Rigid substructure search

mRNA vaccines for cancer immunotherapy

Immunotherapy has emerged as a breakthrough strategy in cancer treatment. mRNA vaccines are an attractive and powerful immunotherapeutic platform against cancer because of their high potency, specificity, versatility, rapid and large-scale development capability, low-cost manufacturing potential, and safety. Recent technological advances in mRNA vaccine design and delivery have accelerated mRNA cancer vaccines' development and clinical application. In this review, we present various cancer vaccine platforms with a focus on nucleic acid vaccines. We discuss rational design and optimization strategies for mRNA cancer vaccine development. We highlight the platforms available for delivery of the mRNA vaccines with a focus on lipid nanoparticles (LNPs) based delivery systems. Finally, we discuss the limitations of mRNA cancer vaccines and future challenges.

Adaptation-proof SARS-CoV-2 vaccine design

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) surface spike glycoprotein - a major antibody target - is critical for virus entry via engagement of human angiotensin-converting enzyme 2 (ACE2) receptor. Despite successes with existing vaccines and therapies that primarily target the receptor binding domain (RBD) of the spike protein, the susceptibility of RBD to mutations provides escape routes for the SARS-CoV-2 from neutralizing antibodies. On the other hand, structural conservation in the spike protein can be targeted to reduce escape mutations and achieve broad protection. Here, we designed candidate stable immunogens that mimic surface features of selected conserved regions of spike protein through 'epitope grafting,' in which we present the target epitope topology on diverse heterologous scaffolds that can structurally accommodate the spike epitopes. Structural characterization of the epitope-scaffolds showed stark agreement with our computational models and target epitopes. The sera from mice immunized with engineered designs display epitope-scaffolds and spike binding activity. We also demonstrated the utility of the designed epitope-scaffolds in diagnostic applications. Taken all together, our study provides important methodology for targeting the conserved, non-RBD structural motifs of spike protein for SARS-CoV-2 epitope vaccine design and demonstrates the potential utility of 'epitope grafting' in rational vaccine design.

Whole proteome mapping of compound-protein interactions

Off-target binding is one of the primary causes of toxic side effects of drugs in clinical development, resulting in failures of clinical trials. While off-target drug binding is a known phenomenon, experimental identification of the undesired protein binders can be prohibitively expensive due to the large pool of possible biological targets. Here, we propose a new strategy combining chemical similarity principle and deep learning to enable proteome-wide mapping of compound-protein interactions. We have developed a pipeline to identify the targets of bioactive molecules by matching them with chemically similar annotated "bait" compounds and ranking them with deep learning. We have constructed a user-friendly web server for drug-target identification based on chemical similarity (DRIFT) to perform searches across annotated bioactive compound datasets, thus enabling high-throughput, multi-ligand target identification, as well as chemical fragmentation of target-binding moieties.

Motor neuron-derived induced pluripotent stem cells as a drug screening platform for amyotrophic lateral sclerosis

The development of cell culture models that recapitulate the etiology and features of nervous system diseases is central to the discovery of new drugs and their translation onto therapies. Neuronal tissues are inaccessible due to skeletal constraints and the invasiveness of the procedure to obtain them. Thus, the emergence of induced pluripotent stem cell (iPSC) technology offers the opportunity to model different neuronal pathologies. Our focus centers on iPSCs derived from amyotrophic lateral sclerosis (ALS) patients, whose pathology remains in urgent need of new drugs and treatment. In this sense, we aim to revise the process to obtain motor neurons derived iPSCs (iPSC-MNs) from patients with ALS as a drug screening model, review current 3D-models and offer a perspective on bioinformatics as a powerful tool that can aid in the progress of finding new pharmacological treatments.

