Quantitative evaluation of protein-DNA interactions using an optimized knowledge-based potential

Liu, Zhijie; Mao, Feng; Guo, Jun‐tao; Yan, Bo; Wang, Peng; Qu, Youxing; Xu, Ying

doi:10.1093/nar/gki204

Cited by 58 publications

(86 citation statements)

References 46 publications

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“…More details were presented in our previous papers [26,29]. The initial knowledge-based atom-pair potentials were extracted from the structural data of the training set with Boltzmann relation [27,28,38,[45][46][47][48][49]. That is…”

Section: Optimization Of the Scoring Functionmentioning

confidence: 99%

Incorporating specificity into optimization: evaluation of SPA using CSAR 2014 and CASF 2013 benchmarks

Yan

Wang

2016

J Comput Aided Mol Des

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Scoring functions of protein-ligand interactions are widely used in computationally docking software and structure-based drug discovery. Accurate prediction of the binding energy between the protein and the ligand is the main task of the scoring function. The accuracy of a scoring function is normally evaluated by testing it on the benchmarks of protein-ligand complexes. In this work, we report the evaluation analysis of an improved version of scoring function SPecificity and Affinity (SPA). By testing on two independent benchmarks Community Structure-Activity Resource (CSAR) 2014 and Comparative Assessment of Scoring Functions (CASF) 2013, the assessment shows that SPA is relatively more accurate than other compared scoring functions in predicting the interactions between the protein and the ligand. We conclude that the inclusion of the specificity in the optimization can effectively suppress the competitive state on the funnel-like binding energy landscape, and make SPA more accurate in identifying the "native" conformation and scoring the binding decoys. The evaluation of SPA highlights the importance of binding specificity in improving the accuracy of the scoring functions.

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Section: Optimization Of the Scoring Functionmentioning

confidence: 99%

Incorporating specificity into optimization: evaluation of SPA using CSAR 2014 and CASF 2013 benchmarks

Yan

Wang

2016

J Comput Aided Mol Des

View full text Add to dashboard Cite

show abstract

“…The weights of different energy terms in our energy function were determined through finding the best threading alignments and sidechain packing on a training set, using a technique called Z-score optimization [37], [38]. The training set consists of 164 selected pairs of query sequence-template structures; 100 random decoy alignments were generated for each pair.…”

Section: Formulation Of the New Paradigmmentioning

confidence: 99%

An Algorithm for Simultaneous Backbone Threading and Side-Chain Packing

Liu

Guo

et al. 2007

Algorithmica

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To utilize fully all available information in protein structure prediction, including both backbone and side-chain structures, we present a novel algorithm for solving a generalized threading problem. In this problem we consider simultaneous backbone threading and side-chain packing during the process of a protein structure prediction. For a given query protein sequence and a template structure, our goal is to find a threading alignment between the query sequence and the template structure, along with a rotamer assignment for each side-chain of the query protein, which optimizes an energy function that combines a backbone threading energy and a side-chain packing energy. This highly computationally challenging problem is solved through first formulating this problem as a graph-based optimization problem. Various graph-theoretic techniques are employed to achieve the computational efficiency to make our algorithm practically useful, which takes advantage of a number of special properties of the graph representing this generalized threading problem. The overall framework of our algorithm is a dynamic programming algorithm implemented on an optimal tree decomposition of the graph representation of our problem. By using various additional heuristic techniques such as dead-end elimination, we have demonstrated that our algorithm can solve a generalized threading problem within a practically acceptable amount of time and space, the first of its kind.

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“…Z score optimization of energy weights: The weights of different energy terms in our energy function were determined through finding the best threading alignments and side-chain packing on a training set, using a technique called Z-score optimization [37,38]. The training set consists of 164 selected pairs of query sequence-template structure, 100 random decoy alignments were generated for each pair.…”

Section: Formulation Of the New Paradigmmentioning

confidence: 99%

An Algorithm for Simultaneous Backbone Threading and Side-Chain Packing

Liu

Guo

et al. 2007

Algorithmica

View full text Add to dashboard Cite

To fully utilize all available information in protein structure prediction, including both backbone and side-chain structures, we present a novel algorithm for solving a generalized threading problem. In this problem, we consider simultaneously backbone threading and side-chain packing during the process of a protein structure prediction. For a given query protein sequence and a template structure, our goal is to find a threading alignment between the query sequence and the template structure, along with a rotamer assignment for each side-chain of the query protein, which optimizes an energy function that combines a backbone threading energy and a side-chain packing energy. This highly computationally challenging problem is solved through first formulating this problem as a graph-based optimization problem. Various graph-theoretic techniques are employed to achieve the computational efficiency to make our algorithm practically useful, which takes advantage of a number of special properties of the graph representing this generalized threading problem. The overall framework of our algorithm is a dynamic programming algorithm implemented on an optimal tree decomposition of the graph representation of our problem. By using various additional heuristic techniques such as the dead-end elimination, we have demonstrated that our algorithm can solve a generalized threading problem within practically acceptable amount of time and space, the first of its kind.

show abstract

Quantitative evaluation of protein-DNA interactions using an optimized knowledge-based potential

Cited by 58 publications

References 46 publications

Incorporating specificity into optimization: evaluation of SPA using CSAR 2014 and CASF 2013 benchmarks

Incorporating specificity into optimization: evaluation of SPA using CSAR 2014 and CASF 2013 benchmarks

An Algorithm for Simultaneous Backbone Threading and Side-Chain Packing

An Algorithm for Simultaneous Backbone Threading and Side-Chain Packing

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