AlloMAPS 2: allosteric fingerprints of the AlphaFold and Pfam-trRosetta predicted structures for engineering and design.

AlloMAPS 2 is an update of the Allosteric Mutation Analysis and Polymorphism of Signalling database, which contains data on allosteric communication obtained for predicted structures in the AlphaFold database (AFDB) and trRosetta-predicted Pfam domains. The data update contains Allosteric Signalling Maps (ASMs) and Allosteric Probing Maps (APMs) quantifying allosteric effects of mutations and of small probe binding, respectively. To ensure quality of the ASMs and APMs, we performed careful and accurate selection of protein sets containing high-quality predicted structures in both databases for each organism/structure, and the data is available for browsing and download. The data for remaining structures are available for download and should be used at user's discretion and responsibility. We believe these massive data can facilitate both diagnostics and drug design within the precision medicine paradigm. Specifically, it can be instrumental in the analysis of allosteric effects of pathological and rescue mutations, providing starting points for fragment-based design of allosteric effectors. The exhaustive character of allosteric signalling and probing fingerprints will be also useful in future developments of corresponding machine learning applications. The database is freely available at: http://allomaps.bii.a-star.edu.sg.

Bovine ultralong CDR-H3 derived knob paratopes elicit potent TNF-α neutralization and enable the generation of novel adalimumab-based antibody architectures with augmented features.

In this work we have generated cattle-derived chimeric ultralong CDR-H3 antibodies targeting tumor necrosis factor α (TNF-α) via immunization and yeast surface display. We identified one particular ultralong CDR-H3 paratope that potently neutralized TNF-α. Interestingly, grafting of the knob architecture onto a peripheral loop of the CH3 domain of the Fc part of an IgG1 resulted in the generation of a TNF-α neutralizing Fc (Fcknob) that did not show any potency loss compared with the parental chimeric IgG format. Eventually, grafting this knob onto the CH3 region of adalimumab enabled the engineering of a novel TNF-α targeting antibody architecture displaying augmented TNF-α inhibition.

Sequence-dependent model of allosteric communication.

The omnipresence and diversity of allosteric regulation in proteins and protein associations complemented by the potential for the design of allosterically acting biologics and drugs call for the development of a new generation of computational models for the analysis of allostery and rational engineering/design of desired signaling and effector molecules determining it. One of the most important challenges is the consideration of the role of amino acid sequence in forming the protein's allosteric communication, including the mode and strength of the allosteric signal that is communicated to the regulated functional site. Here, we present the network-based model with a sequence dependence added in consideration of allosteric communication by combining the structure-based statistical mechanical model of allostery with the Miyazawa-Jernigan residue-residue potential. Applying the model in the analysis of five classical allosteric proteins, we found that it is necessary to consider the following two major determinants: (i) the free energy exerted by the allosteric site on the regulated one and (ii) the background (average) change in dynamics of the overall structure. We show that working together these two components determine the allosteric modulation, calling one to study their dependence on structures, oligomerization states, and sequence divergence in different proteins.

AlloSigMA 2: paving the way to designing allosteric effectors and to exploring allosteric effects of mutations.

The AlloSigMA 2 server provides an interactive platform for exploring the allosteric signaling caused by ligand binding and/or mutations, for analyzing the allosteric effects of mutations and for detecting potential cancer drivers and pathogenic nsSNPs. It can also be used for searching latent allosteric sites and for computationally designing allosteric effectors for these sites with required agonist/antagonist activity. The server is based on the implementation of the Structure-Based Statistical Mechanical Model of Allostery (SBSMMA), which allows one to evaluate the allosteric free energy as a result of the perturbation at per-residue resolution. The Allosteric Signaling Map (ASM) providing a comprehensive residue-by-residue allosteric control over the protein activity can be obtained for any structure of interest. The Allosteric Probing Map (APM), in turn, allows one to perform the fragment-based-like computational design experiment aimed at finding leads for potential allosteric effectors. The server can be instrumental in elucidating of allosteric mechanisms and actions of allosteric mutations, and in the efforts on design of new elements of allosteric control. The server is freely available at: http://allosigma.bii.a-star.edu.sg.

