APL: An angle probability list to improve knowledge-based metaheuristics for the three-dimensional protein structure prediction

Borguesan, Bruno; Silva, Mariel Barbachan e; Grisci, Bruno Iochins; Inostroza-Ponta, Mario; Dorn, Márcio

doi:10.1016/j.compbiolchem.2015.08.006

Cited by 40 publications

(12 citation statements)

References 84 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The contribution of residue neighborhood, that is, the residues that come before and after the residue position of interest, for the amino acid conformation has been extensively demonstrated (Kabat and Wu, 1973;Crasto and Feng, 2001;Hovmöller et al, 2002;Xia and Xie, 2002;Ting et al, 2010;Borguesan et al, 2015;Hollingsworth et al, 2016). In this work, we show that side chains also have clear preferences when taking part into different secondary structures, and not only the main chain, as previously observed (Hovmöller et al, 2002).…”

Section: Discussionsupporting

confidence: 77%

“…Researchers are interested in the rules that determine the protein structure for a given sequence, which is influenced by the intrinsic conformational preference of each amino acid residue and also the interactions of neighbor amino acid residues (Dorn et al, 2014). An approach (knowledgebased prediction methods) to that problem is to explore the conformational particularities of local segments of amino acids in experimental structures solved at atomic resolution and stored in PDB (Borguesan et al, 2015).Structural data are stored in databases or data banks whose number increases every year, the amount of data produced urged the necessity for fast and reliable ways of accessing, retrieving, researching, and understanding these data. In this article, we use high-quality conformational information from the PDB and explore novel approaches to present some of the fundamental aspects and conformational particularities of amino acids in proteins that cannot be easily explored by using traditional Ramachandran plots.…”

mentioning

confidence: 99%

mentioning

confidence: 99%

See 2 more Smart Citations

Everyone Is a Protagonist: Residue Conformational Preferences in High-Resolution Protein Structures

Ligabue-Braun

Borguesan

Verli

et al. 2018

Journal of Computational Biology

Self Cite

View full text Add to dashboard Cite

In many structural bioinformatics problems, there is a broad range of unanswered questions about protein dynamics and amino acid properties. Proteins are not strictly static objects, but rather populate ensembles of conformations. One way to understand these particularities is to analyze the information available in experimental databases. The Ramachandran plot, despite being more than half a century old, remains an utterly useful tool in the study of protein conformation. Based on its assumptions, we inspected a large data set (11,130 protein structures, amounting to 5,255,768 residues) and discriminated the conformational preferences of each residue type regarding their secondary structure participation. These data were studied for phi [Formula: see text], psi [Formula: see text], and side chain chi [Formula: see text] angles, being presented in non-Ramachandranian plots. In the largest analysis of protein conformation made so far, we propose an original plot to depict conformational preferences in relation to different secondary structure elements. Despite confirming previous observations, our results strongly support a unique character for each residue type, whereas also reinforcing the observation that side chains have a major contribution to secondary structure and, by consequence, on protein conformation. This information can be further used in the development of more robust methods and computational strategies for structural bioinformatics problems.

show abstract

Section: Discussionsupporting

confidence: 77%

mentioning

confidence: 99%

mentioning

confidence: 99%

See 1 more Smart Citation

Everyone Is a Protagonist: Residue Conformational Preferences in High-Resolution Protein Structures

Ligabue-Braun

Borguesan

Verli

et al. 2018

Journal of Computational Biology

Self Cite

View full text Add to dashboard Cite

show abstract

“…The main reason for incorporating such information to the method is to constraint the conformational search space. The APL 2 , proposed by Borguesan et al [24] and extended by Corrêa et al [19], aims to assign the angle values to the target amino acids through analysis of the conformational preferences of these amino acids in experimentally determined structures according to their secondary structures and arrangements. To adopt the structural information of known protein templates, concerning the authors, they built histograms of [−180°, 180°] × [−180°, 180°] cells for each aa and SS, generating combinations up to 9 amino acids (1-9) and their secondary structures, and considering the reference aa neighborhood for combinations larger than 1.…”

