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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.
Multi-directionally evaluating the formation mechanism of 1,4-dihydropyridine drug nanosuspensions through experimental validation and computer-aided drug design
Published in Drug Development and Industrial Pharmacy, 2021
Shijie Ma, Jueshuo Guo, Zonghua Tian, Tingting Meng, Yaping Mai, Jianhong Yang
With the continuous development of new drug research and development and pharmaceutical preparations, there are endless explorations of drug research and development methods, such as high throughput screening and computer-aided drug design. Dongfei Liu, Niloofar Heshmati Aghda, and others used high-throughput screening technology with high selectivity and high specificity to explore the formation and controlled release of nanoparticles, making the work more efficient [21–23]. Ouranidis and Medarević et al. understood the fracture mechanism and potential slip surface of nanoparticles by exploring the lattice state and mechanical properties of different drugs to show the microscopic formation mechanism of drug formulations [15,24]. Calvin Andeve Omolo et al. used the MD simulation to study the particle motion and spontaneous combination between drugs and excipients to understand their interactions [25]. Therefore, energetics stacking and computer molecular docking can be used as a virtual method to observe the microscopic state of the system. Combining it with traditional characterization methods can realize the exploration of the formation mechanism of nanosuspensions, especially the display of intermolecular forces.
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.
Supramolecular self-assembled drug delivery system (SADDs) of vancomycin and tocopherol succinate as an antibacterial agent: in vitro, in silico and in vivo evaluations
Published in Pharmaceutical Development and Technology, 2020
Mohammed Salih, Calvin A. Omolo, Nikita Devnarain, Ahmed A. Elrashedy, Chunderika Mocktar, Mahmoud E. S. Soliman, Thirumala Govender
Computer-aided drug design requires crystal structures of biomolecules to analyze molecular dynamics and inter/intramolecular interactions. Due to the lack of available crystal structures of NorA and NorB efflux pumps, we undertook homology modeling as a tool to develop models that could be used to understand the binding interactions between TS with NorA and NorB, respectively. To construct the models, the amino acid sequences for NorA and NorB from MRSA were accessed from UniProt (accession numbers P0A0J6 and Q8NWQ5, respectively) (Consortium 2018). Thereafter, the predictive 3D structures were generated using the SWISS-MODEL server (Supplementary Figures S1 and S2) (Waterhouse et al. 2018). MolProbity was used to generate a Ramachandran Plot to assess and validate modified bond angles and torsional strain (Supplementary Figure S3) (Williams et al. 2018). Results revealed that for the NorA and NorB models, 94.35% and 89.09% of the respective protein’s amino acid residues were in favored regions. This left 4 and 14 outliers, respectively, none of which constituted the protein’s active site.