Sense and simplicity in HADDOCK scoring: Lessons from CASP‐CAPRI round 1

Abstract

Our information‐driven docking approach HADDOCK is a consistent top predictor and scorer since the start of its participation in the CAPRI community‐wide experiment. This sustained performance is due, in part, to its ability to integrate experimental data and/or bioinformatics information into the modelling process, and also to the overall robustness of the scoring function used to assess and rank the predictions. In the CASP‐CAPRI Round 1 scoring experiment we successfully selected acceptable/medium quality models for 18/14 of the 25 targets – a top‐ranking performance among all scorers. Considering that for only 20 targets acceptable models were generated by the community, our effective success rate reaches as high as 90% (18/20). This was achieved using the standard HADDOCK scoring function, which, thirteen years after its original publication, still consists of a simple linear combination of intermolecular van der Waals and Coulomb electrostatics energies and an empirically derived desolvation energy term. Despite its simplicity, this scoring function makes sense from a physico‐chemical perspective, encoding key aspects of biomolecular recognition. In addition to its success in the scoring experiment, the HADDOCK server takes the first place in the server prediction category, with 16 successful predictions. Much like our scoring protocol, because of the limited time per target, the predictions relied mainly on either an ab initio center‐of‐mass and symmetry restrained protocol, or on a template‐based approach whenever applicable. These results underline the success of our simple but sensible prediction and scoring scheme. Proteins 2017; 85:417–423. © 2016 Wiley Periodicals, Inc.

iSEE: Interface Structure, Evolution and Energy-based machine learning predictor of binding affinity changes upon mutations

“…HADDOCK [20] is our in-house docking program, which has been consistently ranking among the top predictors and scorers in CAPRI, a community-wide experiment for the prediction of biomolecular interactions [21]. Its simple but sensible scoring function has contributed much to its success [22]. It includes intermolecular van der Waals (Evdw) and Coulomb electrostatics (Eelec) energies, an empirical desolvation energy term (Edesolv) [23] and buried surface area (BSA), which is only used in intermediate scoring steps and not in the final scoring function.…”

An overview of data-driven HADDOCK strategies in CAPRI rounds 38-45

“…After every stage, the generated models are scored with the simple yet robust HADDOCK scoring function (HS) 27,28 which is a linear weighted sum of energetic and structural terms: 29 , the desolvation energy is a solvent accessible surface area-dependent empirical term 30 which estimates the energetic gain or penalty of burying specific sidechains upon complex formation.…”

iSEE: Interface structure, evolution, and energy‐based machine learning predictor of binding affinity changes upon mutations

“…22 Its simple but sensible scoring function has contributed much to its success. 23 It includes intermolecular van der Waals (Evdw) and Coulomb electrostatics (Eelec) FIGURE 1 The workflow of iSEE predictor. Only the 3D structure of wildtype complex and the mutation information are necessary input for iSEE.…”