Discovery of substrates for a SET domain lysine methyltransferase predicted by multistate computational protein design

Approaching the catalytic mechanism of protein lysine methyltransferases by biochemical and simulation techniques

Protein lysine methyltransferases (PKMTs) transfer up to three methyl groups to the side chains of lysine residues in proteins and fulfill important regulatory functions by controlling protein stability, localization and protein/protein interactions. The methylation reactions are highly regulated, and aberrant methylation of proteins is associated with several types of diseases including neurologic disorders, cardiovascular diseases, and various types of cancer. This review describes novel insights into the catalytic machinery of various PKMTs achieved by the combined application of biochemical experiments and simulation approaches during the last years, focusing on clinically relevant and well-studied enzymes of this group like DOT1L, SMYD1-3, SET7/9, G9a/GLP, SETD2, SUV420H2, NSD1/2, different MLLs and EZH2. Biochemical experiments have unraveled many mechanistic features of PKMTs concerning their substrate and product specificity, processivity and the effects of somatic mutations observed in PKMTs in cancer cells. Structural data additionally provided information about the substrate recognition, enzyme-substrate complex formation, and allowed for simulations of the substrate peptide interaction and mechanism of PKMTs with atomistic resolution by molecular dynamics and hybrid quantum mechanics/molecular mechanics methods. These simulation technologies uncovered important mechanistic details of the PKMT reaction mechanism including the processes responsible for the deprotonation of the target lysine residue, essential conformational changes of the PKMT upon substrate binding, but also rationalized regulatory principles like PKMT autoinhibition. Further developments are discussed that could bring us closer to a mechanistic understanding of catalysis of this important class of enzymes in the near future. The results described here illustrate the power of the investigation of enzyme mechanisms by the combined application of biochemical experiments and simulation technologies.

PeSA 2.0: A software tool for peptide specificity analysis implementing positive and negative motifs and motif-based peptide scoring

There are a vast number of molecular interactions that occur at the cellular level. Among these molecular interactions, interactions between multiple proteins are a widely studied area of research due to the importance of these interactions in cellular function and their potential in drug development. PeSA is a desktop application developed to facilitate the in vitro peptide study analysis to predict protein-protein interactions. PeSA can effortlessly generate visual outputs like motifs, bar charts, and visual matrices. Our implementation of PeSA version 2.0 includes additional tools, including the ability to further score peptide lists for consensus amongst interactions. The software is also able to design de novo peptides based on sequence motifs (sequence generator), which can be used to help design additional experiments for motif validation. Further, the efficacy of the sequence generator was validated using the lysine methyltransferase, SETD8, to identify new substrates of methylation based on motif-based predictions developed using PeSA2.0.

Protein Lysine Methyltransferase SMYD2: A Promising Small Molecule Target for Cancer Therapy

In epigenetic research, the abnormality of protein methylation modification is closely related to the occurrence and development of tumors, which stimulates the interest of researchers in protein methyltransferase research and the efforts to develop corresponding specific small molecule inhibitors. Currently, the protein lysine methyltransferase SMYD2 has been identified as a promising new small molecule target for cancer therapy. But its biological functions have not been fully studied and relatively few inhibitors have been reported, thus this field needs to be further explored. This perspective provides a comprehensive and systematic review of the available resources in this field, including its research status, biological structure, related substrates and methylation mechanisms, and research status of inhibitors. In addition, this perspective elaborates in detail the current challenges in this field, our insights into what needs to be done next, rational drug design of novel SMYD2 inhibitors, and foreseeable development directions in the future.

Evaluation of Jumonji C lysine demethylase substrate preference to guide identification of in vitro substrates

Within the realm of lysine methylation, the discovery of lysine methyltransferase (KMTs) substrates has been burgeoning because of established systematic substrate screening protocols. Here, we describe a protocol enabling the systematic identification of JmjC KDM substrate preference and in vitro substrates. Systematically designed peptide libraries containing methylated lysine residues are used to characterize enzyme-substrate preference and identify new candidate substrates in vitro.

