2,693 Hits in 6.7 sec

Designing Focused Chemical Libraries Enriched in Protein-Protein Interaction Inhibitors using Machine-Learning Methods

Christelle Reynès, Hélène Host, Anne-Claude Camproux, Guillaume Laconde, Florence Leroux, Anne Mazars, Benoit Deprez, Robin Fahraeus, Bruno O. Villoutreix, Olivier Sperandio, Philip E. Bourne
2010 PLoS Computational Biology  
Here, we train machine-learning-based models, mainly decision trees, using a dataset of known PPI inhibitors and of regular drugs in order to determine a global physico-chemical profile for putative PPI  ...  The best model has been transposed into a computer program, PPI-HitProfiler, that can output from any drug-like compound collection a focused chemical library enriched in putative PPI inhibitors.  ...  Therefore, one possible avenue to circumvent this conundrum is to design focused libraries enriched in putative PPI inhibitors.  ... 
doi:10.1371/journal.pcbi.1000695 pmid:20221258 pmcid:PMC2832677 fatcat:dwi7e2ndmfcublzqxiyfeogq6e

Focused chemical libraries – design and enrichment: an example of protein–protein interaction chemical space

Xu Zhang, Stéphane Betzi, Xavier Morelli, Philippe Roche
2014 Future Medicinal Chemistry  
No writing assistance was utilized in the production of this manuscript.  ...  or financial conflict with the subject matter or materials discussed in the manuscript.  ...  machine-learning methods using the general profile of PPI inhibitors as a guide.  ... 
doi:10.4155/fmc.14.57 pmid:24773599 fatcat:hsve5myffze7bc6yptukjzewga

Targeting Plague Virulence Factors: A Combined Machine Learning Method and Multiple Conformational Virtual Screening for the Discovery ofYersiniaProtein Kinase A Inhibitors

Xin Hu, Gerd Prehna, C. Erec Stebbins
2007 Journal of Medicinal Chemistry  
Here, we present an approach integrating a machine learning method, homology modeling, and multiple conformational high-throughput docking for the discovery of YpkA inhibitors.  ...  (A) Sequence alignment of YpkA (115-431) with protein kinases P38 and ERK. Strict sequence conservation is shown in red, and strong sequence conservation is shown in yellow.  ...  Supporting Information Available: The 3D structural models of YpkA, detailed methods on homology modeling, SVM clustering, MD simulations, virtual screening, and YpkA purification, inhibitor data, and  ... 
doi:10.1021/jm070645a pmid:17676727 pmcid:PMC2538798 fatcat:3cia7r5ikbanzc3am3mmw3e45i

2P2IHUNTER: a tool for filtering orthosteric protein-protein interaction modulators via a dedicated support vector machine

V. Hamon, R. Bourgeas, P. Ducrot, I. Theret, L. Xuereb, M. J. Basse, J. M. Brunel, S. Combes, X. Morelli, P. Roche
2013 Journal of the Royal Society Interface  
Research Cite this article: Hamon V et al. 2014 2P2I HUNTER : a tool for filtering orthosteric protein-protein interaction modulators via a dedicated support vector machine.  ...  protocol to filter general screening libraries using a support vector machine (SVM) with 11 standard DRAGON molecular descriptors.  ...  Therefore, the 'Ro4' constitutes a simple and fast method of designing chemical libraries enriched in PPI inhibitors.  ... 
doi:10.1098/rsif.2013.0860 pmid:24196694 pmcid:PMC3836326 fatcat:khg2dkw7sjhine5c5iiyjwn47q

Commercial SARS-CoV-2 Targeted, Protease Inhibitor Focused and Protein–Protein Interaction Inhibitor Focused Molecular Libraries for Virtual Screening and Drug Design

Sebastjan Kralj, Marko Jukič, Urban Bren
2021 International Journal of Molecular Sciences  
We evaluated the SARS-CoV-2-targeted, protease-inhibitor-focused and proteinprotein-interaction-inhibitor-focused libraries to gain a better understanding of how these libraries were designed.  ...  These facts do not bode well for the use of the reviewed libraries in drug design and lend themselves to commercial drug companies to focus on and improve.  ...  Acknowledgments: We gratefully acknowledge the support of NVIDIA Corporation with the donation of GPU hardware that was used in this research. We especially thank OpenEye for their support.  ... 
doi:10.3390/ijms23010393 pmid:35008818 pmcid:PMC8745317 fatcat:3pnm3ezq55ddxnk22w34qwrhga

