Discovery of Nirmatrelvir Resistance Mutations in SARS-CoV-2 3CLpro: A Computational-Experimental Approach.

The COVID-19 pandemic has emphasized the urgency for effective antiviral therapies against SARS-CoV-2. Targeting the main protease (3CLpro) of the virus has emerged as a promising approach, and nirmatrelvir (PF-07321332), the active component of Pfizer's oral drug Paxlovid, has demonstrated remarkable clinical efficacy. However, the emergence of resistance mutations poses a challenge to its continued success. In this study, we employed alchemical free energy perturbation (FEP) alanine scanning to identify nirmatrelvir-resistance mutations within SARS-CoV-2 3CLpro. FEP identified several mutations, which were validated through in vitro IC50 experiments and found to result in 8- and 72-fold increases in nirmatrelvir IC50 values. Additionally, we constructed SARS-CoV-2 omicron replicons containing these mutations, and one of the mutants (S144A/E166A) displayed a 20-fold increase in EC50, confirming the role of FEP in identifying drug-resistance mutations. Our findings suggest that FEP can be a valuable tool in proactively monitoring the emergence of resistant strains and guiding the design of future inhibitors with reduced susceptibility to drug resistance. As nirmatrelvir is currently widely used for treating COVID-19, this research has important implications for surveillance efforts and antiviral development.

In-silico screening and microsecond molecular dynamics simulations to identify single point mutations that destabilize ß-hexosaminidase A causing Tay-Sachs disease.

ß-hexosaminidase A (HexA) protein is responsible for the degradation of GM2 gangliosides in the central and peripheral nervous systems. Tay-Sachs disease occurs when HexA within Hexosaminidase does not properly function and harmful GM2 gangliosides begin to build up within the neurons. In this study, in silico methods such as SIFT, PolyPhen-2, PhD-SNP, and MutPred were utilized to analyze the effects of nonsynonymous single nucleotide polymorphisms (nsSNPs) on HexA in order to identify possible pathogenetic and deleterious variants. Molecular dynamics (MD) simulations showed that two mutants, P25S and W485R, experienced an increase in structural flexibility compared to the native protein. Particularly, there was a decrease in the overall number and frequencies of hydrogen bonds for the mutants compared to the wildtype. MM/GBSA calculations were performed to help assess the change in binding affinity between the wildtype and mutant structures and a mechanism-based inhibitor, NGT, which is known to help increase the residual activity of HexA. Both of the mutants experienced a decrease in the binding affinity from -23.8 kcal/mol in wildtype to -20.9 and -18.7 kcal/mol for the P25S and W485R variants of HexA, respectively.

In silico screening and molecular dynamics simulation of deleterious PAH mutations responsible for phenylketonuria genetic disorder.

Phenylketonuria (PKU) is a genetic disorder that if left untreated can lead to behavioral problems, epilepsy, and even mental retardation. PKU results from mutations within the phenylalanine-4-hydroxylase (PAH) gene that encodes for the PAH protein. The study of all PAH causing mutations is improbable using experimental techniques. In this study, a collection of in silico resources, sorting intolerant from tolerant, Polyphen-2, PhD-SNP, and MutPred were used to identify possible pathogenetic and deleterious PAH non-synonymous single nucleotide polymorphisms (nsSNPs). We identified two variants of PAH, I65N and L311P, to be the most deleterious and disease causing nsSNPs. Molecular dynamics (MD) simulations were carried out to characterize these point mutations on the atomic level. MD simulations revealed increased flexibility and a decrease in the hydrogen bond network for both mutants compared to the native protein. Free energy calculations using the MM/GBSA approach found that BH4 , a drug-based therapy for PKU patients, had a higher binding affinity for I65N and L311P mutants compared to the wildtype protein. We also identify important residues in the BH4 binding pocket that may be of interest for the rational drug design of other PAH drug-based therapies. Lastly, free energy calculations also determined that the I65N mutation may impair the dimerization of the N-terminal regulatory domain of PAH.

Computationally Designed ACE2 Decoy Receptor Binds SARS-CoV-2 Spike (S) Protein with Tight Nanomolar Affinity.

