Biallelic variants in CSMD1 are implicated in a neurodevelopmental disorder with intellectual disability and variable cortical malformations.

CSMD1 (Cub and Sushi Multiple Domains 1) is a well-recognized regulator of the complement cascade, an important component of the innate immune response. CSMD1 is highly expressed in the central nervous system (CNS) where emergent functions of the complement pathway modulate neural development and synaptic activity. While a genetic risk factor for neuropsychiatric disorders, the role of CSMD1 in neurodevelopmental disorders is unclear. Through international variant sharing, we identified inherited biallelic CSMD1 variants in eight individuals from six families of diverse ancestry who present with global developmental delay, intellectual disability, microcephaly, and polymicrogyria. We modeled CSMD1 loss-of-function (LOF) pathogenesis in early-stage forebrain organoids differentiated from CSMD1 knockout human embryonic stem cells (hESCs). We show that CSMD1 is necessary for neuroepithelial cytoarchitecture and synchronous differentiation. In summary, we identified a critical role for CSMD1 in brain development and biallelic CSMD1 variants as the molecular basis of a previously undefined neurodevelopmental disorder.

Computational Exploration of Bio-Degradation Patterns of Various Plastic Types.

Plastic materials are recalcitrant in the open environment, surviving for longer without complete remediation. The current disposal methods of used plastic material are inefficient; consequently, plastic wastes are infiltrating the natural resources of the biosphere. The mixed composition of urban domestic waste with different plastic types makes them unfavorable for recycling; however, natural assimilation in situ is still an option to explore. In this research work, we have utilized previously published reports on the biodegradation of various plastics types and analyzed the pattern of microbial degradation. Our results demonstrate that the biodegradation of plastic material follows the chemical classification of plastic types based on their main molecular backbone. The clustering analysis of various plastic types based on their biodegradation reports has grouped them into two broad categories of C-C (non-hydrolyzable) and C-X (hydrolyzable). The C-C and C-X groups show a statistically significant difference in their biodegradation pattern at the genus level. The Bacilli class of bacteria is found to be reported more often in the C-C category, which is challenging to degrade compared to C-X. Genus enrichment analysis suggests that Pseudomonas and Bacillus from bacteria and Aspergillus and Penicillium from fungi are potential genera for the bioremediation of mixed plastic waste. The lack of uniformity in reporting the results of microbial degradation of plastic also needs to be addressed to enable productive growth in the field. Overall, the result points towards the feasibility of a microbial-based biodegradation solution for mixed plastic waste.

Dynamic Play between Human N-α-acetyltransferase D and H4-mutant Histones: Molecular Dynamics Study.

