A computational simulation appraisal of banana lectin as a potential anti-SARS-CoV-2 candidate by targeting the receptor-binding domain

Journal of Genetic Engineering and Biotechnology

Table 5 The properties and description of the molecular docking results for the four SARS-CoV-2 RBD variants with the four selected BanLecs showing the lowest energy score, binding affinity, and interaction interface

SARS-CoV-2 variants	BanLec	Best model/cluster	ClusPro lowest energy (LE)	Prodigy 𝚫G (kJ/mol)	Interaction interface (all residues)			Interaction interface (with key aa residues in RBD)
SARS-CoV-2 variants	BanLec	Best model/cluster	ClusPro lowest energy (LE)	Prodigy 𝚫G (kJ/mol)	Salt bridges	H- bonds	Non-bonded	Salt bridges	H- bonds	Non-bonded
WT	Ma09 WT	Model 26	−1081.8	−17.4	1	26	297	-	1	4
	Ma09 H84T	Model 01	−1219.9	−12.9	2	19	183	1	10	125
	Mba09 WT	Model 03	−1400.1	−16.0	-	3	245	-	1	14
	Mba09 H115T	Model 01	−1221.0	−14.9	2	25	214	1	19	124
Delta	Ma09 WT	Model 01	−1322.6	−10.7	-	9	125	-	4	81
	Ma09 H84T	Model 19	−1149.9	−14.8	2	19	250	1	14	200
	Mba09 WT	Model 14	−1149.5	−16.1	2	15	220	1	8	171
	Mba09 H115T	Model 04	−1303.5	−13.7	2	12	162	-	6	88
Delta Plus	Ma09 WT	Model 22	−1113.7	−16.3	-	17	218	-	11	166
Delta Plus	Ma09 H84T	Model 12	−1173.5	−16.8	-	-	-	3	-	-
	Mba09 WT	Model 29	−1107.5	−16.4	-	12	179	-	12	179
	Mba09 H115T	Model 01	−1311.6	−12.8	3	14	187	-	9	133
Omicron	Ma09 WT	Model 20	−1208.9	−14.7	3	22	278	2	14	213
	Ma09 H84T	Model 00	−1376.5	−10.8	1	15	166	1	13	140
	Mba09 WT	Model 05	−1370.4	−15.2	2	17	209	-	7	125
	Mba09 H115T	Model 00	−1427.4	−14.4	3	15	217	-	8	162