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
Multidisciplinary Sciences
Xiaoxi Xu, Rajendra Kumari, Jun Zhou, Jing Chen, Binchen Mao, Jingjing Wang, Meiling Zheng, Xiaolong Tu, Xiaoyu An, Xiaobo Chen, Likun Zhang, Xiaoli Tian, Haojie Wang, Xin Dong, Zhengzheng Bao, Sheng Guo, Xuesong Ouyang, Limei Shang, Fei Wang, Xuefei Yan, Rui Zhang, Robert G. J. Vries, Hans Clevers, Qi-Xiang Li
Summary: Patient-derived tumor xenograft (PDX)/organoid (PDO) models, driven by cancer stem cells (CSC), are considered the most predictive models for translational oncology and have been extensively used for testing investigational therapies. We have created a biobank of carcinoma PDX-derived organoids (PDXOs) and confirmed their similarity to parental PDXs in genomics, histopathology, and pharmacology. We demonstrate the applications of this PDXO biobank in high-throughput screening, immune therapies, and in vitro/in vivo imaging.
Article
Statistics & Probability
Yuehao Bai, Joseph P. Romano, Azeem M. Shaikh
Summary: This study focuses on inference for the average treatment effect in randomized controlled trials with a matched pairs design. It demonstrates that commonly used tests for comparing treatment effects are conservative and proposes adjustments to improve accuracy in hypothesis testing. Moreover, the study explores randomization tests and shows that appropriate implementation can lead to exact results in certain distributions.
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
(2022)
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
Chemistry, Medicinal
Hyeongwoo Kim, Kyunghoon Lee, Chansu Kim, Jaechang Lim, Woo Youn Kim
Summary: Recently, generative AI models have been used to generate a large number of compounds for potential applications. However, the synthetic feasibility of these compounds is often in question. To address this, researchers have used deep learning models to estimate the synthetic accessibility of molecules. In this study, the DFRscore model is introduced, which is trained exclusively on drug-focused reactions to provide a practical assessment of synthetic accessibility in drug discovery.
JOURNAL OF CHEMICAL INFORMATION AND MODELING
(2023)
Article
Multidisciplinary Sciences
Xiaoxi Xu, Limei Shang, Philip Wang, Jun Zhou, Xuesong Ouyang, Meiling Zheng, Binchen Mao, Likun Zhang, Bonnie Chen, Jingjing Wang, Jing Chen, Wubin Qian, Sheng Guo, Yujun Huang, Qi-Xiang Li
Summary: PDXs are considered predictive preclinical models driven by CSC, but have practical limitations. Tumor organoids can serve as in vitro equivalents of PDX, overcoming certain limitations and providing more comprehensive research models. Hence, PDX-derived organoids offer a complete model for pharmacology research in vitro and in vivo.
JOVE-JOURNAL OF VISUALIZED EXPERIMENTS
(2021)
Article
Physics, Multidisciplinary
S. J. Paul, S. Moran, M. Arratia, A. El Alaoui, H. Hakobyan, W. Brooks, M. J. Amaryan, W. R. Armstrong, H. Atac, L. Baashen, N. A. Baltzell, L. Barion, M. Bashkanov, M. Battaglieri, I Bedlinskiy, B. Benkel, F. Benmokhtar, A. Bianconi, L. Biondo, A. S. Biselli, M. Bondi, F. Bossu, S. Boiarinov, K-Th Brinkmann, W. J. Briscoe, D. Bulumulla, V. D. Burkert, R. Capobianco, D. S. Carman, A. Celentano, V Chesnokov, T. Chetry, G. Ciullo, P. L. Cole, M. Contalbrigo, G. Costantini, A. D'Angelo, N. Dashyan, R. De Vita, M. Defurne, A. Deur, S. Diehl, C. Dilks, C. Djalali, R. Dupre, H. Egiyan, L. El Fassi, P. Eugenio, S. Fegan, A. Filippi, G. Gavalian, Y. Ghandilyan, G. P. Gilfoyle, A. A. Golubenko, G. Gosta, R. W. Gothe, K. A. Griffioen, M. Guidal, M. Hattawy, T. B. Hayward, D. Heddle, A. Hobart, M. Holtrop, Y. Ilieva, D. G. Ireland, E. L. Isupov, H. S. Jo, R. Johnston, K. Joo, S. Joosten, D. Keller, A. Khanal, M. Khandaker, W. Kim, A. Kripko, V Kubarovsky, V Lagerquist, L. Lanza, M. Leali, S. Lee, P. Lenisa, X. Li, K. Livingston, I. J. D. MacGregor, D. Marchand, V