For complete details on the use and execution of this protocol, please refer to Hoekstra and Biggar (2021).

•

Use of a permutated substrate library to define JmjC KDM recognition motifs

•

JmjC KDM activity is measured via luminescent detection of succinate

•

Recognition motifs enable prediction of novel in vitro substrates of JmjC KDMs

Insights into a Cancer-Target Demethylase: Substrate Prediction through Systematic Specificity Analysis for KDM3A

Jumonji C (JmjC) lysine demethylases (KDMs) catalyze the removal of methyl (-CH₃) groups from modified lysyl residues. Several JmjC KDMs promote cancerous properties and these findings have primarily been in relation to histone demethylation. However, the biological roles of these enzymes are increasingly being shown to also be attributed to non-histone demethylation. Notably, KDM3A has become relevant to tumour progression due to recent findings of this enzyme's role in promoting cancerous phenotypes, such as enhanced glucose consumption and upregulated mechanisms of chemoresistance. To aid in uncovering the mechanism(s) by which KDM3A imparts its oncogenic function(s), this study aimed to unravel KDM3A substrate specificity to predict high-confidence substrates. Firstly, substrate specificity was assessed by monitoring activity towards a peptide permutation library of histone H3 di-methylated at lysine-9 (i.e., H3K9me2). From this, the KDM3A recognition motif was established and used to define a set of high-confidence predictions of demethylation sites from within the KDM3A interactome. Notably, this led to the identification of three in vitro substrates (MLL1, p300, and KDM6B), which are relevant to the field of cancer progression. This preliminary data may be exploited in further tissue culture experiments to decipher the avenues by which KDM3A imparts cancerous phenotypes.

Specificity Analysis of Protein Methyltransferases and Discovery of Novel Substrates Using SPOT Peptide Arrays

Posttranslational methylation of amino acid side chains in proteins mainly occurs on lysine, arginine, glutamine, and histidine residues. It is introduced by different protein methyltransferases (PMTs) and regulates many aspects of protein function including stability, activity, localization, and protein/protein interactions. Although the biological effects of PMTs are mediated by their methylation substrates, the full substrate spectrum of most PMTs is not known. For many PMTs, their activity on a particular potential substrate depends, among other factors, on the peptide sequence containing the target residue for methylation. In this protocol, we describe the application of SPOT peptide arrays to investigate the substrate specificity of PMTs and identify novel substrates. Methylation of SPOT peptide arrays makes it possible to study the methylation of many different peptides in one experiment at reasonable costs and thereby provides detailed information about the specificity of the PMT under investigation. In these experiments, a known substrate sequence is used as template to design a SPOT peptide array containing peptides with single amino acid exchanges at all positions of the sequence. Methylation of the array with the PMT provides detailed preferences for each amino acid at each position in the substrate sequence, yielding a substrate sequence specificity profile. This information can then be used to identify novel potential PMT substrates by in silico data base searches. Methylation of novel substrate candidates can be validated in SPOT arrays at peptide level, followed by validation at protein level in vitro and in cells.

Deconvoluting complex protein interaction networks through reductionist strategies in peptide biochemistry: Modern approaches and research questions

