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)
Article
Biochemistry & Molecular Biology
Takatsugu Kosugi, Masahito Ohue
Summary: The study developed a quantitative estimation index QEPPI specifically for early screening of compounds targeting protein-protein interactions, which showed better performance compared to the commonly used method QED.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2021)
Article
Chemistry, Multidisciplinary
Francesca Vasile, Francesca Lavore, Silvia Gazzola, Chiara Vettraino, Emilio Parisini, Umberto Piarulli, Laura Belvisi, Monica Civera
Summary: Cadherins promote cell-cell adhesion and have broad physiological effects on tissue organization and homeostasis. Dysregulation of cadherins contributes to cancer progression and metastasis. Targeting the cadherin adhesive interface with small-molecule antagonists has potential therapeutic and diagnostic value.
FRONTIERS IN CHEMISTRY
(2022)
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
Biochemistry & Molecular Biology
Naomi Scarano, Elena Abbotto, Francesca Musumeci, Annalisa Salis, Chiara Brullo, Paola Fossa, Silvia Schenone, Santina Bruzzone, Elena Cichero
Summary: This article focuses on the selective inhibitors of SIRT2 enzyme. By using SBVS method, a potential molecular scaffold for designing new SIRT2 inhibitors was identified. Experimental results showed that this molecular scaffold exhibited strong SIRT2 inhibitory activity, validating the effectiveness of the research strategy.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2023)
Article
Chemistry, Medicinal
Laura Calvo-Barreiro, Valerij Talagayev, Szymon Pach, Somaya A. Abdel-Rahman, Gerhard Wolber, Moustafa T. Gabr
Summary: Currently, there are no clinically approved small molecules as immune checkpoint modulators. This study developed a virtual screening strategy to identify small molecules that bind to a novel druggable binding pocket in human ICOS. The strategy successfully found a first-in-class small molecule ICOS binder and validated screening platforms for ICOS-targeted small molecules.
Review
Pharmacology & Pharmacy
F. Potlitz, A. Link, L. Schulig
Summary: Virtual screening approaches, especially AI-assisted deep learning methods, are effective in dealing with ultra-large compound libraries and have shown promise in discovering novel drugs against SARS-CoV-2.
EXPERT OPINION ON DRUG DISCOVERY
(2023)
Article
Biochemistry & Molecular Biology
Chengqian Wei, Junjie Huang, Yu Wang, Yifang Chen, Xin Luo, Shaobo Wang, Zengxue Wu, Jixiang Chen
Summary: A series of new oxadiazole sulfone derivatives containing an amide moiety were synthesized to screen high-efficiency antibacterial agents for rice bacterial diseases. Compound 10 showed excellent antibacterial activity against Xanthomonas oryzae pv. oryzae and Xanthomonas oryzae pv. oryzicola, with EC50 values superior to commercial bactericides. Compound 10 demonstrated superior protective and curative activities against rice bacterial leaf blight and rice bacterial leaf streak compared to other tested compounds. Additionally, compound 10 exhibited potential mechanisms of action by affecting extracellular polysaccharides, cell membranes, and enzyme activity of dihydrolipoamide S-succinyltransferase to inhibit the growth of Xanthomonas oryzae pv. oryzae and Xanthomonas oryzae pv. oryzicola.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2021)
Article
Biochemistry & Molecular Biology
Qingtong Zhou, Wanjing Guo, Antao Dai, Xiaoqing Cai, Marton Vass, Chris de Graaf, Wenqing Shui, Suwen Zhao, Dehua Yang, Ming-Wei Wang
Summary: Allosteric modulators offer pharmacological advantages by affecting downstream signaling without competing for orthosteric sites. Computational approaches were used to identify allosteric modulators targeting GLP-1R, resulting in the discovery of negative and positive modulators through structure-based and ligand-based virtual screening methods, respectively. This computational approach may be applicable for discovering allosteric modulators of other GPCRs.
