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Swarm Intelligence and Evolutionary Algorithms for Drug Design and Development
Published in Sandeep Kumar, Anand Nayyar, Anand Paul, Swarm Intelligence and Evolutionary Algorithms in Healthcare and Drug Development, 2019
Drug design, also termed as the general drug design, is a research methodology of finding new medications based upon the knowledge of the biology targets [1]. The drugs or medications are nothing but the organic small molecules that activate or inhibit the function of a biomolecule-like protein which results in a therapeutic benefit to the patient [2,3]. The procedure of drug design is about designing the molecules which are complementary in both the shape and charge to the bimolecular target which they would interact as well as bind with. The drug design process majorly, but not necessarily, depends upon the computer modelling techniques [4]. This style of modelling is otherwise known as computer-aided drug design. On the other hand, the drug designing process lying over the knowledge of three-dimensional structure of the biomolecular target is known as the “structure-based drug design” [5].
Pharmaceuticals: Some General Aspects
Published in Peter Grunwald, Pharmaceutical Biocatalysis, 2019
Concerning future prospects of enzyme inhibitors as drugs, there is a never-ending need to develop safe, efficient, and affordable new treatment strategies as alternatives to existing ones. These efforts will be supported by using in vitro systems and in silico models to understand pharmacogenetic causes of variability in drug disposition (Brian et al., 2016). Another important aspect is the further improvement of existing structure-based or ligand-based methods and tools of computer-aided drug design and discovery which increases the hit rate of novel drug compounds due to using a much more targeted search than traditional HTS and combinatorial chemistry (Sliwoski et al., 2014). Furthermore, one of the core areas in drug development should be the neglected diseases The Drugs for Neglected Diseases initiative (DNDi) is a drug research and development (R&D) organization that is developing new treatments for neglected patients.
Drug Discovery: From Hits to Clinical Candidates
Published in Divya Vohora, The Third Histamine Receptor, 2008
Sylvain Celanire, Florence Lebon, Holger Stark
The exponential patent application filings and public disclosures of widely diverse chemical series demonstrated the ability of medicinal chemists to identify key features for high-affinity ligands and transformed their creativity into innovative compounds. Such work has been gratefully supported by computer-aided drug design activities. The different in silico approaches described earlier highlighted the combined efforts of computational chemists and biologists to study the ligand-receptor interactions. Recent QSAR studies around Abbott’s arylbenzofuran series [300] as well as refined 3-D pharmacophore ligand-based design strategies from Hoffman-La Roche [301] successfully afford a complementary approach in the early drug discovery phase. Large HTS campaign is the most common starting point for a medicinal chemical strategy. Interestingly, Acadia Pharmaceuticals recently developed a proprietary receptor selection and amplification technology (R-SAT) proliferation assay to measure antagonism and inverse agonism activities [302]. Screening over 250,000 small molecules led to the identification of 15 distinct nonimidazole chemical classes with nanomolar to subnanomolar potency compounds. One of their leads, namely AC-381, showed efficacy in a rat-feeding model.
Lessons learned from the discovery of sodium valproate and what has this meant to future drug discovery efforts?
Published in Expert Opinion on Drug Discovery, 2020
Slobodan M. Janković, Snežana V. Janković
There are several modern techniques that may improve and accelerate drug development, as computer-aided drug design (creation of new molecules ‘in silico’ through the combination of atoms and calculation of possible intramolecular binding energies, graphical representation of the calculated molecules and evaluation of potential interactions with receptor of interest), computer-aided simulations of behavior of a molecule when interacting with various receptors and enzymes, calculations of availability of a free drug in various cellular compartments and use of robotic synthesis and combinatorial chemistry (parallel synthesis of a large number of compounds through all possible combinations of molecular building blocks). However, all these new methods are not helpful if not guided by an experienced clinician-researcher who has an overview of both the unmet needs of patients within the therapeutic area of interest, and feasibility of synthesizing new molecular entities or modifying the existing ones.
Discovery of human autophagy initiation kinase ULK1 inhibitors by multi-directional in silico screening strategies
Published in Journal of Receptors and Signal Transduction, 2019
Poornimaa Mu, Ramanathan Karuppasamy
Currently, computer-aided drug design (CADD) was being extensively used as a rational approach for designing novel drug candidates [11]. In comparison with traditional experimental methods, in silico based virtual screening (VS) and molecular dynamics (MD) simulations were found to be cost-effective and time-saving [12]. For instance, ligand and structure-based virtual screening are one of the quick and powerful assimilation processes [13]. Additionally, molecular docking, a structure-based virtual screening procedure aids to find the ligands position and conformation within the active site of the target protein also a widely used VS procedure [14,15]. In recent times, the integration of both ligand-based and structure-based virtual screening methods was found to be an effective hit identification method [16–18]. Furthermore, molecular dynamic simulation provides detailed information about the interaction of the protein–ligand complex to calculate and analyze each atom’s behavior with respect to the time scale [19]. Thus, the present study attempts to identify the repurposed candidate for ULK1 inhibition by integrating all the above approaches. We believe that this study is of immense importance for the experimental biologist to design next generation cancer therapeutics.
Target-based drug discovery through inversion of quantitative structure-drug-property relationships and molecular simulation: CA IX-sulphonamide complexes
Published in Journal of Enzyme Inhibition and Medicinal Chemistry, 2018
Petar Žuvela, J. Jay Liu, Myunggi Yi, Paweł P. Pomastowski, Gulyaim Sagandykova, Mariusz Belka, Jonathan David, Tomasz Bączek, Krzysztof Szafrański, Beata Żołnowska, Jarosław Sławiński, Claudiu T. Supuran, Ming Wah Wong, Bogusław Buszewski
Computational drug design tools include computer-aided drug design and discovery (CADD), ligand- and structure-based methods (incl. molecular docking, pharmacophore modelling), and afore-mentioned VLS. Structure- and ligand-based approaches greatly differ with respect to the information used for modelling. On top of that, 3 D structure of the target is not always known or troublesome to crystallise6. Molecular docking7 is a traditional method used in CADD in which the preferred orientation of a small molecule corresponding to its binding mode is optimised with respect to the target of interest resulting in formation of a stable complex. Docking algorithms can be applied for the search of potential ligands from a library, modelling of binding mode and affinity of candidate or known ligands8. In spite of efficiency of docking methods, pharmacophore modelling is used more frequently and generally requires less time9, although pharmacophore identification can on occasion arise from a docking study. It is also more precise than the traditional ligand-based approach8. However, protein flexibility is being recognised as of fundamental importance for wider applicability of docking methods and analysis of ligand-induced changes in protein binding sites. Simple molecular dynamics can be introduced for validation of structures obtained through molecular docking.