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  1. Article ; Online: From covalent transition states in chemistry to noncovalent in biology: from

    Fersht, Alan R

    Quarterly reviews of biophysics

    2024  Volume 57, Page(s) e4

    Abstract: 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 ... ...

    Abstract 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
    MeSH term(s) Computer Simulation ; Proteins/chemistry ; Protein Folding ; Protein Engineering ; Biology ; Kinetics ; Thermodynamics
    Chemical Substances Proteins
    Language English
    Publishing date 2024-03-20
    Publishing country England
    Document type Journal Article ; Review
    ZDB-ID 209912-3
    ISSN 1469-8994 ; 0033-5835
    ISSN (online) 1469-8994
    ISSN 0033-5835
    DOI 10.1017/S0033583523000045
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    Zs.B 387: Show issues Location:
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  2. Article ; Online: AlphaFold - A Personal Perspective on the Impact of Machine Learning.

    Fersht, Alan R

    Journal of molecular biology

    2021  Volume 433, Issue 20, Page(s) 167088

    Abstract: 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 ... ...

    Abstract 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 designing entirely novel protein folds and new activities. But, will they produce novel ideas on protein folding pathways and provide new insights into the principles that govern folds?
    MeSH term(s) Animals ; Chymotrypsin/chemistry ; Humans ; Machine Learning ; Models, Molecular ; Protein Conformation ; Protein Folding ; Proteins/chemistry ; Software ; Trypsin/chemistry
    Chemical Substances Proteins ; Chymotrypsin (EC 3.4.21.1) ; Trypsin (EC 3.4.21.4)
    Language English
    Publishing date 2021-06-02
    Publishing country England
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 80229-3
    ISSN 1089-8638 ; 0022-2836
    ISSN (online) 1089-8638
    ISSN 0022-2836
    DOI 10.1016/j.jmb.2021.167088
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  3. Article: AlphaFold – A Personal Perspective on the Impact of Machine Learning

    Fersht, Alan R

    Journal of molecular biology. 2021 May 28,

    2021  

    Abstract: 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 ... ...

    Abstract 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 designing entirely novel protein folds and new activities. But, will they produce novel ideas on protein folding pathways and provide new insights into the principles that govern folds?
    Keywords humans ; molecular biology ; scientists
    Language English
    Dates of publication 2021-0528
    Publishing place Elsevier Ltd
    Document type Article
    Note Pre-press version
    ZDB-ID 80229-3
    ISSN 1089-8638 ; 0022-2836
    ISSN (online) 1089-8638
    ISSN 0022-2836
    DOI 10.1016/j.jmb.2021.167088
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  4. Article ; Online: Profile of Martin Karplus, Michael Levitt, and Arieh Warshel, 2013 nobel laureates in chemistry.

    Fersht, Alan R

    Proceedings of the National Academy of Sciences of the United States of America

    2013  Volume 110, Issue 49, Page(s) 19656–19657

    MeSH term(s) Chemistry/history ; History, 20th Century ; History, 21st Century ; Nobel Prize ; Proteins/chemistry
    Chemical Substances Proteins
    Language English
    Publishing date 2013-11-25
    Publishing country United States
    Document type Historical Article ; Journal Article ; Portrait
    ZDB-ID 209104-5
    ISSN 1091-6490 ; 0027-8424
    ISSN (online) 1091-6490
    ISSN 0027-8424
    DOI 10.1073/pnas.1320569110
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  5. Article ; Online: NF-κB Rel subunit exchange on a physiological timescale.

    Biancalana, Matthew / Natan, Eviatar / Lenardo, Michael J / Fersht, Alan R

    Protein science : a publication of the Protein Society

    2021  Volume 30, Issue 9, Page(s) 1818–1832

    Abstract: 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 ... ...