BACKGROUND: Many N-terminal acetyltransferases (NATs) play important role in the posttranslational modifications of histone tails. Research showed that these enzymes have been reported upregulated in many cancers. NatD is known to acetylate H4/H2A at the N-terminal. During lung cancer, this enzyme competes with the protein kinase CK2α and blocks the phosphorylation of H4 and, acetylates. It also, we observed that H4 has various mutations at the N-terminal and we considered only four mutations (S1C, R3C, G4D and G4S) to study the impacts of these mutations on H4 binding with NatD using MD simulation. OBJECTIVE: Our main objective in this study was to understand the structure and dynamics of hNatD under the influence of WT and MT H4 histones bindings. The previous experimental study reported that mutations on H4 N-terminus reduce the catalytic efficiency of N-Terminal acetylation. But here, we performed a molecular- level study thus, we can understand how these mutations (S1C, R3C, G4D and G4S) cause significant depletion in catalytic efficiency of hNatD. METHODS: Purely computational approaches were employed to investigate the impacts of four mutations in human histone H4 on its binding with the N-α-acetyltransferase D. Initially, molecular docking was used to dock the histone H4 peptide with the N-α-acetyltransferase. Next, all-atom molecular dynamics simulation was performed to probe the structural deviation and dynamics of N-α-acetyltransferase D under the binding of WT and MT H4 histones. RESULTS: Our results show that R3C stabilizes the NatD whereas the remaining mutations destabilize the NatD. Thus, mutations have significant impacts on NatD structure. Our finding supports the previous analysis also. Another interesting observation is that the enzymatic activity of hNatD is altered due to the considerably large deviation of acetyl-CoA from its original position (G4D). Further, simulation and correlation data suggest which regions of the hNatD are highly flexible and rigid and, which domains or residues have the correlation and anticorrelation. As hNatD is overexpressed in lung cancer, it is an important drug target for cancer hence, our study provides structural information to target hNatD. CONCLUSION: In this study, we examined the impacts of WT and MTs (S1C, R3C, G4D and G4S) histone H4 decapeptides on their bindings with hNatD by using 100 ns all-atom MD simulation. Our results support the previous finding that the mutant H4 histones reduce the catalytic efficiency of hNatD. The MD posttrajectory analyses revealed that S1C, G4S and G4D mutants remarkably alter the residue network in hNatD. The intramolecular hydrogen bond analysis suggested that there is a considerable number of loss of hydrogen bonds in hNatD of hNatD-H4_G4D and hNatD-H4_G4S complexes whereas a large number of hydrogen bonds were increased in hNatD of hNatD-H4_R3C complex during the entire simulations. This implies that R3C mutant binding to hNatD brings stability in hNatD in comparison with WT and other MTs complexes. The linear mutual information (LMI) and Betweenness centrality (BC) suggest that S1C, G4D and G4S significantly disrupt the catalytic site residue network as compared to R3C mutation in H4 histone. Thus, this might be the cause of a notable reduction in the catalytic efficiency of hNatD in these three mutant complexes. Further, interaction analysis supports that E126 is the important residue for the acetyltransferase mechanisms as it is dominantly found to have interactions with numerous residues of MTs histones in MD frames. Additionally, intermolecular hydrogen bond and RMSD analyses of acetyl-CoA predict the higher stability of acetyl-CoA inside the WT complex of hNatD and R3C complex. Also, we report here the structural and dynamic aspects and residue interactions network (RIN) of hNatD to target it to control cell proliferation in lung cancer conditions.

In silico characterization of mutations circulating in SARS-CoV-2 structural proteins.

SARS-CoV-2 has recently emerged as a pandemic that has caused more than 2.4 million deaths worldwide. Since the onset of infections, several full-length sequences of viral genome have been made available which have been used to gain insights into viral dynamics. We utilised a meta-data driven comparative analysis tool for sequences (Meta-CATS) algorithm to identify mutations in 829 SARS-CoV-2 genomes from around the world. The algorithm predicted sixty-one mutations among SARS-CoV-2 genomes. We observed that most of the mutations were concentrated around three protein coding genes viz nsp3 (non-structural protein 3), RdRp (RNA-directed RNA polymerase) and Nucleocapsid (N) proteins of SARS-CoV-2. We used various computational tools including normal mode analysis (NMA), C-α discrete molecular dynamics (DMD) and all-atom molecular dynamic simulations (MD) to study the effect of mutations on functionality, stability and flexibility of SARS-CoV-2 structural proteins including envelope (E), N and spike (S) proteins. PredictSNP predictor suggested that four mutations (L37H in E, R203K and P344S in N and D614G in S) out of seven were predicted to be neutral whilst the remaining ones (P13L, S197L and G204R in N) were predicted to be deleterious in nature thereby impacting protein functionality. NMA, C-α DMD and all-atom MD suggested some mutations to have stabilizing roles (P13L, S197L and R203K in N protein) where remaining ones were predicted to destabilize mutant protein. In summary, we identified significant mutations in SARS-CoV-2 genomes as well as used computational approaches to further characterize the possible effect of highly significant mutations on SARS-CoV-2 structural proteins.Communicated by Ramaswamy H. Sarma.

Revolutionizing enzyme engineering through artificial intelligence and machine learning.

