Covalent docking predicts substrates for haloalkanoate dehalogenase superfamily phosphatases

Landscape of In Silico Tools for Modeling Covalent Modification of Proteins: A Review on Computational Covalent Drug Discovery

Covalent drug discovery has been a challenging research area given the struggle of finding a sweet balance between selectivity and reactivity for these drugs, the lack of which often leads to off-target activities and hence undesirable side effects. However, there has been a resurgence in covalent drug design following the success of several covalent drugs such as boceprevir (2011), ibrutinib (2013), neratinib (2017), dacomitinib (2018), zanubrutinib (2019), and many others. Design of covalent drugs includes many crucial factors, where "evaluation of the binding affinity" and "a detailed mechanistic understanding on covalent inhibition" are at the top of the list. Well-defined experimental techniques are available to elucidate these factors; however, often they are expensive and/or time-consuming and hence not suitable for high throughput screens. Recent developments in in silico methods provide promise in this direction. In this report, we review a set of recent publications that focused on developing and/or implementing novel in silico techniques in "Computational Covalent Drug Discovery (CCDD)". We also discuss the advantages and disadvantages of these approaches along with what improvements are required to make it a great tool in medicinal chemistry in the near future.

Covalent docking in CDOCKER

Targeted covalent inhibitors (TCIs) are considered to be an important component in the toolbox of drug discovery and about 30% of currently marketed drugs are TCIs. Although these drugs raise concerns about toxicity, their high potencies and prolonged effects result in less-frequent drug dosing and wide therapeutic margins for patients. This leads to increased interests in developing new computational methods to identify novel covalent inhibitors. The implementation of successful in silico docking algorithms have the potential to provide significant savings of time and money in the discovery of lead compounds. In this paper, we describe the implementation and testing of a covalent docking methodology in Rigid CDOCKER and the optimization of the corresponding physics-based scoring function with an additional customizable covalent bond grid potential which represents the free energy change of bond formation between the ligand and the receptor. We optimize the covalent bond grid potential for different common covalent bond formation reaction in TCIs. The average runtime for docking one covalent compound is 15 minutes which is comparable or faster than other well-established covalent docking methods. We demonstrate comparable top rank accuracy compared with other covalent docking algorithms using the pose prediction benchmark dataset for covalent docking algorithms developed by the Keserű group. Finally, we construct a retrospective virtual screening benchmark dataset containing 8 different receptor targets with different covalent bond formation reactions. To our knowledge, this is the largest dataset for benchmarking covalent docking methods. We show that our new covalent docking algorithm has the ability to identify lead compounds among a large chemical space. The largest AUC value is 0.909 for the target receptor CATK and the warhead chemistry of the covalent inhibitors is addition to the aldehyde functionality.

Phylogenomic analysis and metabolic role reconstruction of mutualistic Rhizobiales hindgut symbionts of Acromyrmex leaf-cutting ants

Rhizobiales are well-known plant-root nitrogen-fixing symbionts, but the functions of insect-associated Rhizobiales are poorly understood. We obtained genomes of three strains associated with Acromyrmex leaf-cutting ants and show that, in spite of being extracellular gut symbionts, they lost all pathways for essential amino acid biosynthesis, making them fully dependent on their hosts. Comparison with 54 Rhizobiales genomes showed that all insect-associated Rhizobiales lost the ability to fix nitrogen and that the Acromyrmex symbionts had exceptionally also lost the urease genes. However, the Acromyrmex strains share biosynthesis pathways for riboflavin vitamin, queuosine and a wide range of antioxidant enzymes likely to be beneficial for the ant fungus-farming symbiosis. We infer that the Rhizobiales symbionts catabolize excess of fungus-garden-derived arginine to urea, supplementing complementary Mollicutes symbionts that turn arginine into ammonia and infer that these combined symbiont activities stabilize the fungus-farming mutualism. Similar to the Mollicutes symbionts, the Rhizobiales species have fully functional CRISPR/Cas and R-M phage defenses, suggesting that these symbionts are important enough for the ant hosts to have precluded the evolution of metabolically cheaper defenseless strains.