AlloMAPS: allosteric mutation analysis and polymorphism of signaling database.

AlloMAPS database provides data on the causality and energetics of allosteric communication obtained with the structure-based statistical mechanical model of allostery (SBSMMA). The database contains data on allosteric signaling in three sets of proteins and protein chains: (i) 46 proteins with comprehensively annotated functional and allosteric sites; (ii) 1908 protein chains from PDBselect set of chains with low (<25%) sequence identity; (iii) 33 proteins with more than 50 known pathological SNPs in each molecule. In addition to energetics of allosteric signaling between known functional and regulatory sites, allosteric modulation caused by the binding to these sites, by SNPs, and by mutations designated by the user can be explored. Allosteric Signaling Maps (ASMs), which are produced via the exhaustive computational scanning for stabilizing and destabilizing mutations and for the modulation range caused by the sequence position are available for each protein/protein chain in the database. We propose to use this database for evaluating the effects of allosteric signaling in the search for latent regulatory sites and in the design of allosteric sites and effectors. The database is freely available at: http://allomaps.bii.a-star.edu.sg.

Synergistic Allostery in Multiligand-Protein Interactions.

Amide hydrogen-deuterium exchange mass spectrometry is powerful for describing combinatorial coupling effects of a cooperative ligand pair binding at noncontiguous sites: adenosine at the ATP-pocket and a docking peptide (PIFtide) at the PIF-pocket, on a model protein kinase PDK1. Binding of two ligands to PDK1 reveal multiple hotspots of synergistic allostery with cumulative effects greater than the sum of individual effects mediated by each ligand. We quantified this synergism and ranked these hotspots using a difference in deuteration-based approach, which showed that the strongest synergistic effects were observed at three of the critical catalytic loci of kinases: the αB-αC helices, and HRD-motif loop, and DFG-motif. Additionally, we observed weaker synergistic effects at a distal GHI-subdomain locus. Synergistic changes in deuterium exchange observed at a distal site but not at the intermediate sites of the large lobe of the kinase reveals allosteric propagation in proteins to operate through two modes. Direct electrostatic interactions between polar and charged amino acids that mediate targeted relay of allosteric signals, and diffused relay of allosteric signals through soft matter-like hydrophobic core amino acids. Furthermore, we provide evidence that the conserved ß-3 strand lysine of protein kinases (Lys111 of PDK1) functions as an integrator node to coordinate allosteric coupling of the two ligand-binding sites. It maintains indirect interactions with the ATP-pocket and mediates a critical salt bridge with a glutamate (Glu130) of αC helix, which is conserved across all kinases. In summary, allosteric propagation in cooperative, dual-liganded enzyme targets is bidirectional and synergistic and offers a strategy for combinatorial drug development.

Exploring chromatin hierarchical organization via Markov State Modelling.

We propose a new computational method for exploring chromatin structural organization based on Markov State Modelling of Hi-C data represented as an interaction network between genomic loci. A Markov process describes the random walk of a traveling probe in the corresponding energy landscape, mimicking the motion of a biomolecule involved in chromatin function. By studying the metastability of the associated Markov State Model upon annealing, the hierarchical structure of individual chromosomes is observed, and corresponding set of structural partitions is identified at each level of hierarchy. Then, the notion of effective interaction between partitions is derived, delineating the overall topology and architecture of chromosomes. Mapping epigenetic data on the graphs of intra-chromosomal effective interactions helps in understanding how chromosome organization facilitates its function. A sketch of whole-genome interactions obtained from the analysis of 539 partitions from all 23 chromosomes, complemented by distributions of gene expression regulators and epigenetic factors, sheds light on the structure-function relationships in chromatin, delineating chromosomal territories, as well as structural partitions analogous to topologically associating domains and active / passive epigenomic compartments. In addition to the overall genome architecture shown by effective interactions, the affinity between partitions of different chromosomes was analyzed as an indicator of the degree of association between partitions in functionally relevant genomic interactions. The overall static picture of whole-genome interactions obtained with the method presented in this work provides a foundation for chromatin structural reconstruction, for the modelling of chromatin dynamics, and for exploring the regulation of genome function. The algorithms used in this study are implemented in a freely available Python package ChromaWalker (https://bitbucket.org/ZhenWahTan/chromawalker).

