scoring) and up to 65−70% (triple scoring). However, in all tested cases, no clear relationships could be found between docking and ranking accuracies. Moreover, predicting the absolute binding free energy of true hits was not possible whatever docking accuracy was achieved and scoring function used. As the best docking/consensus scoring combination varies with the selected target and the physicoch...

http://bioinfo-pharma.u-strasbg.fr/labwebsite/publications/paper48.pdf

Protein-based virtual screening of chemical databases. 1. Evaluation of different docking/scoring combinations.

CAPRI is a communitywide experiment to assess the capacity of protein-docking methods to predict protein-protein interactions. Nineteen groups participated in rounds 1 and 2 of CAPRI and submitted blind structure predictions for seven protein-protein complexes based on the known structure of the component proteins. The predictions were compared to the unpublished X-ray structures of the complexes. We describe here the motivations for launching CAPRI, the rules that we applied to select targets and run the experiment, and some conclusions that can already be drawn. The results stress the need for new scoring functions and for methods handling the conformation changes that were observed in some of the target systems. CAPRI has already been a powerful drive for the community of computational biologists who development docking algorithms. We hope that this issue of Proteins will also be of interest to the community of structural biologists, which we call upon to provide new targets for future rounds of CAPRI, and to all molecular biologists who view protein-protein recognition as an essential process.

/pdf/capri-a-critical-assessment-of-predicted-interactions-d7a3cmrerj.pdf

CAPRI: A Critical Assessment of PRedicted Interactions

The docking section of CASP2 is reviewed. Seven small molecule ligand–protein targets and one protein–protein target were available for predictions. Many of the small molecule ligand complexes involved serine proteases. Overall results for the small molecule targets were good, with at least one prediction for each target being within 3 A root-mean-square deviation (RMSD) for nearly all targets and within 2 A RMSD for over half the targets. However, no single docking method seemed to consistently perform best. In addition, the predictions closest to the experimental results were not always those ranked the highest, pointing out that the evaluation (scoring) of potential solutions is still an area that needs improvement. The protein–protein target proved more difficult. None of the predictions did well in reproducing the geometry of the complex, although in many cases the interacting surfaces of the two proteins were predicted with reasonable accuracy. This target consisted of two large proteins and, therefore was a demanding target for docking methods. Proteins, Suppl. 1:198–204, 1997. © 1998 Wiley-Liss, Inc.

J. Scott Dixon

Papers

Evaluation of the CASP2 docking section