    Abstract 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 preference for the formation of the p50/p65 heterodimer, which demonstrated a kinetic stability of at least an order of magnitude greater than either homodimer. These results suggest that specific DNA targets of either the p50 or p65 homodimers can only be targeted when these subunits are expressed exclusively, or with the intervention of additional post-translational modifications. Together, this work implies a new model of how cells can modulate NF-κB activity by fine-tuning the relative proportions of the p50 and p65 proteins, as well as their time of expression. This work thus provides a new quantitative interpretation of Rel dimer distribution in the cell, particularly for those who are developing mathematical models of NF-κB activity.
    MeSH term(s) Binding Sites ; Cloning, Molecular ; DNA/chemistry ; DNA/genetics ; DNA/metabolism ; Escherichia coli/genetics ; Escherichia coli/metabolism ; Gene Expression ; Genetic Vectors/chemistry ; Genetic Vectors/metabolism ; Humans ; Kinetics ; Models, Molecular ; NF-kappa B p50 Subunit/chemistry ; NF-kappa B p50 Subunit/genetics ; NF-kappa B p50 Subunit/metabolism ; Oligodeoxyribonucleotides/chemistry ; Oligodeoxyribonucleotides/metabolism ; Protein Binding ; Protein Conformation, alpha-Helical ; Protein Conformation, beta-Strand ; Protein Interaction Domains and Motifs ; Protein Multimerization ; Protein Subunits/chemistry ; Protein Subunits/genetics ; Protein Subunits/metabolism ; Recombinant Proteins/chemistry ; Recombinant Proteins/genetics ; Recombinant Proteins/metabolism ; Thermodynamics ; Transcription Factor RelA/chemistry ; Transcription Factor RelA/genetics ; Transcription Factor RelA/metabolism
    Chemical Substances NF-kappa B p50 Subunit ; Oligodeoxyribonucleotides ; Protein Subunits ; Recombinant Proteins ; Transcription Factor RelA ; DNA (9007-49-2)
    Language English
    Publishing date 2021-06-04
    Publishing country United States
    Document type Journal Article ; Research Support, N.I.H., Extramural
    ZDB-ID 1106283-6
    ISSN 1469-896X ; 0961-8368
    ISSN (online) 1469-896X
    ISSN 0961-8368
    DOI 10.1002/pro.4134
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    Zs.A 3407: Show issues Location:
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  6. Article ; Online: Multisite aggregation of p53 and implications for drug rescue.

    Wang, GuoZhen / Fersht, Alan R

    Proceedings of the National Academy of Sciences of the United States of America

    2017  Volume 114, Issue 13, Page(s) E2634–E2643

    Abstract: Protein aggregation is involved in many diseases. Often, a unique aggregation-prone sequence polymerizes to form regular fibrils. Many oncogenic mutants of the tumor suppressor p53 rapidly aggregate but form amorphous fibrils. A peptide surrounding ... ...

    Abstract Protein aggregation is involved in many diseases. Often, a unique aggregation-prone sequence polymerizes to form regular fibrils. Many oncogenic mutants of the tumor suppressor p53 rapidly aggregate but form amorphous fibrils. A peptide surrounding Ile254 is proposed to be the aggregation-driving sequence in cells. We identified several different aggregating sites from limited proteolysis of harvested aggregates and effects of mutations on kinetics and products of aggregation. We present a model whereby the amorphous nature of the aggregates results from multisite branching of polymerization after slow unfolding of the protein, which may be a common feature of aggregation of large proteins. Greatly lowering the aggregation propensity of any one single site, including the site of Ile254, by mutation did not inhibit aggregation in vitro because aggregation could still occur via the other sites. Inhibition of an individual site is, accordingly, potentially unable to prevent aggregation in vivo. However, cancer cells are specifically killed by peptides designed to inhibit the Ile254 sequence and further aggregation-driving sequences that we have found. Consistent with our proposed mechanism of aggregation, we found that such peptides did not inhibit aggregation of mutant p53 in vitro. The cytotoxicity was not eliminated by knockdown of p53 in 2D cancer cell cultures. The peptides caused rapid cell death, much faster than usually expected for p53-mediated transcription-dependent apoptosis. There may also be non-p53 targets for those peptides in cancer cells, such as p63, or the peptides may alter other interactions of partly denatured p53 with receptors.
    MeSH term(s) Humans ; Models, Theoretical ; Mutation ; Neoplasms/genetics ; Protein Aggregation, Pathological ; Protein Domains ; Tumor Suppressor Protein p53/chemistry ; Tumor Suppressor Protein p53/metabolism
    Chemical Substances Tumor Suppressor Protein p53
    Language English
    Publishing date 2017-03-14
    Publishing country United States
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 209104-5
    ISSN 1091-6490 ; 0027-8424
    ISSN (online) 1091-6490
    ISSN 0027-8424
    DOI 10.1073/pnas.1700308114
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  7. Article ; Online: ChemBioChem@20-Some Reflections.

