scholarly journals Disentangling the contribution of each descriptive characteristic of every single mutation to its functional effects

2019 ◽  
Author(s):  
C. K. Sruthi ◽  
Meher K. Prakash
Keyword(s):  
Artificial Intelligence ◽  
Experimental Data ◽  
Amino Acid ◽  
Active Site ◽  
Single Mutation ◽  
Physico Chemical ◽  
Chemical Descriptors ◽  
Mutational Effect

AbstractMutational effects predictions continue to improve in accuracy as advanced artificial intelligence (AI) algorithms are trained on exhaustive experimental data. The next natural questions to ask are if it is now possible to gain insights into which attribute of the mutation contributes how much to the mutational effects, and if one can develop universal rules for mapping the descriptors to mutational effects. In this work, we mainly address the former aspect using a framework of interpretable AI. Relations between the physico-chemical descriptors and their contributions to the mutational effects are extracted by analyzing the data on 29,832 variants from 8 systematic deep-mutational scan studies. It is found that the intuitive dependences of fitness and solubility on the distance of the amino acid from active site could be extracted and quantified. The dependence of the mutational effect contributions on the number of contacts an amino acid has or the BLOSUM score descriptor of the change showed universal trends. Our attempts in the present work to explain the quantitative differences in the dependence on conservation and SASA across proteins were not successful. The work nevertheless brings transparency into the predictions, development of rules, and will hopefully lead to uncovering the universalities among these rules.

scholarly journals Modeling Drugs-PLGA Nanoparticles Interactions Using Gaussian Processes: Pharmaceutics Informatics Approach

2021 ◽  
Author(s):  
Rania M. Hathout ◽  
Orchid A Mahmoud ◽  
Dalia S Ali ◽  
Marina Mamdouh ◽  
Abdelkader A Metwally
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Gaussian Processes ◽  
Plga Nanoparticles ◽  
Binding Energies ◽  
Machine Learning Method ◽  
Learning Method ◽  
Physico Chemical ◽  
Chemical Descriptors ◽  
Delta G

The objective of this study was to correlate the binding of drugs on a very popular nanoparticulate polymeric matrix; PLGA nanoparticles with their main constitutional, electronic and physico-chemical descriptors. Gaussian Processes (GPs) was the artificial intelligence machine learning method that was utilized to fulfil this task. The method could successfully model the results where optimum values of the investigated descriptors of the loaded drugs were deduced. A percentage bias of 12.68 % ± 2.1 was obtained in predicting the binding energies of a group of test drugs. As a conclusion, GPs could successfully model the drugs-PLGA interactions associated with a good predicting power. The GPs-predicted binding energies (ΔG) can easily be projected to the drugs loading as was previously proven. Adopting the “Pharmaceutics Informatics” approach can save the pharmaceutical industry and the drug delivery scientists a lot of exerted resources, efforts and time.

Identifying Physico-Chemical Laws from the Robotically Collected Data

2019 ◽  
Author(s):  
Liwei Cao ◽  
Danilo Russo ◽  
Vassilios S. Vassiliadis ◽  
Alexei Lapkin
Keyword(s):  
Experimental Data ◽  
Numerical Models ◽  
Predictor Variable ◽  
Physical Models ◽  
Training Data ◽  
Mixed Integer ◽  
Physico Chemical ◽  
Data Points ◽  
Future Work ◽  
The Relationship

<p>A mixed-integer nonlinear programming (MINLP) formulation for symbolic regression was proposed to identify physical models from noisy experimental data. The formulation was tested using numerical models and was found to be more efficient than the previous literature example with respect to the number of predictor variables and training data points. The globally optimal search was extended to identify physical models and to cope with noise in the experimental data predictor variable. The methodology was coupled with the collection of experimental data in an automated fashion, and was proven to be successful in identifying the correct physical models describing the relationship between the shear stress and shear rate for both Newtonian and non-Newtonian fluids, and simple kinetic laws of reactions. Future work will focus on addressing the limitations of the formulation presented in this work, by extending it to be able to address larger complex physical models.</p><p><br></p>

Fluoroquinolone-3-carboxamide Amino Acid Conjugates: Synthesis, Antibacterial Properties And Molecular Modeling Studies

2020 ◽  
Vol 17 (1) ◽  
pp. 71-84
Author(s):  
Riham M. Bokhtia ◽  
Siva S. Panda ◽  
Adel S. Girgis ◽  
Hitesh H. Honkanadavar ◽  
Tarek S. Ibrahim ◽  
...  
Keyword(s):  
Experimental Data ◽  
Antibacterial Activity ◽  
Amino Acid ◽  
Bacterial Infections ◽  
Antibacterial Agents ◽  
Antibacterial Properties ◽  
Computational Studies ◽  
Protecting Group ◽  
Amino Acid Conjugates ◽  
Molecular Modeling Studies

Background: Bacterial infections are considered as one of the major global health threats, so it is very essential to design and develop new antibacterial agents to overcome the drawbacks of existing antibacterial agents. Method: The aim of this work is to synthesize a series of new fluoroquinolone-3-carboxamide amino acid conjugates by molecular hybridization. We utilized benzotriazole chemistry to synthesize the desired hybrid conjugates. Result: All the conjugates were synthesized in good yields, characterized, evaluated for their antibacterial activity. The compounds were screened for their antibacterial activity using methods adapted from the Clinical and Laboratory Standards Institute. Synthesized conjugates were tested for activity against medically relevant pathogens; Escherichia coli (ATCC 25922), Pseudomonas aeruginosa (ATCC 27856) Staphylococcus aureus (ATCC 25923) and Enterococcus faecalis (ATCC 19433). Conclusion: The observed antibacterial experimental data indicates the selectivity of our synthesized conjugates against E.Coli. The protecting group on amino acids decreases the antibacterial activity. The synthesized conjugates are non-toxic to the normal cell lines. The experimental data were supported by computational studies.