High-Efficiency Secretion and Directed Evolution of Chitinase BcChiA1 in Bacillus subtilis for the Conversion of Chitinaceous Wastes Into Chitooligosaccharides

Limitations of enzyme production and activity pose a challenge for efficient degradation of chitinaceous wastes. To solve this problem, we engineered a system for high-yielding extracellular secretion of chitinase A1 from Bacillus circulans (BcChiA1) in B. subtilis. Furthermore, an innovative chitinase high-throughput screening method based on colloidal chitin stained with Remazol Brilliant Blue R (CC-RBB) was established and used to identify three mutants with improved chitinase activity: Y10A/R301A/E327A (Mu1), Y10A/D81A/E327A (Mu2), and F38A/K88A/R301A (Mu3). Their highest specific activity reached 1004.83 ± 0.87 U/mg, representing a 16.89-fold increase in activity compared to native BcChiA1. Additionally, we found that there is a synergistic effect between BcChiA1 and a lytic polysaccharide monooxygenase from Bacillus atrophaeus (BatLPMO10), which increased the chitin processing efficiency by 50% after combining the two enzymes. The yield of chitooligosaccharide (COS) production using the mutant Mu1 and BatLPMO10 reached 2885.25 ± 2.22 mg/L. Taken together, the results indicated that the CC-RBB high-throughput screening method is a useful tool for chitinase screening, and evolution of BcChiA1 in collaboration with BatLPMO10 has tremendous application potential in the biological treatment of chitinaceous wastes for COS production.

Production of riboflavin and related cofactors by biotechnological processes

Riboflavin (RF) and its active forms, the cofactors flavin mononucleotide (FMN) and flavin adenine dinucleotide (FAD), have been extensively used in the food, feed and pharmaceutical industries. Modern commercial production of riboflavin is based on microbial fermentation, but the established genetically engineered production strains are facing new challenges due to safety concerns in the food and feed additives industry. High yields of flavin mononucleotide and flavin adenine dinucleotide have been obtained using whole-cell biocatalysis processes. However, the necessity of adding expensive precursors results in high production costs. Consequently, developing microbial cell factories that are capable of efficiently producing flavin nucleotides at low cost is an increasingly attractive approach. The biotechnological processes for the production of RF and its cognate cofactors are reviewed in this article.

Overcoming insecticide resistance through computational inhibitor design

Insecticides allow control of agricultural pests and disease vectors and are vital for global food security and health. The evolution of resistance to insecticides, such as organophosphates (OPs), is a serious and growing concern. OP resistance often involves sequestration or hydrolysis of OPs by carboxylesterases. Inhibiting carboxylesterases could, therefore, restore the effectiveness of OPs for which resistance has evolved. Here, we use covalent virtual screening to produce nano-/picomolar boronic acid inhibitors of the carboxylesterase αE7 from the agricultural pest Lucilia cuprina as well as a common Gly137Asp αE7 mutant that confers OP resistance. These inhibitors, with high selectivity against human acetylcholinesterase and low to no toxicity in human cells and in mice, act synergistically with the OPs diazinon and malathion to reduce the amount of OP required to kill L. cuprina by up to 16-fold and abolish resistance. The compounds exhibit broad utility in significantly potentiating another OP, chlorpyrifos, against the common pest, the peach-potato aphid (Myzus persicae). These compounds represent a solution to OP resistance as well as to environmental concerns regarding overuse of OPs, allowing significant reduction of use without compromising efficacy.

Systematic Studies on the Protocol and Criteria for Selecting a Covalent Docking Tool

With the resurgence of drugs with covalent binding mechanisms, much attention has been paid to docking methods for the discovery of targeted covalent inhibitors. The existence of many available covalent docking tools has inspired development of a systematic and objective procedure and criteria with which to evaluate these programs. In order to find a tool appropriate to studies of a covalently binding system, protocols and criteria are proposed for protein–ligand covalent docking studies. This paper consists of three sections: (1) curating a standard data set to evaluate covalent docking tools objectively; (2) establishing criteria to measure the performance of a tool applied for docking ligands into a complex system; and (3) creating a protocol to evaluate and select covalent binding tools. The protocols were applied to evaluate four covalent docking tools (MOE, GOLD, CovDock, and ICM-Pro) and parameters affecting covalent docking performance were investigated.