    Fersht, Alan R / Gölitz, Peter / Lehn, Jean-Marie

    Chembiochem : a European journal of chemical biology

    2019  Volume 21, Issue 1-2, Page(s) 5–6

    Abstract: Looking back, looking forward: In 2000, ChemBioChem debuted. The chemistry of carbohydrates, nucleic acids, peptides, proteins, natural products and other small molecules had reached a level that allowed biological questions to be probed. Today, there is ...

    Abstract Looking back, looking forward: In 2000, ChemBioChem debuted. The chemistry of carbohydrates, nucleic acids, peptides, proteins, natural products and other small molecules had reached a level that allowed biological questions to be probed. Today, there is no end in sight to studying biological matter with chemical tools or making use of biological methods to produce chemicals.
    MeSH term(s) Biological Products/chemistry ; Biological Products/metabolism ; Carbohydrates/chemistry ; Humans ; Nucleic Acids/chemistry ; Nucleic Acids/metabolism ; Peptides/chemistry ; Peptides/metabolism ; Proteins/chemistry ; Proteins/metabolism ; Synthetic Biology
    Chemical Substances Biological Products ; Carbohydrates ; Nucleic Acids ; Peptides ; Proteins
    Language English
    Publishing date 2019-11-26
    Publishing country Germany
    Document type Editorial ; Research Support, Non-U.S. Gov't
    ZDB-ID 2020469-3
    ISSN 1439-7633 ; 1439-4227
    ISSN (online) 1439-7633
    ISSN 1439-4227
    DOI 10.1002/cbic.201900658
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  8. Article ; Online: The p53 Pathway: Origins, Inactivation in Cancer, and Emerging Therapeutic Approaches.

    Joerger, Andreas C / Fersht, Alan R

    Annual review of biochemistry

    2016  Volume 85, Page(s) 375–404

    Abstract: Inactivation of the transcription factor p53, through either direct mutation or aberrations in one of its many regulatory pathways, is a hallmark of virtually every tumor. In recent years, screening for p53 activators and a better understanding of the ... ...

