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A special issue of International Journal of Molecular Sciences (ISSN 1422-0067). This special issue belongs to the section "Molecular Informatics".

Deadline for manuscript submissions: closed (31 October 2022) | Viewed by 20617

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Prof. Dr. Jesús Vicente de Julián-Ortiz

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Molecular Topology and Drug Design Research Unit, Department of Physical Chemistry, Faculty of Pharmacy, University of Valencia, Valencia, Spain
Interests: computational chemistry; medicinal chemistry
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Dr. Francisco Torrens

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Institut Universitari de Ciència Molecular, Universitat de València, Edifici d’Instituts de Paterna, P.O. Box 22085, E-46071 València, Spain
Interests: physical chemistry; theoretical chemistry; computational chemistry; modelling and simulation; computer-aided drug design and development
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Prof. Dr. Gloria Castellano

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Centro de Investigación Traslacional San Alberto Magno (CITSAM), Catholic University of Valencia San Vicente Mártir, 46001 Valencia, Spain
Interests: natural products; organic chemistry; phytochemistry; medicinal plant chemistry; food chemistry
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

There is currently a great, ongoing effort to better understand and treat diseases. Computational modeling is becoming increasingly important in biomedical research for understanding how biomolecules interact at the molecular level, as well as the molecular mechanisms of disease. Regarding their applications in xenobiotics, computational methods are fundamental for the discovery of drugs and the assessment of risks associated with chemicals, due to their multiple uses in the collection, processing, analysis and modeling of data. This means that animal testing is less necessary. Drug design is a multi-objective process in which various characteristics, such as efficacy, pharmacokinetics, and safety, must be optimized. With this in mind, advances in computational intelligence and machine learning are providing a basis for more effective searches of chemical spaces and the prediction of biological properties based on molecular structure. This issue aims to show different approaches and technologies that could be implemented in drug design in the near future.

Prof. Dr. Jesús Vicente de Julián-Ortiz
Dr. Francisco Torrens
Prof. Dr. Gloria Castellano
Guest Editors

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Keywords

molecular modeling
drug design
molecular mechanism
mathematical chemistry
structure–activity relationships
molecular descriptors
pharmacokinetics
toxicity

Published Papers (10 papers)

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Research

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25 pages, 3200 KiB

Open AccessArticle

by Ángela García-García, Jesus Vicente de Julián-Ortiz, Jorge Gálvez, David Font, Carles Ayats, María del Remedio Guna Serrano, Carlos Muñoz-Collado, Rafael Borrás and José Manuel Villalgordo

Int. J. Mol. Sci. 2022, 23(23), 15057; https://doi.org/10.3390/ijms232315057 - 01 Dec 2022

Cited by 1 | Viewed by 1348

Abstract

A method to identify molecular scaffolds potentially active against the Mycobacterium tuberculosis complex (MTBC) is developed. A set of structurally heterogeneous agents against MTBC was used to obtain a mathematical model based on topological descriptors. This model was statistically validated through a Leave-n-Out test. It successfully discriminated between active or inactive compounds over 86% in database sets. It was also useful to select new potential antituberculosis compounds in external databases. The selection of new substituted pyrimidines, pyrimidones and triazolo[1,5-a]pyrimidines was particularly interesting because these structures could provide new scaffolds in this field. The seven selected candidates were synthesized and six of them showed activity in vitro. Full article

(This article belongs to the Special Issue Computational Studies of Drugs and Biomolecules)

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18 pages, 5759 KiB

Open AccessArticle

Pharmacophore Synergism in Diverse Scaffold Clinches in Aurora Kinase B

by Vijay H. Masand, Sami A. Al-Hussain, Mithilesh M. Rathore, Sumer D. Thakur, Siddhartha Akasapu, Abdul Samad, Aamal A. Al-Mutairi and Magdi E. A. Zaki

Int. J. Mol. Sci. 2022, 23(23), 14527; https://doi.org/10.3390/ijms232314527 - 22 Nov 2022

