P
Pavel V. Pogodin
Researcher at Institute of Business & Medical Careers
Publications - 30
Citations - 1203
Pavel V. Pogodin is an academic researcher from Institute of Business & Medical Careers. The author has contributed to research in topics: chEMBL & Virtual screening. The author has an hindex of 11, co-authored 27 publications receiving 714 citations. Previous affiliations of Pavel V. Pogodin include Russian National Research Medical University & Russian Academy.
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Journal ArticleDOI
Prediction of the Biological Activity Spectra of Organic Compounds Using the Pass Online Web Resource
Dmitry Filimonov,Alexey Lagunin,Tatyana A. Gloriozova,A. V. Rudik,D. S. Druzhilovskii,Pavel V. Pogodin,Pavel V. Pogodin,Vladimir Poroikov,Vladimir Poroikov +8 more
TL;DR: In this paper, the authors present a web resource for the prediction of the biological activity spectra of organic compounds based on their structural formulas for more than 4000 types of biological activity with average accuracy above 95% (http://www.way2drug.com/passonline ).
Journal ArticleDOI
CoMPARA: Collaborative Modeling Project for Androgen Receptor Activity.
Kamel Mansouri,Nicole Kleinstreuer,Ahmed Abdelaziz,Domenico Alberga,Vinicius M. Alves,Vinicius M. Alves,Patrik L. Andersson,Carolina Horta Andrade,Fang Bai,Ilya A. Balabin,Davide Ballabio,Emilio Benfenati,Barun Bhhatarai,Scott Boyer,Jingwen Chen,Viviana Consonni,Sherif Farag,Denis Fourches,Alfonso T. García-Sosa,Paola Gramatica,Francesca Grisoni,Christopher M. Grulke,Huixiao Hong,Dragos Horvath,Xin Hu,Ruili Huang,Nina Jeliazkova,Jiazhong Li,Xuehua Li,Huanxiang Liu,Serena Manganelli,Giuseppe Felice Mangiatordi,Uko Maran,Gilles Marcou,Todd M. Martin,Eugene N. Muratov,Dac-Trung Nguyen,Orazio Nicolotti,Nikolai Georgiev Nikolov,Ulf Norinder,Ester Papa,Michel Petitjean,Geven Piir,Pavel V. Pogodin,Vladimir Poroikov,Xianliang Qiao,Ann M. Richard,Alessandra Roncaglioni,Patricia Ruiz,Chetan Rupakheti,Chetan Rupakheti,Sugunadevi Sakkiah,Alessandro Sangion,Karl-Werner Schramm,Chandrabose Selvaraj,Imran Shah,Sulev Sild,Lixia Sun,Olivier Taboureau,Yun Tang,Igor V. Tetko,Roberto Todeschini,Weida Tong,Daniela Trisciuzzi,Alexander Tropsha,George Van Den Driessche,Alexandre Varnek,Zhongyu Wang,Eva Bay Wedebye,Antony J. Williams,Hongbin Xie,Alexey V. Zakharov,Ziye Zheng,Richard S. Judson +73 more
TL;DR: The Collaborative Modeling Project for Androgen Receptor Activity (CoMPARA) efforts are described, which follows the steps of the Collaborative Estrogen Recept Activity Prediction Project (CERAPP).
Journal ArticleDOI
CLC-Pred: A freely available web-service for in silico prediction of human cell line cytotoxicity for drug-like compounds.
Alexey Lagunin,Varvara Dubovskaja,Anastasia V. Rudik,Pavel V. Pogodin,Dmitry S. Druzhilovskiy,Tatyana A. Gloriozova,Dmitry Filimonov,Narahari G. Sastry,Vladimir Poroikov +8 more
TL;DR: The previously developed PASS (Prediction of Activity Spectra for Substances) algorithm was used to create and validate the classification SAR models for predicting the cytotoxicity of chemicals against different types of human cell lines using ChEMBL experimental data.
Journal ArticleDOI
Chemo- and bioinformatics resources for in silico drug discovery from medicinal plants beyond their traditional use: a critical review
Alexey Lagunin,Rajesh Kumar Goel,Dinesh Y. Gawande,Priynka Pahwa,Tatyana A. Gloriozova,Alexander V. Dmitriev,Sergey Ivanov,A. V. Rudik,Varvara I. Konova,Pavel V. Pogodin,D. S. Druzhilovsky,Vladimir Poroikov +11 more
TL;DR: This review contains a practical example of the application of combined chemo- and bioinformatics methods to study pleiotropic therapeutic effects of 50 medicinal plants from Traditional Indian Medicine.
Journal ArticleDOI
Computer-aided prediction of biological activity spectra for organic compounds: the possibilities and limitations
Vladimir Poroikov,Dmitrii Filimonov,Tatyana A. Gloriozova,Alexey Lagunin,Dmitry S. Druzhilovskiy,A. V. Rudik,Leonid A. Stolbov,Alexander V. Dmitriev,Olga Tarasova,Sergey Ivanov,Pavel V. Pogodin +10 more
TL;DR: The current version of the PASS program for prediction of biological activity spectra of organic compounds based on analysis of structure—activity relationships (SAR) for a training set containing information on more than 1000 000 biologically active organic compounds is described.