Following the decoding of the first human genome, researchers have vastly improved their understanding of cell biology and its regulation. As a result, it has become clear that it is not merely genetic information, but the aberrant changes in the functionality and connectivity of its encoded proteins that drive cell response to periods of stress and external cues. Therefore, proper utilization of refined methods that help to describe protein signalling or regulatory networks (i.e., functional connectivity), can help us understand how change in the signalling landscape effects the cell. However, given the vast complexity in 'how and when' proteins communicate or interact with each other, it is extremely difficult to define, characterize, and understand these interaction networks in a tangible manner. Herein lies the challenge of tackling the functional proteome; its regulation is encoded in multiple layers of interaction, chemical modification and cell compartmentalization. To address and refine simple research questions, modern reductionist strategies in protein biochemistry have successfully used peptide-based experiments; their summation helping to simplify the overall complexity of these protein interaction networks. In this way, peptides are powerful tools used in fundamental research that can be readily applied to comparative biochemical research. Understanding and defining how proteins interact is one of the key aspects towards understanding how the proteome functions. To date, reductionist peptide-based research has helped to address a wide range of proteome-related research questions, including the prediction of enzymes substrates, identification of posttranslational modifications, and the annotation of protein interaction partners. Peptide arrays have been used to identify the binding specificity of reader domains, which are able to recognise the posttranslational modifications; forming dynamic protein interactions that are dependent on modification state. Finally, representing one of the fastest growing classes of inhibitor molecules, peptides are now begin explored as "disruptors" of protein-protein interactions or enzyme activity. Collectively, this review will discuss the use of peptides, peptide arrays, peptide-oriented computational biochemistry as modern reductionist strategies in deconvoluting the functional proteome.

Lysine Methylation Regulators Moonlighting outside the Epigenome

Landmark discoveries made nearly two decades ago identified known transcriptional regulators as histone lysine methyltransferases. Since then, the field of lysine methylation signaling has been dominated by studies of how this small chemical posttranslational modification regulates gene expression and other chromatin-based processes. However, recent advances in mass-spectrometry-based proteomics have revealed that histones are just a subset of the thousands of eukaryotic proteins marked by lysine methylation. As the writers, erasers, and readers of histone lysine methylation are emerging as a promising therapeutic target class for cancer and other diseases, a key challenge for the field is to define the full spectrum of activities for these proteins. Here we summarize recent discoveries implicating non-histone lysine methylation as a major regulator of diverse cellular processes. We further discuss recent technological innovations that are enabling the expanded study of lysine methylation signaling. Collectively, these findings are shaping our understanding of the fundamental mechanisms of non-histone protein regulation through this dynamic and multi-functional posttranslational modification.

Exploration of the Substrate Preference of Lysine Methyltransferase SMYD3 by Molecular Dynamics Simulations

SMYD3, a SET and MYND domain containing lysine methyltransferase, catalyzes the transfer of the methyl group from a methyl donor onto the Nε group of a lysine residue in the substrate protein. Methylation of MAP3 kinase kinase (MAP3K2) by SMYD3 has been implicated in Ras-driven tumorigenesis. The crystal structure of SMYD3 in complex with MAP3K2 peptide reveals a shallow hydrophobic pocket (P-2), which accommodates the binding of a phenylalanine residue at the -2 position of the substrate (F258) is a crucial determinant of substrate specificity of SMYD3. To better understand the substrate preference of SMYD3 at the -2 position, molecular dynamics (MD) simulations and the MM/GBSA method were performed on the crystal structure of SMYD3-MAP3K2 complex (PDB: 5EX0) after substitution of F258 residue of MAP3K2 to each of the other 19 natural residues, respectively. Binding free energy calculations reveal that the P-2 pocket prefers an aromatic hydrophobic group and none of the substitutions behave better than the wild-type phenylalanine residue does. Furthermore, we investigated the structure-activity relationships (SAR) of a series of non-natural phenylalanine derivative substitutions at the -2 position and found that quite a few modifications on the sidechain of F258 residue could strengthen its binding to the P-2 pocket of SMYD3. These explorations provide insights into developing novel SMYD3 inhibitors with high potency and high selectivity against MAP3K2 and cancer.

