Genome-Wide Analysis of the Peroxidase Gene Family and Verification of Lignin Synthesis-Related Genes in Watermelon

Watermelon (Citrullus lanatus) is an important horticultural crop worldwide, but peel cracking caused by peel hardness severely decreases its quality. Lignification is one of the important functions of class III peroxidase (PRX), and its accumulation in the plant cell wall leads to cell thickening and wood hardening. For in-depth physiological and genetical understanding, we studied the relationship between peel hardness and lignin accumulation and the role of PRXs affecting peel lignin biosynthesis using genome-wide bioinformatics analysis. The obtained results showed that lignin accumulation gradually increased to form the peel stone cell structure, and tissue lignification led to peel hardness. A total of 79 ClPRXs (class III) were identified using bioinformatics analysis, which were widely distributed on 11 chromosomes. The constructed phylogenetics indicated that ClPRXs were divided into seven groups and eleven subclasses, and gene members of each group had highly conserved intron structures. Repeated pattern analysis showed that deletion and replication events occurred during the process of ClPRX amplification. However, in the whole-protein sequence alignment analysis, high homology was not observed, although all contained four conserved functional sites. Repeated pattern analysis showed that deletion and replication events occurred during ClPRXs’ amplification process. The prediction of the promoter cis-acting element and qRT-PCR analysis in four tissues (leaf, petiole, stem, and peel) showed different expression patterns for tissue specificity, abiotic stress, and hormone response by providing a genetic basis of the ClPRX gene family involved in a variety of physiological processes in plants. To our knowledge, we for the first time report the key roles of two ClPRXs in watermelon peel lignin synthesis. In conclusion, the extensive data collected in this study can be used for additional functional analysis of ClPRXs in watermelon growth and development and hormone and abiotic stress response.

A Structural Perspective of Reps from CRESS-DNA Viruses and Their Bacterial Plasmid Homologues

Rolling circle replication (RCR) is ubiquitously used by cellular and viral systems for genome and plasmid replication. While the molecular mechanism of RCR has been described, the structural mechanism is desperately lacking. Circular-rep encoded single stranded DNA (CRESS-DNA) viruses employ a viral encoded replicase (Rep) to initiate RCR. The recently identified prokaryotic homologues of Reps may also be responsible for initiating RCR. Reps are composed of an endonuclease, oligomerization, and ATPase domain. Recent structural studies have provided structures for all these domains such that an overall mechanism of RCR initiation can begin to be synthesized. However, structures of Rep in complex with its various DNA substrates and/or ligands are lacking. Here we provide a 3D bioinformatic review of the current structural information available for Reps. We combine an excess of 1590 sequences with experimental and predicted structural data from 22 CRESS-DNA groups to identify similarities and differences between Reps that lead to potentially important functional sites. Experimental studies of these sites may shed light on how Reps execute their functions. Furthermore, we identify Rep-substrate or Rep-ligand structures that are urgently needed to better understand the structural mechanism of RCR.

Structural Features of Cytochrome b5–Cytochrome b5 Reductase Complex Formation and Implications for the Intramolecular Dynamics of Cytochrome b5 Reductase

Membrane cytochrome b5 reductase is a pleiotropic oxidoreductase that uses primarily soluble reduced nicotinamide adenine dinucleotide (NADH) as an electron donor to reduce multiple biological acceptors localized in cellular membranes. Some of the biological acceptors of the reductase and coupled redox proteins might eventually transfer electrons to oxygen to form reactive oxygen species. Additionally, an inefficient electron transfer to redox acceptors can lead to electron uncoupling and superoxide anion formation by the reductase. Many efforts have been made to characterize the involved catalytic domains in the electron transfer from the reduced flavoprotein to its electron acceptors, such as cytochrome b5, through a detailed description of the flavin and NADH-binding sites. This information might help to understand better the processes and modifications involved in reactive oxygen formation by the cytochrome b5 reductase. Nevertheless, more than half a century since this enzyme was first purified, the one-electron transfer process toward potential electron acceptors of the reductase is still only partially understood. New advances in computational analysis of protein structures allow predicting the intramolecular protein dynamics, identifying potential functional sites, or evaluating the effects of microenvironment changes in protein structure and dynamics. We applied this approach to characterize further the roles of amino acid domains within cytochrome b5 reductase structure, part of the catalytic domain, and several sensors and structural domains involved in the interactions with cytochrome b5 and other electron acceptors. The computational analysis results allowed us to rationalize some of the available spectroscopic data regarding ligand-induced conformational changes leading to an increase in the flavin adenine dinucleotide (FAD) solvent-exposed surface, which has been previously correlated with the formation of complexes with electron acceptors.

