Ammara Riaz, A. Rasul, Iqra Sarfraz, Javaria Nawaz, A. Sadiqa, Rabia Zara, Samreen Gul Khan, Z. Selamoğlu
{"title":"Chemical Biology Toolsets for Drug Discovery and Target Identification","authors":"Ammara Riaz, A. Rasul, Iqra Sarfraz, Javaria Nawaz, A. Sadiqa, Rabia Zara, Samreen Gul Khan, Z. Selamoğlu","doi":"10.5772/intechopen.91732","DOIUrl":"https://doi.org/10.5772/intechopen.91732","url":null,"abstract":"Chemical biology is the scientific discipline that deals with the application of chemical techniques and often small molecules produced through synthetic chemistry, to the manipulation and study of biological systems. Its working framework ranges from simple chemical entities to complex drugs by employing the principles of biological origin. This chapter particularly focuses on the principles and working models of chemical biology to discover new drug leads. Drug discovery is an extensive and multifaceted complex process. Chemical biology uses both natural and synthetic compounds with the best therapeutic potential and verifies them by employing the best possible chemical toolsets. Screening of compounds is done by the use of phenotypic as well as the target-based screening to identify and characterize the potent hits. After the identification of target, it is characterized, and validated by extensive testing. The next step is the validation of hits obtained, and lead compounds are tested in clinical trials before introducing them for commercial application.","PeriodicalId":203376,"journal":{"name":"Cheminformatics and its Applications","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125414344","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Cell-Penetrating Peptides: A Challenge for Drug Delivery","authors":"Sonia Aroui, A. Kénani","doi":"10.5772/intechopen.91684","DOIUrl":"https://doi.org/10.5772/intechopen.91684","url":null,"abstract":"Cell-penetrating peptide (CPP) is a term that describes relatively short amphipathic and cationic peptides (7–30 amino acid residues) with rapid translocation across the cell membrane. They can be used to deliver molecular bioactive cargoes due to their efficacy in cellular internalization and also to their low cytotoxicity. In this review we provide an overview of the current approaches and describe the potential of CPP-based drug delivery systems and indicate their powerful promise for clinical efficacy.","PeriodicalId":203376,"journal":{"name":"Cheminformatics and its Applications","volume":"255 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115866148","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Visible Evolution from Primitive Organisms to Homo sapiens","authors":"K. Sorimachi","doi":"10.5772/INTECHOPEN.91170","DOIUrl":"https://doi.org/10.5772/INTECHOPEN.91170","url":null,"abstract":"The ratios of amino acids to the total amino acids deduced from the complete genome and those of nucleotides to the total nucleotides in the genome are useful indexes to characterize various large genomes among different species from bacteria to Homo sapiens . These indexes are not only independent of species but also of genome size. Using these indexes, the following results were obtained: (1) primitive life forms appeared to have similar amino acid compositions to present day organisms; (2) cellular amino acid compositions that are similar among various species and between whole cells and complete genomes; (3) genome structure that is homogeneously constructed from putative small units encoding proteins of similar amino acid compositions, followed by synchronous mutations over the genome; (4) all organisms can be classified into two groups, “GC-rich” and “AT-rich,” based on their nucleotide contents, or “terrestrial” and “aquatic vertebrates” based on natural selection by cluster analyses using amino acid contents as the traits; and (5) evolution based on nucleotide content alterations can be expressed by definitive equations. Thus, the ratios of amino acids or nucleotides to their total contents are useful indexes for characterizing genomes, regardless of species differences and genome sizes. The two normalized nucleotide contents are universally expressed regression line.","PeriodicalId":203376,"journal":{"name":"Cheminformatics and its Applications","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130462120","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Accelerating Chemical Tool Discovery by Academic Collaborative Models","authors":"Bahne Stechmann, W. Fecke","doi":"10.5772/intechopen.91138","DOIUrl":"https://doi.org/10.5772/intechopen.91138","url":null,"abstract":"The development of chemical tool compounds becomes increasingly important for chemical biology research projects in many