The combinatorial space of an enzyme sequence has astronomical possibilities and exploring it with contemporary experimental techniques is arduous and often ineffective. Multi-target objectives such as concomitantly achieving improved selectivity, solubility and activity of an enzyme have narrow plausibility under approaches of restricted mutagenesis and combinatorial search. Traditional enzyme engineering approaches have a limited scope for complex optimization due to the requirement of a priori knowledge or experimental burden of screening huge protein libraries. The recent surge in high-throughput experimental methods including Next Generation Sequencing and automated screening has flooded the field of molecular biology with big-data, which requires us to re-think our concurrent approaches towards enzyme engineering. Artificial Intelligence (AI) and Machine Learning (ML) have great potential to revolutionize smart enzyme engineering without the explicit need for a complete understanding of the underlying molecular system. Here, we portray the role and position of AI techniques in the field of enzyme engineering along with their scope and limitations. In addition, we explain how the traditional approaches of directed evolution and rational design can be extended through AI tools. Recent successful examples of AI-assisted enzyme engineering projects and their deviation from traditional approaches are highlighted. A comprehensive picture of current challenges and future avenues for AI in enzyme engineering are also discussed.

Molecular Basis of Iterative C─H Oxidation by TamI, a Multifunctional P450 monooxygenase from the Tirandamycin Biosynthetic Pathway.

Biocatalysis offers an expanding and powerful strategy to construct and diversify complex molecules by C─H bond functionalization. Due to their high selectivity, enzymes have become an essential tool for C─H bond functionalization and offer complementary reactivity to small-molecule catalysts. Hemoproteins, particularly cytochromes P450, have proven effective for selective oxidation of unactivated C─H bonds. Previously, we reported the in vitro characterization of an oxidative tailoring cascade in which TamI, a multifunctional P450 functions co-dependently with the TamL flavoprotein to catalyze regio- and stereoselective hydroxylations and epoxidation to yield tirandamycin A and tirandamycin B. TamI follows a defined order including 1) C10 hydroxylation, 2) C11/C12 epoxidation, and 3) C18 hydroxylation. Here we present a structural, biochemical, and computational investigation of TamI to understand the molecular basis of its substrate binding, diverse reactivity, and specific reaction sequence. The crystal structure of TamI in complex with tirandamycin C together with molecular dynamics simulations and targeted mutagenesis suggest that hydrophobic interactions with the polyene chain of its natural substrate are critical for molecular recognition. QM calculations and molecular dynamics simulations of TamI with variant substrates provided detailed information on the molecular basis of sequential reactivity, and pattern of regio- and stereo-selectivity in catalyzing the three-step oxidative cascade.

Genetic diversity of NDUFV1-dependent mitochondrial complex I deficiency.

Medical genomics research performed in diverse population facilitates a better understanding of the genetic basis of developmental disorders, with regional implications for community genetics. Autosomal recessive mitochondrial complex I deficiency (MCID) accounts for a constellation of clinical features, including encephalopathies, myopathies, and Leigh Syndrome. Using whole-exome sequencing, we identified biallelic missense variants in NDUFV1 that encodes the 51-kD subunit of complex I (NADH dehydrogenase) NDUFV1. Mapping the variants on published crystal structures of mitochondrial complex I demonstrate that the novel c.1118T > C (p.(Phe373Ser)) variant is predicted to diminish the affinity of the active pocket of NDUFV1 for FMN that correlates to an early onset of debilitating MCID symptoms. The c.1156C > T (p.(Arg386Cys)) variant is predicted to alter electron shuttling required for energy production and correlate to a disease onset in childhood. NDUFV1 c.1156C > T (p.(Arg386Cys)) represents a founder variant in South Asian populations that have value in prioritizing this variant in a population-specific manner for genetic diagnostic evaluation. In conclusion, our results demonstrate the advantage of analyzing population-specific sequences to understand the disease pathophysiology and prevalence of inherited risk variants in the underrepresented populations.

N-terminal diproline and charge group effects on the stabilization of helical conformation in alanine-based short peptides: CD studies with water and methanol as solvent.

