Article
Biochemistry & Molecular Biology
Manfred S. Weiss, Jan Wollenhaupt, Galen J. Correy, James S. Fraser, Andreas Heine, Gerhard Klebe, Tobias Krojer, Marjolein Thunnissen, Nicholas M. Pearce
Summary: Jaskolski et al. analyzed diffraction data sets from fragment-screening group depositions and claimed that these data are problematic. However, we demonstrate that none of the criticisms persist if the data are treated properly.
Article
Computer Science, Software Engineering
Qusay Sarhan, Bestoun S. Ahmed, Miroslav Bures, Kamal Z. Zamli
Summary: This study reviews 143 research papers on software module clustering to investigate various aspects of clustering methods, applications, processes, algorithms, and evaluation methods. Researchers discuss research gaps and challenges in this field, providing a useful reference for future studies.
IEEE TRANSACTIONS ON SOFTWARE ENGINEERING
(2022)
Article
Chemistry, Multidisciplinary
Felix Torres, Matthias Buetikofer, Gabriela R. R. Stadler, Alois Renn, Harindranath Kadavath, Raitis Bobrovs, Kristaps Jaudzems, Roland Riek
Summary: Although nuclear magnetic resonance (NMR) is commonly used in fragment-based drug design, its lack of sensitivity has limited its implementation in high-throughput screening. However, photochemically induced dynamic nuclear polarization (photo-CIDNP) is a promising method that can improve the sensitivity of NMR. This research demonstrates the detection of weak binders using low micromolar concentrations, exploiting the polarization enhancement provided by photo-CIDNP and achieving faster interaction detection compared to standard techniques. Furthermore, an automated flow-through platform and a photo-CIDNP fragment library are presented, providing a comprehensive approach for fragment-based screening.
JOURNAL OF THE AMERICAN CHEMICAL SOCIETY
(2023)
Article
Computer Science, Software Engineering
Navid Teymourian, Habib Izadkhah, Ayaz Isazadeh
Summary: This paper presents a new and fast clustering algorithm, FCA, that overcomes the time and space constraints of existing algorithms by performing operations on the dependency matrix and extracting other matrices. Experimental results show that the proposed algorithm achieves higher quality modularization compared to hierarchical algorithms and can compete with search-based algorithms and a clustering algorithm based on subsystem patterns. Additionally, the running time of the proposed algorithm is much shorter than that of other algorithms.
IEEE TRANSACTIONS ON SOFTWARE ENGINEERING
(2022)
Article
Computer Science, Information Systems
Yegor Bugayenko, Kirill Daniakin, Mirko Farina, Zamira Kholmatova, Artem Kruglov, Witold Pedrycz, Giancarlo Succi
Summary: Software repositories contain valuable information about software development, and many studies use data analytics and clustering methods to analyze them. This study applies consensus clustering and multiple cluster validity indices to overcome limitations seen in previous research. Experimental studies reveal seven clusters of software repositories and their relation to developers' activity.
Article
Engineering, Biomedical
Aidan Brougham-Cook, Ishita Jain, David A. Kukla, Faisal Masood, Hannah Kimmel, Hyeon Ryoo, Salman R. Khetani, Gregory H. Underhill
Summary: Liver fibrosis, a common feature of progressive liver disease, involves hepatic stellate cells (HSCs) as main drivers, affected by external bio-chemo-mechanical changes. The composition and stiffness of the extracellular matrix (ECM) regulate HSC fibrogenic phenotype and proliferation, leading to distinct phenotypic clusters based on microenvironment context. The study highlights the potential functional adaptations of HSCs to specific bio-chemo-mechanical changes and the importance of microenvironment in healthy, disease, and treatment settings.
ACTA BIOMATERIALIA
(2022)
Article
Biochemistry & Molecular Biology
Shamkhal Baybekov, Gilles Marcou, Pascal Ramos, Olivier Saurel, Jean-Luc Galzi, Alexandre Varnek
Summary: This paper reports comprehensive experimental and chemoinformatics analyses of the solubility of 939 fragments in dimethyl sulfoxide (DMSO), leading to the construction of a Support Vector Classification model with good performance in 5-fold cross-validation. Anomalous data points were identified and addressed, and both the datasets and the model are available for access.