Article
Chemistry, Multidisciplinary
Ashley E. Modell, Frank Marrone, Nihar R. Panigrahi, Yingkai Zhang, Paramjit S. Arora
Summary: Constrained peptides are a valuable source of ligands for protein surfaces, but their binding affinity is often limited. This study proposes the use of nonnatural side chains to enhance binding affinity by accessing unoccupied crevices on the receptor surface. The computational method, AlphaSpace, was used to predict peptide ligands for the KIX domain of the p300/CBP coactivator, and experimental screening was performed to fine-tune the nonnatural side chains. The combined computational-experimental approach offers a general framework for optimizing peptidomimetics as inhibitors of protein-protein interactions.
JOURNAL OF THE AMERICAN CHEMICAL SOCIETY
(2022)
Article
Biochemistry & Molecular Biology
Sadhana Sundararajan, Keerthana Karunakaran, Rajiniraja Muniyan
Summary: The highly flexible nature of Mycobacterium tuberculosis (Mtb) is attributed to its tough cell wall and multiple gene interaction system, making it resistant to frontline TB drugs. In this study, in-silico structure based drug discovery was used to understand the interaction of compounds from an open source library (NPASS) with the target protein FabD. Three compounds with strong binding energies were identified and further evaluated for their interaction with FabD protein. The potential hit compounds could be considered for in-vitro evaluation against mutated FabD protein.
JOURNAL OF BIOMOLECULAR STRUCTURE & DYNAMICS
(2023)
Article
Chemistry, Multidisciplinary
Ross P. Thomas, Rachel E. Heap, Francesca Zappacosta, Emma K. Grant, Peter Pogany, Stephen Besley, David J. Fallon, Michael M. Hann, David House, Nicholas C. O. Tomkinson, Jacob T. Bush
Summary: The study introduces a screening platform that combines 'direct-to-biology' high-throughput chemistry with photoreactive fragments for rapid synthesis and screening of chemical tools. The platform allows for iterative design-make-test cycles to accelerate the development and optimization of chemical tools and medicinal chemistry starting points with minimal resource investment.
Article
Pharmacology & Pharmacy
Vishwesh Venkatraman, Thomas H. Colligan, George T. Lesica, Daniel R. Olson, Jeremiah Gaiser, Conner J. Copeland, Travis J. Wheeler, Amitava Roy
Summary: The SARS-CoV2 pandemic emphasizes the importance of efficient drug identification methods. Virtual screening methods have the potential to evaluate billions of candidate molecules, expanding the search space and speeding up discovery. This article describes a new screening pipeline called drugsniffer, capable of rapidly exploring drug candidates from a library of billions of molecules.
FRONTIERS IN PHARMACOLOGY
(2022)
Article
Pharmacology & Pharmacy
Huizhen Ge, Lizeng Peng, Zhou Sun, Huanxiang Liu, Yulin Shen, Xiaojun Yao
Summary: In this study, novel HPK1 inhibitors were identified using virtual screening and kinase inhibition assays. Molecular dynamics simulations were performed to analyze the interaction between the identified compounds and HPK1 kinase domain. The most potent compound showed potential for further development as an HPK1 inhibitor for immunotherapy.
FRONTIERS IN PHARMACOLOGY
(2022)
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)
Article
Biochemical Research Methods
Sai Raghavendra Maddhuri Venkata Subramaniya, Genki Terashi, Aashish Jain, Yuki Kagaya, Daisuke Kihara
Summary: This study introduces a novel contact map refinement method called ContactGAN, utilizing Generative Adversarial Networks (GAN). ContactGAN demonstrates significant improvement in contact prediction accuracy, leading to enhanced accuracy of protein tertiary structure models.
Article
Biochemistry & Molecular Biology
Jacob Verburgt, Daisuke Kihara
Summary: Protein structure docking involves predicting the quaternary structure of a protein complex from individual tertiary structures of its subunits, typically done in two main steps: docking the subunits rigidly to form the complex, followed by structure refinement. Benchmarking eight protein structure refinement methods showed that improving the fraction of native contacts between subunits was straightforward, while refining backbone dependent metrics based on Root Mean Square Deviation proved more challenging.
PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS
(2022)
Article
Chemistry, Multidisciplinary
Lyman Monroe, Daisuke Kihara
Summary: The stability of protein structures can be measured by AFM pulling experiments, and this study used computational pulling to estimate the accuracy of protein structure models. It was found that near-native models can be selected by examining the break forces, indicating that high break force indicates high stability of models.
JOURNAL OF COMPUTATIONAL CHEMISTRY
(2022)
Article
Biochemical Research Methods
Florent Langenfeld, Tunde Aderinwale, Charles Christoffer, Woong-Hee Shin, Genki Terashi, Xiao Wang, Daisuke Kihara, Halim Benhabiles, Karim Hammoudi, Adnane Cabani, Feryal Windal, Mahmoud Melkemi, Ekpo Otu, Reyer Zwiggelaar, David Hunter, Yonghuai Liu, Lea Sirugue, Vinh-Thuyen Nguyen-Truong, Danh Le, Hai-Dang Nguyen, Minh-Triet Tran, Matthieu Montes
Summary: Proteins play a crucial role in cellular mechanisms and activities. This study assesses the ability of different methods to detect similarities between proteins based on their surface geometry, and discusses the influence of electrostatic information on protein surfaces.
JOURNAL OF MOLECULAR GRAPHICS & MODELLING
(2022)
Article
Biology
Tunde Aderinwale, Vijay Bharadwaj, Charles Christoffer, Genki Terashi, Zicong Zhang, Rashidedin Jahandideh, Yuki Kagaya, Daisuke Kihara
Summary: The 3D-AF-Surfer tool enables real-time structure-based search and comparison of protein structures between AlphaFold2 models and the PDB database, facilitating structural analysis and application research.
COMMUNICATIONS BIOLOGY
(2022)
Article
Biochemical Research Methods
Genki Terashi, Xiao Wang, Sai Raghavendra Maddhuri Venkata Subramaniya, John J. G. Tesmer, Daisuke Kihara
Summary: The DAQ score is a method that assesses the consistency of amino acid assignment in protein structure models with local density from cryo-EM maps. It uses deep learning to estimate the likelihood that the local density corresponds to different amino acids and assesses the consistency of the assignment with that likelihood.
Article
Plant Sciences
Anna T. Olek, Phillip S. Rushton, Daisuke Kihara, Peter Ciesielski, Uma K. Aryal, Zicong Zhang, Cynthia Stauffacher, Maureen C. McCann, Nicholas C. Carpita
Summary: This study investigated two plant-unique sequences in cellulose synthases and found that certain amino acid residues within these sequences play a crucial role in their function, while others do not.
Article
Biochemical Research Methods
Charles Christoffer, Daisuke Kihara
Summary: Proteins and nucleic acids play crucial roles in various cellular processes, and their interactions are of great importance. Understanding the mechanisms of these interactions requires considering the 3D atomic structures of protein-nucleic acid complexes. When experimental structures are not available, protein docking can generate useful models computationally. However, traditional protein docking methods often have limitations in considering large-scale flexibility. Our previous work introduced a flexible protein docking method, Flex-LZerD, which can model ordered proteins undergoing significant conformational changes and is compatible with nucleic acids. In this study, we further demonstrate the ability of Flex-LZerD to model interactions between proteins and nucleic acids, showing an expanded range of interactions and conformational changes compared to previous methods.
Article
Biochemistry & Molecular Biology
Woong-Hee Shin, Keiko Kumazawa, Kenichiro Imai, Takatsugu Hirokawa, Daisuke Kihara
Summary: The driving mechanisms of many biological functions in a cell involve physical interactions between proteins. Protein-protein interactions (PPIs) also play a significant role in disease development, making them promising therapeutic targets in the pharmaceutical industry. This study introduces a novel method called protein-protein interaction-Surfer, which uses a three-dimensional Zernike descriptor (3DZD) to compare and quantify the similarity of local surface regions of PPIs. The performance of protein-protein interaction-Surfer was evaluated using datasets of PPIs, demonstrating its ability to identify similar potential drug binding regions without sequence and structure similarity.
