PPI-hotspotID for detecting protein-protein interaction hot spots from the free protein structure.

Experimental detection of residues critical for protein-protein interactions (PPI) is a time-consuming, costly, and labor-intensive process. Hence, high-throughput PPI-hot spot prediction methods have been developed, but they have been validated using relatively small datasets, which may compromise their predictive reliability. Here, we introduce PPI-hotspotID, a novel method for identifying PPI-hot spots using the free protein structure, and validated it on the largest collection of experimentally confirmed PPI-hot spots to date. We explored the possibility of detecting PPI-hot spots using (i) FTMap in the PPI mode, which identifies hot spots on protein-protein interfaces from the free protein structure, and (ii) the interface residues predicted by AlphaFold-Multimer. PPI-hotspotID yielded better performance than FTMap and SPOTONE, a webserver for predicting PPI-hot spots given the protein sequence. When combined with the AlphaFold-Multimer-predicted interface residues, PPI-hotspotID yielded better performance than either method alone. Furthermore, we experimentally verified several PPI-hotspotID-predicted PPI-hot spots of eukaryotic elongation factor 2. Notably, PPI-hotspotID can reveal PPI-hot spots not obvious from complex structures, including those in indirect contact with binding partners. PPI-hotspotID serves as a valuable tool for understanding PPI mechanisms and aiding drug design. It is available as a web server (https://ppihotspotid.limlab.dnsalias.org/) and open-source code (https://github.com/wrigjz/ppihotspotid/).

Solution Ionic Strength Can Modulate Functional Loop Conformations in E. coli Dihydrofolate Reductase.

The observation of multiple conformations of a functional loop (termed M20) in the Escherichia coli dihydrofolate reductase (ecDHFR) enzyme triggered the proposition that large-scale motions of protein structural elements contribute to enzyme catalysis. The transition of the M20 loop from a closed conformation to an occluded conformation was thought to aid the rate-limiting release of the products. However, the influence of charged species in the solution environment on the observed M20 loop conformations, independent of charged ligands bound to the enzyme, had not been considered. Molecular dynamics simulations of ecDHFR in model CaCl2 solutions of varying molar ionic strengths IM reveal a substantial free energy barrier between occluded and closed M20 loop states at IM exceeding the E. coli threshold (∼0.24 M). This barrier may facilitate crystallization of ecDHFR in the occluded state, consistent with ecDHFR structures obtained at IM exceeding 0.3 M. At lower IM (≤0.15 M), the M20 loop can explore the occluded state, but prefers an open/partially closed conformation, again consistent with ecDHFR structures. Our findings caution against using ecDHFR structures obtained at nonphysiological ionic strengths in interpreting catalytic events or in structure-based drug design.

Using protein language models for protein interaction hot spot prediction with limited data.

BACKGROUND: Protein language models, inspired by the success of large language models in deciphering human language, have emerged as powerful tools for unraveling the intricate code of life inscribed within protein sequences. They have gained significant attention for their promising applications across various areas, including the sequence-based prediction of secondary and tertiary protein structure, the discovery of new functional protein sequences/folds, and the assessment of mutational impact on protein fitness. However, their utility in learning to predict protein residue properties based on scant datasets, such as protein-protein interaction (PPI)-hotspots whose mutations significantly impair PPIs, remained unclear. Here, we explore the feasibility of using protein language-learned representations as features for machine learning to predict PPI-hotspots using a dataset containing 414 experimentally confirmed PPI-hotspots and 504 PPI-nonhot spots. RESULTS: Our findings showcase the capacity of unsupervised learning with protein language models in capturing critical functional attributes of protein residues derived from the evolutionary information encoded within amino acid sequences. We show that methods relying on protein language models can compete with methods employing sequence and structure-based features to predict PPI-hotspots from the free protein structure. We observed an optimal number of features for model precision, suggesting a balance between information and overfitting. CONCLUSIONS: This study underscores the potential of transformer-based protein language models to extract critical knowledge from sparse datasets, exemplified here by the challenging realm of predicting PPI-hotspots. These models offer a cost-effective and time-efficient alternative to traditional experimental methods for predicting certain residue properties. However, the challenge of explaining why specific features are important for determining certain residue properties remains.

