Article
Biochemistry & Molecular Biology
Ningning Fan, Steffen Hirte, Johannes Kirchmair
Summary: In this study, three strategies for maximizing the virtual screening performance of pairwise comparison methods for 2D and 3D molecular structures were explored. The integration of 2D and 3D methods using a parallel selection strategy showed the clearest advantages. The integrated approach yielded higher AUC values, EF1%, and SRR1% compared to using 2D and 3D methods separately with a single query molecule.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2022)
Article
Biochemistry & Molecular Biology
Oluwakemi Ebenezer, Maryam A. Jordaan, Nkululeko Damoyi, Michael Shapi
Summary: Noroviruses are non-enveloped viruses causing acute gastroenteritis in humans. The RNA-dependent RNA polymerase is a critical target for developing anti-norovirus agents. Compounds CID-57930781 and CID-44396095 show promising potential as human norovirus inhibitors.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2021)
Article
Computer Science, Interdisciplinary Applications
Gelareh Valizadeh, Farshid Babapour Mofrad, Ahmad Shalbaf
Summary: A novel parametric-based feature selection method using three-dimensional spherical harmonic shape descriptors of the left ventricle for intelligent myocardial infarction classification was proposed and validated using a dataset from the ACDC database. The study demonstrated the effectiveness of combining SH coefficients and machine learning techniques, introducing an optimal feature set with maximum discriminant strength. Results showed superior performance compared to conventional methods and clinical measures, confirming the method's accuracy and generalizability in dilated cardiomyopathy detection.
MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING
(2021)
Article
Biochemical Research Methods
Zhenla Jiang, Jianrong Xu, Aixia Yan, Ling Wang
Summary: The study evaluated 15 3D molecular similarity programs against two datasets and found that some academic tools may outperform commercial software in terms of virtual screening performance; 3D similarity VS tools exhibit considerable capability in capturing active compounds with new chemotypes; Multiple conformers generally improve performance for most 3D similarity tools.
BRIEFINGS IN BIOINFORMATICS
(2021)
Article
Chemistry, Medicinal
Erma Fatiha Muhammad, Ashutosh Kumar, Habibah A. Wahab, Kam Y. J. Zhang
Summary: A new class of AChE inhibitors, 1,2,4-triazolylthioethanones, was identified using a virtual screening approach. These compounds showed IC50 values ranging from 0.15 +/- 0.07 to 3.32 +/- 0.92 μM, and could potentially serve as a starting point for novel therapeutics for Alzheimer's disease.
MOLECULAR INFORMATICS
(2021)
Article
Biochemical Research Methods
Yue Zhao, Xiang-Gui Wang, Zhong-Ye Ma, Guo-Li Xiong, Zhi-Jiang Yang, Yan Cheng, Ai-Ping Lu, Zhi-Jun Huang, Dong-Sheng Cao
Summary: PARP1 inhibitors are important for ovarian and breast cancer therapies, but current inhibitors have some disadvantages. By employing various virtual screening methods and discovering molecules with novel frameworks, the screening efficiency can be improved, laying the foundation for broader clinical applications.
BRIEFINGS IN BIOINFORMATICS
(2021)
Article
Biochemistry & Molecular Biology
Maiia E. Bragina, Antoine Daina, Marta A. S. Perez, Olivier Michielin, Vincent Zoete
Summary: SwissSimilarity is a web tool for virtual screening of chemical libraries to find molecules similar to a compound of interest. The new version offers additional methods for estimating molecular similarity and improved user experience.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2022)
Article
Chemistry, Medicinal
Nattanan Jiwacharoenchai, Rungroj Saruengkhanphasit, Worawat Niwetmarin, Supaporn Seetaha, Kiattawee Choowongkomon, Somsak Ruchirawat, Chatchakorn Eurtivong
Summary: By conducting a similarity search on the U.S. Enhanced National Cancer Institute Database Browser 2.2, compounds related to a known EGFR-TK inhibitor were identified. Five candidates with strong antiproliferative activities against overexpressed EGFR-TK cancer cell lines were selected through virtual screening and bioactivity testing. Molecular docking analysis and physicochemical property calculations suggested their potential as drug-like orally active compounds.
BIOORGANIC & MEDICINAL CHEMISTRY LETTERS
(2022)
Article
Engineering, Multidisciplinary
Giuseppe Puglisi, Nicola M. Pugno
Summary: In this study, we propose a new conceptual approach to achieve unattained dissipative properties based on the friction of slender concentric sliding columns. By searching for the optimal topology in a telescopic system and using multiscale self-similar reconstruction, we obtain a theoretical optimal fractal limit system. The dissipation of this system shows a great advantage compared to material dissipation, and it has potential applications in various technological fields.
INTERNATIONAL JOURNAL OF ENGINEERING SCIENCE
(2022)
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)
Article
Biochemistry & Molecular Biology
Jacob Spiegel, Hanoch Senderowitz
Summary: Virtual screening is a common method used in drug and material design projects. The enrichment optimization algorithm (EOA) is a recently developed algorithm that can derive QSAR models for virtual screening. In this study, an improved version of EOA was compared with three docking tools and showed superior performance in terms of overall and initial success of the virtual screening process. The EOA algorithm has the potential to be combined with molecular docking to develop target-specific scoring functions.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2022)
Article
Computer Science, Artificial Intelligence
Fouaz Berrhail, Hacene Belhadef, Mohammed Haddad
Summary: LBVS plays a crucial role in the early stage of drug discovery, solving time and cost issues associated with traditional methods. The proposed method based on Deep Convolutional Neural Network (DCNN) demonstrates superior performance compared to conventional methods through new learning representation for chemical compounds.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Chemistry, Applied
Zhenjie Mao, Hong Jiang, Jianan Sun, Xiangzhao Mao
Summary: In this study, molecular docking and BLAST were used to rapidly screen and optimize XO inhibitory peptides from Pacific white shrimp. Seven new peptides were identified, and YNITGW showed the strongest activity. Insertion of Trp residue enhanced the inhibitory activity. This study demonstrated that molecular docking is a novel and feasible method for obtaining bio-active peptides.
Article
Biochemistry & Molecular Biology
Elena Rica, Susana Alvarez, Francesc Serratosa
Summary: This paper explores the distance between attributed graphs for analyzing bioactivity dissimilarity, optimizing it by defining transformation costs, and proposing an algorithm to learn these costs. Experimental results demonstrate that with learned costs, the identification of bioactivity similarities in a group of molecules can be improved.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2021)
Article
Computer Science, Artificial Intelligence
Asuka Hisatomi, Hitomi Koba, Kazunori Mizuno, Satoshi Ono
Summary: Escher-like tiling design is a challenging problem, and conventional methods have some issues. In this paper, a new method called ELTHON is proposed, which can generate tileable shapes more effectively and avoid the generation of non-tileable shapes. Experimental results show that ELTHON outperforms traditional methods in the design process.
APPLIED SOFT COMPUTING
(2021)