FRONTIERS IN MOLECULAR BIOSCIENCES
(2023)
Letter
Biochemical Research Methods
Tsukasa Nakamura, Xiao Wang, Genki Terashi, Daisuke Kihara
Article
Biochemistry & Molecular Biology
Jennifer J. Lee, Swetha Ramadesikan, Adrianna F. Black, Charles Christoffer, Andres F. Pacheco Pacheco, Sneha Subramanian, Claudia B. Hanna, Gillian Barth, Cynthia V. Stauffacher, Daisuke Kihara, Ruben Claudio Aguilar
Summary: Lowe Syndrome is caused by mutations in the OCRL1 gene and is characterized by congenital cataracts, intellectual disability, and kidney malfunction. This study focuses on investigating the impact of OCRL1 variants on the biochemical and phenotypic characteristics. The results suggest that not all mutations affecting the catalytic domain impair OCRL1's enzymatic activity, supporting the hypothesis of an inactive conformation.
Article
Biochemical Research Methods
Xiao Wang, Genki Terashi, Daisuke Kihara
Summary: DNA and RNA play vital roles in cellular processes, and understanding their functions relies on the knowledge of their three-dimensional structures. However, modeling the structures of DNA and RNA remains challenging, especially at resolutions lower than atomic level, and there is a lack of computational methods for nucleic acid structure modeling. In this study, a fully automated de novo DNA/RNA structure modeling method based on deep learning called CryoREAD is proposed. CryoREAD accurately identifies and models phosphate, sugar and base positions in cryo-EM maps, outperforming existing methods. The method was also applied to cryo-EM maps of SARS-CoV-2 biomolecular complexes.
Article
Biology
Nabil Ibtehaz, Yuki Kagaya, Daisuke Kihara
Summary: This study utilizes a self-supervised protocol to generate functionally informed embedding representations for protein domains, which outperform large-scale protein language models in function prediction tasks. A new function prediction method based on these domain embeddings achieves superior performance compared to existing predictors.
COMMUNICATIONS BIOLOGY
(2023)
Article
Biochemical Research Methods
Sai Raghavendra Maddhuri Venkata Subramaniya, Genki Terashi, Daisuke Kihara
Summary: This study presents a novel approach called EM-GAN that modifies input cryo-EM maps to improve protein structure modeling. The method uses a 3D generative adversarial network (GAN) trained on high- and low-resolution density maps to learn density patterns and enhance the suitability of the input maps. Extensive testing on a dataset of 65 EM maps with resolutions ranging from 3-6A demonstrated significant improvements in structure modeling using popular protein structure modeling tools.
Review
Biochemistry & Molecular Biology
Sushmita Basu, Daisuke Kihara, Lukasz Kurgan
Summary: One important characteristic of intrinsically disordered regions (IDRs) is their ability to interact with various molecules. In recent years, the prediction of binding IDRs in protein sequences has become more significant. These prediction tools utilize various predictive architectures, including scoring functions, regular expressions, traditional and deep machine learning, and meta-models. Efforts are currently focused on developing deep neural network-based architectures and expanding the coverage to include RNA, DNA, and lipid-binding IDRs.
COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL
(2023)
Article
Biochemical Research Methods
K. Ramki, G. Thiruppathi, Selva Kumar Ramasamy, P. Sundararaj, P. Sakthivel
Summary: A chromone-based ratiometric fluorescent probe L2 was developed for the selective detection of Hg(II) in a semiaqueous solution. The probe exhibited enhanced fluorescence in its aggregated state and even higher fluorescence when chelated with Hg(II). The probe demonstrated high sensitivity and specificity for Hg(II) detection and was successfully applied for imaging Hg(II) in a living model.
Article
Biochemical Research Methods
Qun Zhang, Rui Yang, Gang Liu, Shiyan Jiang, Jiarui Wang, Juqiang Lin, Tingyin Wang, Jing Wang, Zufang Huang
Summary: This research aims to develop a cost-effective and portable method for measuring creatinine levels using the enhanced Tyndall effect phenomenon. The method offers a promising solution for monitoring renal healthcare in resource-limited settings.