A sensor complements the steric gate when DNA polymerase ϵ discriminates ribonucleotides.

The cellular imbalance between high concentrations of ribonucleotides (NTPs) and low concentrations of deoxyribonucleotides (dNTPs), is challenging for DNA polymerases when building DNA from dNTPs. It is currently believed that DNA polymerases discriminate against NTPs through a steric gate model involving a clash between a tyrosine and the 2'-hydroxyl of the ribonucleotide in the polymerase active site in B-family DNA polymerases. With the help of crystal structures of a B-family polymerase with a UTP or CTP in the active site, molecular dynamics simulations, biochemical assays and yeast genetics, we have identified a mechanism by which the finger domain of the polymerase sense NTPs in the polymerase active site. In contrast to the previously proposed polar filter, our experiments suggest that the amino acid residue in the finger domain senses ribonucleotides by steric hindrance. Furthermore, our results demonstrate that the steric gate in the palm domain and the sensor in the finger domain are both important when discriminating NTPs. Structural comparisons reveal that the sensor residue is conserved among B-family polymerases and we hypothesize that a sensor in the finger domain should be considered in all types of DNA polymerases.

Representation matters: responding to the current campaign against DEI efforts.

Abandonment of diversity, equity and inclusion programs undermines fairness and the productivity of research.

Science after Brexit: bright spots on the Horizon?

Is scientific partnership between the UK and EU on the Horizon?

KIF-Key Interactions Finder: A program to identify the key molecular interactions that regulate protein conformational changes.

Simulation datasets of proteins (e.g., those generated by molecular dynamics simulations) are filled with information about how a non-covalent interaction network within a protein regulates the conformation and, thus, function of the said protein. Most proteins contain thousands of non-covalent interactions, with most of these being largely irrelevant to any single conformational change. The ability to automatically process any protein simulation dataset to identify non-covalent interactions that are strongly associated with a single, defined conformational change would be a highly valuable tool for the community. Furthermore, the insights generated from this tool could be applied to basic research, in order to improve understanding of a mechanism of action, or for protein engineering, to identify candidate mutations to improve/alter the functionality of any given protein. The open-source Python package Key Interactions Finder (KIF) enables users to identify those non-covalent interactions that are strongly associated with any conformational change of interest for any protein simulated. KIF gives the user full control to define the conformational change of interest as either a continuous variable or categorical variable, and methods from statistics or machine learning can be applied to identify and rank the interactions and residues distributed throughout the protein, which are relevant to the conformational change. Finally, KIF has been applied to three diverse model systems (protein tyrosine phosphatase 1B, the PDZ3 domain, and the KE07 series of Kemp eliminases) in order to illustrate its power to identify key features that regulate functionally important conformational dynamics.

The perceived decline of "disruptive" science and technology.

The discussion about science's purported loss of disruptive innovation must not distract from the underlying problems that prevent science from deploying its full potential.

Q-RepEx: A Python pipeline to increase the sampling of empirical valence bond simulations.

The exploration of chemical systems occurs on complex energy landscapes. Comprehensively sampling rugged energy landscapes with many local minima is a common problem for molecular dynamics simulations. These multiple local minima trap the dynamic system, preventing efficient sampling. This is a particular challenge for large biochemical systems with many degrees of freedom. Replica exchange molecular dynamics (REMD) is an approach that accelerates the exploration of the conformational space of a system, and thus can be used to enhance the sampling of complex biomolecular processes. In parallel, the empirical valence bond (EVB) approach is a powerful approach for modeling chemical reactivity in biomolecular systems. Here, we present an open-source Python-based tool that interfaces with the Q simulation package, and increases the sampling efficiency of the EVB free energy perturbation/umbrella sampling approach by means of REMD. This approach, Q-RepEx, both decreases the computational cost of the associated REMD-EVB simulations, and opens the door to more efficient studies of biochemical reactivity in systems with significant conformational fluctuations along the chemical reaction coordinate.

Scholars in peril: when being a scientist can land you in jail (or worse).

The scientific community needs to speak up loudly to support colleagues who are persecuted and imprisoned for political reasons.

Late-termination of pregnancy for medical reasons: when abortion isn't really by choice.

Repealing Roe vs. Wade and the consequences for medical abortion.

Complex Loop Dynamics Underpin Activity, Specificity, and Evolvability in the (ßα)8 Barrel Enzymes of Histidine and Tryptophan Biosynthesis.

