scholarly journals Drugging Fuzzy Complexes in Transcription

2021 ◽  
Vol 8 ◽  
Author(s):  
Bonnie G. Su ◽  
Matthew J. Henley
Keyword(s):  
Transcription Factor ◽  
Transcription Factors ◽  
Drug Discovery ◽  
Drug Design ◽  
Drug Targets ◽  
Chemical Biology ◽  
Intrinsic Disorder ◽  
High Degree ◽  
Screening Approaches

Transcription factors (TFs) are one of the most promising but underutilized classes of drug targets. The high degree of intrinsic disorder in both the structure and the interactions (i.e., “fuzziness”) of TFs is one of the most important challenges to be addressed in this context. Here, we discuss the impacts of fuzziness on transcription factor drug discovery, describing how disorder poses fundamental problems to the typical drug design, and screening approaches used for other classes of proteins such as receptors or enzymes. We then speculate on ways modern biophysical and chemical biology approaches could synergize to overcome many of these challenges by directly addressing the challenges imposed by TF disorder and fuzziness.

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.

scholarly journals Advances toward structure-based drug discovery for inflammasome targets

2021 ◽  
Vol 219 (1) ◽  
Author(s):  
Li Wang ◽  
Michael A. Crackower ◽  
Hao Wu
Keyword(s):  
Drug Discovery ◽  
High Resolution ◽  
Drug Design ◽  
Structural Biology ◽  
Drug Targets ◽  
Unmet Need ◽  
Structure Based Drug Design ◽  
Important Family ◽  
Recent Advances

Inflammasome proteins play an important role in many diseases of high unmet need, making them attractive drug targets. However, drug discovery for inflammasome proteins has been challenging in part due to the difficulty in solving high-resolution structures using cryo-EM or crystallography. Recent advances in the structural biology of NLRP3 and NLRP1 have provided the first set of data that proves a promise for structure-based drug design for this important family of targets.

Zika virus drug targets: a missing link in drug design and discovery – a route map to fill the gap

RSC Advances ◽  
2016 ◽  
Vol 6 (73) ◽  
pp. 68719-68731 ◽  
Author(s):  
Pritika Ramharack ◽  
Mahmoud E. S. Soliman
Keyword(s):  
Drug Discovery ◽  
Drug Design ◽  
Viral Replication ◽  
Zika Virus ◽  
In Silico ◽  
Drug Targets ◽  
Missing Link ◽  
Potential Inhibitors

This review depicts anin silicoroute map for ZIKV drug discovery, thus revealing novel potential inhibitors of viral replication.

An in silico structure-based approach to anti-infective drug discovery

Parasitology ◽  
2013 ◽  
Vol 141 (1) ◽  
pp. 17-27 ◽  
Author(s):  
FRASER CUNNINGHAM ◽  
MARTIN J. McPHILLIE ◽  
A. PETER JOHNSON ◽  
COLIN W. G. FISHWICK
Keyword(s):  
Drug Discovery ◽  
In Silico ◽  
High Throughput Screening ◽  
Drug Targets ◽  
Enzyme Inhibitors ◽  
Cell Activity ◽  
Structure Based Drug Design ◽  
Lead Compounds ◽  
Target Mode ◽  
Screening Approaches

SUMMARYIn light of the low success rate of target-based genomics and HTS (High Throughput Screening) approaches in anti-infective drug discovery, in silico structure-based drug design (SBDD) is becoming increasingly prominent at the forefront of drug discovery. In silico SBDD can be used to identify novel enzyme inhibitors rapidly, where the strength of this approach lies with its ability to model and predict the outcome of protein-ligand binding. Over the past 10 years, our group have applied this approach to a diverse number of anti-infective drug targets ranging from bacterial D-ala-D-ala ligase to Plasmodium falciparum DHODH. Our search for new inhibitors has produced lead compounds with both enzyme and whole-cell activity with established on-target mode of action. This has been achieved with greater speed and efficiency compared with the more traditional HTS initiatives and at significantly reduced cost and manpower.

scholarly journals An Updated Review of Computer-Aided Drug Design and Its Application to COVID-19

2021 ◽  
Vol 2021 ◽  
pp. 1-18
Author(s):  
Arun Bahadur Gurung ◽  
Mohammad Ajmal Ali ◽  
Joongku Lee ◽  
Mohammad Abul Farah ◽  
Khalid Mashay Al-Anazi
Keyword(s):  
Drug Discovery ◽  
Drug Design ◽  
Drug Targets ◽  
Pharmacophore Modeling ◽  
Review Article ◽  
Drug Candidate ◽  
Computational Techniques ◽  
Computer Aided Drug Design ◽  
Structure Based Drug Design ◽  
Computer Aided

The recent outbreak of the deadly coronavirus disease 19 (COVID-19) pandemic poses serious health concerns around the world. The lack of approved drugs or vaccines continues to be a challenge and further necessitates the discovery of new therapeutic molecules. Computer-aided drug design has helped to expedite the drug discovery and development process by minimizing the cost and time. In this review article, we highlight two important categories of computer-aided drug design (CADD), viz., the ligand-based as well as structured-based drug discovery. Various molecular modeling techniques involved in structure-based drug design are molecular docking and molecular dynamic simulation, whereas ligand-based drug design includes pharmacophore modeling, quantitative structure-activity relationship (QSARs), and artificial intelligence (AI). We have briefly discussed the significance of computer-aided drug design in the context of COVID-19 and how the researchers continue to rely on these computational techniques in the rapid identification of promising drug candidate molecules against various drug targets implicated in the pathogenesis of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The structural elucidation of pharmacological drug targets and the discovery of preclinical drug candidate molecules have accelerated both structure-based as well as ligand-based drug design. This review article will help the clinicians and researchers to exploit the immense potential of computer-aided drug design in designing and identification of drug molecules and thereby helping in the management of fatal disease.