From Laptop to Benchtop to Bedside: Structure-based Drug Design on Protein Targets

Lu Chen, John K. Morrow, Hoang T. Tran, Sharangdhar S. Phatak, Lei Du-Cuny, Shuxing Zhang
2012 Current drug metabolism  
Keywords Structure-based drug design; protein modeling; focused library design; pharmacophore; flexible docking; high-throughput virtual screening; de novo design; protein-protein interaction; polypharmacology  ...  Structure-based drug design has resulted in fruitful successes drug discovery targeting protein-ligand and protein-protein interactions.  ...  Acknowledgments This work was supported in part by the US Department of Defense Concept Awards (BC085871), US National Institute of Health P41 grant (5P41GM079588-03), Grant # IRG-08-061-01 from the American  ... 
doi:10.2174/138920012799362837 fatcat:arxeeeslsvbdvgkjmzenhxp7pe

From Laptop to Benchtop to Bedside: Structure-based Drug Design on Protein Targets

Lu Chen, John K. Morrow, Hoang T. Tran, Sharangdhar S. Phatak, Lei Du-Cuny, Shuxing Zhang
2012 Current pharmaceutical design  
Structure-based drug design has resulted in fruitful successes drug discovery targeting proteinligand and protein-protein interactions.  ...  In this review, state-of-the-art techniques for protein modeling (e.g. structure prediction, modeling protein flexibility, etc.), hit identification/ optimization (e.g. molecular docking, focused library  ...  Acknowledgments This work was supported in part by the US Department of Defense Concept Awards (BC085871), US National Institute of Health P41 grant (5P41GM079588-03), Grant # IRG-08-061-01 from the American  ... 
doi:10.2174/138161212799436386 pmid:22316152 pmcid:PMC3820560 fatcat:rs7ddwb5ozbgrfrjqgnzn7ixzq

Structure-Based Virtual Screening for Drug Discovery: a Problem-Centric Review

Tiejun Cheng, Qingliang Li, Zhigang Zhou, Yanli Wang, Stephen H. Bryant
2012 AAPS Journal  
by means of machine learning techniques.  ...  We emphasized the researchers' practical efforts in real projects by understanding the ligand-target binding interactions as a premise.  ...  ACKNOWLEDGMENTS We thank the Intramural Research Program of the National Institutes of Health (NIH), National Library of Medicine (NLM) for funding support.  ... 
doi:10.1208/s12248-012-9322-0 pmid:22281989 pmcid:PMC3282008 fatcat:zc5f4ey6kzdulbwfyloavroaeq

Virtual screening web servers: designing chemical probes and drug candidates in the cyberspace

2020 Briefings in Bioinformatics  
Virtual screening methods are among the most popular computational approaches in pharmaceutical research.  ...  In parallel, many different types of algorithms are being developed to manipulate these chemical objects and associated bioactivity data.  ...  Statistical machine learning methods can be used for classification purpose.  ... 
doi:10.1093/bib/bbaa034 pmid:32187356 pmcid:PMC7986591 fatcat:mq3csvzjkfekhpjfti2wmyipxi

Key Topics in Molecular Docking for Drug Design

Pedro H. M. Torres, Ana C. R. Sodero, Paula Jofily, Floriano P. Silva-Jr
2019 International Journal of Molecular Sciences  
their advantages and caveats, (ii) the advances in consensus methods, (iii) recent algorithms and applications using fragment-based approaches, and (iv) the use of machine learning algorithms in molecular  ...  In this review, we present an overview of the method and attempt to summarise recent developments regarding four main aspects of molecular docking approaches: (i) the available benchmarking sets, highlighting  ...  Thus, effectively, this strategy is largely used to create more focused libraries.  ... 
doi:10.3390/ijms20184574 pmid:31540192 pmcid:PMC6769580 fatcat:ye5rdnonofc3jjaizbncrdx2yu

Design and Construction of a Focused DNA-Encoded Library for Multivalent Chromatin Reader Proteins

