New Perspectives on Chemoinformatics and Drug Design

A special issue of Pharmaceuticals (ISSN 1424-8247). This special issue belongs to the section "Medicinal Chemistry".

Deadline for manuscript submissions: 25 July 2024 | Viewed by 9490

Special Issue Editors


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Guest Editor
Department of Biological Sciences, State University of Southwest of Bahia, Jequié 45208-091, BA, Brazil
Interests: drug discovery; molecular dynamics; ligand screening; artificial intelligence; bioinformatics

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Guest Editor
Institute of Biological Sciences, Federal University of Minas Gerais, Belo Horizonte 31270-901, Brazil
Interests: animal health; veterinary microbiology; bacterial genetics; genomics; bioinformatics
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Department of Genetics, Ecology, and Evolution, Institute of Biological Sciences, Federal University of Minas Gerais (UFMG), Belo Horizonte 31270-901, Brazil
Interests: multiomics; bioinformatics; target discovery; targeted drug development

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Guest Editor
Department of Microbiology, Institute of Biological Sciences, Federal University of Minas Gerais, Belo Horizonte 30270-901, Brazil
Interests: bioinformatics; genomics; vaccinology; antifungals
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Traditional drug discovery and development is generally a highly time-consuming and expensive process. Over the last three decades, computational methods have been assisting the development of new chemical compounds to mitigate many diseases and issues related to human and veterinary health, using traditional molecular modeling approaches including protein homology modeling as well as lead discovery using ligand screening with large molecular databases including the structure and pharmacophore-based ligand comparisons. In addition, molecular dynamics (MD) using molecular mechanics (MM) and quantum molecular mechanics (QMM) methods coupled to PBSA and GBSA approaches has been extensively used for describing molecular interactions between small molecules and their pharmacological targets. On the other hand, the increasing number of health and environmental issues, such as new emerging infectious diseases, antimicrobial resistance, and new pharmacological targets for life-style diseases urges for a faster and more accurate response from the scientific community to provide better drug candidates against all these pathogeneses.

We invite authors to submit original research and review articles in the fields of drug discovery and cheminformatics focused on, but not restricted to:

  • Artificial intelligence (AI) methods for ligand-based virtual screening and receptor-based virtual screening, fragment-based drug development, ligand clustering and classification, drug repurposing, and structural characterization of new pharmacological protein targets;
  • Novel approaches in applied molecular dynamics for drug discovery, including the description of protein–ligand interactions, protein structure and small molecule structural elucidation, metadynamics, and accelerating molecular dynamic methods applied in drug interactions;
  • Drug repurposing methods using cheminformatics approaches;
  • Novel drugs against antibiotic resistance;
  • Novel drug design and reverse vaccinology against emerging infectious diseases;
  • Peptidomics-, nano-chemoinformatics-, and immunoinformatics-based drug discovery;
  • Tools and databases for drug design and cheminformatics.

We especially encourage authors from the Global South (countries from Latin America, Africa, Asia, Oceania, and developing countries) to showcase their research, innovations, and contribution in this field. 

All accepted manuscripts will be published as a Special Issue in Pharmaceuticals, allowing the scientific community to have a wide view of new approaches in computational chemistry and drug development.

Dr. Bruno Silva Andrade
Dr. Vasco Azevedo
Dr. Debmalya Barh
Dr. Aristóteles Góes-Neto
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. Pharmaceuticals is an international peer-reviewed open access monthly 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 2900 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

  • drug discovery
  • cheminformatics
  • artificial intelligence
  • drug repurposing
  • ligand screening
  • molecular dynamics
  • computational methods
  • emerging viruses
  • antibiotics
  • reverse vaccinology

Published Papers (4 papers)

