ArticlePloS one2012
What can we learn from the evolution of protein-ligand interactions to aid the design of new therapeutics?
Article in PloS one, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
12 citing papers in PubMed.
- Revealing Propolis Potential Activity on Inhibiting Estrogen Receptor and Heat Shock Protein 90 Overexpressed in Breast Cancer by Bioinformatics Approaches.Bioinformatics and biology insights · 2024Article
- Non-Extensive Fragmentation of Natural Products and Pharmacophore-Based Virtual Screening as a Practical Approach to Identify Novel Promising Chemical Scaffolds.Frontiers in chemistry · 2021Article
- A systematic analysis of atomic protein-ligand interactions in the PDB.MedChemComm · 2017Article
- TIBLE: a web-based, freely accessible resource for small-molecule binding data for mycobacterial species.Database : the journal of biological databases and curation · 2017Article
- Avoiding drug resistance through extended drug target interfaces: a case for stapled peptides.Oncotarget · 2016Article
- Flexibility and small pockets at protein-protein interfaces: New insights into druggability.Progress in biophysics and molecular biology · 2015Review
- Molecular Property Design: Does Everyone Get It?ACS medicinal chemistry letters · 2015Article
- Article
- Focusing on shared subpockets - new developments in fragment-based drug discovery.Expert opinion on drug discovery · 2015Review
- Drug-Like Protein-Protein Interaction Modulators: Challenges and Opportunities for Drug Discovery and Chemical Biology.Molecular informatics · 2014Review
- The role of ligand efficiency metrics in drug discovery.Nature reviews. Drug discovery · 2014Review
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Efforts to increase affinity in the design of new therapeutic molecules have tended to lead to greater lipophilicity, a factor that is generally agreed to be contributing to the low success rate of new drug candidates. Our aim is to provide a structural perspective to the study of lipophilic efficiency and to compare molecular interactions created over evolutionary time with those designed by humans. We show that natural complexes typically engage in more polar contacts than synthetic molecules bound to proteins. The synthetic molecules also have a higher proportion of unmatched heteroatoms at the interface than the natural sets. These observations suggest that there are lessons to be learnt from Nature, which could help us to improve the characteristics of man-made molecules. In particular, it is possible to increase the density of polar contacts without increasing lipophilicity and this is best achieved early in discovery while molecules remain relatively small.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.