Analysis of the Substrate Specificity of the SMYD2 Protein Lysine Methyltransferase and Discovery of Novel Non-Histone Substrates

The SMYD2 protein lysine methyltransferase methylates various histone and non‐histone proteins and is overexpressed in several cancers. Using peptide arrays, we investigated the substrate specificity of the enzyme, revealing a recognition of leucine (or weaker phenylalanine) at the −1 peptide site and disfavor of acidic residues at the +1 to +3 sites. Using this motif, novel SMYD2 peptide substrates were identified, leading to the discovery of 32 novel peptide substrates with a validated target site. Among them, 19 were previously reported to be methylated at the target lysine in human cells, strongly suggesting that SMYD2 is the protein lysine methyltransferase responsible for this activity. Methylation of some of the novel peptide substrates was tested at the protein level, leading to the identification of 14 novel protein substrates of SMYD2, six of which were more strongly methylated than p53, the best SMYD2 substrate described so far. The novel SMYD2 substrate proteins are involved in diverse biological processes such as chromatin regulation, transcription, and intracellular signaling. The results of our study provide a fundament for future investigations into the role of this important enzyme in normal development and cancer.

Lysine methylation signaling of non-histone proteins in the nucleus

Lysine methylation, catalyzed by protein lysine methyltransferases (PKMTs), is a central post-translational modification regulating many signaling pathways. It has direct and indirect effects on chromatin structure and transcription. Accumulating evidence suggests that dysregulation of PKMT activity has a fundamental impact on the development of many pathologies. While most of these works involve in-depth analysis of methylation events in the context of histones, in recent years, it has become evident that methylation of non-histone proteins also plays a pivotal role in cell processes. This review highlights the importance of non-histone methylation, with focus on methylation events taking place in the nucleus. Known experimental platforms which were developed to identify new methylation events, as well as examples of specific lysine methylation signaling events which regulate key transcription factors, are presented. In addition, the role of these methylation events in normal and disease states is emphasized.

A functional proteomics platform to reveal the sequence determinants of lysine methyltransferase substrate selectivity

Lysine methylation is a key regulator of histone protein function. Beyond histones, few connections have been made to the enzymes responsible for the deposition of these posttranslational modifications. Here, we debut a high-throughput functional proteomics platform that maps the sequence determinants of lysine methyltransferase (KMT) substrate selectivity without a priori knowledge of a substrate or target proteome. We demonstrate the predictive power of this approach for identifying KMT substrates, generating scaffolds for inhibitor design, and predicting the impact of missense mutations on lysine methylation signaling. By comparing KMT selectivity profiles to available lysine methylome datasets, we reveal a disconnect between preferred KMT substrates and the ability to detect these motifs using standard mass spectrometry pipelines. Collectively, our studies validate the use of this platform for guiding the study of lysine methylation signaling and suggest that substantial gaps exist in proteome-wide curation of lysine methylomes.

Chemical and Biochemical Perspectives of Protein Lysine Methylation

Protein lysine methylation is a distinct posttranslational modification that causes minimal changes in the size and electrostatic status of lysine residues. Lysine methylation plays essential roles in regulating fates and functions of target proteins in an epigenetic manner. As a result, substrates and degrees (free versus mono/di/tri) of protein lysine methylation are orchestrated within cells by balanced activities of protein lysine methyltransferases (PKMTs) and demethylases (KDMs). Their dysregulation is often associated with neurological disorders, developmental abnormalities, or cancer. Methyllysine-containing proteins can be recognized by downstream effector proteins, which contain methyllysine reader domains, to relay their biological functions. While numerous efforts have been made to annotate biological roles of protein lysine methylation, limited work has been done to uncover mechanisms associated with this modification at a molecular or atomic level. Given distinct biophysical and biochemical properties of methyllysine, this review will focus on chemical and biochemical aspects in addition, recognition, and removal of this posttranslational mark. Chemical and biophysical methods to profile PKMT substrates will be discussed along with classification of PKMT inhibitors for accurate perturbation of methyltransferase activities. Semisynthesis of methyllysine-containing proteins will also be covered given the critical need for these reagents to unambiguously define functional roles of protein lysine methylation.