Cited by 1 | Viewed by 1299

Abstract

Aurora kinase B (AKB) is a crucial signaling kinase with an important role in cell division. Therefore, inhibition of AKB is an attractive approach to the treatment of cancer. In the present work, extensive quantitative structure–activity relationships (QSAR) analysis has been performed using a set of 561 structurally diverse aurora kinase B inhibitors. The Organization for Economic Cooperation and Development (OECD) guidelines were used to develop a QSAR model that has high statistical performance (R²_tr = 0.815, Q²_LMO = 0.808, R²_ex = 0.814, CCC_ex = 0.899). The seven-variable-based newly developed QSAR model has an excellent balance of external predictive ability (Predictive QSAR) and mechanistic interpretation (Mechanistic QSAR). The QSAR analysis successfully identifies not only the visible pharmacophoric features but also the hidden features. The analysis indicates that the lipophilic and polar groups—especially the H-bond capable groups—must be present at a specific distance from each other. Moreover, the ring nitrogen and ring carbon atoms play important roles in determining the inhibitory activity for AKB. The analysis effectively captures reported as well as unreported pharmacophoric features. The results of the present analysis are also supported by the reported crystal structures of inhibitors bound to AKB. Full article

(This article belongs to the Special Issue Computational Studies of Drugs and Biomolecules)

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11 pages, 2588 KiB

Open AccessArticle

MSClustering: A Cytoscape Tool for Multi-Level Clustering of Biological Networks

by Bo-Kai Ge, Geng-Ming Hu, Rex Chen and Chi-Ming Chen

Int. J. Mol. Sci. 2022, 23(22), 14240; https://doi.org/10.3390/ijms232214240 - 17 Nov 2022

Cited by 3 | Viewed by 1589

Abstract

MSClustering is an efficient software package for visualizing and analyzing complex networks in Cytoscape. Based on the distance matrix of a network that it takes as input, MSClustering automatically displays the minimum span clustering (MSC) of the network at various characteristic levels. To produce a view of the overall network structure, the app then organizes the multi-level results into an MSC tree. Here, we demonstrate the package’s phylogenetic applications in studying the evolutionary relationships of complex systems, including 63 beta coronaviruses and 197 GPCRs. The validity of MSClustering for large systems has been verified by its clustering of 3481 enzymes. Through an experimental comparison, we show that MSClustering outperforms five different state-of-the-art methods in the efficiency and reliability of their clustering. Full article

(This article belongs to the Special Issue Computational Studies of Drugs and Biomolecules)

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24 pages, 4478 KiB

Open AccessArticle

Dual Inhibitors of AChE and BACE-1 for Reducing Aβ in Alzheimer’s Disease: From In Silico to In Vivo

by Noa Stern, Alexandra Gacs, Enikő Tátrai, Beáta Flachner, István Hajdú, Krisztina Dobi, István Bágyi, György Dormán, Zsolt Lőrincz, Sándor Cseh, Attila Kígyós, József Tóvári and Amiram Goldblum

Int. J. Mol. Sci. 2022, 23(21), 13098; https://doi.org/10.3390/ijms232113098 - 28 Oct 2022

Cited by 8 | Viewed by 1885

Abstract

Alzheimer’s disease (AD) is a complex and widespread condition, still not fully understood and with no cure yet. Amyloid beta (Aβ) peptide is suspected to be a major cause of AD, and therefore, simultaneously blocking its formation and aggregation by inhibition of the enzymes BACE-1 (β-secretase) and AChE (acetylcholinesterase) by a single inhibitor may be an effective therapeutic approach, as compared to blocking one of these targets or by combining two drugs, one for each of these targets. We used our ISE algorithm to model each of the AChE peripheral site inhibitors and BACE-1 inhibitors, on the basis of published data, and constructed classification models for each. Subsequently, we screened large molecular databases with both models. Top scored molecules were docked into AChE and BACE-1 crystal structures, and 36 Molecules with the best weighted scores (based on ISE indexes and docking results) were sent for inhibition studies on the two enzymes. Two of them inhibited both AChE (IC₅₀ between 4–7 μM) and BACE-1 (IC₅₀ between 50–65 μM). Two additional molecules inhibited only AChE, and another two molecules inhibited only BACE-1. Preliminary testing of inhibition by F681-0222 (molecule 2) on APPswe/PS1dE9 transgenic mice shows a reduction in brain tissue of soluble Aβ42. Full article