Justin M. Rectenwald, Shiva Krishna Reddy Guduru, Zhao Dang, Leonard B. Collins, Yi-En Liao, Jacqueline L. Norris-Drouin, Stephanie H. Cholensky, Kyle W. Kaufmann, Scott M. Hammond, Dmitri B. Kireev, Stephen V. Frye, Kenneth H. Pearce
2020 Molecules  
Using computational methods, along with structure-based knowledge, we have designed and constructed a focused DNA-Encoded Library (DEL) containing approximately 60,000 compounds targeting bi-valent methyl-lysine  ...  We anticipate that this target-class focused approach will serve as a new method for rapid discovery of inhibitors for multivalent chromatin reader domains.  ...  Acknowledgments: We thank Caroline Foley and Jacob Larson for internal review of the manuscript and many others in the UNC CICBDD for suggestions and helpful discussions.  ... 
doi:10.3390/molecules25040979 pmid:32098353 pmcid:PMC7070942 fatcat:knrq7anxtvcgvknvw4yrewywvy

TeachOpenCADD: a teaching platform for computer-aided drug design using open source packages and data

Dominique Sydow, Andrea Morger, Maximilian Driller, Andrea Volkamer
2019 Journal of Cheminformatics  
Here, we present TeachOpenCADD, a teaching platform developed by students for students, using open source compound and protein data as well as basic and CADD-related Python packages.  ...  Owing to the increase in freely available software and data for cheminformatics and structural bioinformatics, research for computer-aided drug design (CADD) is more and more built on modular, reproducible  ...  structures using PyMOL, including either the whole proteins or focusing on their binding sites.  ... 
doi:10.1186/s13321-019-0351-x pmid:30963287 pmcid:PMC6454689 fatcat:4bgex5cfovezlajlr46uedsytq

A Comprehensive Review on Current Advances in Peptide Drug Development and Design

Andy Chi-Lung Lee, Janelle Louise Harris, Kum Kum Khanna, Ji-Hong Hong
2019 International Journal of Molecular Sciences  
of peptide–protein interactions (PepPIs) with an aim to assist experimental biologists exploit suitable docking methods to advance peptide interfering strategies against PPIs.  ...  Importantly, a variety of computation-aided rational designs for peptide therapeutics have been developed, which aim to deliver comprehensive docking for peptide–protein interaction interfaces.  ...  CPPpred web servers such CPPpred-RF or KELM-CPPpred allow the prediction and design of CPPs from a query input protein sequence using machine learning-based models [46] [47] [48] .  ... 
doi:10.3390/ijms20102383 fatcat:wjv3k734yrbsrncqok2i5lj7ym

Prioritisation of Compounds for 3CLpro Inhibitor Development on SARS-CoV-2 Variants

Marko Jukič, Blaž Škrlj, Gašper Tomšič, Sebastian Pleško, Črtomir Podlipnik, Urban Bren
2021 Molecules  
We coupled the virtual screening experiment to a machine learning-supported classification and activity regression study to bring maximal enrichment and available structural data on known 3CLpro inhibitors  ...  With this in mind, we performed a high throughput virtual screening experiment using CmDock and the "In-Stock" chemical library to prepare prioritisation lists of compounds for further studies.  ...  Acknowledgments: We gratefully acknowledge NVIDIA Corporation's support with the donation of GPU hardware used in this research.  ... 
doi:10.3390/molecules26103003 pmid:34070140 pmcid:PMC8158358 fatcat:3ckggktnora6zamcurakuq2bla

Overcoming Chemical, Biological, and Computational Challenges in the Development of Inhibitors Targeting Protein-Protein Interactions

Luca Laraia, Grahame McKenzie, David R. Spring, Ashok R. Venkitaraman, David J. Huggins
2015 Chemistry and Biology  
Protein-protein interactions (PPIs) underlie the majority of biological processes, signaling, and disease.  ...  However, there are a number of challenges inherent in developing small-molecule PPI inhibitors that have prevented these approaches from reaching their full potential.  ...  ChemDiv, Asinex, Comminex, Life Chemicals, Otava Chemicals, and NQuix all have libraries targeted at PPIs, which use both the RO4, decision trees, and machine-learning methods (Neugebauer et al., 2007  ... 
doi:10.1016/j.chembiol.2015.04.019 pmid:26091166 pmcid:PMC4518475 fatcat:5jqgp7z36fdn7ant6p5wmplewe
« Previous Showing results 1 — 15 out of 2,693 results