    Abstract Inactivation of the transcription factor p53, through either direct mutation or aberrations in one of its many regulatory pathways, is a hallmark of virtually every tumor. In recent years, screening for p53 activators and a better understanding of the molecular mechanisms of oncogenic perturbations of p53 function have opened up a host of novel avenues for therapeutic intervention in cancer: from the structure-guided design of chemical chaperones to restore the function of conformationally unstable p53 cancer mutants, to the development of potent antagonists of the negative regulators MDM2 and MDMX and other modulators of the p53 pathway for the treatment of cancers with wild-type p53. Some of these compounds have now moved from proof-of-concept studies into clinical trials, with prospects for further, personalized anticancer medicines. We trace the structural evolution of the p53 pathway, from germ-line surveillance in simple multicellular organisms to its pluripotential role in humans.
    MeSH term(s) Animals ; Antineoplastic Agents, Alkylating/chemical synthesis ; Antineoplastic Agents, Alkylating/therapeutic use ; Cell Cycle Proteins ; Clinical Trials as Topic ; Drug Design ; Gene Expression Regulation, Neoplastic ; Humans ; Molecular Docking Simulation ; Molecular Targeted Therapy ; Mutation ; Neoplasms/drug therapy ; Neoplasms/genetics ; Neoplasms/metabolism ; Neoplasms/pathology ; Nuclear Proteins/antagonists & inhibitors ; Nuclear Proteins/chemistry ; Nuclear Proteins/genetics ; Nuclear Proteins/metabolism ; Protein Multimerization ; Protein Structure, Secondary ; Proto-Oncogene Proteins/antagonists & inhibitors ; Proto-Oncogene Proteins/chemistry ; Proto-Oncogene Proteins/genetics ; Proto-Oncogene Proteins/metabolism ; Proto-Oncogene Proteins c-mdm2/antagonists & inhibitors ; Proto-Oncogene Proteins c-mdm2/chemistry ; Proto-Oncogene Proteins c-mdm2/genetics ; Proto-Oncogene Proteins c-mdm2/metabolism ; Signal Transduction ; Tumor Suppressor Protein p53/agonists ; Tumor Suppressor Protein p53/chemistry ; Tumor Suppressor Protein p53/genetics ; Tumor Suppressor Protein p53/metabolism
    Chemical Substances Antineoplastic Agents, Alkylating ; Cell Cycle Proteins ; MDM4 protein, human ; Nuclear Proteins ; Proto-Oncogene Proteins ; Tumor Suppressor Protein p53 ; MDM2 protein, human (EC 2.3.2.27) ; Proto-Oncogene Proteins c-mdm2 (EC 2.3.2.27)
    Language English
    Publishing date 2016-05-04
    Publishing country United States
    Document type Journal Article ; Review
    ZDB-ID 207924-0
    ISSN 1545-4509 ; 0066-4154
    ISSN (online) 1545-4509
    ISSN 0066-4154
    DOI 10.1146/annurev-biochem-060815-014710
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    Uc I Zs.209: Show issues Location:
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  9. Article ; Online: Mechanism of initiation of aggregation of p53 revealed by Φ-value analysis.

    Wang, GuoZhen / Fersht, Alan R

    Proceedings of the National Academy of Sciences of the United States of America

    2015  Volume 112, Issue 8, Page(s) 2437–2442

    Abstract: Many oncogenic mutations inactivate the tumor suppressor p53 by destabilizing it, leading to its rapid aggregation. Small molecule drugs are being developed to stabilize such mutants. The kinetics of aggregation of p53 is deceptively simple. The initial ... ...

    Abstract Many oncogenic mutations inactivate the tumor suppressor p53 by destabilizing it, leading to its rapid aggregation. Small molecule drugs are being developed to stabilize such mutants. The kinetics of aggregation of p53 is deceptively simple. The initial steps in the micromolar concentration range follow apparent sigmoidal sequential first-order kinetics, with rate constants k1 and k2. However, the aggregation kinetics of a panel of mutants prepared for Φ-value analysis has now revealed a bimolecular reaction hidden beneath the observed first-order kinetics. Φu measures the degree of local unfolding on a scale of 0-1. A number of sequential Φu-values of ∼1 for k1 and k2 over the molecule implied more than one protein molecule must be reacting, which was confirmed by finding a clear concentration dependence at submicromolar protein. Numerical simulations showed that the kinetics of the more complex mechanism is difficult, if not impossible, to distinguish experimentally from simple first order under many reaction conditions. Stabilization of mutants by small molecules will be enhanced because they decrease both k1 and k2. The regions with high Φu-values point to the areas where stabilization of mutant proteins would have the greatest effect.
    MeSH term(s) Benzothiazoles ; Biophysical Phenomena ; Computer Simulation ; Kinetics ; Mutant Proteins/chemistry ; Mutant Proteins/metabolism ; Protein Aggregates ; Protein Structure, Tertiary ; Thiazoles/metabolism ; Tumor Suppressor Protein p53/chemistry ; Tumor Suppressor Protein p53/metabolism
    Chemical Substances Benzothiazoles ; Mutant Proteins ; Protein Aggregates ; Thiazoles ; Tumor Suppressor Protein p53 ; thioflavin T (2390-54-7)
    Language English
    Publishing date 2015-02-09
    Publishing country United States
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 209104-5
    ISSN 1091-6490 ; 0027-8424
    ISSN (online) 1091-6490
    ISSN 0027-8424
    DOI 10.1073/pnas.1500243112
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  10. Article ; Online: Propagation of aggregated p53: Cross-reaction and coaggregation vs. seeding.

