Systems-level effects of allosteric perturbations to a model molecular switch

Disentangling the mutational effects on protein stability and interaction of human MLH1

Missense mutations can have diverse effects on proteins, depending on their location within the protein and the specific amino acid substitution. Mutations in the DNA mismatch repair gene MLH1 are associated with Lynch syndrome, yet the underlying mechanism of most disease-causing mutations remains elusive. To address this gap, we aim to disentangle the mutational effects on two essential properties for MLH1 function: protein stability and protein-protein interaction. We systematically examine the cellular abundance and interaction with PMS2 of 4839 (94%) MLH1 variants in the C-terminal domain. Our combined data shows that most MLH1 variants lose interaction with PMS2 due to reduced cellular abundance. However, substitutions to charged residues in the canonical interface lead to reduced interaction with PMS2. Unexpectedly, we also identify a distal region in the C-terminal domain of MLH1 where substitutions cause both decreased and increased binding with PMS2, and propose a region in PMS2 as the binding site. Our data correlate with clinical classifications of benign and pathogenic MLH1 variants and align with thermodynamic stability predictions and evolutionary conservation. This work provides mechanistic insights into variant consequences and may help interpret MLH1 variants.

Engineering a DNA polymerase for modifying large RNA at specific positions

The synthesis of large RNA with precise modifications at specific positions is in high demand for both basic research and therapeutic applications, but efficient methods are limited. Engineered DNA polymerases have recently emerged as attractive tools for RNA labelling, offering distinct advantages over conventional RNA polymerases. Here, through semi-rational designs, we engineered a DNA polymerase variant and used it to precisely incorporate a diverse range of modifications, including base modifications, 2'-ribose modifications and backbone modifications, into desired positions within RNA. We achieved efficiencies exceeding 85% in the majority of modification cases, demonstrating success in introducing 2'-O-methyl, phosphorothioate, N4-acetylcytidine and a fluorophore to specific sites in eGFP and Firefly luciferase messenger RNA. Our mRNA products with N4-acetylcytidine, 2'-O-methyl and/or phosphorothioate have demonstrated the ability to enhance stability and affect protein production. This method presents a promising tool for the comprehensive functionalization of RNA, enabling the introduction of plentiful modifications irrespective of RNA lengths and sequences.

Biochemistry and genetics are coming together to improve our understanding of genotype to phenotype relationships

Since genome sequencing became accessible, determining how specific differences in genotypes lead to complex phenotypes such as disease has become one of the key goals in biomedicine. Predicting effects of sequence variants on cellular or organismal phenotype faces several challenges. First, variants simultaneously affect multiple protein properties and predicting their combined effect is complex. Second, effects of changes in a single protein propagate through the cellular network, which we only partially understand. In this review, we emphasize the importance of both biochemistry and genetics in addressing these challenges. Moreover, we highlight work that blurs the distinction between biochemistry and genetics fields to provide new insights into the genotype-to-phenotype relationships.

Pathogenic single nucleotide polymorphisms in RhoA gene: Insights into structural and functional impacts on RhoA-PLD1 interaction through molecular dynamics simulation

Molecular switches serve as key regulators of biological systems by acting as one of the crucial driving forces in the initiation of signal transduction pathway cascades. The Ras homolog gene family member A (RhoA) is one of the molecular switches that binds with GTP in order to cycle between an active GTP-bound state and an inactive GDP-bound state. Any aberrance in control over this circuit, particularly due to any perturbation in switching, leads to the development of different pathogenicity. Consequently, the single nucleotide polymorphisms (SNPs) within the RhoA gene, especially deleterious genetic variations, are crucial to study to forecast structural alteration and their functional impacts in light of disease onset. In this comprehensive study, we employed a range of computational tools to screen the deleterious SNPs of RhoA from 207 nonsynonymous SNPs (nsSNPs). By utilizing 7 distinct tools for further analysis, 8 common deleterious SNPs were sorted, among them 5 nsSNPs (V9G, G17E, E40K, A61T, F171L) were found to be in the highly conserved regions, with E40K and A61T at G2 and G3 motif of the GTP-binding domain respectively, indicating potential perturbation in GTP/GDP binding ability of the protein. RhoA-GDP complex interacts with the enzyme phospholipase, specifically PLD1, to regulate different cellular activities. PLD1 is also a crucial regulator of thrombosis and cancer. In that line of focus, our initial structural analysis of Y66H, A61T, G17E, I86N, and I151T mutations of RhoA revealed remarkable decreased hydrophobicity from which we further filtered out G17E and I86N which may have potential impact on the RhoA-GDP-PLD1 complex. Intriguingly, the comparative 250 ns (ns) molecular dynamics (MD) simulation of these two mutated complexes revealed overall structural instability and altered interaction patterns. Therefore, further investigation into these deleterious mutations with in vitro and in vivo studies could lead to the identification of potential biomarkers in terms of different pathogenesis and could also be utilized in personalized therapeutic targets in the long run.

