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Computational and Synthetic Approaches of Drug Discovery in Cancer and Neurological Disorders

A special issue of Molecules (ISSN 1420-3049). This special issue belongs to the section "Medicinal Chemistry".

Deadline for manuscript submissions: closed (29 February 2024) | Viewed by 10635

Special Issue Editors


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Guest Editor
Rajarshi Shahu College of Pharmacy, Buldhana 443001, Maharashtra, India
Interests: CADD; structure-based drug design; molecular docking; molecular dynamics; computational and experimental anticancer activity

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Guest Editor
Department of Chemical Technology, Dr. Babasaheb Ambedkar Marthwada University, Auranagabad, Maharashtra, India
Interests: computational and experimental anticancer studies; synthesis of bioactive compounds

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Guest Editor
Department of Pharmaceutical Chemistry, R. C. Patel Institute of Pharmaceutical Education and Research, Shirpur 425405, Maharashtra, India
Interests: computational and experimental neuroscience

Special Issue Information

Dear Colleagues,

Cancer is one of the world's most miserable diseases; while advances in molecular and cellular biology have resulted in a decrease in cancer-related mortality, drug discovery and cancer development are time-consuming and costly processes. In the past few years, there have been constant improvements in the research and development of new anticancer drugs. Several compounds including small molecules, antibodies, and immunomodulators have been approved to treat cancer. Despite significant advances in the field of drug discovery of anti-cancer agents, there is still a considerable need for novel and improved drug therapies in combination with conventional techniques. With numerous studies reporting significant results in the treatment of various types of cancer, computational and synthetic approaches are  among the most promising fields of drug discovery research.

Neurodegenerative diseases are multifactorial debilitating disorders of the central nervous system (CNS) affecting 30 million people around the globe. Neurological disorders, such as Alzheimer’s (AD), Parkinson’s (PD), Huntington’s diseases (HD), amyotrophic lateral sclerosis (ALS), and epilepsy comprise a group of neuropathologies characterized by specific etiologies with distinct morphological and pathophysiological features of the involved targets. In this Special Issue, we gather more recent information to understand the structure–function relationship of potential CNS modulator ligands that will advance the understanding of many aspects of brain function at the molecular, cellular, and systems level, in order to provide new treatment modalities. Moreover, taking stock of these target selective compounds reminds us that the future is bright, and that the persistent, thoughtful, creative, and collaborative efforts stand an excellent chance of solving the most stubborn and intractable neurological problems.

Currently, in silico approaches are an essential part of the drug discovery process, primarily because they can accelerate the entire drug development pathway by finding and discovering new prospective therapeutics with significant savings in terms of cost and time. Furthermore, computer-aided drug design (CADD) benefits from the use of artificial intelligence (AI) approaches at many stages of the drug development pipeline. Computational approaches, such as  structure-based drug designing, ligand-based drug designing, and combined structure-based and ligand-based approaches can be used at different levels for target identification or lead discovery, representing a key resource for medicinal scientists to foster the optimization of small molecules.

For this Special issue, we invite researchers to submit their original research articles, short communications, and review articles addressing the use of CADD in the design and optimization of small molecules for the treatment of cancer and neurological disorders. We urge the submission of purely in silico studies, as well as computational studies with experimental validations.

Dr. Deepak K. Lokwani
Dr. Aniket P. Sarkate
Dr. Vinod G. Ugale
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Molecules is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • design and synthesis
  • anticancer agents
  • EGFR
  • HDAC
  • neurological disorders
  • glutamate modulators
  • GABA
  • computer-aided drug design

Published Papers (4 papers)