    Wang, GuoZhen / Fersht, Alan R

    Proceedings of the National Academy of Sciences of the United States of America

    2015  Volume 112, Issue 8, Page(s) 2443–2448

    Abstract: Destabilized mutant p53s coaggregate with WT p53, p63, and p73 in cancer cell lines. We found that stoichiometric amounts of aggregation-prone mutants induced only small amounts of WT p53 to coaggregate, and preformed aggregates did not significantly ... ...

    Abstract Destabilized mutant p53s coaggregate with WT p53, p63, and p73 in cancer cell lines. We found that stoichiometric amounts of aggregation-prone mutants induced only small amounts of WT p53 to coaggregate, and preformed aggregates did not significantly seed the aggregation of bulk protein. Similarly, p53 mutants trapped only small amounts of p63 and p73 into their p53 aggregates. Tetrameric full-length protein aggregated at similar rates and kinetics to isolated core domains, but there was some induced aggregation of WT by mutants in hetero-tetramers. p53 aggregation thus differs from the usual formation of amyloid fibril or prion aggregates where tiny amounts of preformed aggregate rapidly seed further aggregation. The proposed aggregation mechanism of p53 of rate-determining sequential unfolding and combination of two molecules accounts for the difference. A molecule of fast-unfolding mutant preferentially reacts with another molecule of mutant and only occasionally traps a slower unfolding WT molecule. The mutant population rapidly self-aggregates before much WT protein is depleted. Subsequently, WT protein self-aggregates at its normal rate. However, the continual production of mutant p53 in a cancer cell would gradually trap more and more WT and other proteins, accounting for the observations of coaggregates in vivo. The mechanism corresponds more to trapping by cross-reaction and coaggregation rather than classical seeding and growth.
    MeSH term(s) Benzothiazoles ; Computer Simulation ; DNA-Binding Proteins/chemistry ; DNA-Binding Proteins/metabolism ; Kinetics ; Mutant Proteins/chemistry ; Mutant Proteins/metabolism ; Mutation/genetics ; Nuclear Proteins/chemistry ; Nuclear Proteins/metabolism ; Protein Aggregates ; Protein Multimerization ; Protein Structure, Tertiary ; Thiazoles/metabolism ; Time Factors ; Tumor Protein p73 ; Tumor Suppressor Protein p53/chemistry ; Tumor Suppressor Protein p53/metabolism ; Tumor Suppressor Proteins/chemistry ; Tumor Suppressor Proteins/metabolism
    Chemical Substances Benzothiazoles ; DNA-Binding Proteins ; Mutant Proteins ; Nuclear Proteins ; Protein Aggregates ; Thiazoles ; Tumor Protein p73 ; Tumor Suppressor Protein p53 ; Tumor Suppressor Proteins ; thioflavin T (2390-54-7)
    Language English
    Publishing date 2015-02-09
    Publishing country United States
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 209104-5
    ISSN 1091-6490 ; 0027-8424
    ISSN (online) 1091-6490
    ISSN 0027-8424
    DOI 10.1073/pnas.1500262112
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