Revealing Unexplored Sequence-Function Space Using Sequence Similarity Networks

The rapidly expanding number of protein sequences found in public databases can improve our understanding of how protein functions evolve. However, our current knowledge of protein function likely represents a small fraction of the diverse repertoire that exists in nature. Integrative computational methods can facilitate the discovery of new protein functions and enzymatic reactions through the observation and investigation of the complex sequence-structure-function relationships within protein superfamilies. Here, we highlight the use of sequence similarity networks (SSNs) to identify previously unexplored sequence and function space. We exemplify this approach using the nitroreductase (NTR) superfamily. We demonstrate that SSN investigations can provide a rapid and effective means to classify groups of proteins, therefore exposing experimentally unexplored sequences that may exhibit novel functionality. Integration of such approaches with systematic experimental characterization will expand our understanding of the functional diversity of enzymes and their associated physiological roles.

Docking of Covalent Ligands: Challenges and Approaches

Covalent ligands have recently regained considerable attention in drug discovery. The rational design of such ligands, however, is still faced with particular challenges, mostly related to the fact that covalent bond formation is a quantum mechanical phenomenon which cannot adequately be handled by the force fields or empirical approaches typically used for noncovalent protein-ligand interactions. Although the necessity for quantum chemical approaches is clear, they cannot yet routinely be applied on large data sets of ligands or for a broader exploration of binding modes in docking calculations. On the other hand, technical solutions for performing docking calculations with covalent ligands are available, but their scope is normally quite limited. Scoring functions typically neglect the contribution from covalent bond formation completely. In this situation, the question arises how to approach covalent ligands and which methods to choose for their docking and design.

Crius: A novel fragment-based algorithm of de novo substrate prediction for enzymes

The study of enzyme substrate specificity is vital for developing potential applications of enzymes. However, the routine experimental procedures require lot of resources in the discovery of novel substrates. This article reports an in silico structure-based algorithm called Crius, which predicts substrates for enzyme. The results of this fragment-based algorithm show good agreements between the simulated and experimental substrate specificities, using a lipase from Candida antarctica (CALB), a nitrilase from Cyanobacterium syechocystis sp. PCC6803 (Nit6803), and an aldo-keto reductase from Gluconobacter oxydans (Gox0644). This opens new prospects of developing computer algorithms that can effectively predict substrates for an enzyme.

Determinants and Prediction of Esterase Substrate Promiscuity Patterns

Esterases receive special attention because of their wide distribution in biological systems and environments and their importance for physiology and chemical synthesis. The prediction of esterases' substrate promiscuity level from sequence data and the molecular reasons why certain such enzymes are more promiscuous than others remain to be elucidated. This limits the surveillance of the sequence space for esterases potentially leading to new versatile biocatalysts and new insights into their role in cellular function. Here, we performed an extensive analysis of the substrate spectra of 145 phylogenetically and environmentally diverse microbial esterases, when tested with 96 diverse esters. We determined the primary factors shaping their substrate range by analyzing substrate range patterns in combination with structural analysis and protein-ligand simulations. We found a structural parameter that helps rank (classify) the promiscuity level of esterases from sequence data at 94% accuracy. This parameter, the active site effective volume, exemplifies the topology of the catalytic environment by measuring the active site cavity volume corrected by the relative solvent accessible surface area (SASA) of the catalytic triad. Sequences encoding esterases with active site effective volumes (cavity volume/SASA) above a threshold show greater substrate spectra, which can be further extended in combination with phylogenetic data. This measure provides also a valuable tool for interrogating substrates capable of being converted. This measure, found to be transferred to phosphatases of the haloalkanoic acid dehalogenase superfamily and possibly other enzymatic systems, represents a powerful tool for low-cost bioprospecting for esterases with broad substrate ranges, in large scale sequence data sets.

Recent Advances and Applications of Molecular Docking to G Protein-Coupled Receptors

The growing number of studies on G protein-coupled receptors (GPCRs) family are a source of noticeable improvement in our understanding of the functioning of these proteins. GPCRs are responsible for a vast part of signaling in vertebrates and, as such, invariably remain in the spotlight of medicinal chemistry. A deeper insight into the underlying mechanisms of interesting phenomena observed in GPCRs, such as biased signaling or allosteric modulation, can be gained with experimental and computational studies. The latter play an important role in this process, since they allow for observations on scales inaccessible for most other methods. One of the key steps in such studies is proper computational reconstruction of actual ligand-receptor or protein-protein interactions, a process called molecular docking. A number of improvements and innovative applications of this method were documented recently. In this review, we focus particularly on innovations in docking to GPCRs.

