MM-align: a quick algorithm for aligning multiple-chain protein complex structures using iterative dynamic programming

By Srayanta Mukherjee, Yang Zhang. 2009

187 citations recorded by the source corpus.

Structural comparison of multiple-chain protein complexes is essential in many studies of protein–protein interactions. We develop a new algorithm, MM-align, for sequence-independent alignment of protein complex structures. The algorithm is built on a heuristic iteration of a modified Needleman–Wunsch dynamic programming (DP) algorithm, with the alignment score specified by the inter-complex residue distances. The multiple chains in each complex are first joined, in every possible order, and then simultaneously aligned with cross-chain alignments prevented. The alignments of interface residues are enhanced by an interface-specific weighting factor. MM-align is tested on a large-scale benchmark set of 205 × 3897 non-homologous multiple-chain complex pairs. Compared with a naïve extension of the monomer alignment program of TM-align, the alignment accuracy of MM-align is significantly higher as judged by the average TM-score of the physically-aligned residues. MM-align is about two times faster than TM-align because of omitting the cross-alignment zone of the DP matrix. It also shows that the enhanced alignment of the interfaces helps in identifying biologically relevant protein complex pairs.

Subfields: Materials Chemistry, Molecular Biology

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Citations in the corpus

Prediction of homo- and hetero-protein complexes by protein docking and template-based modeling: a CASP-CAPRI experiment (2016, unknown): “44 For computational efficiency, MM-align was applied only to the 100 proteins with the highest monomer structure similarity to the target.”
MMDB and VAST+: tracking structural similarities between macromolecular complexes (2013, background): “A small number of approaches have been published in the past few years that examine structural similarity of macromolecular complexes (21,22).”
A de novo protein binding pair by computational design and directed evolution (2011, methodology): “…whether our design protocol had recapitulated a backbone orientation already observed in nature, we applied the MM-align and TM-align algorithms (Mukherjee and Zhang, 2009; Zhang and Skolnick, 2005) to search for similar arrangements amongst both multiple chain complexes and monomers in the…”
Assessment of CASP10 contact‐assisted predictions (2014, background): “…abundance of programs to compare protein monomers, there are surprisingly few programs available designed to compare multichain complexes, and hence deal with the added complication of chain id ambiguity and cross-chain alignments,29 where a whole chain can be aligned to parts of two other chains.”
Continuous Automated Model EvaluatiOn (CAMEO) complementing the critical assessment of structure prediction in CASP12 (2018, unknown): “Currently, most methods require human intervention and only very few servers can automatically predict quaternary structure(25) CAMEO supports new algorithmic developments by providing new scoring schemes for developers, such as “QS-score” that was recently added to CAMEO, alongside with a growing n”
Predicting the Effect of Mutations on Protein-Protein Binding Interactions through Structure-Based Interface Profiles (2015, background): “8 obtained from MM-align [66] to another structure in the complex library, it is removed from the database.”
Limits and potential of combined folding and docking (2021, methodology): “We also MM-align for comparing docked models [38].”
Improved multimer prediction using massive sampling with AlphaFold in CASP15 (2023, methodology): “…submitting identical81 predictions a filter was added to make sure submitted predictions were not more similar than82 TMscore>0.8 using MM-align (Mukherjee and Zhang, 2009).83 2.3 Multiple Sequence Alignment84 The input multiple sequence alignments and template search were generated by the…”
Improved metrics for comparing structures of macromolecular assemblies determined by 3D electron-microscopy (2017, methodology): “50 maps each were chosen randomly from two major categories, ribosomes and viruses, and 30 maps for the categories of chaperones and other sample types; structure superposition of fitted atomic coordinates corresponding to maps in each category was carried out using MMalign (Mukherjee and Zhang, 200”