scholarly journals Structure-guided, target-based drug discovery – exploiting genome information from HIV to mycobacterial infections

2016 ◽  
Vol 62 (3) ◽  
pp. 262-272
Author(s):  
Sony Malhotra ◽  
Sherine E. Thomas ◽  
Bernardo Ochoa Montano ◽  
Tom L. Blundell
Keyword(s):  
Drug Discovery ◽  
Binding Sites ◽  
Target Identification ◽  
Hiv Protease ◽  
Inhibitor Binding ◽  
Mycobacterial Infections ◽  
Lead Compounds ◽  
Lead Optimisation ◽  
Genome Information ◽  
Fragment Based Drug Discovery

The use of protein crystallography in structure-guided drug discovery allows identification of potential inhibitor-binding sites and optimisation of interactions of hits and lead compounds with a target protein. An early example of this approach was the use of the structure of HIV protease in designing AIDS antivirals. More recently, use of structure-guided design with fragment-based drug discovery, which reduces the size of screening libraries by decreasing complexity, has improved ligand efficiency in drug design. Here, we discuss the use of structure-guided target identification and lead optimisation using fragment-based approaches in the development of new antimicrobials for mycobacterial infections.

Modern Paradigm Towards Potential Target Identification for Antiviral (SARS-nCoV-2) and Anticancer Lipopeptides: A Pharmacophore-Based Approach

2022 ◽  
Author(s):  
Manisha Yadav ◽  
J. Satya Eswari
Keyword(s):  
Drug Discovery ◽  
Target Identification ◽  
Target Prediction ◽  
Cost Effective ◽  
Time Saving ◽  
Web Based ◽  
Target Proteins ◽  
Lead Compounds ◽  
Potential Target ◽  
Biopharmaceutical Properties

Background: Lipopeptides are potential microbial metabolites that are abandoned with broad spectrum biopharmaceutical properties ranging from antimicrobial, antiviral and anticancer, etc. Clinical studies are not much explored beyond the experimental methods to understand drug mechanisms on target proteins at the molecular level for large molecules. Due to the less available studies on potential target proteins of lipopeptide based drugs, their potential inhibitory role for more obvious treatment on disease have not been explored in the direction of lead optimization. However, Computational approaches need to be utilized to explore drug discovery aspects on lipopeptide based drugs, which are time saving and cost-effective techniques. Methods: Here a ligand-based drug discovery approach is coupled with reverse pharmacophore-mapping for the prediction of potential targets for antiviral (SARS-nCoV-2) and anticancer lipopeptides. Web-based servers PharmMapper and Swiss Target Prediction are used for the identification of target proteins for lipopeptides surfactin and iturin produced by Bacillus subtilis. Results: The studies have given the insight to treat the diseases with next-generation large molecule therapeutics. Results also indicate the affinity for Angiotensin-Converting Enzymes (ACE) and proteases as the potential viral targets for these categories of peptide therapeutics. A target protein for the Human Papilloma Virus (HPV) has also been mapped. Conclusion: The work will further help in exploring computer-aided drug designing of novel compounds with greater efficiency where the structure of the target proteins and lead compounds are known.  

scholarly journals Crystallographic Fragment-Based Drug Discovery: Use of a Brominated Fragment Library Targeting HIV Protease

2013 ◽  
Vol 83 (2) ◽  
pp. 141-148 ◽  
Author(s):  
Theresa Tiefenbrunn ◽  
Stefano Forli ◽  
Meaghan Happer ◽  
Ana Gonzalez ◽  
Yingssu Tsai ◽  
...  
Keyword(s):  
Drug Discovery ◽  
Hiv Protease ◽  
Fragment Library ◽  
Fragment Based Drug Discovery

Fragment Dissolved Molecular Dynamics: A systematic and efficient method to locate binding sites

