HOMSTRAD: A database of protein structure alignments for homologous families

By Kenji Mizuguchi, Charlotte M. Deane, Tom L. Blundell, John P. Overington. 1998

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Citations in the corpus

Fast, scalable generation of high-quality protein multiple sequence alignments using Clustal Omega (2011, methodology): “Here, each alignment is made up of a core of a Homstrad (Mizuguchi et al, 1998) structure-based alignment of at least five sequences.”
LOMETS: A local meta-threading-server for protein structure prediction (2007, methodology): “It aligns target sequence proﬁle against template structural proﬁle collected from HOMSTRAD (19).”
Multiple Sequence Alignment Based on Profile Alignment of Intermediate Sequences (2007, methodology): “…and SPEM (Zhou and Zhou 2005), which is among the best multiple alignment algorithms that utilize additional hits from database search, on benchmark multiple alignments from BAliBASE (Thompson et al. 2005), HOMSTRAD (Mizuguchi et al. 1998), PRE-FAB (Edgar 2004), and SABmark (Van Walle et al. 2004).”
Defining and searching for structural motifs using DeepView/Swiss-PdbViewer (2012, methodology): “, FSSP [7], THREADER [8], FOLDFIT [9], and others [10-12] have been developed, followed by methods for fold classification, such as SCOP [13] and CATH [14].”
DECIPHER: harnessing local sequence context to improve protein multiple sequence alignment (2015, methodology): “…was made because: (i) the definition of core blocks varies between benchmarks, (ii) some scoring procedures make use of the entire alignment [44], (iii) pairwise distance is calculated using the whole alignment, and (iv) the HOMSTRAD [39] and SABmark benchmarks do not delineate core blocks.”
ProbCons: Probabilistic consistency-based multiple sequence alignment. (2005, methodology): “The BAliBASE 2.01 benchmark alignment database is a collection of 141 reference protein alignments consisting of structural alignments from the FSSP (Holm and Sander 1996) and HOMSTRAD (Mizuguchi et al. 1998) databases and hand-constructed alignments from the literature.”
DALI and the persistence of protein shape (2019, unknown): “30 The example is plastocyanin/azurin.”
CATHEDRAL: A Fast and Effective Algorithm to Predict Folds and Domain Boundaries from Multidomain Protein Structures (2007, methodology): “The alignments in BAliBASE are selected from the FSSP [36] or HOMSTRAD [39] structural databases, or from manually constructed structural alignments taken from the literature.”
M-Coffee: combining multiple sequence alignment methods with T-Coffee (2006, methodology): “The main benchmark dataset was derived from the February 2005 release of HOMSTRAD (18).”
Exploiting sequence and structure homologs to identify protein–protein binding sites (2005, unknown): “The manually curated structure alignments retrieved from the Homstrad database 64 were mapped to these proteins.”
Protein Loop Modeling Using a New Hybrid Energy Function and Its Application to Modeling in Inaccurate Structural Environments (2014, methodology): “A set of 23 loop modeling targets were constructed from the HOMSTRAD set [29] using template-based models generated with MODELLER 9.”
PRALINE: a multiple sequence alignment toolbox that integrates homology-extended and secondary structure information (2005, methodology): “In Table 1, the performance of the homology-extended alignment strategy on 254 HOMSTRAD ( 17 ) multiple alignment cases has been compared with the state-of-the-art methods T-COFFEEv2.03 and MUSCLEv3.51.”
GUIDANCE2: accurate detection of unreliable alignment regions accounting for the uncertainty of multiple parameters (2015, methodology): “For HOMSTRAD we used the 232 MSAs with more than three sequences.”