Even with the availability of vaccines, therapeutic options for COVID-19 still remain highly desirable, especially in hospitalized patients with moderate or severe disease. Soluble ACE2 (sACE2) is a promising therapeutic candidate that neutralizes SARS CoV-2 infection by acting as a decoy. Using computational mutagenesis, we designed a number of sACE2 derivatives carrying three to four mutations. The top-predicted sACE2 decoy based on the in silico mutagenesis scan was subjected to molecular dynamics and free-energy calculations for further validation. After illuminating the mechanism of increased binding for our designed sACE2 derivative, the design was verified experimentally by flow cytometry and BLI-binding experiments. The computationally designed sACE2 decoy (ACE2-FFWF) bound the receptor-binding domain of SARS-CoV-2 tightly with low nanomolar affinity and ninefold affinity enhancement over the wild type. Furthermore, cell surface expression was slightly greater than wild-type ACE2, suggesting that the design is well-folded and stable. Having an arsenal of high-affinity sACE2 derivatives will help to buffer against the emergence of SARS CoV-2 variants. Here, we show that computational methods have become sufficiently accurate for the design of therapeutics for current and future viral pandemics.

Perioperative and Complication Related Outcomes for Robotic-Assisted vs Open Radical Cystectomy: A Comparative National Surgical Quality Improvement Project Analysis.

Background: Radical cystectomy (RC) is standard of care for muscle-invasive bladder cancer, but it comes with significant perioperative risk, with half of the patients experiencing major postoperative complications. Robot-assisted radical cystectomies (RARCs) have aimed to decrease patient morbidity and been increasingly adopted in North America. Currently, both open radical cystectomies (ORCs) and RARCs are frequently performed. The aim of this study is to contribute to the existing literature using newly available data from the American College of Surgeons National Surgical Quality Improvement Project (NSQIP), representing one of the most recent, largest multi-institutional studies, while uniquely accounting for a variety of factors, including type of urinary diversion, cancer staging, and neoadjuvant chemotherapy. Methods: RC procedures performed between 2019 and 2021 were identified in NSQIP and the corresponding cystectomy-targeted database. Cases in the ORC group were planned open procedures, and cases in the RARC group were robot assisted, including unplanned conversion to open cases for intention to treat. Chi-square and t-tests were performed to compare baseline demographics and operative parameters. Multivariate analysis was performed for outcomes, including major complications, minor complications, and 30-day mortality rates, while adjusting for baseline differences significant on univariate analysis. Results: Five thousand three hundred forty-three RC cases were identified. Of these, 70% underwent planned ORC, while 30% received RARC. RARC was associated with longer operative times and shorter hospital length of stay compared with ORC. On multivariate analysis, there was no difference between the cohorts in 30-day rates of major complications, hospital readmissions, need for reoperation, or mortality. ORC was, however, associated with higher rates of minor complications, bleeding, superficial surgical site infections, and anastomotic leak. Conclusions: In the NSQIP database, ORC is associated with higher rates of 30-day minor complications, most notably bleeding, compared with RARC. However, there is no difference in regard to perioperative major morbidity or mortality rates. This study is unique in the size of the cohorts compared, timeliness of data (2019-2021), applicability to a variety of different practice settings across the country, and ability to control for factors, such as type of urinary diversion and pathological bladder cancer staging, as well as use of neoadjuvant chemotherapy. This study was approved by the Institutional Review Board (IRB) specific to Thomas Jefferson University.

A computationally designed ACE2 decoy has broad efficacy against SARS-CoV-2 omicron variants and related viruses in vitro and in vivo.

SARS-CoV-2, especially B.1.1.529/omicron and its sublineages, continues to mutate to evade monoclonal antibodies and antibodies elicited by vaccination. Affinity-enhanced soluble ACE2 (sACE2) is an alternative strategy that works by binding the SARS-CoV-2 S protein, acting as a 'decoy' to block the interaction between the S and human ACE2. Using a computational design strategy, we designed an affinity-enhanced ACE2 decoy, FLIF, that exhibited tight binding to SARS-CoV-2 delta and omicron variants. Our computationally calculated absolute binding free energies (ABFE) between sACE2:SARS-CoV-2 S proteins and their variants showed excellent agreement to binding experiments. FLIF displayed robust therapeutic utility against a broad range of SARS-CoV-2 variants and sarbecoviruses, and neutralized omicron BA.5 in vitro and in vivo. Furthermore, we directly compared the in vivo therapeutic efficacy of wild-type ACE2 (non-affinity enhanced ACE2) against FLIF. A few wild-type sACE2 decoys have shown to be effective against early circulating variants such as Wuhan in vivo. Our data suggest that moving forward, affinity-enhanced ACE2 decoys like FLIF may be required to combat evolving SARS-CoV-2 variants. The approach described herein emphasizes how computational methods have become sufficiently accurate for the design of therapeutics against viral protein targets. Affinity-enhanced ACE2 decoys remain highly effective at neutralizing omicron subvariants.

An in silico approach for identification of novel inhibitors as potential therapeutics targeting COVID-19 main protease.