Protein folding problem remains a formidable challenge as main chain, side chain and solvent interactions remain entangled and have been difficult to resolve. Alanine-based short peptides are promising models to dissect protein folding initiation and propagation structurally as well as energetically. The effect of N-terminal diproline and charged side chains is assessed on the stabilization of helical conformation in alanine-based short peptides using circular dichroism (CD) with water and methanol as solvent. A1 (Ac-Pro-Pro-Ala-Lys-Ala-Lys-Ala-Lys-Ala-NH2 ) is designed to assess the effect of N-terminal homochiral diproline and lysine side chains to induce helical conformation. A2 (Ac-Pro-Pro-Glu-Glu-Ala-Ala-Lys-Lys-Ala-NH2 ) and A3 (Ac-dPro-Pro-Glu-Glu-Ala-Ala-Lys-Lys-Ala-NH2 ) with N-terminal homochiral and heterochiral diproline, respectively, are designed to assess the effect of Glu...Lys (i, i + 4) salt bridge interactions on the stabilization of helical conformation. The CD spectra of A1, A2 and A3 in water manifest different amplitudes of the observed polyproline II (PPII) signals, which indicate different conformational distributions of the polypeptide structure. The strong effect of solvent substitution from water to methanol is observed for the peptides, and CD spectra in methanol evidence A2 and A3 as helical folds. Temperature-dependent CD spectra of A1 and A2 in water depict an isodichroic point reflecting coexistence of two conformations, PPII and ß-strand conformation, which is consistent with the previous studies. The results illuminate the effect of N-terminal diproline and charged side chains in dictating the preferences for extended-ß, semi-extended PPII and helical conformation in alanine-based short peptides. The results of the present study will enhance our understanding on stabilization of helical conformation in short peptides and hence aid in the design of novel peptides with helical structures. Copyright © 2017 European Peptide Society and John Wiley & Sons, Ltd.

Prion protein dynamics before aggregation.

Prion diseases, like Alzheimer's disease and Parkinson disease, are rapidly progressive neurodegenerative disorders caused by misfolding followed by aggregation and accumulation of protein deposits in neuronal cells. Here we measure intramolecular polypeptide backbone reconfiguration as a way to understand the molecular basis of prion aggregation. Our hypothesis is that when reconfiguration is either much faster or much slower than bimolecular diffusion, biomolecular association is not stable, but as the reconfiguration rate becomes similar to the rate of biomolecular diffusion, the association is more stable and subsequent aggregation is faster. Using the technique of Trp-Cys contact quenching, we investigate the effects of various conditions on reconfiguration dynamics of the Syrian hamster and rabbit prion proteins. This protein exhibits behavior in all three reconfiguration regimes. We conclude that the hamster prion is prone to aggregation at pH 4.4 because its reconfiguration rate is slow enough to expose hydrophobic residues on the same time scale that bimolecular association occurs, whereas the rabbit sequence avoids aggregation by reconfiguring 10 times faster than the hamster sequence.

Scrutiny of chain-length and N-terminal effects in α-helix folding: a molecular dynamics study on polyalanine peptides.

Protein folding remains an unsolved problem as main-chain, side-chain, and solvent interactions remain entangled and have been hard to resolve. Polyalanines are promising models to analyze protein folding initiation and propagation structurally as well as energetically. In the present work, the effect of chain-length and N-terminal residue stereochemistry in polyalanine peptides are investigated for their role in the nucleation of α-helical conformation. The end-protected polyalanine peptides, tetra-alanine, Ac-LAla4-NHMe (Ia) and Ac-DAla-LAla3-NHMe (Ib), hexa-alanine, Ac-LAla6-NHMe (IIa) and Ac-DAla-LAla5-NHMe (IIb), and octa-alanine, Ac-LAla8-NHMe (IIIa) and Ac-DAla-LAla7-NHMe (IIIb), are assessed as chain-length and stereochemical-structure perturbed models. The appreciable variations in the sampling of α-helical conformation, including a sampling of α-helix folds, due to the cooperative effect of chain-length and N-terminal residue stereochemistry have been noted. The electrostatics of α-helical conformation rather than the conformational entropy of the main-chain appear to be decisive in the initiation of α-helix folding. The results of the present work will enhance our understanding on the nucleation of α-helical conformation in short peptides and aid in the design of novel peptides with α-helical structure that can modulate disease-related protein-protein interactions.