2020 ◽  
Author(s):  
Cristian Privat ◽  
Jose M. Granadino-Roldan ◽  
Jordi Bonet ◽  
Maria Santos Tomas ◽  
Juan Jesús Pérez ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Drug Discovery ◽  
Computational Methods ◽  
Efficient Method ◽  
Binding Sites ◽  
Protein Denaturation ◽  
Fragment Based Drug Discovery

Diverse computational methods to support Fragment-based drug discovery (FBDD) are available in the literature. Despite their demonstrated efficacy to support FBDD campaigns, they exhibit some drawbacks such as protein denaturation...

scholarly journals Rationalizing Viral Drug Target Identification Using Computational Approaches : The SARS-CoV-2 Spike Glycoprotein S Case Study

2020 ◽  
Author(s):  
Petr Popov ◽  
Pavel Buslaev ◽  
Igor Kozlovskii ◽  
Mark Zaretskii ◽  
Dmitry Karlov ◽  
...  
Keyword(s):  
Drug Discovery ◽  
Binding Site ◽  
Binding Sites ◽  
Drug Target ◽  
Conformational Transition ◽  
Target Identification ◽  
Drug Binding ◽  
Spike Glycoprotein ◽  
Important Amino Acid ◽  
Drug Target Identification

<div><div><div><p>COVID-19 emphasized the need for fast reaction tools to fight global biological threats such as viruses. Rapid drug discovery is one of the strategies for efficient social response. The success of a drug discovery campaign critically depends on the selected drug target, and the wrong target nullifies all the efforts to develop a drug. Viral drug target identification is a challenging problem, and computational methods can reduce the number of candidate targets. Here we present a structure-based approach to identify vulnerable regions in viral proteins that comprise drug binding sites. To detect promising binding sites, we take into account protein dynamics, accessibility, and mutability of the binding site, coupled with the putative mechanism of action of a drug. Applying to the SARS-CoV-2 Spike Glycoprotein S, we observed conformation- and oligomer-specific glycan-free binding site that is proximal to the receptor binding domain and comprises topologically important amino acid residues. Molecular dynamics simulations of Spike in complex with drug-like molecules docked into the binding sites revealed shifted equilibrium towards the inactive conformation compared to the ligand-free simulations. Small molecules targeting this binding site could prevent the closed-to-open conformational transition of the Spike protein, thus, allosterically inhibit the interaction with the human angiotensin-converting enzyme 2 receptor.</p></div></div></div>

Fragments: where are we now?

2020 ◽  
Vol 48 (1) ◽  
pp. 271-280 ◽  
Author(s):  
James Osborne ◽  
Stanislava Panova ◽  
Magdalini Rapti ◽  
Tatsuya Urushima ◽  
Harren Jhoti
Keyword(s):  
Drug Discovery ◽  
Drug Administration ◽  
Clinical Studies ◽  
Food And Drug Administration ◽  
Library Design ◽  
Lead Optimisation ◽  
Fragment Library ◽  
The Future ◽  
Fragment Based Drug Discovery

Fragment-based drug discovery (FBDD) has become a mainstream technology for the identification of chemical hit matter in drug discovery programs. To date, the food and drug administration has approved four drugs, and over forty compounds are in clinical studies that can trace their origins to a fragment-based screen. The challenges associated with implementing an FBDD approach are many and diverse, ranging from the library design to developing methods for identifying weak affinity compounds. In this article, we give an overview of current progress in fragment library design, fragment to lead optimisation and on the advancement in techniques used for screening. Finally, we will comment on the future opportunities and challenges in this field.

scholarly journals Rationalizing Viral Drug Target Identification Using Computational Approaches : The SARS-CoV-2 Spike Glycoprotein S Case Study

2020 ◽  
Author(s):  
Petr Popov ◽  
Pavel Buslaev ◽  
Igor Kozlovskii ◽  
Mark Zaretskii ◽  
Dmitry Karlov ◽  
...  
Keyword(s):  
Drug Discovery ◽  
Binding Site ◽  
Binding Sites ◽  
Drug Target ◽  
Conformational Transition ◽  
Target Identification ◽  
Drug Binding ◽  
Spike Glycoprotein ◽  
Important Amino Acid ◽  
Drug Target Identification

