SCIENCE VERSUS PHILOSOPHY, PROPOUNDED BY ANNMBHATT SPECIAL PERSPECTIVE ON GRAVITY

Annambhatna, the author of the argument, has said "adyapatana samvayikaranam gravitvam"1 while defining the property called gravity in the order of merits in the collection of arguments. That is to say that the unusual cause of the first reaction is called gravity. “Dvitiya dipatnasyavega samvayikaranatvada veges tivyaptivaranayadyeti” i.e. to prevent overlapping in velocity etc There is an unusual reason for that first process. Here it is certainly necessary to appreciate the subtle vision and technical and scientific knowledge of Annabhatt. The symptoms were also reasonable to some extent but they knew that once the deceleration process has started in the object, the velocity generated by that deceleration process is the cause of the forward reaction. Thus the progressively generated velocity is the cause of the progressive deceleration process. The scientific explanation of the process is as follows.

Murburn precepts for redox dynamics in glycolysis, Cori cycle and Warburg effect: Is lactate dehydrogenase a murzyme?

Physiological redox conversion of alpha-hydroxy/keto acids is believed to be reversibly carried out by (de)hydrogenases, employing nicotinamide cofactors. With lactate dehydrogenase (LDH) as example, we point out that while the utilization of NADH for the reduction of pyruvate to lactate (the post-glycolytic reaction) can be mediated via the classical Michaelis-Menten mechanism, the oxidation of lactate to pyruvate (with or without the uphill reduction of NADH) necessitates alternative physiological approaches. This reaction could be more efficiently coupled/catalyzed with/by murzyme activities, which employ diffusible reactive (oxygen) species (DRS/DROS/ROS). Such a scheme would enable the cellular system to tide over the unfavorable energy barriers of the forward reaction (~450 kJ/mol; earlier considered to be ~25 kJ/mole!), and give kinetically viable conversions. Further, the new mechanism does not necessitate any ‘smart decision-making’ by the pertinent redox isozyme(s). For LDH, the new theory explains its multimeric nature, non-variant structure of the isozymes’ active sites and accounts for why lactate is transported to the liver for further utilization within the physiological purview of Cori cycle. The theoretical insights, in silico evidence and analyses of literature herein also enrich our understanding of ‘lactic acidosis’ (in clinical context), Warburg effect and approach for cancer therapy.

Enhancing the Heterologous Fructosyltransferase Activity of Kluyveromyces lactis: Developing a Scaled-Up Process and Abolishing Invertase by CRISPR/Cas9 Genome Editing

The enzymatic production of prebiotic fructo-oligosaccharides (FOS) from sucrose involves fructosyltransferases (FFTs) and invertases, both of which catalyze forward (transferase) and reverse (hydrolysis) reactions. FOS yields can therefore be increased by favoring the forward reaction. We investigated process conditions that favored transferase activity in the yeast strain Kluyveromyces lactis GG799, which expresses a native invertase and a heterologous FFT from Aspergillus terreus. To maximize transferase activity while minimizing native invertase activity in a scaled-up process, we evaluated two reactor systems in terms of oxygen input capacity in relation to the cell dry weight. In the 0.5-L reactor, we found that galactose was superior to lactose for the induction of the LAC4 promoter, and we optimized the induction time and induction to carbon source ratio using a response surface model. Based on the critical parameter of oxygen supply, we scaled up the process to 7 L using geometric similarity and a higher oxygen transport rate, which boosted the transferase activity by 159%. To favor the forward reaction even more, we deleted the native invertase gene by CRISPR/Cas9 genome editing and compared the ΔInv mutant to the original production strain in batch and fed-batch reactions. In fed-batch mode, we found that the ΔInv mutant increased the transferase activity by a further 66.9%. The enhanced mutant strain therefore provides the basis for a highly efficient and scalable fed-batch process for the production of FOS.

Completion of Partial Reaction Equations

We present a deep-learning model for inferring missing molecules in reaction equations. Such an algorithm features multiple interesting behaviors. First, it can infer the necessary reagents and solvents in chemical transformations specified only in terms of main compounds, as often resulting from retrosynthetic analyses. The completion with necessary reagents ensures that reaction equations are compatible with deep-learning models relying on a complete reaction specification. Second, it can cure existing datasets by detecting missing compounds, such as reagents that are essential for given classes of reactions. Finally, this model is a generalization of models for forward reaction prediction and retrosynthetic analysis, as both can be formulated in terms of incomplete reaction equations. We illustrate that a single trained model, based on the transformer architecture and acting on reaction SMILES strings, can address all three points.<br><br>Workshop paper at the Machine Learning for Molecules Workshop at NeurIPS 2020.<br>

Completion of Partial Reaction Equations

We present a deep-learning model for inferring missing molecules in reaction equations. Such an algorithm features multiple interesting behaviors. First, it can infer the necessary reagents and solvents in chemical transformations specified only in terms of main compounds, as often resulting from retrosynthetic analyses. The completion with necessary reagents ensures that reaction equations are compatible with deep-learning models relying on a complete reaction specification. Second, it can cure existing datasets by detecting missing compounds, such as reagents that are essential for given classes of reactions. Finally, this model is a generalization of models for forward reaction prediction and retrosynthetic analysis, as both can be formulated in terms of incomplete reaction equations. We illustrate that a single trained model, based on the transformer architecture and acting on reaction SMILES strings, can address all three points.<br><br>Workshop paper at the Machine Learning for Molecules Workshop at NeurIPS 2020.<br>

