Article
Multidisciplinary Sciences
Valeria Scardino, Juan I. Di Filippo, Claudio N. Cavasotto
Summary: A crucial component in structure-based drug discovery is high-quality three-dimensional structures of protein targets. When experimental structures are not available, homology modeling has been the preferred method. AlphaFold, an AI-based protein structure prediction method, has shown impressive accuracy. However, our evaluation using docking-based drug discovery revealed that AF models consistently performed worse compared to experimental structures. Post-modeling refinement strategies may be crucial to increase the chances of success.
Article
Biochemical Research Methods
Lianming Du, Chaoyue Geng, Qianglin Zeng, Ting Huang, Jie Tang, Yiwen Chu, Kelei Zhao
Summary: Molecular docking is a crucial approach in drug discovery and pharmaceutical research, and Dockey is a flexible and intuitive graphical interface tool that automates docking and analysis of large-scale ligands and receptors in parallel.
BRIEFINGS IN BIOINFORMATICS
(2023)
Review
Pharmacology & Pharmacy
Tong Qin, Zihao Zhu, Xiang Simon Wang, Jie Xia, Song Wu
Summary: The authors reviewed various computational methods for representing protein-ligand interfaces and discussed the impact on machine learning model performance. They highlighted the trend of extracting binding features automatically using deep learning, while also noting areas for improvement.
EXPERT OPINION ON DRUG DISCOVERY
(2021)
Article
Biochemical Research Methods
Taj Mohammad, Yash Mathur, Md Imtaiyaz Hassan
Summary: InstaDock is a free and open access GUI program that efficiently performs molecular docking and high-throughput virtual screening. It is the easiest and more interactive interface for molecular docking and high-throughput virtual screening compared to existing GUIs.
BRIEFINGS IN BIOINFORMATICS
(2021)
Article
Chemistry, Medicinal
Kushagra Kashyap, Pinaki Prasad Mahapatra, Shakil Ahmed, Erdem Buyukbingol, Mohammad Imran Siddiqi
Summary: In this study, a 3D convolutional neural network-based ALR2 inhibitor classification technique was developed, which successfully identified the top 10 compounds with high binding affinity. These compounds exhibited superior blood-brain barrier penetration efficiency and potential ALR2 inhibition activity, making them promising candidates for further research and optimization as anti-diabetic neuropathy drugs.
JOURNAL OF CHEMICAL INFORMATION AND MODELING
(2023)
Article
Biochemistry & Molecular Biology
Doretta Cuffaro, Aleix Gimeno, Bianca Laura Bernardoni, Riccardo Di Leo, Gerard Pujadas, Santiago Garcia-Vallve, Susanna Nencetti, Armando Rossello, Elisa Nuti
Summary: Scientists developed a virtual screening workflow to identify selective non-zinc-binding MMP-13 inhibitors by targeting its specific structural features. Three ligands that could inhibit MMP-13 in the micromolar range were discovered, and one of them showed selectivity over other MMPs. Structure-based analysis guided the chemical optimization, resulting in a new N-acyl hydrazone-based derivative with improved inhibitory activity and selectivity for the target enzyme.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2023)
Article
Biochemistry & Molecular Biology
Sohee Kwon, Chaok Seok
Summary: Protein-ligand docking is a crucial computational technique used for understanding protein functions and designing new molecules. One challenge in protein-ligand docking is accounting for protein conformational changes induced by ligand binding. This study introduces a docking method called CSAlign-Dock, which incorporates structure alignment to known complex structures and demonstrates superior performance.
COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL
(2023)
Review
Biochemistry & Molecular Biology
Hui Zhu, Yulin Zhang, Wei Li, Niu Huang
Summary: Structure-based virtual screening, also known as molecular docking, has gained increasing application in the early stage of drug discovery for discovering small-molecule ligands based on protein structures. This review comprehensively surveys the prospective applications of molecular docking with solid experimental validations. The analysis includes the novelty of targets and docking hits, practical protocols of docking screening, and the subsequent experimental validations. The majority of virtual screenings were performed on widely studied targets, with only a small portion focused on less-explored new targets. GLIDE is the most popular docking software, while the DOCK 3 series excels in large-scale virtual screening. The identified hits are promising in structural novelty, with a quarter of them exhibiting better potency than 1 μM. However, most studies only conducted in vitro bioassays for validation, potentially limiting the further characterization and development of the active compounds.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2022)
Article
Biochemistry & Molecular Biology
Gianvito Grasso, Arianna Di Gregorio, Bojan Mavkov, Dario Piga, Giuseppe Falvo D'Urso Labate, Andrea Danani, Marco A. Deriu
Summary: In this paper, a novel blind docking protocol based on Autodock-Vina is proposed, which combines binding site identification and binding pose prediction through systematic exploration of protein volume. With the application of MM/GBSA re-scoring procedures, the accuracy of protein-ligand bound state can be improved. Tested on various protein-ligand complexes, the FRAD approach combined with MM/GBSA re-scoring is considered a powerful tool to increase accuracy and efficiency, especially when the ligand-binding site is unknown.
JOURNAL OF BIOMOLECULAR STRUCTURE & DYNAMICS
(2022)
Article
Biochemical Research Methods
Chao Li, Jinxing Li, Jun Sun, Li Mao, Vasile Palade, Bilal Ahmad
Summary: In this study, a parallel multi-swarm cooperative particle swarm model is proposed, which achieves outstanding performance in protein-ligand docking and virtual screening.
BMC BIOINFORMATICS
(2022)
Article
Biochemical Research Methods
Qilong Wu, Sheng-You Huang
Summary: Covalent inhibitors have attracted attention for their long residence time, high binding efficiency, and strong selectivity. The development of computational tools like HCovDock, an efficient docking algorithm for covalent protein-ligand interactions, is valuable for modeling and screening of covalent drugs. HCovDock outperforms seven other state-of-the-art covalent docking programs and exhibits a high success rate in reproducing experimentally observed structures and virtual screening.
BRIEFINGS IN BIOINFORMATICS
(2023)
Article
Biochemical Research Methods
Qilong Wu, Sheng-You Huang
Summary: Covalent inhibitors are highly valued for their long residence time, high binding efficiency, and strong selectivity. The development of computational tools like molecular docking, such as HCovDock, is important for modeling covalent protein-ligand interactions and screening potential drugs. HCovDock shows better performance than other state-of-the-art docking programs and has high success rates in reproducing experimentally observed structures.
BRIEFINGS IN BIOINFORMATICS
(2022)
Article
Medicine, Research & Experimental
Li-Chun Lin, Hsin-Yi Chang, Tony Eight Lin, Jyh-Ruey Lin, Shih-Min Hsia, Kai-Cheng Hsu, Tsui-Chin Huang
Summary: This study identified novel GLS inhibitors through structure-based virtual screening and demonstrated their potential in anticancer treatment.
BIOMEDICINE & PHARMACOTHERAPY
(2022)
Article
Chemistry, Medicinal
Joel Ricci-Lopez, Sergio A. Aguila, Michael K. Gilson, Carlos A. Brizuela
Summary: The study demonstrates that using machine learning methods to process ensemble docking results can significantly improve the predictive power of structure-based virtual screening.
JOURNAL OF CHEMICAL INFORMATION AND MODELING
(2021)
Article
Biology
Yulong Shi, Xinben Zhang, Yanqing Yang, Tingting Cai, Cheng Peng, Leyun Wu, Liping Zhou, Jiaxin Han, Minfei Ma, Weiliang Zhu, Zhijian Xu
Summary: In order to improve the reliability of drug target prediction, researchers integrated multiple-conformation based docking, 2D/3D ligand similarity search, and deep learning methods to construct a comprehensive platform called D3CARP for target prediction and virtual screening.
COMPUTERS IN BIOLOGY AND MEDICINE
(2023)