Prediction of Protein Sites and Physicochemical Properties Related to Functional Specificity

Specificity Determining Positions (SDPs) are protein sites responsible for functional specificity within a family of homologous proteins. These positions are extracted from a family’s multiple sequence alignment and complement the fully conserved positions as predictors of functional sites. SDP analysis is now routinely used for locating these specificity-related sites in families of proteins of biomedical or biotechnological interest with the aim of mutating them to switch specificities or design new ones. There are many different approaches for detecting these positions in multiple sequence alignments. Nevertheless, existing methods report the potential SDP positions but they do not provide any clue on the physicochemical basis behind the functional specificity, which has to be inferred a-posteriori by manually inspecting these positions in the alignment. In this work, a new methodology is presented that, concomitantly with the detection of the SDPs, automatically provides information on the amino-acid physicochemical properties more related to the change in specificity. This new method is applied to two different multiple sequence alignments of homologous of the well-studied RasH protein representing different cases of functional specificity and the results discussed in detail.

Functional Importance of Hydrophobic Patches on the Ebola Virus VP35 IFN-Inhibitory Domain

Viral protein 35 (VP35) of Ebola virus (EBOV) is a multifunctional protein that mainly acts as a viral polymerase cofactor and an interferon antagonist. VP35 interacts with the viral nucleoprotein (NP) and double-stranded RNA for viral RNA transcription/replication and inhibition of type I interferon (IFN) production, respectively. The C-terminal portion of VP35, which is termed the IFN-inhibitory domain (IID), is important for both functions. To further identify critical regions in this domain, we analyzed the physical properties of the surface of VP35 IID, focusing on hydrophobic patches, which are expected to be functional sites that are involved in interactions with other molecules. Based on the known structural information of VP35 IID, three hydrophobic patches were identified on its surface and their biological importance was investigated using minigenome and IFN-β promoter-reporter assays. Site-directed mutagenesis revealed that some of the amino acid substitutions that were predicted to disrupt the hydrophobicity of the patches significantly decreased the efficiency of viral genome replication/transcription due to reduced interaction with NP, suggesting that the hydrophobic patches might be critical for the formation of a replication complex through the interaction with NP. It was also found that the hydrophobic patches were involved in the IFN-inhibitory function of VP35. These results highlight the importance of hydrophobic patches on the surface of EBOV VP35 IID and also indicate that patch analysis is useful for the identification of amino acid residues that directly contribute to protein functions.

Characterizing disease-associated human proteins without available protein structures or homologues

Mutations in human proteins lead to diseases. The structure of these proteins can help understand the mechanism of such diseases and develop therapeutics against them. With improved deep learning techniques such as RoseTTAFold and AlphaFold, we can predict the structure of these proteins even in the absence of structural homologues. We modeled and extracted the domains from 553 disease-associated human proteins. We noticed that the model quality was higher and the RMSD lower between AlphaFold and RoseTTAFold models for domains that could be assigned to CATH families as compared to those which could be assigned to Pfam families of unknown structure or could not be assigned to either. We predicted ligand-binding sites, protein-protein interfaces, conserved residues and destabilising effects caused by residue mutations in these predicted structures. We then explored whether the disease-associated mutations were in the proximity of these predicted functional sites or if they destabilized the protein structure based on ddG calculations. We could explain 80% of these disease-associated mutations based on proximity to functional sites or structural destabilization. Usage of models from the two state-of-the-art techniques provide better confidence in our predictions, and we explain 93 additional mutations based on RoseTTAFold models which could not be explained based solely on AlphaFold models.

