Multistaged In Silico Discovery of the Best SARS-CoV-2 Main Protease Inhibitors amongst 3009 Clinical and FDA-Approved Compounds

被引:3
|
作者
Eissa, Ibrahim H. [1 ]
Saleh, Abdulrahman M. [1 ]
Al-Rashood, Sara T. [2 ]
El-Attar, Abdul-Aziz M. M. [3 ]
Metwaly, Ahmed M. [4 ,5 ]
机构
[1] Al Azhar Univ, Fac Pharm Boys, Pharmaceut Med Chem & Drug Design Dept, Cairo 11884, Egypt
[2] King Saud Univ, Coll Pharm, Dept Pharmaceut Chem, PO Box 2457, Riyadh 11451, Saudi Arabia
[3] Al Azhar Univ, Fac Pharm, Pharmaceut Analyt Chem Dept, Cairo 11884, Egypt
[4] Al Azhar Univ, Fac Pharm Boys, Pharmacognosy & Med Plants Dept, Cairo 11884, Egypt
[5] City Sci Res & Technol Applicat SRTA City, Biopharmaceut Prod Res Dept, Genet Engn & Biotechnol Res Inst, Alexandria 21934, Egypt
关键词
MOLECULAR-DYNAMICS; FINGERPRINTS; SIMULATIONS; PERFORMANCE; STRATEGIES; DOCKING; 3D-QSAR; CHARMM; GUI;
D O I
10.1155/2024/5084553
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
As a follow-up to our teamwork's former work against SARS-CoV-2, eight compounds (ramelteon (68), prilocaine (224), nefiracetam (339), cyclandelate (911), mepivacaine (2325), ropivacaine (2351), tasimelteon (2384), and levobupivacaine (2840)) were revealed as the best potentially active SARS-CoV-2 inhibitors targeting the main protease (PDB ID: 5R84), M-pro. The compounds were named in the midst of 3009 FDA and clinically approved compounds employing a multistaged in silico method. A molecular fingerprints study with GWS, the cocrystallized ligand of the M-pro, indicated the resemblance of 150 candidates. Consequently, a structure similarity experiment disclosed the best twenty-nine analogous. Then, molecular docking studies were done against the M-pro active site and showed the binding of the best compounds. Next, a 3D-pharmacophore study confirmed the obtained results for the eight compounds by exhibiting relative fit values of more than 90% (except for 68, 74%, and 2384, 83%). Levobupivacaine (2840) showed the most accurate docking and pharmacophore scores and was picked for further MD simulations experiments (RMSD, RMSF, R-g, SASA, and H-H bonding) over 100 ns. The MD simulations results revealed the accurate binding as well as the optimum dynamics of the M-pro-levobupivacaine complex. Finally, MM-PBSA studies were conducted and indicated the favorable bonding of the M-pro-levobupivacaine complex with a free energy value of -235 kJ/mol. The fulfilled outcomes hold out hope of beating COVID-19 through more in vitro and in vivo research for the named compounds.
引用
收藏
页数:19
相关论文
共 50 条
  • [31] Virtual screening of approved drugs as potential SARS-CoV-2 main protease inhibitors
    Jimenez-Alberto, Alicia
    Maria Ribas-Aparicio, Rosa
    Aparicio-Ozores, Gerardo
    Castelan-Vega, Juan A.
    COMPUTATIONAL BIOLOGY AND CHEMISTRY, 2020, 88 (88)
  • [32] Reprofiling of approved drugs against SARS-CoV-2 main protease: an in-silico study
    Kumar, Prateek
    Bhardwaj, Taniya
    Kumar, Ankur
    Gehi, Bhuvaneshwari R.
    Kapuganti, Shivani K.
    Garg, Neha
    Nath, Gopal
    Giri, Rajanish
    JOURNAL OF BIOMOLECULAR STRUCTURE & DYNAMICS, 2022, 40 (07): : 3170 - 3184
  • [33] Rutin and flavone analogs as prospective SARS-CoV-2 main protease inhibitors: In silico drug discovery study
    Ibrahim, Mahmoud A. A.
