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Protein structure databases

Identification of potential interleukin-8 inhibitors acting on the interactive site between chemokine and CXCR2 receptor: A computational approach

Thi-Thuy-Nga Tran, Que-Huong Tran, [ ... ], Khac-Minh Thai

Structural systems pharmacology: A framework for integrating metabolic network and structure-based virtual screening for drug discovery against bacteria

Elmira Nazarshodeh, Sayed-Amir Marashi, Sajjad Gharaghani

Principal component analysis of alpha-helix deformations in transmembrane proteins

Alexander Bevacqua, Sachit Bakshi, Yu Xia

PDBrenum: A webserver and program providing Protein Data Bank files renumbered according to their UniProt sequences

Bulat Faezov, Roland L. Dunbrack Jr.

Predicting aptamer sequences that interact with target proteins using an aptamer-protein interaction classifier and a Monte Carlo tree search approach

Gwangho Lee, Gun Hyuk Jang, Ho Young Kang, Giltae Song

Molecular dynamics analysis of N-acetyl-D-glucosamine against specific SARS-CoV-2’s pathogenicity factors

Ömür Baysal, Naeem Abdul Ghafoor, [ ... ], Volha Kniazeva

MCPdb: The bacterial microcompartment database

Jessica M. Ochoa, Kaylie Bair, [ ... ], Todd O. Yeates

Naegleria fowleri: Protein structures to facilitate drug discovery for the deadly, pathogenic free-living amoeba

Logan Tillery, Kayleigh Barrett, [ ... ], Wesley C. Van Voorhis

A chemical interpretation of protein electron density maps in the worldwide protein data bank

Sen Yao, Hunter N. B. Moseley

A simple strategy to enhance the speed of protein secondary structure prediction without sacrificing accuracy

Sheng-Hung Juan, Teng-Ruei Chen, Wei-Cheng Lo

Structure-based drug repositioning explains ibrutinib as VEGFR2 inhibitor

Melissa F. Adasme, Daniele Parisi, [ ... ], Michael Schroeder

Multifaceted analysis of training and testing convolutional neural networks for protein secondary structure prediction

Maxim Shapovalov, Roland L. Dunbrack Jr., Slobodan Vucetic

QUATgo: Protein quaternary structural attributes predicted by two-stage machine learning approaches with heterogeneous feature encoding

Chi-Hua Tung, Ching-Hsuan Chien, [ ... ], Yen-Wei Chu

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