An Antibody-Drug Conjugate for Multiple Myeloma Prepared by Multi-Arm Linkers.

First-line treatment of multiple myeloma, a prevalent blood cancer lacking a cure, using anti-CD38 daratumumab antibody and lenalidomide is often inadequate due to relapse and severe side effects. To enhance drug safety and efficacy, an antibody-drug conjugate, TE-1146, comprising six lenalidomide drug molecules site-specifically conjugated to a reconfigured daratumumab to deliver cytotoxic lenalidomide to tumor cells is developed. TE-1146 is prepared using the HighDAR platform, which employs i) a maleimide-containing "multi-arm linker" to conjugate multiple drug molecules creating a drug bundle, and ii) a designed peptide with a Zn2+-binding cysteine at the C-termini of a reconfigured daratumumab for site-specific drug bundle conjugation. It is shown that TE-1146 remains intact and effectively enters CD38-expressing tumor cells, releasing lenalidomide, leading to enhanced cell-killing effects compared to lenalidomide/daratumumab alone or their combination. This reveals the remarkable potency of lenalidomide once internalized by myeloma cells. TE-1146 precisely delivers lenalidomide to target CD38-overexpressing tumor cells. In contrast, lenalidomide without daratumumab cannot easily enter cells, whereas daratumumab without lenalidomide relies on Fc-dependent effector functions to kill tumor cells.

System-Specific Parameter Optimization for Nonpolarizable and Polarizable Force Fields.

The accuracy of classical force fields (FFs) has been shown to be limited for the simulation of cation-protein systems despite their importance in understanding the processes of life. Improvements can result from optimizing the parameters of classical FFs or by extending the FF formulation by terms describing charge transfer (CT) and polarization (POL) effects. In this work, we introduce our implementation of the CTPOL model in OpenMM, which extends the classical additive FF formula by adding CT and POL. Furthermore, we present an open-source parametrization tool, called FFAFFURR, that enables the (system-specific) parametrization of OPLS-AA and CTPOL models. The performance of our workflow was evaluated by its ability to reproduce quantum chemistry energies and by molecular dynamics simulations of a zinc-finger protein.

Site-specific Conjugation of 6 DOTA Chelators to a CA19-9-targeting scFv-Fc Antibody for Imaging and Therapy.

Antibodies conjugated with diagnostic/therapeutic radionuclides are attractive options for inoperable cancers lacking accurate imaging methods and effective therapeutics, such as pancreatic cancer. Hence, we have produced an antibody radionuclide conjugate termed TE-1132 comprising a α-CA19-9 scFv-Fc that is site-specifically conjugated at each C-terminus to 3 DOTA chelators via a cysteine-containing peptide linker. The smaller scFv-Fc size facilitates diffusivity within solid tumors, whereas the chelator-to-antibody ratio of six enabled 177Lu-radiolabeled TE-1132 to exhibit high radioactivity up to 520 MBq/nmol. In mice bearing BxPC3 tumors, immuno-SPECT/CT imaging of [111In]In-TE-1132 and the biodistribution of [177Lu]Lu-TE-1132 showed selective tumor accumulation. Single and multiple doses of [177Lu]Lu-TE-1132 effectively inhibited the BxPC3 tumor growth and prolonged the survival of mice with no irreversible body weight loss or hematopoietic damage. The adequate pharmacokinetic parameters, prominent tumor accumulation, and efficacy with good safety in mice encourage the further investigation of theranostic TE-1132 for treating pancreatic cancer.

Protein Ca2+-Sites Prone to Sr2+ Substitution: Implications for Strontium Therapy.