Mascagna, B. McKinnon, Z. E. Meziani, S. Migliorati, R. G. Milner, T. Mineeva, M. Mirazita, V. Mokeev, P. Moran, C. Munoz Camacho, K. Neupane, D. Nguyen, S. Niccolai, G. Niculescu, M. Osipenko, A. Ostrovidov, P. Pandey, M. Paolone, L. L. Pappalardo, R. Paremuzyan, E. Pasyuk, W. Phelps, N. Pilleux, D. Pocanic, O. Pogorelko, M. Pokhrel, J. Poudel, J. W. Price, Y. Prok, B. A. Raue, T. Reed, M. Ripani, G. Rosner, F. Sabatie, C. Salgado, A. Schmidt, R. A. Schumacher, Y. G. Sharabian, E. Shirokov, U. Shrestha, P. Simmerling, D. Sokhan, N. Sparveris, S. Stepanyan, I. I. Strakovsky, S. Strauch, J. A. Tan, R. Tyson, M. Ungaro, S. Vallarino, L. Venturelli, H. Voskanyan, E. Voutier, X. Wei, R. Wishart, M. H. Wood, N. Zachariou, Z. W. Zhao, V Ziegler, M. Zurek
Summary: We present the first measurement of dihadron angular correlations in electron-nucleus scattering. The results show a strong suppression effect for azimuthally opposite pairs, no suppression effect for nearby pairs, and an enhancement effect for pairs with large invariant mass. These findings indicate that angular correlation studies are important for understanding the formation and interaction of hadrons inside nuclei.
PHYSICAL REVIEW LETTERS
(2022)
Article
Chemistry, Medicinal
Junhui Park, Gaeun Sung, SeungHyun Lee, SeungHo Kang, ChunKyun Park
Summary: The paper explores the activity cliff phenomenon in drug-target interactions and introduces a graph convolutional network model for predicting activity cliffs, showing superiority in comparison to other methods for popular target datasets. Additionally, the use of gradient-weighted class activation mapping is demonstrated to visualize activation weights at nodes in molecular graphs, potentially aiding in the identification of important substructures for molecular docking.
JOURNAL OF CHEMICAL INFORMATION AND MODELING
(2022)
Article
Chemistry, Multidisciplinary
Youness Moukhliss, Yassine Koubi, Marwa Alaqarbeh, Hafiz Muzzammel Rehman, Hamid Maghat, Abdelouahid Sbai, Mohammed Bouachrine, Tahar Lakhlifi
Summary: This study applied the 3D-QSAR method to analyze a set of isoxazole-based compounds and proposed five new drug candidates (Pr1-Pr5). The interactions between the drug candidates and the antioxidant receptor 1HD2 were studied using molecular docking. ADME analysis showed that these drug candidates are orally bioavailable with high gastrointestinal absorption and good permeability. Molecular dynamics simulation confirmed the stability of the complexes formed between the drug candidates and 1HD2. A synthesis pathway for the drug candidates was proposed using the retrosynthesis approach. This study provides valuable information on the antioxidant activity of isoxazole-based compounds.
Article
Biology
Bo Zhang
Summary: Many recent efforts have focused on evaluating the ability of real-world evidence (RWE) generated from non-randomized, observational data to produce results similar to those from randomized controlled trials (RCTs). One notable initiative is the RCT DUPLICATE, which aims to reconcile findings from observational studies and RCTs. A network-flow-based statistical matching algorithm is proposed to create well-matched pairs from observational data, eliminating differences between study populations.
Article
Chemistry, Physical
Kunyu Wang, Bertrand Siboulet, Jean-Francois Dufreche
Summary: Simulating the molecular-level structures of electrical double layers is crucial for understanding the mechanism of ion adsorption on solid surfaces. Recent molecular dynamics studies reveal that the interaction between ion sites is similar to cation-anion pairs in the solvent. The present study demonstrates the collective effects in the adsorption of alkaline-earth chloride solution on an amorphous silica surface and provides insights into the ion-ion and ion-site specificities.