The art of designed coiled-coils for the regulation of mammalian cells

Synthetic biology aims to engineer complex biological systems using modular elements, with coiled-coil (CC) dimer-forming modules are emerging as highly useful building blocks in the regulation of protein assemblies and biological processes. Those small modules facilitate highly specific and orthogonal protein-protein interactions, offering versatility for the regulation of diverse biological functions. Additionally, their design rules enable precise control and tunability over these interactions, which are crucial for specific applications. Recent advancements showcase their potential for use in innovative therapeutic interventions and biomedical applications. In this review, we discuss the potential of CCs, exploring their diverse applications in mammalian cells, such as synthetic biological circuit design, transcriptional and allosteric regulation, cellular assemblies, chimeric antigen receptor (CAR) T cell regulation, and genome editing and their role in advancing the understanding and regulation of cellular processes.

The energetic and allosteric landscape for KRAS inhibition

Thousands of proteins have been validated genetically as therapeutic targets for human diseases1. However, very few have been successfully targeted, and many are considered 'undruggable'. This is particularly true for proteins that function via protein-protein interactions-direct inhibition of binding interfaces is difficult and requires the identification of allosteric sites. However, most proteins have no known allosteric sites, and a comprehensive allosteric map does not exist for any protein. Here we address this shortcoming by charting multiple global atlases of inhibitory allosteric communication in KRAS. We quantified the effects of more than 26,000 mutations on the folding of KRAS and its binding to six interaction partners. Genetic interactions in double mutants enabled us to perform biophysical measurements at scale, inferring more than 22,000 causal free energy changes. These energy landscapes quantify how mutations tune the binding specificity of a signalling protein and map the inhibitory allosteric sites for an important therapeutic target. Allosteric propagation is particularly effective across the central β-sheet of KRAS, and multiple surface pockets are genetically validated as allosterically active, including a distal pocket in the C-terminal lobe of the protein. Allosteric mutations typically inhibit binding to all tested effectors, but they can also change the binding specificity, revealing the regulatory, evolutionary and therapeutic potential to tune pathway activation. Using the approach described here, it should be possible to rapidly and comprehensively identify allosteric target sites in many proteins.

Designed allosteric protein logic

The regulation of protein function by external or internal signals is one of the key features of living organisms. The ability to directly control the function of a selected protein would represent a valuable tool for regulating biological processes. Here, we present a generally applicable regulation of proteins called INSRTR, based on inserting a peptide into a loop of a target protein that retains its function. We demonstrate the versatility and robustness of coiled-coil-mediated regulation, which enables designs for either inactivation or activation of selected protein functions, and implementation of two-input logic functions with rapid response in mammalian cells. The selection of insertion positions in tested proteins was facilitated by using a predictive machine learning model. We showcase the robustness of the INSRTR strategy on proteins with diverse folds and biological functions, including enzymes, signaling mediators, DNA binders, transcriptional regulators, reporters, and antibody domains implemented as chimeric antigen receptors in T cells. Our findings highlight the potential of INSRTR as a powerful tool for precise control of protein function, advancing our understanding of biological processes and developing biotechnological and therapeutic interventions.