Strontium (Sr), an alkali metal with properties similar to calcium, in the form of soluble salts is used to treat osteoporosis. Despite the information accumulated on the role of Sr2+ as a Ca2+ mimetic in biology and medicine, there is no systematic study of how the outcome of the competition between the two dications depends on the physicochemical properties of (i) the metal ions, (ii) the first- and second-shell ligands, and (iii) the protein matrix. Specifically, the key features of a Ca2+-binding protein that enable Sr2+ to displace Ca2+ remain unclear. To address this, we studied the competition between Ca2+ and Sr2+ in protein Ca2+-binding sites using density functional theory combined with the polarizable continuum model. Our findings indicate that Ca2+-sites with multiple strong charge-donating protein ligands, including one or more bidentately bound Asp-/Glu- that are relatively buried and rigid are protected against Sr2+ attack. On the other hand, Ca2+-sites crowded with multiple protein ligands may be prone to Sr2+ displacement if they are solvent-exposed and flexible enough so that an extra backbone ligand from the outer shell can bind to Sr2+. In addition, solvent-exposed Ca2+ sites with only a few weak charge-donating ligands that can rearrange to fit the strontium's coordination requirements are susceptible to Sr2+ displacement. We provide the physical basis of these results and discuss potential novel protein targets of therapeutic Sr2+.

A strategy for evaluating potential antiviral resistance to small molecule drugs and application to SARS-CoV-2.

Alterations in viral fitness cannot be inferred from only mutagenesis studies of an isolated viral protein. To-date, no systematic analysis has been performed to identify mutations that improve virus fitness and reduce drug efficacy. We present a generic strategy to evaluate which viral mutations might diminish drug efficacy and applied it to assess how SARS-CoV-2 evolution may affect the efficacy of current approved/candidate small-molecule antivirals for Mpro, PLpro, and RdRp. For each drug target, we determined the drug-interacting virus residues from available structures and the selection pressure of the virus residues from the SARS-CoV-2 genomes. This enabled the identification of promising drug target regions and small-molecule antivirals that the virus can develop resistance. Our strategy of utilizing sequence and structural information from genomic sequence and protein structure databanks can rapidly assess the fitness of any emerging virus variants and can aid antiviral drug design for future pathogens.

Α γ-tubulin complex-dependent pathway suppresses ciliogenesis by promoting cilia disassembly.

The primary cilium, a microtubule-based sensory organelle, undergoes cycles of assembly and disassembly that govern the cell cycle progression critical to cell proliferation and differentiation. Although cilia assembly has been studied extensively, the molecular mechanisms underlying cilia disassembly are less well understood. Here, we uncover a γ-tubulin ring complex (γ-TuRC)-dependent pathway that promotes cilia disassembly and thereby prevents cilia formation. We further demonstrate that Kif2A, a kinesin motor that bears microtubule-depolymerizing activity, is recruited to the cilium basal body in a γ-TuRC-dependent manner. Our mechanistic analyses show that γ-TuRC specifically recruits Kif2A via the GCP2 subunit and its binding partner Mzt2. Hence, despite the long-standing view that γ-TuRC acts mainly as a microtubule template, we illustrate that its functional heterogeneity at the basal body facilitates both microtubule nucleation and Kif2A recruitment-mediated regulation of ciliogenesis, ensuring cell cycle progression.

Factors allowing small monovalent Li+ to displace Ca2+ in proteins.