    Mohamed, Eslam A. R.
    Abdelrahman, Alaa H. M.
    Allemailem, Khaled S.
    Moustafa, Mahmoud F.
    Shawky, Ahmed M.
    Mahzari, Ali
    Hakami, Abdulrahim Refdan
    Abdeljawaad, Khlood A. A.
    Atia, Mohamed A. M.
    JOURNAL OF MOLECULAR GRAPHICS & MODELLING, 2021, 105
  • [34] Rutin and flavone analogs as prospective SARS-CoV-2 main protease inhibitors: In silico drug discovery study
    Ibrahim, Mahmoud A.A.
    Mohamed, Eslam A.R.
    Abdelrahman, Alaa H.M.
    Allemailem, Khaled S.
    Moustafa, Mahmoud F.
    Shawky, Ahmed M.
    Mahzari, Ali
    Hakami, Abdulrahim Refdan
    Abdeljawaad, Khlood A.A.
    Atia, Mohamed A.M.
    Journal of Molecular Graphics and Modelling, 2021, 105
  • [35] In silico structure-based discovery of a SARS-CoV-2 main protease inhibitor
    Wen, Lei
    Tang, Kaiming
    Chik, Kenn Ka-Heng
    Chan, Chris Chun-Yiu
    Tsang, Jessica Oi-Ling
    Liang, Ronghui
    Cao, Jianli
    Huang, Yaoqiang
    Luo, Cuiting
    Cai, Jian-Piao
    Ye, Zi-Wei
    Yin, Feifei
    Chu, Hin
    Jin, Dong-Yan
    Yuen, Kwok-Yung
    Yuan, Shuofeng
    Chan, Jasper Fuk-Woo
    INTERNATIONAL JOURNAL OF BIOLOGICAL SCIENCES, 2021, 17 (06): : 1555 - 1564
  • [36] Binary-QSAR guided virtual screening of FDA approved drugs and compounds in clinical investigation against SARS-CoV-2 main protease
    Oktay, Lalehan
    Erdemoglu, Ece
    Tolu, Ilayda
    Yumak, Yesim
    Ozcan, Aysenur
    Acar, Elif
    Buyukkilic, Sehriban
    Olkan, Alpsu
    Durdagi, Serdar
    TURKISH JOURNAL OF BIOLOGY, 2021, 45 (04) : 459 - +
  • [37] Discovery of 2-thiobenzimidazoles as noncovalent inhibitors of SARS-CoV-2 main protease
    Deodato, Davide
    Asad, Nadeem
    Dore, Timothy M.
    BIOORGANIC & MEDICINAL CHEMISTRY LETTERS, 2022, 72
  • [38] In silico tuning of binding selectivity for new SARS-CoV-2 main protease inhibitors
    Wang, Feng
    Vasilyev, Vladislav
    COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE, 2025, 262
  • [39] Repurposing FDA-Approved Drugs as Potential Inhibitors of SARS-CoV-2 PLpro: A Comprehensive Computational Study
    Metwaly, Ahmed M.
    Elkaeed, Eslam B.
    Alsfouk, Aisha A.
    Ibrahim, Ibrahim M.
    Soliman, Omar A.
    Elkady, Hazem
    Eissa, Ibrahim H.
    JOURNAL OF COMPUTATIONAL BIOPHYSICS AND CHEMISTRY, 2024, 23 (09): : 1209 - 1231
  • [40] In silico screening of potential antiviral inhibitors against SARS-CoV-2 main protease
    Palanisamy, Kandhan
    Maiyelvaganan, K. Rudharachari
    Kamalakannan, Shanmugasundaram
    Thilagavathi, Ramasamy
    Selvam, Chelliah
    Prakash, Muthuramalingam
    MOLECULAR SIMULATION, 2023, 49 (02) : 175 - 185