Reversing allosteric communication: From detecting allosteric sites to inducing and tuning targeted allosteric response.

The omnipresence of allosteric regulation together with the fundamental role of structural dynamics in this phenomenon have initiated a great interest to the detection of regulatory exosites and design of corresponding effectors. However, despite a general consensus on the key role of dynamics most of the earlier efforts on the prediction of allosteric sites are heavily crippled by the static nature of the underlying methods, which are either structure-based approaches seeking for deep surface pockets typical for "traditional" orthosteric drugs or sequence-based techniques exploiting the conservation of protein sequences. Because of the critical role of global protein dynamics in allosteric signaling, we investigate the hypothesis of reversibility in allosteric communication, according to which allosteric sites can be detected via the perturbation of the functional sites. The reversibility is tested here using our structure-based perturbation model of allostery, which allows one to analyze the causality and energetics of allosteric communication. We validate the "reverse perturbation" hypothesis and its predictive power on a set of classical allosteric proteins, then, on the independent extended benchmark set. We also show that, in addition to known allosteric sites, the perturbation of the functional sites unravels rather extended protein regions, which can host latent regulatory exosites. These protein parts that are dynamically coupled with functional sites can also be used for inducing and tuning allosteric communication, and an exhaustive exploration of the per-residue contributions to allosteric effects can eventually lead to the optimal modulation of protein activity. The site-effector interactions necessary for a specific mode and level of allosteric communication can be fine-tuned by adjusting the site's structure to an available effector molecule and by the design or selection of an appropriate ligand.

AlloSigMA: allosteric signaling and mutation analysis server.

MOTIVATION: Allostery is an omnipresent mechanism of the function modulation in proteins via either effector binding or mutations in the exosites. Despite the growing number of online servers and databases devoted to prediction/classification of allosteric sites and their characteristics, there is a lack of resources for an efficient and quick estimation of the causality and energetics of allosteric communication. RESULTS: The AlloSigMA server implements a unique approach on the basis of the recently introduced structure-based statistical mechanical models of allosteric signaling. It provides an interactive framework for estimating the allosteric free energy as a result of the ligand(s) binding, mutation(s) and their combinations. Latent regulatory exosites and allosteric effect of mutations can be detected and explored, facilitating the research efforts in protein engineering and allosteric drug design. AVAILABILITY AND IMPLEMENTATION: The AlloSigMA server is freely available at http://allosigma.bii.a-star.edu.sg/home/. CONTACT: igorb@bii.a-star.edu.sg.

The telomere-binding protein Tbf1 demarcates snoRNA gene promoters in Saccharomyces cerevisiae.

Small nucleolar RNAs (snoRNAs) play a key role in ribosomal RNA biogenesis, yet factors controlling their expression are unknown. We found that the majority of Saccharomyces snoRNA promoters display an aRCCCTaa sequence motif at the upstream border of a TATA-containing nucleosome-free region. Genome-wide ChIP-seq analysis showed that these motifs are bound by Tbf1, a telomere-binding protein known to recognize mammalian-like T(2)AG(3) repeats at subtelomeric regions. Tbf1 has over 100 additional promoter targets, including several other genes involved in ribosome biogenesis and the TBF1 gene itself. Tbf1 is required for full snoRNA expression, yet it does not influence nucleosome positioning at snoRNA promoters. In contrast, Tbf1 contributes to nucleosome exclusion at non-snoRNA promoters, where it selectively colocalizes with the Tbf1-interacting zinc-finger proteins Vid22 and Ygr071c. Our data show that, besides the ribosomal protein gene regulator Rap1, a second telomere-binding protein also functions as a transcriptional regulator linked to yeast ribosome biogenesis.