Adaptation-proof SARS-CoV-2 vaccine design

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) surface spike glycoprotein - a major antibody target - is critical for virus entry via engagement of human angiotensin-converting enzyme 2 (ACE2) receptor. Despite successes with existing vaccines and therapies that primarily target the receptor binding domain (RBD) of the spike protein, the susceptibility of RBD to mutations provides escape routes for the SARS-CoV-2 from neutralizing antibodies. On the other hand, structural conservation in the spike protein can be targeted to reduce escape mutations and achieve broad protection. Here, we designed candidate stable immunogens that mimic surface features of selected conserved regions of spike protein through 'epitope grafting,' in which we present the target epitope topology on diverse heterologous scaffolds that can structurally accommodate the spike epitopes. Structural characterization of the epitope-scaffolds showed stark agreement with our computational models and target epitopes. The sera from mice immunized with engineered designs display epitope-scaffolds and spike binding activity. We also demonstrated the utility of the designed epitope-scaffolds in diagnostic applications. Taken all together, our study provides important methodology for targeting the conserved, non-RBD structural motifs of spike protein for SARS-CoV-2 epitope vaccine design and demonstrates the potential utility of 'epitope grafting' in rational vaccine design.

Toward rational vaccine engineering

Technological revolutions in several fields have pushed the boundaries of vaccine design and provided new avenues for vaccine development. Next-generation vaccine platforms have shown promise in targeting challenging antigens, for which traditional approaches have been ineffective. With advances in protein engineering, structural biology, computational biology and immunology, the structural vaccinology approach, which uses protein structure information to develop immunogens, holds promise for future vaccine design. In this review, we highlight various vaccine development strategies, along with their advantages and limitations. We discuss the rational vaccine design approach, which focuses on structure-based vaccine design. Finally, we discuss antigen engineering using the epitope-scaffold approach, gaps in structural vaccinology, and remaining challenges in vaccine design.

Searching for methyllysine-binding aromatic cages

Methylation of lysine residues plays crucial roles in a wide variety of cell signaling processes. While the biological importance of recognition of methylated histones by reader domains in the cell nucleus is well established, the processes associated with methylation of non-histone proteins, particularly in the cytoplasm of the cell, are not well understood. Here, we describe a search for potential methyllysine readers using a rapid structural motif-mining algorithm Erebus, the PDB database, and knowledge of the methyllysine binding mechanisms.

Electrostatic regulation of blue copper sites

In the last 50 years, the blue copper proteins became central targets of investigation. Extensive experiments focused on the Cu coordination to probe the effect of local perturbations on its properties. We found that local electric fields, generated by charged residues evolutionarily placed throughout the protein edifice, mainly second sphere, but also more remotely, constitute an additional significant factor regulating blue copper proteins. These fields are not random, but exhibit a highly specific directionality, negative with respect to the and vectors in the Cu first shell. The field magnitude contributes to fine-tuning of the geometric and electronic properties of Cu sites in individual blue copper proteins. Specifically, the local electric fields evidently control the Cu–S_Met bond distance, Cu(ii)–S_Cys bond covalency, and the energies of the frontier molecular orbitals, which, in turn, govern the Cu(ii/i) reduction potential and the relative absorption intensities at 450 nm and 600 nm.

Intramolecular electric fields in blue copper proteins are oriented in a fixed way to modulate properties of their copper sites: they control the first-shell copper interactions to influence geometric, spectroscopic, and redox behavior.

A fast protein binding site comparison algorithm for proteome-wide protein function prediction and drug repurposing

The expansion of three-dimensional protein structures and enhanced computing power have significantly facilitated our understanding of protein sequence/structure/function relationships. A challenge in structural genomics is to predict the function of uncharacterized proteins. Protein function deconvolution based on global sequence or structural homology is impracticable when a protein relates to no other proteins with known function, and in such cases, functional relationships can be established by detecting their local ligand binding site similarity. Here, we introduce a sequence order-independent comparison algorithm, PocketShape, for structural proteome-wide exploration of protein functional site by fully considering the geometry of the backbones, orientation of the sidechains, and physiochemical properties of the pocket-lining residues. PocketShape is efficient in distinguishing similar from dissimilar ligand binding site pairs by retrieving 99.3% of the similar pairs while rejecting 100% of the dissimilar pairs on a dataset containing 1538 binding site pairs. This method successfully classifies 83 enzyme structures with diverse functions into 12 clusters, which is highly in accordance with the actual structural classification of proteins classification. PocketShape also achieves superior performances than other methods in protein profiling based on experimental data. Potential new applications for representative SARS-CoV-2 drugs Remdesivir and 11a are predicted. The high accuracy and time-efficient characteristics of PocketShape will undoubtedly make it a promising complementary tool for proteome-wide protein function inference and drug repurposing study.