The Smyd Family of Methyltransferases: Role in Cardiac and Skeletal Muscle Physiology and Pathology

Protein methylation plays a pivotal role in the regulation of various cellular processes including chromatin remodeling and gene expression. SET and MYND domain-containing proteins (Smyd) are a special class of lysine methyltransferases whose catalytic SET domain is split by an MYND domain. The hallmark feature of this family was thought to be the methylation of histone H3 (on lysine 4). However, several studies suggest that the role of the Smyd family is dynamic, targeting unique histone residues associated with both transcriptional activation and repression. Smyd proteins also methylate several non-histone proteins to regulate various cellular processes. Although we are only beginning to understand their specific molecular functions and role in chromatin remodeling, recent studies have advanced our understanding of this relatively uncharacterized family, highlighting their involvement in development, cell growth and differentiation and during disease in various animal models. This review summarizes our current knowledge of the structure, function and methylation targets of the Smyd family and provides a compilation of data emphasizing their prominent role in cardiac and skeletal muscle physiology and pathology.

SMYD2 lysine methyltransferase regulates leukemia cell growth and regeneration after genotoxic stress

The molecular determinants governing escape of Acute Myeloid Leukemia (AML) cells from DNA damaging therapy remain poorly defined and account for therapy failures. To isolate genes responsible for leukemia cells regeneration following multiple challenges with irradiation we performed a genome-wide shRNA screen. Some of the isolated hits are known players in the DNA damage response (e.g. p53, CHK2), whereas other, e.g. SMYD2 lysine methyltransferase (KMT), remains uncharacterized in the AML context. Here we report that SMYD2 knockdown confers relative resistance to human AML cells against multiple classes of DNA damaging agents. Induction of the transient quiescence state upon SMYD2 downregulation correlated with the resistance. We revealed that diminished SMYD2 expression resulted in the upregulation of the related methyltransferase SET7/9, suggesting compensatory relationships. Indeed, pharmacological targeting of SET7/9 with (R)-PFI2 inhibitor preferentially inhibited the growth of cells expressing low levels of SMYD2.

Finally, decreased expression of SMYD2 in AML patients correlated with the reduced sensitivity to therapy and lower probability to achieve complete remission. We propose that the interplay between SMYD2 and SET7/9 levels shifts leukemia cells from growth to quiescence state that is associated with the higher resistance to DNA damaging agents and rationalize SET7/9 pharmacological targeting in AML.

MFPred: Rapid and accurate prediction of protein-peptide recognition multispecificity using self-consistent mean field theory

Multispecificity-the ability of a single receptor protein molecule to interact with multiple substrates-is a hallmark of molecular recognition at protein-protein and protein-peptide interfaces, including enzyme-substrate complexes. The ability to perform structure-based prediction of multispecificity would aid in the identification of novel enzyme substrates, protein interaction partners, and enable design of novel enzymes targeted towards alternative substrates. The relatively slow speed of current biophysical, structure-based methods limits their use for prediction and, especially, design of multispecificity. Here, we develop a rapid, flexible-backbone self-consistent mean field theory-based technique, MFPred, for multispecificity modeling at protein-peptide interfaces. We benchmark our method by predicting experimentally determined peptide specificity profiles for a range of receptors: protease and kinase enzymes, and protein recognition modules including SH2, SH3, MHC Class I and PDZ domains. We observe robust recapitulation of known specificities for all receptor-peptide complexes, and comparison with other methods shows that MFPred results in equivalent or better prediction accuracy with a ~10-1000-fold decrease in computational expense. We find that modeling bound peptide backbone flexibility is key to the observed accuracy of the method. We used MFPred for predicting with high accuracy the impact of receptor-side mutations on experimentally determined multispecificity of a protease enzyme. Our approach should enable the design of a wide range of altered receptor proteins with programmed multispecificities.