Respiratory disease caused by a novel coronavirus, COVID-19, has been labeled a pandemic by the World Health Organization. Very little is known about the infection mechanism for this virus. More importantly, there are no drugs or vaccines that can cure or prevent a person from getting COVID-19. In this study, the binding affinity of 2692 protease inhibitor compounds that are known in the protein data bank, are calculated against the main protease of the novel coronavirus with docking and molecular dynamics (MD). Both the docking and MD methods predict the macrocyclic tissue factor-factor VIIa (PubChem ID: 118098670) inhibitor to bind strongly with the main protease with a binding affinity of -10.6 and -10.0 kcal/mol, respectively. The TF-FVIIa inhibitors are known to prevent the coagulation of blood and have antiviral activity as shown in the case of SARS coronavirus. Two more inhibitors, phenyltriazolinones (PubChem ID: 104161460) and allosteric HCV NS5B polymerase thumb pocket 2 (PubChem ID: 163632044) have shown antiviral activity and also have high affinity towards the main protease of COVID-19. Furthermore, these inhibitors interact with the catalytic dyad in the active site of the COVID-19 main protease that is especially important in viral replication. The calculated theoretical dissociation constants of the proposed COVID-19 inhibitors are found to be very similar to the experimental dissociation constant values of similar protease-inhibitor systems.Communicated by Ramaswamy H. Sarma.

Prediction and evaluation of deleterious and disease causing non-synonymous SNPs (nsSNPs) in human NF2 gene responsible for neurofibromatosis type 2 (NF2).

The majority of genetic variations in the human genome that lead to variety of different diseases are caused by non-synonymous single nucleotide polymorphisms (nsSNPs). Neurofibromatosis type 2 (NF2) is a deadly disease caused by nsSNPs in the NF2 gene that encodes for a protein called merlin. This study used various in silico methods, SIFT, Polyphen-2, PhD-SNP and MutPred, to investigate the pathogenic effect of 14 nsSNPs in the merlin FERM domain. The G197C and L234R mutations were found to be two deleterious and disease mutations associated with the mild and severe forms of NF2, respectively. Molecular dynamics (MD) simulations were conducted to understand the stability, structure and dynamics of these mutations. Both mutant structures experienced larger flexibility compared to the wildtype. The L234R mutant suffered from more prominent structural instability, which may help to explain why it is associated with the more severe form of NF2. The intramolecular hydrogen bonding in L234R mutation decreased from the wildtype, while intermolecular hydrogen bonding of L234R mutation with solvent greatly increased. The native contacts were also found to be important. Protein-protein docking revealed that L234R mutation decreased the binding complementarity and binding affinity of LATS2 to merlin, which may have an impact on merlin's ability to regulate the Hippo signaling pathway. The calculated binding affinity of the LATS2 to L234R mutant and wildtype merlin protein is found to be 21.73 and -11 kcal/mol, respectively. The binding affinity of the wildtype merlin agreed very well with the experimental value, -8 kcal/mol.Communicated by Ramaswamy H. Sarma.

New Insights into the Role of Hydrogen Bonding in Furanoside Binding to Protein.

Furanosides have been subjected to extensive studies owing to their inherent flexibility, which is believed to play an important role in the survival and pathogenicity of different disease-causing organisms in the human body. This study reports the binding free energy (ΔG) and specificity of arabinofuranose oligosaccharides to a protein, arabinanase (Arb43A), with the use of potential of mean force (PMF) calculations using the umbrella-sampling simulations. Long molecular dynamics simulations have been carried out to understand intermolecular interactions in the arabinofuranose-protein complex. The PMF for pulling the α-(1 → 5)-linked L-arabinohexaose (ligand) from the protein provides a large free energy of binding, -16.8 kcal/mol. The ΔG of the nonreducing arabinotriose end is found to be -12.6 kcal/mol, while the ΔG of the reducing end is calculated to be -7.7 kcal/mol. In the absence of nonreducing arabinotrioside, the ΔG of the reducing arabinotrioside is -8.5 kcal/mol. Similarly, in the absence of reducing arabinotrioside, the ΔG of the nonreducing arabinotrioside is calculated to be -9.4 kcal/mol. The main contributing factor in the protein-arabinofuranose binding is hydrogen bonding. Acidic amino acid residues, Glu and Asp, with furanosides produce the strongest hydrogen bonding. Araf-A, B, and C construct the reducing arabinotriose, while Araf-D, E, and F construct the nonreducing arabinotriose. Since most of the hydrogen-bonding occupancies belong to Araf-D and Araf-E, the nonreducing arabinotriose is bound to protein more strongly than the reducing arabinotriose. This explains why the reducing arabinotriose can detach from the protein in nature.