Article
Chemistry, Multidisciplinary
Jiazhen He, Eva Nittinger, Christian Tyrchan, Werngard Czechtizky, Atanas Patronov, Esben Jannik Bjerrum, Ola Engkvist
Summary: Molecular optimization is a fundamental problem in drug discovery, and deep learning methods are proposed to surpass the limited capability of matched molecular pairs (MMPs) and achieve more general structural modifications for improving drug profiles.
JOURNAL OF CHEMINFORMATICS
(2022)
Article
Chemistry, Multidisciplinary
Vincent F. Scalfani, Vishank D. Patel, Avery M. Fernandez
Summary: This article demonstrates how to create Chemical Space Networks (CSNs) using a Python RDKit and NetworkX workflow, and introduces different CSN visualization features and network analysis calculations.
JOURNAL OF CHEMINFORMATICS
(2022)
Article
Engineering, Chemical
Gergo Ignacz, Cong Yang, Gyorgy Szekely
Summary: A medium-throughput system (MTS) for organic solvent nanofiltration (OSN) was developed in this study to generate a dataset containing 336 different molecules, revealing weak dependence of rejection values on functional groups and molecular weight within a certain range. The study also proposed a novel structural similarity-based indexing method for comparing solutes and established the first open access and searchable dataset for OSN rejection values.
JOURNAL OF MEMBRANE SCIENCE
(2022)
Article
Mathematics, Applied
A. A. El-Atik, Y. Tashkandy, S. Jafari, A. A. Nasef, W. Emam, M. Badr
Summary: This article focuses on studying DNA sequence mutations using multisets, relations, metric functions, topology, and association indices. Different methods of identifying mutations are utilized to aid biologists in decision-making.
Article
Chemistry, Applied
Jun Qiu, Jun Li, Jacob Albrecht, Jacob Janey
Summary: CHEM-SP is a simple method for predicting solubility in water and organic solvents using 2-D chemical structures and a reference solubility library, producing results that are equivalent or better than other prediction models.
ORGANIC PROCESS RESEARCH & DEVELOPMENT
(2021)
Article
Chemistry, Multidisciplinary
Chaofeng Lou, Hongbin Yang, Hua Deng, Mengting Huang, Weihua Li, Guixia Liu, Philip W. Lee, Yun Tang
Summary: Chemical mutagenicity is a significant concern in early drug discovery. We developed a well-trained consensus model to reverse mutagenicity using a large data set, which demonstrated the value of these transformation rules for optimizing compounds with mutagenic effects.
JOURNAL OF CHEMINFORMATICS
(2023)
Article
Biochemistry & Molecular Biology
Kenneth Lopez-Perez, Edgar Lopez-Lopez, Jose L. Medina-Franco, Ramon Alain Miranda-Quintana
Summary: Visualization of chemical space is crucial in various aspects of chemistry, such as compound library design and exploring structure-property relationships. ChemMaps is a visualization methodology that approximates compound distribution in large datasets based on satellite compounds with a similar mapping. Extended similarity indices are proposed to identify relevant regions and reduce high-dimensional data in describing a library's chemical space.
Article
Chemistry, Physical
Nirmala Parisutham, Nadarajan Rethnasamy
Summary: The physical and biological properties of a chemical molecule are related to its structure, with compounds sharing similar structure often having similar properties. Finding structural similarities between chemical structures helps identify common behaviors of molecules.
JOURNAL OF MOLECULAR STRUCTURE
(2021)
Article
Computer Science, Interdisciplinary Applications
Alexander D. Smith, Pawel Dlotko, Victor M. Zavala
Summary: A primary hypothesis in scientific and engineering studies is that data has structure, which is traditionally described using statistics and signal processing. Topological Data Analysis offers a new perspective by representing datasets as geometric objects and providing dimensionality reduction techniques. Topological features provide multiscale information and are stable under perturbations.
COMPUTERS & CHEMICAL ENGINEERING
(2021)
Article
Chemistry, Multidisciplinary
Pau Nadal Rodriguez, Ouldouz Ghashghaei, Anna M. M. Schoepf, Sam Benson, Marc Vendrell, Rodolfo Lavilla
Summary: Charting the chemical reaction space around the combination of carbonyls, amines, and isocyanoacetates allows the discovery of new multicomponent processes leading to a variety of unsaturated imidazolone scaffolds. The resulting compounds exhibit the chromophore of the green fluorescent protein and the core of the natural product coelenterazine. Despite the competitive nature of the pathways involved, general protocols provide selective access to desired chemotypes. Furthermore, unprecedented reactivity at the C-2 position of the imidazolone core is described, directly affording C, S, and N-derivatives featuring natural products (e.g. leucettamines), potent kinase inhibitors, and fluorescent probes with suitable optical and biological profiles.
ANGEWANDTE CHEMIE-INTERNATIONAL EDITION
(2023)
Article
Computer Science, Artificial Intelligence
Caleb Belth, Alican Buyukcakir, Danai Koutra
Summary: The traditional approach to link prediction in networks faces challenges due to the lack of a test set and the exponentially large search space of node pairs. In this study, we introduce LINKWALDO, a framework that effectively selects a concise set of candidate pairs from the search space using a combination of stochastic block models and node proximity models. Results on various networks show that LinkWaldo outperforms baseline methods in identifying missing and future links.
KNOWLEDGE AND INFORMATION SYSTEMS
(2022)
Article
Biochemistry & Molecular Biology
Muaaz Mutaz Alajlani
Summary: Bedaquiline, a novel adenosine triphosphate synthase inhibitor, is an antituberculosis drug belonging to the class of diarylquinolines. This study proposes a new approach using eight-score principal component analysis (PCA) provided by the ChemGPS-NP model to enhance discrimination in favor of bedaquiline and identify potentially similar compounds.
