# Identification of Some Glutamic Acid Derivatives with Biological Potential by Computational Methods
## 2 Results and Discussion
### Algorithm for Designing Glutamic Acid Derivatives and Studies Underlying Their Development  
The derivatives included in the first two classes were designed based on the specific chemical properties of amino acids resulting from reactions at the carboxyl and amino functional groups. Blocking these essential functional groups in the amino acid's structure could bring significant changes in terms of its biochemical metabolism; consequently, derivatives with potential pharmaceutical effects are sought [24; 25; 26; 27]. The following classes of compounds comprise structures containing pharmacophores responsible for the anti-cancer effect: thiazole derivatives, 1,3-oxazole derivatives [28; 29; 30], alkylating agents [28; 31; 32; 33; 34; 35], inhibitors of histone deacetylase [36; 37; 38; 39], ribonucleotide reductase [40; 41; 42], glutamate synthetase inhibitors, and mitochondrial transporters of the SLC25A family [43; 44; 45; 46; 47; 48; 49; 50; 51; 52; 53; 54; 55; 56; 57; 58; 59; 60]. Compounds belonging to these classes have been intensively studied [7; 61]. Based on data published about histone deacetylase, compounds from class 4B were designed [39; 42; 6  
Based on the information about plant-derived substances with proven anti-cancer effect, we have structurally created compounds of group 5A-E: colchicine derivatives, nef-ine derivatives, 7-hydroxynicerine derivatives, lycorine derivatives, 5,6-dehydroglycorine derivatives, and natural compounds conjugated with glutamic acid residues [28; 72; 73; 74; 75; 76; 77; 78; 79; 80; 81; 82; 83; 84; 85; 86; 87; 88; 89]. In addition, the hypothesis that conjugation with a single molecule of glutamic acid could bring benefits compared with the basic compounds of natural origin is being tested through computational studies. The in silico determination of (1) physicochemical and structural parameters, which implies the determination of heavy atoms (HA), heavy aromatic atoms (HAA), fraction Csp3, rotatable bonds (RB), H-bond acceptors, H-bond donors, molar refractivity (MR), and total polar surface area (TPSA); (2) protonation (acidic pKa, basic pKa, pKa score, isoelectric point (pI), and microspecies); and (3) electric charge (molar polarisability), is detailed in Table S3 (Supplementary Materials). Water solubility was computed using AquaSol [90], Chemicalize [91], and SwissADME [92], and the results are detailed in Table S4 (Supplementary Materials). Lipophilicity and partition coefficients are presented in Table S5 (Supplementary Materials). Toxicity studies were performed in silico by applying the Cramer rules, and the Kroess and Verhaar scheme (Table S6; Supplementary Materials). Other toxicity parameters were also determined, such as carcinogenicity (genotoxic and non-genotoxic) and mutagenicity, skin and eye irritation/corrosion, effect on the reproductive system, biodegradability, and protein and DNA binding alerts, which were evaluated using Toxtree and OSIRIS [93; 94]. Results are listed in Tables S7 and S8 (Supplementary Materials). Pharmacokinetic properties were evaluated for each compound in terms of permeability (gastrointestinal absorption, blood-brain barrier permeability) and interactions with P-gp. In addition, we assessed the enzyme inhibitory effect on some isoforms of cytochrome P450 (Table S9; Supplementary Materials). Based on the previously calculated properties, we evaluated whether these compounds meet the \"drug-likeness\" criteria according to the [PERSON], [PERSON], [PERSON], [PERSON], and [PERSON] rules. The number of rules violated by each molecule is shown in Table S10 (Supplementary Materials), along with the bioavailability score, drug-likeness score, lead-likeness score, and synthetic accessibility score. Compounds that were too reactive, toxic, or did not have the suitable properties to become lead compounds were removed.