Activating Sphingosine-1-phospahte signaling in endothelial cells increases myosin light chain phosphorylation to decrease endothelial permeability thereby inhibiting cancer metastasis

Targeting the metastatic process to prevent disease dissemination in cancer remains challenging. One step in the metastatic cascade involves cancer cells transiting through the vascular endothelium after inflammation has increased the permeability of this cellular layer. Reducing inflammation-mediated gaps in the vascular endothelium could potentially be used to retard metastasis. This study describes the development of a novel ASR396-containing nanoparticle designed to activate the Sphingosine-1-Phosphate Receptor 1 (S1PR1) in order to tighten the junctions between the endothelial cells lining the vascular endothelium thereby inhibiting metastasis. ASR396 was derived from the S1PR1 agonist SEW2871 through chemical modification enabling the new compound to be loaded into a nanoliposome. ASR396 retained S1PR1 binding activity and the nanoliposomal formulation (nanoASR396) made it systemically bioavailable upon intravenous injection. Studies conducted in microvessels demonstrated that nanoASR396 significantly attenuated inflammatory mediator-induced permeability increase through the S1PR1 activation. Similarly, nanoASR396 inhibited gap formation mediated by inflammatory agents on an endothelial cell monolayer by decreasing levels of phosphorylated myosin light chain protein thereby inhibiting cellular contractility. In animal models, nanoASR396 inhibited lung metastasis by up to 80%, indicating its potential for retarding melanoma metastasis. Thus, a novel bioavailable nanoparticle-based S1PR1 agonist has been developed to negate the effects of inflammatory mediators on the vascular endothelium in order to reduce the metastatic dissemination of cancer cells.

New computational protein design methods for de novo small molecule binding sites

Protein binding to small molecules is fundamental to many biological processes, yet it remains challenging to predictively design this functionality de novo. Current state-of-the-art computational design methods typically rely on existing small molecule binding sites or protein scaffolds with existing shape complementarity for a target ligand. Here we introduce new methods that utilize pools of discrete contacts between protein side chains and defined small molecule ligand substructures (ligand fragments) observed in the Protein Data Bank. We use the Rosetta Molecular Modeling Suite to recombine protein side chains in these contact pools to generate hundreds of thousands of energetically favorable binding sites for a target ligand. These composite binding sites are built into existing scaffold proteins matching the intended binding site geometry with high accuracy. In addition, we apply pools of side chain rotamers interacting with the target ligand to augment Rosetta's conventional design machinery and improve key metrics known to be predictive of design success. We demonstrate that our method reliably builds diverse binding sites into different scaffold proteins for a variety of target molecules. Our generalizable de novo ligand binding site design method provides a foundation for versatile design of protein to interface previously unattainable molecules for applications in medical diagnostics and synthetic biology.

Development of a Novel Multi-Isoform ALDH Inhibitor Effective as an Antimelanoma Agent