(This article belongs to the Special Issue Computational Studies of Drugs and Biomolecules)

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19 pages, 2365 KiB

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Role of the Guanidinium Groups in Ligand–Receptor Binding of Arginine-Containing Short Peptides to the Slow Sodium Channel: Quantitative Approach to Drug Design of Peptide Analgesics

by Vera B. Plakhova, Dmitriy M. Samosvat, Georgy G. Zegrya, Valentina A. Penniyaynen, Arina D. Kalinina, Ma Ke, Svetlana A. Podzorova, Boris V. Krylov and Ilya V. Rogachevskii

Int. J. Mol. Sci. 2022, 23(18), 10640; https://doi.org/10.3390/ijms231810640 - 13 Sep 2022

Cited by 4 | Viewed by 1326

Abstract

Several arginine-containing short peptides have been shown by the patch-clamp method to effectively modulate the Na_V1.8 channel activation gating system, which makes them promising candidates for the role of a novel analgesic medicinal substance. As demonstrated by the organotypic tissue culture method, all active and inactive peptides studied do not trigger the downstream signaling cascades controlling neurite outgrowth and should not be expected to evoke adverse side effects on the tissue level upon their medicinal administration. The conformational analysis of Ac-RAR-NH₂, Ac-RER-NH₂, Ac-RAAR-NH₂, Ac-REAR-NH₂, Ac-RERR-NH₂, Ac-REAAR-NH₂, Ac-PRERRA-NH₂, and Ac-PRARRA-NH₂ has made it possible to find the structural parameter, the value of which is correlated with the target physiological effect of arginine-containing short peptides. The distances between the positively charged guanidinium groups of the arginine side chains involved in intermolecular ligand–receptor ion–ion bonds between the attacking peptide molecules and the Na_V1.8 channel molecule should fall within a certain range, the lower threshold of which is estimated to be around 9 Å. The distance values have been calculated to be below 9 Å in the inactive peptide molecules, except for Ac-RER-NH₂, and in the range of 9–12 Å in the active peptide molecules. Full article

(This article belongs to the Special Issue Computational Studies of Drugs and Biomolecules)

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20 pages, 4808 KiB

Open AccessArticle

Exploration of N-Arylsulfonyl-indole-2-carboxamide Derivatives as Novel Fructose-1,6-bisphosphatase Inhibitors by Molecular Simulation

by Yilan Zhao, Honghao Yang, Fengshou Wu, Xiaogang Luo, Qi Sun, Weiliang Feng, Xiulian Ju and Genyan Liu

Int. J. Mol. Sci. 2022, 23(18), 10259; https://doi.org/10.3390/ijms231810259 - 06 Sep 2022

Cited by 5 | Viewed by 1254

Abstract

A series of N-arylsulfonyl-indole-2-carboxamide derivatives have been identified as potent fructose-1,6-bisphosphatase (FBPase) inhibitors (FBPIs) with excellent selectivity for the potential therapy of type II diabetes mellitus. To explore the structure–activity relationships (SARs) and the mechanisms of action of these FBPIs, a systematic computational study was performed in the present study, including three-dimensional quantitative structure–activity relationship (3D-QSAR) modeling, pharmacophore modeling, molecular dynamics (MD), and virtual screening. The constructed 3D-QSAR models exhibited good predictive ability with reasonable parameters using comparative molecular field analysis (q² = 0.709, R² = 0.979, r_pre² = 0.932) and comparative molecular similarity indices analysis (q² = 0.716, R² = 0.978, r_pre² = 0.890). Twelve hit compounds were obtained by virtual screening using the best pharmacophore model in combination with molecular dockings. Three compounds with relatively higher docking scores and better ADME properties were then selected for further studies by docking and MD analyses. The docking results revealed that the amino acid residues Met18, Gly21, Gly26, Leu30, and Thr31 at the binding site were of great importance for the effective bindings of these FBPIs. The MD results indicated that the screened compounds VS01 and VS02 could bind with FBPase stably as its cognate ligand in dynamic conditions. This work identified several potential FBPIs by modeling studies and might provide important insights into developing novel FBPIs. Full article

