MptpA Kinetics Enhanced by Allosteric Control of an Active Conformation

Mechanistic Insight Into the Conformational Changes of Cas8 Upon Binding to Different PAM Sequences in the Transposon-Encoded Type I-F CRISPR-Cas System

The INTEGRATE system is a gene-editing approach that offers advantages over the widely used CRISPR-Cas9 system. It does not introduce double strand breaks in the target DNA but rather integrates the desired DNA sequence directly into it. The first step in the integration process is PAM recognition, which is critical to understanding and optimizing the system. Experimental testing revealed varying integration efficiencies of different PAM mutants, and computational simulations were carried out to gain mechanistic insight into the conformational changes of Cas8 during PAM recognition. Our results showed that the interaction between Arg246 and guanine at position (-1) of the target strand is critical for PAM recognition. We found that unfavorable interactions in the 5'-AC-3' PAM mutant disrupted this interaction and may be responsible for its 0% integration efficiency. Additionally, we discovered that PAM sequences not only initiate the integration process but also regulate it through an allosteric mechanism that connects the N-terminal domain and the helical bundle of Cas8. This allosteric regulation was present in all PAMs tested, even those with lower integration efficiencies, such as 5'-TC-3' and 5'-AC-3'. We identified the Cas8 residues that are involved in this regulation. Our findings provide valuable insights into PAM recognition mechanisms in the INTEGRATE system and can help improve the gene-editing technology.

What is allosteric regulation? Exploring the exceptions that prove the rule!

"Allosteric" was first introduced to mean the other site (i.e., a site distinct from the active or orthosteric site), an adjective for "regulation" to imply a regulatory outcome resulting from ligand binding at another site. That original idea outlines a system with two ligand-binding events at two distinct locations on a macromolecule (originally a protein system), which defines a four-state energy cycle. An allosteric energy cycle provides a quantifiable allosteric coupling constant and focuses our attention on the unique properties of the four equilibrated protein complexes that constitute the energy cycle. Because many observed phenomena have been referenced as "allosteric regulation" in the literature, the goal of this work is to use literature examples to explore which systems are and are not consistent with the two-ligand thermodynamic energy cycle-based definition of allosteric regulation. We emphasize the need for consistent language so comparisons can be made among the ever-increasing number of allosteric systems. Building on the mutually exclusive natures of an energy cycle definition of allosteric regulation versus classic two-state models, we conclude our discussion by outlining how the often-proposed Rube-Goldberg-like mechanisms are likely inconsistent with an energy cycle definition of allosteric regulation.

Shikonin and Juglone Inhibit Mycobacterium tuberculosis Low-Molecular-Weight Protein Tyrosine Phosphatase a (Mt-PTPa)

Low-molecular-weight protein tyrosine phosphatases (LMW-PTPs) are involved in promoting the intracellular survival of Mycobacterium tuberculosis (Mtb), the causative organism of tuberculosis. These PTPs directly alter host signalling pathways to evade the hostile environment of macrophages and avoid host clearance. Among these, protein tyrosine phosphatase A (Mt-PTPa) is implicated in phagosome acidification failure, thereby inhibiting phagosome maturation to promote Mycobacterium tuberculosis (Mtb) survival. In this study, we explored Mt-PTPa as a potential drug target for treating Mtb. We started by screening a library of 502 pure natural compounds against the activities of Mt-PTPa in vitro, with a threshold of 50% inhibition of activity via a <500 µM concentration of the candidate drugs. The initial screen identified epigallocatechin, myricetin, rosmarinic acid, and shikonin as hits. Among these, the naphthoquinone, shikonin (5, 8-dihydroxy-2-[(1R)-1-hydroxy-4-methyl-3-pentenyl]-1,4-naphthoquinone), showed the strongest inhibition (IC50 33 µM). Further tests showed that juglone (5-hydroxy-1,4-naphthalenedione), another naphthoquinone, displayed similar potent inhibition of Mt-PTPa to shikonin. Kinetic analysis of the inhibition patterns suggests a non-competitive inhibition mechanism for both compounds, with inhibitor constants (Ki) of 8.5 µM and 12.5 µM for shikonin and juglone, respectively. Our findings are consistent with earlier studies suggesting that Mt-PTPa is susceptible to specific allosteric modulation via a non-competitive or mixed inhibition mechanism.

MDiGest: A Python package for describing allostery from molecular dynamics simulations

Many biological processes are regulated by allosteric mechanisms that communicate with distant sites in the protein responsible for functionality. The binding of a small molecule at an allosteric site typically induces conformational changes that propagate through the protein along allosteric pathways regulating enzymatic activity. Elucidating those communication pathways from allosteric sites to orthosteric sites is, therefore, essential to gain insights into biochemical processes. Targeting the allosteric pathways by mutagenesis can allow the engineering of proteins with desired functions. Furthermore, binding small molecule modulators along the allosteric pathways is a viable approach to target reactions using allosteric inhibitors/activators with temporal and spatial selectivity. Methods based on network theory can elucidate protein communication networks through the analysis of pairwise correlations observed in molecular dynamics (MD) simulations using molecular descriptors that serve as proxies for allosteric information. Typically, single atomic descriptors such as α-carbon displacements are used as proxies for allosteric information. Therefore, allosteric networks are based on correlations revealed by that descriptor. Here, we introduce a Python software package that provides a comprehensive toolkit for studying allostery from MD simulations of biochemical systems. MDiGest offers the ability to describe protein dynamics by combining different approaches, such as correlations of atomic displacements or dihedral angles, as well as a novel approach based on the correlation of Kabsch-Sander electrostatic couplings. MDiGest allows for comparisons of networks and community structures that capture physical information relevant to allostery. Multiple complementary tools for studying essential dynamics include principal component analysis, root mean square fluctuation, as well as secondary structure-based analyses.