The aldehyde dehydrogenases (ALDH) are a major family of detoxifying enzymes that contribute to cancer progression and therapy resistance. ALDH overexpression is associated with a poor prognosis in many cancer types. The use of multi-ALDH isoform or isoform-specific ALDH inhibitors as anticancer agents is currently hindered by the lack of viable candidates. Most multi-ALDH isoform inhibitors lack bioavailability and are nonspecific or toxic, whereas most isoform-specific inhibitors are not effective as monotherapy due to the overlapping functions of ALDH family members. The present study details the development of a novel, potent, multi-isoform ALDH inhibitor, called KS100. The rationale for drug development was that inhibition of multiple ALDH isoforms might be more efficacious for cancer compared with isoform-specific inhibition. Enzymatic IC50s of KS100 were 207, 1,410, and 240 nmol/L toward ALDH1A1, 2, and 3A1, respectively. Toxicity of KS100 was mitigated by development of a nanoliposomal formulation, called NanoKS100. NanoKS100 had a loading efficiency of approximately 69% and was stable long-term. NanoKS100 was 5-fold more selective for killing melanoma cells compared with normal human fibroblasts. NanoKS100 administered intravenously at a submaximal dose (3-fold lower) was effective at inhibiting xenografted melanoma tumor growth by approximately 65% without organ-related toxicity. Mechanistically, inhibition by KS100 significantly reduced total cellular ALDH activity to increase reactive oxygen species generation, lipid peroxidation, and accumulation of toxic aldehydes leading to apoptosis and autophagy. Collectively, these data suggest the successful preclinical development of a nontoxic, bioavailable, nanoliposomal formulation containing a novel multi-ALDH isoform inhibitor effective in the treatment of cancer.

Rationally designed carbohydrate-occluded epitopes elicit HIV-1 Env-specific antibodies

An array of carbohydrates masks the HIV-1 surface protein Env, contributing to the evasion of humoral immunity. In most HIV-1 isolates ‘glycan holes’ occur due to natural sequence variation, potentially revealing the underlying protein surface to the immune system. Here we computationally design epitopes that mimic such surface features (carbohydrate-occluded neutralization epitopes or CONE) of Env through ‘epitope transplantation’, in which the target region is presented on a carrier protein scaffold with preserved structural properties. Scaffolds displaying the four CONEs are examined for structure and immunogenicity. Crystal structures of two designed proteins reflect the computational models and accurately mimic the native conformations of CONEs. The sera from rabbits immunized with several CONE immunogens display Env binding activity. Our method determines essential structural elements for targets of protective antibodies. The ability to design immunogens with high mimicry to viral proteins also makes possible the exploration of new templates for vaccine development.

Areas of HIV envelope (Env) that aren’t covered by glycans are potential targets for antibodies. Here, the authors computationally design small protein mimics of four such epitopes and show that they can induce Env binding antibodies in rabbits.

Molecular Docking at a Glance

The current chapter introduces different aspects of molecular docking technique in order to give an overview to the readers about the topics which will be dealt with throughout this volume. Like many other fields of science, molecular docking studies has experienced a lagging period of slow and steady increase in terms of acquiring attention of scientific community as well as its frequency of application, followed by a pronounced era of exponential expansion in theory, methodology, areas of application and performance due to developments in related technologies such as computational resources and theoretical as well as experimental biophysical methods. In the following sections the evolution of molecular docking will be reviewed and its different components including methods, search algorithms, scoring functions, validation of the methods, and area of applications plus few case studies will be touched briefly.

Computational Protein Design Through Grafting and Stabilization

Computational grafting of target residues onto existing protein scaffolds is a powerful method for the design of proteins with novel function. In the grafting method side chain mutations are introduced into a preexisting protein scaffold to recreate a target functional motif. The success of this approach relies on two primary criteria: (1) the availability of compatible structural scaffolds, and (2) the introduction of mutations that do not affect the protein structure or stability. To identify compatible structural motifs we use the Erebus webserver, to search the protein data bank (PDB) for user-defined structural scaffolds. To identify potential design mutations we use the Eris webserver, which accurately predicts changes in protein stability resulting from mutations. Mutations that increase the protein stability are more likely to maintain the protein structure and therefore produce the desired function. Together these tools provide effective methods for identifying existing templates and guiding further design experiments. The software tools for scaffold searching and design are available at http://dokhlab.org .

