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Pharmaceuticals
Volume 15
Issue 3
10.3390/ph15030303
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Article

Exploring the Prominent and Concealed Inhibitory Features for Cytoplasmic Isoforms of Hsp90 Using QSAR Analysis

by
Magdi E. A. Zaki
1,*,
Sami A. Al-Hussain
1,
Syed Nasir Abbas Bukhari
2,
Vijay H. Masand
3,*,
Mithilesh M. Rathore
3,
Sumer D. Thakur
4 and
Vaishali M. Patil
5
1
Department of Chemistry, Faculty of Science, Imam Mohammad Ibn Saud Islamic University, Riyadh 13318, Saudi Arabia
2
Department of Pharmaceutical Chemistry, College of Pharmacy, Jouf University, Al Jouf 72388, Saudi Arabia
3
Department of Chemistry, Vidya Bharati Mahavidyalaya, Amravati 444 602, Maharashtra, India
4
Department of Chemistry, RDIK and NKD College, Badnera-Amravati 444 701, Maharashtra, India
5
Department of Pharmaceutical Chemistry, KIET School of Pharmacy, KIET Group of Institutions, Delhi-NCR, Ghaziabad 201206, Uttar Pradesh, India
*
Authors to whom correspondence should be addressed.
Pharmaceuticals 2022, 15(3), 303; https://doi.org/10.3390/ph15030303
Submission received: 21 January 2022 / Revised: 19 February 2022 / Accepted: 23 February 2022 / Published: 1 March 2022
(This article belongs to the Special Issue In Silico Approaches in Drug Design)
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Abstract

Cancer is a major life-threatening disease with a high mortality rate in many countries. Even though different therapies and options are available, patients generally prefer chemotherapy. However, serious side effects of anti-cancer drugs compel us to search for a safer drug. To achieve this target, Hsp90 (heat shock protein 90), which is responsible for stabilization of many oncoproteins in cancer cells, is a promising target for developing an anti-cancer drug. The QSAR (Quantitative Structure–Activity Relationship) could be useful to identify crucial pharmacophoric features to develop a Hsp90 inhibitor. Therefore, in the present work, a larger dataset encompassing 1141 diverse compounds was used to develop a multi-linear QSAR model with a balance of acceptable predictive ability (Predictive QSAR) and mechanistic interpretation (Mechanistic QSAR). The new developed six-parameter model satisfies the recommended values for a good number of validation parameters such as R2tr = 0.78, Q2LMO = 0.77, R2ex = 0.78, and CCCex = 0.88. The present analysis reveals that the Hsp90 inhibitory activity is correlated with different types of nitrogen atoms and other hidden structural features such as the presence of hydrophobic ring/aromatic carbon atoms within a specific distance from the center of mass of the molecule, etc. Thus, the model successfully identified a variety of reported as well as novel pharmacophoric features. The results of QSAR analysis are further vindicated by reported crystal structures of compounds with Hsp90.
Keywords: Hsp90; cancer; QSAR; machine learning; pharmacophores Hsp90; cancer; QSAR; machine learning; pharmacophores

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MDPI and ACS Style

Zaki, M.E.A.; Al-Hussain, S.A.; Bukhari, S.N.A.; Masand, V.H.; Rathore, M.M.; Thakur, S.D.; Patil, V.M. Exploring the Prominent and Concealed Inhibitory Features for Cytoplasmic Isoforms of Hsp90 Using QSAR Analysis. Pharmaceuticals 2022, 15, 303. https://doi.org/10.3390/ph15030303

AMA Style

Zaki MEA, Al-Hussain SA, Bukhari SNA, Masand VH, Rathore MM, Thakur SD, Patil VM. Exploring the Prominent and Concealed Inhibitory Features for Cytoplasmic Isoforms of Hsp90 Using QSAR Analysis. Pharmaceuticals. 2022; 15(3):303. https://doi.org/10.3390/ph15030303

Chicago/Turabian Style

Zaki, Magdi E. A., Sami A. Al-Hussain, Syed Nasir Abbas Bukhari, Vijay H. Masand, Mithilesh M. Rathore, Sumer D. Thakur, and Vaishali M. Patil. 2022. "Exploring the Prominent and Concealed Inhibitory Features for Cytoplasmic Isoforms of Hsp90 Using QSAR Analysis" Pharmaceuticals 15, no. 3: 303. https://doi.org/10.3390/ph15030303

APA Style

Zaki, M. E. A., Al-Hussain, S. A., Bukhari, S. N. A., Masand, V. H., Rathore, M. M., Thakur, S. D., & Patil, V. M. (2022). Exploring the Prominent and Concealed Inhibitory Features for Cytoplasmic Isoforms of Hsp90 Using QSAR Analysis. Pharmaceuticals, 15(3), 303. https://doi.org/10.3390/ph15030303

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