Overlapping riboflavin supply pathways in bacteria

Riboflavin derivatives are essential cofactors for a myriad of flavoproteins. In bacteria, flavins importance extends beyond their role as intracellular protein cofactors, as secreted flavins are a key metabolite in a variety of physiological processes. Bacteria obtain riboflavin through the endogenous riboflavin biosynthetic pathway (RBP) or by the use of importer proteins. Bacteria frequently encode multiple paralogs of the RBP enzymes and as for other micronutrient supply pathways, biosynthesis and uptake functions largely coexist. It is proposed that bacteria shut down biosynthesis and would rather uptake riboflavin when the vitamin is environmentally available. Recently, the overlap of riboflavin provisioning elements has gained attention and the functions of duplicated paralogs of RBP enzymes started to be addressed. Results point towards the existence of a modular structure in the bacterial riboflavin supply pathways. Such structure uses subsets of RBP genes to supply riboflavin for specific functions. Given the importance of riboflavin in intra and extracellular bacterial physiology, this complex array of riboflavin provision pathways may have developed to contend with the various riboflavin requirements. In riboflavin-prototrophic bacteria, riboflavin transporters could represent a module for riboflavin provision for particular, yet unidentified processes, rather than substituting for the RBP as usually assumed.

Designer protein delivery: From natural to engineered affinity-controlled release systems

Exploiting binding affinities between molecules is an established practice in many fields, including biochemical separations, diagnostics, and drug development; however, using these affinities to control biomolecule release is a more recent strategy. Affinity-controlled release takes advantage of the reversible nature of noncovalent interactions between a therapeutic protein and a binding partner to slow the diffusive release of the protein from a vehicle. This process, in contrast to degradation-controlled sustained-release formulations such as poly(lactic-co-glycolic acid) microspheres, is controlled through the strength of the binding interaction, the binding kinetics, and the concentration of binding partners. In the context of affinity-controlled release--and specifically the discovery or design of binding partners--we review advances in in vitro selection and directed evolution of proteins, peptides, and oligonucleotides (aptamers), aided by computational design.

Docking Screens for Novel Ligands Conferring New Biology

It is now plausible to dock libraries of 10 million molecules against targets over several days or weeks. When the molecules screened are commercially available, they may be rapidly tested to find new leads. Although docking retains important liabilities (it cannot calculate affinities accurately nor even reliably rank order high-scoring molecules), it can often can distinguish likely from unlikely ligands, often with hit rates above 10%. Here we summarize the improvements in libraries, target quality, and methods that have supported these advances, and the open access resources that make docking accessible. Recent docking screens for new ligands are sketched, as are the binding, crystallographic, and in vivo assays that support them. Like any technique, controls are crucial, and key experimental ones are reviewed. With such controls, docking campaigns can find ligands with new chemotypes, often revealing the new biology that may be docking's greatest impact over the next few years.

Multiple alternative substrate kinetics

The specificity of enzymes for their respective substrates has been a focal point of enzyme kinetics since the initial characterization of metabolic chemistry. Various processes to quantify an enzyme's specificity using kinetics have been utilized over the decades. Fersht's definition of the ratio kcat/Km for two different substrates as the "specificity constant" (ref [7]), based on the premise that the important specificity existed when the substrates were competing in the same reaction, has become a consensus standard for enzymes obeying Michaelis-Menten kinetics. The expansion of the theory for the determination of the relative specificity constants for a very large number of competing substrates, e.g. those present in a combinatorial library, in a single reaction mixture has been developed in this contribution. The ratio of kcat/Km for isotopologs has also become a standard in mechanistic enzymology where kinetic isotope effects have been measured by the development of internal competition experiments with extreme precision. This contribution extends the theory of kinetic isotope effects to internal competition between three isotopologs present at non-tracer concentrations in the same reaction mix. This article is part of a special issue titled: Enzyme Transition States from Theory and Experiment.