Toward Allosterically Increased Catalytic Activity of Insulin-Degrading Enzyme against Amyloid Peptides.

The physiological role of insulin-degrading enzyme (IDE) in the intracytosolic clearance of amyloid ß (Aß) and other amyloid-like peptides supports a hypothesis that human IDE hyperactivation could be therapeutically beneficial for the treatment of late-onset Alzheimer's disease (AD). The major challenge standing in the way of this goal is increasing the specific catalytic activity of IDE against the Aß substrate. There were previous indications that the allosteric mode of IDE activity regulation could potentially provide a highly specific path toward degradation of amyloid-like peptides, while not dramatically affecting activity against other substrates. Recently developed theoretical concepts are used here to explore potential allosteric modulation of the IDE activity as a result of single-residue mutations. Five candidates are selected for experimental follow-up and allosteric free energy calculations: Ser137Ala, Lys396Ala, Asp426Ala, Phe807Ala, and Lys898Ala. Our experiments show that three mutations (Ser137Ala, Phe807Ala, and Lys898Ala) decrease the Km of the Aß substrate. Mutation Lys898Ala results in increased catalytic activity of IDE; on the other hand, Lys364Ala does not change the activity and Asp426Ala diminishes it. Quantifying effects of mutations in terms of allosteric free energy, we show that favorable mutations lead to stabilization of the catalytic sites and other function-relevant distal sites as well as increased dynamics of the IDE-N and IDE-C halves that allow efficient substrate entrance and cleavage. A possibility for intramolecular upregulation of IDE activity against amyloid peptides via allosteric mutations calls for further investigations in this direction. Ultimately, we are hopeful it will lead to the development of IDE-based drugs for the treatment of the late-onset form of AD characterized by an overall impairment of Aß clearance.

Structure-Based Statistical Mechanical Model Accounts for the Causality and Energetics of Allosteric Communication.

Allostery is one of the pervasive mechanisms through which proteins in living systems carry out enzymatic activity, cell signaling, and metabolism control. Effective modeling of the protein function regulation requires a synthesis of the thermodynamic and structural views of allostery. We present here a structure-based statistical mechanical model of allostery, allowing one to observe causality of communication between regulatory and functional sites, and to estimate per residue free energy changes. Based on the consideration of ligand free and ligand bound systems in the context of a harmonic model, corresponding sets of characteristic normal modes are obtained and used as inputs for an allosteric potential. This potential quantifies the mean work exerted on a residue due to the local motion of its neighbors. Subsequently, in a statistical mechanical framework the entropic contribution to allosteric free energy of a residue is directly calculated from the comparison of conformational ensembles in the ligand free and ligand bound systems. As a result, this method provides a systematic approach for analyzing the energetics of allosteric communication based on a single structure. The feasibility of the approach was tested on a variety of allosteric proteins, heterogeneous in terms of size, topology and degree of oligomerization. The allosteric free energy calculations show the diversity of ways and complexity of scenarios existing in the phenomenology of allosteric causality and communication. The presented model is a step forward in developing the computational techniques aimed at detecting allosteric sites and obtaining the discriminative power between agonistic and antagonistic effectors, which are among the major goals in allosteric drug design.

Optimized Markov state models for metastable systems.

A method is proposed to identify target states that optimize a metastability index amongst a set of trial states and use these target states as milestones (or core sets) to build Markov State Models (MSMs). If the optimized metastability index is small, this automatically guarantees the accuracy of the MSM, in the sense that the transitions between the target milestones is indeed approximately Markovian. The method is simple to implement and use, it does not require that the dynamics on the trial milestones be Markovian, and it also offers the possibility to partition the system's state-space by assigning every trial milestone to the target milestones it is most likely to visit next and to identify transition state regions. Here the method is tested on the Gly-Ala-Gly peptide, where it is shown to correctly identify the expected metastable states in the dihedral angle space of the molecule without a priori information about these states. It is also applied to analyze the folding landscape of the Beta3s mini-protein, where it is shown to identify the folded basin as a connecting hub between an helix-rich region, which is entropically stabilized, and a beta-rich region, which is energetically stabilized and acts as a kinetic trap.

