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Journal : Bioinformatics and Biomedical Research Journal

Identification of Significant Proteins in Coronavirus Disease 2019 Protein-Protein Interaction Using Principal Component Analysis and ClusterONE Ananta Kusuma, Wisnu; Farhan Ramadhani , Hilmi; Annisa
Bioinformatics and Biomedical Research Journal Vol. 3 No. 2 (2020): Volume 3 issue 2
Publisher : Future Science

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Coronavirus Disease 2019 (COVID-19) will cause disease complications and organ damage due to excessive inflammatory reactions if left untreated. Computational analysis of protein-protein interactions can be carried out in various ways, including topological analysis and clustering of protein-protein interaction networks. Topological analysis can identify significant proteins by measuring the most important nodes with centrality measurements. By using Principal Component Analysis (PCA), the types of centrality measures were extracted into the overall centrality value. The study aimed to found significant proteins in COVID-19 protein-protein interactions using PCA and ClusterONE. This study used 57 proteins associated with COVID-19 to obtain protein networks. All of these proteins are homo sapiens organism. The number of proteins and the number of interactions from 57 proteins were 357 proteins and 1686 interactions. The results of this study consisted of two clusters; the best cluster was the first cluster with a lower p-value but had an average overall centrality value that closed to the second cluster. There are twenty important proteins in that cluster, and all of these proteins are related to COVID-19. These proteins are expected to be used in the process of discovering medicinal compounds in COVID-19.
Prediction of Drug-Target Interaction Using Random Forest in Coronavirus Disease 2019 Case Fadli , Aulia; Annisa , Annisa; Kusuma, Wisnu Ananta
Bioinformatics and Biomedical Research Journal Vol. 4 No. 1 (2021): Vol 4 No 1 (2021)
Publisher : Future Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11594/bbrj.04.01.01

Abstract

Coronavirus disease 2019 is an infectious disease that causes severe respiratory, digestive, and systemic infections that caused a pandemic in 2019. One of the focuses of the drug development process to fight the coronavirus disease 2019 is by carrying out drug repurposing. This study uses random forest with a feature-based chemogenomics approach on the drug-target interaction data of coronavirus disease 2019. The feature extraction process is carried out on compounds and protein using PubChem fingerprint and amino acid composition respectively. Feature selection using XGBoost is done to reduce the data dimension. The random undersampling process was also carried out to solve the problem of imbalanced data in the dataset. Using the cross-validation process, the random forest model produced an average accuracy value of 0.98, recall value of 0.92, precision value of 0.95, AUROC value of 0.95, and F1 score of 0.93. The random forest model also produced an accuracy value of 0.99, recall value of 0.93, the precision value of 0.94, AUROC value of 0.99, and F-measure of 0.94 when used to predict the original dataset (dataset without random undersampling process).
Co-Authors Abdul Aziz Abdul Rahman Saleh Agus Buono Ahmad, Tarmizi Aini Fazriani Aisah Rini Susanti Alami, Tegar Albert Adrianus Ali Djamhuri Annisa Annisa Annisa , Annisa Annisa Annisa Annisa Annisa Annisa Annisa Annisa Annisa Anton Suryatama Arini Aha Pekuwali Arini Pekuwali Arwan Subakti Ary Prabowo Auliatifani, Reza Auliya Ilmiawati Auriza Rahmad Akbar Badollahi Mustafa Badrut Tamam Bahrul Ulum BUDI TJAHJONO Budi Tjahjono Dahrul Syah Diah Handayani Dian Indah Savitri Dian Kartika Utami Essy Harnelly Fadli , Aulia Fahrury Romdendine, Muhammad Farhan Ramadhani , Hilmi Farit Mochamad Afendi Farohaji Kurniawan Fatriani, Rizka Fazriani, Aini Firman Ardiansyah Halida Ernita Handayani, Vitri Aprilla Hanifah Nuryani Lioe Hardi, Wishnu Hasibuan, Lailan Sahrina Hendra Rahmawan Hendra Rahmawan Hera Dwi Novita Heru Sukoco Imas Sukaesih Sitanggang Indra Astuti Ira Maryati Irfan Wahyudin Irma Herawati Suparto Irman Hermadi Irmanida Batubara Irvan Lewenusa ISKANDAR ZULKARNAEN SIREGAR Isnan Mulia Janti G. Sudjana Jaya Sena Turana Joni Prasetyo Kana Saputra S Kangko, Danang Dwijo Karlisa Priandana Khaydanur Khaydanur Khaydanur, Khaydanur Laela Wulansari Larasati Larasati Lina Herlina Tresnawati Listina Setyarini Lusi Agus Setiani Maggy T. Suhartono Mala Nurilmala Medria Kusuma Dewi Hardhienata Mohamad Rafi Mohamad Rafi Mohamad Rafi Mohammad Romano Diansyah Mohammad Romano Diansyah Muchlishah Rosyadah Muh Fadhil Al-Haaq Ginoga Muhammad Asyhar Agmalaro Muhammad Subianto Mulyati Mulyati Mushthofa Mushthofa Mushthofa Muttaqin, Muhammad Rafi Nabila Sekar Ramadhanti Nasution, Tegar Alami Nengsih, Nunuk Kurniati Norma Nur Azizah Nunuk Kurniati Nengsih Nur Choiriyati Nurdevi Noviana Ovi Sofia Pramita Andarwati Prihasuti Harsani Priyo Raharjo Pudji Muljono Purnajaya, Akhmad Rezki Purnomo, Tsania Firqin Ramdan Satra Ratu Mutiara Siregar Refianto Damai Darmawan Refianto Damai Darmawan Resnawati Reza Auliatifani Rif’ati, Lutfah Rizky Maulidya Afifa Ronald Marseno Rosy Aldina Rudi Heryanto SATRIYAS ILYAS Septaningsih, Dewi Anggraini Siti Syahidatul Helma Sony Hartono Wijaya Sri Nurdiati Sulistyo Basuki Sulistyo Basuki Supriyanto, Arif Syahid Abdullah Syarifah Aini Syarifah Fathimah Azzahra Syukriyansyah Taufik Djatna Toni Afandi Tsania Firqin Purnomo Usman, Muhammad Syafiuddin Wa Ode Rahma Agus Udaya Manarfa Wahjuni, Sri Widya Sari Wijaya, Eko Praja Hamid Wina Yulianti Wishnu Hardi Wulansari, Laela Yandra Arkeman Yessy Yanitasari Yudhi Trisna Atmajaya Yulianah Yulianah Yunita Fauzia Achmad Zulkarnaen, Silvia Alviani