Because Li+ and Ca2+ differ in both charge and size, the possibility that monovalent Li+ could dislodge the bulkier, divalent Ca2+ in Ca2+ proteins had not been considered. However, our recent density functional theory/continuum dielectric calculations predicted that Li+ could displace the native Ca2+ from the C2 domain of cytosolic PKCα/γ. This would reduce electrostatic interactions between the Li+-bound C2 domain and the membrane, consistent with experimental studies showing that Li+ can inhibit the translocation of cytoplasmic PKC to membranes. Besides the trinuclear Ca2+-site in the PKCα/γ C2 domain, it is not known whether other Ca2+-sites in human proteins may be susceptible to Li+ substitution. Furthermore, it is unclear what factors determine the outcome of the competition between divalent Ca2+ and monovalent Li+. Here we show that the net charge of residues in the first and second coordination shell is a key determinant of the selectivity for divalent Ca2+ over monovalent Li+ in proteins: neutral/anionic Ca2+-carboxylate sites are protected against Li+ attack. They are further protected by outer-shell Asp-/Glu- and the protein matrix rigidifying the Ca2+-site or limiting water entry. In contrast, buried, cationic Ca2+-sites surrounded by Arg+/Lys+, which are found in the C2 domains of PKCα/γ, as well as certain synaptotagmins, are prone to Li+ attack.

From quantum-derived principles underlying cysteine reactivity to combating the COVID-19 pandemic.

The COVID-19 pandemic poses a challenge in coming up with quick and effective means to counter its cause, the SARS-CoV-2. Here, we show how the key factors governing cysteine reactivity in proteins derived from combined quantum mechanical/continuum calculations led to a novel multi-targeting strategy against SARS-CoV-2, in contrast to developing potent drugs/vaccines against a single viral target such as the spike protein. Specifically, they led to the discovery of reactive cysteines in evolutionary conserved Zn2+-sites in several SARS-CoV-2 proteins that are crucial for viral polypeptide proteolysis as well as viral RNA synthesis, proofreading, and modification. These conserved, reactive cysteines, both free and Zn2+-bound, can be targeted using the same Zn-ejector drug (disulfiram/ebselen), which enables the use of broad-spectrum anti-virals that would otherwise be removed by the virus's proofreading mechanism. Our strategy of targeting multiple, conserved viral proteins that operate at different stages of the virus life cycle using a Zn-ejector drug combined with other broad-spectrum anti-viral drug(s) could enhance the barrier to drug resistance and antiviral effects, as compared to each drug alone. Since these functionally important nonstructural proteins containing reactive cysteines are highly conserved among coronaviruses, our proposed strategy has the potential to tackle future coronaviruses. This article is categorized under:Structure and Mechanism > Reaction Mechanisms and CatalysisStructure and Mechanism > Computational Biochemistry and BiophysicsElectronic Structure Theory > Density Functional Theory.

Allosteric coupling between transmembrane segment 4 and the selectivity filter of TALK1 potassium channels regulates their gating by extracellular pH.

Opening of two-pore domain K+ channels (K2Ps) is regulated by various external cues, such as pH, membrane tension, or temperature, which allosterically modulate the selectivity filter (SF) gate. However, how these cues cause conformational changes in the SF of some K2P channels remains unclear. Herein, we investigate the mechanisms by which extracellular pH affects gating in an alkaline-activated K2P channel, TALK1, using electrophysiology and molecular dynamics (MD) simulations. We show that R233, located at the N-terminal end of transmembrane segment 4, is the primary pHo sensor. This residue distally regulates the orientation of the carbonyl group at the S1 potassium-binding site through an interacting network composed of residues on transmembrane segment 4, the pore helix domain 1, and the SF. Moreover, in the presence of divalent cations, we found the acidic pH-activated R233E mutant recapitulates the network interactions of protonated R233. Intriguingly, our data further suggested stochastic coupling between R233 and the SF gate, which can be described by an allosteric gating model. We propose that this allosteric model could predict the hybrid pH sensitivity in heterodimeric channels with alkaline-activated and acidic-activated K2P subunits.

PPI-HotspotDB: Database of Protein-Protein Interaction Hot Spots.