Missense variants reveal functional insights into the human ARID family of gene regulators

Missense variants are alterations to protein coding sequences that result in amino acid substitutions. They can be deleterious if the amino acid is required for maintaining structure or/and function, but are likely to be tolerated at other sites. Consequently, missense variation within a healthy population can mirror the effects of negative selection on protein structure and function, such that functional sites on proteins are often depleted of missense variants. Advances in high-throughput sequencing have dramatically increased the sample size of available human variation data, allowing for population-wide analysis of selective pressures. In this study, we developed a convenient set of tools, called 1D-to-3D, for visualizing the positions of missense variants on protein sequences and structures. We used these tools to characterize human homologues of the ARID family of gene regulators. ARID family members are implicated in multiple cancer types, developmental disorders, and immunological diseases but current understanding of their mechanistic roles is incomplete. Combined with phylogenetic and structural analyses, our approach allowed us to characterise sites important for protein-protein interactions, histone modification recognition, and DNA binding by the ARID proteins. We find that comparing missense depletion patterns among paralogs can reveal sub-functionalization at the level of domains. We propose that visualizing missense variants and their depletion on structures can serve as a valuable tool for complementing evolutionary and experimental findings.

Deep learning methods for designing proteins scaffolding functional sites

Current approaches to de novo design of proteins harboring a desired binding or catalytic motif require pre-specification of an overall fold or secondary structure composition, and hence considerable trial and error can be required to identify protein structures capable of scaffolding an arbitrary functional site. Here we describe two complementary approaches to the general functional site design problem that employ the RosettaFold and AlphaFold neural networks which map input sequences to predicted structures. In the first "constrained hallucination" approach, we carry out gradient descent in sequence space to optimize a loss function which simultaneously rewards recapitulation of the desired functional site and the ideality of the surrounding scaffold, supplemented with problem-specific interaction terms, to design candidate immunogens presenting epitopes recognized by neutralizing antibodies, receptor traps for escape-resistant viral inhibition, metalloproteins and enzymes, and target binding proteins with designed interfaces expanding around known binding motifs. In the second "missing information recovery" approach, we start from the desired functional site and jointly fill in the missing sequence and structure information needed to complete the protein in a single forward pass through an updated RoseTTAFold trained to recover sequence from structure in addition to structure from sequence. We show that the two approaches have considerable synergy, and AlphaFold2 structure prediction calculations suggest that the approaches can accurately generate proteins containing a very wide array of functional sites.

A New Paradigm for KIM-PTP Drug Discovery: Identification of Allosteric Sites with Potential for Selective Inhibition Using Virtual Screening and LEI Analysis

The kinase interaction motif protein tyrosine phosphatases (KIM-PTPs), HePTP, PTPSL and STEP, are involved in the negative regulation of mitogen-activated protein kinase (MAPK) signalling pathways and are important therapeutic targets for a number of diseases. We have used VSpipe, a virtual screening pipeline, to identify a ligand cluster distribution that is unique to this subfamily of PTPs. Several clusters map onto KIM-PTP specific sequence motifs in contrast to the cluster distribution obtained for PTP1B, a classic PTP that mapped to general PTP motifs. Importantly, the ligand clusters coincide with previously reported functional and substrate binding sites in KIM-PTPs. Assessment of the KIM-PTP specific clusters, using ligand efficiency index (LEI) plots generated by the VSpipe, ascertained that the binders in these clusters reside in a more drug-like chemical–biological space than those at the active site. LEI analysis showed differences between clusters across all KIM-PTPs, highlighting a distinct and specific profile for each phosphatase. The most druggable cluster sites are unexplored allosteric functional sites unique to each target. Exploiting these sites may facilitate the delivery of inhibitors with improved drug-like properties, with selectivity amongst the KIM-PTPs and over other classical PTPs.