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Research

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16 pages, 4248 KiB  
Article
Evaluating Known Zika Virus NS2B-NS3 Protease Inhibitor Scaffolds via In Silico Screening and Biochemical Assays
by Lucianna H. Santos, Rafael E. O. Rocha, Diego L. Dias, Beatriz M. R. M. Ribeiro, Mateus Sá M. Serafim, Jônatas S. Abrahão and Rafaela S. Ferreira
Pharmaceuticals 2023, 16(9), 1319; https://doi.org/10.3390/ph16091319 - 19 Sep 2023
Viewed by 1206
Abstract
The NS2B-NS3 protease (NS2B-NS3pro) is regarded as an interesting molecular target for drug design, discovery, and development because of its essential role in the Zika virus (ZIKV) cycle. Although no NS2B-NS3pro inhibitors have reached clinical trials, the employment of drug-like scaffolds can facilitate [...] Read more.
The NS2B-NS3 protease (NS2B-NS3pro) is regarded as an interesting molecular target for drug design, discovery, and development because of its essential role in the Zika virus (ZIKV) cycle. Although no NS2B-NS3pro inhibitors have reached clinical trials, the employment of drug-like scaffolds can facilitate the screening process for new compounds. In this study, we performed a combination of ligand-based and structure-based in silico methods targeting two known non-peptide small-molecule scaffolds with micromolar inhibitory activity against ZIKV NS2B-NS3pro by a virtual screening (VS) of promising compounds. Based on these two scaffolds, we selected 13 compounds from an initial library of 509 compounds from ZINC15’s similarity search. These compounds exhibited structural modifications that are distinct from previously known compounds yet keep pertinent features for binding. Despite promising outcomes from molecular docking and initial enzymatic assays against NS2B-NS3pro, confirmatory assays with a counter-screening enzyme revealed an artifactual inhibition of the assessed compounds. However, we report two compounds, 9 and 11, that exhibited antiviral properties at a concentration of 50 μM in cellular-based assays. Overall, this study provides valuable insights into the ongoing research on anti-ZIKV compounds to facilitate and improve the development of new inhibitors. Full article
(This article belongs to the Special Issue New Perspectives on Chemoinformatics and Drug Design)
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20 pages, 2379 KiB  
Article
Molecular Multi-Target Approach for Human Acetylcholinesterase, Butyrylcholinesterase and β-Secretase 1: Next Generation for Alzheimer’s Disease Treatment
by Géssica Oliveira Mendes, Samuel Silva da Rocha Pita, Paulo Batista de Carvalho, Michel Pires da Silva, Alex Gutterres Taranto and Franco Henrique Andrade Leite
Pharmaceuticals 2023, 16(6), 880; https://doi.org/10.3390/ph16060880 - 15 Jun 2023
Cited by 1 | Viewed by 1517
Abstract
Alzheimer’s Disease (AD) is a neurodegenerative condition characterized by progressive memory loss and other affected cognitive functions. Pharmacological therapy of AD relies on inhibitors of the enzymes acetylcholinesterase (AChE) and butyrylcholinesterase (BChE), offering only a palliative effect and being incapable of stopping or [...] Read more.
Alzheimer’s Disease (AD) is a neurodegenerative condition characterized by progressive memory loss and other affected cognitive functions. Pharmacological therapy of AD relies on inhibitors of the enzymes acetylcholinesterase (AChE) and butyrylcholinesterase (BChE), offering only a palliative effect and being incapable of stopping or reversing the neurodegenerative process. However, recent studies have shown that inhibiting the enzyme β-secretase 1 (BACE-1) may be able to stop neurodegeneration, making it a promising target. Considering these three enzymatic targets, it becomes feasible to apply computational techniques to guide the identification and planning of molecules capable of binding to all of them. After virtually screening 2119 molecules from a library, 13 hybrids were built and further screened by triple pharmacophoric model, molecular docking, and molecular dynamics (t = 200 ns). The selected hybrid G meets all stereo-electronic requirements to bind to AChE, BChE, and BACE-1 and offers a promising structure for future synthesis, enzymatic testing, and validation. Full article
(This article belongs to the Special Issue New Perspectives on Chemoinformatics and Drug Design)
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Review

