scholarly journals Computational Approaches: Drug Discovery and Design in Medicinal Chemistry and Bioinformatics

Molecules ◽  
2021 ◽  
Vol 26 (24) ◽  
pp. 7500
Author(s):  
Marco Tutone ◽  
Anna Maria Almerico
Keyword(s):  
Drug Discovery ◽  
Drug Design ◽  
Medicinal Chemistry ◽  
Computational Approaches

To date, computational approaches have been recognized as a key component in drug design and discovery workflows [...]

Experimental and Computational Approaches to Improve Binding Affinity in Chemical Biology and Drug Discovery

2020 ◽  
Vol 20 (19) ◽  
pp. 1651-1660
Author(s):  
Anuraj Nayarisseri
Keyword(s):  
Drug Discovery ◽  
Drug Design ◽  
Binding Affinity ◽  
Chemical Biology ◽  
De Novo ◽  
Structure Based Drug Design ◽  
Computational Approaches ◽  
Drug Designing ◽  
Traditional Drug ◽  
Computer Based

Drug discovery is one of the most complicated processes and establishment of a single drug may require multidisciplinary attempts to design efficient and commercially viable drugs. The main purpose of drug design is to identify a chemical compound or inhibitor that can bind to an active site of a specific cavity on a target protein. The traditional drug design methods involved various experimental based approaches including random screening of chemicals found in nature or can be synthesized directly in chemical laboratories. Except for the long cycle design and time, high cost is also the major issue of concern. Modernized computer-based algorithm including structure-based drug design has accelerated the drug design and discovery process adequately. Surprisingly from the past decade remarkable progress has been made concerned with all area of drug design and discovery. CADD (Computer Aided Drug Designing) based tools shorten the conventional cycle size and also generate chemically more stable and worthy compounds and hence reduce the drug discovery cost. This special edition of editorial comprises the combination of seven research and review articles set emphasis especially on the computational approaches along with the experimental approaches using a chemical synthesizing for the binding affinity in chemical biology and discovery as a salient used in de-novo drug designing. This set of articles exfoliates the role that systems biology and the evaluation of ligand affinity in drug design and discovery for the future.

Analogue-based drug discovery: Contributions to medicinal chemistry principles and drug design strategies. Microtubule stabilizers as a case in point (Special Topic Article)

2012 ◽  
Vol 84 (7) ◽  
pp. 1479-1542 ◽  
Author(s):  
Mohammad H. El-Dakdouki ◽  
Paul W. Erhardt
Keyword(s):  
Drug Discovery ◽  
Drug Design ◽  
Medicinal Chemistry ◽  
Drug Distribution ◽  
Therapeutic Agents ◽  
Special Topic ◽  
Design Strategies ◽  
Basic Principles ◽  
Research Activities ◽  
Alternative Drug

The benefits of utilizing marketed drugs as starting points to discover new therapeutic agents have been well documented within the IUPAC series of books that bear the title Analogue-based Drug Discovery (ABDD). Not as clearly demonstrated, however, is that ABDD also contributes to the elaboration of new basic principles and alternative drug design strategies that are useful to the field of medicinal chemistry in general. After reviewing the ABDD programs that have evolved around the area of microtubule-stabilizing chemo-therapeutic agents, the present article delineates the associated research activities that additionally contributed to general strategies that can be useful for prodrug design, identifying pharmacophores, circumventing multidrug resistance (MDR), and achieving targeted drug distribution.

scholarly journals Recent advances in synthetic approaches for medicinal chemistry of C-nucleosides

2018 ◽  
Vol 14 ◽  
pp. 772-785 ◽  
Author(s):  
Kartik Temburnikar ◽  
Katherine L Seley-Radtke
Keyword(s):  
Drug Discovery ◽  
Drug Design ◽  
Nucleophilic Substitution ◽  
Medicinal Chemistry ◽  
Structural Diversity ◽  
Synthetic Analogues ◽  
Structural Modifications ◽  
Modular Synthesis ◽  
Recent Advances ◽  
Synthetic Approaches

C-nucleosides have intrigued biologists and medicinal chemists since their discovery in 1950's. In that regard, C-nucleosides and their synthetic analogues have resulted in promising leads in drug design. Concurrently, advances in chemical syntheses have contributed to structural diversity and drug discovery efforts. Convergent and modular approaches to synthesis have garnered much attention in this regard. Among them nucleophilic substitution at C1' has seen wide applications providing flexibility in synthesis, good yields, the ability to maneuver stereochemistry as well as to incorporate structural modifications. In this review, we describe recent reports on the modular synthesis of C-nucleosides with a focus on D-ribonolactone and sugar modifications that have resulted in potent lead molecules.

AutoLinker: Automatic Fragment Linking with Deep Conditional Transformer Neural Networks

2020 ◽  
Author(s):  
Yuyao Yang ◽  
Shuangjia Zheng ◽  
Shimin Su ◽  
Jun Xu ◽  
Hongming Chen
Keyword(s):  
Neural Networks ◽  
Drug Discovery ◽  
Drug Design ◽  
State Of The Art ◽  
The State ◽  
Generative Model ◽  
Lead Optimization ◽  
Scaffold Hopping ◽  
Reference Models ◽  
Lead Generation

Fragment based drug design represents a promising drug discovery paradigm complimentary to the traditional HTS based lead generation strategy. How to link fragment structures to increase compound affinity is remaining a challenge task in this paradigm. Hereby a novel deep generative model (AutoLinker) for linking fragments is developed with the potential for applying in the fragment-based lead generation scenario. The state-of-the-art transformer architecture was employed to learn the linker grammar and generate novel linker. Our results show that, given starting fragments and user customized linker constraints, our AutoLinker model can design abundant drug-like molecules fulfilling these constraints and its performance was superior to other reference models. Moreover, several examples were showcased that AutoLinker can be useful tools for carrying out drug design tasks such as fragment linking, lead optimization and scaffold hopping.

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