disciplines of life sciences. In addition, they form essential parts in both academic and industrial drug discovery efforts. The required expertise and technology platforms for the identification and optimization of these potent and target-selective small molecules often exceed the capabilities of academic groups and smaller companies. Over the years, several initiatives were created all over the world which address this issue by either creating networks or consortia of academic institutes, public-private partnerships with industry, or even dedicated new research infrastructures for chemical biology. Several of these organizations and their different access models will be described. We will focus in particular on the model of EU-OPENSCREEN ERIC, a new European Research Infrastructure which was founded in 2018 and consists of more than 20 partner institutes from eight countries.","PeriodicalId":203376,"journal":{"name":"Cheminformatics and its Applications","volume":"87 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131509560","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
M. A. Santos, L. F. S. D. Oliveira, A. Figueiredo, Fábio dos Santos Gil, Márcio de Souza Farias, H. Bitencourt, J. R. Lobato, Raimundo Dirceu de P. Farreira, S. S. Alves, Edilson Luiz C. de Aquino, José Ciríaco-Pinheiro
{"title":"Molecular Electrostatic Potential and Chemometric Techniques as Tools to Design Bioactive Compounds","authors":"M. A. Santos, L. F. S. D. Oliveira, A. Figueiredo, Fábio dos Santos Gil, Márcio de Souza Farias, H. Bitencourt, J. R. Lobato, Raimundo Dirceu de P. Farreira, S. S. Alves, Edilson Luiz C. de Aquino, José Ciríaco-Pinheiro","doi":"10.5772/intechopen.89113","DOIUrl":"https://doi.org/10.5772/intechopen.89113","url":null,"abstract":"In this chapter, firstly, we briefly review aspects of the approximation of quantum chemistry, molecular electrostatic potential (MEP), and chemometrics techniques, which are accredited as important tools in the development of chemical science and are frequently used in the study and design of bioactive compounds. Ultimately, we use MEP and pattern recognition (PR) techniques as tools to design nitrofuran compounds with biological activity against Trypanosoma cruzi ( T. cruzi ). PR models (PCA, HCA, KNN, SDA, and SIMCA) were constructed and demonstrated that 23 nitrofurans can be classified into two classes or groups: more active and less active according to their degrees of activity against T. cruzi . Properties such as charge on the N atom of the nitro group (QN1); the difference between the highest occupied molecular orbital (HOMO) energy and the lowest unoccupied molecular orbital (LUMO) energy (GAP energy); molecular representation of structure based on electron diffraction code of signal 5, unweighted (Mor05u); and Moriguchi water–octanol partition coefficient (MlogP) are responsible for the classification into more active and less active studied nitrofurans. It is interesting to notice that these properties represent three distinct classes of interactions between the nitrofurans and the biological receptor: electronic (QN1 and GAP energy), steric (Mor05u), and hydrophobic (MlogP). The results of the application of PR models on the validation set evidenced two nitrofuran compounds (compounds 25 and 30 ) as more promising for synthesis and biological assays, which in the future can be used to validate our PR models.","PeriodicalId":203376,"journal":{"name":"Cheminformatics and its Applications","volume":"82 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116228294","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Artificial Intelligence-Based Drug Design and Discovery","authors":"Y. Lo, Gui Ren, H. Honda, K. Davis","doi":"10.5772/intechopen.89012","DOIUrl":"https://doi.org/10.5772/intechopen.89012","url":null,"abstract":"The drug discovery process from hit-to-lead has been a challenging task that requires simultaneously optimizing numerous factors from maximizing compound activity, efficacy to minimizing toxicity and adverse reactions. Recently, the advance of artificial intelligence technique enables drugs to be efficiently purposed in silico prior to chemical synthesis and experimental evaluation. In this chapter, we present fundamental concepts of artificial intelligence and their application in drug design and discovery. The emphasis will be on machine learning and deep learning, which demonstrated extensive utility in many branches of computer-aided drug discovery including de novo drug design, QSAR (Quantitative Structure–Activity Relationship) analysis, drug repurposing and chemical space visualization. We will demonstrate how artificial intelligence techniques can be leveraged for developing