Harnessing Nature's Diversity: Discovering organophosphate bioscavenger characteristics among low molecular weight proteins

Organophosphate poisoning can occur from exposure to agricultural pesticides or chemical weapons. This exposure inhibits acetylcholinesterase resulting in increased acetylcholine levels within the synaptic cleft causing loss of muscle control, seizures, and death. Mitigating the effects of organophosphates in our bodies is critical and yet an unsolved challenge. Here, we present a computational strategy that integrates structure mining and modeling approaches, using which we identify novel candidates capable of interacting with a serine hydrolase probe (with equilibrium binding constants ranging from 4 to 120 μM). One candidate Smu. 1393c catalyzes the hydrolysis of the organophosphate omethoate (kcat/Km of (2.0 ± 1.3) × 10-1 M-1s-1) and paraoxon (kcat/Km of (4.6 ± 0.8) × 103 M-1s-1), V- and G-agent analogs respectively. In addition, Smu. 1393c protects acetylcholinesterase activity from being inhibited by two organophosphate simulants. We demonstrate that the utilized approach is an efficient and highly-extendable framework for the development of prophylactic therapeutics against organophosphate poisoning and other important targets. Our findings further suggest currently unknown molecular evolutionary rules governing natural diversity of the protein universe, which make it capable of recognizing previously unseen ligands.

Artificial Diiron Enzymes with a De Novo Designed Four-Helix Bundle Structure

A single polypeptide chain may provide an astronomical number of conformers. Nature selected only a trivial number of them through evolution, composing an alphabet of scaffolds, that can afford the complete set of chemical reactions needed to support life. These structural templates are so stable that they allow several mutations without disruption of the global folding, even having the ability to bind several exogenous cofactors. With this perspective, metal cofactors play a crucial role in the regulation and catalysis of several processes. Nature is able to modulate the chemistry of metals, adopting only a few ligands and slightly different geometries. Several scaffolds and metal-binding motifs are representing the focus of intense interest in the literature. This review discusses the widespread four-helix bundle fold, adopted as a scaffold for metal binding sites in the context of de novo protein design to obtain basic biochemical components for biosensing or catalysis. In particular, we describe the rational refinement of structure/function in diiron-oxo protein models from the due ferri (DF) family. The DF proteins were developed by us through an iterative process of design and rigorous characterization, which has allowed a shift from structural to functional models. The examples reported herein demonstrate the importance of the synergic application of de novo design methods as well as spectroscopic and structural characterization to optimize the catalytic performance of artificial enzymes.

Rapid search for tertiary fragments reveals protein sequence-structure relationships

Finding backbone substructures from the Protein Data Bank that match an arbitrary query structural motif, composed of multiple disjoint segments, is a problem of growing relevance in structure prediction and protein design. Although numerous protein structure search approaches have been proposed, methods that address this specific task without additional restrictions and on practical time scales are generally lacking. Here, we propose a solution, dubbed MASTER, that is both rapid, enabling searches over the Protein Data Bank in a matter of seconds, and provably correct, finding all matches below a user-specified root-mean-square deviation cutoff. We show that despite the potentially exponential time complexity of the problem, running times in practice are modest even for queries with many segments. The ability to explore naturally plausible structural and sequence variations around a given motif has the potential to synthesize its design principles in an automated manner; so we go on to illustrate the utility of MASTER to protein structural biology. We demonstrate its capacity to rapidly establish structure-sequence relationships, uncover the native designability landscapes of tertiary structural motifs, identify structural signatures of binding, and automatically rewire protein topologies. Given the broad utility of protein tertiary fragment searches, we hope that providing MASTER in an open-source format will enable novel advances in understanding, predicting, and designing protein structure.

A real-time all-atom structural search engine for proteins

Protein designers use a wide variety of software tools for de novo design, yet their repertoire still lacks a fast and interactive all-atom search engine. To solve this, we have built the Suns program: a real-time, atomic search engine integrated into the PyMOL molecular visualization system. Users build atomic-level structural search queries within PyMOL and receive a stream of search results aligned to their query within a few seconds. This instant feedback cycle enables a new “designability”-inspired approach to protein design where the designer searches for and interactively incorporates native-like fragments from proven protein structures. We demonstrate the use of Suns to interactively build protein motifs, tertiary interactions, and to identify scaffolds compatible with hot-spot residues. The official web site and installer are located at http://www.degradolab.org/suns/ and the source code is hosted at https://github.com/godotgildor/Suns (PyMOL plugin, BSD license), https://github.com/Gabriel439/suns-cmd (command line client, BSD license), and https://github.com/Gabriel439/suns-search (search engine server, GPLv2 license).

