SWISS-MODEL: homology modelling of protein structures and complexes

Abstract

Homology modelling has matured into an important technique in structural biology, significantly contributing to narrowing the gap between known protein sequences and experimentally determined structures. Fully automated workflows and servers simplify and streamline the homology modelling process, also allowing users without a specific computational expertise to generate reliable protein models and have easy access to modelling results, their visualization and interpretation. Here, we present an update to the SWISS-MODEL server, which pioneered the field of automated modelling 25 years ago and been continuously further developed. Recently, its functionality has been extended to the modelling of homo- and heteromeric complexes. Starting from the amino acid sequences of the interacting proteins, both the stoichiometry and the overall structure of the complex are inferred by homology modelling. Other major improvements include the implementation of a new modelling engine, ProMod3 and the introduction a new local model quality estimation method, QMEANDisCo. SWISS-MODEL is freely available at https://swissmodel.expasy.org.

Figure 1.

Performance comparison between ProMod-II and ProMod3 modelling engines. Performance is measured on a benchmark dataset of 250 targets collected during the CAMEO time range 20 October 2017–13 January 2018. For each target, the same template and target-template alignment were used as input for both modelling engines. Each data point represents the difference in model accuracy in terms of all-atom IDDT score. ProMod3 shows a statically significant improvement of 2.65 IDDT points on average (P-value = 1.1E–43) based on paired t-test.

Figure 2.

Modelling example of the Ferrodoxin/Ferredoxin-NADP(+) Reductase hetero dimeric complex. (A) Decision tree of templates clustered according to their quaternary structure features: oligomeric state, stoichiometry, topology and interface similarity. Three different clusters are formed based on interface similarity between templates. (B) PPI fingerprint analysis of available template structures. The ratio between interface and surface residue entropy (interface conservation, y-axis) is reported as a function of evolutionary distance (sequence identity, x-axis). Templates corresponding to SMTL ID: 1ewy.1 (in blue) and SMTL ID: 1gaq.1 (in green) show the typical conservation pattern observed for biologically relevant interfaces, with stronger conservation signal in the sequence identity range between 40 and 60%. Considering also remote homologs (below 40% sequence identity), only the interface in template SMTL ID: 1gaq.1 is deemed as conserved (interface/surface conservation ratio below zero). Template corresponding to SMTL ID: 3w5u.1 (in red) displays an interface/surface conservation ratio close to zero, as observed in crystal contacts/artefacts. (C) Structure superposition of available templates. Each template is coloured according to same colouring scheme of Figure 2A and B. Templates corresponding to SMTL ID: 1ewy.1 (in blue) and 1gaq.1 (in green) show similar arrangement of FNR and Fd in the complex. Template SMTL ID: 3w5u.1 (red) shows a different localization of the Fd moiety. Cross-linked cysteines are shown in sticks. (D) Structure superposition between model and native structure of the root FNR:Fd complex. The model is coloured according to its local quality using a colour gradient from blue (high quality) to red (low quality) as measured by all-atom IDDT score. The native structure of the complex is shown in light gray.