Single-point mutations of certain residues (so-called hot spots) impair/disrupt protein-protein interactions (PPIs), leading to pathogenesis and drug resistance. Conventionally, a PPI-hot spot is identified when its replacement decreased the binding free energy significantly, generally by ≥2 kcal/mol. The relatively few mutations with such a significant binding free energy drop limited the number of distinct PPI-hot spots. By defining PPI-hot spots based on mutations that have been manually curated in UniProtKB to significantly impair/disrupt PPIs in addition to binding free energy changes, we have greatly expanded the number of distinct PPI-hot spots by an order of magnitude. These experimentally determined PPI-hot spots along with available structures have been collected in a database called PPI-HotspotDB. We have applied the PPI-HotspotDB to create a nonredundant benchmark, PPI-Hotspot+PDBBM, for assessing methods to predict PPI-hot spots using the free structure as input. PPI-HotspotDB will benefit the design of mutagenesis experiments and development of PPI-hot spot prediction methods. The database and benchmark are freely available at https://ppihotspot.limlab.dnsalias.org.

Efficient Strategy to Design Protease Inhibitors: Application to Enterovirus 71 2A Protease.

One strategy to counter viruses that persistently cause outbreaks is to design molecules that can specifically inhibit an essential multifunctional viral protease. Herein, we present such a strategy using well-established methods to first identify a region present only in viral (but not human) proteases and find peptides that can bind specifically to this "unique" region by maximizing the protease-peptide binding free energy iteratively using single-point mutations starting with the substrate peptide. We applied this strategy to discover pseudosubstrate peptide inhibitors for the multifunctional 2A protease of enterovirus 71 (EV71), a key causative pathogen for hand-foot-and-mouth disease affecting young children, along with coxsackievirus A16. Four peptide candidates predicted to bind EV71 2A protease more tightly than the natural substrate were experimentally validated and found to inhibit protease activity. Furthermore, the crystal structure of the best pseudosubstrate peptide bound to the EV71 2A protease was determined to provide a molecular basis for the observed inhibition. Since the 2A proteases of EV71 and coxsackievirus A16 share nearly identical sequences and structures, our pseudosubstrate peptide inhibitor may prove useful in inhibiting the two key pathogens of hand-foot-and-mouth disease.

Calcium in Signaling: Its Specificity and Vulnerabilities toward Biogenic and Abiogenic Metal Ions.

Divalent calcium ion (Ca2+) plays an indispensable role as a second messenger in a myriad of signal transduction processes. Of utmost importance for the faultless functioning of calcium-modulated signaling proteins is their binding selectivity of the native metal cation over rival biogenic/abiogenic metal ion contenders in the intra/extracellular fluids. In this Perspective, we summarize recent findings on the competition between the cognate Ca2+ and other biogenic or abiogenic divalent cations for binding to Ca2+-signaling proteins or organic cofactors. We describe the competition between the two most abundant intracellular biogenic metal ions (Mg2+ and Ca2+) for Ca2+-binding sites in signaling proteins, followed by the rivalry between native Ca2+ and "therapeutic" Li+ as well as "toxic" Pb2+. We delineate the key factors governing the rivalry between the native and non-native cations in proteins and highlight key implications for the biological performance of the respective proteins/organic cofactors.

Trinuclear Calcium Site in the C2 Domain of PKCα/γ Is Prone to Lithium Attack.

Lithium (Li+) is the first-line therapy for bipolar disorder and a candidate drug for various diseases such as amyotrophic lateral sclerosis, multiple sclerosis, and stroke. Despite being the captivating subject of many studies, the mechanism of lithium's therapeutic action remains unclear. To date, it has been shown that Li+ competes with Mg2+ and Na+ to normalize the activity of inositol and neurotransmitter-related signaling proteins, respectively. Furthermore, Li+ may co-bind with Mg2+-loaded adenosine or guanosine triphosphate to alter the complex's susceptibility to hydrolysis and mediate cellular signaling. Bipolar disorder patients exhibit abnormally high cytosolic Ca2+ levels and protein kinase C (PKC) hyperactivity that can be downregulated by long-term Li+ treatment. However, the possibility that monovalent Li+ could displace the bulkier divalent Ca2+ and inhibit PKC activity has not been considered. Here, using density functional theory calculations combined with continuum dielectric methods, we show that Li+ may displace the native dication from the positively charged trinuclear site in the C2 domain of cytosolic PKCα/γ. This would affect the membrane-docking ability of cytosolic PKCα/γ and reduce the abnormally high membrane-associated active PKCα/γ levels, thus downregulating the PKC hyperactivity found in bipolar patients.