(This article belongs to the Special Issue Computational Studies of Drugs and Biomolecules)

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19 pages, 26998 KiB

Open AccessArticle

In-Silico Drug Toxicity and Interaction Prediction for Plant Complexes Based on Virtual Screening and Text Mining

by Feng Zhang, Kumar Ganesan, Yan Li and Jianping Chen

Int. J. Mol. Sci. 2022, 23(17), 10056; https://doi.org/10.3390/ijms231710056 - 02 Sep 2022

Cited by 1 | Viewed by 2268

Abstract

Potential drug toxicities and drug interactions of redundant compounds of plant complexes may cause unexpected clinical responses or even severe adverse events. On the other hand, super-additivity of drug interactions between natural products and synthetic drugs may be utilized to gain better performance in disease management. Although without enough datasets for prediction model training, based on the SwissSimilarity and PubChem platforms, for the first time, a feasible workflow of prediction of both toxicity and drug interaction of plant complexes was built in this study. The optimal similarity score threshold for toxicity prediction of this system is 0.6171, based on an analysis of 20 different herbal medicines. From the PubChem database, 31 different sections of toxicity information such as “Acute Effects”, “NIOSH Toxicity Data”, “Interactions”, “Hepatotoxicity”, “Carcinogenicity”, “Symptoms”, and “Human Toxicity Values” sections have been retrieved, with dozens of active compounds predicted to exert potential toxicities. In Spatholobus suberectus Dunn (SSD), there are 9 out of 24 active compounds predicted to play synergistic effects on cancer management with various drugs or factors. The synergism between SSD, luteolin and docetaxel in the management of triple-negative breast cancer was proved by the combination index assay, synergy score detection assay, and xenograft model. Full article

(This article belongs to the Special Issue Computational Studies of Drugs and Biomolecules)

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15 pages, 4007 KiB

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Pharmaceutical Cocrystals of Ethenzamide: Molecular Structure Analysis Based on Vibrational Spectra and DFT Calculations

by Mei Wan, Jiyuan Fang, Jiadan Xue, Jianjun Liu, Jianyuan Qin, Zhi Hong, Jiusheng Li and Yong Du

Int. J. Mol. Sci. 2022, 23(15), 8550; https://doi.org/10.3390/ijms23158550 - 01 Aug 2022

Cited by 7 | Viewed by 1632

Abstract

Pharmaceutical cocrystals can offer another advanced strategy for drug preparation and development and can facilitate improvements to the physicochemical properties of active pharmaceutical ingredients (APIs) without altering their chemical structures and corresponding pharmacological activities. Therefore, cocrystals show a great deal of potential in the development and research of drugs. In this work, pharmaceutical cocrystals of ethenzamide (ETZ) with 2,6-dihydroxybenzoic acid (26DHBA), 2,4-dihydroxybenzoic acid (24DHBA) and gallic acid (GA) were synthesized by the solvent evaporation method. In order to gain a deeper understanding of the structural changes after ETZ cocrystallization, terahertz time domain spectroscopy (THz-TDS) and Raman spectroscopy were used to characterize the single starting samples, corresponding physical mixtures and the cocrystals. In addition, the possible molecular structures of ETZ-GA, ETZ-26DHBA and ETZ-24DHBA cocrystals were optimized by density functional theory (DFT). The results of THz and Raman spectra with the DFT simulations for the three cocrystals revealed that the ETZ-GA cocrystal formed an O−H∙∙∙O hydrogen bond between the -OH of GA and oxygen of the amide group of the ETZ molecule, and it was also found that ETZ formed a dimer through a supramolecular amide–amide homosynthon; meanwhile, the ETZ-26DHBA cocrystal was formed by a powerful supramolecular acid–amide heterosynthon, and the ETZ-24DHBA cocrystal formed the O−H∙∙∙O hydrogen bond between the 4-hydroxy group of 24DHBA and oxygen of the amide group of the ETZ molecule. It could be seen that in the molecular structure analysis of the three cocrystals, the position and number of hydroxyl groups in the coformers play an essential role in guiding the formation of specific supramolecular synthons. Full article