<div><div><div><p>COVID-19 emphasized the need for fast reaction tools to fight global biological threats such as viruses. Rapid drug discovery is one of the strategies for efficient social response. The success of a drug discovery campaign critically depends on the selected drug target, and the wrong target nullifies all the efforts to develop a drug. Viral drug target identification is a challenging problem, and computational methods can reduce the number of candidate targets. Here we present a structure-based approach to identify vulnerable regions in viral proteins that comprise drug binding sites. To detect promising binding sites, we take into account protein dynamics, accessibility, and mutability of the binding site, coupled with the putative mechanism of action of a drug. Applying to the SARS-CoV-2 Spike Glycoprotein S, we observed conformation- and oligomer-specific glycan-free binding site that is proximal to the receptor binding domain and comprises topologically important amino acid residues. Molecular dynamics simulations of Spike in complex with drug-like molecules docked into the binding sites revealed shifted equilibrium towards the inactive conformation compared to the ligand-free simulations. Small molecules targeting this binding site could prevent the closed-to-open conformational transition of the Spike protein, thus, allosterically inhibit the interaction with the human angiotensin-converting enzyme 2 receptor.</p></div></div></div>

Predicting the Strength of Stacking Interactions Between Heterocycles and Aromatic Amino Acid Side Chains

2019 ◽  
Author(s):  
Andrea N. Bootsma ◽  
Analise C. Doney ◽  
Steven Wheeler
Keyword(s):  
Amino Acid ◽  
Binding Sites ◽  
Aromatic Amino Acid ◽  
Aromatic Amino Acids ◽  
Biologically Active ◽  
Side Chains ◽  
Stacking Interactions ◽  
Inhibitor Binding ◽  
Protein Binding Sites ◽  
Amino Acid Side Chains

<p>Despite the ubiquity of stacking interactions between heterocycles and aromatic amino acids in biological systems, our ability to predict their strength, even qualitatively, is limited. Based on rigorous <i>ab initio</i> data, we have devised a simple predictive model of the strength of stacking interactions between heterocycles commonly found in biologically active molecules and the amino acid side chains Phe, Tyr, and Trp. This model provides rapid predictions of the stacking ability of a given heterocycle based on readily-computed heterocycle descriptors. We show that the values of these descriptors, and therefore the strength of stacking interactions with aromatic amino acid side chains, follow simple predictable trends and can be modulated by changing the number and distribution of heteroatoms within the heterocycle. This provides a simple conceptual model for understanding stacking interactions in protein binding sites and optimizing inhibitor binding in drug design.</p>

Current Approaches to Drug Discovery for Chagas Disease: Methodological Advances

2019 ◽  
Vol 22 (8) ◽  
pp. 509-520
Author(s):  
Cauê B. Scarim ◽  
Chung M. Chin
Keyword(s):  
Drug Discovery ◽  
Chagas Disease ◽  
Drug Candidates ◽  
Lead Compounds ◽  
New Drug ◽  
Compound Libraries ◽  
Screening Assays ◽  
Cruzi Infection

Background: In recent years, there has been an improvement in the in vitro and in vivo methodology for the screening of anti-chagasic compounds. Millions of compounds can now have their activity evaluated (in large compound libraries) by means of high throughput in vitro screening assays. Objective: Current approaches to drug discovery for Chagas disease. Method: This review article examines the contribution of these methodological advances in medicinal chemistry in the last four years, focusing on Trypanosoma cruzi infection, obtained from the PubMed, Web of Science, and Scopus databases. Results: Here, we have shown that the promise is increasing each year for more lead compounds for the development of a new drug against Chagas disease. Conclusion: There is increased optimism among those working with the objective to find new drug candidates for optimal treatments against Chagas disease.

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