Emerging maps of allosteric regulation in cellular networks

Allosteric regulation is classically defined as action at a distance, where a perturbation outside of a protein active site affects function. While this definition has motivated many studies of allosteric mechanisms at the level of protein structure, translating these insights to the allosteric regulation of entire cellular processes - and their crosstalk - has received less attention, despite the broad importance of allostery for cellular regulation foreseen by Jacob and Monod. Here, we revisit an evolutionary model for the widespread emergence of allosteric regulation in colocalized proteins, describe supporting evidence, and discuss emerging advances in mapping allostery in cellular networks that link precise and often allosteric perturbations at the molecular level to functional changes at the pathway and systems levels.

Recent breakthroughs in computational structural biology harnessing the power of sequences and structures

Recent advances in computational approaches and their integration into structural biology enable tackling increasingly complex questions. Here, we discuss several key areas, highlighting breakthroughs and remaining challenges. Theoretical modeling has provided tools to accurately predict and design protein structures on a scale currently difficult to achieve using experimental approaches. Molecular Dynamics simulations have become faster and more precise, delivering actionable information inaccessible by current experimental methods. Virtual screening workflows allow a high-throughput approach to discover ligands that bind and modulate protein function, while Machine Learning methods enable the design of proteins with new functionalities. Integrative structural biology combines several of these approaches, pushing the frontiers of structural and functional characterization to ever larger systems, advancing towards a complete understanding of the living cell. These breakthroughs will accelerate and significantly impact diverse areas of science.

A complete allosteric map of a GTPase switch in its native cellular network

Allosteric regulation is central to protein function in cellular networks. A fundamental open question is whether cellular regulation of allosteric proteins occurs only at a few defined positions or at many sites distributed throughout the structure. Here, we probe the regulation of GTPases-protein switches that control signaling through regulated conformational cycling-at residue-level resolution by deep mutagenesis in the native biological network. For the GTPase Gsp1/Ran, we find that 28% of the 4,315 assayed mutations show pronounced gain-of-function responses. Twenty of the sixty positions enriched for gain-of-function mutations are outside the canonical GTPase active site switch regions. Kinetic analysis shows that these distal sites are allosterically coupled to the active site. We conclude that the GTPase switch mechanism is broadly sensitive to cellular allosteric regulation. Our systematic discovery of new regulatory sites provides a functional map to interrogate and target GTPases controlling many essential biological processes.

From systems to structure - using genetic data to model protein structures

Understanding the effects of genetic variation is a fundamental problem in biology that requires methods to analyse both physical and functional consequences of sequence changes at systems-wide and mechanistic scales. To achieve a systems view, protein interaction networks map which proteins physically interact, while genetic interaction networks inform on the phenotypic consequences of perturbing these protein interactions. Until recently, understanding the molecular mechanisms that underlie these interactions often required biophysical methods to determine the structures of the proteins involved. The past decade has seen the emergence of new approaches based on coevolution, deep mutational scanning and genome-scale genetic or chemical-genetic interaction mapping that enable modelling of the structures of individual proteins or protein complexes. Here, we review the emerging use of large-scale genetic datasets and deep learning approaches to model protein structures and their interactions, and discuss the integration of structural data from different sources.

Diverse Molecular Mechanisms Underlying Pathogenic Protein Mutations: Beyond the Loss-of-Function Paradigm

Most known disease-causing mutations occur in protein-coding regions of DNA. While some of these involve a loss of protein function (e.g., through premature stop codons or missense changes that destabilize protein folding), many act via alternative molecular mechanisms and have dominant-negative or gain-of-function effects. In nearly all cases, these non-loss-of-function mutations can be understood by considering interactions of the wild-type and mutant protein with other molecules, such as proteins, nucleic acids, or small ligands and substrates. Here, we review the diverse molecular mechanisms by which pathogenic mutations can have non-loss-of-function effects, including by disrupting interactions, increasing binding affinity, changing binding specificity, causing assembly-mediated dominant-negative and dominant-positive effects, creating novel interactions, and promoting aggregation and phase separation. We believe that increased awareness of these diverse molecular disease mechanisms will lead to improved diagnosis (and ultimately treatment) of human genetic disorders. Expected final online publication date for the Annual Review of Genomics and Human Genetics, Volume 23 is October 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.