Disrupted chromatin architecture in olfactory sensory neurons: looking for the link from COVID-19 infection to anosmia.

We tackle here genomic mechanisms of a rapid onset and recovery from anosmia-a potential diagnostic indicator for early-stage COVID-19 infection. Based on previous observations on how olfactory receptor (OR) gene expression is regulated via chromatin structure in mice, we hypothesized that the disruption of the OR gene expression and, respectively, deficiency of the OR function can be caused by chromatin reorganization taking place upon SARS-CoV-2 infection. We obtained chromatin ensemble reconstructions from COVID-19 patients and control samples using our original computational framework for the whole-genome 3D chromatin ensemble reconstruction. Specifically, we used megabase-scale structural units and effective interactions between them obtained in the Markov State modelling of the Hi-C contact network as an unput in the stochastic embedding procedure of the whole-genome 3D chromatin ensemble reconstruction. We have also developed here a new procedure for analyzing fine structural hierarchy with (sub)TAD-size units in local chromatin regions, which we apply here to parts of chromosomes containing OR genes and corresponding regulatory elements. We observed structural modifications in COVID-19 patients on different levels of chromatin organization, from the alteration of whole genome structure and chromosomal intermingling to reorganization of contacts between chromatin loops at the level of topologically associating domains. While complementary data on known regulatory elements point to potential pathology-associated changes within the overall picture of chromatin alterations, further investigation using additional epigenetic factors mapped on 3D reconstructions with improved resolution will be required for better understanding of anosmia caused by SARS-CoV-2 infection.

Molecular Modeling of the Deamidation Reaction in Solution: A Theoretical-Computational Study.

In this work, a theoretical-computational method is applied to study the deamidation reaction, a critical post-translational modification in proteins, using a simple model molecule in solution. The method allows one to comprehensively address the environmental effect, thereby enabling one to accurately derive the kinetic rate constants for the three main steps of the deamidation process. The results presented, in rather good agreement with the available experimental data, underline the necessity for a rigorous treatment of environmental factors and a precise kinetic model to correctly assess the overall kinetics of the deamidation reaction.

AI/ML combined with next-generation sequencing of VHH immune repertoires enables the rapid identification of de novo humanized and sequence-optimized single domain antibodies: a prospective case study.

Introduction: In this study, we demonstrate the feasibility of yeast surface display (YSD) and nextgeneration sequencing (NGS) in combination with artificial intelligence and machine learning methods (AI/ML) for the identification of de novo humanized single domain antibodies (sdAbs) with favorable early developability profiles. Methods: The display library was derived from a novel approach, in which VHH-based CDR3 regions obtained from a llama (Lama glama), immunized against NKp46, were grafted onto a humanized VHH backbone library that was diversified in CDR1 and CDR2. Following NGS analysis of sequence pools from two rounds of fluorescence-activated cell sorting we focused on four sequence clusters based on NGS frequency and enrichment analysis as well as in silico developability assessment. For each cluster, long short-term memory (LSTM) based deep generative models were trained and used for the in silico sampling of new sequences. Sequences were subjected to sequence- and structure-based in silico developability assessment to select a set of less than 10 sequences per cluster for production. Results: As demonstrated by binding kinetics and early developability assessment, this procedure represents a general strategy for the rapid and efficient design of potent and automatically humanized sdAb hits from screening selections with favorable early developability profiles.

Conservation and Diversity in Allosteric Fingerprints of Proteins for Evolutionary-inspired Engineering and Design.