Enzymes are conformationally dynamic, and their dynamical properties play an important role in regulating their specificity and evolvability. In this context, substantial attention has been paid to the role of ligand-gated conformational changes in enzyme catalysis; however, such studies have focused on tremendously proficient enzymes such as triosephosphate isomerase and orotidine 5'-monophosphate decarboxylase, where the rapid (µs timescale) motion of a single loop dominates the transition between catalytically inactive and active conformations. In contrast, the (ßα)8-barrels of tryptophan and histidine biosynthesis, such as the specialist isomerase enzymes HisA and TrpF, and the bifunctional isomerase PriA, are decorated by multiple long loops that undergo conformational transitions on the ms (or slower) timescale. Studying the interdependent motions of multiple slow loops, and their role in catalysis, poses a significant computational challenge. This work combines conventional and enhanced molecular dynamics simulations with empirical valence bond simulations to provide rich details of the conformational behavior of the catalytic loops in HisA, PriA, and TrpF, and the role of their plasticity in facilitating bifunctionality in PriA and evolved HisA variants. In addition, we demonstrate that, similar to other enzymes activated by ligand-gated conformational changes, loops 3 and 4 of HisA and PriA act as gripper loops, facilitating the isomerization of the large bulky substrate ProFAR, albeit now on much slower timescales. This hints at convergent evolution on these different (ßα)8-barrel scaffolds. Finally, our work reemphasizes the potential of engineering loop dynamics as a tool to artificially manipulate the catalytic repertoire of TIM-barrel proteins.

Essential Functional Interplay of the Catalytic Groups in Acid Phosphatase.

The cooperative interplay between the functional devices of a preorganized active site is fundamental to enzyme catalysis. An in-depth understanding of this phenomenon is central to elucidating the remarkable efficiency of natural enzymes and provides an essential benchmark for enzyme design and engineering. Here, we study the functional interconnectedness of the catalytic nucleophile (His18) in an acid phosphatase by analyzing the consequences of its replacement with aspartate. We present crystallographic, biochemical, and computational evidence for a conserved mechanistic pathway via a phospho-enzyme intermediate on Asp18. Linear free-energy relationships for phosphoryl transfer from phosphomonoester substrates to His18/Asp18 provide evidence for the cooperative interplay between the nucleophilic and general-acid catalytic groups in the wild-type enzyme, and its substantial loss in the H18D variant. As an isolated factor of phosphatase efficiency, the advantage of a histidine compared to an aspartate nucleophile is ∼104-fold. Cooperativity with the catalytic acid adds ≥102-fold to that advantage. Empirical valence bond simulations of phosphoryl transfer from glucose 1-phosphate to His and Asp in the enzyme explain the loss of activity of the Asp18 enzyme through a combination of impaired substrate positioning in the Michaelis complex, as well as a shift from early to late protonation of the leaving group in the H18D variant. The evidence presented furthermore suggests that the cooperative nature of catalysis distinguishes the enzymatic reaction from the corresponding reaction in solution and is enabled by the electrostatic preorganization of the active site. Our results reveal sophisticated discrimination in multifunctional catalysis of a highly proficient phosphatase active site.

5 suggestions to increase grant application success rates.

A few suggestions and advice to increase the success chances of your grant application.

Adventures on the Routes of Protein Evolution-In Memoriam Dan Salah Tawfik (1955-2021).

Understanding how proteins evolved not only resolves mysteries of the past, but also helps address challenges of the future, particularly those relating to the design and engineering of new protein functions. Here we review the work of Dan S. Tawfik, one of the pioneers of this area, highlighting his seminal contributions in diverse fields such as protein design, high throughput screening, protein stability, fundamental enzyme-catalyzed reactions and promiscuity, that underpin biology and the origins of life. We discuss the influence of his work on how our models of enzyme and protein function have developed and how the main driving forces of molecular evolution were elucidated. The discovery of the rugged routes of evolution has enabled many practical applications, some which are now widely used.

Exploiting enzyme evolution for computational protein design.

Recent years have seen an explosion of interest in understanding the physicochemical parameters that shape enzyme evolution, as well as substantial advances in computational enzyme design. This review discusses three areas where evolutionary information can be used as part of the design process: (i) using ancestral sequence reconstruction (ASR) to generate new starting points for enzyme design efforts; (ii) learning from how nature uses conformational dynamics in enzyme evolution to mimic this process in silico; and (iii) modular design of enzymes from smaller fragments, again mimicking the process by which nature appears to create new protein folds. Using showcase examples, we highlight the importance of incorporating evolutionary information to continue to push forward the boundaries of enzyme design studies.