Influence of solution ionic strength on the stabilities of M20 loop conformations in apo E. coli dihydrofolate reductase.

Interactions among ions and their specific interactions with macromolecular solutes are known to play a central role in biomolecular stability. However, similar effects in the conformational stability of protein loops that play functional roles, such as binding ligands, proteins, and DNA/RNA molecules, remain relatively unexplored. A well-characterized enzyme that has such a functional loop is Escherichia coli dihydrofolate reductase (ecDHFR), whose so-called M20 loop has been observed in three ordered conformations in crystal structures. To explore how solution ionic strengths may affect the M20 loop conformation, we proposed a reaction coordinate that could quantitatively describe the loop conformation and used it to classify the loop conformations in representative ecDHFR x-ray structures crystallized in varying ionic strengths. The Protein Data Bank survey indicates that at ionic strengths (I) below the intracellular ion concentration-derived ionic strength in E. coli (I ≤ 0.237M), the ecDHFR M20 loop tends to adopt open/closed conformations, and rarely an occluded loop state, but when I is >0.237M, the loop tends to adopt closed/occluded conformations. Distance-dependent electrostatic potentials around the most mobile M20 loop region from molecular dynamics simulations of ecDHFR in equilibrated CaCl2 solutions of varying ionic strengths show that high ionic strengths (I = 0.75/1.5M) can preferentially stabilize the loop in closed/occluded conformations. These results nicely correlate with conformations derived from ecDHFR structures crystallized in varying ionic strengths. Altogether, our results suggest caution in linking M20 loop conformations derived from crystal structures solved at ionic strengths beyond that tolerated by E. coli to the ecDHFR function.

Correction to "Synergistic Inhibition of SARS-CoV-2 Replication Using Disulfiram/Ebselen and Remdesivir".

[This corrects the article DOI: 10.1021/acsptsci.1c00022.].

Correction: Multi-targeting of functional cysteines in multiple conserved SARS-CoV-2 domains by clinically safe Zn-ejectors.

[This corrects the article DOI: 10.1039/D0SC02646H.].

Synergistic Inhibition of SARS-CoV-2 Replication Using Disulfiram/Ebselen and Remdesivir.

The SARS-CoV-2 replication and transcription complex (RTC) comprising nonstructural protein (nsp) 2-16 plays crucial roles in viral replication, reducing the efficacy of broad-spectrum nucleoside analog drugs such as remdesivir and evading innate immune responses. Most studies target a specific viral component of the RTC such as the main protease or the RNA-dependent RNA polymerase. In contrast, our strategy is to target multiple conserved domains of the RTC to prevent SARS-CoV-2 genome replication and to create a high barrier to viral resistance and/or evasion of antiviral drugs. We show that the clinically safe Zn-ejector drugs disulfiram and ebselen can target conserved Zn2+ sites in SARS-CoV-2 nsp13 and nsp14 and inhibit nsp13 ATPase and nsp14 exoribonuclease activities. As the SARS-CoV-2 nsp14 domain targeted by disulfiram/ebselen is involved in RNA fidelity control, our strategy allows coupling of the Zn-ejector drug with a broad-spectrum nucleoside analog that would otherwise be excised by the nsp14 proofreading domain. As proof-of-concept, we show that disulfiram/ebselen, when combined with remdesivir, can synergistically inhibit SARS-CoV-2 replication in Vero E6 cells. We present a mechanism of action and the advantages of our multitargeting strategy, which can be applied to any type of coronavirus with conserved Zn2+ sites.