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Research

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13 pages, 2244 KiB  
Article
Multi-Omics Analysis Revealed Increased De Novo Synthesis of Serine and Lower Activity of the Methionine Cycle in Breast Cancer Cell Lines
by Monika Pankevičiūtė-Bukauskienė, Valeryia Mikalayeva, Vaidotas Žvikas, V. Arvydas Skeberdis and Sergio Bordel
Molecules 2023, 28(11), 4535; https://doi.org/10.3390/molecules28114535 - 3 Jun 2023
Viewed by 1513
Abstract
A pipeline for metabolomics, based on UPLC-ESI-MS, was tested on two malignant breast cancer cell lines of the sub-types ER(+), PR(+), and HER2(3+) (MCF-7 and BCC), and one non-malignant epithelial cancer cell line (MCF-10A). This allowed us to quantify 33 internal metabolites, 10 [...] Read more.
A pipeline for metabolomics, based on UPLC-ESI-MS, was tested on two malignant breast cancer cell lines of the sub-types ER(+), PR(+), and HER2(3+) (MCF-7 and BCC), and one non-malignant epithelial cancer cell line (MCF-10A). This allowed us to quantify 33 internal metabolites, 10 of which showed a concentration profile associated with malignancy. Whole-transcriptome RNA-seq was also carried out for the three mentioned cell lines. An integrated analysis of metabolomics and transcriptomics was carried out using a genome-scale metabolic model. Metabolomics revealed the depletion of several metabolites that have homocysteine as a precursor, which was consistent with the lower activity of the methionine cycle caused by lower expression of the AHCY gene in cancer cell lines. Increased intracellular serine pools in cancer cell lines appeared to result from the over-expression of PHGDH and PSPH, which are involved in intracellular serine biosynthesis. An increased concentration of pyroglutamic acid in malignant cells was linked to the overexpression of the gene CHAC1. Full article
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19 pages, 30528 KiB  
Article
Cytotoxic Activity, Topoisomerase I Inhibition and In Silico Studies of New Sesquiterpene-aryl Ester Derivatives of (-) Drimenol
by Ileana Araque, Javiera Ramírez, Rut Vergara, Jaime Mella, Pablo Aránguiz, Luis Espinoza, Waleska Vera, Iván Montenegro, Cristian O. Salas, Joan Villena and Mauricio A. Cuellar
Molecules 2023, 28(9), 3959; https://doi.org/10.3390/molecules28093959 - 8 May 2023
Viewed by 1710
Abstract
In this study, we aimed to evaluate two sets of sesquiterpene-aryl derivatives linked by an ester bond, their cytotoxic activities, and their capacity to activate caspases 3/7 and inhibit human topoisomerase I (TOP1). A total of 13 compounds were synthesized from the natural [...] Read more.
In this study, we aimed to evaluate two sets of sesquiterpene-aryl derivatives linked by an ester bond, their cytotoxic activities, and their capacity to activate caspases 3/7 and inhibit human topoisomerase I (TOP1). A total of 13 compounds were synthesized from the natural sesquiterpene (-)-drimenol and their cytotoxic activity was evaluated in vitro against three cancer cell lines: PC-3 (prostate cancer), HT-29 (colon cancer), MCF-7 (breast cancer), and an immortalized non-tumoral cell line (MCF-10). From the results, it was observed that 6a was the most promising compound due to its cytotoxic effect on three cancer cell lines and its selectivity, 6a was 100-fold more selective than 5-FU in MCF-7 and 20-fold in PC-3. It was observed that 6a also induced apoptosis by caspases 3/7 activity using a Capsase-Glo-3/7 assay kit and inhibited TOP1. A possible binding mode of 6a in a complex with TOP1-DNA was proposed by docking and molecular dynamics studies. In addition, 6a was predicted to have a good pharmacokinetic profile for oral administration. Therefore, through this study, it was demonstrated that the drimane scaffold should be considered in the search of new antitumoral agents. Full article
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19 pages, 3609 KiB  
Article
Identification of Novel Natural Dual HDAC and Hsp90 Inhibitors for Metastatic TNBC Using e-Pharmacophore Modeling, Molecular Docking, and Molecular Dynamics Studies
by Nihal AbdElmoniem, Marwa H. Abdallah, Rua M. Mukhtar, Fatima Moutasim, Ahmed Rafie Ahmed, Alaa Edris, Walaa Ibraheem, Alaa A. Makki, Eman M. Elshamly, Rashid Elhag, Wadah Osman, Ramzi A. Mothana and Abdulrahim A. Alzain
Molecules 2023, 28(4), 1771; https://doi.org/10.3390/molecules28041771 - 13 Feb 2023
Cited by 10 | Viewed by 2932
Abstract
Breast cancer (BC) is one of the main types of cancer that endangers women’s lives. The characteristics of triple-negative breast cancer (TNBC) include a high rate of recurrence and the capacity for metastasis; therefore, new therapies are urgently needed to combat TNBC. Dual [...] Read more.
Breast cancer (BC) is one of the main types of cancer that endangers women’s lives. The characteristics of triple-negative breast cancer (TNBC) include a high rate of recurrence and the capacity for metastasis; therefore, new therapies are urgently needed to combat TNBC. Dual targeting HDAC6 and Hsp90 has shown good synergistic effects in treating metastatic TNBC. The goal of this study was to find potential HDAC6 and Hsp90 dual inhibitors. Therefore, several in silico approaches have been used. An e-pharmacophore model generation based on the HDAC6-ligand complex and subsequently a pharmacophore-based virtual screening on 270,450 natural compounds from the ZINC were performed, which resulted in 12,663 compounds that corresponded to the obtained pharmacophoric hypothesis. These compounds were docked into HDAC6 and Hsp90. This resulted in the identification of three compounds with good docking scores and favorable free binding energy against the two targets. The top three compounds, namely ZINC000096116556, ZINC000020761262, and ZINC000217668954, were further subjected to ADME prediction and molecular dynamic simulations, which showed promising results in terms of pharmacokinetic properties and stability. As a result, these three compounds can be considered potential HDAC6 and Hsp90 dual inhibitors and are recommended for experimental evaluation. Full article
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Review

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31 pages, 6333 KiB  
Review
Matrix Metalloproteinases Inhibitors in Cancer Treatment: An Updated Review (2013–2023)
by Shriefa Almutairi, Hanin Moh’d Kalloush, Nour A. Manoon and Sanaa K. Bardaweel
Molecules 2023, 28(14), 5567; https://doi.org/10.3390/molecules28145567 - 21 Jul 2023
Cited by 7 | Viewed by 3475
Abstract
Matrix metalloproteinases (MMPs) are identifiable members of proteolytic enzymes that can degrade a wide range of proteins in the extracellular matrix (ECM). MMPs can be categorized into six groups based on their substrate specificity and structural differences: collagenases, gelatinases, stromelysins, matrilysins, metalloelastase, and [...] Read more.
Matrix metalloproteinases (MMPs) are identifiable members of proteolytic enzymes that can degrade a wide range of proteins in the extracellular matrix (ECM). MMPs can be categorized into six groups based on their substrate specificity and structural differences: collagenases, gelatinases, stromelysins, matrilysins, metalloelastase, and membrane-type MMPs. MMPs have been linked to a wide variety of biological processes, such as cell transformation and carcinogenesis. Over time, MMPs have been evaluated for their role in cancer progression, migration, and metastasis. Accordingly, various MMPs have become attractive therapeutic targets for anticancer drug development. The first generations of broad-spectrum MMP inhibitors displayed effective inhibitory activities but failed in clinical trials due to poor selectivity. Thanks to the evolution of X-ray crystallography, NMR analysis, and homology modeling studies, it has been possible to characterize the active sites of various MMPs and, consequently, to develop more selective, second-generation MMP inhibitors. In this review, we summarize the computational and synthesis approaches used in the development of MMP inhibitors and their evaluation as potential anticancer agents. Full article
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