Conformational Dynamics of Lysine Methyltransferase Smyd2. Insights into the Different Substrate Crevice Characteristics of Smyd2 and Smyd3

Smyd2, the SET and MYND domain containing protein lysine methyltransferase, targets histone and nonhistone substrates. Methylation of nonhistone substrates has direct implications in cancer development and progression. Dynamic regulation of Smyd2 activity and the structural basis of broad substrate specificity still remain elusive. Herein, we report on extensive molecular dynamics simulations on a full length Smyd2 in the presence and absence of AdoMet cofactor (covering together 1.3 μs of sampling), and the accompanying conformational transitions. Additionally, dynamics of the C-terminal domain (CTD) and structural features of substrate crevices of Smyd2 and Smyd3 are compared. The CTD of Smyd2 exhibits conformational flexibility in both states. In the holo form, however, it undergoes larger hinge motions resulting in more opened configurations than the apo form, which is confined around the partially open starting X-ray configuration. AdoMet binding triggers increased elasticity of the CTD leading Smyd2 to adopt fully opened configurations, which completely exposes the substrate binding crevice. These long-range concerted motions highlight Smyd2's ability to target substrates of varying sizes. Substrate crevices of Smyd2 and Smyd3 show distinct features in terms of spatial, hydration, and electrostatic properties that emphasize their characteristic modes of substrates interaction and entry pathways for inhibitor binding. On the whole, our study shows how the elasticity and hinge motion of the CTD regulate its functional role and underpin the basis of broad substrate specificity of Smyd2. We also highlight the specific structural principles that guide substrate and inhibitor binding to Smyd2 and Smyd3.

A charge-suppressing strategy for probing protein methylation

Methylation of arginine and lysine (RK) residues play essential roles in epigenetics and the regulation of gene expression. However, research in this area is often hindered by the lack of effective tools for probing the protein methylation. Here, we present an antibody-free strategy to capture protein methylation on RK residues by using chemical reactions to eliminate the charges on un-modified RK residues and peptide N-termini. Peptides containing methylated RK residues remain positively charged and are then enriched by strong cation exchange chromatography, followed by high-resolution mass spectrometry identification.

Large-Scale Structure-Based Prediction and Identification of Novel Protease Substrates Using Computational Protein Design

Characterizing the substrate specificity of protease enzymes is critical for illuminating the molecular basis of their diverse and complex roles in a wide array of biological processes. Rapid and accurate prediction of their extended substrate specificity would also aid in the design of custom proteases capable of selectively and controllably cleaving biotechnologically or therapeutically relevant targets. However, current in silico approaches for protease specificity prediction, rely on, and are therefore limited by, machine learning of sequence patterns in known experimental data. Here, we describe a general approach for predicting peptidase substrates de novo using protein structure modeling and biophysical evaluation of enzyme-substrate complexes. We construct atomic resolution models of thousands of candidate substrate-enzyme complexes for each of five model proteases belonging to the four major protease mechanistic classes-serine, cysteine, aspartyl, and metallo-proteases-and develop a discriminatory scoring function using enzyme design modules from Rosetta and AMBER's MMPBSA. We rank putative substrates based on calculated interaction energy with a modeled near-attack conformation of the enzyme active site. We show that the energetic patterns obtained from these simulations can be used to robustly rank and classify known cleaved and uncleaved peptides and that these structural-energetic patterns have greater discriminatory power compared to purely sequence-based statistical inference. Combining sequence and energetic patterns using machine-learning algorithms further improves classification performance, and analysis of structural models provides physical insight into the structural basis for the observed specificities. We further tested the predictive capability of the model by designing and experimentally characterizing the cleavage of four novel substrate motifs for the hepatitis C virus NS3/4 protease using an in vivo assay. The presented structure-based approach is generalizable to other protease enzymes with known or modeled structures, and complements existing experimental methods for specificity determination.