Section: Conformational Preferences Of Amino Acidsmentioning

confidence: 99%

A dynamic evolutionary multi-agent system to predict the 3D structure of proteins

Corrêa

Arantes

Sens

et al. 2020

2020 IEEE Congress on Evolutionary Computation (CEC)

Self Cite

View full text Add to dashboard Cite

The protein structure prediction is one of the key problems in Structural Bioinformatics. The protein function is directly related to its conformation and the folding can provide to researchers better understandings about the protein roles in the cell. Several computational methods have been proposed over the last decades to tackle the problem. In this paper, we propose an ab initio algorithm with database information for the protein structure prediction problem. We do so by designing some versions of a multi-agent system that use concepts of dynamic distributed evolutionary algorithms to speed up and improve the optimization by better adapting the algorithm to the target protein. The dynamic strategy consists of auto-adapting the number of optimization agents according to the needs and current status of the optimization process. The system is able to scale in/out itself depending on some diversity criteria. The algorithms also take advantage of structural knowledge from the Protein Data Bank to better guide the search and constraint the state space. To validate our computational strategies, we tested them on a set of eight protein sequences. The obtained results were topologically compatible with the experimental correspondent ones, thus corroborating the promising performance of the strategies.

show abstract

“…There are several techniques that enable global minima search, such as big bang methodology (BB) (Lazauskas et al, 2017), basin-hopping (BH) (Rondina and Da Silva, 2013) and evolutionary algorithms, such as genetic algorithms (GA) (Johnston, 2003). Especially, GAs have been successfully applied to predict chemical structures from clusters to protein folding (Johnston, 2003; Louis and McDonnel, 2004; Heiles et al, 2012; Silva et al, 2014b; Borguesan et al, 2015; Song et al, 2018). Even so, finding the global minimum associated with these chemical systems implies efficiently exploring the most reasonable portions of their PES, which still is a challenging task.…”

Section: Introductionmentioning

confidence: 99%

A New Genetic Algorithm Approach Applied to Atomic and Molecular Cluster Studies

Silva

Belchior

2019

Front. Chem.

View full text Add to dashboard Cite

A new procedure is suggested to improve genetic algorithms for the prediction of structures of nanoparticles. The strategy focuses on managing the creation of new individuals by evaluating the efficiency of operators (o1, o2,…,o13) in generating well-adapted offspring. This is done by increasing the creation rate of operators with better performance and decreasing that rate for the ones which poorly fulfill the task of creating favorable new generation. Additionally, several strategies (thirteen at this level of approach) from different optimization techniques were implemented on the actual genetic algorithm. Trials were performed on the general case studies of 26 and 55-atom clusters with binding energy governed by a Lennard-Jones empirical potential with all individuals being created by each of the particular thirteen operators tested. A 18-atom carbon cluster and some polynitrogen systems were also studied within REBO potential and quantum approaches, respectively. Results show that our management strategy could avoid bad operators, keeping the overall method performance with great confidence. Moreover, amongst the operators taken from the literature and tested herein, the genetic algorithm was faster when the generation of new individuals was carried out by the twist operator, even when compared to commonly used operators such as Deaven and Ho cut-and-splice crossover. Operators typically designed for basin-hopping methodology also performed well on the proposed genetic algorithm scheme.

show abstract

APL: An angle probability list to improve knowledge-based metaheuristics for the three-dimensional protein structure prediction

Cited by 40 publications

References 84 publications

Everyone Is a Protagonist: Residue Conformational Preferences in High-Resolution Protein Structures

Everyone Is a Protagonist: Residue Conformational Preferences in High-Resolution Protein Structures

A dynamic evolutionary multi-agent system to predict the 3D structure of proteins

A New Genetic Algorithm Approach Applied to Atomic and Molecular Cluster Studies

Contact Info

Product

Resources

About