Alan Fersht
University of Cambridge
H-index: 160
Europe-United Kingdom
Description
Alan Fersht, With an exceptional h-index of 160 and a recent h-index of 51 (since 2020), a distinguished researcher at University of Cambridge, specializes in the field of protein folding misfolding p53 and cancer.
His recent articles reflect a diverse array of research interests and contributions to the field:
From covalent transition states in chemistry to noncovalent in biology: from β-to Φ-value analysis of protein folding
AlphaFold–A personal perspective on the impact of machine learning
NF‐κB Rel subunit exchange on a physiological timescale
A structure-guided molecular chaperone approach for restoring the transcriptional activity of the p53 cancer mutant Y220C (vol 11, pg 2491, 2019)
Targeting cavity-creating p53 cancer mutations with small-molecule stabilizers: the Y220X paradigm
Professor Information
University | University of Cambridge |
---|---|
Position | Emeritus Group Leader MRC Laboratory of Molecular Biology |
Citations(all) | 94199 |
Citations(since 2020) | 11446 |
Cited By | 86672 |
hIndex(all) | 160 |
hIndex(since 2020) | 51 |
i10Index(all) | 567 |
i10Index(since 2020) | 241 |
University Profile Page | University of Cambridge |
Research & Interests List
protein folding misfolding p53 and cancer
Top articles of Alan Fersht
From covalent transition states in chemistry to noncovalent in biology: from β-to Φ-value analysis of protein folding
Solving the mechanism of a chemical reaction requires determining the structures of all the ground states on the pathway and the elusive transition states linking them. 2024 is the centenary of Brønsted’s landmark paper that introduced the β-value and structure-activity studies as the only experimental means to infer the structures of transition states. It involves making systematic small changes in the covalent structure of the reactants and analysing changes in activation and equilibrium-free energies. Protein engineering was introduced for an analogous procedure, Φ-value analysis, to analyse the noncovalent interactions in proteins central to biological chemistry. The methodology was developed first by analysing noncovalent interactions in transition states in enzyme catalysis. The mature procedure was then applied to study transition states in the pathway of protein folding – ‘part (b) of the protein folding problem …
Authors
Alan R Fersht
Published Date
2024/1
AlphaFold–A personal perspective on the impact of machine learning
I outline how over my career as a protein scientist Machine Learning has impacted my area of science and one of my pastimes, chess, where there are some interesting parallels. In 1968, modelling of three-dimensional structures was initiated based on a known structure as a template, the problem of the pathway of protein folding was posed and bets were taken in the emerging field of Machine Learning on whether computers could outplay humans at chess. Half a century later, Machine Learning has progressed from using computational power combined with human knowledge in solving problems to playing chess without human knowledge being used, where it has produced novel strategies. Protein structures are being solved by Machine Learning based on human-derived knowledge but without templates. There is much promise that programs like AlphaFold based on Machine Learning will be powerful tools for …
Authors
Alan R Fersht
Published Date
2021/10/1
NF‐κB Rel subunit exchange on a physiological timescale
The Rel proteins of the NF‐κB complex comprise one of the most investigated transcription factor families, forming a variety of hetero‐ or homodimers. Nevertheless, very little is known about the fundamental kinetics of NF‐κB complex assembly, or the inter‐conversion potential of dimerised Rel subunits. Here, we examined an unexplored aspect of NF‐κB dynamics, focusing on the dissociation and reassociation of the canonical p50 and p65 Rel subunits and their ability to form new hetero‐ or homodimers. We employed a soluble expression system to enable the facile production of NF‐κB Rel subunits, and verified these proteins display canonical NF‐κB nucleic acid binding properties. Using a combination of biophysical techniques, we demonstrated that, at physiological temperatures, homodimeric Rel complexes routinely exchange subunits with a half‐life of less than 10 min. In contrast, we found a dramatic …
Authors
Matthew Biancalana,Eviatar Natan,Michael J Lenardo,Alan R Fersht
Journal
Protein Science
Published Date
2021/9
A structure-guided molecular chaperone approach for restoring the transcriptional activity of the p53 cancer mutant Y220C (vol 11, pg 2491, 2019)
Aim The p53 cancer mutation Y220C creates a conformationally unstable protein with a unique elongated surface crevice that can be targeted by molecular chaperones. We report the structure-guided optimization of the carbazole-based stabilizer PK083. Materials & methods Biophysical, cellular and x-ray crystallographic techniques have been employed to elucidate the mode of action of the carbazole scaffolds. Results Targeting an unoccupied subsite of the surface crevice with heterocycle-substituted PK083 analogs resulted in a 70-fold affinity increase to single-digit micromolar levels, increased thermal stability and decreased rate of aggregation of the mutant protein. PK9318, one of the most potent binders, restored p53 signaling in the liver cancer cell line HUH-7 with homozygous Y220C mutation. Conclusion The p53-Y220C mutant is an excellent paradigm for the development of mutant p53 rescue drugs via …
Authors
Matthias R Bauer,Rhiannon N Jones,Raysa K Tareque,Bradley Springett,Felix A Dingler,Lorena Verduci,Ketan J Patel,Alan R Fersht,Andreas C Joerger,John Spencer
Journal
Future Medicinal Chemistry
Published Date
2019/10
Targeting cavity-creating p53 cancer mutations with small-molecule stabilizers: the Y220X paradigm
We have previously shown that the thermolabile, cavity-creating p53 cancer mutant Y220C can be reactivated by small-molecule stabilizers. In our ongoing efforts to unearth druggable variants of the p53 mutome, we have now analyzed the effects of other cancer-associated mutations at codon 220 on the structure, stability, and dynamics of the p53 DNA-binding domain (DBD). We found that the oncogenic Y220H, Y220N, and Y220S mutations are also highly destabilizing, suggesting that they are largely unfolded under physiological conditions. A high-resolution crystal structure of the Y220S mutant DBD revealed a mutation-induced surface crevice similar to that of Y220C, whereas the corresponding pocket’s accessibility to small molecules was blocked in the structure of the Y220H mutant. Accordingly, a series of carbazole-based small molecules, designed for stabilizing the Y220C mutant, also bound to and …
Authors
Matthias R Bauer,Andreas Krämer,Giovanni Settanni,Rhiannon N Jones,Xiaomin Ni,Raysa Khan Tareque,Alan R Fersht,John Spencer,Andreas C Joerger
Journal
ACS Chemical Biology
Published Date
2020/1/28
Professor FAQs
What is Alan Fersht's h-index at University of Cambridge?
The h-index of Alan Fersht has been 51 since 2020 and 160 in total.
What are Alan Fersht's top articles?
The articles with the titles of
From covalent transition states in chemistry to noncovalent in biology: from β-to Φ-value analysis of protein folding
AlphaFold–A personal perspective on the impact of machine learning
NF‐κB Rel subunit exchange on a physiological timescale
A structure-guided molecular chaperone approach for restoring the transcriptional activity of the p53 cancer mutant Y220C (vol 11, pg 2491, 2019)
Targeting cavity-creating p53 cancer mutations with small-molecule stabilizers: the Y220X paradigm
are the top articles of Alan Fersht at University of Cambridge.
What are Alan Fersht's research interests?
The research interests of Alan Fersht are: protein folding misfolding p53 and cancer
What is Alan Fersht's total number of citations?
Alan Fersht has 94,199 citations in total.
What are the co-authors of Alan Fersht?
The co-authors of Alan Fersht are Greg Winter, Valerie D. Daggett, Gideon schreiber, Robin Leatherbarrow, Dr S.E. Jackson, Christopher M Johnson.