Books

 

 

 

Projects

 

 

 

Citation

 

Editorships

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Frontiers Section Editor (Bioinformatics and Biophysics) for the Current Drug Targets ISSN: 1873-5592

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Section Editor (Bioinformatics in Drug Design and Discovery) for the Current Medicinal Chemistry ISSN: 1875-533X

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Member of the Editorial Board for the PeerJ ISSN: 2167-8359

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Member of the Editorial Board for the Current Bioinformatics ISSN: 2212-392X (Online) ISSN: 1574-8936 (Print)

 

Research

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Protein-Ligand Interacions

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Molecular Docking

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Bioinspired Computing

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Computational Systems Biology

 

Recent Publications

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Volkart PA et al. Curr Drug Targets. 2019;20(7):716-726

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Russo S, De Azevedo WF. Curr Med Chem 2019. 26(10):1908-1919

        

Tutorials

Programs PDF
Ramachandran Plot in Python

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Here we describe a program written in Python to generate Ramachandran plots. Information to generate plots is based on the atomic coordinates of a protein structure in the PDB format. In the Ramachandran plot, the x-axis is for phi angle and y-axis is for psi. Both axis range from -180o to +180o.

Keywords: Crystal Structure; Ramachadran plot; protein structure; Python; rotatable angles; torsion angles

Dihedral Angle in Python

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This tutorial presents the equation for the dihedral angle and describes its implementation in the Python programming language. A dihedral angle is defined by four non collinear points. Points P1, P2, and P3 define the plane P1P2P3, points P2, P3, and P4 define a second plane, referred to as P2P3P4. The angle between these two planes is referred to as dihedral angle thera.

Keywords: Dihedral angle; Python; geometry

B-factor Plot in Python

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Here we describe a program to generate B-factor plot using information from a PDB (Berman, Westbrook, Feng et al. 2000; Berman, Battistuz, Bhat et al. 2002; Westbrook et al., 2003) file. The program generates a plot where we have the mean B-factor per residue in a PDB file. In the plot we have three lines, one for all atoms in the residue, the second for main-chain atoms and the last for side-chain atoms. Only protein atoms are considered for the plot. In the plot, x-axis is for residue number and y-axis is for mean B-factor in Å2.

Keywords: Protein structure; B-factor; temperature factor; Debye-waller factor; Protein Data Bank; Python

Docking Root Mean Square Deviation in Python

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In molecular docking simulations, the best pose is the one closer to the structure determined by x-ray crystallography. Therefore, we must establish a methodology that assesses the quality of the computer-generated solution (pose). This quality can be calculated using the root mean-square deviation (RMSD), which is a measure of the differences between values predicted by a model and the values actually observed from the object being modeled or estimated (protein-igand complex). The docking RMSD is calculated between two sets of atomic coordinates, in this case, one for the crystallographic structure (x1, y1, z1; the object being modeled) and another for the atomic coordinates obtained from the docking simulations (x2, y2, z2; predicted model) (Heberlé and De Azevedo, 2011)

Keywords: Protein-ligand docking; protein-ligand interactions; root mean-square deviation; Protein Data Bank; Python

Linear Regression in Python Using NumPy

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In this tutorial, it is shown how to program a simple linear regression analysis using polyfit() function available in the NumPy library. The code is straightforward and has been posted for educational purposes. The program reads a csv file and selects two columns of this file to carry out a linear regression analysis. The program shows the results on the screen and generates a plot file. The code itself is not optimized and is provided as it is with no guarantees (GNU license). To run the program described here; it is necessary to have Python 3 installed. We also need the NumPy and Matplotlib libraries.

Keywords: Linear regression; python; NumPy; csv file; polyfit()