Hand-in-hand work of physics and evolution delivered protein universe with diversity of forms, sizes, and functions. Pervasiveness and advantageous traits of allostery made it an important component of the protein function regulation, calling for thorough investigation of its structural determinants and evolution. Learning directly from nature, we explored here allosteric communication in several major folds and repeat proteins, including α/ß and ß-barrels, ß-propellers, Ig-like fold, ankyrin and α/ß leucine-rich repeat proteins, which provide structural platforms for many different enzymatic and signalling functions. We obtained a picture of conserved allosteric communication characteristic in different fold types, modifications of the structure-driven signalling patterns via sequence-determined divergence to specific functions, as well as emergence and potential diversification of allosteric regulation in multi-domain proteins and oligomeric assemblies. Our observations will be instrumental in facilitating the engineering and de novo design of proteins with allosterically regulated functions, including development of therapeutic biologics. In particular, results described here may guide the identification of the optimal structural platforms (e.g. fold type, size, and oligomerization states) and the types of diversifications/perturbations, such as mutations, effector binding, and order-disorder transition. The tunable allosteric linkage across distant regions can be used as a pivotal component in the design/engineering of modular biological systems beyond the traditional scaffolding function.

Allosteric perspective on the mutability and druggability of the SARS-CoV-2 Spike protein.

Recent developments in the SARS-CoV-2 pandemic point to its inevitable transformation into an endemic disease, urging both refinement of diagnostics for emerging variants of concern (VOCs) and design of variant-specific drugs in addition to vaccine adjustments. Exploring the structure and dynamics of the SARS-CoV-2 Spike protein, we argue that the high-mutability characteristic of RNA viruses coupled with the remarkable flexibility and dynamics of viral proteins result in a substantial involvement of allosteric mechanisms. While allosteric effects of mutations should be considered in predictions and diagnostics of new VOCs, allosteric drugs advantageously avoid escape mutations via non-competitive inhibition originating from alternative distal locations. The exhaustive allosteric signaling and probing maps presented herein provide a comprehensive picture of allostery in the spike protein, making it possible to locate potential mutations that could work as new VOC "drivers" and to determine binding patches that may be targeted by newly developed allosteric drugs.

Three-dimensional chromatin ensemble reconstruction via stochastic embedding.

We propose a comprehensive method for reconstructing the whole-genome chromatin ensemble from the Hi-C data. The procedure starts from Markov state modeling (MSM), delineating the structural hierarchy of chromatin organization with partitioning and effective interactions archetypal for corresponding levels of hierarchy. The stochastic embedding procedure introduced in this work provides the 3D ensemble reconstruction, using effective interactions obtained by the MSM as the input. As a result, we obtain the structural ensemble of a genome, allowing one to model the functional and the cell-type variability in the chromatin structure. The whole-genome reconstructions performed on the human B lymphoblastoid (GM12878) and lung fibroblast (IMR90) Hi-C data unravel distinctions in their morphologies and in the spatial arrangement of intermingling chromosomal territories, paving the way to studies of chromatin dynamics, developmental changes, and conformational transitions taking place in normal cells and during potential pathological developments.

Exploring the Allosteric Territory of Protein Function.

While the pervasiveness of allostery in proteins is commonly accepted, we further show the generic nature of allosteric mechanisms by analyzing here transmembrane ion-channel viroporin 3a and RNA-dependent RNA polymerase (RdRp) from SARS-CoV-2 along with metabolic enzymes isocitrate dehydrogenase 1 (IDH1) and fumarate hydratase (FH) implicated in cancers. Using the previously developed structure-based statistical mechanical model of allostery (SBSMMA), we share our experience in analyzing the allosteric signaling, predicting latent allosteric sites, inducing and tuning targeted allosteric response, and exploring the allosteric effects of mutations. This, yet incomplete list of phenomenology, forms a complex and unique allosteric territory of protein function, which should be thoroughly explored. We propose a generic computational framework, which not only allows one to obtain a comprehensive allosteric control over proteins but also provides an opportunity to approach the fragment-based design of allosteric effectors and drug candidates. The advantages of allosteric drugs over traditional orthosteric compounds, complemented by the emerging role of the allosteric effects of mutations in the expansion of the cancer mutational landscape and in the increased mutability of viral proteins, leave no choice besides further extensive studies of allosteric mechanisms and their biomedical implications.