JOURNAL OF PHYSICAL CHEMISTRY C
(2023)
Article
Medicine, General & Internal
Katie Ferguson, Matthew Neilson, Rachel Mercer, Jenny King, Kelly Marshall, Hugh Welch, Selina Tsim, Nick A. Maskell, Najib M. Rahman, Matthew Evison, Kevin G. Blyth
Summary: Meso-ORIGINS is an ambitious study that aims to collect 63 matched benign-mesothelioma tissue pairs through longitudinal surveillance and repeat biopsy. It consists of a prospective study and a retrospective cohort study to evaluate recruitment feasibility and technical feasibility, as well as to determine the sample size. Rating: 8 out of 10.
Article
Chemistry, Physical
Enliang Wang, Nora G. Kling, Aaron C. LaForge, Razib Obaid, Shashank Pathak, Surjendu Bhattacharyya, Severin Meister, Florian Trost, Hannes Lindenblatt, Patrizia Schoch, Matthias Kubel, Thomas Pfeifer, Artem Rudenko, Sergio Diaz-Tendero, Fernando Martin, Robert Moshammer, Daniel Rolles, Nora Berrah
Summary: Pump-probe spectroscopy with an extreme ultraviolet (XUV) free-electron laser is used to study ultrafast H2+ and H3+ formation from ethanol. The formation of H2+ and H3+ is triggered by the creation of a dication from the first pulse and disruptively probed by a second pulse. The ratio of H2+ to H3+ increases with time delay at lower photon energies but remains constant at higher photon energy, indicating a competition between electron and proton transfer.
JOURNAL OF PHYSICAL CHEMISTRY LETTERS
(2023)
Article
Chemistry, Physical
Pierre Desesquelles, Dominik Domin, Lejin Xu, Nguyen-Thi Van-Oanh
Summary: This paper analyzes the fragmentation and hydrogen losses from the fluorene cation using the SMF model, and determines the contributions of different types of hydrogen atom pairings to the production of hydrogen molecules. The results show a good agreement with experimental data when considering same ring pairing.
Article
Biochemistry & Molecular Biology
Maksim Sorokin, Anton A. Buzdin, Anastasia Guryanova, Victor Efimov, Maria V. Suntsova, Marianna A. Zolotovskaia, Elena V. Koroleva, Marina I. Sekacheva, Victor S. Tkachev, Andrew Garazha, Kristina Kremenchutckaya, Aleksey Drobyshev, Aleksander Seryakov, Alexander Gudkov, Irina V. Alekseenko, Olga Rakitina, Maria B. Kostina, Uliana Vladimirova, Aleksey Moisseev, Dmitry Bulgin, Elena Radomskaya, Viktor Shestakov, Vladimir P. Baklaushev, Vladimir Prassolov, Petr V. Shegay, Xinmin Li, Elena V. Poddubskaya, Nurshat Gaifullin
Summary: We compared the molecular profiles of tumor-adjacent and autopsy-derived healthy normal tissues and found systemic molecular differences in immune cell activation, cellular respiration, telomerase activation, cellular apoptosis, and chemical perception. Furthermore, we observed differences in the expression of cancer drug targets between tumor-adjacent and normal tissues. However, caution should be taken when using postmortal tissues as RNA degradation may lead to artifact differential expression profiles.
COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL
(2023)
Article
Biochemistry & Molecular Biology
Abdul Hameed, Khalid Mohammed Khan, Syeda Tazeen Zehra, Ramasa Ahmed, Zahid Shafiq, Syeda Mahwish Bakht, Muhammad Yaqub, Mazhar Hussain, Antonio de la Vega de Len, Norbert Furtmann, Juergen Bajorath, Hazoor Ahmad Shad, Muhammad Nawaz Tahir, Jamshed Iqbal
BIOORGANIC CHEMISTRY
(2015)
Article
Biochemistry & Molecular Biology
Antonio de la Vega de Leon, Shilva Kayastha, Dilyana Dimova, Thomas Schultz, Juergen Bajorath
JOURNAL OF COMPUTER-AIDED MOLECULAR DESIGN
(2015)
Article
Chemistry, Medicinal
Veerabahu Shanmugasundaram, Liying Zhang, Shilva Kayastha, Antonio de la Vega de Leon, Dilyana Dimova, Juergen Bajorath
JOURNAL OF MEDICINAL CHEMISTRY
(2016)
Article
Chemistry, Medicinal
Antonio de la Vega de Leon, Juergen Bajorath
FUTURE MEDICINAL CHEMISTRY
(2016)
Article
Chemistry, Medicinal
Dragos Horvath, Gilles Marcou, Alexandre Varnek, Shilva Kayastha, Antonio de la Vega de Leon, Juergen Bajorath
JOURNAL OF CHEMICAL INFORMATION AND MODELING
(2016)
Article
Biochemistry & Molecular Biology
Andrew Anighoro, Antonio de la Vega de Leon, Jurgen Bajorath
JOURNAL OF COMPUTER-AIDED MOLECULAR DESIGN
(2016)
Article
Chemistry, Multidisciplinary
Antonio de la Vega de Leon, Beining Chen, Valerie J. Gillet
JOURNAL OF CHEMINFORMATICS
(2018)
Article
Biology
Elvira Diamantopoulou, Sarah Baxendale, Antonio de la Vega de Leon, Anzar Asad, Celia J. Holdsworth, Leila Abbas, Valerie J. Gillet, Giselle R. Wiggin, Tanya T. Whitfield
Article
Medicine, Research & Experimental
Emma J. Kenyon, Nerissa K. Kirkwood, Sian R. Kitcher, Richard J. Goodyear, Marco Derudas, Daire M. Cantillon, Sarah Baxendale, Antonio de la Vega de Leon, Virginia N. Mahieu, Richard T. Osgood, Charlotte Donald Wilson, James C. Bull, Simon J. Waddell, Tanya T. Whitfield, Simon E. Ward, Corne J. Kros, Guy P. Richardson
Summary: By screening compounds, a series of compounds that protect mammalian hair cells from the ototoxic effects of aminoglycoside antibiotics were identified. These compounds block the MET channel of hair cells, with one compound, UoS-7692, being effective against gentamicin, kanamycin, and tobramycin.
Article
Pharmacology & Pharmacy
Anzar Asad, Nahal O. O. Shahidan, Antonio de la Vega de Leon, Giselle R. R. Wiggin, Tanya T. T. Whitfield, Sarah Baxendale
Summary: Researchers identified 17 compounds that can treat both muscular and myelination defects, of which 3 are new hits. These findings provide important starting material for the development of new drugs for Adgrg6 receptor.
BASIC & CLINICAL PHARMACOLOGY & TOXICOLOGY
(2023)
Article
Chemistry, Multidisciplinary
James D. Grayson, Matthew P. Baumgartner, Cleide Dos Santos Souza, Samuel J. Dawes, Imane Ghafir El Idrissi, Jennifer C. Louth, Sasha Stimpson, Emma Mead, Charlotte Dunbar, Joanna Wolak, Gary Sharman, David Evans, Anastasia Zhuravleva, Margarita Segovia Roldan, Nicola Antonio Colabufo, Ke Ning, Claire Garwood, James A. Thomas, Benjamin M. Partridge, Antonio de la Vega de Leon, Valerie J. Gillet, Amelia P. Rauter, Beining Chen
Summary: This study presents a new approach for identifying functional Aβo binding compounds to treat Alzheimer's disease. Two compounds were found to disrupt the toxic effects of Aβo in HEK293 cells and neural cells derived from hiPSC.
Proceedings Paper
Computer Science, Artificial Intelligence
Jo Bates, David Cameron, Alessandro Checco, Paul Clough, Frank Hopfgartner, Suvodeep Mazumdar, Laura Sbaffi, Peter Stordy, Antonio de la Vega de Leon
FAT* '20: PROCEEDINGS OF THE 2020 CONFERENCE ON FAIRNESS, ACCOUNTABILITY, AND TRANSPARENCY
(2020)
Meeting Abstract
Chemistry, Multidisciplinary
Antonio de la Vega de Leon, Val Gillet
ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY
(2018)
Meeting Abstract
Chemistry, Multidisciplinary
Antonio de la Vega de Leon, Val Gillet
ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY
(2017)
Meeting Abstract
Chemistry, Multidisciplinary
Jorg Benningshof, Pauline van Meurs, Sander van Assema, Gerhard Mueller, Dagmar Stumpfe, Antonio de la Vega de Leon, Norbert Furtmann, Dilyana Dimova, Jurgen Bajorath
ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY
(2016)