scholarly journals Concepts and Core Principles of Fragment-Based Drug Design

Molecules ◽  
2019 ◽  
Vol 24 (23) ◽  
pp. 4309 ◽  
Author(s):  
Philine Kirsch ◽  
Alwin M. Hartman ◽  
Anna K. H. Hirsch ◽  
Martin Empting
Keyword(s):  
Drug Discovery ◽  
Drug Design ◽  
Drug Targets ◽  
Enzyme Inhibitor ◽  
Evaluation Methods ◽  
Inhibitor Design ◽  
General Introduction ◽  
Library Selection ◽  
Fragment Based Drug Discovery

In this review, a general introduction to fragment-based drug design and the underlying concepts is given. General considerations and methodologies ranging from library selection/construction over biophysical screening and evaluation methods to in-depth hit qualification and subsequent optimization strategies are discussed. These principles can be generally applied to most classes of drug targets. The examples given for fragment growing, merging, and linking strategies at the end of the review are set in the fields of enzyme-inhibitor design and macromolecule–macromolecule interaction inhibition. Building upon the foundation of fragment-based drug discovery (FBDD) and its methodologies, we also highlight a few new trends in FBDD.

scholarly journals Abstract P-25: High-Resolution Cryo-Electron Microscopy Structure of the Staphylococcus Aureus Ribosome Brings to Light New Possible Drug Targets

2021 ◽  
Vol 11 (Suppl_1) ◽  
pp. S22-S23
Author(s):  
Alexander Golubev ◽  
Bulat Fatkhullin ◽  
Iskander Khusainov ◽  
Shamil Validov ◽  
Marat Yusupov ◽  
...  
Keyword(s):  
Staphylococcus Aureus ◽  
Protein Synthesis ◽  
Drug Discovery ◽  
Drug Design ◽  
Messenger Rna ◽  
Drug Targets ◽  
Structural Data ◽  
New Drugs ◽  
Fine Tuning ◽  
Structure Based Drug Design

Background: Antibiotic resistance is a growing worldwide problem. One of the major resistant bacterial pathogens is Staphylococcus aureus, which became a burden of healthcare systems around the world. To overcome the issue, more drug discovery studies are needed. One of the main antibiotic targets is a ribosome – the central hub of protein synthesis. Structural data of the ribosome and its features are a crucial milestone for the effective development of new drugs, especially using structure-based drug design approaches. Apart from many small structural features, ribosome possesses rRNA modifications that play a role in the fine-tuning of protein synthesis. Detailed species-specific structural data of the S. aureus ribosome is also a useful model for understanding the resistance mechanisms. This information could help with the design of new antibiotics and the upgrading of old ones. The data on S. aureus ribosomal RNA modifications and corresponding modification enzymes are very limited. Our aim was to improve the current models of the S. aureus ribosome by determining its structure with functional ligands at a much higher resolution - thereby creating a foundation for structure-based drug design experiments and research of new drug targets. Methods: The S. aureus ribosome complex consists of three components: ribosome, fMet-tRNAfMet, mRNA and 70S ribosome. The complex from purified components was formed in vitro and applied to cryo-EM grids. Data was collected at Titan Krios with Gatan K2 detector (IGBMC, France). The data was processed and modeled in Relion 2.1, Chimera, Coot, and Phenix. Results: We determined the cryo-EM reconstruction at 3.2 Å resolution of the S. aureus ribosome with P-site tRNA, messenger RNA. Based on the experimental map and existing bioinformatic data, we at the first time identified and assigned 10 modifications of S. aureus rRNA. We analyzed the positions of rRNA modifications and their possible functions. Conclusion: In this study, we describe our structure of S. aureus ribosome with functional ligands. The present model is the highest resolution and most precise that is available at the moment. We propose a set of methyltransferases as targets for future drug discovery studies. The proposed methyltransferases and corresponding modifications may play an important role in protein synthesis and its regulation.

Combating Diseases with Computational Strategies Used for Drug Design and Discovery

2019 ◽  
Vol 18 (32) ◽  
pp. 2743-2773 ◽  
Author(s):  
Farahnaz R. Makhouri ◽  
Jahan B. Ghasemi
Keyword(s):  
Drug Discovery ◽  
Drug Design ◽  
Computational Methods ◽  
Drug Targets ◽  
Structural Information ◽  
Target Identification ◽  
Lead Discovery ◽  
Human Proteins ◽  
Almost All ◽  
Discovery Pipeline

Computer-aided drug discovery (CADD) tools have provided an effective way in the drug discovery pipeline for expediting of this long process and economizing the cost of research and development. Due to the dramatic increase in the availability of human proteins as drug targets and small molecule information due to the advances in bioinformatics, cheminformatics, genomics, proteomics, and structural information, the applicability of in silico drug discovery has been extended. Computational approaches have been used at almost all stages in the drug discovery pipeline including target identification and validation, lead discovery and optimization, and pharmacokinetic and toxicity profiles prediction. As each area covers a variety of computational methods, it is unmanageable to assess comprehensively all areas of CADD applications or every aspect of an area in one review article. However, in this article, we tried to present an overview of computational methods used in almost all the areas concerned with drug design and highlight some of the recent successes.

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