Forward Reaction Prediction as Reverse Verification: A Novel Approach to Retrosynthesis

Pupils' intuitive knowledge can lead them to verify multiplication by means of division. Based on this analogy, this study introduces the basic reverse verification concept to verify retrosynthesis through forward reaction. In this work, we present a "combined" model approach for retrosynthetic reaction prediction, where the first model is applied to retrosynthesis, and the second model, which is a "verified" model, is applied to the forward reaction prediction to verify the top-n reactants predicted by the retrosynthetic model. Using a "combined" model borrowed from human language translation, sequence-to-sequence (seq2seq) + transformer models, we improve the top-1 accuracy of retrosynthetic prediction by 4.3% (37.4% vs 41.7%). The application of the similarity + seq2seq models increases the top-1 accuracy by 4.6% (52.9% vs 57.5%). In this way, we can not only improve the accuracy but also automate the evaluation of the synthetic route.

Forward Reaction Prediction as Reverse Verification: A Novel Approach to Retrosynthesis

Pupils' intuitive knowledge can lead them to verify multiplication by means of division. Based on this analogy, this study introduces the basic reverse verification concept to verify retrosynthesis through forward reaction. In this work, we present a "combined" model approach for retrosynthetic reaction prediction, where the first model is applied to retrosynthesis, and the second model, which is a "verified" model, is applied to the forward reaction prediction to verify the top-n reactants predicted by the retrosynthetic model. Using a "combined" model borrowed from human language translation, sequence-to-sequence (seq2seq) + transformer models, we improve the top-1 accuracy of retrosynthetic prediction by 4.3% (37.4% vs 41.7%). The application of the similarity + seq2seq models increases the top-1 accuracy by 4.6% (52.9% vs 57.5%). In this way, we can not only improve the accuracy but also automate the evaluation of the synthetic route.

Elucidating the unusual reaction kinetics of D-glucuronyl C5-epimerase

The chemoenzymatic synthesis of heparin, through a multienzyme process, represents a critical challenge in providing a safe and effective substitute for this animal-sourced anticoagulant drug. D-glucuronyl C5-epimerase (C5-epi) is an enzyme acting on a heparin precursor, N-sulfoheparosan, catalyzing the reversible epimerization of D-glucuronic acid (GlcA) to L-iduronic acid (IdoA). The absence of reliable assays for C5-epi has limited elucidation of the enzymatic reaction and kinetic mechanisms. Real time and offline assays are described that rely on 1D 1H NMR to study the activity of C5-epi. Apparent steady-state kinetic parameters for both the forward and the pseudo-reverse reactions of C5-epi are determined for the first time using polysaccharide substrates directly relevant to the chemoenzymatic synthesis and biosynthesis of heparin. The forward reaction shows unusual sigmoidal kinetic behavior, and the pseudo-reverse reaction displays nonsaturating kinetic behavior. The atypical sigmoidal behavior of the forward reaction was probed using a range of buffer additives. Surprisingly, the addition of 25 mM each of CaCl2 and MgCl2 resulted in a forward reaction exhibiting more conventional Michaelis–Menten kinetics. The addition of 2-O-sulfotransferase, the next enzyme involved in heparin synthesis, in the absence of 3′-phosphoadenosine 5′-phosphosulfate, also resulted in C5-epi exhibiting a more conventional Michaelis–Menten kinetic behavior in the forward reaction accompanied by a significant increase in apparent Vmax. This study provides critical information for understanding the reaction kinetics of C5-epi, which may result in improved methods for the chemoenzymatic synthesis of bioengineered heparin.

Perturbation of phosphoglycerate kinase 1 (PGK1) only marginally affects glycolysis in cancer cells

Phosphoglycerate kinase 1 (PGK1) plays important roles in glycolysis, yet its forward reaction kinetics are unknown, and its role especially in regulating cancer cell glycolysis is unclear. Here, we developed an enzyme assay to measure the kinetic parameters of the PGK1-catalyzed forward reaction. The Km values for 1,3-bisphosphoglyceric acid (1,3-BPG, the forward reaction substrate) were 4.36 μm (yeast PGK1) and 6.86 μm (human PKG1). The Km values for 3-phosphoglycerate (3-PG, the reverse reaction substrate and a serine precursor) were 146 μm (yeast PGK1) and 186 μm (human PGK1). The Vmax of the forward reaction was about 3.5- and 5.8-fold higher than that of the reverse reaction for the human and yeast enzymes, respectively. Consistently, the intracellular steady-state concentrations of 3-PG were between 180 and 550 μm in cancer cells, providing a basis for glycolysis to shuttle 3-PG to the serine synthesis pathway. Using siRNA-mediated PGK1-specific knockdown in five cancer cell lines derived from different tissues, along with titration of PGK1 in a cell-free glycolysis system, we found that the perturbation of PGK1 had no effect or only marginal effects on the glucose consumption and lactate generation. The PGK1 knockdown increased the concentrations of fructose 1,6-bisphosphate, dihydroxyacetone phosphate, glyceraldehyde 3-phosphate, and 1,3-BPG in nearly equal proportions, controlled by the kinetic and thermodynamic states of glycolysis. We conclude that perturbation of PGK1 in cancer cells insignificantly affects the conversion of glucose to lactate in glycolysis.