Hot Spots & Hot Regions Detection Using Classification Algorithms in BMPs Complexes at the Protein-Protein Interface with the Ground-State Energy Feature

O. Chaparro-Amaro, M. Martínez-Felipe, J. Martínez-Castro

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

We present the results of the application of some machine learning algorithms to predict the hot spots & hot regions residues in protein complexes at the protein-protein interface between their polypeptide chains. The dataset consisted of twenty-nine bone morphogenetic proteins (BMPs) obtained from the Protein Data Bank (PDB). The training features were selected from biochemical and biophysical properties such as B-factor, hydrophobicity index, prevalence score, accessible surface area (ASA), conservation score, and the ground-state energy (using Density Functional Theory (DFT)) of each amino acid of these interfaces. Also, we implemented parallel CPU/GPU hardware acceleration techniques during the preprocessing in order to speed up the ASA and DFT calculations with more efficient execution times. We evaluated the performance of the classifiers with several metrics. The random forest classifier obtained the best performance, achieving an average of 90 % of well-classified residues in both the true negative and true positive rates.

Original languageEnglish
Title of host publicationPattern Recognition - 14th Mexican Conference, MCPR 2022, Proceedings
EditorsOsslan Osiris Vergara-Villegas, Vianey Guadalupe Cruz-Sánchez, Juan Humberto Sossa-Azuela, Jesús Ariel Carrasco-Ochoa, José Francisco Martínez-Trinidad, José Arturo Olvera-López
PublisherSpringer Science and Business Media Deutschland GmbH
Pages3-14
Number of pages12
ISBN (Print)9783031077494
DOIs
StatePublished - 2022
Event14th Mexican Conference on Pattern Recognition, MCPR 2022 - Ciudad Juárez, Mexico
Duration: 22 Jun 202225 Jun 2022

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume13264 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference14th Mexican Conference on Pattern Recognition, MCPR 2022
Country/TerritoryMexico
CityCiudad Juárez
Period22/06/2225/06/22

Keywords

  • BMPs
  • DFT
  • Hot regions
  • Hot spots

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