(This article belongs to the Special Issue Computational Studies of Drugs and Biomolecules)

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15 pages, 3815 KiB

Open AccessArticle

The Discovery of Potent SHP2 Inhibitors with Anti-Proliferative Activity in Breast Cancer Cell Lines

by Rose Ghemrawi, Mostafa Khair, Shaima Hasan, Raghad Aldulaymi, Shaikha S. AlNeyadi, Noor Atatreh and Mohammad A. Ghattas

Int. J. Mol. Sci. 2022, 23(8), 4468; https://doi.org/10.3390/ijms23084468 - 18 Apr 2022

Cited by 1 | Viewed by 3911

Abstract

Despite available treatments, breast cancer is the leading cause of cancer-related death. Knowing that the tyrosine phosphatase SHP2 is a regulator in tumorigenesis, developing inhibitors of SHP2 in breast cells is crucial. Our study investigated the effects of new compounds, purchased from NSC, on the phosphatase activity of SHP2 and the modulation of breast cancer cell lines’ proliferation and viability. A combined ligand-based and structure-based virtual screening protocol was validated, then performed, against SHP2 active site. Top ranked compounds were tested via SHP2 enzymatic assay, followed by measuring IC50 values. Subsequently, hits were tested for their anti-breast cancer viability and proliferative activity. Our experiments identified three compounds 13030, 24198, and 57774 as SHP2 inhibitors, with IC50 values in micromolar levels and considerable selectivity over the analogous enzyme SHP1. Long MD simulations of 500 ns showed a very promising binding mode in the SHP2 catalytic pocket. Furthermore, these compounds significantly reduced MCF-7 breast cancer cells’ proliferation and viability. Interestingly, two of our hits can have acridine or phenoxazine cyclic system known to intercalate in ds DNA. Therefore, our novel approach led to the discovery of SHP2 inhibitors, which could act as a starting point in the future for clinically useful anticancer agents. Full article

(This article belongs to the Special Issue Computational Studies of Drugs and Biomolecules)

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Review

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22 pages, 579 KiB

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Molecular Biosimilarity—An AI-Driven Paradigm Shift

by Sarfaraz K. Niazi

Int. J. Mol. Sci. 2022, 23(18), 10690; https://doi.org/10.3390/ijms231810690 - 14 Sep 2022

Cited by 4 | Viewed by 2930

Abstract

Scientific, technical, and bioinformatics advances have made it possible to establish analytics-based molecular biosimilarity for the approval of biosimilars. If the molecular structure is identical and other product- and process-related attributes are comparable within the testing limits, then a biosimilar candidate will have the same safety and efficacy as its reference product. Classical testing in animals and patients is much less sensitive in terms of identifying clinically meaningful differences, as is reported in the literature. The recent artificial intelligence (AI)-based protein structure prediction model, AlphaFold-2, has confirmed that the primary structure of proteins always determines their 3D structure; thus, we can deduce that a biosimilar with an identical primary structure will have the same efficacy and safety. Further confirmation of the thesis has been established using technologies that are now much more sensitive. For example, mass spectrometry (MS) is thousands of times more sensitive and accurate when compared to any form of biological testing. While regulatory agencies have begun waiving animal testing and, in some cases, clinical efficacy testing, the removal of clinical pharmacology profiling brings with it a dramatic paradigm shift, reducing development costs without compromising safety or efficacy. A list of 160+ products that are ready to enter as biosimilars has been shared. Major actions from regulatory agencies and developers are required to facilitate this paradigm shift. Full article

(This article belongs to the Special Issue Computational Studies of Drugs and Biomolecules)

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