Article
Computer Science, Artificial Intelligence
Bahman Arasteh, Mohammad Bagher Karimi, Razieh Sadegi
Summary: This research proposes a new method for improving software module clustering, which performs better in obtaining the best clustering quality and has higher data stability and faster execution time.
NEURAL COMPUTING & APPLICATIONS
(2023)
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
Computer Science, Information Systems
Babak Pourasghar, Habib Izadkhah, Ayaz Isazadeh, Shahriar Lotfi
Summary: By introducing a graph-based clustering algorithm named GMA, this paper presents a new modularization technique to better understand software system structures and software refactoring. Experimental results demonstrate that the algorithm produces a modularization closer to human expert's decomposition.
INFORMATION AND SOFTWARE TECHNOLOGY
(2021)
Article
Computer Science, Artificial Intelligence
Sukhkirandeep Kaur, Roohie Naaz Mir, Aditya Khamparia, Poonam Rani, Deepak Gupta, Ashish Khanna
Summary: Wireless Sensor Networks face the major challenge of energy conservation, and clustering is considered the most efficient technique to reduce energy consumption. A new clustering approach proposed in this study, along with the implementation of heterogeneity, shows improved stability and energy efficiency in random networks.
COGNITIVE SYSTEMS RESEARCH
(2021)
Article
Immunology
Sourya Shrestha, Kathryn Winglee, Andrew Hill, Tambi Shaw, Jonathan Smith, J. Steve Kammerer, Benjamin J. Silk, Suzanne Marks, David Dowdy
Summary: This study uses mechanistic transmission models to analyze the transmission of tuberculosis in the United States and finds significant heterogeneity at both the individual and state levels. Improving detection of transmission clusters and identifying the drivers of heterogeneity will be crucial for reducing TB transmission.
CLINICAL INFECTIOUS DISEASES
(2022)
Article
Chemistry, Medicinal
Hongyi Zhou, Hongnan Cao, Jeffrey Skolnick
Summary: In modern drug discovery, virtual ligand screening (VLS) is commonly used to reduce time and cost before experimental ligand screening. A new approach called FRAGSITE improves VLS precision and recall by integrating ligand fragment scores with global ligand similarity scores, outperforming state-of-the-art methods and showing better performance on challenging sets.
JOURNAL OF CHEMICAL INFORMATION AND MODELING
(2021)
Article
Biochemical Research Methods
Jakub W. Kaminski, Laura Vera, Dennis P. Stegmann, Jonatan Vering, Deniz Eris, Kate M. L. Smith, Chia Ying Huang, Nathalie Meier, Julia Steuber, Meitian Wang, Guenter Fritz, Justyna A. Wojdyla, May E. Sharpe
Summary: Fragment-based drug discovery has been proven to be an effective and efficient method for identifying new chemical scaffolds. X-ray crystallography can be used to validate and develop identified fragments, and recent technological advancements have enabled the development of dedicated platforms for FBDD using X-ray crystallography.
ACTA CRYSTALLOGRAPHICA SECTION D-STRUCTURAL BIOLOGY
(2022)
Article
Biochemistry & Molecular Biology
Laszlo Petri, Peter Aabranyi-Balogh, Noemi Csorba, Aaron Keeley, Jozsef Simon, Ivan Randelovic, Jozsef Tovari, Gitta Schlosser, Daniel Szabo, Laszlo Drahos, Gyoergy M. Keseru
Summary: SuFEx chemistry is based on the unique reactivity of the sulfonyl fluoride group with a range of nucleophiles. Sulfonyl fluorides can label multiple nucleophilic amino acid residues, making them popular in both chemical biology and medicinal chemistry applications. In this study, a small sulfonyl fluoride library was synthesized and characterized, resulting in the identification of a 3-carboxybenzenesulfonyl fluoride warhead for tagging nucleophilic residues. Coupling diverse fragments to this warhead could yield a library of sulfonyl fluoride bits (SuFBits) for screening against protein targets, facilitated by mass spectrometry identification of weak fragments.