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17 pages, 1275 KiB  
Review
Associations between Nutrigenomic Effects and Incidences of Microbial Resistance against Novel Antibiotics
by Mohamed A. Raslan, Sara A. Raslan, Eslam M. Shehata, Amr S. Mahmoud, Kenneth Lundstrom, Debmalya Barh, Vasco Azevedo and Nagwa A. Sabri
Pharmaceuticals 2023, 16(8), 1093; https://doi.org/10.3390/ph16081093 - 01 Aug 2023
Viewed by 1393
Abstract
Nutrigenomics is the study of the impact of diets or nutrients on gene expression and phenotypes using high-throughput technologies such as transcriptomics, proteomics, metabolomics, etc. The bioactive components of diets and nutrients, as an environmental factor, transmit information through altered gene expression and [...] Read more.
Nutrigenomics is the study of the impact of diets or nutrients on gene expression and phenotypes using high-throughput technologies such as transcriptomics, proteomics, metabolomics, etc. The bioactive components of diets and nutrients, as an environmental factor, transmit information through altered gene expression and hence the overall function and traits of the organism. Dietary components and nutrients not only serve as a source of energy but also, through their interactions with genes, regulate gut microbiome composition, the production of metabolites, various biological processes, and finally, health and disease. Antimicrobial resistance in pathogenic and probiotic microorganisms has emerged as a major public health concern due to the presence of antimicrobial resistance genes in various food products. Recent evidence suggests a correlation between the regulation of genes and two-component and other signaling systems that drive antibiotic resistance in response to diets and nutrients. Therefore, diets and nutrients may be alternatively used to overcome antibiotic resistance against novel antibiotics. However, little progress has been made in this direction. In this review, we discuss the possible implementations of nutrigenomics in antibiotic resistance against novel antibiotics. Full article
(This article belongs to the Special Issue New Perspectives on Chemoinformatics and Drug Design)
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18 pages, 2663 KiB  
Review
Advances in the Applications of Bioinformatics and Chemoinformatics
by Mohamed A. Raslan, Sara A. Raslan, Eslam M. Shehata, Amr S. Mahmoud and Nagwa A. Sabri
Pharmaceuticals 2023, 16(7), 1050; https://doi.org/10.3390/ph16071050 - 24 Jul 2023
Cited by 7 | Viewed by 4424
Abstract
Chemoinformatics involves integrating the principles of physical chemistry with computer-based and information science methodologies, commonly referred to as “in silico techniques”, in order to address a wide range of descriptive and prescriptive chemistry issues, including applications to biology, drug discovery, and related molecular [...] Read more.
Chemoinformatics involves integrating the principles of physical chemistry with computer-based and information science methodologies, commonly referred to as “in silico techniques”, in order to address a wide range of descriptive and prescriptive chemistry issues, including applications to biology, drug discovery, and related molecular areas. On the other hand, the incorporation of machine learning has been considered of high importance in the field of drug design, enabling the extraction of chemical data from enormous compound databases to develop drugs endowed with significant biological features. The present review discusses the field of cheminformatics and proposes the use of virtual chemical libraries in virtual screening methods to increase the probability of discovering novel hit chemicals. The virtual libraries address the need to increase the quality of the compounds as well as discover promising ones. On the other hand, various applications of bioinformatics in disease classification, diagnosis, and identification of multidrug-resistant organisms were discussed. The use of ensemble models and brute-force feature selection methodology has resulted in high accuracy rates for heart disease and COVID-19 diagnosis, along with the role of special formulations for targeting meningitis and Alzheimer’s disease. Additionally, the correlation between genomic variations and disease states such as obesity and chronic progressive external ophthalmoplegia, the investigation of the antibacterial activity of pyrazole and benzimidazole-based compounds against resistant microorganisms, and its applications in chemoinformatics for the prediction of drug properties and toxicity—all the previously mentioned—were presented in the current review. Full article
(This article belongs to the Special Issue New Perspectives on Chemoinformatics and Drug Design)
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