Biological Function and Chemistry of Endothelin. A Review

1999 ◽  
Vol 64 (8) ◽  
pp. 1211-1252 ◽  
Author(s):  
Jan Hlaváček ◽  
Renáta Marcová
Keyword(s):  
Biological Activity ◽  
Amino Acid ◽  
Biological Function ◽  
Biological Properties ◽  
Structural Basis ◽  
Amino Acid Residues ◽  
Snake Venoms ◽  
Vasoactive Peptides ◽  
Physico Chemical ◽  
Endothelin A

The first part of this review deals with the biosynthesis and a biological function of strongly vasoactive peptides named endothelins (ETs) including vasoactive intestinal contractor. Where it was useful, snake venoms sarafotoxins which are structural endothelin derivatives, were also mentioned. In the second part, an attention is paid to structural basis of the ETs biological activity, with respect to alterations of amino acid residues in the parent peptides modifying the conformation and consequently the physico-chemical and biological properties in corresponding ETs analogs. Special attention is focussed on the area of ETs receptors and their interaction with peptide and non peptide agonists and antagonists, important in designing selective inhibitors of ETs receptors potentially applicable as drugs in a medicine. A review with 182 references.

scholarly journals Alteration of high and low spin equilibrium by a single mutation of amino acid 209 in mouse cytochromes P450

1991 ◽  
Vol 266 (6) ◽  
pp. 3380-3382
Author(s):  
M Iwasaki ◽  
R Juvonen ◽  
R Lindberg ◽  
M Negishi
Keyword(s):  
Amino Acid ◽  
Cytochromes P450 ◽  
Single Mutation

scholarly journals Derived amino acid sequence and identification of active site residues of Escherichia coli beta-hydroxydecanoyl thioester dehydrase.

1988 ◽  
Vol 263 (10) ◽  
pp. 4641-4646 ◽  
Author(s):  
J E Cronan ◽  
W B Li ◽  
R Coleman ◽  
M Narasimhan ◽  
D de Mendoza ◽  
...  
Keyword(s):  
Escherichia Coli ◽  
Amino Acid ◽  
Amino Acid Sequence ◽  
Active Site ◽  
Active Site Residues

scholarly journals Fe(2)OG: an integrated HMM profile-based web server to predict and analyze putative non-haem iron(II)- and 2-oxoglutarate-dependent dioxygenase function in protein sequences

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Siddhartha Kundu
Keyword(s):  
Amino Acid ◽  
Water Molecule ◽  
Active Site ◽  
Ferrous Iron ◽  
Web Server ◽  
Protein Sequences ◽  
Diverse Group ◽  
And Function ◽  
Functionally Diverse ◽  
Haem Iron

Abstract Objective Non-haem iron(II)- and 2-oxoglutarate-dependent dioxygenases (i2OGdd), are a taxonomically and functionally diverse group of enzymes. The active site comprises ferrous iron in a hexa-coordinated distorted octahedron with the apoenzyme, 2-oxoglutarate and a displaceable water molecule. Current information on novel i2OGdd members is sparse and relies on computationally-derived annotation schema. The dissimilar amino acid composition and variable active site geometry thereof, results in differing reaction chemistries amongst i2OGdd members. An additional need of researchers is a curated list of sequences with putative i2OGdd function which can be probed further for empirical data. Results This work reports the implementation of $$Fe\left(2\right)OG$$ F e 2 O G , a web server with dual functionality and an extension of previous work on i2OGdd enzymes $$\left(Fe\left(2\right)OG\equiv \{H2OGpred,DB2OG\}\right)$$ F e 2 O G ≡ { H 2 O G p r e d , D B 2 O G } . $$Fe\left(2\right)OG$$ F e 2 O G , in this form is completely revised, updated (URL, scripts, repository) and will strengthen the knowledge base of investigators on i2OGdd biochemistry and function. $$Fe\left(2\right)OG$$ F e 2 O G , utilizes the superior predictive propensity of HMM-profiles of laboratory validated i2OGdd members to predict probable active site geometries in user-defined protein sequences. $$Fe\left(2\right)OG$$ F e 2 O G , also provides researchers with a pre-compiled list of analyzed and searchable i2OGdd-like sequences, many of which may be clinically relevant. $$Fe(2)OG$$ F e ( 2 ) O G , is freely available (http://204.152.217.16/Fe2OG.html) and supersedes all previous versions, i.e., H2OGpred, DB2OG.

scholarly journals Amino acid sequence of the active site of Acanthamoeba myosin II.

1986 ◽  
Vol 261 (4) ◽  
pp. 1844-1848
Author(s):  
M A Atkinson ◽  
E A Robinson ◽  
E Appella ◽  
E D Korn
Keyword(s):  
Amino Acid ◽  
Amino Acid Sequence ◽  
Active Site ◽  
Myosin Ii
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