Design of a zinc-finger hydrolase with a synthetic αßß protein.

Recent advances in protein design have opened avenues for the creation of artificial enzymes needed for biotechnological and pharmaceutical applications. However, designing efficient enzymes remains an unrealized ambition, as the design must incorporate a catalytic apparatus specific for the desired reaction. Here we present a de novo design approach to evolve a minimal carbonic anhydrase mimic. We followed a step-by-step design of first folding the main chain followed by sequence variation for substrate binding and catalysis. To optimize the fold, we designed an αßß protein based on a Zn-finger. We then inverse-designed the sequences to provide stability to the fold along with flexibility of linker regions to optimize Zn binding and substrate hydrolysis. The resultant peptides were synthesized and assessed for Zn and substrate binding affinity by fluorescence and ITC followed by evaluation of catalytic efficiency with UV-based enzyme kinetic assays. We were successful in mimicking carbonic anhydrase activity in a peptide of twenty two residues, using p-nitrophenyl acetate as a CO2 surrogate. Although our design had modest activity, being a simple structure is an advantage for further improvement in efficiency. Our approach opens a way forward to evolving an efficient biocatalyst for any industrial reaction of interest.

Stereochemistry and solvent role in protein folding: nuclear magnetic resonance and molecular dynamics studies of poly-L and alternating-L,D homopolypeptides in dimethyl sulfoxide.

The competing interactions folding and unfolding protein structure remain obscure. Using homopolypeptides, we ask if poly-L structure may have a role. We mutate the structure to alternating-L,D stereochemistry and substitute water as the fold-promoting solvent with methanol and dimethyl sulfoxide (DMSO) as the fold-denaturing solvents. Circular dichroism and molecular dynamics established previously that, while both isomers were folded in water, the poly-L isomer was unfolded and alternating-L,D isomer folded in methanol. Nuclear magnetic resonance and molecular dynamics establish now that both isomers are unfolded in DMSO. We calculated energetics of folding-unfolding equilibrium with water and methanol as solvents. We have now calculated interactions of unfolded polypeptide structures with DMSO as solvent. Methanol was found to unfold and water fold poly-L structure as a dielectric. DMSO has now been found to unfold both poly-L and alternating-L,D structures by strong solvation of peptides to disrupt their hydrogen bonds. Accordingly, we propose that while linked peptides fold protein structure with hydrogen bonds they unfold the structure electrostatically due to the stereochemical effect of the poly-L structure. Protein folding to ordering of peptide hydrogen bonds with water as canonical solvent may thus involve two specific and independent solvent effects-one, strong screening of electrostatics of poly-L linked peptides, and two, weak dipolar solvation of peptides. Correspondingly, protein denaturation may involve two independent solvent effects-one, weak dielectric to unfold poly-L structure electrostatically, and two, strong polarity to disrupt peptide hydrogen bonds by solvation of peptides.

Zinc-finger hydrolase: Computational selection of a linker and a sequence towards metal activation with a synthetic αßß protein.

The zinc-finger protein is targeted for computational redesign as a hydrolase enzyme. Successful in having zinc activated for hydrolase function, the study validates the stepwise approach to having the protein tuned in main-chain structure stereochemically and over side chains chemically. A leucine homopolypeptide, harboring histidines to tri coordinate zinc and d-amino-acid-nucleated α-helix and ß-hairpin building blocks of an αßß protein, is taken up for modeling, first with cyana, in a mixed-chirality linker between the building blocks, and then with IDeAS, in a sequence over side chains. The designed mixed-chirality polypeptide structure is proven to order as an intended αßß fold and capture zinc to activate its role as a hydrolase catalyst. The design approach to have protein folds defined stereochemically and receptor and catalysis functions defined chemically is presented, and illustrates L- and D-α-amino-acid structures as the alphabet integrating chemical- and stereochemical-structure variables as its letters.