Parallel-ProBiS: fast parallel algorithm for local structural comparison of protein structures and binding sites

The ProBiS algorithm performs a local structural comparison of the query protein surface against the nonredundant database of protein structures. It finds proteins that have binding sites in common with the query protein. Here, we present a new parallelized algorithm, Parallel-ProBiS, for detecting similar binding sites on clusters of computers. The obtained speedups of the parallel ProBiS scale almost ideally with the number of computing cores up to about 64 computing cores. Scaling is better for larger than for smaller query proteins. For a protein with almost 600 amino acids, the maximum speedup of 180 was achieved on two interconnected clusters with 248 computing cores. Source code of Parallel-ProBiS is available for download free for academic users at http://probis.cmm.ki.si/download.

ProBiS-2012: web server and web services for detection of structurally similar binding sites in proteins

The ProBiS web server is a web server for detection of structurally similar binding sites in the PDB and for local pairwise alignment of protein structures. In this article, we present a new version of the ProBiS web server that is 10 times faster than earlier versions, due to the efficient parallelization of the ProBiS algorithm, which now allows significantly faster comparison of a protein query against the PDB and reduces the calculation time for scanning the entire PDB from hours to minutes. It also features new web services, and an improved user interface. In addition, the new web server is united with the ProBiS-Database and thus provides instant access to pre-calculated protein similarity profiles for over 29 000 non-redundant protein structures. The ProBiS web server is particularly adept at detection of secondary binding sites in proteins. It is freely available at http://probis.cmm.ki.si/old-version, and the new ProBiS web server is at http://probis.cmm.ki.si.

Crystal structure of a trapped catalytic intermediate suggests that forced atomic proximity drives the catalysis of mIPS

1-L-myo-inositol-phosphate synthase (mIPS) catalyzes the first step of the unique, de novo pathway of inositol biosynthesis. However, details about the complex mIPS catalytic mechanism, which requires oxidation, enolization, intramolecular aldol cyclization, and reduction, are not fully known. To gain further insight into this mechanism, we determined the crystal structure of the wild-type mIPS from Archaeoglobus fulgidus at 1.7 Å, as well as the crystal structures of three active-site mutants. Additionally, we obtained the structure of mIPS with a trapped 5-keto-glucose-6-phosphate intermediate at 2 Å resolution by a novel (to our knowledge) process of activating the crystal at high temperature. A comparison of all of the crystal structures of mIPS described in this work suggests a novel type of catalytic mechanism that relies on the forced atomic proximity of functional groups. The lysine cluster is contained in a small volume in the active site, where random motions of these side chains are responsible for the progress of the complex multistep reaction as well as for the low rate of catalysis. The mechanism requires that functional groups of Lys-274, Lys-278, Lys-306, and Lys-367 assume differential roles in the protonation/deprotonation steps that must occur during the mIPS reaction. This mechanism is supported by the complete loss of activity of the enzyme caused by the Leu-257 mutation to Ala that releases the lysine containment.

ProBiS-database: precalculated binding site similarities and local pairwise alignments of PDB structures

ProBiS-Database is a searchable repository of precalculated local structural alignments in proteins detected by the ProBiS algorithm in the Protein Data Bank. Identification of functionally important binding regions of the protein is facilitated by structural similarity scores mapped to the query protein structure. PDB structures that have been aligned with a query protein may be rapidly retrieved from the ProBiS-Database, which is thus able to generate hypotheses concerning the roles of uncharacterized proteins. Presented with uncharacterized protein structure, ProBiS-Database can discern relationships between such a query protein and other better known proteins in the PDB. Fast access and a user-friendly graphical interface promote easy exploration of this database of over 420 million local structural alignments. The ProBiS-Database is updated weekly and is freely available online at http://probis.cmm.ki.si/database.