Approaches and Guidelines for the Identification of Novel Substrates of Protein Lysine Methyltransferases

Protein lysine methylation is emerging as a general post-translational modification (PTM) with essential functions regulating protein stability, activity, and protein-protein interactions. One of the outstanding challenges in this field is linking protein lysine methyltransferases (PKMTs) with specific substrates and lysine methylation events in a systematic manner. Inability to validate reported PKMT substrates delayed progress in the field and cast unnecessary doubt about protein lysine methylation as a truly general PTM. Here, we aim to provide a concise guide to help avoid some of the most common pitfalls in studies searching for new PKMT substrates and propose a set of seven basic biochemical rules: (1) include positive controls; (2) use target lysine mutations of substrate proteins as negative controls; (3) use inactive enzyme variants as negative controls; (4) report quantitative methylation data; (5) consider PKMT specificity; (6) validate methyl lysine antibodies; and (7) connect cellular and in vitro results. We explain the logic behind them and discuss how they should be implemented in the experimental work.

Computational protein design for given backbone: recent progresses in general method-related aspects

To achieve high success rate in protein design requires a reliable sequence design method to find amino acid sequences that stably fold into a desired backbone structure. This problem is addressed by computational protein design through the approach of energy minimization. Here we review recent method progresses related to improving the accuracy of this approach. First, the quality of the energy model is a key factor. Second, with structure sensitive energy functions, whether and how backbone flexibility is considered can have large effects on design accuracy, although usually only small adjustments of the backbone structure itself are involved. Third, the effective accuracy of design results can be boosted by post-processing a small number of designed sequences with complementary models that may not be efficient enough for full sequence optimization. Finally, computational method development will benefit greatly from increasingly efficient experimental approaches that can be applied to obtain extensive feedbacks.

Quantitative Profiling of the Activity of Protein Lysine Methyltransferase SMYD2 Using SILAC-Based Proteomics

The significance of non-histone lysine methylation in cell biology and human disease is an emerging area of research exploration. The development of small molecule inhibitors that selectively and potently target enzymes that catalyze the addition of methyl-groups to lysine residues, such as the protein lysine mono-methyltransferase SMYD2, is an active area of drug discovery. Critical to the accurate assessment of biological function is the ability to identify target enzyme substrates and to define enzyme substrate specificity within the context of the cell. Here, using stable isotopic labeling with amino acids in cell culture (SILAC) coupled with immunoaffinity enrichment of mono-methyl-lysine (Kme1) peptides and mass spectrometry, we report a comprehensive, large-scale proteomic study of lysine mono-methylation, comprising a total of 1032 Kme1 sites in esophageal squamous cell carcinoma (ESCC) cells and 1861 Kme1 sites in ESCC cells overexpressing SMYD2. Among these Kme1 sites is a subset of 35 found to be potently down-regulated by both shRNA-mediated knockdown of SMYD2 and LLY-507, a selective small molecule inhibitor of SMYD2. In addition, we report specific protein sequence motifs enriched in Kme1 sites that are directly regulated by endogenous SMYD2 activity, revealing that SMYD2 substrate specificity is more diverse than expected. We further show direct activity of SMYD2 toward BTF3-K2, PDAP1-K126 as well as numerous sites within the repetitive units of two unique and exceptionally large proteins, AHNAK and AHNAK2. Collectively, our findings provide quantitative insights into the cellular activity and substrate recognition of SMYD2 as well as the global landscape and regulation of protein mono-methylation.

Protein sequence design and its applications

Design of proteins has far-reaching potentials in diverse areas that span repurposing of the protein scaffold for reactions and substrates that they were not naturally meant for, to catching a glimpse of the ephemeral proteins that nature might have sampled during evolution. These non-natural proteins, either in synthesized or virtual form have opened the scope for the design of entities that not only rival their natural counterparts but also offer a chance to visualize the protein space continuum that might help to relate proteins and understand their associations. Here, we review the recent advances in protein engineering and design, in multiple areas, with a view to drawing attention to their future potential.