Diversity in Medicinal Chemistry Space

Gorse, Alain-Dominique

doi:10.2174/156802606775193310

Cited by 108 publications

(56 citation statements)

References 214 publications

(338 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…size, shape, polarity, charge, electrostatics, flexibility, secondary structure and hydrogen bonding capabilities) covered by the descriptors exceeds previously reported attempts to physicochemically describe cavities 1,8,9,11,13,18,32. The idea of describing cavities and analysing the cavity property relationships is comparable to the characterisation of small molecules, for example in investigations of molecular diversity39–42 and/or the creation of quantitative structure-activity relationship (QSAR) models 43,44. To explore the structural and physicochemical space of cavities, their key properties were extracted from the descriptor matrix using Principal Component Analysis (PCA).…”

Section: Introductionmentioning

confidence: 63%

Mapping of ligand‐binding cavities in proteins

2009

View full text Add to dashboard Cite

The complex interactions between proteins and small organic molecules (ligands) are intensively studied because they play key roles in biological processes and drug activities. Here, we present a novel approach to characterise and map the ligand-binding cavities of proteins without direct geometric comparison of structures, based on Principal Component Analysis of cavity properties (related mainly to size, polarity and charge). This approach can provide valuable information on the similarities, and dissimilarities, of binding cavities due to mutations, between-species differences and flexibility upon ligand-binding. The presented results show that information on ligand-binding cavity variations can complement information on protein similarity obtained from sequence comparisons. The predictive aspect of the method is exemplified by successful predictions of serine proteases that were not included in the model construction. The presented strategy to compare ligand-binding cavities of related and unrelated proteins has many potential applications within protein and medicinal chemistry, for example in the characterisation and mapping of “orphan structures”, selection of protein structures for docking studies in structure-based design and identification of proteins for selectivity screens in drug design programs.

show abstract

Section: Introductionmentioning

confidence: 63%

Mapping of ligand‐binding cavities in proteins

2009

View full text Add to dashboard Cite

show abstract

“…Observation of the cosmos has led astrophysicists to map the universe and suggest that there are about 10 23 stars gathered in 10 11 galaxies [9]. In parallel, consideration of the real number of possible ligands has been the subject of savvy estimates [10, 11]. Complicating the matter is the fact that not all chemically plausible molecular structures might be synthetically accessible nor might they be affordable.…”

Section: The Landscape Of Modern Drug Discoverymentioning

confidence: 99%

Current Progress in Structure-Based Rational Drug Design Marks a New Mindset in Drug Discovery

Lounnas

Ritschel

Kelder³

et al. 2013

Computational and Structural Biotechnology Journal

190

123

View full text Add to dashboard Cite

The past decade has witnessed a paradigm shift in preclinical drug discovery with structure-based drug design (SBDD) making a comeback while high-throughput screening (HTS) methods have continued to generate disappointing results. There is a deficit of information between identified hits and the many criteria that must be fulfilled in parallel to convert them into preclinical candidates that have a real chance to become a drug. This gap can be bridged by investigating the interactions between the ligands and their receptors. Accurate calculations of the free energy of binding are still elusive; however progresses were made with respect to how one may deal with the versatile role of water. A corpus of knowledge combining X-ray structures, bioinformatics and molecular modeling techniques now allows drug designers to routinely produce receptor homology models of increasing quality. These models serve as a basis to establish and validate efficient rationales used to tailor and/or screen virtual libraries with enhanced chances of obtaining hits. Many case reports of successful SBDD show how synergy can be gained from the combined use of several techniques. The role of SBDD with respect to two different classes of widely investigated pharmaceutical targets: (a) protein kinases (PK) and (b) G-protein coupled receptors (GPCR) is discussed. Throughout these examples prototypical situations covering the current possibilities and limitations of SBDD are presented.

show abstract

“…The goal is to improve the chemical content without significantly increasing the size of compound libraries [89]. Several cheminformatics approaches utilizing molecular fingerprints, scaffold-based, and graph-based representations have been used to represent the diversity of chemical space [90]. Large databases are pre-filtered to create smaller databases that capture the diversity of the entire set.…”

Section: Virtual and Biochemical Approaches To Identify Ptp Inhibimentioning

confidence: 99%

Integrating virtual and biochemical screening for protein tyrosine phosphatase inhibitor discovery

Martin

Narang

Medina-Franco

et al. 2014

Methods

View full text Add to dashboard Cite

Protein tyrosine phosphatases (PTPs) represent an important class of enzymes that mediate signal transduction and control diverse aspects of cell behavior. The importance of their activity is exemplified by their significant contribution to disease etiology with over half of all human PTP genes implicated in at least one disease. Small molecule inhibitors targeting individual PTPs are important biological tools, and are needed to fully characterize the function of these enzymes. Moreover, potent and selective PTP inhibitors hold the promise to transform the treatment of many diseases. While numerous methods exist to develop PTP-directed small molecules, we have found that complimentary use of both virtual (in silico) and biochemical (in vitro) screening approaches expedite compound identification and drug development. Here, we summarize methods pertinent to our work and others. Focusing on specific challenges and successes we have experienced, we discuss the considerable caution that must be taken to avoid enrichment of inhibitors that function by non-selective oxidation. We also discuss the utility of using “open” PTP structures to identify active-site directed compounds, a rather unconventional choice for virtual screening. When integrated closely, virtual and biochemical screening can be used in a productive workflow to identify small molecules targeting PTPs.

show abstract

Diversity in Medicinal Chemistry Space

Cited by 108 publications

References 214 publications

Mapping of ligand‐binding cavities in proteins

Mapping of ligand‐binding cavities in proteins

Current Progress in Structure-Based Rational Drug Design Marks a New Mindset in Drug Discovery

Integrating virtual and biochemical screening for protein tyrosine phosphatase inhibitor discovery

Contact Info

Product

Resources

About