Research Topic

Integration of Structural Biology Data in Lead Drug Discovery and Optimization

About this Research Topic

Most drug targets are macromolecules (i.e., proteins, nucleic acids, and their complexes). The rational design and testing of drug-lead compounds targeting specific sites on a macromolecule can be driven by a knowledge of the macromolecular target structure and of the atomic details of its interactions with small compounds. 


Traditionally, macromolecular NMR and X-ray crystallography have been the experimental structural techniques of choice for structure-based drug lead discovery, with Cryo-EM the latest addition to the same toolbox. Structural data contributes to the design and generation of initial lead compounds and to the subsequent pharmaceutical chemistry process that bridges from lead to final active pharmaceutical drug.


The advance in structural biology methodologies, computational approaches, and high-throughput methods provided researchers with a huge amount of bewildering data. The integration of such data in the drug development pipeline, in order to convert information into knowledge, has always been a non-trivial problem and constitutes one of the most exciting applications of the so-called “Integrative Structural Biology”. A good lead (and any new drug) must simultaneously satisfy multiple requirements, such as affinity, non-toxicity, as well as several crucial properties such as suitable absorption, distribution, metabolism, and excretion (ADME) profiles and synthesisability. At the same time, the molecular details of the lead-target binding are crucial to predict and rationalize most of those requirements. Traditionally, each of these objectives has been tackled using a linear approach in which successive aspects were optimized sequentially by using experimental and/or computational approaches. This Research Topic will focus on novel approaches for integration of in silico analyses and experimental structural data in workflows for the discovery of new drugs, ultimately supporting the faster and more efficient delivery of drugs to the market.


This Research Topic accepts Original Research articles, Perspectives, and Reviews. Topics of interest include, but are not limited to, the following:


• Integrative Software Platforms for in-silico Multi-Objective Optimised Drug Discovery.


• Integration of Molecular Dynamics and Virtual Screening in Lead Discovery.


• Fragment screening and high-throughput approaches for structural-based drug discovery. 


• Identification and structural characterization of novel potential drug targets.


• New insights in the structural biology and drug discovery of difficult targets.


• Multi-Objective Optimization Drug Design 


• Structural biology and drug repurposing


Keywords: Structural Biology, Structural Data, Drug Discovery, Drug Target, Optimization, in silico, Screening, High-Throughput


Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.

Most drug targets are macromolecules (i.e., proteins, nucleic acids, and their complexes). The rational design and testing of drug-lead compounds targeting specific sites on a macromolecule can be driven by a knowledge of the macromolecular target structure and of the atomic details of its interactions with small compounds. 


Traditionally, macromolecular NMR and X-ray crystallography have been the experimental structural techniques of choice for structure-based drug lead discovery, with Cryo-EM the latest addition to the same toolbox. Structural data contributes to the design and generation of initial lead compounds and to the subsequent pharmaceutical chemistry process that bridges from lead to final active pharmaceutical drug.


The advance in structural biology methodologies, computational approaches, and high-throughput methods provided researchers with a huge amount of bewildering data. The integration of such data in the drug development pipeline, in order to convert information into knowledge, has always been a non-trivial problem and constitutes one of the most exciting applications of the so-called “Integrative Structural Biology”. A good lead (and any new drug) must simultaneously satisfy multiple requirements, such as affinity, non-toxicity, as well as several crucial properties such as suitable absorption, distribution, metabolism, and excretion (ADME) profiles and synthesisability. At the same time, the molecular details of the lead-target binding are crucial to predict and rationalize most of those requirements. Traditionally, each of these objectives has been tackled using a linear approach in which successive aspects were optimized sequentially by using experimental and/or computational approaches. This Research Topic will focus on novel approaches for integration of in silico analyses and experimental structural data in workflows for the discovery of new drugs, ultimately supporting the faster and more efficient delivery of drugs to the market.


This Research Topic accepts Original Research articles, Perspectives, and Reviews. Topics of interest include, but are not limited to, the following:


• Integrative Software Platforms for in-silico Multi-Objective Optimised Drug Discovery.


• Integration of Molecular Dynamics and Virtual Screening in Lead Discovery.


• Fragment screening and high-throughput approaches for structural-based drug discovery. 


• Identification and structural characterization of novel potential drug targets.


• New insights in the structural biology and drug discovery of difficult targets.


• Multi-Objective Optimization Drug Design 


• Structural biology and drug repurposing


Keywords: Structural Biology, Structural Data, Drug Discovery, Drug Target, Optimization, in silico, Screening, High-Throughput


Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.

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Submission Deadlines

14 September 2021 Manuscript

Participating Journals

Manuscripts can be submitted to this Research Topic via the following journals:

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Topic Editors

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Submission Deadlines

14 September 2021 Manuscript

Participating Journals

Manuscripts can be submitted to this Research Topic via the following journals:

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