Article
Chemistry, Multidisciplinary
Alina F. Saifina, Sergey V. Kartashov, Adam I. Stash, Vladimir G. Tsirelson, Robert R. Fayzullin
Summary: This paper presents a binding approach based on the electrostatic and kinetic force density fields to explain interatomic interactions, structures, and chemical reactions. The study investigates various aspects including the arrangement of zero-flux surfaces, compression of force-field pseudoatoms, penetration of bonded atoms, distortion of force fields, and binding paths. The concept of force-induced push-pull assembling of interacting atoms is introduced, and the force-based binding structure is proposed. The crystal structures of chalcogen and tetrel bonding resemble the initial and transition states of nucleophilic substitution reactions.
CRYSTAL GROWTH & DESIGN
(2023)
Article
Biochemical Research Methods
Brett A. Vaughn, Angus J. Koller, Zhihengyu Chen, Shin Hye Ahn, C. Shaun Loveless, Shelbie J. Cingoranelli, Yi Yang, Anthony Cirri, Christopher J. Johnson, Suzanne E. Lapi, Karena W. Chapman, Eszter Boros
Summary: The close homology between scandium and lutetium allows for the development of coordination complexes suitable for biological applications, with similar structural features and biological properties observed when their trivalent ions are coordinated by large ligand architectures.
BIOCONJUGATE CHEMISTRY
(2021)
Article
Food Science & Technology
Gaurav Joshi, Jayant Sindhu, Shikha Thakur, Abhilash Rana, Geetika Sharma, Mayank, Ramarao Poduri
Summary: Nature is a valuable resource for drug discovery and natural products derived from plants have shown therapeutic potential during global health crisis such as Covid-19. This study aims to provide researchers with updated information on natural product-based drug discovery for Covid-19, exploring the concept of chemical space and molecular similarity parameters for lead molecule identification. The outcomes were validated through Molecular Dynamics studies and align with the chemical space ranking.
FOOD AND CHEMICAL TOXICOLOGY
(2021)
Correction
Biochemistry & Molecular Biology
Bijun Zhang, Martin Vogt, Gerald M. Maggiora, Juergen Bajorath
JOURNAL OF COMPUTER-AIDED MOLECULAR DESIGN
(2015)
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Biochemistry & Molecular Biology
Mengjun Wu, Martin Vogt, Gerald M. Maggiora, Juergen Bajorath
JOURNAL OF COMPUTER-AIDED MOLECULAR DESIGN
(2016)
Article
Biochemistry & Molecular Biology
Bijun Zhang, Martin Vogt, Gerald M. Maggiora, Juergen Bajorath
JOURNAL OF COMPUTER-AIDED MOLECULAR DESIGN
(2015)
Editorial Material
Chemistry, Medicinal
Gerald Maggiora
FUTURE MEDICINAL CHEMISTRY
(2016)
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Biochemistry & Molecular Biology
Martin Vogt, Dagmar Stumpfe, Gerald M. Maggiora, Juergen Bajorath
JOURNAL OF COMPUTER-AIDED MOLECULAR DESIGN
(2016)
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Cell Biology
Robert Kraft, Allon Kahn, Jose L. Medina-Franco, Mikayla L. Orlowski, Cayla Baynes, Fabian Lopez-Vallejo, Kobus Barnard, Gerald M. Maggiora, Linda L. Restifo
DISEASE MODELS & MECHANISMS
(2013)
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Chemistry, Medicinal
Martin Vogt, Preeti Iyer, Gerald M. Maggiora, Juergen Bajorath
JOURNAL OF CHEMICAL INFORMATION AND MODELING
(2013)
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Biochemistry & Molecular Biology
Ye Hu, Gerald M. Maggiora, Juergen Bajorath
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(2013)
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Biochemistry & Molecular Biology
Magdalena Zwierzyna, Martin Vogt, Gerald M. Maggiora, Juergen Bajorath
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(2015)
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Biochemistry & Molecular Biology
Gerald M. Maggiora, Jurgen Bajorath
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(2014)
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Chemistry, Medicinal
Gerald Maggiora, Martin Vogt, Dagmar Stumpfe, Juergen Bajorath
JOURNAL OF MEDICINAL CHEMISTRY
(2014)
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Chemistry, Medicinal
Preeti Iyer, Dagmar Stumpfe, Martin Vogt, J. Bajorath, G. M. Maggiora
MOLECULAR INFORMATICS
(2013)
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Chemistry, Medicinal
Julien Burton, Joachim Petit, Emeric Danloy, Gerald M. Maggiora, Daniel P. Vercauteren
MOLECULAR INFORMATICS
(2013)
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Oncology
Sara A. Byron, Nhan L. Tran, Rebecca F. Halperin, Joanna J. Phillips, John G. Kuhn, John F. de Groot, Howard Colman, Keith L. Ligon, Patrick Y. Wen, Timothy F. Cloughesy, Ingo K. Mellinghoff, Nicholas A. Butowski, JennieW. Taylor, Jennifer L. Clarke, Susan M. Chang, Mitchel S. Berger, Annette M. Molinaro, Gerald M. Maggiora, Sen Peng, Sara Nasser, Winnie S. Liang, Jeffrey M. Trent, Michael E. Berens, John D. Carpten, David W. Craig, Michael D. Prados
CLINICAL CANCER RESEARCH
(2018)