A new size‐independent score for pairwise protein structure alignment and its application to structure classification and nucleic‐acid binding prediction

Yang, Yuedong; Zhan, Jian; Zhao, Huiying; Zhou, Yaoqi

doi:10.1002/prot.24100

Cited by 73 publications

(87 citation statements)

References 45 publications

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“…For the DUD dataset, SPOT-Ligand makes an improvement of 19-35% in enrichment factors. This difference is mainly contributed by improvement in structural alignment of SPalign [24] over TM-align or its variant Fr-TM-align. [17,36] SPalign employs a scoring function that has removed the dependence of protein-protein alignment on protein sizes.…”

Section: Discussionmentioning

confidence: 93%

“…The target protein structure is first structurally compared to the representative chains in TPL90 by using SPalign. [24] All protein chains with SP-score > 0.4 to the query structure are selected. If the number of selected chains is below 100, top 100 chains are chosen to increase the sensitivity.…”

Section: Binding-homology-search-based Virtual Screeningmentioning

confidence: 99%

“…[24] Here, we examine the usefulness of SPalign for binding-homology-search-based virtual screening by using DUD and DUD-E benchmarks. We showed that SPOT-Ligand has a consistent performance, regardless of the benchmarks employed, indicating the robustness of the results obtained.…”

Section: Introductionmentioning

confidence: 99%

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SPOT‐Ligand: Fast and effective structure‐based virtual screening by binding homology search according to ligand and receptor similarity

2016

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Structure-based virtual screening usually involves docking of a library of chemical compounds onto the functional pocket of the target receptor so as to discover novel classes of ligands. However, the overall success rate remains low and screening a large library is computationally intensive. An alternative to this "ab initio" approach is virtual screening by binding homology search. In this approach, potential ligands are predicted based on similar interaction pairs (similarity in receptors and ligands). SPOT-Ligand is an approach that integrates ligand similarity by Tanimoto coefficient and receptor similarity by protein structure alignment program SPalign. The method was found to yield a consistent performance in DUD and DUD-E docking benchmarks even if model structures were employed. It improves over docking methods (DOCK6 and AUTODOCK Vina) and has a performance comparable to or better than other binding-homology methods (FINDsite and PoLi) with higher computational efficiency. The server is available at http://sparks-lab.org. © 2016 Wiley Periodicals, Inc.

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Section: Discussionmentioning

confidence: 93%

Section: Binding-homology-search-based Virtual Screeningmentioning

confidence: 99%

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SPOT‐Ligand: Fast and effective structure‐based virtual screening by binding homology search according to ligand and receptor similarity

2016

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“…Thus, minimizing the TM-score weighted RMSD tends to minimize the TM-score more effectively and to converge more efficiently [30]. It might be worth mentioning that the weight calculation requires a superposition as the input, and thus it cannot be adopted in the first step.…”

Section: Superposition Refinement With Random Subsetsmentioning

confidence: 99%

“…This process is repeated until the residue pair set are unchanged. Similar heuristic approaches have also been used in recent protein structure alignment tools [11,35,20,30,25].…”

Section: Introductionmentioning

confidence: 99%

Compare local pocket and global protein structure models by small structure patterns

Cui

Kuwahara

et al. 2015

Proceedings of the 6th ACM Conference on Bioinformatics, Computational Biology and Health Informatics

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Researchers proposed several criteria to assess the quality of predicted protein structures because it is one of the essential tasks in the Critical Assessment of Techniques for Protein Structure Prediction (CASP) competitions. Popular criteria include root mean squared deviation (RMSD), MaxSub score, TM-score, GDT-TS and GDT-HA scores. All these criteria require calculation of rigid transformations to superimpose the the predicted protein structure to the native protein structure. Yet, how to obtain the rigid transformations is unknown or with high time complexity, and, hence, heuristic algorithms were proposed.In this work, we carefully design various small structure patterns, including the ones specifically tuned for local pockets. Such structure patterns are biologically meaningful, and address the issue of relying on a sufficient number of backbone residue fragments for existing methods. We sample the rigid transformations from these small structure patterns; and the optimal superpositions yield by these small structures are refined and reported. As a result, among 11, 669 pairs of predicted and native local protein pocket models * To whom all correspondence should be addressed (email: shuaicli@cityu.edu.hk). † To whom all correspondence should be addressed (email: xin.gao@kaust.edu.sa).Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from permissions@acm.org. BCB '15, September 9-12, 2015 from the CASP10 dataset, the GDT-TS scores calculated by our method are significantly higher than those calculated by LGA. Moreover, our program is computationally much more efficient.Source codes and executables are publicly available at

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Computational Prediction of Carbohydrate‐Binding Proteins and Binding Sites

et al. 2018

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Protein-carbohydrate interaction is essential for biological systems, and carbohydrate-binding proteins (CBPs) are important targets when designing antiviral and anticancer drugs. Due to the high cost and difficulty associated with experimental approaches, many computational methods have been developed as complementary approaches to predict CBPs or carbohydrate-binding sites. However, most of these computational methods are not publicly available. Here, we provide a comprehensive review of related studies and demonstrate our two recently developed bioinformatics methods. The method SPOT-CBP is a template-based method for detecting CBPs based on structure through structural homology search combined with a knowledge-based scoring function. This method can yield model complex structure in addition to accurate prediction of CBPs. Furthermore, it has been observed that similarly accurate predictions can be made using structures from homology modeling, which has significantly expanded its applicability. The other method, SPRINT-CBH, is a de novo approach that predicts binding residues directly from protein sequences by using sequence information and predicted structural properties. This approach does not need structurally similar templates and thus is not limited by the current database of known protein-carbohydrate complex structures. These two complementary methods are available at https://sparks-lab.org. © 2018 by John Wiley & Sons, Inc.

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A new size‐independent score for pairwise protein structure alignment and its application to structure classification and nucleic‐acid binding prediction

Cited by 73 publications

References 45 publications

SPOT‐Ligand: Fast and effective structure‐based virtual screening by binding homology search according to ligand and receptor similarity

SPOT‐Ligand: Fast and effective structure‐based virtual screening by binding homology search according to ligand and receptor similarity

Compare local pocket and global protein structure models by small structure patterns

Computational Prediction of Carbohydrate‐Binding Proteins and Binding Sites

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