chemoinformatics pipelines and presented with real-world case studies and practi-cal applications in drug design and discovery. Finally, we will discuss limitations and future direction to guide this rapidly evolving field.","PeriodicalId":203376,"journal":{"name":"Cheminformatics and its Applications","volume":"794 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131408438","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Semantic Similarity in Cheminformatics","authors":"J. Ferreira, Francisco M. Couto","doi":"10.5772/intechopen.89032","DOIUrl":"https://doi.org/10.5772/intechopen.89032","url":null,"abstract":"Similarity in chemistry has been applied to a variety of problems: to predict biochemical properties of molecules, to disambiguate chemical compound references in natural language, to understand the evolution of metabolic pathways, to predict drug-drug interactions, to predict therapeutic substitution of antibiotics, to estimate whether a compound is harmful, etc. While measures of similarity have been created that make use of the structural properties of the molecules, some ontologies (the Chemical Entities of Biological Interest (ChEBI) being one of the most relevant) capture chemistry knowledge in machine-readable formats and can be used to improve our notions of molecular similarity. Ontologies in the biomedical domain have been extensively used to compare entities of biological interest, a technique known as ontology-based semantic similarity. This has been applied to various bio-logically relevant entities, such as genes, proteins, diseases, and anatomical structures, as well as in the chemical domain. This chapter introduces the fundamental concepts of ontology-based semantic similarity, its application in cheminformatics, its relevance in previous studies, and future potential. It also discusses the existing challenges in this area, tracing a parallel with other domains, particularly genomics, where this technique has been used more often and for longer.","PeriodicalId":203376,"journal":{"name":"Cheminformatics and its Applications","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120959645","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Chemoinformatic Approach: The Case of Natural Products of Panama","authors":"D. Olmedo, J. Medina‐Franco","doi":"10.5772/INTECHOPEN.87779","DOIUrl":"https://doi.org/10.5772/INTECHOPEN.87779","url":null,"abstract":"Chemoinformatic analysis was used to characterize a compound database of natural products from Panama and other reference collections. Data mining allowed to compare drug-likeness properties with public and commercial software and to achieve a statistical analysis of the physicochemical properties. Visualization of the chemical space in 3D indicates a high structural similarity. Molecular flexibility and complexity were evaluated using 2D descriptors, whereas the molecular scaffold was obtained using the Murcko method, and these showed few differences between the explored data set. In this chapter, we also present and discuss an example of the application of the chemoinformatic approach using the concept of modeling the activity landscape to study the structure-activity relationships (SARs) of compounds with activity against Plasmodium falciparum.","PeriodicalId":203376,"journal":{"name":"Cheminformatics and its Applications","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128914596","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Chemical Reactivity Properties and Bioactivity Scores of the Angiotensin II Vasoconstrictor Octapeptide","authors":"N. Flores-Holguín, J. Frau, D. Glossman-Mitnik","doi":"10.5772/INTECHOPEN.86736","DOIUrl":"https://doi.org/10.5772/INTECHOPEN.86736","url":null,"abstract":"Eight density functionals, CAM-B3LYP, LC- ω PBE, M11, MN12SX, N12SX, ω B97, ω B97X, and ω B97XD, in connection with the Def2TZVP basis set were assessed together with the SMD solvation model for the calculation of the molecular and chemical reactivity properties of the angiotensin II vasoconstrictor octapeptide in the presence of water. All the chemical reactivity descriptors for the systems were calculated via conceptual density functional theory (CDFT). The potential bioavailability and druggability as well as the bioactivity scores for angiotensin II were predicted through different methodologies already reported in the literature which have been previously validated during the study of different peptidic systems.","PeriodicalId":203376,"journal":{"name":"Cheminformatics and its Applications","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121911038","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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